diff --git a/Part 2/Data_Wrangling.ipynb b/Part 1/Data_Wrangling.ipynb
old mode 100755
new mode 100644
similarity index 100%
rename from Part 2/Data_Wrangling.ipynb
rename to Part 1/Data_Wrangling.ipynb
diff --git a/Part 2/single_family_home_values.csv b/Part 1/single_family_home_values.csv
old mode 100755
new mode 100644
similarity index 100%
rename from Part 2/single_family_home_values.csv
rename to Part 1/single_family_home_values.csv
diff --git a/Part 1/ESSdata.csv b/Part 2/ESSdata.csv
old mode 100755
new mode 100644
similarity index 100%
rename from Part 1/ESSdata.csv
rename to Part 2/ESSdata.csv
diff --git a/Part 1/Section-2.ipynb b/Part 2/Section-2.ipynb
old mode 100755
new mode 100644
similarity index 100%
rename from Part 1/Section-2.ipynb
rename to Part 2/Section-2.ipynb
diff --git a/Part 1/curse_of_dimensionality.png b/Part 2/curse_of_dimensionality.png
old mode 100755
new mode 100644
similarity index 100%
rename from Part 1/curse_of_dimensionality.png
rename to Part 2/curse_of_dimensionality.png
diff --git a/Part 1/pca_pic.png b/Part 2/pca_pic.png
old mode 100755
new mode 100644
similarity index 100%
rename from Part 1/pca_pic.png
rename to Part 2/pca_pic.png
diff --git a/Part 1/pca_vector.png b/Part 2/pca_vector.png
old mode 100755
new mode 100644
similarity index 100%
rename from Part 1/pca_vector.png
rename to Part 2/pca_vector.png
diff --git a/Part 1/svm.png b/Part 2/svm.png
old mode 100755
new mode 100644
similarity index 100%
rename from Part 1/svm.png
rename to Part 2/svm.png
diff --git a/Part 3/ESSdata.csv b/Part 3/ESSdata.csv
deleted file mode 100755
index 1f2a4a7..0000000
--- a/Part 3/ESSdata.csv	
+++ /dev/null
@@ -1,8595 +0,0 @@
-cntry,idno,year,tvtot,ppltrst,pplfair,pplhlp,happy,sclmeet,sclact,gndr,agea,partner
-CH,5.0,6,3.0,3.0,10.0,5.0,8.0,5.0,4.0,2.0,60.0,1.0
-CH,25.0,6,6.0,5.0,7.0,5.0,9.0,3.0,2.0,2.0,59.0,1.0
-CH,26.0,6,1.0,8.0,8.0,8.0,7.0,6.0,3.0,1.0,24.0,2.0
-CH,28.0,6,4.0,6.0,6.0,7.0,10.0,6.0,2.0,2.0,64.0,1.0
-CH,29.0,6,5.0,6.0,7.0,5.0,8.0,7.0,2.0,2.0,55.0,1.0
-CH,36.0,6,4.0,6.0,7.0,3.0,8.0,7.0,4.0,2.0,,2.0
-CH,40.0,6,3.0,0.0,5.0,2.0,0.0,2.0,2.0,1.0,76.0,1.0
-CH,41.0,6,2.0,4.0,5.0,3.0,10.0,5.0,2.0,2.0,30.0,1.0
-CH,51.0,6,2.0,8.0,8.0,8.0,9.0,6.0,4.0,2.0,84.0,2.0
-CH,53.0,6,4.0,4.0,4.0,8.0,7.0,4.0,2.0,2.0,62.0,1.0
-CH,55.0,6,1.0,6.0,7.0,7.0,9.0,5.0,2.0,2.0,33.0,1.0
-CH,56.0,6,4.0,5.0,7.0,7.0,7.0,5.0,3.0,1.0,40.0,1.0
-CH,57.0,6,4.0,7.0,7.0,4.0,9.0,6.0,2.0,1.0,69.0,1.0
-CH,58.0,6,2.0,1.0,9.0,7.0,8.0,4.0,3.0,1.0,59.0,2.0
-CH,68.0,6,4.0,4.0,5.0,3.0,8.0,1.0,2.0,2.0,32.0,1.0
-CH,73.0,6,5.0,4.0,5.0,5.0,9.0,3.0,3.0,2.0,70.0,1.0
-CH,81.0,6,4.0,5.0,7.0,7.0,8.0,3.0,3.0,1.0,61.0,1.0
-CH,82.0,6,2.0,7.0,7.0,7.0,6.0,6.0,3.0,1.0,30.0,1.0
-CH,84.0,6,0.0,9.0,7.0,8.0,9.0,5.0,4.0,1.0,21.0,2.0
-CH,86.0,6,2.0,6.0,6.0,6.0,8.0,4.0,3.0,2.0,36.0,1.0
-CH,87.0,6,7.0,3.0,4.0,4.0,7.0,6.0,4.0,1.0,51.0,1.0
-CH,96.0,6,1.0,8.0,8.0,6.0,8.0,7.0,4.0,1.0,25.0,2.0
-CH,98.0,6,2.0,7.0,7.0,8.0,9.0,6.0,3.0,1.0,62.0,1.0
-CH,104.0,6,2.0,4.0,8.0,8.0,9.0,6.0,2.0,2.0,20.0,2.0
-CH,108.0,6,0.0,7.0,7.0,4.0,9.0,4.0,2.0,2.0,22.0,1.0
-CH,117.0,6,0.0,6.0,7.0,5.0,7.0,6.0,2.0,2.0,32.0,1.0
-CH,118.0,6,2.0,7.0,6.0,5.0,8.0,4.0,3.0,2.0,35.0,1.0
-CH,119.0,6,0.0,5.0,8.0,6.0,9.0,4.0,2.0,2.0,26.0,1.0
-CH,121.0,6,2.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,35.0,1.0
-CH,133.0,6,7.0,8.0,5.0,5.0,8.0,5.0,3.0,2.0,54.0,1.0
-CH,135.0,6,6.0,8.0,8.0,3.0,5.0,6.0,1.0,2.0,38.0,2.0
-CH,137.0,6,3.0,2.0,3.0,2.0,9.0,5.0,2.0,1.0,38.0,1.0
-CH,148.0,6,0.0,5.0,6.0,10.0,10.0,6.0,2.0,2.0,82.0,2.0
-CH,149.0,6,5.0,8.0,3.0,2.0,6.0,6.0,3.0,1.0,69.0,2.0
-CH,161.0,6,1.0,7.0,7.0,8.0,6.0,4.0,3.0,2.0,24.0,2.0
-CH,162.0,6,7.0,7.0,6.0,8.0,8.0,6.0,2.0,2.0,53.0,1.0
-CH,168.0,6,2.0,6.0,6.0,7.0,8.0,6.0,3.0,2.0,46.0,2.0
-CH,177.0,6,4.0,5.0,8.0,8.0,8.0,4.0,3.0,1.0,38.0,1.0
-CH,179.0,6,4.0,7.0,7.0,3.0,9.0,6.0,3.0,1.0,47.0,1.0
-CH,180.0,6,6.0,5.0,7.0,4.0,7.0,4.0,2.0,1.0,72.0,1.0
-CH,185.0,6,2.0,4.0,4.0,5.0,9.0,7.0,3.0,1.0,22.0,2.0
-CH,193.0,6,5.0,3.0,5.0,5.0,8.0,3.0,4.0,2.0,,1.0
-CH,200.0,6,2.0,9.0,7.0,7.0,9.0,7.0,2.0,1.0,16.0,2.0
-CH,216.0,6,1.0,7.0,5.0,7.0,7.0,7.0,3.0,1.0,20.0,2.0
-CH,218.0,6,0.0,8.0,8.0,7.0,9.0,5.0,2.0,1.0,42.0,1.0
-CH,219.0,6,5.0,7.0,7.0,7.0,8.0,7.0,3.0,2.0,16.0,2.0
-CH,220.0,6,4.0,7.0,7.0,7.0,8.0,6.0,3.0,1.0,57.0,2.0
-CH,231.0,6,2.0,8.0,8.0,7.0,8.0,6.0,4.0,2.0,45.0,1.0
-CH,232.0,6,1.0,8.0,8.0,6.0,9.0,4.0,4.0,1.0,28.0,1.0
-CH,251.0,6,3.0,5.0,5.0,4.0,6.0,3.0,2.0,1.0,85.0,1.0
-CH,257.0,6,2.0,7.0,5.0,6.0,8.0,6.0,3.0,1.0,48.0,1.0
-CH,258.0,6,2.0,9.0,9.0,8.0,9.0,5.0,2.0,1.0,85.0,2.0
-CH,260.0,6,6.0,0.0,1.0,5.0,6.0,2.0,1.0,2.0,52.0,2.0
-CH,261.0,6,2.0,3.0,5.0,5.0,8.0,5.0,3.0,2.0,30.0,2.0
-CH,270.0,6,2.0,6.0,8.0,8.0,10.0,5.0,3.0,2.0,51.0,1.0
-CH,271.0,6,1.0,10.0,9.0,9.0,7.0,6.0,2.0,2.0,29.0,1.0
-CH,273.0,6,2.0,7.0,8.0,7.0,8.0,5.0,3.0,1.0,51.0,1.0
-CH,279.0,6,1.0,8.0,8.0,5.0,8.0,5.0,3.0,1.0,62.0,2.0
-CH,295.0,6,0.0,6.0,9.0,6.0,10.0,4.0,3.0,2.0,27.0,1.0
-CH,297.0,6,3.0,8.0,9.0,4.0,8.0,6.0,3.0,1.0,42.0,2.0
-CH,303.0,6,3.0,6.0,3.0,7.0,9.0,7.0,2.0,2.0,47.0,1.0
-CH,308.0,6,0.0,8.0,6.0,6.0,9.0,4.0,2.0,2.0,24.0,2.0
-CH,318.0,6,4.0,8.0,8.0,5.0,10.0,5.0,3.0,1.0,79.0,1.0
-CH,322.0,6,3.0,5.0,7.0,4.0,9.0,5.0,3.0,2.0,70.0,1.0
-CH,323.0,6,3.0,3.0,3.0,3.0,9.0,3.0,2.0,2.0,44.0,1.0
-CH,332.0,6,7.0,6.0,7.0,5.0,8.0,4.0,2.0,2.0,70.0,1.0
-CH,333.0,6,2.0,3.0,3.0,3.0,8.0,6.0,3.0,1.0,30.0,1.0
-CH,339.0,6,4.0,4.0,7.0,8.0,6.0,7.0,5.0,2.0,92.0,2.0
-CH,345.0,6,2.0,7.0,7.0,3.0,9.0,5.0,3.0,1.0,45.0,1.0
-CH,354.0,6,5.0,4.0,7.0,6.0,7.0,3.0,2.0,1.0,50.0,1.0
-CH,357.0,6,2.0,7.0,7.0,8.0,8.0,5.0,3.0,2.0,37.0,1.0
-CH,359.0,6,1.0,7.0,6.0,7.0,8.0,6.0,3.0,1.0,48.0,1.0
-CH,362.0,6,3.0,1.0,6.0,5.0,9.0,4.0,3.0,1.0,64.0,1.0
-CH,369.0,6,5.0,8.0,5.0,4.0,10.0,5.0,3.0,1.0,75.0,1.0
-CH,380.0,6,1.0,5.0,7.0,3.0,10.0,4.0,5.0,1.0,20.0,2.0
-CH,400.0,6,0.0,7.0,8.0,8.0,9.0,6.0,3.0,2.0,45.0,1.0
-CH,402.0,6,6.0,4.0,6.0,2.0,8.0,4.0,2.0,2.0,79.0,2.0
-CH,404.0,6,2.0,4.0,5.0,3.0,8.0,5.0,3.0,1.0,47.0,2.0
-CH,405.0,6,2.0,8.0,7.0,9.0,10.0,3.0,3.0,1.0,19.0,2.0
-CH,407.0,6,2.0,8.0,8.0,5.0,9.0,5.0,2.0,1.0,52.0,1.0
-CH,412.0,6,2.0,5.0,5.0,8.0,6.0,4.0,2.0,1.0,60.0,1.0
-CH,417.0,6,4.0,2.0,5.0,4.0,9.0,4.0,3.0,2.0,31.0,2.0
-CH,420.0,6,2.0,4.0,5.0,5.0,9.0,7.0,3.0,2.0,35.0,2.0
-CH,422.0,6,1.0,7.0,8.0,4.0,6.0,2.0,2.0,1.0,48.0,1.0
-CH,425.0,6,3.0,0.0,2.0,0.0,8.0,6.0,3.0,2.0,37.0,2.0
-CH,427.0,6,4.0,6.0,5.0,4.0,10.0,6.0,3.0,2.0,65.0,1.0
-CH,430.0,6,3.0,6.0,3.0,3.0,7.0,7.0,5.0,1.0,68.0,1.0
-CH,434.0,6,3.0,5.0,5.0,2.0,1.0,5.0,2.0,1.0,27.0,2.0
-CH,441.0,6,5.0,5.0,8.0,8.0,5.0,6.0,2.0,2.0,84.0,2.0
-CH,443.0,6,7.0,4.0,3.0,1.0,8.0,4.0,2.0,2.0,40.0,2.0
-CH,444.0,6,2.0,8.0,7.0,5.0,9.0,6.0,4.0,1.0,28.0,1.0
-CH,447.0,6,5.0,3.0,5.0,4.0,7.0,3.0,3.0,1.0,58.0,1.0
-CH,448.0,6,2.0,7.0,8.0,6.0,7.0,2.0,2.0,1.0,58.0,1.0
-CH,456.0,6,2.0,4.0,7.0,5.0,7.0,2.0,2.0,2.0,39.0,1.0
-CH,457.0,6,0.0,8.0,8.0,8.0,8.0,4.0,2.0,2.0,20.0,2.0
-CH,459.0,6,3.0,8.0,5.0,7.0,7.0,6.0,2.0,1.0,32.0,1.0
-CH,461.0,6,3.0,6.0,7.0,7.0,8.0,6.0,3.0,1.0,16.0,2.0
-CH,471.0,6,0.0,8.0,8.0,7.0,10.0,5.0,3.0,2.0,36.0,1.0
-CH,476.0,6,2.0,5.0,3.0,2.0,8.0,6.0,3.0,1.0,67.0,2.0
-CH,481.0,6,5.0,7.0,5.0,4.0,7.0,7.0,3.0,1.0,23.0,2.0
-CH,491.0,6,5.0,7.0,6.0,6.0,7.0,6.0,3.0,2.0,69.0,1.0
-CH,494.0,6,1.0,5.0,7.0,7.0,10.0,6.0,3.0,2.0,45.0,1.0
-CH,496.0,6,5.0,4.0,6.0,6.0,7.0,3.0,2.0,1.0,45.0,1.0
-CH,497.0,6,2.0,10.0,8.0,8.0,10.0,7.0,3.0,1.0,56.0,1.0
-CH,498.0,6,6.0,3.0,3.0,5.0,7.0,4.0,2.0,1.0,39.0,1.0
-CH,501.0,6,4.0,9.0,9.0,9.0,10.0,5.0,2.0,1.0,59.0,1.0
-CH,502.0,6,1.0,4.0,5.0,10.0,10.0,6.0,3.0,1.0,42.0,1.0
-CH,503.0,6,1.0,9.0,8.0,8.0,9.0,7.0,3.0,1.0,23.0,2.0
-CH,504.0,6,6.0,7.0,5.0,5.0,9.0,6.0,2.0,2.0,75.0,1.0
-CH,506.0,6,3.0,3.0,7.0,5.0,8.0,2.0,3.0,2.0,78.0,2.0
-CH,508.0,6,3.0,6.0,4.0,3.0,8.0,3.0,1.0,1.0,57.0,1.0
-CH,509.0,6,0.0,5.0,5.0,3.0,9.0,6.0,3.0,2.0,33.0,1.0
-CH,512.0,6,4.0,5.0,5.0,9.0,8.0,6.0,3.0,2.0,55.0,1.0
-CH,516.0,6,2.0,8.0,7.0,8.0,9.0,5.0,3.0,2.0,32.0,1.0
-CH,520.0,6,7.0,5.0,8.0,6.0,8.0,6.0,2.0,2.0,83.0,2.0
-CH,522.0,6,2.0,5.0,5.0,6.0,10.0,4.0,3.0,1.0,24.0,2.0
-CH,524.0,6,3.0,6.0,5.0,8.0,9.0,5.0,3.0,1.0,74.0,1.0
-CH,526.0,6,0.0,7.0,6.0,8.0,9.0,6.0,2.0,2.0,25.0,2.0
-CH,539.0,6,6.0,6.0,5.0,6.0,9.0,6.0,3.0,1.0,46.0,1.0
-CH,546.0,6,2.0,7.0,7.0,7.0,8.0,4.0,4.0,2.0,49.0,1.0
-CH,551.0,6,3.0,7.0,5.0,3.0,7.0,4.0,1.0,1.0,68.0,1.0
-CH,563.0,6,1.0,6.0,7.0,6.0,9.0,6.0,3.0,2.0,37.0,1.0
-CH,568.0,6,5.0,9.0,9.0,10.0,10.0,4.0,,2.0,39.0,1.0
-CH,569.0,6,4.0,7.0,8.0,5.0,8.0,6.0,4.0,2.0,58.0,1.0
-CH,570.0,6,3.0,7.0,8.0,7.0,8.0,6.0,3.0,2.0,19.0,2.0
-CH,575.0,6,3.0,7.0,4.0,4.0,9.0,7.0,3.0,1.0,21.0,2.0
-CH,576.0,6,3.0,4.0,3.0,3.0,7.0,2.0,1.0,2.0,45.0,2.0
-CH,578.0,6,5.0,5.0,7.0,7.0,10.0,4.0,2.0,2.0,43.0,1.0
-CH,581.0,6,2.0,5.0,5.0,3.0,8.0,7.0,5.0,1.0,32.0,2.0
-CH,586.0,6,5.0,7.0,6.0,4.0,8.0,4.0,3.0,1.0,68.0,1.0
-CH,587.0,6,3.0,5.0,8.0,8.0,9.0,5.0,1.0,2.0,86.0,2.0
-CH,590.0,6,4.0,5.0,4.0,3.0,7.0,4.0,3.0,2.0,50.0,1.0
-CH,597.0,6,6.0,4.0,2.0,5.0,8.0,4.0,3.0,1.0,65.0,1.0
-CH,600.0,6,4.0,5.0,6.0,3.0,8.0,6.0,3.0,2.0,61.0,1.0
-CH,605.0,6,4.0,3.0,6.0,5.0,7.0,6.0,3.0,1.0,60.0,1.0
-CH,606.0,6,1.0,4.0,4.0,3.0,8.0,3.0,3.0,2.0,62.0,1.0
-CH,607.0,6,6.0,4.0,6.0,8.0,8.0,5.0,3.0,2.0,74.0,1.0
-CH,609.0,6,6.0,4.0,8.0,5.0,7.0,6.0,2.0,2.0,42.0,1.0
-CH,610.0,6,2.0,7.0,5.0,5.0,9.0,5.0,2.0,2.0,51.0,1.0
-CH,613.0,6,2.0,7.0,8.0,5.0,7.0,7.0,3.0,1.0,24.0,2.0
-CH,618.0,6,3.0,5.0,7.0,8.0,8.0,6.0,3.0,2.0,50.0,1.0
-CH,625.0,6,5.0,3.0,4.0,4.0,10.0,6.0,3.0,2.0,67.0,1.0
-CH,630.0,6,1.0,8.0,10.0,7.0,8.0,6.0,3.0,1.0,55.0,1.0
-CH,633.0,6,1.0,6.0,8.0,6.0,8.0,6.0,3.0,2.0,23.0,1.0
-CH,637.0,6,4.0,6.0,8.0,9.0,9.0,6.0,2.0,2.0,60.0,1.0
-CH,643.0,6,1.0,8.0,7.0,7.0,8.0,6.0,2.0,1.0,44.0,1.0
-CH,646.0,6,6.0,8.0,7.0,6.0,9.0,6.0,2.0,2.0,42.0,1.0
-CH,648.0,6,1.0,5.0,5.0,5.0,7.0,4.0,3.0,2.0,37.0,2.0
-CH,655.0,6,3.0,1.0,4.0,5.0,5.0,6.0,2.0,2.0,45.0,2.0
-CH,658.0,6,1.0,7.0,8.0,6.0,10.0,4.0,3.0,1.0,27.0,1.0
-CH,660.0,6,3.0,5.0,5.0,4.0,8.0,4.0,5.0,1.0,59.0,1.0
-CH,663.0,6,0.0,6.0,8.0,4.0,9.0,4.0,4.0,2.0,57.0,1.0
-CH,666.0,6,1.0,8.0,10.0,3.0,8.0,6.0,3.0,1.0,58.0,2.0
-CH,675.0,6,2.0,7.0,7.0,5.0,7.0,4.0,4.0,2.0,47.0,1.0
-CH,676.0,6,5.0,6.0,0.0,5.0,10.0,3.0,2.0,2.0,91.0,2.0
-CH,680.0,6,3.0,7.0,8.0,7.0,8.0,6.0,2.0,2.0,16.0,2.0
-CH,684.0,6,1.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,34.0,1.0
-CH,685.0,6,7.0,7.0,7.0,2.0,5.0,6.0,1.0,1.0,60.0,2.0
-CH,686.0,6,2.0,3.0,10.0,5.0,10.0,7.0,,2.0,,1.0
-CH,690.0,6,1.0,5.0,7.0,3.0,9.0,5.0,3.0,2.0,51.0,1.0
-CH,692.0,6,7.0,4.0,7.0,4.0,6.0,3.0,4.0,2.0,68.0,2.0
-CH,693.0,6,4.0,3.0,6.0,4.0,4.0,2.0,1.0,1.0,36.0,1.0
-CH,696.0,6,4.0,7.0,4.0,5.0,7.0,5.0,3.0,2.0,51.0,1.0
-CH,697.0,6,6.0,3.0,4.0,5.0,6.0,5.0,2.0,1.0,65.0,1.0
-CH,698.0,6,0.0,7.0,7.0,4.0,9.0,6.0,1.0,2.0,37.0,1.0
-CH,701.0,6,1.0,5.0,6.0,8.0,5.0,4.0,2.0,2.0,58.0,2.0
-CH,703.0,6,7.0,6.0,8.0,7.0,8.0,7.0,3.0,1.0,22.0,2.0
-CH,706.0,6,5.0,4.0,5.0,4.0,6.0,2.0,1.0,1.0,39.0,1.0
-CH,707.0,6,4.0,2.0,5.0,4.0,9.0,6.0,4.0,2.0,23.0,2.0
-CH,708.0,6,1.0,7.0,2.0,3.0,8.0,6.0,3.0,1.0,68.0,1.0
-CH,709.0,6,6.0,6.0,7.0,8.0,8.0,7.0,2.0,1.0,65.0,1.0
-CH,711.0,6,3.0,3.0,3.0,3.0,9.0,6.0,4.0,2.0,40.0,1.0
-CH,713.0,6,2.0,0.0,0.0,5.0,10.0,5.0,1.0,2.0,28.0,1.0
-CH,714.0,6,3.0,6.0,8.0,6.0,9.0,6.0,4.0,1.0,17.0,2.0
-CH,715.0,6,2.0,8.0,8.0,5.0,,6.0,4.0,1.0,70.0,1.0
-CH,716.0,6,1.0,0.0,5.0,5.0,10.0,6.0,2.0,2.0,52.0,1.0
-CH,717.0,6,3.0,6.0,4.0,10.0,10.0,2.0,2.0,2.0,32.0,1.0
-CH,720.0,6,1.0,5.0,7.0,7.0,7.0,6.0,4.0,1.0,54.0,2.0
-CH,722.0,6,1.0,4.0,9.0,8.0,8.0,6.0,3.0,2.0,31.0,1.0
-CH,724.0,6,0.0,8.0,8.0,7.0,10.0,5.0,3.0,2.0,55.0,1.0
-CH,728.0,6,3.0,5.0,5.0,3.0,5.0,3.0,2.0,1.0,76.0,1.0
-CH,729.0,6,3.0,4.0,8.0,5.0,7.0,5.0,3.0,2.0,69.0,2.0
-CH,730.0,6,6.0,3.0,6.0,4.0,9.0,6.0,4.0,2.0,23.0,2.0
-CH,733.0,6,7.0,5.0,0.0,3.0,8.0,7.0,3.0,1.0,41.0,1.0
-CH,739.0,6,3.0,9.0,10.0,7.0,9.0,7.0,2.0,2.0,,2.0
-CH,740.0,6,3.0,2.0,4.0,4.0,7.0,4.0,2.0,1.0,39.0,1.0
-CH,741.0,6,3.0,7.0,7.0,7.0,8.0,3.0,3.0,1.0,63.0,1.0
-CH,743.0,6,5.0,5.0,7.0,5.0,8.0,7.0,3.0,2.0,44.0,1.0
-CH,747.0,6,2.0,5.0,8.0,8.0,10.0,6.0,3.0,2.0,69.0,1.0
-CH,748.0,6,3.0,9.0,7.0,7.0,9.0,6.0,3.0,2.0,45.0,2.0
-CH,757.0,6,5.0,4.0,4.0,5.0,8.0,6.0,2.0,2.0,51.0,1.0
-CH,759.0,6,4.0,5.0,5.0,4.0,9.0,6.0,3.0,1.0,43.0,1.0
-CH,760.0,6,1.0,6.0,8.0,8.0,9.0,5.0,3.0,1.0,48.0,1.0
-CH,761.0,6,6.0,7.0,8.0,5.0,10.0,6.0,4.0,1.0,62.0,1.0
-CH,762.0,6,1.0,7.0,5.0,8.0,8.0,7.0,4.0,1.0,16.0,2.0
-CH,764.0,6,0.0,6.0,7.0,7.0,9.0,6.0,3.0,2.0,36.0,1.0
-CH,770.0,6,3.0,9.0,9.0,9.0,8.0,6.0,4.0,2.0,74.0,1.0
-CH,771.0,6,2.0,7.0,8.0,6.0,9.0,4.0,2.0,2.0,56.0,1.0
-CH,774.0,6,2.0,5.0,6.0,5.0,9.0,5.0,3.0,2.0,70.0,1.0
-CH,778.0,6,3.0,6.0,7.0,7.0,7.0,3.0,1.0,2.0,35.0,1.0
-CH,779.0,6,3.0,5.0,8.0,4.0,8.0,4.0,3.0,1.0,41.0,1.0
-CH,781.0,6,4.0,4.0,4.0,5.0,3.0,5.0,2.0,1.0,78.0,1.0
-CH,788.0,6,1.0,5.0,5.0,7.0,8.0,6.0,3.0,1.0,41.0,1.0
-CH,789.0,6,0.0,7.0,3.0,5.0,,3.0,1.0,2.0,35.0,2.0
-CH,790.0,6,3.0,4.0,8.0,6.0,8.0,3.0,4.0,1.0,62.0,1.0
-CH,793.0,6,2.0,7.0,9.0,8.0,10.0,5.0,3.0,1.0,67.0,1.0
-CH,796.0,6,3.0,9.0,8.0,8.0,8.0,3.0,2.0,1.0,53.0,1.0
-CH,797.0,6,1.0,5.0,6.0,5.0,7.0,7.0,2.0,1.0,59.0,1.0
-CH,800.0,6,0.0,8.0,6.0,5.0,8.0,6.0,1.0,2.0,35.0,1.0
-CH,801.0,6,0.0,8.0,8.0,3.0,7.0,6.0,2.0,1.0,53.0,2.0
-CH,803.0,6,0.0,9.0,6.0,6.0,8.0,7.0,4.0,2.0,64.0,2.0
-CH,809.0,6,3.0,7.0,7.0,7.0,9.0,6.0,3.0,1.0,56.0,1.0
-CH,810.0,6,7.0,2.0,3.0,6.0,10.0,6.0,3.0,2.0,38.0,1.0
-CH,814.0,6,3.0,0.0,0.0,3.0,8.0,7.0,3.0,2.0,45.0,1.0
-CH,817.0,6,7.0,2.0,3.0,7.0,9.0,5.0,2.0,1.0,75.0,1.0
-CH,819.0,6,5.0,5.0,4.0,4.0,6.0,7.0,4.0,1.0,28.0,2.0
-CH,821.0,6,4.0,1.0,7.0,3.0,9.0,6.0,4.0,1.0,57.0,1.0
-CH,822.0,6,4.0,5.0,5.0,6.0,9.0,4.0,2.0,1.0,,1.0
-CH,824.0,6,2.0,6.0,7.0,3.0,9.0,3.0,2.0,1.0,25.0,1.0
-CH,827.0,6,3.0,4.0,6.0,4.0,10.0,6.0,4.0,2.0,52.0,1.0
-CH,834.0,6,5.0,6.0,6.0,5.0,8.0,6.0,3.0,2.0,50.0,1.0
-CH,838.0,6,5.0,7.0,7.0,5.0,9.0,4.0,3.0,2.0,31.0,1.0
-CH,842.0,6,2.0,5.0,9.0,6.0,6.0,6.0,4.0,2.0,31.0,1.0
-CH,844.0,6,2.0,6.0,6.0,5.0,8.0,6.0,2.0,1.0,73.0,2.0
-CH,847.0,6,4.0,6.0,7.0,7.0,7.0,6.0,3.0,2.0,43.0,1.0
-CH,850.0,6,1.0,7.0,8.0,8.0,9.0,6.0,1.0,1.0,60.0,1.0
-CH,852.0,6,3.0,6.0,5.0,6.0,6.0,4.0,2.0,1.0,72.0,2.0
-CH,857.0,6,3.0,4.0,7.0,9.0,9.0,6.0,3.0,1.0,25.0,1.0
-CH,858.0,6,3.0,7.0,6.0,5.0,8.0,5.0,3.0,2.0,35.0,1.0
-CH,860.0,6,3.0,5.0,5.0,7.0,9.0,6.0,2.0,2.0,16.0,2.0
-CH,861.0,6,2.0,7.0,4.0,7.0,9.0,5.0,3.0,2.0,29.0,1.0
-CH,862.0,6,3.0,4.0,3.0,3.0,10.0,2.0,2.0,1.0,68.0,1.0
-CH,875.0,6,1.0,9.0,10.0,9.0,9.0,6.0,3.0,1.0,33.0,1.0
-CH,877.0,6,4.0,6.0,4.0,6.0,8.0,2.0,1.0,1.0,26.0,1.0
-CH,880.0,6,2.0,8.0,8.0,9.0,8.0,6.0,3.0,2.0,36.0,2.0
-CH,881.0,6,4.0,4.0,8.0,8.0,8.0,6.0,2.0,2.0,16.0,2.0
-CH,883.0,6,5.0,8.0,8.0,4.0,9.0,5.0,3.0,1.0,67.0,1.0
-CH,893.0,6,2.0,9.0,9.0,9.0,10.0,7.0,3.0,1.0,23.0,2.0
-CH,898.0,6,5.0,6.0,8.0,6.0,8.0,4.0,1.0,2.0,79.0,1.0
-CH,900.0,6,1.0,8.0,7.0,6.0,8.0,5.0,2.0,1.0,57.0,1.0
-CH,903.0,6,5.0,5.0,4.0,5.0,8.0,4.0,3.0,2.0,57.0,2.0
-CH,908.0,6,3.0,2.0,2.0,3.0,8.0,4.0,2.0,1.0,80.0,2.0
-CH,910.0,6,4.0,4.0,5.0,7.0,8.0,6.0,1.0,1.0,81.0,2.0
-CH,911.0,6,3.0,7.0,7.0,5.0,7.0,6.0,4.0,1.0,35.0,1.0
-CH,912.0,6,2.0,6.0,8.0,6.0,8.0,5.0,1.0,1.0,47.0,1.0
-CH,920.0,6,2.0,3.0,7.0,6.0,2.0,4.0,2.0,2.0,68.0,1.0
-CH,921.0,6,5.0,6.0,5.0,6.0,8.0,5.0,3.0,1.0,,1.0
-CH,923.0,6,3.0,8.0,8.0,8.0,10.0,7.0,4.0,2.0,63.0,1.0
-CH,924.0,6,0.0,8.0,8.0,7.0,8.0,3.0,1.0,1.0,52.0,1.0
-CH,927.0,6,2.0,3.0,4.0,4.0,5.0,6.0,2.0,1.0,51.0,1.0
-CH,931.0,6,0.0,8.0,7.0,5.0,7.0,6.0,2.0,1.0,19.0,2.0
-CH,934.0,6,7.0,2.0,7.0,7.0,5.0,5.0,2.0,2.0,71.0,2.0
-CH,937.0,6,0.0,7.0,7.0,5.0,9.0,7.0,3.0,2.0,42.0,1.0
-CH,939.0,6,4.0,6.0,8.0,8.0,7.0,6.0,3.0,2.0,21.0,2.0
-CH,941.0,6,5.0,6.0,8.0,9.0,8.0,4.0,1.0,1.0,71.0,1.0
-CH,944.0,6,4.0,7.0,8.0,5.0,8.0,7.0,2.0,2.0,17.0,2.0
-CH,947.0,6,3.0,7.0,5.0,2.0,7.0,5.0,4.0,1.0,74.0,1.0
-CH,951.0,6,2.0,1.0,6.0,3.0,3.0,7.0,3.0,1.0,23.0,2.0
-CH,953.0,6,1.0,5.0,7.0,7.0,7.0,6.0,3.0,2.0,63.0,1.0
-CH,955.0,6,5.0,5.0,5.0,7.0,8.0,4.0,3.0,2.0,81.0,1.0
-CH,961.0,6,7.0,5.0,10.0,10.0,10.0,5.0,3.0,2.0,82.0,1.0
-CH,962.0,6,5.0,3.0,3.0,3.0,7.0,4.0,2.0,1.0,34.0,1.0
-CH,963.0,6,2.0,3.0,4.0,7.0,5.0,6.0,3.0,1.0,22.0,2.0
-CH,966.0,6,6.0,4.0,6.0,6.0,4.0,3.0,2.0,2.0,30.0,1.0
-CH,967.0,6,3.0,5.0,10.0,6.0,10.0,4.0,1.0,2.0,54.0,1.0
-CH,976.0,6,2.0,5.0,8.0,8.0,10.0,6.0,5.0,2.0,52.0,1.0
-CH,979.0,6,6.0,4.0,5.0,4.0,8.0,4.0,3.0,1.0,80.0,1.0
-CH,980.0,6,3.0,5.0,5.0,5.0,7.0,6.0,3.0,2.0,26.0,1.0
-CH,987.0,6,4.0,6.0,8.0,6.0,8.0,6.0,3.0,1.0,52.0,2.0
-CH,990.0,6,3.0,8.0,7.0,9.0,6.0,3.0,2.0,2.0,74.0,1.0
-CH,1001.0,6,5.0,4.0,7.0,6.0,9.0,3.0,3.0,1.0,76.0,1.0
-CH,1004.0,6,3.0,8.0,8.0,2.0,9.0,,3.0,2.0,68.0,1.0
-CH,1009.0,6,2.0,7.0,8.0,6.0,9.0,5.0,3.0,1.0,58.0,2.0
-CH,1016.0,6,6.0,4.0,5.0,5.0,9.0,5.0,3.0,2.0,42.0,1.0
-CH,1017.0,6,7.0,4.0,8.0,3.0,10.0,1.0,1.0,2.0,70.0,1.0
-CH,1027.0,6,2.0,5.0,5.0,7.0,8.0,5.0,5.0,2.0,48.0,2.0
-CH,1029.0,6,4.0,2.0,1.0,3.0,10.0,6.0,5.0,1.0,79.0,2.0
-CH,1031.0,6,0.0,9.0,9.0,6.0,10.0,6.0,5.0,1.0,42.0,1.0
-CH,1033.0,6,7.0,3.0,3.0,2.0,10.0,6.0,3.0,2.0,28.0,1.0
-CH,1035.0,6,3.0,8.0,7.0,7.0,8.0,6.0,4.0,1.0,43.0,1.0
-CH,1036.0,6,5.0,5.0,9.0,10.0,10.0,5.0,3.0,1.0,40.0,1.0
-CH,1037.0,6,6.0,3.0,4.0,4.0,9.0,6.0,2.0,1.0,24.0,2.0
-CH,1041.0,6,5.0,5.0,7.0,5.0,9.0,6.0,2.0,1.0,69.0,1.0
-CH,1043.0,6,5.0,5.0,8.0,5.0,10.0,2.0,4.0,1.0,72.0,1.0
-CH,1044.0,6,7.0,2.0,5.0,8.0,8.0,6.0,1.0,1.0,84.0,2.0
-CH,1046.0,6,2.0,1.0,8.0,8.0,9.0,3.0,3.0,1.0,48.0,1.0
-CH,1049.0,6,1.0,5.0,7.0,6.0,10.0,4.0,4.0,2.0,85.0,1.0
-CH,1050.0,6,3.0,7.0,7.0,10.0,10.0,6.0,2.0,1.0,51.0,1.0
-CH,1051.0,6,0.0,4.0,8.0,3.0,8.0,5.0,2.0,2.0,49.0,2.0
-CH,1052.0,6,2.0,5.0,8.0,7.0,8.0,6.0,3.0,2.0,19.0,2.0
-CH,1060.0,6,7.0,2.0,4.0,1.0,7.0,6.0,2.0,2.0,44.0,1.0
-CH,1061.0,6,4.0,1.0,9.0,10.0,8.0,6.0,4.0,2.0,68.0,1.0
-CH,1062.0,6,5.0,8.0,7.0,5.0,9.0,6.0,4.0,2.0,39.0,1.0
-CH,1063.0,6,1.0,4.0,5.0,7.0,9.0,4.0,2.0,2.0,27.0,1.0
-CH,1066.0,6,6.0,3.0,7.0,9.0,6.0,4.0,3.0,1.0,51.0,1.0
-CH,1067.0,6,2.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,24.0,1.0
-CH,1072.0,6,3.0,2.0,4.0,4.0,8.0,4.0,2.0,2.0,35.0,1.0
-CH,1076.0,6,0.0,7.0,7.0,6.0,9.0,5.0,4.0,1.0,48.0,2.0
-CH,1083.0,6,5.0,6.0,6.0,4.0,6.0,2.0,3.0,2.0,43.0,1.0
-CH,1086.0,6,1.0,7.0,8.0,6.0,8.0,4.0,2.0,1.0,23.0,2.0
-CH,1088.0,6,3.0,5.0,6.0,7.0,8.0,7.0,2.0,1.0,27.0,2.0
-CH,1090.0,6,7.0,7.0,8.0,6.0,8.0,7.0,4.0,2.0,51.0,1.0
-CH,1096.0,6,5.0,5.0,5.0,6.0,8.0,4.0,3.0,2.0,,1.0
-CH,1106.0,6,1.0,8.0,9.0,5.0,8.0,6.0,1.0,2.0,,1.0
-CH,1107.0,6,5.0,3.0,6.0,5.0,8.0,6.0,4.0,2.0,38.0,2.0
-CH,1112.0,6,0.0,8.0,8.0,6.0,10.0,3.0,,2.0,52.0,1.0
-CH,1117.0,6,7.0,5.0,8.0,5.0,7.0,5.0,2.0,1.0,79.0,2.0
-CH,1118.0,6,0.0,7.0,7.0,5.0,8.0,4.0,2.0,2.0,34.0,1.0
-CH,1127.0,6,7.0,3.0,8.0,9.0,10.0,6.0,2.0,2.0,89.0,2.0
-CH,1133.0,6,3.0,8.0,8.0,8.0,9.0,6.0,3.0,2.0,48.0,1.0
-CH,1134.0,6,6.0,7.0,5.0,0.0,5.0,4.0,2.0,1.0,86.0,1.0
-CH,1135.0,6,2.0,6.0,7.0,7.0,8.0,6.0,3.0,1.0,41.0,1.0
-CH,1137.0,6,1.0,6.0,8.0,6.0,8.0,6.0,3.0,2.0,16.0,2.0
-CH,1138.0,6,2.0,5.0,6.0,4.0,7.0,4.0,3.0,1.0,34.0,1.0
-CH,1141.0,6,6.0,5.0,7.0,8.0,9.0,5.0,3.0,2.0,58.0,1.0
-CH,1144.0,6,0.0,8.0,8.0,7.0,8.0,6.0,3.0,2.0,42.0,1.0
-CH,1148.0,6,2.0,3.0,4.0,3.0,6.0,5.0,3.0,2.0,31.0,2.0
-CH,1152.0,6,2.0,5.0,8.0,7.0,10.0,6.0,3.0,1.0,60.0,1.0
-CH,1154.0,6,4.0,4.0,5.0,6.0,8.0,5.0,2.0,1.0,70.0,1.0
-CH,1159.0,6,5.0,5.0,5.0,3.0,6.0,5.0,2.0,1.0,46.0,1.0
-CH,1164.0,6,1.0,9.0,9.0,7.0,9.0,6.0,2.0,2.0,34.0,1.0
-CH,1168.0,6,6.0,5.0,5.0,2.0,8.0,7.0,3.0,2.0,41.0,1.0
-CH,1173.0,6,2.0,3.0,5.0,4.0,9.0,5.0,2.0,2.0,43.0,1.0
-CH,1174.0,6,3.0,8.0,7.0,5.0,9.0,3.0,3.0,1.0,48.0,1.0
-CH,1182.0,6,2.0,6.0,8.0,8.0,9.0,2.0,2.0,2.0,47.0,1.0
-CH,1183.0,6,4.0,4.0,4.0,3.0,9.0,6.0,3.0,2.0,42.0,1.0
-CH,1188.0,6,2.0,4.0,5.0,,5.0,3.0,1.0,2.0,45.0,1.0
-CH,1189.0,6,2.0,7.0,9.0,7.0,9.0,5.0,3.0,2.0,56.0,1.0
-CH,1194.0,6,4.0,8.0,8.0,6.0,8.0,6.0,3.0,2.0,58.0,1.0
-CH,1198.0,6,0.0,8.0,8.0,7.0,8.0,4.0,2.0,2.0,42.0,2.0
-CH,1201.0,6,1.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,40.0,1.0
-CH,1208.0,6,0.0,8.0,8.0,4.0,9.0,6.0,4.0,2.0,38.0,1.0
-CH,1209.0,6,1.0,4.0,7.0,7.0,8.0,4.0,2.0,1.0,62.0,1.0
-CH,1217.0,6,2.0,5.0,7.0,4.0,10.0,6.0,2.0,2.0,19.0,2.0
-CH,1222.0,6,2.0,5.0,5.0,7.0,9.0,5.0,2.0,2.0,41.0,1.0
-CH,1223.0,6,4.0,8.0,4.0,7.0,10.0,6.0,3.0,2.0,61.0,1.0
-CH,1229.0,6,2.0,5.0,7.0,8.0,10.0,6.0,2.0,1.0,54.0,1.0
-CH,1230.0,6,0.0,8.0,2.0,5.0,8.0,2.0,3.0,1.0,37.0,1.0
-CH,1233.0,6,5.0,10.0,8.0,8.0,9.0,7.0,3.0,1.0,70.0,1.0
-CH,1236.0,6,2.0,5.0,8.0,7.0,10.0,4.0,2.0,1.0,74.0,1.0
-CH,1237.0,6,4.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,23.0,2.0
-CH,1240.0,6,0.0,8.0,8.0,8.0,9.0,5.0,3.0,2.0,56.0,1.0
-CH,1242.0,6,2.0,8.0,9.0,6.0,9.0,7.0,3.0,1.0,46.0,1.0
-CH,1245.0,6,5.0,9.0,8.0,8.0,10.0,5.0,2.0,1.0,61.0,1.0
-CH,1247.0,6,2.0,2.0,4.0,2.0,3.0,1.0,1.0,2.0,41.0,2.0
-CH,1254.0,6,2.0,6.0,4.0,4.0,8.0,6.0,2.0,1.0,27.0,1.0
-CH,1264.0,6,3.0,8.0,8.0,7.0,8.0,7.0,3.0,1.0,16.0,2.0
-CH,1265.0,6,5.0,8.0,8.0,8.0,9.0,5.0,3.0,2.0,23.0,2.0
-CH,1266.0,6,4.0,2.0,2.0,3.0,8.0,5.0,3.0,2.0,17.0,2.0
-CH,1269.0,6,1.0,8.0,7.0,7.0,7.0,3.0,3.0,1.0,56.0,1.0
-CH,1278.0,6,4.0,2.0,4.0,3.0,6.0,2.0,1.0,1.0,69.0,1.0
-CH,1282.0,6,2.0,8.0,8.0,8.0,8.0,3.0,3.0,2.0,32.0,1.0
-CH,1288.0,6,3.0,4.0,5.0,7.0,9.0,6.0,2.0,2.0,51.0,2.0
-CH,1290.0,6,2.0,7.0,8.0,7.0,9.0,6.0,3.0,1.0,24.0,1.0
-CH,1293.0,6,1.0,4.0,8.0,4.0,9.0,6.0,3.0,2.0,58.0,1.0
-CH,1303.0,6,4.0,7.0,4.0,8.0,10.0,4.0,3.0,1.0,41.0,1.0
-CH,1306.0,6,3.0,7.0,8.0,7.0,8.0,6.0,2.0,1.0,34.0,2.0
-CH,1310.0,6,2.0,10.0,10.0,10.0,10.0,6.0,3.0,2.0,68.0,1.0
-CH,1311.0,6,4.0,8.0,7.0,10.0,9.0,3.0,2.0,1.0,49.0,1.0
-CH,1312.0,6,3.0,7.0,8.0,6.0,9.0,6.0,3.0,1.0,61.0,1.0
-CH,1319.0,6,3.0,6.0,7.0,7.0,8.0,5.0,3.0,2.0,60.0,2.0
-CH,1322.0,6,1.0,5.0,8.0,7.0,10.0,6.0,1.0,2.0,16.0,2.0
-CH,1328.0,6,1.0,5.0,4.0,4.0,9.0,6.0,4.0,1.0,56.0,2.0
-CH,1333.0,6,6.0,9.0,8.0,9.0,8.0,4.0,2.0,2.0,69.0,1.0
-CH,1347.0,6,4.0,3.0,6.0,3.0,9.0,4.0,3.0,1.0,36.0,1.0
-CH,1349.0,6,4.0,6.0,7.0,4.0,7.0,6.0,3.0,2.0,21.0,2.0
-CH,1353.0,6,0.0,8.0,8.0,7.0,9.0,5.0,2.0,1.0,56.0,1.0
-CH,1356.0,6,5.0,6.0,8.0,7.0,8.0,6.0,2.0,1.0,61.0,1.0
-CH,1361.0,6,4.0,4.0,8.0,8.0,8.0,5.0,3.0,1.0,17.0,2.0
-CH,1362.0,6,4.0,6.0,8.0,4.0,7.0,5.0,3.0,2.0,73.0,2.0
-CH,1367.0,6,3.0,8.0,2.0,5.0,9.0,5.0,3.0,2.0,51.0,1.0
-CH,1369.0,6,2.0,5.0,7.0,5.0,7.0,4.0,2.0,1.0,67.0,1.0
-CH,1370.0,6,1.0,9.0,9.0,8.0,7.0,3.0,2.0,2.0,54.0,1.0
-CH,1371.0,6,5.0,0.0,6.0,5.0,9.0,4.0,3.0,1.0,60.0,1.0
-CH,1375.0,6,7.0,4.0,5.0,2.0,7.0,1.0,1.0,1.0,57.0,2.0
-CH,1378.0,6,4.0,6.0,6.0,6.0,7.0,6.0,2.0,1.0,31.0,2.0
-CH,1379.0,6,2.0,5.0,6.0,7.0,9.0,4.0,2.0,2.0,45.0,2.0
-CH,1382.0,6,5.0,2.0,5.0,0.0,10.0,3.0,2.0,2.0,50.0,2.0
-CH,1390.0,6,3.0,0.0,0.0,0.0,5.0,2.0,1.0,2.0,61.0,2.0
-CH,1402.0,6,1.0,4.0,7.0,7.0,10.0,6.0,3.0,2.0,19.0,2.0
-CH,1404.0,6,6.0,8.0,8.0,6.0,8.0,6.0,3.0,2.0,56.0,2.0
-CH,1405.0,6,4.0,0.0,7.0,6.0,7.0,4.0,3.0,2.0,,1.0
-CH,1409.0,6,2.0,8.0,8.0,4.0,10.0,4.0,2.0,1.0,36.0,1.0
-CH,1410.0,6,7.0,8.0,8.0,8.0,10.0,5.0,2.0,2.0,,2.0
-CH,1418.0,6,2.0,6.0,6.0,4.0,10.0,7.0,3.0,2.0,45.0,1.0
-CH,1431.0,6,3.0,7.0,10.0,5.0,7.0,7.0,4.0,2.0,23.0,2.0
-CH,1432.0,6,4.0,3.0,5.0,3.0,9.0,6.0,1.0,1.0,69.0,1.0
-CH,1436.0,6,3.0,8.0,8.0,7.0,8.0,6.0,3.0,2.0,40.0,1.0
-CH,1439.0,6,0.0,5.0,5.0,3.0,8.0,6.0,2.0,1.0,30.0,2.0
-CH,1447.0,6,4.0,5.0,7.0,4.0,8.0,6.0,3.0,1.0,20.0,2.0
-CH,1448.0,6,2.0,7.0,7.0,7.0,10.0,6.0,3.0,2.0,62.0,1.0
-CH,1449.0,6,4.0,5.0,5.0,5.0,10.0,7.0,3.0,2.0,23.0,1.0
-CH,1450.0,6,6.0,5.0,3.0,8.0,8.0,4.0,2.0,2.0,61.0,2.0
-CH,1451.0,6,3.0,7.0,9.0,8.0,7.0,7.0,2.0,1.0,49.0,1.0
-CH,1453.0,6,5.0,7.0,7.0,4.0,8.0,6.0,1.0,2.0,78.0,2.0
-CH,1454.0,6,4.0,5.0,4.0,2.0,5.0,4.0,3.0,1.0,76.0,2.0
-CH,1457.0,6,2.0,7.0,9.0,9.0,9.0,6.0,3.0,2.0,31.0,2.0
-CH,1462.0,6,3.0,5.0,8.0,5.0,5.0,3.0,3.0,1.0,,2.0
-CH,1463.0,6,1.0,7.0,7.0,7.0,9.0,6.0,3.0,2.0,35.0,1.0
-CH,1468.0,6,5.0,9.0,8.0,7.0,10.0,6.0,3.0,1.0,30.0,1.0
-CH,1471.0,6,3.0,10.0,,10.0,8.0,3.0,3.0,2.0,47.0,1.0
-CH,1477.0,6,2.0,9.0,9.0,10.0,9.0,6.0,3.0,2.0,26.0,1.0
-CH,1478.0,6,4.0,3.0,3.0,3.0,7.0,5.0,2.0,1.0,65.0,1.0
-CH,1484.0,6,5.0,5.0,5.0,6.0,6.0,3.0,2.0,1.0,61.0,1.0
-CH,1490.0,6,3.0,7.0,5.0,3.0,8.0,6.0,2.0,1.0,33.0,1.0
-CH,1495.0,6,1.0,5.0,10.0,4.0,8.0,6.0,4.0,2.0,58.0,1.0
-CH,1502.0,6,3.0,6.0,7.0,7.0,7.0,6.0,2.0,1.0,74.0,1.0
-CH,1504.0,6,2.0,7.0,8.0,7.0,4.0,6.0,4.0,2.0,46.0,2.0
-CH,1505.0,6,5.0,6.0,7.0,8.0,8.0,6.0,4.0,2.0,35.0,2.0
-CH,1507.0,6,2.0,7.0,8.0,6.0,8.0,5.0,3.0,2.0,51.0,1.0
-CH,1508.0,6,0.0,7.0,9.0,8.0,8.0,5.0,3.0,2.0,27.0,2.0
-CH,1510.0,6,0.0,6.0,7.0,7.0,8.0,7.0,4.0,2.0,22.0,2.0
-CH,1513.0,6,6.0,5.0,5.0,1.0,9.0,6.0,3.0,1.0,34.0,1.0
-CH,1527.0,6,5.0,7.0,7.0,7.0,7.0,6.0,1.0,2.0,44.0,1.0
-CH,1530.0,6,2.0,8.0,10.0,5.0,8.0,3.0,2.0,2.0,57.0,1.0
-CH,1535.0,6,1.0,9.0,5.0,6.0,7.0,3.0,2.0,2.0,43.0,2.0
-CH,1536.0,6,5.0,6.0,4.0,5.0,7.0,4.0,2.0,1.0,62.0,1.0
-CH,1542.0,6,3.0,8.0,2.0,8.0,9.0,6.0,3.0,2.0,79.0,1.0
-CH,1547.0,6,2.0,7.0,7.0,6.0,7.0,6.0,3.0,1.0,16.0,2.0
-CH,1553.0,6,6.0,5.0,9.0,5.0,10.0,7.0,2.0,1.0,19.0,2.0
-CH,1554.0,6,5.0,5.0,6.0,6.0,8.0,5.0,3.0,2.0,48.0,1.0
-CH,1562.0,6,7.0,5.0,8.0,5.0,5.0,7.0,1.0,1.0,65.0,2.0
-CH,1573.0,6,4.0,3.0,5.0,3.0,10.0,6.0,2.0,1.0,46.0,2.0
-CH,1577.0,6,6.0,4.0,5.0,6.0,7.0,6.0,4.0,2.0,48.0,1.0
-CH,1579.0,6,5.0,3.0,5.0,5.0,8.0,5.0,2.0,1.0,41.0,1.0
-CH,1583.0,6,5.0,3.0,5.0,6.0,9.0,3.0,,2.0,46.0,2.0
-CH,1588.0,6,6.0,0.0,10.0,10.0,9.0,4.0,2.0,1.0,74.0,1.0
-CH,1594.0,6,7.0,4.0,2.0,7.0,7.0,4.0,2.0,1.0,79.0,1.0
-CH,1597.0,6,0.0,4.0,5.0,2.0,8.0,5.0,2.0,2.0,41.0,2.0
-CH,1600.0,6,2.0,0.0,10.0,10.0,10.0,4.0,3.0,1.0,69.0,1.0
-CH,1603.0,6,4.0,3.0,6.0,3.0,7.0,4.0,3.0,2.0,22.0,2.0
-CH,1604.0,6,4.0,4.0,1.0,5.0,8.0,6.0,1.0,1.0,18.0,2.0
-CH,1605.0,6,0.0,6.0,7.0,7.0,8.0,7.0,3.0,1.0,21.0,2.0
-CH,1615.0,6,4.0,2.0,8.0,4.0,9.0,5.0,2.0,2.0,61.0,1.0
-CH,1620.0,6,4.0,8.0,9.0,5.0,7.0,4.0,3.0,2.0,64.0,1.0
-CH,1624.0,6,0.0,7.0,8.0,7.0,8.0,6.0,3.0,2.0,40.0,1.0
-CH,1637.0,6,3.0,6.0,7.0,6.0,10.0,6.0,4.0,2.0,22.0,2.0
-CH,1638.0,6,3.0,7.0,7.0,6.0,8.0,5.0,3.0,2.0,46.0,1.0
-CH,1639.0,6,3.0,6.0,7.0,5.0,9.0,4.0,3.0,1.0,56.0,2.0
-CH,1643.0,6,5.0,3.0,5.0,6.0,9.0,7.0,4.0,1.0,19.0,2.0
-CH,1653.0,6,2.0,8.0,8.0,7.0,8.0,6.0,2.0,2.0,31.0,2.0
-CH,1654.0,6,2.0,5.0,6.0,5.0,7.0,5.0,4.0,2.0,48.0,2.0
-CH,1656.0,6,6.0,7.0,7.0,6.0,10.0,3.0,,1.0,78.0,1.0
-CH,1657.0,6,2.0,3.0,3.0,4.0,8.0,6.0,3.0,2.0,16.0,2.0
-CH,1662.0,6,7.0,7.0,8.0,8.0,8.0,6.0,2.0,1.0,19.0,2.0
-CH,1667.0,6,2.0,6.0,5.0,4.0,10.0,6.0,3.0,1.0,22.0,2.0
-CH,1668.0,6,1.0,8.0,8.0,6.0,8.0,6.0,3.0,1.0,35.0,2.0
-CH,1671.0,6,3.0,6.0,5.0,8.0,8.0,6.0,3.0,1.0,16.0,2.0
-CH,1683.0,6,6.0,8.0,9.0,8.0,9.0,7.0,4.0,2.0,16.0,2.0
-CH,1686.0,6,4.0,7.0,8.0,10.0,9.0,6.0,4.0,1.0,71.0,1.0
-CH,1689.0,6,4.0,8.0,6.0,8.0,9.0,6.0,2.0,2.0,40.0,1.0
-CH,1691.0,6,6.0,6.0,6.0,8.0,10.0,7.0,3.0,2.0,59.0,1.0
-CH,1693.0,6,2.0,4.0,5.0,4.0,8.0,6.0,3.0,1.0,18.0,2.0
-CH,1701.0,6,2.0,5.0,4.0,3.0,8.0,,2.0,2.0,50.0,1.0
-CH,1707.0,6,5.0,7.0,10.0,5.0,5.0,6.0,4.0,2.0,92.0,2.0
-CH,1709.0,6,3.0,4.0,4.0,5.0,10.0,3.0,3.0,2.0,38.0,1.0
-CH,1718.0,6,3.0,5.0,3.0,5.0,8.0,6.0,3.0,2.0,18.0,2.0
-CH,1719.0,6,3.0,6.0,6.0,7.0,8.0,5.0,4.0,1.0,20.0,2.0
-CH,1720.0,6,2.0,4.0,6.0,6.0,8.0,5.0,3.0,1.0,32.0,2.0
-CH,1723.0,6,3.0,8.0,7.0,4.0,10.0,5.0,2.0,1.0,31.0,1.0
-CH,1726.0,6,3.0,7.0,4.0,7.0,9.0,2.0,4.0,1.0,57.0,1.0
-CH,1738.0,6,3.0,3.0,6.0,4.0,8.0,7.0,2.0,2.0,17.0,2.0
-CH,1743.0,6,0.0,7.0,6.0,8.0,10.0,2.0,2.0,2.0,47.0,1.0
-CH,1748.0,6,2.0,4.0,5.0,7.0,6.0,2.0,1.0,2.0,48.0,1.0
-CH,1750.0,6,3.0,7.0,7.0,5.0,5.0,4.0,2.0,1.0,51.0,1.0
-CH,1753.0,6,1.0,3.0,3.0,3.0,7.0,4.0,2.0,1.0,42.0,2.0
-CH,1755.0,6,4.0,8.0,8.0,6.0,9.0,4.0,2.0,2.0,38.0,1.0
-CH,1756.0,6,0.0,9.0,9.0,7.0,7.0,4.0,3.0,2.0,40.0,2.0
-CH,1757.0,6,3.0,6.0,7.0,8.0,8.0,5.0,3.0,1.0,48.0,1.0
-CH,1765.0,6,2.0,0.0,5.0,5.0,3.0,3.0,2.0,2.0,86.0,1.0
-CH,1766.0,6,6.0,7.0,8.0,4.0,8.0,7.0,3.0,2.0,24.0,2.0
-CH,1769.0,6,6.0,7.0,8.0,7.0,10.0,4.0,2.0,2.0,58.0,1.0
-CH,1776.0,6,1.0,6.0,5.0,7.0,9.0,6.0,3.0,1.0,33.0,1.0
-CH,1788.0,6,4.0,8.0,7.0,7.0,8.0,5.0,3.0,1.0,63.0,1.0
-CH,1790.0,6,4.0,5.0,7.0,5.0,7.0,4.0,2.0,1.0,28.0,2.0
-CH,1791.0,6,1.0,8.0,9.0,9.0,8.0,6.0,3.0,2.0,39.0,1.0
-CH,1792.0,6,3.0,8.0,8.0,6.0,8.0,4.0,2.0,1.0,55.0,1.0
-CH,1797.0,6,3.0,5.0,5.0,5.0,7.0,4.0,2.0,2.0,39.0,1.0
-CH,1801.0,6,5.0,5.0,4.0,7.0,9.0,6.0,3.0,1.0,82.0,1.0
-CH,1802.0,6,7.0,5.0,5.0,2.0,7.0,6.0,3.0,2.0,50.0,2.0
-CH,1803.0,6,0.0,5.0,9.0,8.0,8.0,4.0,1.0,2.0,27.0,2.0
-CH,1805.0,6,3.0,1.0,5.0,5.0,6.0,6.0,4.0,1.0,81.0,1.0
-CH,1809.0,6,4.0,2.0,8.0,6.0,7.0,5.0,3.0,2.0,38.0,1.0
-CH,1815.0,6,5.0,6.0,5.0,6.0,8.0,5.0,2.0,2.0,58.0,1.0
-CH,1816.0,6,2.0,8.0,7.0,7.0,9.0,6.0,3.0,2.0,32.0,2.0
-CH,1817.0,6,0.0,7.0,7.0,7.0,8.0,5.0,3.0,2.0,61.0,1.0
-CH,1819.0,6,4.0,6.0,4.0,5.0,8.0,5.0,3.0,2.0,55.0,1.0
-CH,1829.0,6,4.0,8.0,8.0,7.0,9.0,4.0,5.0,1.0,89.0,1.0
-CH,1832.0,6,3.0,7.0,7.0,7.0,9.0,7.0,4.0,2.0,36.0,1.0
-CH,1844.0,6,5.0,7.0,8.0,6.0,8.0,4.0,3.0,1.0,,1.0
-CH,1849.0,6,3.0,6.0,8.0,6.0,9.0,6.0,3.0,2.0,71.0,1.0
-CH,1850.0,6,4.0,5.0,7.0,5.0,8.0,7.0,3.0,2.0,56.0,1.0
-CH,1852.0,6,1.0,5.0,5.0,3.0,8.0,4.0,2.0,2.0,70.0,1.0
-CH,1854.0,6,4.0,5.0,7.0,6.0,9.0,2.0,2.0,1.0,55.0,1.0
-CH,1869.0,6,2.0,5.0,7.0,7.0,8.0,6.0,5.0,2.0,45.0,2.0
-CH,1877.0,6,1.0,3.0,5.0,4.0,8.0,6.0,3.0,1.0,56.0,2.0
-CH,1888.0,6,3.0,5.0,4.0,4.0,7.0,6.0,3.0,2.0,24.0,2.0
-CH,1897.0,6,5.0,0.0,4.0,8.0,8.0,7.0,3.0,2.0,33.0,1.0
-CH,1906.0,6,5.0,6.0,7.0,4.0,8.0,3.0,3.0,1.0,41.0,1.0
-CH,1914.0,6,4.0,5.0,2.0,2.0,8.0,3.0,3.0,1.0,39.0,1.0
-CH,1917.0,6,5.0,6.0,5.0,4.0,7.0,5.0,3.0,1.0,46.0,2.0
-CH,1921.0,6,3.0,5.0,7.0,4.0,8.0,3.0,3.0,1.0,49.0,1.0
-CH,1924.0,6,2.0,3.0,5.0,5.0,8.0,6.0,3.0,1.0,49.0,1.0
-CH,1929.0,6,2.0,7.0,7.0,6.0,8.0,5.0,4.0,1.0,,1.0
-CH,1940.0,6,3.0,1.0,3.0,5.0,8.0,6.0,3.0,2.0,19.0,2.0
-CH,1941.0,6,4.0,7.0,7.0,7.0,8.0,3.0,3.0,1.0,61.0,1.0
-CH,1943.0,6,3.0,9.0,7.0,9.0,9.0,7.0,4.0,2.0,17.0,2.0
-CH,1955.0,6,0.0,0.0,,,8.0,4.0,,2.0,50.0,2.0
-CH,1968.0,6,3.0,6.0,4.0,5.0,9.0,6.0,3.0,2.0,59.0,1.0
-CH,1969.0,6,2.0,7.0,8.0,8.0,8.0,5.0,3.0,2.0,58.0,2.0
-CH,1971.0,6,5.0,5.0,6.0,8.0,8.0,6.0,3.0,2.0,74.0,1.0
-CH,1978.0,6,1.0,4.0,4.0,4.0,7.0,4.0,3.0,1.0,42.0,1.0
-CH,1982.0,6,3.0,5.0,7.0,8.0,8.0,4.0,4.0,1.0,61.0,2.0
-CH,1991.0,6,1.0,6.0,7.0,7.0,9.0,6.0,2.0,2.0,22.0,1.0
-CH,1992.0,6,7.0,5.0,2.0,7.0,9.0,5.0,2.0,2.0,61.0,2.0
-CH,1998.0,6,4.0,6.0,6.0,8.0,8.0,6.0,3.0,2.0,49.0,1.0
-CH,2000.0,6,6.0,3.0,5.0,7.0,7.0,6.0,3.0,2.0,17.0,2.0
-CH,2004.0,6,1.0,5.0,3.0,5.0,10.0,2.0,1.0,2.0,,1.0
-CH,2005.0,6,2.0,7.0,10.0,9.0,9.0,6.0,2.0,1.0,37.0,1.0
-CH,2007.0,6,5.0,7.0,7.0,7.0,8.0,7.0,2.0,2.0,43.0,1.0
-CH,2008.0,6,7.0,3.0,1.0,1.0,8.0,5.0,1.0,1.0,67.0,2.0
-CH,2011.0,6,0.0,8.0,7.0,7.0,8.0,5.0,2.0,1.0,43.0,1.0
-CH,2017.0,6,2.0,8.0,9.0,9.0,9.0,5.0,3.0,1.0,16.0,2.0
-CH,2020.0,6,2.0,3.0,6.0,7.0,7.0,6.0,3.0,1.0,55.0,1.0
-CH,2021.0,6,1.0,7.0,8.0,5.0,6.0,3.0,2.0,2.0,56.0,1.0
-CH,2027.0,6,2.0,7.0,9.0,5.0,7.0,4.0,1.0,1.0,57.0,1.0
-CH,2028.0,6,1.0,4.0,5.0,6.0,8.0,5.0,2.0,1.0,36.0,1.0
-CH,2036.0,6,4.0,0.0,5.0,7.0,10.0,4.0,3.0,2.0,,1.0
-CH,2041.0,6,2.0,9.0,9.0,8.0,7.0,6.0,3.0,1.0,40.0,2.0
-CH,2049.0,6,3.0,3.0,5.0,7.0,10.0,5.0,2.0,2.0,47.0,1.0
-CH,2052.0,6,2.0,4.0,4.0,5.0,10.0,6.0,2.0,2.0,56.0,2.0
-CH,2060.0,6,2.0,5.0,8.0,6.0,8.0,5.0,3.0,1.0,53.0,1.0
-CH,2062.0,6,5.0,4.0,6.0,7.0,7.0,4.0,2.0,1.0,28.0,1.0
-CH,2063.0,6,3.0,6.0,8.0,8.0,10.0,4.0,4.0,2.0,57.0,1.0
-CH,2077.0,6,3.0,7.0,9.0,5.0,7.0,7.0,3.0,1.0,39.0,1.0
-CH,2078.0,6,2.0,9.0,7.0,5.0,8.0,5.0,3.0,2.0,56.0,1.0
-CH,2084.0,6,2.0,7.0,9.0,10.0,10.0,6.0,2.0,2.0,46.0,1.0
-CH,2090.0,6,1.0,8.0,8.0,5.0,7.0,6.0,3.0,1.0,40.0,1.0
-CH,2092.0,6,5.0,8.0,8.0,1.0,9.0,5.0,2.0,2.0,54.0,1.0
-CH,2095.0,6,7.0,9.0,9.0,5.0,10.0,5.0,4.0,1.0,35.0,1.0
-CH,2102.0,6,5.0,5.0,7.0,5.0,8.0,5.0,3.0,1.0,55.0,1.0
-CH,2106.0,6,3.0,3.0,5.0,6.0,7.0,4.0,2.0,1.0,39.0,1.0
-CH,2111.0,6,7.0,7.0,2.0,3.0,7.0,6.0,3.0,2.0,27.0,1.0
-CH,2112.0,6,3.0,8.0,7.0,6.0,10.0,5.0,2.0,1.0,33.0,1.0
-CH,2113.0,6,3.0,7.0,8.0,8.0,8.0,5.0,2.0,2.0,54.0,2.0
-CH,2115.0,6,1.0,8.0,8.0,7.0,8.0,5.0,2.0,1.0,52.0,1.0
-CH,2124.0,6,0.0,3.0,3.0,3.0,9.0,5.0,2.0,2.0,52.0,1.0
-CH,2128.0,6,2.0,8.0,7.0,7.0,9.0,5.0,2.0,1.0,34.0,1.0
-CH,2129.0,6,2.0,2.0,5.0,6.0,8.0,5.0,2.0,1.0,75.0,2.0
-CH,2131.0,6,3.0,5.0,7.0,8.0,8.0,3.0,4.0,2.0,79.0,1.0
-CH,2133.0,6,3.0,7.0,7.0,7.0,7.0,7.0,4.0,1.0,23.0,2.0
-CH,2135.0,6,3.0,8.0,7.0,6.0,9.0,6.0,5.0,2.0,25.0,2.0
-CH,2154.0,6,5.0,8.0,5.0,8.0,8.0,6.0,3.0,2.0,69.0,2.0
-CH,2159.0,6,0.0,5.0,8.0,5.0,9.0,5.0,3.0,1.0,39.0,1.0
-CH,2160.0,6,7.0,4.0,3.0,5.0,9.0,2.0,2.0,1.0,80.0,1.0
-CH,2161.0,6,5.0,6.0,8.0,4.0,7.0,2.0,2.0,2.0,69.0,1.0
-CH,2167.0,6,4.0,2.0,2.0,2.0,5.0,4.0,3.0,2.0,19.0,2.0
-CH,2169.0,6,3.0,7.0,7.0,8.0,7.0,6.0,3.0,1.0,69.0,1.0
-CH,2180.0,6,5.0,5.0,8.0,5.0,10.0,3.0,1.0,1.0,78.0,1.0
-CH,2182.0,6,7.0,7.0,5.0,2.0,4.0,4.0,1.0,1.0,42.0,2.0
-CH,2183.0,6,0.0,7.0,6.0,5.0,9.0,6.0,,2.0,68.0,2.0
-CH,2190.0,6,2.0,3.0,5.0,6.0,8.0,6.0,3.0,2.0,26.0,2.0
-CH,2192.0,6,3.0,5.0,6.0,4.0,10.0,5.0,3.0,1.0,63.0,1.0
-CH,2193.0,6,6.0,3.0,4.0,4.0,9.0,7.0,2.0,2.0,21.0,2.0
-CH,2196.0,6,2.0,7.0,8.0,8.0,8.0,4.0,2.0,1.0,59.0,1.0
-CH,2197.0,6,0.0,8.0,8.0,5.0,8.0,6.0,3.0,2.0,63.0,1.0
-CH,2201.0,6,3.0,8.0,8.0,8.0,8.0,5.0,3.0,1.0,59.0,1.0
-CH,2203.0,6,5.0,7.0,5.0,7.0,8.0,5.0,2.0,1.0,57.0,2.0
-CH,2205.0,6,1.0,8.0,10.0,8.0,10.0,5.0,3.0,1.0,46.0,1.0
-CH,2209.0,6,0.0,7.0,8.0,7.0,7.0,5.0,2.0,2.0,50.0,2.0
-CH,2211.0,6,2.0,7.0,6.0,5.0,10.0,6.0,2.0,2.0,36.0,1.0
-CH,2217.0,6,4.0,10.0,10.0,9.0,10.0,5.0,2.0,2.0,41.0,1.0
-CH,2221.0,6,7.0,7.0,7.0,8.0,8.0,4.0,2.0,2.0,75.0,1.0
-CH,2228.0,6,3.0,6.0,8.0,7.0,7.0,6.0,3.0,1.0,22.0,2.0
-CH,2229.0,6,0.0,7.0,7.0,4.0,8.0,6.0,3.0,2.0,45.0,2.0
-CH,2236.0,6,4.0,3.0,3.0,4.0,7.0,6.0,2.0,2.0,37.0,1.0
-CH,2237.0,6,2.0,10.0,10.0,9.0,10.0,4.0,3.0,2.0,79.0,1.0
-CH,2239.0,6,3.0,7.0,7.0,6.0,9.0,4.0,3.0,1.0,47.0,1.0
-CH,2241.0,6,2.0,6.0,4.0,3.0,10.0,6.0,4.0,1.0,48.0,1.0
-CH,2243.0,6,4.0,5.0,7.0,4.0,9.0,6.0,2.0,1.0,55.0,1.0
-CH,2244.0,6,7.0,2.0,5.0,7.0,5.0,1.0,1.0,2.0,,2.0
-CH,2247.0,6,3.0,3.0,3.0,5.0,8.0,6.0,3.0,1.0,23.0,2.0
-CH,2248.0,6,3.0,5.0,8.0,2.0,10.0,2.0,3.0,1.0,59.0,1.0
-CH,2249.0,6,1.0,6.0,7.0,4.0,7.0,6.0,4.0,1.0,30.0,2.0
-CH,2251.0,6,3.0,6.0,7.0,5.0,7.0,6.0,3.0,1.0,36.0,1.0
-CH,2256.0,6,3.0,7.0,7.0,5.0,8.0,5.0,3.0,2.0,47.0,1.0
-CH,2257.0,6,3.0,8.0,6.0,5.0,7.0,6.0,2.0,2.0,40.0,1.0
-CH,2262.0,6,5.0,7.0,7.0,4.0,8.0,6.0,4.0,1.0,33.0,1.0
-CH,2265.0,6,1.0,7.0,4.0,8.0,7.0,6.0,3.0,1.0,21.0,2.0
-CH,2267.0,6,1.0,7.0,9.0,5.0,8.0,6.0,2.0,2.0,53.0,2.0
-CH,2270.0,6,5.0,6.0,4.0,6.0,6.0,6.0,2.0,1.0,44.0,2.0
-CH,2272.0,6,0.0,8.0,7.0,5.0,5.0,3.0,1.0,1.0,64.0,1.0
-CH,2273.0,6,1.0,7.0,7.0,5.0,8.0,7.0,3.0,1.0,21.0,2.0
-CH,2284.0,6,3.0,7.0,7.0,7.0,9.0,7.0,3.0,1.0,23.0,2.0
-CH,2289.0,6,1.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,23.0,2.0
-CH,2290.0,6,7.0,7.0,7.0,7.0,8.0,4.0,3.0,1.0,71.0,1.0
-CH,2294.0,6,3.0,5.0,9.0,7.0,7.0,6.0,4.0,2.0,86.0,2.0
-CH,2295.0,6,6.0,7.0,5.0,5.0,5.0,5.0,2.0,2.0,60.0,1.0
-CH,2298.0,6,3.0,3.0,8.0,5.0,8.0,5.0,2.0,1.0,20.0,2.0
-CH,2315.0,6,4.0,7.0,8.0,3.0,3.0,5.0,3.0,1.0,32.0,1.0
-CH,2318.0,6,2.0,4.0,5.0,5.0,8.0,6.0,3.0,1.0,23.0,1.0
-CH,2319.0,6,2.0,9.0,8.0,8.0,9.0,6.0,4.0,1.0,18.0,2.0
-CH,2322.0,6,2.0,3.0,7.0,4.0,9.0,6.0,4.0,1.0,30.0,1.0
-CH,2326.0,6,2.0,6.0,5.0,5.0,7.0,6.0,3.0,2.0,17.0,2.0
-CH,2329.0,6,3.0,8.0,8.0,5.0,10.0,6.0,2.0,2.0,74.0,1.0
-CH,2330.0,6,6.0,7.0,5.0,4.0,8.0,4.0,3.0,2.0,71.0,2.0
-CH,2333.0,6,4.0,3.0,6.0,4.0,6.0,3.0,1.0,2.0,51.0,1.0
-CH,2334.0,6,2.0,4.0,4.0,5.0,8.0,6.0,3.0,2.0,37.0,1.0
-CH,2335.0,6,6.0,5.0,5.0,3.0,8.0,6.0,4.0,1.0,61.0,2.0
-CH,2338.0,6,2.0,5.0,8.0,8.0,7.0,6.0,,1.0,38.0,2.0
-CH,2343.0,6,3.0,8.0,3.0,2.0,9.0,4.0,3.0,1.0,79.0,1.0
-CH,2345.0,6,3.0,6.0,7.0,4.0,9.0,4.0,3.0,2.0,16.0,2.0
-CH,2346.0,6,4.0,5.0,7.0,7.0,8.0,7.0,3.0,2.0,27.0,2.0
-CH,2347.0,6,4.0,10.0,10.0,10.0,10.0,5.0,,1.0,43.0,1.0
-CH,2350.0,6,0.0,7.0,8.0,8.0,7.0,2.0,1.0,2.0,63.0,1.0
-CH,2352.0,6,0.0,7.0,8.0,5.0,8.0,6.0,4.0,2.0,28.0,1.0
-CH,2356.0,6,1.0,7.0,7.0,4.0,9.0,6.0,3.0,1.0,28.0,1.0
-CH,2358.0,6,3.0,8.0,10.0,7.0,10.0,7.0,4.0,2.0,60.0,1.0
-CH,2366.0,6,2.0,4.0,4.0,5.0,7.0,6.0,4.0,1.0,47.0,2.0
-CH,2376.0,6,2.0,8.0,7.0,7.0,7.0,4.0,3.0,2.0,45.0,1.0
-CH,2382.0,6,3.0,7.0,6.0,5.0,5.0,6.0,3.0,1.0,54.0,1.0
-CH,2383.0,6,6.0,7.0,8.0,5.0,9.0,3.0,2.0,1.0,76.0,1.0
-CH,2388.0,6,4.0,7.0,7.0,7.0,7.0,4.0,3.0,2.0,70.0,1.0
-CH,2392.0,6,4.0,5.0,6.0,6.0,7.0,6.0,3.0,1.0,53.0,1.0
-CH,2397.0,6,2.0,5.0,5.0,5.0,,4.0,1.0,1.0,48.0,2.0
-CH,2403.0,6,7.0,5.0,5.0,5.0,8.0,4.0,2.0,2.0,69.0,1.0
-CH,2419.0,6,0.0,2.0,4.0,4.0,8.0,4.0,4.0,2.0,94.0,2.0
-CH,2425.0,6,6.0,2.0,7.0,9.0,8.0,7.0,3.0,1.0,42.0,1.0
-CH,2427.0,6,4.0,8.0,8.0,6.0,9.0,7.0,2.0,2.0,36.0,1.0
-CH,2429.0,6,2.0,8.0,5.0,3.0,8.0,4.0,4.0,1.0,54.0,1.0
-CH,2430.0,6,1.0,2.0,8.0,3.0,8.0,6.0,3.0,2.0,42.0,1.0
-CH,2431.0,6,4.0,5.0,7.0,6.0,5.0,7.0,3.0,1.0,25.0,1.0
-CH,2433.0,6,3.0,5.0,5.0,7.0,8.0,6.0,2.0,2.0,20.0,1.0
-CH,2434.0,6,4.0,6.0,7.0,9.0,10.0,5.0,2.0,2.0,29.0,1.0
-CH,2435.0,6,2.0,2.0,3.0,0.0,8.0,6.0,2.0,1.0,30.0,2.0
-CH,2439.0,6,3.0,4.0,5.0,5.0,6.0,4.0,2.0,1.0,39.0,1.0
-CH,2448.0,6,2.0,5.0,0.0,5.0,2.0,3.0,2.0,2.0,84.0,2.0
-CH,2452.0,6,3.0,3.0,5.0,8.0,8.0,5.0,3.0,2.0,48.0,1.0
-CH,2454.0,6,4.0,8.0,8.0,6.0,9.0,5.0,1.0,2.0,30.0,1.0
-CH,2456.0,6,1.0,5.0,,7.0,5.0,5.0,4.0,2.0,20.0,2.0
-CH,2457.0,6,3.0,3.0,7.0,7.0,8.0,6.0,2.0,2.0,39.0,1.0
-CH,2459.0,6,2.0,8.0,8.0,4.0,10.0,3.0,1.0,1.0,51.0,1.0
-CH,2462.0,6,3.0,5.0,5.0,6.0,8.0,3.0,3.0,1.0,54.0,1.0
-CH,2464.0,6,3.0,8.0,8.0,8.0,10.0,4.0,3.0,2.0,24.0,1.0
-CH,2465.0,6,5.0,7.0,5.0,3.0,9.0,7.0,4.0,1.0,19.0,2.0
-CH,2466.0,6,2.0,6.0,7.0,7.0,9.0,6.0,3.0,2.0,37.0,1.0
-CH,2474.0,6,7.0,8.0,2.0,8.0,10.0,5.0,2.0,2.0,70.0,1.0
-CH,2477.0,6,2.0,2.0,4.0,4.0,5.0,3.0,3.0,2.0,41.0,1.0
-CH,2482.0,6,3.0,6.0,8.0,8.0,8.0,6.0,2.0,1.0,31.0,1.0
-CH,2485.0,6,3.0,3.0,7.0,5.0,6.0,6.0,2.0,1.0,49.0,1.0
-CH,2486.0,6,3.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,20.0,2.0
-CH,2487.0,6,1.0,6.0,3.0,8.0,6.0,4.0,4.0,1.0,52.0,1.0
-CH,2488.0,6,5.0,3.0,4.0,3.0,9.0,6.0,4.0,1.0,69.0,1.0
-CH,2489.0,6,1.0,5.0,3.0,5.0,7.0,4.0,2.0,2.0,54.0,2.0
-CH,2491.0,6,5.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,,1.0
-CH,2498.0,6,7.0,6.0,6.0,3.0,8.0,6.0,5.0,2.0,80.0,1.0
-CH,2500.0,6,1.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,34.0,2.0
-CH,2514.0,6,5.0,10.0,8.0,6.0,9.0,5.0,2.0,1.0,67.0,1.0
-CH,2515.0,6,4.0,0.0,7.0,5.0,10.0,7.0,4.0,2.0,59.0,1.0
-CH,2528.0,6,1.0,6.0,7.0,6.0,9.0,5.0,3.0,2.0,67.0,1.0
-CH,2539.0,6,4.0,7.0,5.0,8.0,8.0,4.0,4.0,1.0,53.0,2.0
-CH,2540.0,6,1.0,6.0,7.0,7.0,10.0,6.0,4.0,1.0,31.0,2.0
-CH,2545.0,6,2.0,4.0,8.0,3.0,10.0,5.0,1.0,1.0,30.0,1.0
-CH,2555.0,6,0.0,8.0,8.0,2.0,10.0,6.0,3.0,1.0,44.0,1.0
-CH,2557.0,6,2.0,7.0,5.0,4.0,9.0,6.0,3.0,1.0,22.0,2.0
-CH,2558.0,6,6.0,3.0,5.0,5.0,8.0,3.0,2.0,1.0,70.0,1.0
-CH,2560.0,6,4.0,6.0,7.0,6.0,6.0,5.0,2.0,1.0,25.0,2.0
-CH,2566.0,6,0.0,3.0,3.0,4.0,7.0,6.0,2.0,2.0,28.0,2.0
-CH,2567.0,6,3.0,2.0,5.0,2.0,6.0,4.0,2.0,2.0,29.0,1.0
-CH,2568.0,6,0.0,8.0,8.0,7.0,9.0,7.0,5.0,2.0,54.0,2.0
-CH,2569.0,6,2.0,9.0,6.0,5.0,8.0,5.0,3.0,1.0,46.0,1.0
-CH,2571.0,6,2.0,8.0,8.0,3.0,8.0,6.0,2.0,1.0,32.0,2.0
-CH,2573.0,6,3.0,8.0,10.0,9.0,9.0,5.0,3.0,1.0,59.0,1.0
-CH,2581.0,6,3.0,1.0,1.0,1.0,10.0,7.0,3.0,1.0,64.0,1.0
-CH,2582.0,6,1.0,3.0,6.0,4.0,7.0,5.0,3.0,2.0,20.0,2.0
-CH,2584.0,6,5.0,2.0,3.0,9.0,8.0,3.0,2.0,2.0,24.0,2.0
-CH,2589.0,6,4.0,5.0,5.0,5.0,9.0,6.0,5.0,2.0,48.0,1.0
-CH,2601.0,6,4.0,2.0,2.0,2.0,8.0,3.0,1.0,2.0,61.0,2.0
-CH,2620.0,6,7.0,5.0,5.0,5.0,6.0,6.0,4.0,1.0,71.0,1.0
-CH,2621.0,6,5.0,6.0,7.0,7.0,7.0,5.0,2.0,2.0,54.0,2.0
-CH,2625.0,6,2.0,6.0,9.0,5.0,8.0,7.0,3.0,2.0,16.0,2.0
-CH,2626.0,6,1.0,7.0,8.0,4.0,10.0,6.0,3.0,1.0,35.0,1.0
-CH,2627.0,6,5.0,5.0,8.0,8.0,8.0,4.0,3.0,1.0,58.0,1.0
-CH,2630.0,6,1.0,7.0,7.0,5.0,8.0,6.0,4.0,1.0,51.0,2.0
-CH,2631.0,6,6.0,5.0,8.0,5.0,6.0,6.0,2.0,1.0,69.0,1.0
-CH,2634.0,6,1.0,5.0,5.0,5.0,10.0,6.0,4.0,1.0,52.0,1.0
-CH,2639.0,6,2.0,7.0,7.0,8.0,8.0,4.0,2.0,2.0,44.0,1.0
-CH,2640.0,6,0.0,7.0,7.0,7.0,9.0,7.0,5.0,1.0,40.0,2.0
-CH,2642.0,6,6.0,8.0,8.0,5.0,8.0,7.0,2.0,1.0,57.0,1.0
-CH,2643.0,6,3.0,8.0,7.0,3.0,9.0,6.0,2.0,1.0,59.0,1.0
-CH,2644.0,6,2.0,8.0,4.0,6.0,9.0,4.0,4.0,2.0,49.0,1.0
-CH,2648.0,6,3.0,6.0,5.0,7.0,10.0,5.0,3.0,1.0,54.0,1.0
-CH,2651.0,6,1.0,7.0,10.0,10.0,10.0,7.0,4.0,2.0,57.0,1.0
-CH,2652.0,6,6.0,8.0,8.0,5.0,8.0,5.0,2.0,1.0,44.0,1.0
-CH,2666.0,6,2.0,5.0,5.0,4.0,9.0,6.0,1.0,1.0,80.0,2.0
-CH,2668.0,6,7.0,8.0,8.0,7.0,9.0,6.0,2.0,2.0,29.0,1.0
-CH,2670.0,6,5.0,5.0,5.0,5.0,8.0,5.0,3.0,2.0,72.0,2.0
-CH,2672.0,6,6.0,9.0,3.0,8.0,7.0,7.0,3.0,2.0,82.0,2.0
-CH,2674.0,6,4.0,5.0,4.0,3.0,10.0,5.0,4.0,1.0,62.0,1.0
-CH,2675.0,6,6.0,6.0,4.0,6.0,9.0,6.0,2.0,1.0,16.0,2.0
-CH,2676.0,6,3.0,4.0,7.0,6.0,5.0,6.0,2.0,2.0,55.0,2.0
-CH,2683.0,6,3.0,6.0,10.0,0.0,10.0,7.0,2.0,2.0,69.0,2.0
-CH,2684.0,6,2.0,8.0,7.0,5.0,9.0,7.0,3.0,2.0,22.0,2.0
-CH,2687.0,6,0.0,5.0,5.0,6.0,9.0,5.0,3.0,2.0,33.0,1.0
-CH,2689.0,6,2.0,7.0,5.0,6.0,6.0,5.0,3.0,2.0,83.0,2.0
-CH,2693.0,6,2.0,0.0,5.0,7.0,10.0,5.0,2.0,2.0,49.0,1.0
-CH,2699.0,6,5.0,7.0,3.0,7.0,9.0,6.0,2.0,1.0,44.0,1.0
-CH,2702.0,6,4.0,2.0,5.0,7.0,9.0,3.0,2.0,2.0,19.0,2.0
-CH,2711.0,6,3.0,5.0,5.0,5.0,10.0,6.0,3.0,1.0,81.0,1.0
-CH,2713.0,6,1.0,7.0,8.0,5.0,10.0,4.0,4.0,1.0,57.0,1.0
-CH,2714.0,6,3.0,5.0,8.0,5.0,9.0,6.0,3.0,2.0,21.0,1.0
-CH,2716.0,6,5.0,8.0,8.0,7.0,6.0,6.0,3.0,1.0,32.0,2.0
-CH,2720.0,6,6.0,2.0,6.0,6.0,8.0,4.0,3.0,2.0,,2.0
-CH,2728.0,6,6.0,6.0,7.0,4.0,7.0,6.0,4.0,2.0,49.0,1.0
-CH,2729.0,6,1.0,7.0,9.0,9.0,8.0,6.0,3.0,2.0,16.0,2.0
-CH,2732.0,6,1.0,3.0,5.0,3.0,8.0,5.0,2.0,1.0,27.0,2.0
-CH,2738.0,6,2.0,6.0,7.0,4.0,7.0,5.0,3.0,2.0,51.0,1.0
-CH,2741.0,6,7.0,8.0,9.0,6.0,10.0,5.0,,2.0,64.0,2.0
-CH,2745.0,6,3.0,7.0,6.0,7.0,8.0,4.0,3.0,2.0,35.0,1.0
-CH,2749.0,6,2.0,4.0,9.0,10.0,5.0,3.0,1.0,2.0,26.0,2.0
-CH,2752.0,6,1.0,8.0,8.0,9.0,9.0,6.0,4.0,1.0,53.0,1.0
-CH,2757.0,6,3.0,3.0,5.0,5.0,7.0,5.0,3.0,2.0,32.0,2.0
-CH,2765.0,6,2.0,6.0,5.0,5.0,9.0,4.0,2.0,1.0,60.0,1.0
-CH,2772.0,6,4.0,0.0,5.0,5.0,7.0,2.0,3.0,1.0,76.0,1.0
-CH,2773.0,6,2.0,6.0,5.0,7.0,6.0,6.0,4.0,1.0,85.0,1.0
-CH,2774.0,6,0.0,7.0,9.0,7.0,8.0,5.0,5.0,2.0,40.0,1.0
-CH,2775.0,6,7.0,3.0,5.0,1.0,5.0,1.0,1.0,1.0,50.0,1.0
-CH,2776.0,6,7.0,6.0,6.0,5.0,8.0,4.0,2.0,1.0,81.0,2.0
-CH,2777.0,6,4.0,7.0,7.0,4.0,8.0,6.0,4.0,1.0,24.0,1.0
-CH,2782.0,6,7.0,5.0,7.0,8.0,5.0,3.0,1.0,1.0,61.0,2.0
-CH,2784.0,6,1.0,7.0,8.0,9.0,9.0,4.0,1.0,2.0,37.0,1.0
-CH,2787.0,6,5.0,5.0,6.0,5.0,8.0,4.0,3.0,1.0,69.0,1.0
-CH,2788.0,6,2.0,5.0,5.0,6.0,8.0,5.0,2.0,1.0,,1.0
-CH,2793.0,6,3.0,6.0,6.0,5.0,8.0,4.0,3.0,1.0,42.0,1.0
-CH,2795.0,6,6.0,7.0,7.0,7.0,9.0,4.0,3.0,2.0,56.0,1.0
-CH,2797.0,6,3.0,5.0,8.0,7.0,8.0,4.0,3.0,2.0,70.0,1.0
-CH,2800.0,6,3.0,5.0,5.0,4.0,8.0,7.0,3.0,1.0,25.0,2.0
-CH,2803.0,6,4.0,5.0,10.0,0.0,10.0,4.0,2.0,2.0,26.0,1.0
-CH,2805.0,6,2.0,8.0,7.0,7.0,8.0,5.0,3.0,1.0,53.0,2.0
-CH,2806.0,6,6.0,8.0,5.0,8.0,10.0,2.0,2.0,1.0,52.0,1.0
-CH,2807.0,6,1.0,8.0,7.0,9.0,8.0,6.0,3.0,2.0,70.0,1.0
-CH,2809.0,6,4.0,7.0,7.0,6.0,8.0,4.0,,2.0,49.0,1.0
-CH,2811.0,6,7.0,10.0,10.0,5.0,7.0,5.0,1.0,1.0,74.0,1.0
-CH,2812.0,6,6.0,7.0,5.0,6.0,8.0,5.0,1.0,1.0,64.0,1.0
-CH,2813.0,6,6.0,3.0,2.0,1.0,8.0,6.0,4.0,1.0,63.0,2.0
-CH,2814.0,6,2.0,3.0,7.0,7.0,8.0,6.0,3.0,1.0,55.0,1.0
-CH,2817.0,6,3.0,7.0,5.0,5.0,8.0,6.0,4.0,1.0,19.0,2.0
-CH,2821.0,6,2.0,8.0,8.0,8.0,9.0,6.0,2.0,2.0,42.0,1.0
-CH,2826.0,6,0.0,5.0,5.0,2.0,5.0,6.0,3.0,2.0,45.0,1.0
-CH,2828.0,6,2.0,6.0,4.0,6.0,8.0,5.0,4.0,2.0,52.0,1.0
-CH,2835.0,6,3.0,5.0,5.0,5.0,9.0,5.0,3.0,2.0,35.0,1.0
-CH,2839.0,6,1.0,3.0,3.0,4.0,7.0,6.0,2.0,1.0,30.0,2.0
-CH,2842.0,6,5.0,8.0,8.0,7.0,8.0,4.0,3.0,1.0,68.0,1.0
-CH,2845.0,6,4.0,6.0,5.0,3.0,7.0,6.0,3.0,1.0,40.0,1.0
-CH,2847.0,6,5.0,6.0,6.0,5.0,8.0,6.0,4.0,2.0,72.0,2.0
-CH,2851.0,6,,5.0,5.0,5.0,7.0,4.0,4.0,1.0,52.0,1.0
-CH,2853.0,6,6.0,7.0,5.0,7.0,8.0,6.0,2.0,1.0,45.0,1.0
-CH,2855.0,6,5.0,5.0,9.0,7.0,10.0,3.0,2.0,2.0,22.0,2.0
-CH,2858.0,6,6.0,3.0,10.0,8.0,8.0,3.0,2.0,2.0,,1.0
-CH,2861.0,6,4.0,8.0,9.0,7.0,8.0,6.0,4.0,2.0,52.0,1.0
-CH,2872.0,6,3.0,6.0,3.0,4.0,9.0,6.0,2.0,1.0,29.0,1.0
-CH,2876.0,6,4.0,3.0,5.0,5.0,5.0,,2.0,2.0,60.0,1.0
-CH,2878.0,6,2.0,8.0,7.0,7.0,8.0,7.0,3.0,2.0,29.0,2.0
-CH,2879.0,6,3.0,1.0,3.0,2.0,9.0,4.0,3.0,1.0,44.0,1.0
-CH,2882.0,6,4.0,8.0,8.0,8.0,8.0,5.0,2.0,2.0,18.0,2.0
-CH,2884.0,6,5.0,0.0,7.0,7.0,8.0,4.0,2.0,2.0,73.0,2.0
-CH,2885.0,6,4.0,2.0,3.0,1.0,3.0,4.0,3.0,2.0,34.0,2.0
-CH,2888.0,6,2.0,7.0,8.0,7.0,8.0,6.0,4.0,2.0,69.0,1.0
-CH,2890.0,6,5.0,7.0,7.0,5.0,8.0,4.0,2.0,1.0,75.0,1.0
-CH,2893.0,6,5.0,7.0,7.0,8.0,10.0,3.0,3.0,1.0,,1.0
-CH,2894.0,6,3.0,5.0,7.0,5.0,9.0,6.0,4.0,1.0,24.0,1.0
-CH,2900.0,6,4.0,7.0,7.0,6.0,10.0,2.0,2.0,2.0,59.0,1.0
-CH,2905.0,6,7.0,5.0,4.0,7.0,7.0,6.0,3.0,2.0,67.0,1.0
-CH,5.0,7,2.0,8.0,9.0,7.0,9.0,6.0,4.0,1.0,69.0,1.0
-CH,25.0,7,4.0,4.0,2.0,5.0,6.0,5.0,3.0,1.0,30.0,1.0
-CH,26.0,7,3.0,8.0,8.0,6.0,8.0,7.0,5.0,2.0,49.0,2.0
-CH,28.0,7,2.0,7.0,7.0,5.0,9.0,6.0,2.0,1.0,51.0,1.0
-CH,29.0,7,2.0,4.0,7.0,0.0,8.0,6.0,2.0,2.0,32.0,2.0
-CH,36.0,7,4.0,5.0,6.0,4.0,9.0,7.0,3.0,2.0,31.0,2.0
-CH,40.0,7,7.0,7.0,5.0,4.0,10.0,6.0,4.0,1.0,75.0,1.0
-CH,41.0,7,7.0,5.0,5.0,5.0,10.0,6.0,3.0,1.0,30.0,1.0
-CH,51.0,7,7.0,7.0,6.0,4.0,8.0,7.0,4.0,2.0,65.0,2.0
-CH,53.0,7,4.0,6.0,4.0,5.0,8.0,6.0,3.0,1.0,67.0,1.0
-CH,55.0,7,1.0,8.0,8.0,6.0,6.0,4.0,3.0,1.0,49.0,1.0
-CH,56.0,7,6.0,10.0,2.0,0.0,8.0,6.0,3.0,1.0,43.0,1.0
-CH,57.0,7,5.0,7.0,7.0,7.0,8.0,4.0,3.0,2.0,50.0,1.0
-CH,58.0,7,5.0,8.0,8.0,5.0,9.0,5.0,2.0,1.0,85.0,2.0
-CH,68.0,7,7.0,4.0,2.0,6.0,10.0,6.0,3.0,2.0,26.0,1.0
-CH,73.0,7,4.0,6.0,6.0,6.0,8.0,4.0,2.0,1.0,60.0,1.0
-CH,81.0,7,6.0,9.0,8.0,7.0,9.0,6.0,4.0,2.0,35.0,1.0
-CH,82.0,7,5.0,6.0,8.0,5.0,8.0,7.0,5.0,1.0,29.0,1.0
-CH,84.0,7,2.0,8.0,5.0,3.0,10.0,5.0,3.0,1.0,33.0,1.0
-CH,86.0,7,1.0,7.0,5.0,8.0,9.0,7.0,2.0,1.0,17.0,2.0
-CH,87.0,7,3.0,5.0,5.0,2.0,7.0,4.0,3.0,2.0,44.0,1.0
-CH,96.0,7,2.0,6.0,6.0,6.0,9.0,6.0,3.0,2.0,35.0,1.0
-CH,98.0,7,2.0,5.0,5.0,1.0,7.0,3.0,2.0,1.0,57.0,1.0
-CH,104.0,7,1.0,8.0,7.0,7.0,9.0,5.0,2.0,1.0,47.0,1.0
-CH,108.0,7,6.0,6.0,6.0,5.0,7.0,6.0,5.0,1.0,24.0,2.0
-CH,117.0,7,3.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,32.0,1.0
-CH,118.0,7,2.0,3.0,6.0,7.0,9.0,6.0,3.0,1.0,52.0,1.0
-CH,119.0,7,6.0,8.0,3.0,7.0,7.0,2.0,2.0,1.0,69.0,1.0
-CH,121.0,7,2.0,2.0,2.0,10.0,9.0,5.0,1.0,2.0,84.0,2.0
-CH,133.0,7,4.0,6.0,6.0,7.0,7.0,7.0,2.0,1.0,63.0,1.0
-CH,135.0,7,2.0,6.0,4.0,6.0,5.0,6.0,1.0,2.0,46.0,2.0
-CH,137.0,7,7.0,5.0,6.0,5.0,8.0,6.0,3.0,1.0,19.0,2.0
-CH,148.0,7,6.0,7.0,5.0,4.0,8.0,6.0,1.0,2.0,36.0,2.0
-CH,149.0,7,3.0,8.0,9.0,8.0,9.0,5.0,3.0,2.0,29.0,2.0
-CH,161.0,7,4.0,3.0,3.0,5.0,5.0,6.0,4.0,2.0,18.0,2.0
-CH,162.0,7,1.0,5.0,5.0,4.0,7.0,6.0,2.0,2.0,53.0,1.0
-CH,168.0,7,2.0,7.0,7.0,8.0,8.0,7.0,3.0,2.0,25.0,2.0
-CH,177.0,7,3.0,5.0,5.0,7.0,10.0,6.0,3.0,2.0,30.0,1.0
-CH,179.0,7,0.0,6.0,4.0,7.0,10.0,6.0,2.0,2.0,72.0,1.0
-CH,180.0,7,3.0,6.0,6.0,2.0,9.0,7.0,4.0,1.0,36.0,2.0
-CH,185.0,7,3.0,8.0,5.0,7.0,8.0,6.0,4.0,1.0,31.0,2.0
-CH,193.0,7,7.0,4.0,6.0,5.0,8.0,6.0,1.0,2.0,19.0,2.0
-CH,200.0,7,7.0,0.0,10.0,4.0,10.0,6.0,2.0,2.0,78.0,2.0
-CH,216.0,7,2.0,8.0,8.0,4.0,8.0,4.0,2.0,1.0,49.0,1.0
-CH,218.0,7,2.0,4.0,8.0,5.0,6.0,6.0,2.0,1.0,75.0,1.0
-CH,219.0,7,7.0,5.0,10.0,10.0,10.0,7.0,5.0,2.0,89.0,2.0
-CH,220.0,7,3.0,3.0,6.0,2.0,9.0,6.0,2.0,1.0,41.0,1.0
-CH,231.0,7,4.0,7.0,8.0,8.0,8.0,7.0,4.0,2.0,55.0,2.0
-CH,232.0,7,3.0,4.0,3.0,5.0,7.0,2.0,2.0,2.0,53.0,1.0
-CH,251.0,7,7.0,4.0,5.0,0.0,8.0,7.0,3.0,1.0,33.0,2.0
-CH,257.0,7,7.0,7.0,6.0,5.0,8.0,5.0,1.0,2.0,69.0,2.0
-CH,258.0,7,5.0,4.0,7.0,3.0,10.0,5.0,3.0,2.0,65.0,1.0
-CH,260.0,7,1.0,5.0,5.0,5.0,6.0,5.0,3.0,1.0,22.0,2.0
-CH,261.0,7,0.0,9.0,8.0,8.0,8.0,7.0,4.0,2.0,18.0,2.0
-CH,270.0,7,3.0,5.0,5.0,3.0,10.0,7.0,5.0,1.0,80.0,1.0
-CH,271.0,7,6.0,0.0,5.0,4.0,7.0,4.0,3.0,1.0,67.0,1.0
-CH,273.0,7,3.0,5.0,7.0,5.0,10.0,6.0,4.0,2.0,69.0,1.0
-CH,279.0,7,2.0,5.0,5.0,4.0,9.0,5.0,3.0,1.0,56.0,1.0
-CH,295.0,7,7.0,5.0,7.0,7.0,8.0,4.0,3.0,1.0,49.0,1.0
-CH,297.0,7,1.0,5.0,4.0,5.0,10.0,7.0,5.0,1.0,71.0,2.0
-CH,303.0,7,3.0,4.0,0.0,3.0,7.0,6.0,3.0,2.0,28.0,2.0
-CH,308.0,7,0.0,8.0,8.0,7.0,9.0,7.0,3.0,1.0,25.0,2.0
-CH,318.0,7,1.0,3.0,3.0,3.0,10.0,7.0,5.0,2.0,55.0,1.0
-CH,322.0,7,0.0,7.0,8.0,5.0,9.0,7.0,3.0,1.0,20.0,2.0
-CH,323.0,7,2.0,7.0,5.0,3.0,8.0,4.0,3.0,1.0,46.0,2.0
-CH,332.0,7,3.0,1.0,5.0,6.0,6.0,3.0,1.0,2.0,27.0,1.0
-CH,333.0,7,5.0,6.0,9.0,8.0,9.0,4.0,2.0,1.0,34.0,1.0
-CH,339.0,7,4.0,8.0,8.0,7.0,10.0,5.0,3.0,1.0,43.0,1.0
-CH,345.0,7,2.0,5.0,8.0,8.0,8.0,5.0,1.0,2.0,58.0,1.0
-CH,354.0,7,2.0,8.0,8.0,7.0,7.0,6.0,3.0,2.0,55.0,2.0
-CH,357.0,7,5.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,48.0,1.0
-CH,359.0,7,5.0,4.0,7.0,7.0,7.0,6.0,3.0,1.0,23.0,2.0
-CH,362.0,7,4.0,5.0,5.0,5.0,7.0,4.0,3.0,2.0,30.0,1.0
-CH,369.0,7,6.0,7.0,7.0,6.0,9.0,7.0,4.0,1.0,41.0,1.0
-CH,380.0,7,3.0,5.0,5.0,6.0,8.0,6.0,2.0,1.0,67.0,1.0
-CH,400.0,7,5.0,5.0,5.0,6.0,8.0,4.0,3.0,1.0,72.0,1.0
-CH,402.0,7,6.0,5.0,2.0,7.0,7.0,4.0,4.0,1.0,71.0,1.0
-CH,404.0,7,2.0,9.0,9.0,6.0,9.0,5.0,2.0,2.0,39.0,1.0
-CH,405.0,7,3.0,7.0,5.0,8.0,9.0,7.0,2.0,1.0,23.0,2.0
-CH,407.0,7,1.0,7.0,8.0,6.0,9.0,6.0,4.0,1.0,22.0,2.0
-CH,412.0,7,2.0,9.0,7.0,7.0,10.0,6.0,3.0,1.0,27.0,1.0
-CH,417.0,7,6.0,7.0,8.0,7.0,9.0,6.0,4.0,2.0,22.0,2.0
-CH,420.0,7,7.0,9.0,8.0,4.0,6.0,6.0,2.0,2.0,,2.0
-CH,422.0,7,2.0,5.0,7.0,5.0,9.0,7.0,3.0,1.0,56.0,1.0
-CH,425.0,7,2.0,6.0,4.0,6.0,10.0,7.0,2.0,1.0,65.0,1.0
-CH,427.0,7,4.0,6.0,6.0,3.0,8.0,6.0,3.0,2.0,53.0,1.0
-CH,430.0,7,4.0,3.0,5.0,2.0,9.0,7.0,3.0,1.0,25.0,2.0
-CH,434.0,7,1.0,5.0,2.0,4.0,10.0,6.0,3.0,1.0,18.0,2.0
-CH,441.0,7,3.0,4.0,5.0,4.0,7.0,6.0,4.0,1.0,16.0,2.0
-CH,443.0,7,1.0,1.0,3.0,4.0,8.0,4.0,1.0,1.0,54.0,1.0
-CH,444.0,7,2.0,3.0,7.0,3.0,4.0,6.0,3.0,2.0,54.0,2.0
-CH,447.0,7,3.0,6.0,8.0,6.0,10.0,6.0,4.0,2.0,59.0,1.0
-CH,448.0,7,3.0,4.0,8.0,7.0,9.0,7.0,4.0,2.0,54.0,1.0
-CH,456.0,7,1.0,7.0,7.0,7.0,8.0,4.0,2.0,1.0,48.0,1.0
-CH,457.0,7,3.0,5.0,4.0,4.0,8.0,6.0,3.0,2.0,56.0,1.0
-CH,459.0,7,4.0,8.0,8.0,6.0,8.0,3.0,3.0,1.0,40.0,1.0
-CH,461.0,7,7.0,1.0,0.0,0.0,5.0,6.0,3.0,2.0,75.0,1.0
-CH,471.0,7,5.0,8.0,7.0,7.0,9.0,7.0,1.0,2.0,63.0,2.0
-CH,476.0,7,2.0,4.0,7.0,5.0,7.0,5.0,1.0,1.0,51.0,2.0
-CH,481.0,7,7.0,5.0,0.0,5.0,5.0,7.0,2.0,2.0,36.0,2.0
-CH,491.0,7,5.0,10.0,8.0,5.0,10.0,6.0,1.0,1.0,39.0,1.0
-CH,494.0,7,4.0,5.0,7.0,5.0,8.0,5.0,2.0,1.0,58.0,1.0
-CH,496.0,7,0.0,7.0,8.0,8.0,9.0,7.0,1.0,2.0,29.0,2.0
-CH,497.0,7,2.0,8.0,8.0,5.0,10.0,6.0,4.0,1.0,75.0,1.0
-CH,498.0,7,5.0,6.0,7.0,4.0,8.0,7.0,2.0,1.0,83.0,2.0
-CH,501.0,7,5.0,5.0,7.0,5.0,10.0,3.0,3.0,2.0,53.0,1.0
-CH,502.0,7,2.0,6.0,4.0,5.0,10.0,7.0,5.0,2.0,22.0,2.0
-CH,503.0,7,2.0,5.0,7.0,8.0,8.0,6.0,4.0,2.0,51.0,2.0
-CH,504.0,7,4.0,6.0,8.0,7.0,7.0,5.0,2.0,1.0,64.0,1.0
-CH,506.0,7,7.0,3.0,3.0,5.0,7.0,4.0,2.0,2.0,65.0,1.0
-CH,508.0,7,3.0,2.0,1.0,4.0,9.0,6.0,2.0,2.0,20.0,2.0
-CH,509.0,7,3.0,5.0,5.0,3.0,10.0,4.0,3.0,1.0,32.0,1.0
-CH,512.0,7,2.0,5.0,7.0,6.0,8.0,4.0,4.0,2.0,51.0,1.0
-CH,516.0,7,0.0,7.0,6.0,4.0,5.0,7.0,1.0,2.0,60.0,1.0
-CH,520.0,7,5.0,4.0,5.0,3.0,6.0,7.0,3.0,2.0,23.0,2.0
-CH,522.0,7,3.0,7.0,2.0,7.0,9.0,3.0,3.0,1.0,53.0,2.0
-CH,524.0,7,5.0,6.0,6.0,7.0,7.0,6.0,4.0,2.0,71.0,2.0
-CH,526.0,7,7.0,7.0,7.0,6.0,9.0,5.0,2.0,1.0,42.0,1.0
-CH,539.0,7,4.0,5.0,4.0,5.0,7.0,7.0,3.0,1.0,19.0,2.0
-CH,546.0,7,3.0,6.0,8.0,5.0,8.0,4.0,5.0,1.0,73.0,1.0
-CH,551.0,7,5.0,5.0,6.0,6.0,8.0,4.0,1.0,2.0,61.0,2.0
-CH,563.0,7,4.0,8.0,7.0,5.0,8.0,4.0,3.0,1.0,47.0,1.0
-CH,568.0,7,3.0,8.0,8.0,4.0,9.0,4.0,3.0,2.0,35.0,1.0
-CH,569.0,7,5.0,3.0,5.0,3.0,6.0,3.0,2.0,2.0,39.0,1.0
-CH,570.0,7,2.0,7.0,6.0,5.0,10.0,6.0,3.0,2.0,18.0,2.0
-CH,575.0,7,6.0,7.0,7.0,4.0,8.0,7.0,4.0,2.0,50.0,2.0
-CH,576.0,7,0.0,10.0,10.0,0.0,10.0,1.0,3.0,1.0,19.0,2.0
-CH,578.0,7,2.0,7.0,7.0,6.0,8.0,5.0,2.0,1.0,36.0,2.0
-CH,581.0,7,5.0,7.0,9.0,6.0,10.0,6.0,3.0,2.0,30.0,1.0
-CH,586.0,7,6.0,7.0,3.0,7.0,7.0,6.0,4.0,1.0,39.0,1.0
-CH,587.0,7,4.0,5.0,5.0,7.0,8.0,6.0,2.0,2.0,52.0,2.0
-CH,590.0,7,2.0,6.0,7.0,3.0,8.0,4.0,2.0,2.0,37.0,1.0
-CH,597.0,7,7.0,7.0,5.0,2.0,7.0,6.0,5.0,1.0,68.0,1.0
-CH,600.0,7,1.0,5.0,7.0,6.0,9.0,7.0,4.0,2.0,34.0,1.0
-CH,605.0,7,1.0,7.0,6.0,8.0,10.0,7.0,3.0,2.0,49.0,1.0
-CH,606.0,7,3.0,5.0,6.0,5.0,7.0,4.0,4.0,1.0,56.0,1.0
-CH,607.0,7,3.0,7.0,9.0,8.0,9.0,6.0,2.0,1.0,67.0,1.0
-CH,609.0,7,3.0,3.0,7.0,3.0,8.0,5.0,5.0,1.0,44.0,1.0
-CH,610.0,7,4.0,5.0,6.0,5.0,8.0,6.0,3.0,2.0,16.0,2.0
-CH,613.0,7,4.0,6.0,7.0,5.0,10.0,5.0,3.0,1.0,32.0,1.0
-CH,618.0,7,1.0,6.0,6.0,6.0,9.0,4.0,5.0,1.0,18.0,2.0
-CH,625.0,7,5.0,0.0,0.0,3.0,9.0,6.0,2.0,1.0,33.0,2.0
-CH,630.0,7,7.0,8.0,7.0,7.0,8.0,5.0,3.0,2.0,39.0,2.0
-CH,633.0,7,3.0,4.0,8.0,8.0,9.0,5.0,3.0,2.0,78.0,1.0
-CH,637.0,7,7.0,1.0,1.0,1.0,10.0,5.0,3.0,1.0,56.0,2.0
-CH,643.0,7,0.0,8.0,7.0,8.0,8.0,5.0,3.0,2.0,37.0,2.0
-CH,646.0,7,3.0,5.0,6.0,5.0,6.0,4.0,2.0,2.0,39.0,1.0
-CH,648.0,7,0.0,7.0,7.0,8.0,8.0,5.0,3.0,1.0,34.0,2.0
-CH,655.0,7,1.0,8.0,6.0,6.0,9.0,6.0,3.0,2.0,21.0,2.0
-CH,658.0,7,1.0,3.0,5.0,5.0,9.0,5.0,2.0,1.0,19.0,2.0
-CH,660.0,7,0.0,5.0,8.0,5.0,8.0,7.0,3.0,1.0,27.0,2.0
-CH,663.0,7,3.0,5.0,8.0,6.0,9.0,6.0,3.0,2.0,31.0,1.0
-CH,666.0,7,2.0,0.0,0.0,8.0,4.0,5.0,3.0,2.0,34.0,1.0
-CH,675.0,7,6.0,8.0,5.0,3.0,8.0,6.0,3.0,1.0,35.0,2.0
-CH,676.0,7,5.0,8.0,4.0,7.0,9.0,5.0,3.0,1.0,79.0,1.0
-CH,680.0,7,6.0,4.0,6.0,3.0,9.0,6.0,3.0,1.0,21.0,2.0
-CH,684.0,7,2.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,39.0,1.0
-CH,685.0,7,1.0,7.0,7.0,6.0,10.0,6.0,2.0,1.0,18.0,2.0
-CH,686.0,7,7.0,5.0,5.0,5.0,9.0,5.0,3.0,1.0,44.0,1.0
-CH,690.0,7,5.0,5.0,8.0,7.0,7.0,6.0,3.0,2.0,32.0,1.0
-CH,692.0,7,7.0,5.0,7.0,5.0,8.0,5.0,4.0,2.0,59.0,1.0
-CH,693.0,7,3.0,7.0,7.0,4.0,9.0,6.0,3.0,2.0,39.0,1.0
-CH,696.0,7,7.0,5.0,5.0,7.0,8.0,5.0,1.0,1.0,,1.0
-CH,697.0,7,2.0,3.0,5.0,4.0,10.0,5.0,2.0,1.0,32.0,1.0
-CH,698.0,7,7.0,5.0,5.0,3.0,8.0,5.0,2.0,1.0,63.0,1.0
-CH,701.0,7,4.0,5.0,8.0,6.0,9.0,4.0,2.0,1.0,57.0,1.0
-CH,703.0,7,3.0,9.0,6.0,7.0,8.0,2.0,5.0,2.0,63.0,1.0
-CH,706.0,7,0.0,6.0,6.0,6.0,10.0,5.0,3.0,2.0,60.0,1.0
-CH,707.0,7,4.0,6.0,6.0,4.0,6.0,3.0,3.0,2.0,49.0,1.0
-CH,708.0,7,2.0,4.0,8.0,7.0,10.0,7.0,4.0,2.0,71.0,1.0
-CH,709.0,7,6.0,4.0,4.0,4.0,8.0,6.0,3.0,2.0,33.0,1.0
-CH,711.0,7,4.0,6.0,6.0,3.0,8.0,3.0,2.0,1.0,67.0,1.0
-CH,713.0,7,0.0,7.0,7.0,4.0,7.0,4.0,1.0,2.0,21.0,2.0
-CH,714.0,7,4.0,5.0,5.0,5.0,6.0,5.0,3.0,2.0,33.0,1.0
-CH,715.0,7,4.0,6.0,6.0,6.0,9.0,4.0,2.0,2.0,72.0,1.0
-CH,716.0,7,2.0,3.0,3.0,3.0,8.0,4.0,3.0,2.0,44.0,1.0
-CH,717.0,7,3.0,6.0,6.0,5.0,9.0,6.0,4.0,1.0,21.0,2.0
-CH,720.0,7,7.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,42.0,1.0
-CH,722.0,7,6.0,7.0,6.0,6.0,7.0,4.0,4.0,1.0,,1.0
-CH,724.0,7,0.0,4.0,4.0,4.0,8.0,4.0,3.0,1.0,17.0,2.0
-CH,728.0,7,3.0,5.0,6.0,6.0,8.0,4.0,3.0,2.0,28.0,1.0
-CH,729.0,7,5.0,7.0,7.0,6.0,8.0,7.0,3.0,2.0,60.0,1.0
-CH,730.0,7,5.0,5.0,5.0,5.0,8.0,6.0,3.0,2.0,72.0,2.0
-CH,733.0,7,2.0,5.0,3.0,3.0,9.0,3.0,3.0,1.0,59.0,1.0
-CH,739.0,7,2.0,8.0,8.0,5.0,10.0,6.0,3.0,1.0,35.0,1.0
-CH,740.0,7,3.0,7.0,8.0,7.0,7.0,4.0,3.0,1.0,46.0,1.0
-CH,741.0,7,2.0,8.0,7.0,7.0,8.0,6.0,3.0,1.0,38.0,2.0
-CH,743.0,7,0.0,9.0,9.0,6.0,9.0,4.0,2.0,1.0,,1.0
-CH,747.0,7,2.0,7.0,5.0,5.0,8.0,5.0,2.0,1.0,70.0,2.0
-CH,748.0,7,2.0,4.0,6.0,6.0,7.0,6.0,3.0,2.0,25.0,1.0
-CH,757.0,7,2.0,5.0,5.0,7.0,7.0,6.0,2.0,2.0,20.0,2.0
-CH,759.0,7,4.0,7.0,5.0,7.0,7.0,6.0,3.0,2.0,19.0,2.0
-CH,760.0,7,4.0,5.0,5.0,2.0,7.0,6.0,3.0,2.0,52.0,2.0
-CH,761.0,7,6.0,8.0,6.0,5.0,9.0,4.0,3.0,1.0,63.0,1.0
-CH,762.0,7,1.0,8.0,8.0,2.0,8.0,3.0,1.0,2.0,62.0,1.0
-CH,764.0,7,5.0,5.0,8.0,5.0,8.0,5.0,3.0,1.0,47.0,1.0
-CH,770.0,7,2.0,8.0,3.0,9.0,10.0,6.0,3.0,2.0,30.0,1.0
-CH,771.0,7,2.0,3.0,5.0,5.0,7.0,4.0,3.0,1.0,78.0,1.0
-CH,774.0,7,3.0,5.0,8.0,8.0,8.0,6.0,3.0,2.0,64.0,1.0
-CH,778.0,7,2.0,3.0,4.0,7.0,10.0,6.0,3.0,1.0,69.0,1.0
-CH,779.0,7,5.0,7.0,9.0,4.0,7.0,5.0,2.0,1.0,33.0,2.0
-CH,781.0,7,3.0,3.0,8.0,4.0,10.0,6.0,4.0,2.0,32.0,1.0
-CH,788.0,7,4.0,6.0,5.0,6.0,8.0,6.0,1.0,2.0,73.0,1.0
-CH,789.0,7,1.0,8.0,8.0,3.0,10.0,4.0,4.0,1.0,,1.0
-CH,790.0,7,2.0,7.0,7.0,6.0,8.0,5.0,3.0,1.0,49.0,1.0
-CH,793.0,7,5.0,4.0,8.0,8.0,7.0,4.0,3.0,2.0,45.0,1.0
-CH,796.0,7,7.0,5.0,7.0,3.0,5.0,5.0,2.0,2.0,50.0,2.0
-CH,797.0,7,3.0,5.0,5.0,6.0,7.0,2.0,2.0,2.0,64.0,2.0
-CH,800.0,7,3.0,6.0,6.0,7.0,7.0,5.0,3.0,2.0,45.0,1.0
-CH,801.0,7,1.0,8.0,5.0,4.0,10.0,3.0,2.0,1.0,62.0,1.0
-CH,803.0,7,2.0,8.0,7.0,5.0,8.0,7.0,2.0,1.0,55.0,2.0
-CH,809.0,7,2.0,7.0,7.0,8.0,5.0,4.0,2.0,2.0,56.0,2.0
-CH,810.0,7,1.0,4.0,2.0,6.0,9.0,6.0,3.0,2.0,28.0,1.0
-CH,814.0,7,2.0,5.0,5.0,8.0,9.0,5.0,2.0,1.0,38.0,1.0
-CH,817.0,7,0.0,5.0,4.0,4.0,8.0,5.0,2.0,1.0,35.0,2.0
-CH,819.0,7,1.0,6.0,7.0,4.0,9.0,4.0,3.0,1.0,43.0,1.0
-CH,821.0,7,3.0,5.0,8.0,9.0,8.0,4.0,3.0,1.0,89.0,2.0
-CH,822.0,7,1.0,5.0,7.0,4.0,9.0,6.0,2.0,2.0,55.0,1.0
-CH,824.0,7,3.0,7.0,2.0,10.0,10.0,6.0,3.0,1.0,19.0,2.0
-CH,827.0,7,3.0,5.0,5.0,7.0,9.0,5.0,3.0,1.0,74.0,1.0
-CH,834.0,7,1.0,8.0,8.0,7.0,8.0,6.0,3.0,1.0,48.0,1.0
-CH,838.0,7,5.0,2.0,3.0,3.0,8.0,4.0,2.0,1.0,49.0,1.0
-CH,842.0,7,1.0,2.0,8.0,5.0,6.0,6.0,1.0,1.0,41.0,2.0
-CH,844.0,7,2.0,1.0,5.0,4.0,9.0,4.0,1.0,2.0,21.0,2.0
-CH,847.0,7,3.0,6.0,5.0,10.0,8.0,5.0,3.0,2.0,82.0,2.0
-CH,850.0,7,0.0,6.0,8.0,8.0,9.0,6.0,3.0,2.0,35.0,1.0
-CH,852.0,7,5.0,10.0,5.0,3.0,10.0,7.0,5.0,1.0,42.0,1.0
-CH,857.0,7,4.0,5.0,7.0,7.0,10.0,7.0,3.0,1.0,18.0,2.0
-CH,858.0,7,1.0,6.0,7.0,3.0,9.0,5.0,2.0,2.0,23.0,1.0
-CH,860.0,7,3.0,0.0,0.0,3.0,9.0,5.0,4.0,2.0,43.0,1.0
-CH,861.0,7,2.0,0.0,10.0,5.0,10.0,4.0,3.0,2.0,70.0,1.0
-CH,862.0,7,1.0,7.0,8.0,5.0,9.0,4.0,3.0,1.0,76.0,2.0
-CH,875.0,7,0.0,5.0,8.0,7.0,8.0,6.0,2.0,2.0,38.0,1.0
-CH,877.0,7,0.0,8.0,6.0,6.0,9.0,6.0,3.0,1.0,31.0,1.0
-CH,880.0,7,2.0,5.0,8.0,8.0,9.0,6.0,3.0,2.0,62.0,1.0
-CH,881.0,7,1.0,3.0,7.0,7.0,9.0,6.0,3.0,2.0,31.0,1.0
-CH,883.0,7,3.0,7.0,9.0,7.0,9.0,6.0,4.0,2.0,36.0,1.0
-CH,893.0,7,3.0,4.0,8.0,5.0,8.0,4.0,3.0,2.0,56.0,1.0
-CH,898.0,7,5.0,8.0,8.0,6.0,5.0,4.0,2.0,1.0,39.0,2.0
-CH,900.0,7,4.0,5.0,7.0,8.0,9.0,4.0,2.0,2.0,65.0,1.0
-CH,903.0,7,1.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,46.0,2.0
-CH,908.0,7,2.0,6.0,7.0,8.0,8.0,5.0,2.0,2.0,18.0,2.0
-CH,910.0,7,0.0,7.0,8.0,7.0,8.0,6.0,3.0,2.0,51.0,1.0
-CH,911.0,7,7.0,2.0,8.0,7.0,8.0,5.0,3.0,2.0,79.0,2.0
-CH,912.0,7,6.0,6.0,6.0,7.0,7.0,6.0,3.0,1.0,45.0,2.0
-CH,920.0,7,5.0,7.0,3.0,8.0,8.0,6.0,2.0,1.0,35.0,2.0
-CH,921.0,7,2.0,8.0,8.0,7.0,9.0,4.0,2.0,1.0,55.0,1.0
-CH,923.0,7,5.0,7.0,6.0,5.0,9.0,7.0,3.0,1.0,51.0,1.0
-CH,924.0,7,0.0,2.0,5.0,3.0,9.0,5.0,4.0,1.0,35.0,2.0
-CH,927.0,7,5.0,5.0,7.0,3.0,7.0,4.0,4.0,1.0,53.0,1.0
-CH,931.0,7,3.0,9.0,9.0,6.0,10.0,6.0,3.0,2.0,60.0,1.0
-CH,934.0,7,4.0,10.0,8.0,8.0,9.0,6.0,3.0,1.0,22.0,2.0
-CH,937.0,7,3.0,5.0,6.0,6.0,10.0,7.0,3.0,2.0,31.0,1.0
-CH,939.0,7,6.0,7.0,8.0,6.0,7.0,5.0,2.0,1.0,35.0,1.0
-CH,941.0,7,5.0,8.0,9.0,6.0,9.0,6.0,4.0,1.0,72.0,1.0
-CH,944.0,7,2.0,5.0,8.0,8.0,10.0,6.0,3.0,2.0,71.0,2.0
-CH,947.0,7,6.0,5.0,8.0,8.0,9.0,4.0,2.0,1.0,75.0,1.0
-CH,951.0,7,2.0,8.0,8.0,7.0,7.0,4.0,3.0,2.0,60.0,1.0
-CH,953.0,7,4.0,5.0,5.0,3.0,10.0,4.0,2.0,1.0,70.0,1.0
-CH,955.0,7,7.0,8.0,7.0,5.0,9.0,4.0,4.0,1.0,75.0,1.0
-CH,961.0,7,3.0,7.0,8.0,5.0,8.0,3.0,3.0,1.0,48.0,1.0
-CH,962.0,7,4.0,2.0,5.0,8.0,8.0,4.0,2.0,1.0,62.0,1.0
-CH,963.0,7,4.0,7.0,5.0,7.0,9.0,4.0,3.0,1.0,44.0,1.0
-CH,966.0,7,0.0,4.0,4.0,5.0,5.0,3.0,1.0,1.0,44.0,1.0
-CH,967.0,7,2.0,8.0,8.0,5.0,10.0,4.0,3.0,2.0,37.0,2.0
-CH,976.0,7,2.0,7.0,7.0,6.0,9.0,4.0,3.0,2.0,45.0,1.0
-CH,979.0,7,7.0,10.0,10.0,10.0,5.0,6.0,3.0,2.0,65.0,2.0
-CH,980.0,7,0.0,8.0,7.0,6.0,8.0,6.0,2.0,2.0,48.0,1.0
-CH,987.0,7,3.0,8.0,8.0,8.0,8.0,6.0,2.0,2.0,38.0,1.0
-CH,990.0,7,5.0,2.0,1.0,2.0,4.0,3.0,4.0,2.0,82.0,1.0
-CH,1001.0,7,3.0,7.0,7.0,7.0,9.0,6.0,3.0,2.0,53.0,1.0
-CH,1004.0,7,0.0,10.0,7.0,3.0,10.0,5.0,2.0,2.0,61.0,1.0
-CH,1009.0,7,2.0,8.0,9.0,10.0,10.0,7.0,3.0,2.0,29.0,1.0
-CH,1016.0,7,0.0,6.0,8.0,8.0,10.0,3.0,2.0,2.0,75.0,1.0
-CH,1017.0,7,0.0,5.0,6.0,7.0,7.0,5.0,3.0,2.0,38.0,1.0
-CH,1027.0,7,3.0,5.0,8.0,5.0,8.0,4.0,3.0,2.0,62.0,1.0
-CH,1029.0,7,3.0,6.0,7.0,7.0,9.0,6.0,3.0,1.0,16.0,2.0
-CH,1031.0,7,1.0,2.0,4.0,4.0,5.0,6.0,1.0,2.0,27.0,2.0
-CH,1033.0,7,0.0,7.0,5.0,6.0,8.0,4.0,3.0,2.0,51.0,1.0
-CH,1035.0,7,2.0,9.0,3.0,5.0,7.0,7.0,3.0,1.0,59.0,1.0
-CH,1036.0,7,3.0,5.0,4.0,3.0,4.0,2.0,2.0,1.0,49.0,1.0
-CH,1037.0,7,3.0,7.0,7.0,5.0,10.0,6.0,2.0,1.0,41.0,1.0
-CH,1041.0,7,7.0,5.0,6.0,7.0,6.0,4.0,2.0,1.0,,2.0
-CH,1043.0,7,3.0,6.0,6.0,5.0,8.0,4.0,2.0,1.0,48.0,1.0
-CH,1044.0,7,1.0,7.0,6.0,7.0,8.0,6.0,2.0,1.0,22.0,1.0
-CH,1046.0,7,6.0,8.0,7.0,6.0,9.0,2.0,2.0,1.0,68.0,1.0
-CH,1049.0,7,6.0,8.0,7.0,9.0,8.0,6.0,4.0,1.0,67.0,1.0
-CH,1050.0,7,3.0,5.0,4.0,4.0,7.0,5.0,3.0,1.0,57.0,1.0
-CH,1051.0,7,4.0,5.0,6.0,3.0,8.0,4.0,2.0,1.0,40.0,1.0
-CH,1052.0,7,3.0,5.0,3.0,3.0,7.0,6.0,5.0,2.0,,2.0
-CH,1060.0,7,4.0,8.0,7.0,5.0,8.0,6.0,3.0,2.0,39.0,1.0
-CH,1061.0,7,7.0,4.0,8.0,9.0,8.0,5.0,1.0,2.0,84.0,1.0
-CH,1062.0,7,3.0,5.0,8.0,6.0,8.0,6.0,4.0,1.0,,1.0
-CH,1063.0,7,7.0,2.0,4.0,7.0,9.0,6.0,3.0,1.0,21.0,2.0
-CH,1066.0,7,1.0,7.0,6.0,5.0,8.0,6.0,3.0,1.0,39.0,2.0
-CH,1067.0,7,0.0,6.0,8.0,8.0,8.0,6.0,3.0,2.0,55.0,1.0
-CH,1072.0,7,0.0,7.0,9.0,7.0,9.0,4.0,4.0,2.0,50.0,2.0
-CH,1076.0,7,5.0,6.0,6.0,8.0,7.0,4.0,3.0,1.0,54.0,1.0
-CH,1083.0,7,2.0,5.0,5.0,5.0,8.0,4.0,2.0,2.0,38.0,1.0
-CH,1086.0,7,1.0,9.0,9.0,6.0,8.0,7.0,4.0,2.0,61.0,1.0
-CH,1088.0,7,4.0,4.0,3.0,4.0,5.0,4.0,4.0,1.0,39.0,1.0
-CH,1090.0,7,2.0,8.0,8.0,7.0,8.0,7.0,3.0,1.0,34.0,2.0
-CH,1096.0,7,2.0,8.0,7.0,6.0,8.0,6.0,2.0,1.0,17.0,2.0
-CH,1106.0,7,5.0,7.0,7.0,8.0,6.0,4.0,3.0,2.0,43.0,1.0
-CH,1107.0,7,2.0,3.0,5.0,3.0,7.0,4.0,2.0,1.0,27.0,2.0
-CH,1112.0,7,5.0,0.0,10.0,7.0,9.0,5.0,3.0,2.0,,2.0
-CH,1117.0,7,4.0,9.0,6.0,6.0,8.0,6.0,4.0,1.0,70.0,1.0
-CH,1118.0,7,7.0,4.0,7.0,4.0,9.0,5.0,4.0,1.0,69.0,1.0
-CH,1127.0,7,1.0,6.0,8.0,5.0,9.0,6.0,3.0,1.0,25.0,2.0
-CH,1133.0,7,2.0,5.0,9.0,6.0,9.0,3.0,2.0,2.0,17.0,2.0
-CH,1134.0,7,6.0,7.0,7.0,5.0,10.0,6.0,2.0,2.0,64.0,2.0
-CH,1135.0,7,4.0,6.0,6.0,5.0,8.0,6.0,3.0,2.0,41.0,1.0
-CH,1137.0,7,2.0,7.0,7.0,5.0,8.0,6.0,5.0,1.0,79.0,2.0
-CH,1138.0,7,1.0,8.0,8.0,8.0,9.0,7.0,4.0,1.0,60.0,1.0
-CH,1141.0,7,3.0,5.0,7.0,6.0,9.0,3.0,2.0,2.0,57.0,1.0
-CH,1144.0,7,4.0,5.0,7.0,7.0,9.0,3.0,5.0,2.0,56.0,1.0
-CH,1148.0,7,3.0,8.0,8.0,8.0,9.0,5.0,4.0,1.0,49.0,1.0
-CH,1152.0,7,1.0,5.0,7.0,7.0,9.0,6.0,4.0,2.0,20.0,2.0
-CH,1154.0,7,2.0,10.0,10.0,10.0,9.0,4.0,3.0,2.0,68.0,1.0
-CH,1159.0,7,1.0,7.0,9.0,3.0,10.0,7.0,4.0,1.0,22.0,2.0
-CH,1164.0,7,7.0,6.0,6.0,1.0,9.0,6.0,4.0,1.0,68.0,1.0
-CH,1168.0,7,1.0,2.0,6.0,3.0,8.0,4.0,2.0,2.0,21.0,2.0
-CH,1173.0,7,3.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,16.0,2.0
-CH,1174.0,7,2.0,5.0,3.0,6.0,7.0,3.0,1.0,2.0,34.0,1.0
-CH,1182.0,7,1.0,4.0,7.0,5.0,8.0,6.0,4.0,2.0,17.0,2.0
-CH,1183.0,7,2.0,5.0,5.0,7.0,8.0,5.0,2.0,1.0,64.0,2.0
-CH,1188.0,7,1.0,7.0,8.0,8.0,10.0,7.0,5.0,2.0,68.0,2.0
-CH,1189.0,7,1.0,6.0,4.0,3.0,8.0,7.0,3.0,2.0,54.0,2.0
-CH,1194.0,7,1.0,7.0,4.0,5.0,9.0,6.0,3.0,1.0,43.0,1.0
-CH,1198.0,7,5.0,2.0,3.0,2.0,9.0,6.0,5.0,1.0,30.0,2.0
-CH,1201.0,7,7.0,6.0,7.0,7.0,6.0,4.0,2.0,1.0,78.0,1.0
-CH,1208.0,7,2.0,7.0,6.0,4.0,10.0,7.0,2.0,1.0,52.0,1.0
-CH,1209.0,7,5.0,6.0,7.0,7.0,8.0,4.0,3.0,2.0,18.0,2.0
-CH,1217.0,7,5.0,5.0,9.0,7.0,8.0,7.0,3.0,1.0,17.0,2.0
-CH,1222.0,7,3.0,5.0,8.0,2.0,8.0,6.0,4.0,2.0,39.0,1.0
-CH,1223.0,7,1.0,0.0,8.0,5.0,7.0,4.0,1.0,2.0,21.0,2.0
-CH,1229.0,7,4.0,3.0,5.0,3.0,6.0,2.0,1.0,2.0,50.0,2.0
-CH,1230.0,7,3.0,4.0,7.0,3.0,9.0,6.0,3.0,1.0,33.0,1.0
-CH,1233.0,7,4.0,1.0,1.0,2.0,10.0,4.0,2.0,2.0,41.0,1.0
-CH,1236.0,7,3.0,7.0,8.0,6.0,8.0,6.0,2.0,2.0,,2.0
-CH,1237.0,7,2.0,9.0,8.0,6.0,10.0,6.0,4.0,1.0,36.0,1.0
-CH,1240.0,7,1.0,7.0,8.0,8.0,9.0,2.0,1.0,1.0,31.0,1.0
-CH,1242.0,7,5.0,6.0,7.0,7.0,8.0,5.0,2.0,2.0,44.0,1.0
-CH,1245.0,7,6.0,2.0,3.0,3.0,6.0,6.0,3.0,1.0,,1.0
-CH,1247.0,7,2.0,4.0,7.0,4.0,7.0,5.0,2.0,1.0,23.0,2.0
-CH,1254.0,7,1.0,7.0,8.0,9.0,7.0,6.0,4.0,2.0,82.0,2.0
-CH,1264.0,7,1.0,7.0,8.0,9.0,9.0,6.0,2.0,2.0,23.0,2.0
-CH,1265.0,7,5.0,4.0,5.0,6.0,9.0,5.0,3.0,2.0,39.0,1.0
-CH,1266.0,7,3.0,7.0,6.0,6.0,9.0,3.0,2.0,1.0,,1.0
-CH,1269.0,7,3.0,6.0,8.0,7.0,9.0,6.0,5.0,2.0,47.0,2.0
-CH,1278.0,7,5.0,8.0,8.0,8.0,6.0,4.0,4.0,2.0,65.0,1.0
-CH,1282.0,7,0.0,5.0,8.0,5.0,7.0,5.0,3.0,1.0,69.0,2.0
-CH,1288.0,7,2.0,5.0,7.0,5.0,10.0,6.0,3.0,2.0,85.0,1.0
-CH,1290.0,7,0.0,7.0,8.0,7.0,8.0,6.0,3.0,2.0,25.0,2.0
-CH,1293.0,7,3.0,5.0,7.0,7.0,9.0,5.0,2.0,2.0,52.0,1.0
-CH,1303.0,7,2.0,4.0,6.0,4.0,9.0,6.0,4.0,1.0,24.0,2.0
-CH,1306.0,7,5.0,8.0,9.0,9.0,9.0,4.0,3.0,2.0,68.0,1.0
-CH,1310.0,7,2.0,7.0,8.0,4.0,8.0,6.0,1.0,2.0,31.0,2.0
-CH,1311.0,7,6.0,6.0,10.0,7.0,9.0,6.0,2.0,2.0,83.0,2.0
-CH,1312.0,7,3.0,3.0,5.0,5.0,6.0,6.0,3.0,1.0,40.0,1.0
-CH,1319.0,7,0.0,0.0,4.0,4.0,8.0,3.0,2.0,2.0,25.0,1.0
-CH,1322.0,7,1.0,5.0,4.0,6.0,6.0,4.0,2.0,1.0,16.0,2.0
-CH,1328.0,7,3.0,5.0,5.0,4.0,7.0,2.0,1.0,2.0,73.0,2.0
-CH,1333.0,7,2.0,5.0,5.0,4.0,9.0,7.0,3.0,2.0,48.0,1.0
-CH,1347.0,7,5.0,6.0,4.0,4.0,7.0,4.0,3.0,2.0,73.0,1.0
-CH,1349.0,7,3.0,5.0,8.0,5.0,8.0,6.0,4.0,2.0,52.0,1.0
-CH,1353.0,7,4.0,5.0,7.0,7.0,8.0,4.0,1.0,2.0,20.0,2.0
-CH,1356.0,7,2.0,9.0,9.0,7.0,8.0,4.0,2.0,2.0,18.0,2.0
-CH,1361.0,7,2.0,5.0,7.0,8.0,9.0,3.0,2.0,2.0,18.0,2.0
-CH,1362.0,7,5.0,8.0,10.0,6.0,8.0,4.0,4.0,1.0,89.0,1.0
-CH,1367.0,7,2.0,5.0,8.0,8.0,7.0,5.0,1.0,1.0,52.0,1.0
-CH,1369.0,7,6.0,9.0,8.0,7.0,8.0,5.0,3.0,2.0,27.0,2.0
-CH,1370.0,7,1.0,6.0,5.0,8.0,10.0,4.0,3.0,2.0,34.0,2.0
-CH,1371.0,7,2.0,9.0,0.0,9.0,8.0,5.0,1.0,2.0,70.0,1.0
-CH,1375.0,7,5.0,8.0,10.0,9.0,10.0,3.0,3.0,2.0,81.0,1.0
-CH,1378.0,7,4.0,3.0,6.0,8.0,8.0,5.0,3.0,2.0,49.0,1.0
-CH,1379.0,7,3.0,8.0,5.0,4.0,9.0,5.0,4.0,1.0,46.0,1.0
-CH,1382.0,7,3.0,5.0,6.0,4.0,8.0,6.0,4.0,2.0,33.0,1.0
-CH,1390.0,7,2.0,2.0,2.0,0.0,7.0,2.0,1.0,2.0,31.0,1.0
-CH,1402.0,7,0.0,9.0,8.0,5.0,10.0,6.0,2.0,2.0,34.0,1.0
-CH,1404.0,7,1.0,8.0,8.0,8.0,8.0,6.0,4.0,2.0,59.0,1.0
-CH,1405.0,7,3.0,5.0,6.0,4.0,9.0,5.0,1.0,2.0,63.0,1.0
-CH,1409.0,7,2.0,7.0,7.0,7.0,7.0,4.0,2.0,1.0,49.0,1.0
-CH,1410.0,7,3.0,5.0,6.0,6.0,6.0,6.0,3.0,2.0,36.0,1.0
-CH,1418.0,7,7.0,5.0,8.0,6.0,8.0,2.0,2.0,1.0,73.0,1.0
-CH,1431.0,7,2.0,5.0,5.0,7.0,10.0,6.0,3.0,2.0,42.0,1.0
-CH,1432.0,7,4.0,3.0,3.0,7.0,8.0,6.0,3.0,2.0,64.0,1.0
-CH,1436.0,7,3.0,3.0,7.0,0.0,9.0,6.0,4.0,1.0,25.0,2.0
-CH,1439.0,7,3.0,1.0,3.0,3.0,7.0,6.0,4.0,1.0,30.0,2.0
-CH,1447.0,7,5.0,9.0,6.0,7.0,9.0,5.0,2.0,1.0,28.0,2.0
-CH,1448.0,7,2.0,6.0,6.0,7.0,8.0,4.0,2.0,2.0,21.0,2.0
-CH,1449.0,7,3.0,5.0,3.0,5.0,4.0,5.0,1.0,1.0,42.0,1.0
-CH,1450.0,7,7.0,4.0,5.0,2.0,8.0,2.0,2.0,1.0,45.0,1.0
-CH,1451.0,7,4.0,5.0,7.0,7.0,9.0,7.0,3.0,2.0,23.0,2.0
-CH,1453.0,7,2.0,7.0,8.0,8.0,9.0,6.0,4.0,2.0,,1.0
-CH,1454.0,7,0.0,8.0,8.0,8.0,9.0,6.0,4.0,1.0,47.0,1.0
-CH,1457.0,7,3.0,4.0,2.0,5.0,7.0,3.0,2.0,1.0,86.0,1.0
-CH,1462.0,7,5.0,10.0,5.0,5.0,8.0,6.0,3.0,1.0,,1.0
-CH,1463.0,7,4.0,4.0,5.0,3.0,9.0,5.0,4.0,2.0,53.0,1.0
-CH,1468.0,7,2.0,7.0,8.0,9.0,10.0,6.0,3.0,2.0,18.0,2.0
-CH,1471.0,7,3.0,7.0,8.0,6.0,9.0,5.0,3.0,1.0,40.0,1.0
-CH,1477.0,7,5.0,5.0,1.0,10.0,8.0,2.0,2.0,2.0,51.0,1.0
-CH,1478.0,7,2.0,9.0,7.0,6.0,10.0,5.0,3.0,1.0,51.0,1.0
-CH,1484.0,7,3.0,7.0,7.0,8.0,10.0,4.0,3.0,1.0,84.0,1.0
-CH,1490.0,7,5.0,5.0,8.0,9.0,8.0,4.0,2.0,1.0,33.0,1.0
-CH,1495.0,7,3.0,6.0,8.0,7.0,6.0,4.0,3.0,1.0,55.0,1.0
-CH,1502.0,7,2.0,2.0,5.0,3.0,8.0,7.0,2.0,1.0,18.0,2.0
-CH,1504.0,7,0.0,0.0,8.0,5.0,8.0,6.0,3.0,2.0,40.0,1.0
-CH,1505.0,7,0.0,4.0,2.0,5.0,10.0,6.0,3.0,2.0,38.0,1.0
-CH,1507.0,7,2.0,5.0,7.0,4.0,10.0,6.0,3.0,2.0,70.0,1.0
-CH,1508.0,7,2.0,8.0,8.0,7.0,8.0,6.0,3.0,1.0,51.0,1.0
-CH,1510.0,7,3.0,5.0,7.0,5.0,8.0,5.0,2.0,2.0,36.0,1.0
-CH,1513.0,7,0.0,5.0,7.0,7.0,9.0,6.0,3.0,2.0,52.0,2.0
-CH,1527.0,7,2.0,6.0,4.0,3.0,9.0,7.0,4.0,1.0,36.0,1.0
-CH,1530.0,7,3.0,6.0,7.0,5.0,9.0,6.0,4.0,1.0,73.0,1.0
-CH,1535.0,7,3.0,5.0,5.0,5.0,10.0,4.0,4.0,1.0,46.0,1.0
-CH,1536.0,7,7.0,5.0,7.0,8.0,8.0,6.0,2.0,1.0,69.0,1.0
-CH,1542.0,7,2.0,4.0,8.0,8.0,7.0,6.0,4.0,1.0,48.0,1.0
-CH,1547.0,7,1.0,5.0,7.0,7.0,9.0,5.0,2.0,1.0,18.0,2.0
-CH,1553.0,7,2.0,7.0,5.0,4.0,9.0,6.0,3.0,2.0,19.0,2.0
-CH,1554.0,7,2.0,4.0,4.0,7.0,7.0,5.0,3.0,2.0,43.0,1.0
-CH,1562.0,7,0.0,5.0,8.0,7.0,7.0,5.0,2.0,1.0,55.0,1.0
-CH,1573.0,7,3.0,3.0,4.0,3.0,9.0,6.0,3.0,2.0,34.0,1.0
-CH,1577.0,7,5.0,5.0,5.0,8.0,8.0,7.0,3.0,2.0,53.0,2.0
-CH,1579.0,7,4.0,7.0,7.0,8.0,9.0,6.0,3.0,2.0,56.0,1.0
-CH,1583.0,7,1.0,4.0,6.0,4.0,10.0,6.0,3.0,1.0,17.0,2.0
-CH,1588.0,7,3.0,4.0,4.0,5.0,6.0,2.0,1.0,1.0,21.0,2.0
-CH,1594.0,7,2.0,7.0,4.0,4.0,9.0,6.0,2.0,2.0,18.0,2.0
-CH,1597.0,7,3.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,71.0,1.0
-CH,1600.0,7,5.0,7.0,5.0,7.0,8.0,3.0,2.0,1.0,62.0,2.0
-CH,1603.0,7,6.0,5.0,5.0,5.0,8.0,2.0,1.0,1.0,68.0,2.0
-CH,1604.0,7,3.0,7.0,6.0,6.0,9.0,4.0,2.0,2.0,42.0,1.0
-CH,1605.0,7,4.0,7.0,7.0,7.0,8.0,5.0,3.0,2.0,67.0,1.0
-CH,1615.0,7,3.0,2.0,0.0,2.0,8.0,4.0,4.0,1.0,43.0,1.0
-CH,1620.0,7,3.0,5.0,5.0,7.0,8.0,4.0,2.0,1.0,42.0,2.0
-CH,1624.0,7,0.0,6.0,8.0,5.0,8.0,5.0,2.0,2.0,54.0,1.0
-CH,1637.0,7,5.0,6.0,3.0,8.0,8.0,4.0,3.0,2.0,69.0,1.0
-CH,1638.0,7,2.0,5.0,8.0,6.0,10.0,7.0,5.0,2.0,16.0,2.0
-CH,1639.0,7,1.0,7.0,4.0,8.0,7.0,3.0,2.0,2.0,92.0,2.0
-CH,1643.0,7,4.0,5.0,6.0,7.0,8.0,5.0,3.0,2.0,16.0,2.0
-CH,1653.0,7,1.0,5.0,5.0,7.0,10.0,6.0,3.0,2.0,18.0,2.0
-CH,1654.0,7,4.0,7.0,7.0,6.0,8.0,4.0,3.0,2.0,51.0,1.0
-CH,1656.0,7,2.0,9.0,9.0,7.0,8.0,6.0,3.0,2.0,36.0,1.0
-CH,1657.0,7,2.0,8.0,8.0,7.0,10.0,4.0,2.0,2.0,54.0,2.0
-CH,1662.0,7,1.0,5.0,8.0,8.0,9.0,5.0,2.0,2.0,,1.0
-CH,1667.0,7,2.0,5.0,6.0,6.0,7.0,5.0,3.0,1.0,47.0,2.0
-CH,1668.0,7,2.0,8.0,7.0,8.0,7.0,6.0,4.0,2.0,20.0,2.0
-CH,1671.0,7,3.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,74.0,1.0
-CH,1683.0,7,4.0,8.0,8.0,8.0,8.0,5.0,3.0,1.0,28.0,1.0
-CH,1686.0,7,4.0,5.0,7.0,6.0,8.0,4.0,2.0,1.0,48.0,2.0
-CH,1689.0,7,0.0,4.0,5.0,8.0,9.0,7.0,2.0,2.0,16.0,2.0
-CH,1691.0,7,3.0,1.0,1.0,4.0,10.0,6.0,3.0,1.0,29.0,1.0
-CH,1693.0,7,7.0,5.0,4.0,9.0,10.0,2.0,1.0,2.0,31.0,1.0
-CH,1701.0,7,1.0,7.0,8.0,10.0,9.0,7.0,4.0,2.0,18.0,2.0
-CH,1707.0,7,2.0,9.0,9.0,7.0,8.0,6.0,3.0,2.0,41.0,1.0
-CH,1709.0,7,3.0,7.0,8.0,6.0,7.0,4.0,3.0,1.0,57.0,1.0
-CH,1718.0,7,2.0,0.0,0.0,0.0,10.0,6.0,2.0,2.0,53.0,1.0
-CH,1719.0,7,4.0,6.0,6.0,6.0,7.0,6.0,3.0,1.0,64.0,1.0
-CH,1720.0,7,4.0,3.0,5.0,4.0,8.0,5.0,2.0,1.0,19.0,2.0
-CH,1723.0,7,2.0,8.0,8.0,7.0,9.0,6.0,4.0,1.0,21.0,2.0
-CH,1726.0,7,5.0,3.0,5.0,5.0,8.0,6.0,3.0,2.0,48.0,1.0
-CH,1738.0,7,3.0,7.0,7.0,7.0,8.0,5.0,3.0,1.0,46.0,1.0
-CH,1743.0,7,4.0,3.0,4.0,5.0,9.0,7.0,4.0,1.0,43.0,1.0
-CH,1748.0,7,1.0,8.0,7.0,4.0,7.0,6.0,3.0,2.0,46.0,2.0
-CH,1750.0,7,4.0,4.0,7.0,7.0,8.0,6.0,2.0,1.0,72.0,2.0
-CH,1753.0,7,1.0,8.0,8.0,6.0,9.0,2.0,2.0,2.0,39.0,1.0
-CH,1755.0,7,4.0,6.0,7.0,8.0,8.0,3.0,3.0,1.0,71.0,1.0
-CH,1756.0,7,5.0,10.0,7.0,7.0,10.0,4.0,3.0,1.0,42.0,1.0
-CH,1757.0,7,4.0,4.0,3.0,7.0,10.0,4.0,2.0,2.0,63.0,1.0
-CH,1765.0,7,1.0,5.0,7.0,5.0,8.0,6.0,2.0,1.0,29.0,1.0
-CH,1766.0,7,2.0,3.0,4.0,6.0,4.0,3.0,2.0,2.0,41.0,1.0
-CH,1769.0,7,3.0,7.0,7.0,8.0,7.0,4.0,3.0,1.0,38.0,1.0
-CH,1776.0,7,2.0,3.0,9.0,3.0,7.0,4.0,2.0,2.0,58.0,1.0
-CH,1788.0,7,2.0,4.0,8.0,8.0,9.0,7.0,3.0,1.0,22.0,2.0
-CH,1790.0,7,3.0,7.0,6.0,8.0,7.0,6.0,4.0,2.0,20.0,2.0
-CH,1791.0,7,3.0,5.0,5.0,6.0,8.0,4.0,2.0,2.0,69.0,1.0
-CH,1792.0,7,2.0,9.0,9.0,9.0,9.0,4.0,3.0,1.0,49.0,1.0
-CH,1797.0,7,3.0,7.0,7.0,8.0,6.0,5.0,2.0,1.0,61.0,2.0
-CH,1801.0,7,5.0,0.0,9.0,0.0,8.0,1.0,1.0,2.0,,2.0
-CH,1802.0,7,3.0,4.0,5.0,3.0,7.0,6.0,3.0,2.0,47.0,2.0
-CH,1803.0,7,6.0,0.0,5.0,5.0,8.0,6.0,3.0,1.0,71.0,1.0
-CH,1805.0,7,0.0,8.0,7.0,3.0,9.0,5.0,3.0,1.0,34.0,2.0
-CH,1809.0,7,2.0,2.0,3.0,5.0,9.0,6.0,1.0,2.0,59.0,1.0
-CH,1815.0,7,2.0,7.0,7.0,5.0,7.0,7.0,3.0,2.0,21.0,2.0
-CH,1816.0,7,5.0,0.0,7.0,5.0,8.0,4.0,3.0,2.0,40.0,1.0
-CH,1817.0,7,3.0,7.0,6.0,3.0,5.0,2.0,2.0,1.0,81.0,1.0
-CH,1819.0,7,3.0,5.0,5.0,3.0,3.0,5.0,2.0,1.0,29.0,1.0
-CH,1829.0,7,3.0,0.0,5.0,2.0,7.0,4.0,2.0,1.0,52.0,1.0
-CH,1832.0,7,1.0,5.0,7.0,5.0,6.0,4.0,2.0,2.0,19.0,2.0
-CH,1844.0,7,0.0,4.0,7.0,6.0,8.0,6.0,3.0,2.0,23.0,2.0
-CH,1849.0,7,1.0,5.0,5.0,4.0,8.0,6.0,2.0,2.0,17.0,2.0
-CH,1850.0,7,7.0,3.0,3.0,3.0,8.0,5.0,3.0,2.0,53.0,2.0
-CH,1852.0,7,3.0,7.0,5.0,8.0,8.0,6.0,1.0,1.0,29.0,2.0
-CH,1854.0,7,3.0,4.0,5.0,5.0,8.0,6.0,3.0,1.0,21.0,2.0
-CH,1869.0,7,0.0,4.0,5.0,3.0,8.0,5.0,3.0,1.0,26.0,2.0
-CH,1877.0,7,7.0,4.0,5.0,5.0,8.0,6.0,4.0,2.0,56.0,1.0
-CH,1888.0,7,4.0,4.0,5.0,3.0,9.0,5.0,2.0,1.0,35.0,1.0
-CH,1897.0,7,3.0,7.0,7.0,7.0,8.0,4.0,3.0,1.0,45.0,2.0
-CH,1906.0,7,4.0,2.0,8.0,2.0,8.0,3.0,1.0,1.0,33.0,1.0
-CH,1914.0,7,2.0,5.0,3.0,3.0,7.0,7.0,4.0,1.0,68.0,2.0
-CH,1917.0,7,2.0,7.0,7.0,7.0,7.0,6.0,3.0,1.0,55.0,1.0
-CH,1921.0,7,4.0,4.0,3.0,3.0,5.0,6.0,3.0,2.0,38.0,2.0
-CH,1924.0,7,4.0,5.0,3.0,2.0,7.0,6.0,2.0,1.0,21.0,2.0
-CH,1929.0,7,2.0,6.0,5.0,6.0,9.0,7.0,4.0,2.0,17.0,2.0
-CH,1940.0,7,6.0,4.0,3.0,5.0,8.0,6.0,4.0,2.0,63.0,1.0
-CH,1941.0,7,2.0,8.0,5.0,4.0,5.0,,,2.0,45.0,1.0
-CH,1943.0,7,3.0,7.0,7.0,6.0,9.0,7.0,4.0,2.0,54.0,1.0
-CH,1955.0,7,4.0,7.0,5.0,5.0,10.0,6.0,3.0,1.0,37.0,1.0
-CH,1968.0,7,3.0,8.0,7.0,8.0,9.0,7.0,2.0,2.0,44.0,1.0
-CH,1969.0,7,0.0,9.0,8.0,4.0,10.0,6.0,1.0,2.0,49.0,2.0
-CH,1971.0,7,3.0,7.0,7.0,5.0,6.0,5.0,3.0,1.0,74.0,1.0
-CH,1978.0,7,2.0,6.0,8.0,3.0,9.0,7.0,3.0,2.0,25.0,1.0
-CH,1982.0,7,2.0,8.0,8.0,6.0,9.0,6.0,4.0,1.0,27.0,1.0
-CH,1991.0,7,4.0,6.0,7.0,8.0,10.0,7.0,3.0,2.0,82.0,2.0
-CH,1992.0,7,6.0,7.0,7.0,8.0,8.0,4.0,2.0,2.0,76.0,1.0
-CH,1998.0,7,3.0,5.0,5.0,5.0,9.0,5.0,3.0,1.0,16.0,2.0
-CH,2000.0,7,5.0,4.0,4.0,4.0,9.0,5.0,3.0,1.0,52.0,2.0
-CH,2004.0,7,6.0,6.0,7.0,6.0,8.0,4.0,2.0,1.0,42.0,1.0
-CH,2005.0,7,4.0,6.0,5.0,5.0,9.0,6.0,3.0,1.0,36.0,1.0
-CH,2007.0,7,5.0,2.0,8.0,7.0,5.0,5.0,3.0,1.0,40.0,1.0
-CH,2008.0,7,3.0,4.0,6.0,7.0,9.0,6.0,4.0,2.0,39.0,1.0
-CH,2011.0,7,4.0,5.0,5.0,5.0,8.0,3.0,2.0,2.0,21.0,2.0
-CH,2017.0,7,6.0,8.0,8.0,9.0,10.0,4.0,3.0,1.0,72.0,2.0
-CH,2020.0,7,0.0,8.0,8.0,8.0,10.0,7.0,3.0,1.0,43.0,1.0
-CH,2021.0,7,3.0,7.0,7.0,3.0,7.0,6.0,3.0,2.0,81.0,2.0
-CH,2027.0,7,1.0,9.0,8.0,8.0,7.0,6.0,3.0,2.0,54.0,1.0
-CH,2028.0,7,3.0,8.0,10.0,5.0,10.0,6.0,4.0,2.0,52.0,2.0
-CH,2036.0,7,0.0,10.0,8.0,8.0,7.0,6.0,2.0,1.0,39.0,1.0
-CH,2041.0,7,1.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,35.0,1.0
-CH,2049.0,7,2.0,0.0,3.0,3.0,9.0,7.0,2.0,2.0,48.0,1.0
-CH,2052.0,7,1.0,8.0,5.0,4.0,9.0,6.0,2.0,1.0,37.0,1.0
-CH,2060.0,7,0.0,8.0,8.0,5.0,9.0,6.0,3.0,2.0,36.0,2.0
-CH,2062.0,7,2.0,3.0,8.0,8.0,9.0,6.0,3.0,2.0,45.0,1.0
-CH,2063.0,7,2.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,36.0,1.0
-CH,2077.0,7,4.0,8.0,7.0,7.0,8.0,2.0,2.0,1.0,53.0,1.0
-CH,2078.0,7,6.0,4.0,4.0,4.0,7.0,5.0,1.0,1.0,28.0,2.0
-CH,2084.0,7,7.0,5.0,4.0,6.0,5.0,4.0,3.0,1.0,45.0,2.0
-CH,2090.0,7,2.0,5.0,6.0,6.0,8.0,6.0,3.0,1.0,52.0,1.0
-CH,2092.0,7,2.0,6.0,5.0,3.0,5.0,3.0,2.0,2.0,49.0,1.0
-CH,2095.0,7,2.0,7.0,7.0,6.0,9.0,7.0,3.0,2.0,17.0,2.0
-CH,2102.0,7,0.0,7.0,7.0,8.0,8.0,3.0,2.0,2.0,68.0,2.0
-CH,2106.0,7,3.0,4.0,3.0,5.0,8.0,6.0,4.0,2.0,32.0,1.0
-CH,2111.0,7,0.0,6.0,8.0,9.0,7.0,2.0,2.0,2.0,71.0,1.0
-CH,2112.0,7,3.0,7.0,8.0,7.0,9.0,6.0,1.0,1.0,20.0,2.0
-CH,2113.0,7,2.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,27.0,2.0
-CH,2115.0,7,2.0,5.0,5.0,5.0,8.0,4.0,2.0,1.0,44.0,2.0
-CH,2124.0,7,1.0,6.0,7.0,3.0,8.0,4.0,2.0,1.0,40.0,1.0
-CH,2128.0,7,5.0,9.0,8.0,5.0,10.0,7.0,3.0,1.0,60.0,1.0
-CH,2129.0,7,2.0,4.0,8.0,4.0,8.0,4.0,4.0,1.0,86.0,2.0
-CH,2131.0,7,6.0,8.0,8.0,9.0,5.0,2.0,2.0,2.0,70.0,2.0
-CH,2133.0,7,4.0,2.0,5.0,5.0,10.0,6.0,2.0,1.0,29.0,1.0
-CH,2135.0,7,3.0,2.0,8.0,3.0,7.0,5.0,3.0,1.0,,1.0
-CH,2154.0,7,5.0,9.0,8.0,9.0,10.0,3.0,2.0,2.0,84.0,1.0
-CH,2159.0,7,4.0,6.0,6.0,6.0,6.0,6.0,2.0,2.0,79.0,1.0
-CH,2160.0,7,4.0,8.0,8.0,5.0,9.0,6.0,3.0,2.0,36.0,1.0
-CH,2161.0,7,2.0,6.0,7.0,7.0,8.0,4.0,3.0,2.0,80.0,2.0
-CH,2167.0,7,2.0,5.0,6.0,7.0,6.0,3.0,2.0,2.0,78.0,1.0
-CH,2169.0,7,5.0,7.0,6.0,7.0,9.0,5.0,3.0,1.0,64.0,1.0
-CH,2180.0,7,5.0,5.0,7.0,5.0,6.0,3.0,3.0,1.0,56.0,1.0
-CH,2182.0,7,4.0,5.0,5.0,5.0,5.0,5.0,3.0,2.0,52.0,2.0
-CH,2183.0,7,1.0,5.0,10.0,6.0,9.0,5.0,3.0,1.0,53.0,1.0
-CH,2190.0,7,0.0,4.0,7.0,4.0,10.0,7.0,3.0,2.0,27.0,2.0
-CH,2192.0,7,0.0,8.0,7.0,8.0,8.0,6.0,3.0,2.0,34.0,1.0
-CH,2193.0,7,4.0,7.0,7.0,6.0,8.0,5.0,2.0,2.0,36.0,1.0
-CH,2196.0,7,4.0,5.0,8.0,4.0,3.0,5.0,1.0,2.0,53.0,1.0
-CH,2197.0,7,1.0,5.0,7.0,7.0,9.0,6.0,4.0,2.0,50.0,1.0
-CH,2201.0,7,0.0,8.0,8.0,9.0,9.0,6.0,2.0,2.0,42.0,1.0
-CH,2203.0,7,6.0,2.0,7.0,8.0,6.0,2.0,1.0,2.0,84.0,2.0
-CH,2205.0,7,2.0,4.0,7.0,7.0,9.0,5.0,2.0,2.0,41.0,2.0
-CH,2209.0,7,3.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,57.0,1.0
-CH,2211.0,7,2.0,5.0,9.0,5.0,7.0,6.0,2.0,2.0,46.0,1.0
-CH,2217.0,7,2.0,0.0,0.0,0.0,6.0,6.0,3.0,1.0,21.0,2.0
-CH,2221.0,7,2.0,9.0,8.0,6.0,8.0,7.0,4.0,1.0,42.0,1.0
-CH,2228.0,7,2.0,6.0,5.0,7.0,4.0,4.0,2.0,1.0,35.0,2.0
-CH,2229.0,7,6.0,4.0,5.0,4.0,8.0,3.0,2.0,1.0,68.0,1.0
-CH,2236.0,7,1.0,6.0,4.0,7.0,9.0,4.0,2.0,1.0,38.0,1.0
-CH,2237.0,7,5.0,5.0,8.0,9.0,9.0,5.0,3.0,1.0,18.0,2.0
-CH,2239.0,7,3.0,5.0,7.0,4.0,9.0,5.0,4.0,1.0,42.0,1.0
-CH,2241.0,7,3.0,7.0,6.0,8.0,8.0,6.0,2.0,2.0,35.0,1.0
-CH,2243.0,7,4.0,5.0,6.0,8.0,8.0,4.0,2.0,2.0,19.0,2.0
-CH,2244.0,7,2.0,4.0,3.0,4.0,9.0,6.0,2.0,2.0,23.0,1.0
-CH,2247.0,7,5.0,4.0,6.0,3.0,9.0,7.0,3.0,1.0,27.0,2.0
-CH,2248.0,7,2.0,0.0,5.0,9.0,7.0,6.0,4.0,1.0,45.0,1.0
-CH,2249.0,7,4.0,7.0,8.0,9.0,9.0,6.0,2.0,2.0,63.0,1.0
-CH,2251.0,7,2.0,7.0,3.0,5.0,9.0,7.0,4.0,1.0,17.0,2.0
-CH,2256.0,7,7.0,7.0,8.0,5.0,7.0,2.0,1.0,1.0,82.0,2.0
-CH,2257.0,7,4.0,0.0,2.0,6.0,7.0,6.0,2.0,2.0,63.0,2.0
-CH,2262.0,7,2.0,6.0,6.0,7.0,9.0,6.0,3.0,1.0,23.0,2.0
-CH,2265.0,7,3.0,5.0,9.0,5.0,7.0,6.0,3.0,2.0,49.0,1.0
-CH,2267.0,7,5.0,3.0,3.0,5.0,8.0,4.0,3.0,1.0,46.0,1.0
-CH,2270.0,7,5.0,3.0,5.0,5.0,7.0,4.0,3.0,1.0,52.0,1.0
-CH,2272.0,7,3.0,8.0,9.0,5.0,8.0,4.0,3.0,1.0,78.0,1.0
-CH,2273.0,7,3.0,0.0,0.0,1.0,3.0,2.0,1.0,1.0,62.0,2.0
-CH,2284.0,7,0.0,2.0,2.0,2.0,8.0,4.0,2.0,1.0,50.0,1.0
-CH,2289.0,7,3.0,8.0,6.0,5.0,9.0,6.0,3.0,1.0,72.0,1.0
-CH,2290.0,7,0.0,8.0,2.0,0.0,9.0,4.0,2.0,2.0,87.0,1.0
-CH,2294.0,7,2.0,7.0,4.0,4.0,8.0,6.0,3.0,2.0,23.0,2.0
-CH,2295.0,7,2.0,5.0,6.0,5.0,6.0,4.0,3.0,1.0,46.0,1.0
-CH,2298.0,7,3.0,8.0,7.0,7.0,8.0,6.0,3.0,2.0,33.0,2.0
-CH,2315.0,7,5.0,5.0,8.0,7.0,8.0,5.0,2.0,2.0,42.0,1.0
-CH,2318.0,7,1.0,7.0,3.0,7.0,9.0,6.0,3.0,1.0,30.0,2.0
-CH,2319.0,7,2.0,3.0,3.0,2.0,5.0,6.0,4.0,1.0,53.0,2.0
-CH,2322.0,7,5.0,8.0,8.0,8.0,10.0,6.0,4.0,2.0,37.0,1.0
-CH,2326.0,7,7.0,5.0,5.0,6.0,8.0,3.0,1.0,2.0,,1.0
-CH,2329.0,7,3.0,5.0,5.0,6.0,9.0,5.0,2.0,2.0,76.0,1.0
-CH,2330.0,7,2.0,8.0,8.0,3.0,9.0,6.0,3.0,2.0,50.0,1.0
-CH,2333.0,7,7.0,10.0,9.0,6.0,10.0,7.0,4.0,2.0,50.0,1.0
-CH,2334.0,7,2.0,6.0,6.0,4.0,10.0,6.0,3.0,2.0,20.0,2.0
-CH,2335.0,7,1.0,2.0,4.0,6.0,7.0,4.0,2.0,1.0,33.0,1.0
-CH,2338.0,7,2.0,8.0,7.0,7.0,9.0,5.0,1.0,1.0,48.0,1.0
-CH,2343.0,7,1.0,2.0,2.0,7.0,9.0,6.0,2.0,2.0,36.0,1.0
-CH,2345.0,7,0.0,8.0,8.0,7.0,10.0,6.0,3.0,2.0,39.0,1.0
-CH,2346.0,7,0.0,3.0,2.0,4.0,6.0,6.0,2.0,1.0,19.0,2.0
-CH,2347.0,7,3.0,8.0,8.0,5.0,8.0,6.0,3.0,2.0,74.0,2.0
-CH,2350.0,7,5.0,3.0,7.0,4.0,7.0,3.0,2.0,1.0,,2.0
-CH,2352.0,7,6.0,5.0,7.0,6.0,10.0,7.0,3.0,2.0,44.0,2.0
-CH,2356.0,7,6.0,5.0,3.0,7.0,8.0,6.0,,1.0,32.0,1.0
-CH,2358.0,7,4.0,5.0,4.0,3.0,7.0,5.0,3.0,1.0,36.0,2.0
-CH,2366.0,7,3.0,7.0,6.0,7.0,8.0,3.0,3.0,2.0,37.0,1.0
-CH,2376.0,7,1.0,8.0,8.0,7.0,9.0,6.0,4.0,2.0,69.0,1.0
-CH,2382.0,7,1.0,2.0,8.0,2.0,6.0,6.0,4.0,2.0,49.0,1.0
-CH,2383.0,7,3.0,3.0,5.0,5.0,5.0,6.0,3.0,2.0,54.0,1.0
-CH,2388.0,7,4.0,8.0,8.0,5.0,8.0,6.0,2.0,2.0,75.0,2.0
-CH,2392.0,7,3.0,7.0,3.0,7.0,6.0,6.0,3.0,1.0,54.0,1.0
-CH,2397.0,7,2.0,7.0,8.0,8.0,9.0,6.0,3.0,2.0,52.0,1.0
-CH,2403.0,7,4.0,5.0,6.0,6.0,8.0,4.0,2.0,1.0,54.0,1.0
-CH,2419.0,7,0.0,8.0,8.0,8.0,9.0,4.0,3.0,1.0,39.0,1.0
-CH,2425.0,7,1.0,8.0,8.0,7.0,7.0,4.0,3.0,1.0,63.0,1.0
-CH,2427.0,7,3.0,5.0,8.0,5.0,10.0,3.0,3.0,2.0,91.0,2.0
-CH,2429.0,7,2.0,3.0,5.0,4.0,8.0,6.0,4.0,2.0,36.0,1.0
-CH,2430.0,7,3.0,7.0,5.0,6.0,8.0,6.0,3.0,1.0,18.0,2.0
-CH,2431.0,7,4.0,9.0,10.0,10.0,9.0,4.0,3.0,2.0,64.0,1.0
-CH,2433.0,7,2.0,7.0,7.0,5.0,9.0,5.0,3.0,2.0,59.0,1.0
-CH,2434.0,7,2.0,3.0,5.0,5.0,8.0,5.0,2.0,1.0,27.0,1.0
-CH,2435.0,7,2.0,6.0,8.0,5.0,7.0,5.0,2.0,1.0,16.0,2.0
-CH,2439.0,7,5.0,8.0,8.0,7.0,8.0,6.0,,1.0,73.0,1.0
-CH,2448.0,7,2.0,7.0,7.0,7.0,8.0,4.0,3.0,1.0,20.0,2.0
-CH,2452.0,7,4.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,27.0,1.0
-CH,2454.0,7,7.0,8.0,2.0,5.0,9.0,5.0,3.0,2.0,67.0,1.0
-CH,2456.0,7,3.0,1.0,8.0,9.0,7.0,4.0,,1.0,55.0,1.0
-CH,2457.0,7,0.0,5.0,8.0,8.0,5.0,4.0,,2.0,35.0,2.0
-CH,2459.0,7,2.0,8.0,5.0,5.0,8.0,7.0,3.0,2.0,33.0,1.0
-CH,2462.0,7,3.0,5.0,7.0,6.0,8.0,4.0,3.0,1.0,27.0,2.0
-CH,2464.0,7,7.0,7.0,8.0,10.0,8.0,6.0,,1.0,69.0,1.0
-CH,2465.0,7,3.0,3.0,7.0,5.0,8.0,6.0,3.0,1.0,18.0,2.0
-CH,2466.0,7,3.0,8.0,8.0,8.0,9.0,6.0,3.0,2.0,64.0,1.0
-CH,2474.0,7,6.0,3.0,8.0,7.0,9.0,4.0,3.0,1.0,72.0,1.0
-CH,2477.0,7,3.0,6.0,8.0,6.0,9.0,3.0,3.0,2.0,50.0,1.0
-CH,2482.0,7,1.0,4.0,6.0,7.0,8.0,6.0,3.0,1.0,23.0,2.0
-CH,2485.0,7,2.0,5.0,7.0,6.0,10.0,6.0,,1.0,47.0,1.0
-CH,2486.0,7,0.0,6.0,7.0,7.0,6.0,3.0,2.0,1.0,56.0,1.0
-CH,2487.0,7,1.0,8.0,1.0,1.0,10.0,6.0,3.0,1.0,69.0,1.0
-CH,2488.0,7,5.0,3.0,3.0,3.0,4.0,5.0,3.0,1.0,63.0,1.0
-CH,2489.0,7,1.0,5.0,7.0,2.0,7.0,7.0,3.0,2.0,39.0,1.0
-CH,2491.0,7,5.0,8.0,8.0,6.0,6.0,7.0,3.0,1.0,,2.0
-CH,2498.0,7,4.0,5.0,5.0,3.0,10.0,5.0,4.0,1.0,70.0,1.0
-CH,2500.0,7,5.0,2.0,3.0,8.0,0.0,2.0,4.0,2.0,,1.0
-CH,2514.0,7,1.0,10.0,9.0,8.0,10.0,6.0,3.0,2.0,50.0,2.0
-CH,2515.0,7,2.0,5.0,7.0,7.0,9.0,1.0,3.0,1.0,29.0,1.0
-CH,2528.0,7,1.0,8.0,7.0,4.0,8.0,4.0,3.0,1.0,40.0,1.0
-CH,2539.0,7,5.0,1.0,5.0,4.0,8.0,5.0,3.0,1.0,39.0,1.0
-CH,2540.0,7,6.0,6.0,9.0,6.0,5.0,4.0,2.0,2.0,68.0,1.0
-CH,2545.0,7,0.0,5.0,5.0,5.0,5.0,3.0,3.0,2.0,71.0,1.0
-CH,2555.0,7,1.0,10.0,8.0,8.0,10.0,5.0,3.0,2.0,52.0,1.0
-CH,2557.0,7,5.0,8.0,8.0,7.0,8.0,6.0,4.0,2.0,35.0,1.0
-CH,2558.0,7,4.0,6.0,8.0,8.0,8.0,6.0,3.0,2.0,60.0,1.0
-CH,2560.0,7,0.0,8.0,9.0,2.0,8.0,7.0,1.0,2.0,25.0,2.0
-CH,2566.0,7,2.0,6.0,8.0,7.0,8.0,6.0,2.0,2.0,32.0,1.0
-CH,2567.0,7,1.0,8.0,2.0,10.0,9.0,4.0,2.0,1.0,51.0,1.0
-CH,2568.0,7,2.0,8.0,5.0,4.0,8.0,3.0,1.0,1.0,23.0,2.0
-CH,2569.0,7,4.0,4.0,5.0,4.0,6.0,6.0,2.0,2.0,36.0,1.0
-CH,2571.0,7,4.0,8.0,7.0,8.0,7.0,7.0,3.0,1.0,64.0,1.0
-CH,2573.0,7,3.0,7.0,5.0,7.0,7.0,6.0,3.0,2.0,31.0,2.0
-CH,2581.0,7,2.0,7.0,6.0,5.0,7.0,6.0,2.0,1.0,54.0,2.0
-CH,2582.0,7,0.0,7.0,3.0,8.0,8.0,7.0,3.0,2.0,22.0,2.0
-CH,2584.0,7,4.0,5.0,3.0,7.0,9.0,7.0,4.0,2.0,61.0,1.0
-CH,2589.0,7,5.0,6.0,8.0,6.0,7.0,4.0,4.0,2.0,83.0,1.0
-CH,2601.0,7,4.0,6.0,7.0,7.0,8.0,4.0,3.0,2.0,36.0,1.0
-CH,2620.0,7,0.0,3.0,4.0,3.0,9.0,4.0,2.0,1.0,80.0,1.0
-CH,2621.0,7,0.0,8.0,3.0,2.0,5.0,4.0,2.0,1.0,60.0,1.0
-CH,2625.0,7,2.0,6.0,7.0,7.0,6.0,5.0,2.0,2.0,91.0,2.0
-CH,2626.0,7,4.0,8.0,6.0,5.0,8.0,4.0,3.0,2.0,78.0,1.0
-CH,2627.0,7,4.0,7.0,6.0,5.0,8.0,6.0,3.0,2.0,62.0,1.0
-CH,2630.0,7,4.0,6.0,3.0,5.0,8.0,5.0,3.0,1.0,35.0,1.0
-CH,2631.0,7,4.0,8.0,7.0,7.0,9.0,4.0,1.0,2.0,62.0,1.0
-CH,2634.0,7,5.0,7.0,8.0,7.0,9.0,7.0,5.0,2.0,16.0,2.0
-CH,2639.0,7,3.0,3.0,4.0,5.0,7.0,7.0,2.0,2.0,60.0,1.0
-CH,2640.0,7,0.0,7.0,8.0,7.0,8.0,6.0,3.0,2.0,18.0,2.0
-CH,2642.0,7,4.0,9.0,9.0,7.0,10.0,6.0,4.0,1.0,60.0,1.0
-CH,2643.0,7,7.0,8.0,8.0,5.0,9.0,5.0,3.0,2.0,63.0,1.0
-CH,2644.0,7,7.0,3.0,5.0,2.0,10.0,3.0,1.0,1.0,78.0,1.0
-CH,2648.0,7,4.0,7.0,7.0,5.0,8.0,7.0,3.0,2.0,32.0,1.0
-CH,2651.0,7,2.0,8.0,10.0,9.0,9.0,4.0,4.0,2.0,62.0,1.0
-CH,2652.0,7,6.0,7.0,5.0,7.0,9.0,5.0,2.0,1.0,42.0,1.0
-CH,2666.0,7,4.0,9.0,8.0,6.0,10.0,6.0,3.0,2.0,74.0,1.0
-CH,2668.0,7,6.0,10.0,3.0,10.0,9.0,6.0,3.0,1.0,60.0,2.0
-CH,2670.0,7,2.0,5.0,4.0,5.0,7.0,5.0,3.0,2.0,29.0,1.0
-CH,2672.0,7,4.0,6.0,4.0,5.0,7.0,6.0,2.0,2.0,68.0,2.0
-CH,2674.0,7,7.0,3.0,6.0,3.0,8.0,4.0,2.0,2.0,58.0,1.0
-CH,2675.0,7,3.0,7.0,8.0,2.0,9.0,5.0,3.0,2.0,38.0,1.0
-CH,2676.0,7,0.0,2.0,6.0,6.0,5.0,7.0,3.0,1.0,47.0,2.0
-CH,2683.0,7,2.0,9.0,5.0,8.0,8.0,6.0,3.0,1.0,20.0,2.0
-CH,2684.0,7,2.0,4.0,8.0,8.0,8.0,4.0,3.0,2.0,75.0,2.0
-CH,2687.0,7,2.0,9.0,9.0,9.0,9.0,6.0,4.0,2.0,41.0,1.0
-CH,2689.0,7,3.0,8.0,8.0,7.0,10.0,6.0,4.0,2.0,75.0,1.0
-CH,2693.0,7,1.0,4.0,9.0,7.0,8.0,3.0,1.0,1.0,35.0,1.0
-CH,2699.0,7,3.0,5.0,2.0,4.0,7.0,5.0,3.0,2.0,25.0,2.0
-CH,2702.0,7,6.0,5.0,3.0,6.0,10.0,4.0,2.0,2.0,,1.0
-CH,2711.0,7,0.0,8.0,8.0,7.0,8.0,6.0,,2.0,42.0,1.0
-CH,2713.0,7,1.0,5.0,8.0,5.0,7.0,4.0,3.0,2.0,28.0,1.0
-CH,2714.0,7,4.0,5.0,5.0,2.0,10.0,6.0,1.0,2.0,25.0,1.0
-CH,2716.0,7,0.0,4.0,6.0,4.0,9.0,6.0,5.0,1.0,18.0,2.0
-CH,2720.0,7,0.0,8.0,7.0,5.0,8.0,6.0,4.0,1.0,20.0,2.0
-CH,2728.0,7,4.0,6.0,2.0,4.0,8.0,6.0,3.0,1.0,28.0,2.0
-CH,2729.0,7,2.0,6.0,7.0,7.0,8.0,5.0,3.0,1.0,31.0,1.0
-CH,2732.0,7,4.0,8.0,7.0,4.0,9.0,3.0,3.0,1.0,84.0,2.0
-CH,2738.0,7,5.0,5.0,5.0,5.0,10.0,5.0,2.0,1.0,49.0,2.0
-CH,2741.0,7,2.0,7.0,7.0,7.0,6.0,7.0,2.0,1.0,39.0,2.0
-CH,2745.0,7,5.0,5.0,6.0,10.0,9.0,5.0,3.0,1.0,34.0,1.0
-CH,2749.0,7,1.0,10.0,10.0,8.0,9.0,6.0,4.0,2.0,47.0,2.0
-CH,2752.0,7,0.0,8.0,9.0,9.0,9.0,6.0,3.0,2.0,61.0,1.0
-CH,2757.0,7,2.0,6.0,7.0,8.0,9.0,6.0,3.0,1.0,37.0,1.0
-CH,2765.0,7,2.0,8.0,7.0,7.0,7.0,6.0,3.0,2.0,39.0,2.0
-CH,2772.0,7,2.0,0.0,7.0,8.0,10.0,6.0,3.0,1.0,21.0,2.0
-CH,2773.0,7,0.0,7.0,8.0,6.0,10.0,5.0,2.0,2.0,78.0,1.0
-CH,2774.0,7,4.0,3.0,7.0,3.0,3.0,5.0,1.0,2.0,56.0,2.0
-CH,2775.0,7,2.0,5.0,5.0,7.0,6.0,5.0,2.0,1.0,34.0,1.0
-CH,2776.0,7,4.0,7.0,7.0,5.0,8.0,6.0,2.0,1.0,28.0,2.0
-CH,2777.0,7,0.0,8.0,7.0,7.0,8.0,6.0,3.0,2.0,37.0,1.0
-CH,2782.0,7,2.0,7.0,8.0,8.0,8.0,4.0,2.0,2.0,61.0,1.0
-CH,2784.0,7,0.0,7.0,7.0,6.0,8.0,6.0,4.0,1.0,48.0,2.0
-CH,2787.0,7,1.0,8.0,8.0,7.0,9.0,6.0,4.0,2.0,49.0,1.0
-CH,2788.0,7,2.0,8.0,8.0,3.0,10.0,7.0,5.0,1.0,61.0,2.0
-CH,2793.0,7,5.0,7.0,7.0,8.0,8.0,5.0,3.0,2.0,54.0,1.0
-CH,2795.0,7,4.0,7.0,5.0,4.0,8.0,6.0,1.0,2.0,20.0,2.0
-CH,2797.0,7,4.0,4.0,5.0,7.0,10.0,6.0,4.0,1.0,60.0,1.0
-CH,2800.0,7,3.0,7.0,5.0,4.0,5.0,2.0,3.0,1.0,58.0,1.0
-CH,2803.0,7,5.0,7.0,8.0,6.0,9.0,7.0,4.0,2.0,34.0,1.0
-CH,2805.0,7,3.0,5.0,10.0,7.0,10.0,4.0,3.0,2.0,76.0,2.0
-CH,2806.0,7,2.0,4.0,4.0,5.0,7.0,5.0,2.0,2.0,17.0,2.0
-CH,2807.0,7,2.0,5.0,6.0,3.0,8.0,6.0,2.0,2.0,47.0,1.0
-CH,2809.0,7,1.0,3.0,2.0,4.0,8.0,3.0,2.0,1.0,53.0,1.0
-CH,2811.0,7,5.0,7.0,8.0,9.0,8.0,3.0,1.0,1.0,82.0,1.0
-CH,2812.0,7,6.0,8.0,8.0,5.0,10.0,6.0,3.0,1.0,68.0,1.0
-CH,2813.0,7,1.0,9.0,9.0,6.0,8.0,6.0,2.0,2.0,22.0,1.0
-CH,2814.0,7,7.0,6.0,4.0,5.0,6.0,6.0,3.0,1.0,21.0,2.0
-CH,2817.0,7,2.0,9.0,10.0,8.0,10.0,6.0,4.0,1.0,33.0,2.0
-CH,2821.0,7,2.0,3.0,4.0,4.0,8.0,4.0,3.0,1.0,43.0,1.0
-CH,2826.0,7,3.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,17.0,2.0
-CH,2828.0,7,3.0,4.0,10.0,3.0,2.0,5.0,1.0,2.0,40.0,1.0
-CH,2835.0,7,3.0,7.0,7.0,6.0,8.0,3.0,3.0,2.0,48.0,1.0
-CH,2839.0,7,2.0,2.0,3.0,3.0,8.0,3.0,3.0,1.0,42.0,1.0
-CH,2842.0,7,0.0,7.0,8.0,6.0,9.0,3.0,3.0,2.0,61.0,1.0
-CH,2845.0,7,3.0,7.0,7.0,6.0,7.0,3.0,3.0,2.0,24.0,2.0
-CH,2847.0,7,4.0,3.0,3.0,3.0,6.0,2.0,2.0,1.0,68.0,2.0
-CH,2851.0,7,4.0,7.0,6.0,6.0,9.0,4.0,3.0,2.0,59.0,1.0
-CH,2853.0,7,4.0,7.0,7.0,6.0,7.0,4.0,3.0,2.0,51.0,1.0
-CH,2855.0,7,3.0,8.0,8.0,5.0,9.0,5.0,4.0,1.0,33.0,1.0
-CH,2858.0,7,5.0,5.0,5.0,5.0,5.0,5.0,3.0,2.0,72.0,1.0
-CH,2861.0,7,7.0,5.0,7.0,7.0,9.0,5.0,3.0,2.0,62.0,1.0
-CH,2872.0,7,3.0,5.0,4.0,5.0,8.0,4.0,2.0,1.0,46.0,1.0
-CH,2876.0,7,2.0,10.0,8.0,3.0,9.0,5.0,4.0,1.0,59.0,2.0
-CH,2878.0,7,6.0,5.0,6.0,5.0,7.0,6.0,3.0,1.0,23.0,2.0
-CH,2879.0,7,7.0,6.0,8.0,8.0,9.0,3.0,2.0,2.0,67.0,1.0
-CH,2882.0,7,1.0,7.0,6.0,7.0,8.0,6.0,3.0,1.0,50.0,1.0
-CH,2884.0,7,2.0,8.0,7.0,7.0,8.0,5.0,3.0,1.0,52.0,1.0
-CH,2885.0,7,3.0,7.0,8.0,7.0,8.0,6.0,3.0,2.0,25.0,1.0
-CH,2888.0,7,2.0,7.0,7.0,6.0,8.0,6.0,4.0,2.0,17.0,2.0
-CH,2890.0,7,5.0,4.0,6.0,2.0,10.0,6.0,4.0,1.0,38.0,1.0
-CH,2893.0,7,2.0,5.0,5.0,5.0,9.0,3.0,2.0,2.0,61.0,1.0
-CH,2894.0,7,5.0,7.0,6.0,5.0,7.0,3.0,2.0,2.0,56.0,1.0
-CH,2900.0,7,3.0,3.0,7.0,7.0,8.0,6.0,4.0,2.0,20.0,1.0
-CH,2905.0,7,4.0,5.0,6.0,6.0,8.0,4.0,3.0,1.0,19.0,2.0
-CZ,1001.0,6,2.0,10.0,9.0,4.0,9.0,6.0,3.0,1.0,39.0,1.0
-CZ,1002.0,6,4.0,5.0,4.0,6.0,8.0,6.0,3.0,1.0,29.0,1.0
-CZ,1003.0,6,1.0,9.0,8.0,6.0,9.0,5.0,5.0,1.0,33.0,2.0
-CZ,1004.0,6,3.0,2.0,1.0,2.0,7.0,4.0,3.0,1.0,24.0,2.0
-CZ,1005.0,6,7.0,2.0,10.0,6.0,4.0,5.0,3.0,2.0,63.0,2.0
-CZ,1006.0,6,7.0,3.0,10.0,3.0,3.0,,1.0,2.0,58.0,2.0
-CZ,1007.0,6,4.0,3.0,5.0,3.0,6.0,6.0,1.0,1.0,41.0,1.0
-CZ,1008.0,6,7.0,4.0,4.0,3.0,8.0,6.0,3.0,2.0,43.0,1.0
-CZ,1009.0,6,7.0,4.0,6.0,4.0,7.0,2.0,2.0,1.0,57.0,1.0
-CZ,1010.0,6,6.0,4.0,6.0,6.0,7.0,4.0,3.0,2.0,37.0,1.0
-CZ,1011.0,6,4.0,3.0,3.0,3.0,6.0,6.0,3.0,1.0,27.0,2.0
-CZ,1012.0,6,5.0,6.0,7.0,3.0,7.0,3.0,2.0,2.0,48.0,1.0
-CZ,1013.0,6,6.0,5.0,5.0,5.0,5.0,5.0,1.0,2.0,64.0,1.0
-CZ,1014.0,6,6.0,5.0,5.0,3.0,7.0,6.0,3.0,1.0,31.0,2.0
-CZ,1015.0,6,6.0,3.0,5.0,5.0,6.0,2.0,2.0,1.0,52.0,1.0
-CZ,1016.0,6,3.0,3.0,4.0,2.0,7.0,7.0,3.0,2.0,64.0,1.0
-CZ,1017.0,6,5.0,4.0,4.0,4.0,3.0,2.0,3.0,2.0,38.0,1.0
-CZ,1018.0,6,7.0,1.0,0.0,0.0,10.0,1.0,1.0,1.0,47.0,2.0
-CZ,1019.0,6,7.0,2.0,4.0,2.0,4.0,5.0,1.0,2.0,57.0,1.0
-CZ,1020.0,6,6.0,3.0,5.0,4.0,6.0,4.0,3.0,2.0,74.0,1.0
-CZ,1021.0,6,4.0,7.0,5.0,5.0,5.0,4.0,3.0,1.0,36.0,2.0
-CZ,1022.0,6,7.0,2.0,3.0,4.0,7.0,7.0,4.0,2.0,71.0,1.0
-CZ,1023.0,6,7.0,4.0,3.0,5.0,7.0,6.0,3.0,2.0,65.0,2.0
-CZ,1024.0,6,6.0,7.0,7.0,4.0,6.0,7.0,2.0,2.0,51.0,1.0
-CZ,1025.0,6,4.0,6.0,8.0,4.0,8.0,5.0,3.0,1.0,68.0,2.0
-CZ,1026.0,6,7.0,5.0,6.0,4.0,7.0,4.0,3.0,2.0,69.0,2.0
-CZ,1028.0,6,6.0,3.0,6.0,3.0,6.0,2.0,2.0,2.0,48.0,1.0
-CZ,1029.0,6,5.0,8.0,8.0,8.0,9.0,2.0,1.0,1.0,38.0,1.0
-CZ,1030.0,6,6.0,3.0,3.0,3.0,5.0,4.0,1.0,2.0,72.0,1.0
-CZ,1031.0,6,6.0,5.0,3.0,4.0,7.0,5.0,1.0,1.0,42.0,1.0
-CZ,1032.0,6,7.0,4.0,2.0,5.0,7.0,4.0,4.0,2.0,53.0,1.0
-CZ,1033.0,6,7.0,8.0,7.0,10.0,4.0,2.0,5.0,2.0,54.0,2.0
-CZ,1034.0,6,5.0,2.0,3.0,3.0,2.0,4.0,1.0,1.0,54.0,2.0
-CZ,1035.0,6,4.0,4.0,7.0,5.0,6.0,2.0,2.0,2.0,64.0,1.0
-CZ,1036.0,6,3.0,7.0,7.0,5.0,5.0,6.0,3.0,1.0,23.0,2.0
-CZ,1037.0,6,4.0,5.0,3.0,6.0,8.0,6.0,1.0,2.0,52.0,1.0
-CZ,1038.0,6,7.0,2.0,2.0,4.0,6.0,2.0,,2.0,69.0,1.0
-CZ,1039.0,6,0.0,2.0,3.0,0.0,,5.0,,2.0,59.0,2.0
-CZ,1040.0,6,4.0,4.0,8.0,0.0,9.0,5.0,2.0,2.0,31.0,1.0
-CZ,1041.0,6,7.0,4.0,5.0,5.0,7.0,4.0,1.0,1.0,71.0,2.0
-CZ,1042.0,6,5.0,9.0,7.0,9.0,8.0,5.0,2.0,2.0,31.0,1.0
-CZ,1043.0,6,4.0,7.0,4.0,7.0,7.0,6.0,3.0,2.0,27.0,1.0
-CZ,1044.0,6,7.0,0.0,4.0,4.0,5.0,6.0,1.0,2.0,41.0,2.0
-CZ,1045.0,6,7.0,3.0,3.0,3.0,7.0,7.0,3.0,1.0,67.0,2.0
-CZ,1046.0,6,6.0,5.0,5.0,5.0,8.0,4.0,3.0,1.0,69.0,1.0
-CZ,1047.0,6,2.0,4.0,4.0,4.0,9.0,6.0,4.0,1.0,18.0,2.0
-CZ,1048.0,6,6.0,6.0,6.0,6.0,8.0,6.0,3.0,1.0,40.0,2.0
-CZ,1049.0,6,4.0,8.0,7.0,7.0,9.0,6.0,3.0,1.0,19.0,2.0
-CZ,1050.0,6,6.0,7.0,8.0,7.0,8.0,4.0,2.0,1.0,32.0,1.0
-CZ,1051.0,6,7.0,6.0,6.0,8.0,9.0,5.0,3.0,2.0,32.0,2.0
-CZ,1052.0,6,7.0,4.0,6.0,4.0,4.0,6.0,3.0,2.0,56.0,2.0
-CZ,1053.0,6,2.0,1.0,7.0,7.0,9.0,3.0,3.0,1.0,54.0,1.0
-CZ,1054.0,6,6.0,3.0,4.0,4.0,4.0,2.0,2.0,1.0,47.0,2.0
-CZ,1055.0,6,7.0,1.0,2.0,2.0,5.0,5.0,3.0,1.0,65.0,1.0
-CZ,1056.0,6,7.0,6.0,8.0,6.0,7.0,4.0,3.0,1.0,63.0,1.0
-CZ,1057.0,6,7.0,5.0,5.0,2.0,6.0,6.0,3.0,2.0,64.0,2.0
-CZ,1058.0,6,7.0,5.0,10.0,5.0,,,,1.0,63.0,1.0
-CZ,1059.0,6,7.0,4.0,,3.0,9.0,5.0,3.0,2.0,61.0,1.0
-CZ,1060.0,6,2.0,5.0,7.0,6.0,9.0,3.0,3.0,1.0,60.0,1.0
-CZ,1061.0,6,3.0,4.0,4.0,7.0,8.0,4.0,3.0,2.0,33.0,1.0
-CZ,1062.0,6,2.0,2.0,5.0,0.0,7.0,4.0,2.0,1.0,51.0,1.0
-CZ,1063.0,6,7.0,9.0,9.0,9.0,8.0,5.0,2.0,2.0,59.0,2.0
-CZ,1064.0,6,6.0,2.0,4.0,6.0,6.0,4.0,3.0,2.0,28.0,1.0
-CZ,1065.0,6,6.0,3.0,3.0,4.0,9.0,6.0,5.0,1.0,23.0,2.0
-CZ,1066.0,6,7.0,9.0,10.0,1.0,,1.0,3.0,1.0,,1.0
-CZ,1067.0,6,4.0,4.0,5.0,4.0,5.0,2.0,1.0,1.0,59.0,1.0
-CZ,1068.0,6,3.0,3.0,4.0,4.0,5.0,4.0,2.0,1.0,63.0,1.0
-CZ,1069.0,6,6.0,7.0,7.0,4.0,8.0,6.0,3.0,2.0,18.0,2.0
-CZ,1070.0,6,3.0,6.0,6.0,5.0,7.0,7.0,3.0,1.0,19.0,2.0
-CZ,1071.0,6,6.0,3.0,4.0,4.0,7.0,3.0,1.0,2.0,60.0,2.0
-CZ,1072.0,6,6.0,4.0,6.0,7.0,8.0,4.0,3.0,1.0,50.0,1.0
-CZ,1073.0,6,,5.0,6.0,3.0,8.0,6.0,5.0,1.0,42.0,1.0
-CZ,1074.0,6,6.0,9.0,0.0,6.0,10.0,7.0,4.0,1.0,18.0,2.0
-CZ,1075.0,6,3.0,8.0,7.0,6.0,7.0,4.0,3.0,2.0,57.0,1.0
-CZ,1076.0,6,5.0,5.0,5.0,3.0,9.0,7.0,3.0,2.0,62.0,2.0
-CZ,1077.0,6,6.0,2.0,5.0,,5.0,3.0,2.0,1.0,55.0,1.0
-CZ,1078.0,6,4.0,7.0,7.0,8.0,8.0,6.0,3.0,2.0,17.0,2.0
-CZ,1079.0,6,5.0,4.0,5.0,6.0,6.0,2.0,1.0,1.0,43.0,2.0
-CZ,1080.0,6,1.0,2.0,4.0,4.0,7.0,3.0,3.0,1.0,48.0,2.0
-CZ,1081.0,6,7.0,4.0,3.0,5.0,5.0,2.0,,1.0,,1.0
-CZ,1082.0,6,5.0,1.0,4.0,1.0,4.0,7.0,2.0,1.0,55.0,1.0
-CZ,1083.0,6,4.0,4.0,5.0,7.0,4.0,4.0,2.0,2.0,45.0,1.0
-CZ,1084.0,6,7.0,7.0,8.0,8.0,7.0,5.0,4.0,2.0,16.0,2.0
-CZ,1085.0,6,3.0,5.0,5.0,4.0,8.0,4.0,4.0,1.0,16.0,2.0
-CZ,1086.0,6,7.0,6.0,8.0,8.0,8.0,6.0,1.0,2.0,76.0,2.0
-CZ,1087.0,6,1.0,5.0,6.0,6.0,9.0,5.0,3.0,1.0,46.0,1.0
-CZ,1088.0,6,5.0,1.0,3.0,3.0,7.0,3.0,2.0,1.0,34.0,1.0
-CZ,1089.0,6,6.0,6.0,7.0,6.0,4.0,5.0,3.0,1.0,18.0,2.0
-CZ,1090.0,6,5.0,9.0,7.0,10.0,3.0,2.0,2.0,2.0,25.0,2.0
-CZ,1091.0,6,3.0,10.0,8.0,10.0,9.0,3.0,3.0,2.0,39.0,1.0
-CZ,1092.0,6,4.0,3.0,4.0,1.0,7.0,4.0,2.0,1.0,48.0,2.0
-CZ,1093.0,6,4.0,9.0,9.0,7.0,9.0,6.0,3.0,2.0,16.0,2.0
-CZ,1094.0,6,6.0,4.0,7.0,6.0,7.0,4.0,4.0,1.0,55.0,1.0
-CZ,1095.0,6,5.0,6.0,6.0,6.0,5.0,4.0,3.0,1.0,40.0,2.0
-CZ,1096.0,6,4.0,4.0,5.0,2.0,10.0,7.0,3.0,2.0,25.0,1.0
-CZ,1097.0,6,5.0,6.0,6.0,3.0,8.0,7.0,3.0,1.0,17.0,2.0
-CZ,1098.0,6,5.0,3.0,7.0,2.0,5.0,4.0,2.0,2.0,60.0,2.0
-CZ,1099.0,6,6.0,3.0,7.0,5.0,9.0,4.0,3.0,2.0,67.0,1.0
-CZ,1100.0,6,7.0,0.0,3.0,4.0,6.0,3.0,1.0,2.0,87.0,2.0
-CZ,1101.0,6,3.0,,,,9.0,6.0,3.0,2.0,70.0,2.0
-CZ,1102.0,6,7.0,4.0,7.0,3.0,7.0,4.0,3.0,1.0,38.0,1.0
-CZ,1103.0,6,7.0,7.0,7.0,4.0,6.0,2.0,3.0,1.0,50.0,1.0
-CZ,1104.0,6,7.0,2.0,5.0,5.0,7.0,5.0,3.0,2.0,71.0,2.0
-CZ,1105.0,6,6.0,7.0,3.0,5.0,8.0,6.0,2.0,1.0,45.0,1.0
-CZ,1106.0,6,0.0,9.0,8.0,3.0,10.0,4.0,3.0,2.0,33.0,1.0
-CZ,1107.0,6,7.0,0.0,0.0,0.0,0.0,6.0,3.0,2.0,70.0,2.0
-CZ,1108.0,6,5.0,2.0,4.0,3.0,7.0,4.0,3.0,1.0,39.0,2.0
-CZ,1109.0,6,5.0,2.0,4.0,2.0,8.0,3.0,3.0,2.0,47.0,1.0
-CZ,1110.0,6,4.0,3.0,3.0,3.0,4.0,2.0,1.0,1.0,48.0,1.0
-CZ,1111.0,6,4.0,1.0,0.0,0.0,3.0,1.0,1.0,1.0,38.0,1.0
-CZ,1114.0,6,5.0,7.0,7.0,,7.0,6.0,3.0,1.0,20.0,2.0
-CZ,1116.0,6,7.0,7.0,5.0,4.0,6.0,4.0,5.0,1.0,51.0,1.0
-CZ,1117.0,6,6.0,4.0,5.0,5.0,5.0,5.0,5.0,1.0,51.0,1.0
-CZ,1118.0,6,7.0,5.0,7.0,3.0,5.0,6.0,3.0,1.0,71.0,1.0
-CZ,1119.0,6,5.0,5.0,5.0,2.0,8.0,5.0,2.0,1.0,61.0,2.0
-CZ,1120.0,6,4.0,5.0,5.0,0.0,5.0,5.0,2.0,1.0,60.0,1.0
-CZ,1121.0,6,5.0,5.0,5.0,4.0,5.0,4.0,3.0,2.0,59.0,1.0
-CZ,1122.0,6,7.0,2.0,2.0,2.0,1.0,3.0,1.0,2.0,64.0,1.0
-CZ,1123.0,6,7.0,4.0,7.0,3.0,3.0,5.0,2.0,1.0,79.0,2.0
-CZ,1124.0,6,4.0,5.0,6.0,2.0,9.0,7.0,3.0,1.0,29.0,1.0
-CZ,1125.0,6,5.0,6.0,6.0,6.0,8.0,6.0,3.0,1.0,45.0,1.0
-CZ,1126.0,6,7.0,7.0,5.0,7.0,6.0,2.0,1.0,2.0,51.0,1.0
-CZ,1127.0,6,5.0,9.0,9.0,3.0,10.0,6.0,3.0,1.0,19.0,2.0
-CZ,1128.0,6,7.0,2.0,4.0,0.0,8.0,4.0,3.0,1.0,53.0,1.0
-CZ,1129.0,6,2.0,5.0,6.0,8.0,1.0,6.0,3.0,1.0,19.0,2.0
-CZ,1130.0,6,4.0,7.0,7.0,5.0,7.0,6.0,3.0,1.0,72.0,2.0
-CZ,1131.0,6,6.0,5.0,5.0,2.0,9.0,6.0,3.0,2.0,16.0,2.0
-CZ,1132.0,6,7.0,5.0,5.0,4.0,5.0,2.0,1.0,1.0,50.0,2.0
-CZ,1133.0,6,6.0,6.0,5.0,7.0,4.0,2.0,3.0,1.0,41.0,1.0
-CZ,1134.0,6,7.0,3.0,0.0,0.0,4.0,1.0,3.0,2.0,73.0,2.0
-CZ,1135.0,6,7.0,3.0,8.0,10.0,10.0,6.0,2.0,2.0,,1.0
-CZ,1136.0,6,6.0,8.0,2.0,1.0,7.0,4.0,3.0,1.0,44.0,1.0
-CZ,1137.0,6,6.0,1.0,,2.0,5.0,3.0,3.0,2.0,78.0,2.0
-CZ,1138.0,6,7.0,3.0,6.0,4.0,6.0,4.0,4.0,1.0,,1.0
-CZ,1139.0,6,5.0,8.0,3.0,5.0,8.0,4.0,3.0,2.0,54.0,2.0
-CZ,1140.0,6,4.0,5.0,2.0,0.0,8.0,6.0,3.0,2.0,44.0,2.0
-CZ,1141.0,6,3.0,9.0,8.0,7.0,10.0,6.0,3.0,2.0,16.0,2.0
-CZ,1142.0,6,1.0,7.0,9.0,5.0,8.0,4.0,3.0,2.0,20.0,2.0
-CZ,1143.0,6,7.0,3.0,3.0,3.0,4.0,7.0,3.0,2.0,18.0,2.0
-CZ,1144.0,6,5.0,0.0,0.0,0.0,8.0,4.0,3.0,1.0,51.0,1.0
-CZ,1145.0,6,7.0,4.0,5.0,4.0,7.0,2.0,1.0,1.0,60.0,1.0
-CZ,1146.0,6,2.0,0.0,3.0,5.0,5.0,6.0,3.0,2.0,39.0,2.0
-CZ,1147.0,6,7.0,2.0,4.0,2.0,5.0,6.0,1.0,1.0,62.0,2.0
-CZ,1148.0,6,2.0,3.0,5.0,5.0,8.0,6.0,3.0,2.0,33.0,1.0
-CZ,1149.0,6,4.0,3.0,1.0,9.0,,2.0,,2.0,57.0,1.0
-CZ,1150.0,6,4.0,3.0,5.0,5.0,7.0,6.0,5.0,1.0,35.0,1.0
-CZ,1151.0,6,4.0,10.0,10.0,10.0,9.0,6.0,3.0,2.0,74.0,2.0
-CZ,1152.0,6,,9.0,9.0,9.0,9.0,4.0,3.0,2.0,26.0,1.0
-CZ,1153.0,6,4.0,4.0,3.0,3.0,7.0,5.0,3.0,1.0,38.0,1.0
-CZ,1154.0,6,6.0,2.0,5.0,0.0,7.0,4.0,2.0,2.0,41.0,1.0
-CZ,1155.0,6,6.0,0.0,2.0,2.0,8.0,7.0,1.0,1.0,42.0,1.0
-CZ,1156.0,6,7.0,6.0,4.0,5.0,9.0,2.0,2.0,2.0,70.0,2.0
-CZ,1157.0,6,4.0,4.0,,7.0,7.0,1.0,1.0,2.0,81.0,1.0
-CZ,1158.0,6,6.0,4.0,5.0,4.0,3.0,3.0,1.0,2.0,40.0,1.0
-CZ,1159.0,6,6.0,4.0,6.0,5.0,3.0,2.0,2.0,2.0,68.0,2.0
-CZ,1160.0,6,2.0,3.0,4.0,5.0,5.0,2.0,2.0,2.0,81.0,2.0
-CZ,1161.0,6,7.0,4.0,6.0,3.0,5.0,4.0,2.0,1.0,51.0,1.0
-CZ,1162.0,6,5.0,3.0,5.0,6.0,7.0,2.0,3.0,2.0,54.0,1.0
-CZ,1163.0,6,2.0,0.0,3.0,1.0,7.0,5.0,2.0,1.0,54.0,1.0
-CZ,1164.0,6,3.0,3.0,3.0,3.0,7.0,4.0,3.0,2.0,35.0,2.0
-CZ,1165.0,6,2.0,7.0,7.0,8.0,7.0,2.0,1.0,1.0,33.0,2.0
-CZ,1166.0,6,7.0,5.0,5.0,2.0,5.0,5.0,2.0,2.0,51.0,1.0
-CZ,1167.0,6,7.0,2.0,4.0,4.0,7.0,4.0,3.0,1.0,71.0,1.0
-CZ,1168.0,6,5.0,5.0,5.0,7.0,7.0,4.0,2.0,2.0,46.0,2.0
-CZ,1169.0,6,2.0,2.0,3.0,4.0,9.0,5.0,3.0,2.0,59.0,1.0
-CZ,1170.0,6,1.0,5.0,6.0,6.0,7.0,6.0,3.0,1.0,21.0,2.0
-CZ,1171.0,6,2.0,6.0,7.0,4.0,8.0,4.0,3.0,1.0,56.0,1.0
-CZ,1172.0,6,6.0,7.0,8.0,3.0,9.0,4.0,4.0,1.0,67.0,1.0
-CZ,1173.0,6,5.0,5.0,7.0,3.0,8.0,2.0,3.0,1.0,63.0,1.0
-CZ,1174.0,6,5.0,8.0,8.0,7.0,8.0,3.0,3.0,1.0,55.0,1.0
-CZ,1175.0,6,4.0,1.0,5.0,5.0,8.0,3.0,3.0,1.0,52.0,1.0
-CZ,1176.0,6,5.0,6.0,7.0,4.0,8.0,4.0,2.0,1.0,44.0,1.0
-CZ,1177.0,6,7.0,3.0,5.0,6.0,,2.0,2.0,2.0,79.0,2.0
-CZ,1178.0,6,4.0,3.0,4.0,5.0,7.0,6.0,3.0,2.0,22.0,2.0
-CZ,1179.0,6,7.0,5.0,5.0,5.0,6.0,5.0,2.0,1.0,62.0,2.0
-CZ,1180.0,6,7.0,2.0,2.0,5.0,9.0,7.0,,2.0,72.0,2.0
-CZ,1181.0,6,4.0,6.0,5.0,4.0,6.0,5.0,3.0,2.0,34.0,1.0
-CZ,1182.0,6,3.0,7.0,7.0,8.0,9.0,6.0,3.0,1.0,19.0,2.0
-CZ,1183.0,6,6.0,7.0,7.0,8.0,2.0,2.0,3.0,1.0,73.0,2.0
-CZ,1184.0,6,5.0,8.0,8.0,8.0,5.0,7.0,4.0,1.0,35.0,1.0
-CZ,1185.0,6,4.0,6.0,6.0,6.0,8.0,4.0,2.0,2.0,19.0,2.0
-CZ,1186.0,6,6.0,3.0,3.0,4.0,5.0,4.0,3.0,1.0,44.0,1.0
-CZ,1187.0,6,7.0,2.0,3.0,5.0,5.0,4.0,3.0,1.0,33.0,1.0
-CZ,1188.0,6,3.0,6.0,6.0,7.0,7.0,7.0,3.0,2.0,16.0,2.0
-CZ,1189.0,6,2.0,2.0,8.0,5.0,4.0,4.0,3.0,1.0,41.0,1.0
-CZ,1190.0,6,7.0,5.0,5.0,3.0,10.0,3.0,2.0,2.0,72.0,2.0
-CZ,1191.0,6,3.0,3.0,3.0,4.0,8.0,4.0,2.0,1.0,52.0,2.0
-CZ,1192.0,6,2.0,3.0,4.0,3.0,8.0,7.0,2.0,2.0,23.0,1.0
-CZ,1193.0,6,7.0,1.0,2.0,8.0,5.0,5.0,3.0,1.0,57.0,1.0
-CZ,1194.0,6,2.0,5.0,5.0,7.0,8.0,7.0,3.0,2.0,23.0,2.0
-CZ,1195.0,6,6.0,8.0,7.0,7.0,7.0,2.0,1.0,1.0,34.0,1.0
-CZ,1196.0,6,7.0,7.0,1.0,2.0,10.0,7.0,2.0,2.0,42.0,1.0
-CZ,1197.0,6,2.0,3.0,2.0,4.0,10.0,6.0,1.0,2.0,37.0,1.0
-CZ,1198.0,6,5.0,5.0,5.0,6.0,7.0,4.0,3.0,2.0,43.0,1.0
-CZ,1199.0,6,6.0,4.0,5.0,4.0,6.0,3.0,3.0,1.0,37.0,1.0
-CZ,1200.0,6,6.0,5.0,5.0,4.0,5.0,5.0,4.0,2.0,34.0,2.0
-CZ,1201.0,6,7.0,4.0,3.0,6.0,10.0,3.0,1.0,2.0,64.0,2.0
-CZ,1202.0,6,7.0,9.0,8.0,3.0,5.0,3.0,2.0,2.0,55.0,2.0
-CZ,1203.0,6,2.0,7.0,7.0,3.0,9.0,4.0,3.0,2.0,37.0,1.0
-CZ,1204.0,6,2.0,5.0,5.0,5.0,7.0,2.0,3.0,1.0,47.0,1.0
-CZ,1205.0,6,6.0,0.0,0.0,0.0,3.0,5.0,3.0,1.0,60.0,1.0
-CZ,1206.0,6,3.0,2.0,2.0,1.0,6.0,5.0,3.0,1.0,40.0,2.0
-CZ,1207.0,6,5.0,2.0,2.0,2.0,5.0,5.0,1.0,2.0,60.0,2.0
-CZ,1208.0,6,7.0,4.0,5.0,5.0,8.0,5.0,4.0,2.0,69.0,2.0
-CZ,1209.0,6,7.0,4.0,5.0,4.0,4.0,6.0,,1.0,68.0,2.0
-CZ,1210.0,6,7.0,4.0,6.0,5.0,9.0,3.0,3.0,1.0,71.0,1.0
-CZ,1211.0,6,4.0,2.0,2.0,4.0,5.0,7.0,3.0,1.0,23.0,2.0
-CZ,1212.0,6,4.0,3.0,4.0,2.0,4.0,6.0,3.0,1.0,27.0,2.0
-CZ,1213.0,6,2.0,2.0,2.0,1.0,3.0,7.0,3.0,1.0,24.0,2.0
-CZ,1214.0,6,7.0,8.0,8.0,8.0,9.0,5.0,2.0,2.0,62.0,2.0
-CZ,1215.0,6,6.0,3.0,3.0,4.0,5.0,6.0,3.0,1.0,57.0,1.0
-CZ,1216.0,6,4.0,5.0,5.0,5.0,5.0,2.0,1.0,2.0,39.0,2.0
-CZ,1217.0,6,7.0,2.0,5.0,3.0,5.0,6.0,3.0,2.0,62.0,2.0
-CZ,1218.0,6,6.0,2.0,5.0,2.0,2.0,7.0,4.0,2.0,26.0,2.0
-CZ,1219.0,6,3.0,5.0,7.0,3.0,9.0,4.0,3.0,2.0,40.0,1.0
-CZ,1220.0,6,7.0,5.0,7.0,2.0,4.0,2.0,3.0,2.0,58.0,1.0
-CZ,1221.0,6,5.0,9.0,7.0,8.0,5.0,4.0,3.0,2.0,19.0,2.0
-CZ,1222.0,6,7.0,3.0,5.0,5.0,4.0,2.0,1.0,2.0,76.0,2.0
-CZ,1223.0,6,3.0,4.0,5.0,3.0,10.0,6.0,3.0,1.0,35.0,1.0
-CZ,1224.0,6,0.0,5.0,6.0,7.0,10.0,5.0,3.0,1.0,24.0,2.0
-CZ,1225.0,6,2.0,4.0,4.0,3.0,7.0,6.0,3.0,2.0,54.0,1.0
-CZ,1226.0,6,7.0,5.0,5.0,5.0,5.0,4.0,1.0,1.0,45.0,1.0
-CZ,1227.0,6,7.0,9.0,9.0,10.0,5.0,7.0,3.0,1.0,42.0,1.0
-CZ,1228.0,6,6.0,5.0,5.0,5.0,7.0,4.0,1.0,2.0,41.0,1.0
-CZ,1229.0,6,4.0,5.0,7.0,7.0,8.0,7.0,3.0,1.0,35.0,1.0
-CZ,1230.0,6,7.0,6.0,7.0,5.0,5.0,6.0,5.0,2.0,75.0,2.0
-CZ,1231.0,6,6.0,5.0,7.0,6.0,5.0,4.0,4.0,1.0,56.0,2.0
-CZ,1232.0,6,2.0,3.0,2.0,2.0,5.0,5.0,1.0,1.0,64.0,2.0
-CZ,1233.0,6,7.0,7.0,7.0,7.0,8.0,6.0,3.0,1.0,35.0,1.0
-CZ,1234.0,6,3.0,3.0,3.0,8.0,7.0,4.0,2.0,2.0,69.0,2.0
-CZ,1235.0,6,7.0,4.0,5.0,5.0,6.0,4.0,2.0,2.0,67.0,2.0
-CZ,1236.0,6,3.0,8.0,8.0,6.0,6.0,6.0,3.0,1.0,21.0,2.0
-CZ,1237.0,6,7.0,6.0,7.0,5.0,7.0,4.0,3.0,1.0,37.0,1.0
-CZ,1238.0,6,7.0,0.0,0.0,0.0,9.0,2.0,3.0,1.0,70.0,1.0
-CZ,1239.0,6,6.0,0.0,1.0,1.0,5.0,5.0,3.0,2.0,57.0,2.0
-CZ,1240.0,6,4.0,1.0,0.0,1.0,0.0,2.0,5.0,2.0,64.0,2.0
-CZ,1241.0,6,4.0,0.0,0.0,0.0,2.0,2.0,5.0,1.0,54.0,1.0
-CZ,1242.0,6,5.0,6.0,5.0,5.0,7.0,4.0,2.0,1.0,43.0,1.0
-CZ,1243.0,6,3.0,7.0,8.0,8.0,,5.0,3.0,1.0,71.0,1.0
-CZ,1244.0,6,7.0,4.0,7.0,5.0,8.0,6.0,3.0,2.0,17.0,2.0
-CZ,1245.0,6,,3.0,5.0,5.0,7.0,4.0,3.0,1.0,31.0,1.0
-CZ,1246.0,6,7.0,1.0,5.0,1.0,,7.0,3.0,2.0,62.0,2.0
-CZ,1247.0,6,6.0,4.0,4.0,4.0,3.0,5.0,2.0,2.0,53.0,1.0
-CZ,1248.0,6,6.0,1.0,1.0,1.0,4.0,7.0,3.0,2.0,61.0,1.0
-CZ,1249.0,6,7.0,4.0,4.0,4.0,4.0,6.0,3.0,1.0,69.0,2.0
-CZ,1250.0,6,5.0,3.0,4.0,5.0,8.0,2.0,1.0,2.0,36.0,1.0
-CZ,1251.0,6,2.0,9.0,4.0,8.0,9.0,3.0,2.0,2.0,34.0,1.0
-CZ,1252.0,6,6.0,5.0,2.0,5.0,5.0,4.0,2.0,1.0,17.0,2.0
-CZ,1253.0,6,7.0,5.0,3.0,7.0,3.0,4.0,3.0,2.0,,1.0
-CZ,1254.0,6,7.0,3.0,4.0,4.0,2.0,2.0,1.0,2.0,90.0,2.0
-CZ,1255.0,6,7.0,2.0,5.0,4.0,5.0,3.0,1.0,1.0,58.0,1.0
-CZ,1256.0,6,1.0,6.0,6.0,4.0,3.0,2.0,2.0,1.0,56.0,1.0
-CZ,1257.0,6,6.0,6.0,7.0,7.0,8.0,3.0,3.0,1.0,39.0,1.0
-CZ,1258.0,6,7.0,8.0,3.0,5.0,8.0,7.0,4.0,1.0,18.0,2.0
-CZ,1259.0,6,7.0,1.0,1.0,2.0,5.0,5.0,3.0,2.0,73.0,2.0
-CZ,1260.0,6,5.0,6.0,6.0,7.0,9.0,5.0,2.0,1.0,50.0,1.0
-CZ,1261.0,6,7.0,6.0,7.0,7.0,5.0,5.0,4.0,2.0,23.0,1.0
-CZ,1262.0,6,6.0,3.0,4.0,5.0,8.0,4.0,2.0,1.0,62.0,1.0
-CZ,1263.0,6,4.0,0.0,0.0,0.0,10.0,7.0,3.0,1.0,36.0,1.0
-CZ,1264.0,6,5.0,0.0,0.0,0.0,6.0,7.0,4.0,1.0,30.0,2.0
-CZ,1265.0,6,4.0,7.0,4.0,7.0,6.0,7.0,3.0,2.0,56.0,1.0
-CZ,1266.0,6,5.0,5.0,6.0,5.0,5.0,5.0,,1.0,,2.0
-CZ,1267.0,6,5.0,6.0,,9.0,8.0,6.0,3.0,2.0,33.0,2.0
-CZ,1268.0,6,7.0,,4.0,2.0,7.0,2.0,2.0,2.0,68.0,1.0
-CZ,1269.0,6,6.0,5.0,6.0,7.0,5.0,6.0,4.0,1.0,22.0,2.0
-CZ,1270.0,6,7.0,0.0,6.0,0.0,6.0,1.0,,1.0,,1.0
-CZ,1271.0,6,7.0,7.0,6.0,8.0,7.0,2.0,2.0,2.0,48.0,1.0
-CZ,1272.0,6,6.0,8.0,8.0,8.0,9.0,5.0,3.0,2.0,19.0,2.0
-CZ,1273.0,6,7.0,7.0,7.0,7.0,8.0,5.0,3.0,1.0,42.0,1.0
-CZ,1274.0,6,7.0,8.0,8.0,8.0,6.0,3.0,2.0,2.0,60.0,2.0
-CZ,1275.0,6,0.0,5.0,9.0,8.0,9.0,5.0,3.0,2.0,30.0,2.0
-CZ,1276.0,6,5.0,5.0,7.0,5.0,6.0,6.0,3.0,1.0,27.0,2.0
-CZ,1277.0,6,4.0,4.0,6.0,7.0,7.0,6.0,3.0,2.0,79.0,1.0
-CZ,1278.0,6,6.0,2.0,3.0,6.0,7.0,6.0,4.0,2.0,48.0,1.0
-CZ,1279.0,6,5.0,5.0,8.0,4.0,9.0,6.0,2.0,2.0,32.0,1.0
-CZ,1280.0,6,6.0,3.0,3.0,5.0,4.0,2.0,1.0,2.0,73.0,1.0
-CZ,1281.0,6,6.0,5.0,6.0,6.0,9.0,3.0,3.0,1.0,40.0,1.0
-CZ,1282.0,6,5.0,7.0,6.0,8.0,9.0,5.0,4.0,1.0,43.0,1.0
-CZ,1283.0,6,6.0,8.0,9.0,7.0,9.0,7.0,4.0,2.0,58.0,1.0
-CZ,1284.0,6,7.0,2.0,5.0,3.0,0.0,3.0,1.0,2.0,73.0,2.0
-CZ,1285.0,6,7.0,5.0,4.0,8.0,5.0,6.0,2.0,2.0,68.0,1.0
-CZ,1286.0,6,6.0,4.0,3.0,5.0,10.0,6.0,3.0,2.0,41.0,2.0
-CZ,1287.0,6,7.0,8.0,9.0,3.0,7.0,6.0,1.0,2.0,25.0,1.0
-CZ,1288.0,6,4.0,5.0,3.0,4.0,8.0,6.0,2.0,2.0,45.0,2.0
-CZ,1289.0,6,7.0,4.0,2.0,3.0,,5.0,1.0,2.0,69.0,2.0
-CZ,1290.0,6,7.0,3.0,7.0,0.0,10.0,4.0,3.0,1.0,62.0,2.0
-CZ,1291.0,6,5.0,3.0,3.0,4.0,6.0,6.0,2.0,2.0,26.0,1.0
-CZ,1292.0,6,3.0,4.0,5.0,7.0,5.0,7.0,4.0,1.0,21.0,2.0
-CZ,1293.0,6,0.0,5.0,5.0,5.0,9.0,7.0,3.0,2.0,20.0,2.0
-CZ,1294.0,6,4.0,0.0,5.0,0.0,3.0,1.0,1.0,2.0,33.0,2.0
-CZ,1295.0,6,3.0,5.0,3.0,4.0,4.0,2.0,1.0,2.0,34.0,1.0
-CZ,1296.0,6,6.0,9.0,,9.0,6.0,5.0,1.0,1.0,70.0,1.0
-CZ,1297.0,6,3.0,2.0,,1.0,8.0,2.0,3.0,2.0,61.0,1.0
-CZ,1298.0,6,7.0,1.0,1.0,5.0,6.0,6.0,2.0,2.0,64.0,2.0
-CZ,1299.0,6,6.0,2.0,2.0,3.0,7.0,5.0,3.0,2.0,38.0,1.0
-CZ,1300.0,6,5.0,1.0,1.0,1.0,8.0,5.0,3.0,2.0,58.0,1.0
-CZ,1301.0,6,5.0,1.0,1.0,1.0,5.0,6.0,3.0,1.0,36.0,2.0
-CZ,1302.0,6,7.0,3.0,3.0,3.0,5.0,5.0,2.0,2.0,74.0,2.0
-CZ,1303.0,6,4.0,2.0,2.0,2.0,8.0,6.0,3.0,1.0,29.0,1.0
-CZ,1304.0,6,3.0,3.0,2.0,2.0,6.0,6.0,3.0,2.0,47.0,1.0
-CZ,1305.0,6,7.0,5.0,5.0,5.0,5.0,5.0,1.0,2.0,63.0,1.0
-CZ,1306.0,6,7.0,6.0,5.0,4.0,9.0,6.0,3.0,2.0,23.0,2.0
-CZ,1307.0,6,5.0,0.0,3.0,4.0,7.0,3.0,3.0,2.0,44.0,1.0
-CZ,1308.0,6,6.0,,8.0,6.0,10.0,5.0,3.0,2.0,46.0,1.0
-CZ,1309.0,6,7.0,4.0,6.0,3.0,7.0,2.0,2.0,1.0,60.0,2.0
-CZ,1310.0,6,1.0,7.0,6.0,6.0,9.0,6.0,2.0,1.0,50.0,1.0
-CZ,1311.0,6,7.0,5.0,5.0,4.0,6.0,6.0,2.0,1.0,60.0,1.0
-CZ,1312.0,6,4.0,5.0,5.0,3.0,5.0,4.0,,2.0,74.0,2.0
-CZ,1313.0,6,1.0,5.0,4.0,6.0,8.0,7.0,3.0,1.0,23.0,2.0
-CZ,1314.0,6,,5.0,5.0,5.0,8.0,3.0,2.0,2.0,35.0,2.0
-CZ,1315.0,6,1.0,0.0,1.0,2.0,4.0,7.0,4.0,1.0,19.0,2.0
-CZ,1316.0,6,1.0,,,4.0,8.0,2.0,1.0,2.0,29.0,1.0
-CZ,1317.0,6,7.0,4.0,3.0,3.0,8.0,5.0,3.0,1.0,52.0,1.0
-CZ,1318.0,6,6.0,0.0,6.0,0.0,5.0,5.0,3.0,2.0,29.0,1.0
-CZ,1319.0,6,6.0,6.0,5.0,3.0,5.0,6.0,5.0,2.0,44.0,2.0
-CZ,1320.0,6,6.0,8.0,7.0,8.0,10.0,5.0,3.0,1.0,35.0,1.0
-CZ,1321.0,6,4.0,0.0,0.0,0.0,5.0,1.0,1.0,1.0,36.0,1.0
-CZ,1322.0,6,6.0,5.0,5.0,3.0,8.0,5.0,1.0,2.0,67.0,2.0
-CZ,1323.0,6,7.0,4.0,5.0,4.0,7.0,4.0,2.0,2.0,29.0,1.0
-CZ,1324.0,6,7.0,1.0,2.0,2.0,5.0,4.0,3.0,1.0,72.0,1.0
-CZ,1325.0,6,2.0,2.0,2.0,4.0,8.0,4.0,3.0,2.0,45.0,1.0
-CZ,1326.0,6,4.0,3.0,5.0,5.0,6.0,4.0,3.0,2.0,53.0,2.0
-CZ,1327.0,6,6.0,7.0,7.0,7.0,8.0,4.0,4.0,1.0,69.0,1.0
-CZ,1328.0,6,7.0,0.0,2.0,3.0,6.0,4.0,5.0,1.0,80.0,1.0
-CZ,1329.0,6,4.0,4.0,4.0,3.0,6.0,6.0,3.0,2.0,44.0,1.0
-CZ,1330.0,6,4.0,1.0,8.0,3.0,7.0,4.0,3.0,1.0,44.0,1.0
-CZ,1331.0,6,5.0,,5.0,4.0,8.0,3.0,4.0,2.0,60.0,2.0
-CZ,1332.0,6,2.0,5.0,7.0,7.0,9.0,7.0,2.0,1.0,38.0,1.0
-CZ,1333.0,6,5.0,3.0,4.0,2.0,7.0,6.0,5.0,2.0,69.0,1.0
-CZ,1334.0,6,7.0,2.0,3.0,3.0,5.0,6.0,1.0,2.0,42.0,2.0
-CZ,1335.0,6,5.0,0.0,5.0,5.0,6.0,4.0,2.0,1.0,67.0,1.0
-CZ,1336.0,6,7.0,8.0,9.0,3.0,5.0,4.0,2.0,1.0,50.0,1.0
-CZ,1337.0,6,6.0,8.0,7.0,5.0,9.0,4.0,3.0,1.0,55.0,1.0
-CZ,1338.0,6,4.0,4.0,3.0,5.0,8.0,6.0,3.0,1.0,43.0,1.0
-CZ,1340.0,6,5.0,5.0,6.0,6.0,6.0,4.0,1.0,1.0,56.0,1.0
-CZ,1341.0,6,6.0,7.0,7.0,6.0,7.0,4.0,3.0,2.0,,2.0
-CZ,1342.0,6,4.0,3.0,3.0,7.0,7.0,7.0,3.0,2.0,17.0,2.0
-CZ,1343.0,6,4.0,4.0,5.0,5.0,8.0,4.0,2.0,2.0,79.0,2.0
-CZ,1344.0,6,2.0,5.0,4.0,3.0,8.0,7.0,2.0,2.0,56.0,2.0
-CZ,1345.0,6,7.0,6.0,7.0,8.0,8.0,4.0,4.0,2.0,67.0,1.0
-CZ,1346.0,6,5.0,6.0,6.0,7.0,7.0,6.0,3.0,2.0,54.0,1.0
-CZ,1347.0,6,7.0,6.0,1.0,5.0,5.0,4.0,3.0,1.0,73.0,2.0
-CZ,1348.0,6,7.0,6.0,6.0,6.0,10.0,5.0,3.0,2.0,56.0,1.0
-CZ,1349.0,6,4.0,5.0,5.0,4.0,6.0,2.0,3.0,2.0,40.0,1.0
-CZ,1350.0,6,3.0,0.0,2.0,4.0,3.0,6.0,1.0,1.0,19.0,2.0
-CZ,1351.0,6,7.0,9.0,4.0,3.0,3.0,1.0,3.0,2.0,81.0,1.0
-CZ,1352.0,6,7.0,9.0,9.0,8.0,7.0,6.0,4.0,2.0,23.0,2.0
-CZ,1353.0,6,4.0,4.0,5.0,4.0,6.0,6.0,3.0,1.0,69.0,1.0
-CZ,1354.0,6,2.0,5.0,5.0,4.0,7.0,6.0,3.0,1.0,22.0,2.0
-CZ,1355.0,6,3.0,3.0,1.0,2.0,8.0,3.0,3.0,1.0,46.0,1.0
-CZ,1356.0,6,2.0,9.0,6.0,7.0,7.0,5.0,3.0,1.0,37.0,1.0
-CZ,1357.0,6,4.0,8.0,6.0,9.0,7.0,4.0,3.0,2.0,19.0,2.0
-CZ,1358.0,6,5.0,7.0,7.0,7.0,8.0,4.0,3.0,1.0,42.0,1.0
-CZ,1359.0,6,4.0,3.0,8.0,8.0,10.0,4.0,3.0,1.0,44.0,1.0
-CZ,1360.0,6,7.0,7.0,8.0,3.0,9.0,7.0,2.0,2.0,54.0,1.0
-CZ,1361.0,6,4.0,8.0,8.0,9.0,5.0,6.0,3.0,1.0,16.0,2.0
-CZ,1362.0,6,7.0,2.0,5.0,3.0,8.0,3.0,2.0,1.0,69.0,1.0
-CZ,1363.0,6,6.0,5.0,7.0,9.0,8.0,7.0,3.0,2.0,57.0,1.0
-CZ,1364.0,6,6.0,5.0,8.0,5.0,8.0,2.0,1.0,1.0,61.0,2.0
-CZ,1365.0,6,6.0,4.0,5.0,3.0,5.0,3.0,1.0,2.0,68.0,2.0
-CZ,1366.0,6,7.0,1.0,1.0,1.0,4.0,6.0,1.0,2.0,63.0,2.0
-CZ,1367.0,6,4.0,5.0,4.0,1.0,7.0,6.0,1.0,1.0,49.0,1.0
-CZ,1368.0,6,6.0,0.0,3.0,3.0,8.0,5.0,1.0,2.0,59.0,1.0
-CZ,1369.0,6,7.0,3.0,5.0,2.0,8.0,6.0,3.0,2.0,55.0,1.0
-CZ,1370.0,6,1.0,2.0,3.0,4.0,7.0,6.0,3.0,2.0,31.0,1.0
-CZ,1371.0,6,3.0,6.0,7.0,7.0,8.0,6.0,3.0,2.0,41.0,1.0
-CZ,1372.0,6,6.0,3.0,3.0,6.0,6.0,4.0,2.0,1.0,48.0,1.0
-CZ,1373.0,6,7.0,4.0,4.0,4.0,2.0,1.0,1.0,2.0,81.0,2.0
-CZ,1374.0,6,7.0,7.0,7.0,5.0,7.0,3.0,3.0,1.0,53.0,1.0
-CZ,1375.0,6,7.0,8.0,8.0,8.0,8.0,5.0,3.0,2.0,64.0,1.0
-CZ,1376.0,6,7.0,3.0,3.0,3.0,9.0,7.0,3.0,2.0,68.0,2.0
-CZ,1377.0,6,7.0,2.0,2.0,2.0,9.0,5.0,2.0,1.0,72.0,2.0
-CZ,1378.0,6,5.0,2.0,2.0,8.0,9.0,6.0,3.0,1.0,54.0,1.0
-CZ,1379.0,6,6.0,3.0,3.0,3.0,10.0,7.0,4.0,1.0,58.0,1.0
-CZ,1380.0,6,5.0,3.0,3.0,3.0,5.0,6.0,3.0,2.0,53.0,1.0
-CZ,1381.0,6,5.0,5.0,5.0,4.0,6.0,5.0,2.0,2.0,39.0,1.0
-CZ,1382.0,6,1.0,8.0,8.0,9.0,6.0,2.0,2.0,2.0,44.0,1.0
-CZ,1383.0,6,5.0,4.0,4.0,6.0,10.0,7.0,4.0,1.0,57.0,1.0
-CZ,1384.0,6,7.0,5.0,5.0,5.0,9.0,7.0,3.0,2.0,69.0,2.0
-CZ,1385.0,6,6.0,6.0,8.0,8.0,10.0,7.0,3.0,1.0,23.0,2.0
-CZ,1386.0,6,7.0,3.0,7.0,6.0,,,2.0,1.0,52.0,1.0
-CZ,1387.0,6,7.0,4.0,6.0,4.0,9.0,4.0,2.0,2.0,58.0,1.0
-CZ,1388.0,6,6.0,5.0,7.0,8.0,,4.0,2.0,1.0,56.0,2.0
-CZ,1389.0,6,1.0,3.0,7.0,5.0,5.0,5.0,3.0,2.0,59.0,2.0
-CZ,1390.0,6,5.0,1.0,4.0,4.0,6.0,6.0,3.0,2.0,73.0,2.0
-CZ,1391.0,6,7.0,2.0,2.0,3.0,7.0,4.0,2.0,1.0,90.0,1.0
-CZ,1392.0,6,6.0,5.0,8.0,3.0,8.0,6.0,3.0,2.0,43.0,1.0
-CZ,1393.0,6,3.0,2.0,2.0,2.0,6.0,2.0,2.0,2.0,41.0,2.0
-CZ,1394.0,6,2.0,9.0,9.0,9.0,10.0,7.0,3.0,1.0,25.0,1.0
-CZ,1395.0,6,6.0,0.0,3.0,4.0,8.0,4.0,3.0,2.0,57.0,1.0
-CZ,1396.0,6,4.0,3.0,3.0,5.0,10.0,7.0,3.0,1.0,31.0,1.0
-CZ,1397.0,6,5.0,2.0,2.0,2.0,9.0,7.0,3.0,1.0,57.0,1.0
-CZ,1398.0,6,5.0,2.0,2.0,2.0,9.0,7.0,3.0,1.0,45.0,1.0
-CZ,1399.0,6,7.0,2.0,2.0,6.0,6.0,5.0,2.0,1.0,70.0,1.0
-CZ,1400.0,6,4.0,4.0,4.0,4.0,6.0,4.0,3.0,2.0,32.0,1.0
-CZ,1401.0,6,7.0,6.0,6.0,6.0,8.0,4.0,3.0,2.0,27.0,1.0
-CZ,1402.0,6,7.0,3.0,3.0,3.0,6.0,4.0,3.0,1.0,60.0,2.0
-CZ,1403.0,6,4.0,2.0,2.0,2.0,8.0,4.0,3.0,1.0,47.0,1.0
-CZ,1404.0,6,3.0,5.0,5.0,5.0,9.0,3.0,3.0,1.0,36.0,1.0
-CZ,1405.0,6,6.0,2.0,5.0,3.0,10.0,6.0,3.0,2.0,31.0,2.0
-CZ,1406.0,6,1.0,6.0,6.0,5.0,6.0,3.0,2.0,2.0,42.0,1.0
-CZ,1407.0,6,0.0,5.0,5.0,4.0,7.0,7.0,4.0,1.0,22.0,2.0
-CZ,1408.0,6,4.0,5.0,5.0,4.0,7.0,2.0,2.0,2.0,34.0,2.0
-CZ,1409.0,6,1.0,4.0,6.0,4.0,8.0,4.0,2.0,2.0,31.0,2.0
-CZ,1410.0,6,6.0,2.0,3.0,3.0,2.0,7.0,3.0,1.0,55.0,2.0
-CZ,1411.0,6,5.0,3.0,3.0,3.0,9.0,7.0,3.0,2.0,40.0,2.0
-CZ,1412.0,6,5.0,2.0,2.0,2.0,9.0,7.0,3.0,1.0,43.0,1.0
-CZ,1413.0,6,7.0,2.0,2.0,2.0,9.0,7.0,3.0,1.0,60.0,1.0
-CZ,1414.0,6,4.0,2.0,2.0,2.0,9.0,7.0,3.0,2.0,43.0,2.0
-CZ,1415.0,6,4.0,3.0,3.0,3.0,9.0,7.0,3.0,1.0,32.0,1.0
-CZ,1416.0,6,5.0,2.0,2.0,2.0,9.0,7.0,3.0,1.0,36.0,1.0
-CZ,1417.0,6,1.0,1.0,6.0,7.0,8.0,4.0,3.0,2.0,53.0,2.0
-CZ,1418.0,6,7.0,0.0,2.0,2.0,8.0,6.0,4.0,1.0,46.0,1.0
-CZ,1419.0,6,7.0,2.0,3.0,4.0,6.0,4.0,3.0,1.0,74.0,2.0
-CZ,1420.0,6,5.0,0.0,8.0,0.0,10.0,3.0,4.0,1.0,61.0,1.0
-CZ,1421.0,6,4.0,4.0,4.0,5.0,8.0,6.0,3.0,2.0,17.0,2.0
-CZ,1422.0,6,3.0,7.0,7.0,7.0,8.0,6.0,4.0,1.0,24.0,2.0
-CZ,1423.0,6,2.0,4.0,6.0,7.0,10.0,4.0,3.0,2.0,30.0,1.0
-CZ,1424.0,6,7.0,3.0,3.0,2.0,3.0,2.0,2.0,2.0,67.0,2.0
-CZ,1425.0,6,4.0,3.0,7.0,7.0,6.0,5.0,4.0,1.0,62.0,2.0
-CZ,1426.0,6,6.0,6.0,4.0,7.0,9.0,5.0,2.0,2.0,38.0,1.0
-CZ,1427.0,6,5.0,2.0,2.0,2.0,8.0,7.0,2.0,2.0,42.0,2.0
-CZ,1428.0,6,4.0,2.0,2.0,2.0,8.0,7.0,3.0,1.0,46.0,1.0
-CZ,1429.0,6,6.0,5.0,6.0,7.0,7.0,4.0,4.0,1.0,42.0,1.0
-CZ,1430.0,6,5.0,6.0,7.0,7.0,5.0,6.0,4.0,2.0,46.0,1.0
-CZ,1431.0,6,1.0,2.0,2.0,2.0,10.0,7.0,4.0,2.0,30.0,2.0
-CZ,1432.0,6,7.0,2.0,2.0,2.0,9.0,6.0,2.0,1.0,69.0,1.0
-CZ,1433.0,6,7.0,3.0,2.0,3.0,2.0,7.0,1.0,1.0,69.0,1.0
-CZ,1434.0,6,2.0,6.0,6.0,5.0,7.0,7.0,4.0,2.0,19.0,2.0
-CZ,1435.0,6,3.0,6.0,6.0,6.0,7.0,7.0,3.0,2.0,24.0,
-CZ,1436.0,6,1.0,6.0,6.0,4.0,7.0,6.0,3.0,1.0,30.0,2.0
-CZ,1437.0,6,4.0,1.0,2.0,1.0,9.0,5.0,2.0,2.0,27.0,2.0
-CZ,1438.0,6,6.0,4.0,3.0,3.0,9.0,6.0,2.0,2.0,51.0,1.0
-CZ,1439.0,6,7.0,0.0,2.0,2.0,5.0,2.0,2.0,1.0,,2.0
-CZ,1440.0,6,7.0,8.0,7.0,7.0,10.0,7.0,3.0,1.0,68.0,1.0
-CZ,1441.0,6,2.0,0.0,1.0,1.0,4.0,4.0,3.0,1.0,36.0,1.0
-CZ,1442.0,6,4.0,6.0,5.0,6.0,7.0,7.0,4.0,2.0,19.0,2.0
-CZ,1443.0,6,3.0,5.0,5.0,4.0,7.0,6.0,3.0,2.0,18.0,2.0
-CZ,1444.0,6,3.0,5.0,5.0,5.0,6.0,2.0,2.0,2.0,76.0,2.0
-CZ,1445.0,6,4.0,4.0,8.0,5.0,7.0,5.0,3.0,2.0,30.0,1.0
-CZ,1446.0,6,7.0,5.0,3.0,5.0,7.0,4.0,2.0,2.0,56.0,1.0
-CZ,1447.0,6,5.0,8.0,7.0,7.0,7.0,5.0,3.0,1.0,45.0,1.0
-CZ,1448.0,6,7.0,4.0,1.0,2.0,6.0,1.0,1.0,1.0,,2.0
-CZ,1449.0,6,3.0,3.0,5.0,6.0,7.0,4.0,1.0,1.0,34.0,1.0
-CZ,1450.0,6,3.0,5.0,5.0,5.0,7.0,5.0,4.0,1.0,53.0,2.0
-CZ,1451.0,6,7.0,2.0,3.0,3.0,4.0,3.0,3.0,2.0,65.0,1.0
-CZ,1452.0,6,7.0,5.0,7.0,7.0,9.0,7.0,3.0,2.0,16.0,2.0
-CZ,1453.0,6,7.0,3.0,5.0,5.0,2.0,1.0,3.0,1.0,67.0,2.0
-CZ,1454.0,6,7.0,9.0,9.0,9.0,9.0,6.0,4.0,2.0,26.0,2.0
-CZ,1455.0,6,7.0,6.0,5.0,4.0,4.0,1.0,,2.0,70.0,2.0
-CZ,1456.0,6,7.0,3.0,2.0,3.0,5.0,3.0,2.0,2.0,,2.0
-CZ,1457.0,6,7.0,4.0,5.0,5.0,9.0,7.0,3.0,2.0,17.0,2.0
-CZ,1458.0,6,7.0,4.0,5.0,1.0,7.0,5.0,3.0,2.0,29.0,1.0
-CZ,1459.0,6,7.0,0.0,3.0,5.0,8.0,4.0,3.0,1.0,36.0,2.0
-CZ,1460.0,6,3.0,4.0,5.0,7.0,8.0,6.0,4.0,1.0,18.0,2.0
-CZ,1461.0,6,5.0,7.0,8.0,7.0,10.0,6.0,5.0,2.0,53.0,1.0
-CZ,1462.0,6,7.0,3.0,7.0,4.0,9.0,7.0,2.0,2.0,63.0,2.0
-CZ,1463.0,6,5.0,8.0,6.0,8.0,7.0,4.0,3.0,1.0,40.0,2.0
-CZ,1464.0,6,7.0,7.0,8.0,8.0,7.0,6.0,3.0,2.0,38.0,1.0
-CZ,1465.0,6,3.0,7.0,5.0,6.0,8.0,6.0,5.0,2.0,65.0,2.0
-CZ,1466.0,6,5.0,3.0,4.0,4.0,7.0,5.0,3.0,2.0,47.0,1.0
-CZ,1468.0,6,6.0,8.0,3.0,5.0,7.0,7.0,1.0,2.0,44.0,2.0
-CZ,1469.0,6,2.0,6.0,5.0,6.0,7.0,6.0,3.0,2.0,44.0,1.0
-CZ,1470.0,6,4.0,6.0,6.0,5.0,7.0,4.0,2.0,1.0,53.0,1.0
-CZ,1471.0,6,7.0,2.0,0.0,0.0,3.0,4.0,1.0,2.0,56.0,2.0
-CZ,1472.0,6,5.0,2.0,1.0,1.0,,5.0,1.0,2.0,42.0,2.0
-CZ,1473.0,6,6.0,3.0,3.0,3.0,9.0,7.0,2.0,1.0,49.0,1.0
-CZ,1474.0,6,3.0,2.0,2.0,2.0,0.0,7.0,5.0,1.0,25.0,2.0
-CZ,1475.0,6,6.0,3.0,4.0,5.0,10.0,5.0,3.0,2.0,31.0,1.0
-CZ,1476.0,6,6.0,4.0,3.0,3.0,10.0,7.0,3.0,2.0,46.0,1.0
-CZ,1477.0,6,5.0,3.0,1.0,2.0,9.0,7.0,3.0,1.0,33.0,1.0
-CZ,1478.0,6,3.0,2.0,3.0,4.0,10.0,7.0,1.0,1.0,16.0,2.0
-CZ,1479.0,6,3.0,1.0,1.0,1.0,2.0,7.0,4.0,2.0,32.0,2.0
-CZ,1480.0,6,3.0,6.0,6.0,5.0,7.0,7.0,3.0,2.0,17.0,2.0
-CZ,1481.0,6,3.0,6.0,6.0,6.0,7.0,6.0,3.0,1.0,36.0,2.0
-CZ,1482.0,6,3.0,9.0,8.0,10.0,5.0,7.0,4.0,1.0,17.0,2.0
-CZ,1483.0,6,0.0,7.0,7.0,8.0,7.0,7.0,3.0,1.0,37.0,1.0
-CZ,1485.0,6,7.0,2.0,2.0,5.0,6.0,4.0,2.0,2.0,76.0,2.0
-CZ,1486.0,6,5.0,4.0,4.0,5.0,5.0,2.0,1.0,1.0,55.0,2.0
-CZ,1487.0,6,6.0,2.0,3.0,4.0,9.0,7.0,3.0,1.0,54.0,1.0
-CZ,1488.0,6,6.0,4.0,4.0,9.0,10.0,7.0,2.0,1.0,18.0,2.0
-CZ,1489.0,6,7.0,4.0,4.0,4.0,10.0,7.0,2.0,2.0,17.0,2.0
-CZ,1490.0,6,5.0,2.0,4.0,3.0,10.0,7.0,3.0,1.0,40.0,1.0
-CZ,1491.0,6,5.0,3.0,4.0,6.0,9.0,7.0,3.0,1.0,31.0,1.0
-CZ,1492.0,6,7.0,3.0,3.0,4.0,10.0,7.0,3.0,2.0,57.0,1.0
-CZ,1493.0,6,6.0,3.0,2.0,5.0,9.0,7.0,3.0,1.0,54.0,2.0
-CZ,1494.0,6,7.0,8.0,8.0,8.0,7.0,6.0,3.0,1.0,31.0,1.0
-CZ,1495.0,6,7.0,4.0,5.0,5.0,5.0,6.0,3.0,2.0,55.0,1.0
-CZ,1496.0,6,6.0,3.0,3.0,5.0,10.0,4.0,1.0,2.0,70.0,2.0
-CZ,1497.0,6,4.0,3.0,3.0,2.0,9.0,7.0,3.0,1.0,54.0,1.0
-CZ,1498.0,6,5.0,4.0,8.0,4.0,5.0,4.0,3.0,2.0,53.0,1.0
-CZ,1499.0,6,7.0,0.0,5.0,6.0,5.0,4.0,2.0,2.0,53.0,2.0
-CZ,1500.0,6,4.0,7.0,7.0,3.0,5.0,3.0,1.0,2.0,53.0,1.0
-CZ,1501.0,6,4.0,3.0,5.0,4.0,3.0,6.0,3.0,2.0,,2.0
-CZ,1502.0,6,7.0,0.0,3.0,4.0,10.0,2.0,2.0,2.0,24.0,1.0
-CZ,1503.0,6,6.0,2.0,4.0,3.0,5.0,2.0,2.0,1.0,31.0,1.0
-CZ,1504.0,6,5.0,8.0,5.0,9.0,9.0,7.0,3.0,1.0,33.0,1.0
-CZ,1505.0,6,6.0,4.0,3.0,3.0,9.0,7.0,3.0,1.0,50.0,1.0
-CZ,1506.0,6,5.0,3.0,5.0,5.0,9.0,7.0,3.0,1.0,42.0,1.0
-CZ,1507.0,6,6.0,4.0,3.0,4.0,8.0,3.0,2.0,1.0,73.0,1.0
-CZ,1508.0,6,7.0,0.0,2.0,2.0,0.0,1.0,1.0,2.0,36.0,2.0
-CZ,1509.0,6,5.0,9.0,8.0,8.0,7.0,3.0,3.0,1.0,50.0,1.0
-CZ,1510.0,6,4.0,8.0,8.0,7.0,8.0,4.0,3.0,1.0,44.0,1.0
-CZ,1511.0,6,2.0,4.0,5.0,3.0,7.0,5.0,2.0,1.0,35.0,1.0
-CZ,1512.0,6,7.0,5.0,5.0,5.0,5.0,5.0,2.0,1.0,34.0,1.0
-CZ,1550.0,6,5.0,0.0,5.0,4.0,2.0,4.0,4.0,1.0,78.0,1.0
-CZ,1551.0,6,5.0,2.0,7.0,8.0,9.0,2.0,3.0,2.0,64.0,1.0
-CZ,2001.0,6,7.0,5.0,4.0,4.0,3.0,4.0,2.0,2.0,61.0,1.0
-CZ,2002.0,6,7.0,5.0,6.0,6.0,9.0,2.0,2.0,2.0,50.0,1.0
-CZ,2003.0,6,3.0,3.0,1.0,1.0,7.0,4.0,3.0,2.0,17.0,2.0
-CZ,2004.0,6,3.0,1.0,0.0,0.0,8.0,3.0,3.0,2.0,26.0,1.0
-CZ,2005.0,6,7.0,3.0,5.0,2.0,8.0,6.0,2.0,2.0,83.0,2.0
-CZ,2006.0,6,7.0,3.0,3.0,5.0,7.0,6.0,4.0,1.0,67.0,1.0
-CZ,2007.0,6,5.0,0.0,5.0,0.0,10.0,3.0,1.0,2.0,70.0,2.0
-CZ,2008.0,6,7.0,4.0,4.0,6.0,7.0,4.0,3.0,2.0,32.0,1.0
-CZ,2009.0,6,6.0,3.0,4.0,5.0,7.0,4.0,3.0,1.0,45.0,1.0
-CZ,2010.0,6,7.0,4.0,5.0,3.0,3.0,6.0,2.0,2.0,74.0,2.0
-CZ,2011.0,6,6.0,5.0,5.0,5.0,9.0,3.0,3.0,1.0,63.0,1.0
-CZ,2012.0,6,4.0,4.0,4.0,5.0,3.0,2.0,2.0,1.0,40.0,1.0
-CZ,2013.0,6,7.0,7.0,5.0,5.0,8.0,3.0,4.0,2.0,60.0,1.0
-CZ,2014.0,6,6.0,8.0,8.0,7.0,9.0,4.0,3.0,2.0,38.0,1.0
-CZ,2015.0,6,7.0,0.0,5.0,0.0,3.0,7.0,1.0,2.0,59.0,2.0
-CZ,2016.0,6,6.0,4.0,3.0,8.0,8.0,6.0,3.0,1.0,33.0,2.0
-CZ,2017.0,6,4.0,5.0,5.0,5.0,6.0,4.0,3.0,2.0,75.0,2.0
-CZ,2018.0,6,7.0,3.0,3.0,1.0,5.0,5.0,1.0,1.0,70.0,1.0
-CZ,2019.0,6,4.0,3.0,5.0,2.0,7.0,6.0,3.0,1.0,64.0,1.0
-CZ,2020.0,6,1.0,8.0,1.0,4.0,9.0,7.0,4.0,1.0,19.0,2.0
-CZ,2021.0,6,4.0,8.0,7.0,6.0,9.0,5.0,2.0,2.0,35.0,1.0
-CZ,2022.0,6,6.0,3.0,3.0,4.0,8.0,3.0,2.0,2.0,56.0,1.0
-CZ,2023.0,6,4.0,3.0,4.0,3.0,8.0,1.0,1.0,2.0,75.0,2.0
-CZ,2024.0,6,6.0,5.0,7.0,5.0,4.0,6.0,3.0,2.0,32.0,2.0
-CZ,2025.0,6,7.0,2.0,5.0,4.0,7.0,6.0,3.0,2.0,21.0,2.0
-CZ,2026.0,6,6.0,2.0,6.0,7.0,8.0,5.0,2.0,2.0,63.0,1.0
-CZ,2027.0,6,6.0,8.0,8.0,8.0,7.0,5.0,4.0,2.0,47.0,1.0
-CZ,2028.0,6,2.0,4.0,2.0,4.0,10.0,2.0,3.0,2.0,37.0,2.0
-CZ,2029.0,6,7.0,7.0,7.0,5.0,7.0,4.0,2.0,1.0,43.0,1.0
-CZ,2030.0,6,7.0,8.0,8.0,3.0,5.0,4.0,1.0,1.0,54.0,1.0
-CZ,2031.0,6,7.0,3.0,5.0,3.0,6.0,4.0,1.0,2.0,54.0,1.0
-CZ,2032.0,6,3.0,2.0,3.0,3.0,5.0,3.0,1.0,2.0,79.0,2.0
-CZ,2033.0,6,5.0,4.0,4.0,5.0,9.0,4.0,1.0,1.0,37.0,1.0
-CZ,2034.0,6,5.0,0.0,5.0,5.0,5.0,3.0,3.0,2.0,33.0,1.0
-CZ,2035.0,6,3.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,23.0,2.0
-CZ,2036.0,6,4.0,6.0,2.0,2.0,7.0,3.0,,2.0,,1.0
-CZ,2037.0,6,7.0,5.0,5.0,8.0,9.0,5.0,3.0,2.0,36.0,1.0
-CZ,2038.0,6,6.0,5.0,6.0,3.0,6.0,5.0,3.0,1.0,39.0,1.0
-CZ,2039.0,6,7.0,3.0,3.0,4.0,4.0,5.0,3.0,2.0,48.0,1.0
-CZ,2040.0,6,3.0,4.0,5.0,8.0,3.0,2.0,2.0,1.0,30.0,2.0
-CZ,2041.0,6,5.0,3.0,7.0,7.0,7.0,6.0,2.0,1.0,37.0,1.0
-CZ,2042.0,6,6.0,7.0,9.0,10.0,6.0,5.0,3.0,1.0,18.0,2.0
-CZ,2043.0,6,5.0,0.0,9.0,7.0,7.0,7.0,5.0,2.0,16.0,2.0
-CZ,2044.0,6,7.0,0.0,2.0,2.0,5.0,7.0,2.0,2.0,55.0,1.0
-CZ,2045.0,6,5.0,6.0,7.0,6.0,6.0,3.0,3.0,2.0,91.0,2.0
-CZ,2046.0,6,7.0,3.0,4.0,4.0,8.0,4.0,3.0,1.0,71.0,1.0
-CZ,2047.0,6,7.0,6.0,6.0,6.0,5.0,5.0,2.0,2.0,67.0,2.0
-CZ,2048.0,6,7.0,4.0,4.0,7.0,7.0,2.0,1.0,1.0,75.0,2.0
-CZ,2049.0,6,4.0,3.0,4.0,3.0,7.0,6.0,2.0,1.0,48.0,1.0
-CZ,2050.0,6,7.0,6.0,8.0,7.0,7.0,4.0,3.0,1.0,58.0,1.0
-CZ,2051.0,6,7.0,7.0,8.0,7.0,5.0,6.0,3.0,2.0,70.0,1.0
-CZ,2052.0,6,7.0,5.0,5.0,6.0,5.0,6.0,4.0,2.0,37.0,2.0
-CZ,2053.0,6,7.0,2.0,5.0,3.0,4.0,4.0,2.0,1.0,65.0,1.0
-CZ,2054.0,6,7.0,6.0,6.0,7.0,8.0,6.0,2.0,1.0,29.0,1.0
-CZ,2055.0,6,4.0,7.0,5.0,5.0,7.0,6.0,3.0,1.0,29.0,2.0
-CZ,2056.0,6,0.0,4.0,5.0,2.0,3.0,4.0,1.0,1.0,74.0,1.0
-CZ,2057.0,6,7.0,4.0,5.0,4.0,6.0,6.0,3.0,2.0,39.0,1.0
-CZ,2058.0,6,7.0,4.0,5.0,5.0,8.0,3.0,3.0,1.0,38.0,1.0
-CZ,2059.0,6,4.0,8.0,9.0,3.0,8.0,6.0,3.0,2.0,28.0,2.0
-CZ,2060.0,6,5.0,7.0,7.0,3.0,7.0,6.0,3.0,1.0,64.0,1.0
-CZ,2061.0,6,2.0,4.0,5.0,5.0,5.0,6.0,3.0,2.0,38.0,1.0
-CZ,2062.0,6,7.0,3.0,3.0,5.0,6.0,3.0,3.0,1.0,68.0,1.0
-CZ,2063.0,6,6.0,3.0,6.0,8.0,7.0,5.0,3.0,2.0,59.0,2.0
-CZ,2064.0,6,7.0,5.0,7.0,0.0,7.0,4.0,2.0,1.0,50.0,2.0
-CZ,2065.0,6,7.0,4.0,5.0,2.0,7.0,6.0,3.0,2.0,,2.0
-CZ,2066.0,6,5.0,7.0,7.0,6.0,5.0,5.0,2.0,1.0,43.0,1.0
-CZ,2067.0,6,7.0,7.0,7.0,5.0,5.0,5.0,2.0,1.0,39.0,1.0
-CZ,2068.0,6,7.0,5.0,5.0,4.0,5.0,3.0,2.0,1.0,50.0,1.0
-CZ,2069.0,6,6.0,5.0,5.0,5.0,7.0,6.0,3.0,2.0,17.0,2.0
-CZ,2070.0,6,7.0,4.0,5.0,4.0,6.0,4.0,2.0,2.0,32.0,2.0
-CZ,2071.0,6,7.0,0.0,6.0,3.0,5.0,4.0,4.0,1.0,,1.0
-CZ,2072.0,6,5.0,3.0,6.0,5.0,4.0,6.0,2.0,1.0,59.0,1.0
-CZ,2073.0,6,5.0,3.0,7.0,4.0,7.0,4.0,3.0,1.0,40.0,1.0
-CZ,2074.0,6,7.0,3.0,7.0,8.0,7.0,6.0,4.0,1.0,68.0,1.0
-CZ,2075.0,6,4.0,8.0,2.0,6.0,8.0,5.0,3.0,1.0,40.0,1.0
-CZ,2076.0,6,7.0,7.0,7.0,4.0,7.0,4.0,2.0,2.0,43.0,2.0
-CZ,2077.0,6,3.0,5.0,9.0,8.0,8.0,7.0,1.0,1.0,35.0,1.0
-CZ,2078.0,6,5.0,6.0,7.0,7.0,8.0,6.0,2.0,2.0,79.0,2.0
-CZ,2079.0,6,6.0,2.0,1.0,5.0,10.0,3.0,4.0,2.0,62.0,1.0
-CZ,2080.0,6,7.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,19.0,2.0
-CZ,2081.0,6,7.0,4.0,6.0,3.0,7.0,6.0,2.0,2.0,33.0,1.0
-CZ,2082.0,6,6.0,6.0,7.0,7.0,8.0,4.0,3.0,2.0,27.0,1.0
-CZ,2083.0,6,6.0,5.0,7.0,7.0,7.0,4.0,3.0,2.0,36.0,2.0
-CZ,2084.0,6,3.0,5.0,5.0,5.0,5.0,6.0,4.0,1.0,27.0,2.0
-CZ,2085.0,6,5.0,5.0,5.0,6.0,5.0,5.0,3.0,2.0,49.0,2.0
-CZ,2086.0,6,6.0,1.0,1.0,2.0,4.0,2.0,2.0,1.0,53.0,1.0
-CZ,2087.0,6,7.0,3.0,4.0,3.0,5.0,6.0,2.0,2.0,37.0,2.0
-CZ,2088.0,6,7.0,3.0,6.0,6.0,6.0,7.0,2.0,2.0,44.0,2.0
-CZ,2089.0,6,5.0,1.0,1.0,0.0,7.0,1.0,,1.0,,1.0
-CZ,2090.0,6,3.0,2.0,2.0,3.0,5.0,2.0,3.0,2.0,19.0,2.0
-CZ,2091.0,6,7.0,8.0,10.0,10.0,7.0,5.0,3.0,2.0,18.0,2.0
-CZ,2092.0,6,6.0,8.0,8.0,6.0,8.0,3.0,3.0,1.0,50.0,1.0
-CZ,2093.0,6,7.0,7.0,5.0,3.0,5.0,6.0,4.0,1.0,48.0,1.0
-CZ,2094.0,6,7.0,9.0,10.0,10.0,8.0,6.0,2.0,2.0,68.0,1.0
-CZ,2095.0,6,0.0,5.0,5.0,3.0,5.0,2.0,3.0,2.0,40.0,2.0
-CZ,2096.0,6,4.0,7.0,7.0,4.0,9.0,7.0,3.0,1.0,18.0,2.0
-CZ,2097.0,6,6.0,,,,5.0,1.0,3.0,1.0,16.0,2.0
-CZ,2098.0,6,5.0,6.0,7.0,3.0,10.0,2.0,2.0,2.0,52.0,1.0
-CZ,2099.0,6,4.0,9.0,7.0,8.0,4.0,3.0,1.0,2.0,40.0,2.0
-CZ,2100.0,6,5.0,3.0,3.0,2.0,7.0,3.0,2.0,1.0,51.0,2.0
-CZ,2101.0,6,0.0,9.0,9.0,5.0,9.0,5.0,3.0,2.0,43.0,1.0
-CZ,2102.0,6,5.0,4.0,7.0,3.0,8.0,4.0,3.0,1.0,43.0,1.0
-CZ,2103.0,6,4.0,10.0,10.0,5.0,9.0,6.0,3.0,1.0,44.0,1.0
-CZ,2104.0,6,7.0,9.0,9.0,9.0,5.0,4.0,2.0,1.0,74.0,2.0
-CZ,2105.0,6,4.0,4.0,5.0,3.0,5.0,2.0,1.0,2.0,45.0,1.0
-CZ,2106.0,6,4.0,2.0,5.0,4.0,7.0,6.0,3.0,2.0,,2.0
-CZ,2107.0,6,7.0,6.0,7.0,3.0,7.0,5.0,2.0,1.0,28.0,2.0
-CZ,2108.0,6,7.0,9.0,9.0,9.0,8.0,5.0,4.0,1.0,73.0,1.0
-CZ,2109.0,6,5.0,8.0,8.0,4.0,9.0,4.0,3.0,2.0,47.0,1.0
-CZ,2110.0,6,5.0,5.0,5.0,6.0,8.0,5.0,3.0,1.0,54.0,1.0
-CZ,2111.0,6,7.0,5.0,5.0,5.0,5.0,6.0,1.0,1.0,56.0,1.0
-CZ,2112.0,6,0.0,3.0,9.0,0.0,9.0,4.0,3.0,2.0,58.0,1.0
-CZ,2113.0,6,5.0,3.0,3.0,3.0,8.0,4.0,4.0,1.0,37.0,2.0
-CZ,2114.0,6,6.0,0.0,0.0,2.0,6.0,3.0,4.0,2.0,,1.0
-CZ,2115.0,6,6.0,7.0,7.0,5.0,7.0,4.0,4.0,1.0,57.0,1.0
-CZ,2116.0,6,5.0,0.0,1.0,1.0,6.0,1.0,,1.0,,1.0
-CZ,2117.0,6,6.0,9.0,9.0,8.0,8.0,2.0,2.0,2.0,53.0,
-CZ,2118.0,6,7.0,,8.0,8.0,7.0,3.0,2.0,2.0,56.0,2.0
-CZ,2119.0,6,,6.0,6.0,6.0,,4.0,3.0,2.0,75.0,2.0
-CZ,2120.0,6,6.0,3.0,4.0,5.0,5.0,5.0,3.0,1.0,73.0,1.0
-CZ,2121.0,6,7.0,2.0,4.0,3.0,3.0,4.0,2.0,1.0,76.0,2.0
-CZ,2122.0,6,4.0,8.0,8.0,2.0,7.0,5.0,3.0,1.0,36.0,1.0
-CZ,2123.0,6,4.0,8.0,8.0,7.0,7.0,3.0,3.0,2.0,51.0,1.0
-CZ,2124.0,6,0.0,5.0,1.0,0.0,7.0,3.0,3.0,2.0,34.0,1.0
-CZ,2125.0,6,0.0,7.0,8.0,1.0,8.0,6.0,3.0,1.0,19.0,2.0
-CZ,2126.0,6,6.0,7.0,7.0,4.0,9.0,3.0,1.0,2.0,33.0,1.0
-CZ,2127.0,6,6.0,4.0,7.0,3.0,7.0,4.0,3.0,1.0,56.0,1.0
-CZ,2128.0,6,7.0,0.0,1.0,2.0,2.0,2.0,2.0,2.0,63.0,1.0
-CZ,2129.0,6,7.0,5.0,5.0,5.0,5.0,4.0,2.0,1.0,50.0,2.0
-CZ,2130.0,6,7.0,4.0,4.0,4.0,5.0,2.0,1.0,2.0,69.0,1.0
-CZ,2131.0,6,5.0,6.0,6.0,5.0,8.0,5.0,2.0,1.0,23.0,2.0
-CZ,2132.0,6,7.0,7.0,7.0,4.0,7.0,5.0,1.0,1.0,25.0,1.0
-CZ,2133.0,6,4.0,3.0,4.0,5.0,6.0,1.0,2.0,2.0,33.0,1.0
-CZ,2134.0,6,5.0,4.0,1.0,3.0,2.0,6.0,3.0,2.0,26.0,1.0
-CZ,2135.0,6,7.0,0.0,5.0,2.0,4.0,5.0,1.0,2.0,32.0,1.0
-CZ,2136.0,6,6.0,8.0,8.0,9.0,6.0,5.0,1.0,2.0,69.0,2.0
-CZ,2137.0,6,7.0,6.0,6.0,3.0,7.0,2.0,1.0,1.0,36.0,1.0
-CZ,2138.0,6,6.0,5.0,6.0,6.0,9.0,2.0,2.0,2.0,34.0,1.0
-CZ,2139.0,6,7.0,8.0,8.0,5.0,8.0,4.0,4.0,1.0,71.0,2.0
-CZ,2140.0,6,1.0,9.0,7.0,5.0,10.0,6.0,3.0,2.0,19.0,2.0
-CZ,2141.0,6,6.0,7.0,7.0,6.0,7.0,5.0,2.0,1.0,63.0,1.0
-CZ,2142.0,6,4.0,8.0,8.0,7.0,7.0,6.0,2.0,1.0,62.0,1.0
-CZ,2143.0,6,7.0,0.0,1.0,1.0,5.0,5.0,2.0,2.0,55.0,2.0
-CZ,2144.0,6,4.0,5.0,5.0,4.0,10.0,5.0,3.0,2.0,39.0,1.0
-CZ,2145.0,6,7.0,6.0,6.0,4.0,6.0,5.0,1.0,2.0,52.0,2.0
-CZ,2146.0,6,7.0,5.0,5.0,5.0,3.0,3.0,1.0,2.0,58.0,2.0
-CZ,2147.0,6,6.0,3.0,5.0,4.0,10.0,4.0,3.0,1.0,63.0,1.0
-CZ,2148.0,6,3.0,9.0,7.0,5.0,8.0,5.0,1.0,1.0,48.0,1.0
-CZ,2149.0,6,5.0,0.0,2.0,0.0,3.0,2.0,1.0,2.0,49.0,1.0
-CZ,2150.0,6,4.0,4.0,4.0,4.0,8.0,4.0,2.0,2.0,40.0,1.0
-CZ,2151.0,6,5.0,4.0,4.0,5.0,9.0,5.0,3.0,2.0,60.0,2.0
-CZ,1001.0,7,5.0,3.0,3.0,2.0,7.0,4.0,4.0,2.0,71.0,2.0
-CZ,1002.0,7,5.0,5.0,7.0,3.0,5.0,5.0,1.0,2.0,52.0,1.0
-CZ,1003.0,7,7.0,5.0,4.0,3.0,6.0,4.0,3.0,1.0,55.0,2.0
-CZ,1004.0,7,7.0,5.0,5.0,3.0,7.0,4.0,3.0,1.0,64.0,1.0
-CZ,1005.0,7,3.0,4.0,5.0,5.0,6.0,5.0,3.0,1.0,59.0,1.0
-CZ,1006.0,7,7.0,4.0,4.0,4.0,7.0,6.0,3.0,2.0,62.0,2.0
-CZ,1007.0,7,3.0,5.0,5.0,6.0,5.0,4.0,3.0,2.0,49.0,2.0
-CZ,1008.0,7,7.0,7.0,5.0,3.0,8.0,3.0,2.0,2.0,64.0,2.0
-CZ,1009.0,7,6.0,2.0,2.0,1.0,7.0,5.0,2.0,1.0,40.0,1.0
-CZ,1010.0,7,1.0,4.0,5.0,5.0,7.0,4.0,3.0,1.0,45.0,1.0
-CZ,1011.0,7,1.0,6.0,3.0,5.0,3.0,3.0,3.0,1.0,41.0,1.0
-CZ,1012.0,7,1.0,4.0,6.0,5.0,5.0,4.0,2.0,1.0,48.0,1.0
-CZ,1013.0,7,1.0,5.0,4.0,4.0,4.0,3.0,2.0,1.0,40.0,1.0
-CZ,1014.0,7,1.0,4.0,5.0,3.0,4.0,3.0,3.0,1.0,55.0,1.0
-CZ,1015.0,7,2.0,8.0,4.0,3.0,5.0,3.0,2.0,2.0,40.0,2.0
-CZ,1016.0,7,1.0,5.0,5.0,5.0,4.0,4.0,3.0,2.0,47.0,1.0
-CZ,1017.0,7,2.0,6.0,7.0,5.0,4.0,3.0,2.0,1.0,50.0,1.0
-CZ,1018.0,7,4.0,6.0,5.0,6.0,8.0,3.0,3.0,2.0,42.0,1.0
-CZ,1019.0,7,4.0,2.0,5.0,5.0,6.0,4.0,2.0,2.0,45.0,1.0
-CZ,1020.0,7,4.0,3.0,4.0,4.0,7.0,4.0,3.0,1.0,35.0,1.0
-CZ,1021.0,7,4.0,5.0,7.0,6.0,7.0,4.0,3.0,2.0,41.0,1.0
-CZ,1022.0,7,7.0,8.0,6.0,6.0,8.0,5.0,3.0,2.0,45.0,1.0
-CZ,1023.0,7,6.0,7.0,6.0,4.0,5.0,3.0,1.0,1.0,61.0,1.0
-CZ,1024.0,7,4.0,7.0,3.0,6.0,5.0,4.0,3.0,2.0,28.0,1.0
-CZ,1025.0,7,4.0,6.0,7.0,5.0,8.0,6.0,4.0,1.0,64.0,2.0
-CZ,1026.0,7,5.0,3.0,7.0,0.0,7.0,6.0,3.0,2.0,58.0,1.0
-CZ,1028.0,7,4.0,8.0,7.0,3.0,9.0,7.0,3.0,2.0,18.0,2.0
-CZ,1029.0,7,2.0,5.0,5.0,5.0,9.0,7.0,1.0,2.0,17.0,2.0
-CZ,1030.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,1.0,,1.0
-CZ,1031.0,7,2.0,0.0,8.0,3.0,8.0,2.0,1.0,2.0,52.0,1.0
-CZ,1032.0,7,5.0,0.0,5.0,1.0,5.0,1.0,1.0,2.0,71.0,2.0
-CZ,1033.0,7,3.0,2.0,8.0,5.0,9.0,2.0,3.0,2.0,36.0,1.0
-CZ,1034.0,7,6.0,6.0,7.0,4.0,9.0,3.0,3.0,1.0,49.0,1.0
-CZ,1035.0,7,4.0,4.0,7.0,5.0,8.0,2.0,3.0,1.0,61.0,1.0
-CZ,1036.0,7,7.0,2.0,5.0,0.0,,4.0,2.0,2.0,18.0,2.0
-CZ,1037.0,7,7.0,0.0,10.0,0.0,8.0,4.0,3.0,2.0,62.0,2.0
-CZ,1038.0,7,4.0,1.0,3.0,1.0,7.0,4.0,3.0,1.0,50.0,1.0
-CZ,1039.0,7,7.0,5.0,5.0,5.0,8.0,5.0,2.0,1.0,,1.0
-CZ,1040.0,7,5.0,7.0,7.0,6.0,,5.0,3.0,2.0,42.0,1.0
-CZ,1041.0,7,6.0,6.0,5.0,5.0,9.0,6.0,3.0,2.0,50.0,1.0
-CZ,1042.0,7,4.0,7.0,3.0,7.0,8.0,2.0,2.0,2.0,42.0,
-CZ,1043.0,7,4.0,3.0,3.0,2.0,7.0,1.0,1.0,1.0,59.0,1.0
-CZ,1044.0,7,4.0,7.0,6.0,9.0,5.0,1.0,1.0,1.0,52.0,2.0
-CZ,1045.0,7,7.0,1.0,1.0,1.0,7.0,2.0,3.0,2.0,57.0,1.0
-CZ,1046.0,7,6.0,7.0,6.0,5.0,9.0,,1.0,1.0,71.0,1.0
-CZ,1047.0,7,5.0,8.0,8.0,6.0,10.0,6.0,3.0,1.0,18.0,2.0
-CZ,1048.0,7,6.0,4.0,7.0,8.0,9.0,,1.0,2.0,65.0,1.0
-CZ,1049.0,7,5.0,7.0,5.0,1.0,8.0,6.0,3.0,1.0,20.0,2.0
-CZ,1050.0,7,6.0,9.0,8.0,8.0,7.0,5.0,2.0,2.0,24.0,1.0
-CZ,1051.0,7,3.0,8.0,8.0,6.0,8.0,4.0,4.0,1.0,39.0,
-CZ,1052.0,7,2.0,0.0,2.0,2.0,7.0,5.0,3.0,2.0,35.0,1.0
-CZ,1053.0,7,5.0,3.0,3.0,4.0,9.0,4.0,2.0,2.0,56.0,2.0
-CZ,1054.0,7,4.0,1.0,3.0,1.0,9.0,4.0,3.0,1.0,51.0,1.0
-CZ,1055.0,7,3.0,0.0,0.0,0.0,9.0,5.0,4.0,1.0,19.0,2.0
-CZ,1056.0,7,6.0,3.0,4.0,8.0,9.0,5.0,2.0,2.0,68.0,2.0
-CZ,1057.0,7,5.0,6.0,7.0,6.0,8.0,4.0,3.0,1.0,42.0,1.0
-CZ,1058.0,7,6.0,5.0,3.0,5.0,8.0,4.0,3.0,2.0,65.0,1.0
-CZ,1059.0,7,6.0,4.0,5.0,4.0,9.0,5.0,2.0,1.0,,2.0
-CZ,1060.0,7,6.0,2.0,4.0,4.0,5.0,5.0,1.0,2.0,51.0,2.0
-CZ,1061.0,7,7.0,2.0,2.0,2.0,3.0,6.0,4.0,1.0,74.0,2.0
-CZ,1062.0,7,3.0,6.0,4.0,5.0,3.0,7.0,3.0,2.0,80.0,2.0
-CZ,1063.0,7,6.0,3.0,5.0,3.0,5.0,6.0,4.0,2.0,67.0,1.0
-CZ,1064.0,7,5.0,3.0,6.0,7.0,8.0,4.0,4.0,1.0,59.0,1.0
-CZ,1065.0,7,7.0,6.0,6.0,3.0,10.0,5.0,3.0,1.0,76.0,1.0
-CZ,1066.0,7,2.0,2.0,5.0,5.0,7.0,4.0,2.0,1.0,54.0,1.0
-CZ,1067.0,7,7.0,4.0,4.0,5.0,9.0,6.0,3.0,1.0,,2.0
-CZ,1068.0,7,6.0,8.0,9.0,9.0,2.0,4.0,1.0,2.0,58.0,2.0
-CZ,1069.0,7,6.0,5.0,5.0,6.0,9.0,6.0,3.0,2.0,58.0,1.0
-CZ,1070.0,7,6.0,5.0,5.0,5.0,8.0,5.0,3.0,1.0,,1.0
-CZ,1071.0,7,0.0,8.0,9.0,7.0,8.0,6.0,3.0,1.0,22.0,2.0
-CZ,1072.0,7,3.0,5.0,5.0,3.0,8.0,5.0,3.0,2.0,59.0,1.0
-CZ,1073.0,7,7.0,3.0,7.0,2.0,8.0,5.0,4.0,1.0,63.0,1.0
-CZ,1074.0,7,3.0,0.0,2.0,4.0,9.0,4.0,3.0,2.0,17.0,2.0
-CZ,1075.0,7,2.0,5.0,7.0,3.0,8.0,6.0,3.0,1.0,57.0,1.0
-CZ,1076.0,7,6.0,5.0,5.0,7.0,9.0,4.0,3.0,1.0,75.0,1.0
-CZ,1077.0,7,4.0,5.0,8.0,2.0,8.0,4.0,4.0,1.0,44.0,1.0
-CZ,1078.0,7,4.0,8.0,8.0,5.0,8.0,5.0,4.0,1.0,59.0,2.0
-CZ,1079.0,7,6.0,7.0,3.0,5.0,8.0,6.0,4.0,1.0,64.0,1.0
-CZ,1080.0,7,6.0,2.0,5.0,4.0,9.0,6.0,4.0,2.0,62.0,1.0
-CZ,1081.0,7,6.0,3.0,2.0,2.0,8.0,6.0,4.0,2.0,51.0,1.0
-CZ,1082.0,7,4.0,6.0,6.0,6.0,9.0,5.0,3.0,2.0,40.0,1.0
-CZ,1083.0,7,6.0,3.0,4.0,4.0,6.0,6.0,3.0,1.0,45.0,1.0
-CZ,1084.0,7,4.0,7.0,8.0,7.0,7.0,5.0,2.0,2.0,34.0,2.0
-CZ,1085.0,7,7.0,3.0,3.0,3.0,5.0,5.0,3.0,1.0,60.0,1.0
-CZ,1086.0,7,7.0,4.0,5.0,5.0,6.0,4.0,3.0,1.0,23.0,2.0
-CZ,1087.0,7,5.0,6.0,5.0,4.0,7.0,3.0,3.0,2.0,59.0,1.0
-CZ,1088.0,7,4.0,3.0,2.0,1.0,7.0,4.0,2.0,1.0,42.0,1.0
-CZ,1089.0,7,3.0,8.0,9.0,9.0,8.0,4.0,2.0,2.0,44.0,1.0
-CZ,1090.0,7,6.0,5.0,5.0,5.0,9.0,6.0,2.0,2.0,65.0,2.0
-CZ,1091.0,7,6.0,5.0,4.0,6.0,8.0,5.0,3.0,2.0,67.0,1.0
-CZ,1092.0,7,6.0,4.0,5.0,5.0,9.0,5.0,3.0,2.0,64.0,1.0
-CZ,1093.0,7,3.0,4.0,4.0,3.0,9.0,6.0,4.0,2.0,24.0,2.0
-CZ,1094.0,7,2.0,6.0,3.0,5.0,7.0,6.0,2.0,2.0,33.0,2.0
-CZ,1095.0,7,7.0,2.0,1.0,3.0,6.0,3.0,3.0,2.0,18.0,2.0
-CZ,1096.0,7,6.0,2.0,1.0,0.0,8.0,6.0,4.0,2.0,45.0,1.0
-CZ,1097.0,7,6.0,3.0,4.0,2.0,9.0,5.0,4.0,1.0,47.0,1.0
-CZ,1098.0,7,3.0,5.0,4.0,4.0,9.0,4.0,3.0,1.0,54.0,1.0
-CZ,1099.0,7,3.0,4.0,6.0,4.0,9.0,5.0,4.0,2.0,20.0,2.0
-CZ,1100.0,7,7.0,0.0,0.0,0.0,8.0,4.0,2.0,2.0,43.0,1.0
-CZ,1101.0,7,5.0,4.0,7.0,4.0,10.0,3.0,2.0,1.0,39.0,1.0
-CZ,1102.0,7,5.0,7.0,7.0,6.0,8.0,7.0,4.0,2.0,17.0,2.0
-CZ,1103.0,7,7.0,5.0,8.0,5.0,9.0,4.0,3.0,1.0,22.0,2.0
-CZ,1104.0,7,5.0,0.0,4.0,0.0,7.0,4.0,1.0,2.0,61.0,2.0
-CZ,1105.0,7,2.0,0.0,3.0,1.0,9.0,5.0,3.0,2.0,34.0,1.0
-CZ,1106.0,7,5.0,1.0,2.0,2.0,8.0,6.0,2.0,2.0,27.0,1.0
-CZ,1107.0,7,4.0,1.0,1.0,1.0,9.0,4.0,4.0,1.0,20.0,2.0
-CZ,1108.0,7,4.0,5.0,5.0,2.0,8.0,3.0,2.0,2.0,49.0,1.0
-CZ,1109.0,7,4.0,7.0,7.0,9.0,,3.0,2.0,1.0,44.0,1.0
-CZ,1110.0,7,7.0,4.0,5.0,3.0,8.0,5.0,3.0,2.0,63.0,1.0
-CZ,1111.0,7,4.0,5.0,3.0,1.0,8.0,5.0,3.0,2.0,40.0,1.0
-CZ,1114.0,7,5.0,5.0,0.0,0.0,8.0,5.0,3.0,1.0,42.0,1.0
-CZ,1116.0,7,7.0,5.0,3.0,3.0,8.0,5.0,3.0,2.0,65.0,1.0
-CZ,1117.0,7,4.0,2.0,3.0,4.0,8.0,5.0,2.0,2.0,60.0,1.0
-CZ,1118.0,7,6.0,3.0,5.0,5.0,9.0,6.0,4.0,2.0,50.0,2.0
-CZ,1119.0,7,6.0,0.0,5.0,5.0,9.0,5.0,3.0,1.0,34.0,1.0
-CZ,1120.0,7,2.0,0.0,2.0,3.0,8.0,4.0,3.0,2.0,28.0,2.0
-CZ,1121.0,7,4.0,4.0,3.0,3.0,9.0,5.0,3.0,2.0,62.0,1.0
-CZ,1122.0,7,4.0,3.0,3.0,2.0,7.0,5.0,2.0,2.0,32.0,1.0
-CZ,1123.0,7,5.0,3.0,3.0,2.0,8.0,5.0,3.0,1.0,61.0,1.0
-CZ,1124.0,7,7.0,5.0,5.0,4.0,7.0,3.0,3.0,2.0,46.0,1.0
-CZ,1125.0,7,2.0,2.0,4.0,4.0,9.0,7.0,4.0,2.0,70.0,2.0
-CZ,1126.0,7,5.0,9.0,8.0,8.0,8.0,2.0,3.0,2.0,37.0,1.0
-CZ,1127.0,7,7.0,2.0,3.0,2.0,7.0,6.0,2.0,1.0,65.0,1.0
-CZ,1128.0,7,5.0,4.0,2.0,4.0,7.0,5.0,3.0,2.0,61.0,1.0
-CZ,1129.0,7,7.0,0.0,2.0,5.0,8.0,4.0,3.0,1.0,34.0,1.0
-CZ,1130.0,7,4.0,7.0,3.0,3.0,9.0,5.0,2.0,1.0,61.0,1.0
-CZ,1131.0,7,3.0,2.0,4.0,4.0,3.0,2.0,2.0,1.0,45.0,1.0
-CZ,1132.0,7,4.0,2.0,5.0,4.0,9.0,6.0,5.0,1.0,70.0,1.0
-CZ,1133.0,7,7.0,6.0,7.0,5.0,8.0,4.0,2.0,1.0,80.0,2.0
-CZ,1134.0,7,5.0,3.0,5.0,5.0,8.0,4.0,3.0,2.0,20.0,2.0
-CZ,1135.0,7,6.0,3.0,4.0,4.0,9.0,4.0,3.0,1.0,49.0,1.0
-CZ,1136.0,7,5.0,0.0,3.0,0.0,5.0,5.0,4.0,1.0,30.0,1.0
-CZ,1137.0,7,7.0,3.0,3.0,3.0,7.0,6.0,3.0,1.0,26.0,2.0
-CZ,1138.0,7,5.0,2.0,3.0,3.0,7.0,6.0,3.0,1.0,31.0,2.0
-CZ,1139.0,7,5.0,5.0,5.0,3.0,5.0,5.0,3.0,2.0,30.0,2.0
-CZ,1140.0,7,4.0,2.0,3.0,3.0,8.0,6.0,3.0,2.0,26.0,2.0
-CZ,1141.0,7,4.0,9.0,8.0,5.0,8.0,3.0,,2.0,65.0,2.0
-CZ,1142.0,7,5.0,4.0,5.0,3.0,3.0,3.0,1.0,1.0,50.0,2.0
-CZ,1143.0,7,5.0,2.0,4.0,5.0,7.0,2.0,1.0,2.0,72.0,1.0
-CZ,1144.0,7,3.0,7.0,7.0,6.0,5.0,6.0,3.0,2.0,54.0,1.0
-CZ,1145.0,7,3.0,5.0,3.0,5.0,5.0,4.0,2.0,2.0,37.0,1.0
-CZ,1146.0,7,0.0,6.0,6.0,3.0,8.0,4.0,3.0,1.0,33.0,
-CZ,1147.0,7,0.0,7.0,6.0,6.0,4.0,1.0,1.0,1.0,39.0,2.0
-CZ,1148.0,7,2.0,9.0,9.0,9.0,7.0,1.0,3.0,1.0,17.0,2.0
-CZ,1149.0,7,4.0,6.0,7.0,6.0,4.0,3.0,3.0,2.0,45.0,1.0
-CZ,1150.0,7,7.0,6.0,7.0,4.0,6.0,2.0,3.0,2.0,75.0,1.0
-CZ,1151.0,7,3.0,1.0,5.0,5.0,5.0,4.0,1.0,2.0,42.0,2.0
-CZ,1152.0,7,4.0,4.0,4.0,5.0,7.0,4.0,2.0,1.0,48.0,1.0
-CZ,1153.0,7,5.0,1.0,5.0,3.0,6.0,4.0,3.0,2.0,58.0,1.0
-CZ,1154.0,7,4.0,2.0,5.0,4.0,7.0,2.0,3.0,1.0,44.0,1.0
-CZ,1155.0,7,4.0,6.0,6.0,5.0,5.0,5.0,3.0,2.0,57.0,2.0
-CZ,1156.0,7,1.0,8.0,10.0,6.0,10.0,7.0,3.0,2.0,18.0,1.0
-CZ,1157.0,7,7.0,3.0,6.0,3.0,8.0,6.0,3.0,1.0,44.0,1.0
-CZ,1158.0,7,2.0,8.0,7.0,8.0,8.0,4.0,3.0,1.0,50.0,1.0
-CZ,1159.0,7,2.0,7.0,7.0,7.0,8.0,2.0,2.0,2.0,45.0,1.0
-CZ,1160.0,7,7.0,4.0,7.0,7.0,9.0,4.0,3.0,1.0,35.0,1.0
-CZ,1161.0,7,0.0,10.0,10.0,10.0,9.0,1.0,3.0,1.0,16.0,2.0
-CZ,1162.0,7,5.0,3.0,4.0,3.0,6.0,2.0,2.0,2.0,37.0,1.0
-CZ,1163.0,7,3.0,5.0,5.0,5.0,6.0,3.0,3.0,1.0,44.0,1.0
-CZ,1164.0,7,4.0,1.0,1.0,1.0,,4.0,3.0,1.0,44.0,1.0
-CZ,1165.0,7,4.0,4.0,4.0,4.0,3.0,3.0,2.0,1.0,40.0,1.0
-CZ,1166.0,7,6.0,7.0,6.0,6.0,7.0,2.0,2.0,1.0,40.0,1.0
-CZ,1167.0,7,4.0,4.0,6.0,6.0,6.0,3.0,3.0,1.0,34.0,1.0
-CZ,1168.0,7,4.0,4.0,5.0,5.0,5.0,2.0,1.0,2.0,43.0,1.0
-CZ,1169.0,7,6.0,6.0,6.0,,7.0,3.0,2.0,2.0,35.0,1.0
-CZ,1170.0,7,5.0,4.0,5.0,6.0,5.0,2.0,2.0,2.0,38.0,1.0
-CZ,1171.0,7,5.0,4.0,5.0,6.0,6.0,3.0,3.0,1.0,45.0,1.0
-CZ,1172.0,7,5.0,3.0,3.0,3.0,3.0,3.0,3.0,1.0,43.0,1.0
-CZ,1173.0,7,7.0,2.0,4.0,5.0,6.0,5.0,3.0,2.0,68.0,2.0
-CZ,1174.0,7,2.0,3.0,4.0,3.0,5.0,5.0,2.0,1.0,43.0,1.0
-CZ,1175.0,7,3.0,5.0,5.0,8.0,5.0,4.0,3.0,1.0,75.0,1.0
-CZ,1176.0,7,2.0,7.0,7.0,3.0,8.0,6.0,3.0,2.0,43.0,2.0
-CZ,1177.0,7,2.0,6.0,7.0,8.0,7.0,4.0,3.0,2.0,41.0,1.0
-CZ,1178.0,7,0.0,3.0,6.0,3.0,7.0,3.0,2.0,1.0,23.0,2.0
-CZ,1179.0,7,1.0,4.0,5.0,7.0,10.0,4.0,3.0,1.0,53.0,1.0
-CZ,1180.0,7,7.0,4.0,10.0,6.0,5.0,5.0,3.0,2.0,69.0,2.0
-CZ,1181.0,7,2.0,7.0,7.0,6.0,9.0,6.0,4.0,2.0,29.0,2.0
-CZ,1182.0,7,4.0,5.0,6.0,6.0,8.0,6.0,4.0,1.0,41.0,1.0
-CZ,1183.0,7,4.0,8.0,9.0,4.0,6.0,4.0,2.0,2.0,76.0,1.0
-CZ,1184.0,7,6.0,7.0,8.0,9.0,6.0,4.0,2.0,2.0,55.0,2.0
-CZ,1185.0,7,4.0,1.0,2.0,3.0,7.0,6.0,3.0,1.0,34.0,1.0
-CZ,1186.0,7,6.0,8.0,9.0,7.0,6.0,3.0,2.0,1.0,46.0,1.0
-CZ,1187.0,7,7.0,5.0,5.0,5.0,7.0,2.0,1.0,1.0,,1.0
-CZ,1188.0,7,5.0,6.0,7.0,6.0,8.0,3.0,1.0,1.0,,1.0
-CZ,1189.0,7,7.0,5.0,6.0,6.0,6.0,1.0,3.0,1.0,65.0,1.0
-CZ,1190.0,7,6.0,3.0,3.0,3.0,6.0,4.0,3.0,1.0,46.0,1.0
-CZ,1191.0,7,4.0,6.0,7.0,7.0,5.0,4.0,3.0,2.0,21.0,2.0
-CZ,1192.0,7,5.0,6.0,6.0,5.0,6.0,2.0,3.0,1.0,60.0,1.0
-CZ,1193.0,7,4.0,6.0,5.0,5.0,7.0,2.0,3.0,1.0,,1.0
-CZ,1194.0,7,4.0,4.0,4.0,4.0,7.0,2.0,3.0,1.0,54.0,1.0
-CZ,1195.0,7,5.0,2.0,3.0,5.0,7.0,2.0,3.0,1.0,50.0,1.0
-CZ,1196.0,7,6.0,2.0,3.0,4.0,5.0,5.0,3.0,1.0,24.0,2.0
-CZ,1197.0,7,4.0,1.0,1.0,2.0,9.0,6.0,2.0,2.0,34.0,1.0
-CZ,1198.0,7,1.0,9.0,8.0,7.0,9.0,6.0,1.0,2.0,43.0,2.0
-CZ,1199.0,7,6.0,4.0,7.0,2.0,5.0,3.0,1.0,1.0,,1.0
-CZ,1200.0,7,5.0,5.0,6.0,6.0,3.0,6.0,2.0,2.0,47.0,2.0
-CZ,1201.0,7,2.0,7.0,8.0,8.0,9.0,6.0,2.0,1.0,42.0,2.0
-CZ,1202.0,7,7.0,3.0,3.0,10.0,5.0,2.0,2.0,1.0,48.0,1.0
-CZ,1203.0,7,2.0,8.0,8.0,6.0,9.0,4.0,4.0,1.0,81.0,1.0
-CZ,1204.0,7,7.0,5.0,5.0,0.0,9.0,7.0,1.0,2.0,41.0,1.0
-CZ,1205.0,7,7.0,8.0,9.0,3.0,7.0,6.0,3.0,1.0,37.0,2.0
-CZ,1206.0,7,4.0,4.0,4.0,4.0,10.0,2.0,3.0,1.0,41.0,1.0
-CZ,1207.0,7,6.0,7.0,7.0,7.0,3.0,1.0,2.0,,65.0,2.0
-CZ,1208.0,7,1.0,6.0,5.0,6.0,6.0,1.0,3.0,1.0,17.0,2.0
-CZ,1209.0,7,3.0,8.0,8.0,9.0,8.0,3.0,3.0,2.0,47.0,1.0
-CZ,1210.0,7,0.0,4.0,4.0,4.0,5.0,5.0,3.0,1.0,58.0,2.0
-CZ,1211.0,7,7.0,4.0,6.0,6.0,6.0,1.0,2.0,2.0,75.0,1.0
-CZ,1212.0,7,0.0,6.0,6.0,4.0,8.0,4.0,2.0,1.0,30.0,
-CZ,1213.0,7,0.0,7.0,8.0,7.0,10.0,4.0,1.0,2.0,43.0,1.0
-CZ,1214.0,7,5.0,5.0,3.0,5.0,8.0,5.0,2.0,2.0,53.0,1.0
-CZ,1215.0,7,4.0,8.0,7.0,3.0,10.0,7.0,3.0,2.0,24.0,1.0
-CZ,1216.0,7,3.0,7.0,8.0,2.0,8.0,4.0,3.0,1.0,36.0,1.0
-CZ,1217.0,7,7.0,5.0,5.0,5.0,6.0,3.0,3.0,1.0,46.0,1.0
-CZ,1218.0,7,7.0,2.0,3.0,3.0,8.0,4.0,2.0,2.0,62.0,1.0
-CZ,1219.0,7,7.0,4.0,5.0,5.0,7.0,4.0,3.0,2.0,20.0,2.0
-CZ,1220.0,7,5.0,5.0,6.0,5.0,8.0,5.0,3.0,1.0,36.0,1.0
-CZ,1221.0,7,7.0,2.0,3.0,3.0,3.0,3.0,3.0,1.0,25.0,2.0
-CZ,1222.0,7,4.0,4.0,5.0,5.0,6.0,3.0,3.0,1.0,45.0,1.0
-CZ,1223.0,7,5.0,8.0,8.0,8.0,7.0,1.0,3.0,2.0,56.0,1.0
-CZ,1224.0,7,2.0,6.0,6.0,6.0,6.0,1.0,3.0,2.0,40.0,1.0
-CZ,1225.0,7,0.0,7.0,8.0,8.0,5.0,5.0,4.0,1.0,64.0,2.0
-CZ,1226.0,7,1.0,8.0,9.0,9.0,9.0,4.0,3.0,1.0,29.0,1.0
-CZ,1227.0,7,4.0,4.0,5.0,5.0,3.0,3.0,1.0,2.0,42.0,2.0
-CZ,1228.0,7,3.0,8.0,8.0,7.0,6.0,6.0,3.0,2.0,50.0,1.0
-CZ,1229.0,7,0.0,5.0,5.0,5.0,5.0,5.0,3.0,1.0,18.0,2.0
-CZ,1230.0,7,4.0,5.0,8.0,2.0,8.0,5.0,3.0,1.0,46.0,2.0
-CZ,1231.0,7,5.0,7.0,8.0,2.0,9.0,6.0,3.0,1.0,60.0,1.0
-CZ,1232.0,7,2.0,5.0,7.0,6.0,7.0,7.0,2.0,1.0,16.0,2.0
-CZ,1233.0,7,0.0,5.0,7.0,5.0,8.0,3.0,2.0,1.0,35.0,2.0
-CZ,1234.0,7,7.0,7.0,10.0,5.0,5.0,4.0,3.0,2.0,58.0,2.0
-CZ,1235.0,7,7.0,8.0,7.0,5.0,5.0,4.0,3.0,2.0,70.0,1.0
-CZ,1236.0,7,6.0,6.0,4.0,5.0,9.0,4.0,4.0,1.0,75.0,2.0
-CZ,1237.0,7,7.0,5.0,3.0,4.0,5.0,2.0,2.0,2.0,,1.0
-CZ,1238.0,7,0.0,5.0,4.0,4.0,6.0,5.0,2.0,2.0,43.0,1.0
-CZ,1239.0,7,7.0,1.0,5.0,4.0,5.0,6.0,3.0,1.0,30.0,2.0
-CZ,1240.0,7,4.0,5.0,5.0,5.0,10.0,6.0,,2.0,61.0,2.0
-CZ,1241.0,7,2.0,5.0,7.0,7.0,5.0,3.0,2.0,2.0,42.0,1.0
-CZ,1242.0,7,3.0,5.0,5.0,5.0,5.0,2.0,3.0,1.0,37.0,1.0
-CZ,1243.0,7,5.0,5.0,6.0,3.0,8.0,4.0,3.0,1.0,21.0,2.0
-CZ,1244.0,7,7.0,7.0,2.0,7.0,6.0,5.0,1.0,1.0,,2.0
-CZ,1245.0,7,2.0,0.0,4.0,5.0,10.0,4.0,2.0,2.0,54.0,1.0
-CZ,1246.0,7,1.0,3.0,5.0,1.0,6.0,4.0,,1.0,41.0,1.0
-CZ,1247.0,7,2.0,5.0,5.0,7.0,5.0,4.0,3.0,1.0,71.0,1.0
-CZ,1248.0,7,2.0,5.0,7.0,5.0,8.0,4.0,2.0,1.0,65.0,1.0
-CZ,1249.0,7,3.0,2.0,3.0,4.0,8.0,3.0,3.0,1.0,39.0,1.0
-CZ,1250.0,7,7.0,6.0,6.0,7.0,4.0,1.0,2.0,1.0,55.0,2.0
-CZ,1251.0,7,0.0,8.0,8.0,8.0,7.0,1.0,3.0,2.0,19.0,2.0
-CZ,1252.0,7,1.0,6.0,6.0,6.0,8.0,2.0,3.0,1.0,44.0,1.0
-CZ,1253.0,7,7.0,8.0,9.0,8.0,9.0,1.0,3.0,1.0,74.0,1.0
-CZ,1254.0,7,7.0,4.0,0.0,0.0,4.0,4.0,1.0,2.0,57.0,1.0
-CZ,1255.0,7,2.0,2.0,8.0,5.0,8.0,5.0,3.0,1.0,49.0,2.0
-CZ,1256.0,7,4.0,1.0,7.0,4.0,9.0,5.0,2.0,1.0,56.0,2.0
-CZ,1257.0,7,2.0,6.0,5.0,3.0,8.0,4.0,2.0,1.0,43.0,1.0
-CZ,1258.0,7,5.0,1.0,3.0,3.0,9.0,6.0,3.0,2.0,33.0,1.0
-CZ,1259.0,7,5.0,4.0,4.0,4.0,8.0,2.0,1.0,2.0,52.0,1.0
-CZ,1260.0,7,2.0,5.0,5.0,7.0,8.0,5.0,2.0,1.0,60.0,1.0
-CZ,1261.0,7,7.0,3.0,6.0,1.0,7.0,6.0,2.0,2.0,80.0,2.0
-CZ,1262.0,7,3.0,4.0,7.0,8.0,10.0,6.0,3.0,2.0,54.0,1.0
-CZ,1263.0,7,5.0,9.0,9.0,9.0,4.0,1.0,1.0,2.0,,1.0
-CZ,1264.0,7,7.0,7.0,8.0,7.0,6.0,2.0,2.0,2.0,,1.0
-CZ,1265.0,7,1.0,8.0,8.0,8.0,9.0,4.0,3.0,1.0,45.0,1.0
-CZ,1266.0,7,0.0,4.0,4.0,3.0,,5.0,4.0,1.0,37.0,2.0
-CZ,1267.0,7,3.0,3.0,4.0,3.0,9.0,6.0,3.0,1.0,17.0,2.0
-CZ,1268.0,7,0.0,10.0,8.0,4.0,7.0,6.0,4.0,1.0,23.0,2.0
-CZ,1269.0,7,5.0,6.0,6.0,6.0,7.0,7.0,2.0,2.0,53.0,1.0
-CZ,1270.0,7,6.0,10.0,10.0,10.0,2.0,7.0,3.0,2.0,,1.0
-CZ,1271.0,7,7.0,3.0,2.0,4.0,10.0,7.0,3.0,1.0,31.0,1.0
-CZ,1272.0,7,3.0,3.0,5.0,4.0,3.0,7.0,3.0,1.0,37.0,2.0
-CZ,1273.0,7,4.0,8.0,4.0,7.0,6.0,,2.0,1.0,41.0,1.0
-CZ,1274.0,7,7.0,0.0,0.0,1.0,0.0,7.0,3.0,1.0,59.0,1.0
-CZ,1275.0,7,0.0,5.0,1.0,3.0,6.0,7.0,3.0,1.0,24.0,2.0
-CZ,1276.0,7,6.0,4.0,3.0,1.0,7.0,7.0,1.0,2.0,27.0,1.0
-CZ,1277.0,7,0.0,8.0,7.0,7.0,10.0,6.0,3.0,2.0,31.0,1.0
-CZ,1278.0,7,5.0,9.0,9.0,9.0,6.0,7.0,1.0,1.0,18.0,2.0
-CZ,1279.0,7,0.0,10.0,10.0,10.0,6.0,7.0,3.0,2.0,44.0,2.0
-CZ,1280.0,7,7.0,4.0,5.0,4.0,3.0,2.0,2.0,1.0,73.0,2.0
-CZ,1281.0,7,2.0,4.0,2.0,3.0,5.0,5.0,2.0,2.0,50.0,1.0
-CZ,1282.0,7,6.0,6.0,5.0,4.0,3.0,5.0,3.0,1.0,25.0,2.0
-CZ,1283.0,7,7.0,3.0,6.0,6.0,7.0,6.0,,1.0,74.0,1.0
-CZ,1284.0,7,7.0,0.0,6.0,5.0,6.0,4.0,2.0,2.0,35.0,1.0
-CZ,1285.0,7,7.0,5.0,5.0,5.0,5.0,4.0,2.0,,52.0,2.0
-CZ,1286.0,7,7.0,4.0,6.0,6.0,7.0,6.0,3.0,1.0,40.0,1.0
-CZ,1287.0,7,7.0,3.0,5.0,4.0,7.0,4.0,3.0,1.0,57.0,1.0
-CZ,1288.0,7,5.0,7.0,7.0,7.0,7.0,5.0,3.0,2.0,69.0,1.0
-CZ,1289.0,7,6.0,5.0,6.0,5.0,7.0,3.0,2.0,2.0,39.0,1.0
-CZ,1290.0,7,2.0,2.0,5.0,3.0,9.0,4.0,2.0,1.0,71.0,1.0
-CZ,1291.0,7,6.0,6.0,6.0,3.0,6.0,3.0,2.0,2.0,41.0,2.0
-CZ,1292.0,7,3.0,2.0,2.0,4.0,4.0,5.0,2.0,2.0,60.0,1.0
-CZ,1293.0,7,2.0,6.0,5.0,3.0,8.0,3.0,3.0,2.0,43.0,1.0
-CZ,1294.0,7,5.0,3.0,4.0,6.0,2.0,6.0,3.0,2.0,47.0,1.0
-CZ,1295.0,7,7.0,0.0,5.0,5.0,5.0,1.0,,1.0,75.0,1.0
-CZ,1296.0,7,6.0,5.0,5.0,5.0,7.0,6.0,3.0,1.0,20.0,2.0
-CZ,1297.0,7,7.0,7.0,7.0,7.0,5.0,4.0,2.0,2.0,23.0,2.0
-CZ,1298.0,7,6.0,0.0,0.0,0.0,5.0,4.0,2.0,2.0,45.0,1.0
-CZ,1299.0,7,5.0,6.0,6.0,6.0,7.0,2.0,1.0,2.0,32.0,1.0
-CZ,1300.0,7,5.0,4.0,5.0,6.0,6.0,2.0,1.0,2.0,53.0,2.0
-CZ,1301.0,7,4.0,6.0,6.0,6.0,7.0,4.0,3.0,2.0,27.0,1.0
-CZ,1302.0,7,3.0,6.0,7.0,8.0,8.0,6.0,3.0,1.0,17.0,2.0
-CZ,1303.0,7,5.0,4.0,4.0,5.0,6.0,3.0,2.0,1.0,33.0,2.0
-CZ,1304.0,7,6.0,4.0,4.0,6.0,6.0,2.0,1.0,1.0,,1.0
-CZ,1305.0,7,3.0,8.0,8.0,8.0,10.0,6.0,3.0,1.0,17.0,2.0
-CZ,1306.0,7,6.0,4.0,5.0,5.0,6.0,2.0,2.0,2.0,60.0,1.0
-CZ,1307.0,7,3.0,6.0,6.0,7.0,9.0,4.0,3.0,2.0,20.0,2.0
-CZ,1308.0,7,4.0,3.0,4.0,2.0,7.0,4.0,3.0,2.0,43.0,2.0
-CZ,1309.0,7,2.0,3.0,3.0,3.0,6.0,5.0,2.0,2.0,55.0,1.0
-CZ,1310.0,7,4.0,6.0,6.0,6.0,8.0,6.0,3.0,1.0,24.0,2.0
-CZ,1311.0,7,7.0,9.0,9.0,8.0,7.0,7.0,3.0,2.0,19.0,2.0
-CZ,1312.0,7,4.0,6.0,5.0,6.0,6.0,5.0,1.0,2.0,29.0,1.0
-CZ,1313.0,7,7.0,4.0,6.0,5.0,6.0,2.0,1.0,2.0,74.0,2.0
-CZ,1314.0,7,0.0,,3.0,2.0,0.0,7.0,3.0,1.0,45.0,1.0
-CZ,1315.0,7,5.0,8.0,7.0,8.0,7.0,7.0,2.0,1.0,24.0,2.0
-CZ,1316.0,7,3.0,5.0,5.0,3.0,8.0,5.0,3.0,1.0,43.0,1.0
-CZ,1317.0,7,6.0,4.0,3.0,4.0,6.0,6.0,4.0,1.0,43.0,1.0
-CZ,1318.0,7,4.0,3.0,2.0,3.0,4.0,2.0,3.0,2.0,46.0,1.0
-CZ,1319.0,7,6.0,2.0,6.0,6.0,4.0,6.0,2.0,2.0,65.0,1.0
-CZ,1320.0,7,4.0,2.0,3.0,3.0,8.0,5.0,3.0,2.0,62.0,1.0
-CZ,1321.0,7,1.0,6.0,4.0,4.0,2.0,2.0,4.0,2.0,35.0,1.0
-CZ,1322.0,7,5.0,3.0,4.0,2.0,9.0,3.0,3.0,2.0,55.0,1.0
-CZ,1323.0,7,7.0,4.0,7.0,4.0,5.0,3.0,2.0,1.0,46.0,1.0
-CZ,1324.0,7,1.0,7.0,8.0,5.0,9.0,7.0,3.0,2.0,39.0,2.0
-CZ,1325.0,7,4.0,6.0,6.0,8.0,8.0,4.0,2.0,2.0,35.0,1.0
-CZ,1326.0,7,2.0,3.0,5.0,5.0,9.0,7.0,2.0,2.0,55.0,
-CZ,1327.0,7,3.0,4.0,3.0,0.0,8.0,5.0,3.0,2.0,49.0,2.0
-CZ,1328.0,7,3.0,7.0,7.0,7.0,10.0,6.0,3.0,1.0,16.0,2.0
-CZ,1329.0,7,5.0,3.0,5.0,3.0,5.0,4.0,3.0,2.0,38.0,1.0
-CZ,1330.0,7,5.0,4.0,6.0,3.0,8.0,3.0,3.0,2.0,44.0,1.0
-CZ,1331.0,7,7.0,3.0,3.0,3.0,7.0,5.0,3.0,2.0,55.0,1.0
-CZ,1332.0,7,0.0,3.0,3.0,3.0,8.0,4.0,3.0,1.0,58.0,1.0
-CZ,1333.0,7,7.0,6.0,5.0,3.0,8.0,4.0,3.0,2.0,37.0,2.0
-CZ,1334.0,7,4.0,4.0,5.0,3.0,3.0,5.0,2.0,2.0,33.0,2.0
-CZ,1335.0,7,7.0,2.0,3.0,3.0,7.0,4.0,3.0,2.0,65.0,1.0
-CZ,1336.0,7,4.0,3.0,4.0,4.0,8.0,3.0,3.0,1.0,59.0,1.0
-CZ,1337.0,7,5.0,4.0,4.0,4.0,7.0,4.0,3.0,2.0,54.0,2.0
-CZ,1338.0,7,7.0,4.0,4.0,4.0,8.0,5.0,3.0,2.0,50.0,1.0
-CZ,1340.0,7,3.0,4.0,4.0,4.0,7.0,4.0,3.0,2.0,57.0,1.0
-CZ,1341.0,7,2.0,3.0,3.0,3.0,8.0,5.0,3.0,1.0,29.0,1.0
-CZ,1342.0,7,5.0,4.0,4.0,4.0,9.0,4.0,3.0,2.0,26.0,1.0
-CZ,1343.0,7,7.0,4.0,4.0,4.0,8.0,5.0,3.0,2.0,33.0,1.0
-CZ,1344.0,7,5.0,2.0,3.0,3.0,3.0,5.0,2.0,2.0,48.0,2.0
-CZ,1345.0,7,7.0,5.0,4.0,4.0,7.0,5.0,2.0,2.0,50.0,1.0
-CZ,1346.0,7,3.0,5.0,3.0,2.0,7.0,3.0,2.0,2.0,45.0,1.0
-CZ,1347.0,7,7.0,2.0,3.0,7.0,3.0,6.0,3.0,2.0,54.0,1.0
-CZ,1348.0,7,6.0,4.0,4.0,7.0,9.0,5.0,3.0,2.0,36.0,1.0
-CZ,1349.0,7,0.0,2.0,4.0,4.0,8.0,5.0,2.0,1.0,47.0,1.0
-CZ,1350.0,7,7.0,3.0,3.0,3.0,9.0,5.0,3.0,2.0,22.0,2.0
-CZ,1351.0,7,4.0,4.0,4.0,6.0,8.0,4.0,3.0,2.0,58.0,1.0
-CZ,1352.0,7,4.0,2.0,3.0,3.0,7.0,5.0,3.0,2.0,58.0,2.0
-CZ,1353.0,7,5.0,5.0,3.0,8.0,10.0,7.0,2.0,2.0,18.0,2.0
-CZ,1354.0,7,7.0,6.0,6.0,5.0,9.0,6.0,3.0,2.0,69.0,2.0
-CZ,1355.0,7,6.0,7.0,5.0,7.0,6.0,6.0,3.0,2.0,57.0,2.0
-CZ,1356.0,7,1.0,6.0,2.0,6.0,7.0,5.0,2.0,1.0,34.0,1.0
-CZ,1357.0,7,4.0,10.0,10.0,5.0,9.0,6.0,4.0,2.0,67.0,2.0
-CZ,1358.0,7,4.0,7.0,8.0,6.0,8.0,6.0,3.0,2.0,41.0,1.0
-CZ,1359.0,7,1.0,3.0,8.0,5.0,6.0,5.0,2.0,1.0,54.0,1.0
-CZ,1360.0,7,1.0,3.0,3.0,5.0,6.0,6.0,3.0,2.0,40.0,1.0
-CZ,1361.0,7,7.0,3.0,4.0,5.0,6.0,5.0,2.0,2.0,54.0,2.0
-CZ,1362.0,7,2.0,5.0,8.0,8.0,8.0,6.0,4.0,2.0,51.0,1.0
-CZ,1363.0,7,3.0,3.0,0.0,3.0,5.0,4.0,2.0,2.0,46.0,1.0
-CZ,1364.0,7,5.0,2.0,4.0,4.0,4.0,4.0,3.0,1.0,60.0,2.0
-CZ,1365.0,7,4.0,2.0,0.0,5.0,8.0,6.0,3.0,2.0,28.0,2.0
-CZ,1366.0,7,4.0,5.0,5.0,5.0,5.0,7.0,1.0,2.0,59.0,2.0
-CZ,1367.0,7,6.0,2.0,3.0,3.0,6.0,6.0,3.0,2.0,28.0,2.0
-CZ,1368.0,7,1.0,9.0,9.0,0.0,8.0,7.0,2.0,2.0,28.0,2.0
-CZ,1369.0,7,5.0,6.0,6.0,7.0,9.0,6.0,3.0,2.0,61.0,2.0
-CZ,1370.0,7,0.0,2.0,4.0,3.0,7.0,6.0,2.0,1.0,53.0,2.0
-CZ,1371.0,7,7.0,5.0,5.0,5.0,5.0,6.0,1.0,2.0,64.0,2.0
-CZ,1372.0,7,3.0,6.0,6.0,3.0,7.0,5.0,2.0,1.0,23.0,2.0
-CZ,1373.0,7,1.0,1.0,8.0,3.0,9.0,6.0,3.0,2.0,44.0,2.0
-CZ,1374.0,7,2.0,5.0,7.0,7.0,6.0,6.0,3.0,2.0,21.0,2.0
-CZ,1375.0,7,2.0,4.0,8.0,5.0,8.0,4.0,3.0,1.0,21.0,2.0
-CZ,1376.0,7,5.0,5.0,4.0,6.0,6.0,7.0,1.0,1.0,16.0,2.0
-CZ,1377.0,7,5.0,5.0,7.0,5.0,8.0,6.0,2.0,2.0,56.0,1.0
-CZ,1378.0,7,6.0,3.0,6.0,7.0,8.0,2.0,3.0,1.0,22.0,2.0
-CZ,1379.0,7,5.0,2.0,4.0,4.0,7.0,5.0,3.0,2.0,57.0,2.0
-CZ,1380.0,7,5.0,6.0,6.0,7.0,8.0,3.0,3.0,1.0,55.0,1.0
-CZ,1381.0,7,7.0,2.0,3.0,3.0,7.0,5.0,3.0,2.0,69.0,1.0
-CZ,1382.0,7,4.0,2.0,7.0,7.0,5.0,6.0,4.0,1.0,42.0,1.0
-CZ,1383.0,7,3.0,6.0,7.0,6.0,8.0,6.0,3.0,2.0,19.0,2.0
-CZ,1384.0,7,3.0,6.0,6.0,6.0,8.0,2.0,1.0,1.0,30.0,1.0
-CZ,1385.0,7,7.0,4.0,4.0,5.0,5.0,4.0,2.0,2.0,65.0,1.0
-CZ,1386.0,7,7.0,4.0,6.0,5.0,5.0,5.0,3.0,1.0,71.0,2.0
-CZ,1387.0,7,5.0,3.0,3.0,3.0,,4.0,3.0,2.0,50.0,1.0
-CZ,1388.0,7,5.0,3.0,3.0,2.0,6.0,4.0,2.0,2.0,64.0,1.0
-CZ,1389.0,7,7.0,1.0,3.0,0.0,8.0,2.0,1.0,2.0,72.0,1.0
-CZ,1390.0,7,7.0,2.0,3.0,3.0,5.0,2.0,2.0,1.0,56.0,2.0
-CZ,1391.0,7,4.0,3.0,4.0,0.0,9.0,5.0,3.0,1.0,55.0,1.0
-CZ,1392.0,7,4.0,2.0,2.0,2.0,7.0,5.0,3.0,2.0,56.0,1.0
-CZ,1393.0,7,4.0,6.0,7.0,3.0,4.0,4.0,3.0,1.0,70.0,2.0
-CZ,1394.0,7,4.0,0.0,0.0,0.0,5.0,5.0,4.0,1.0,56.0,1.0
-CZ,1395.0,7,1.0,5.0,5.0,3.0,5.0,5.0,3.0,2.0,21.0,2.0
-CZ,1396.0,7,3.0,0.0,4.0,3.0,2.0,5.0,3.0,1.0,19.0,2.0
-CZ,1397.0,7,6.0,0.0,0.0,0.0,5.0,3.0,3.0,2.0,16.0,2.0
-CZ,1398.0,7,7.0,0.0,0.0,0.0,3.0,5.0,4.0,2.0,62.0,1.0
-CZ,1399.0,7,2.0,0.0,0.0,0.0,5.0,4.0,3.0,2.0,36.0,1.0
-CZ,1400.0,7,6.0,1.0,2.0,2.0,7.0,4.0,3.0,2.0,43.0,1.0
-CZ,1401.0,7,7.0,2.0,5.0,5.0,10.0,7.0,3.0,1.0,24.0,2.0
-CZ,1402.0,7,5.0,0.0,0.0,0.0,5.0,4.0,2.0,1.0,48.0,1.0
-CZ,1403.0,7,4.0,6.0,6.0,7.0,9.0,4.0,3.0,1.0,45.0,1.0
-CZ,1404.0,7,6.0,4.0,3.0,5.0,10.0,7.0,3.0,1.0,36.0,2.0
-CZ,1405.0,7,7.0,0.0,0.0,0.0,10.0,7.0,3.0,1.0,43.0,2.0
-CZ,1406.0,7,5.0,4.0,5.0,6.0,5.0,3.0,2.0,2.0,36.0,1.0
-CZ,1407.0,7,7.0,0.0,7.0,10.0,10.0,7.0,1.0,1.0,17.0,2.0
-CZ,1408.0,7,7.0,4.0,4.0,3.0,5.0,3.0,2.0,1.0,70.0,1.0
-CZ,1409.0,7,3.0,5.0,5.0,5.0,6.0,4.0,3.0,2.0,52.0,1.0
-CZ,1410.0,7,1.0,5.0,6.0,7.0,8.0,2.0,2.0,1.0,35.0,1.0
-CZ,1411.0,7,5.0,7.0,7.0,8.0,6.0,4.0,4.0,1.0,36.0,1.0
-CZ,1412.0,7,6.0,6.0,4.0,6.0,5.0,4.0,4.0,2.0,63.0,1.0
-CZ,1413.0,7,7.0,6.0,6.0,4.0,10.0,6.0,3.0,1.0,32.0,1.0
-CZ,1414.0,7,5.0,10.0,10.0,9.0,10.0,7.0,3.0,2.0,21.0,2.0
-CZ,1415.0,7,5.0,6.0,6.0,3.0,7.0,5.0,3.0,1.0,49.0,1.0
-CZ,1416.0,7,7.0,2.0,2.0,2.0,7.0,5.0,5.0,1.0,51.0,2.0
-CZ,1417.0,7,7.0,5.0,8.0,6.0,9.0,5.0,4.0,1.0,15.0,2.0
-CZ,1418.0,7,4.0,2.0,2.0,3.0,2.0,4.0,2.0,2.0,27.0,1.0
-CZ,1419.0,7,5.0,4.0,3.0,6.0,9.0,6.0,3.0,1.0,39.0,1.0
-CZ,1420.0,7,7.0,0.0,1.0,0.0,8.0,6.0,1.0,2.0,48.0,2.0
-CZ,1421.0,7,2.0,0.0,5.0,1.0,8.0,3.0,3.0,1.0,31.0,1.0
-CZ,1422.0,7,1.0,0.0,0.0,0.0,5.0,5.0,3.0,2.0,40.0,1.0
-CZ,1423.0,7,5.0,2.0,2.0,3.0,1.0,5.0,2.0,1.0,36.0,1.0
-CZ,1424.0,7,5.0,3.0,5.0,4.0,5.0,3.0,2.0,2.0,50.0,1.0
-CZ,1425.0,7,4.0,4.0,5.0,3.0,4.0,4.0,2.0,2.0,23.0,1.0
-CZ,1426.0,7,4.0,2.0,3.0,2.0,5.0,4.0,3.0,2.0,34.0,2.0
-CZ,1427.0,7,5.0,7.0,7.0,5.0,10.0,7.0,4.0,2.0,31.0,1.0
-CZ,1428.0,7,7.0,4.0,3.0,3.0,5.0,6.0,4.0,1.0,45.0,1.0
-CZ,1429.0,7,7.0,2.0,4.0,3.0,4.0,3.0,2.0,2.0,35.0,1.0
-CZ,1430.0,7,7.0,4.0,5.0,5.0,5.0,4.0,3.0,2.0,70.0,2.0
-CZ,1431.0,7,3.0,5.0,5.0,5.0,7.0,6.0,4.0,1.0,31.0,1.0
-CZ,1432.0,7,6.0,6.0,3.0,4.0,6.0,3.0,3.0,2.0,39.0,2.0
-CZ,1433.0,7,6.0,7.0,7.0,7.0,7.0,5.0,3.0,1.0,49.0,1.0
-CZ,1434.0,7,6.0,1.0,5.0,1.0,7.0,2.0,2.0,2.0,60.0,1.0
-CZ,1435.0,7,7.0,9.0,9.0,9.0,9.0,6.0,5.0,2.0,20.0,2.0
-CZ,1436.0,7,4.0,5.0,6.0,3.0,8.0,6.0,3.0,2.0,40.0,1.0
-CZ,1437.0,7,4.0,5.0,5.0,3.0,8.0,3.0,3.0,2.0,58.0,1.0
-CZ,1438.0,7,3.0,2.0,2.0,2.0,5.0,6.0,1.0,1.0,51.0,2.0
-CZ,1439.0,7,7.0,4.0,5.0,5.0,7.0,7.0,3.0,2.0,69.0,2.0
-CZ,1440.0,7,6.0,5.0,3.0,5.0,8.0,6.0,2.0,2.0,47.0,2.0
-CZ,1441.0,7,7.0,6.0,4.0,5.0,9.0,7.0,4.0,1.0,68.0,1.0
-CZ,1442.0,7,0.0,3.0,3.0,3.0,8.0,5.0,3.0,1.0,63.0,2.0
-CZ,1443.0,7,5.0,3.0,6.0,5.0,7.0,3.0,4.0,1.0,65.0,2.0
-CZ,1444.0,7,3.0,2.0,6.0,5.0,8.0,7.0,2.0,2.0,24.0,1.0
-CZ,1445.0,7,7.0,9.0,9.0,9.0,9.0,6.0,4.0,2.0,22.0,2.0
-CZ,1446.0,7,4.0,6.0,5.0,5.0,6.0,3.0,3.0,2.0,39.0,1.0
-CZ,1447.0,7,3.0,5.0,5.0,5.0,5.0,3.0,3.0,1.0,42.0,2.0
-CZ,1448.0,7,7.0,8.0,3.0,6.0,4.0,5.0,2.0,1.0,74.0,2.0
-CZ,1449.0,7,2.0,4.0,5.0,5.0,6.0,3.0,3.0,1.0,49.0,1.0
-CZ,1450.0,7,3.0,4.0,5.0,5.0,7.0,6.0,3.0,1.0,47.0,1.0
-CZ,1451.0,7,7.0,3.0,3.0,3.0,5.0,4.0,3.0,2.0,69.0,1.0
-CZ,1452.0,7,4.0,2.0,4.0,3.0,8.0,4.0,2.0,2.0,36.0,1.0
-CZ,1453.0,7,4.0,5.0,5.0,5.0,5.0,3.0,1.0,1.0,61.0,1.0
-CZ,1454.0,7,5.0,7.0,5.0,6.0,7.0,4.0,4.0,2.0,35.0,1.0
-CZ,1455.0,7,3.0,2.0,5.0,2.0,5.0,3.0,1.0,1.0,40.0,1.0
-CZ,1456.0,7,4.0,3.0,4.0,3.0,5.0,5.0,4.0,2.0,41.0,1.0
-CZ,1457.0,7,3.0,5.0,5.0,5.0,7.0,3.0,3.0,2.0,56.0,1.0
-CZ,1458.0,7,6.0,4.0,3.0,4.0,6.0,5.0,3.0,1.0,54.0,1.0
-CZ,1459.0,7,6.0,6.0,6.0,6.0,8.0,3.0,3.0,1.0,56.0,1.0
-CZ,1460.0,7,7.0,9.0,8.0,6.0,10.0,6.0,3.0,1.0,23.0,2.0
-CZ,1461.0,7,7.0,6.0,6.0,5.0,8.0,4.0,3.0,2.0,55.0,2.0
-CZ,1462.0,7,5.0,5.0,5.0,4.0,5.0,3.0,3.0,2.0,63.0,1.0
-CZ,1463.0,7,4.0,5.0,5.0,5.0,5.0,3.0,3.0,2.0,42.0,1.0
-CZ,1464.0,7,6.0,5.0,5.0,5.0,5.0,3.0,3.0,2.0,33.0,2.0
-CZ,1465.0,7,5.0,5.0,5.0,4.0,4.0,3.0,2.0,2.0,64.0,1.0
-CZ,1466.0,7,6.0,4.0,3.0,2.0,5.0,4.0,3.0,1.0,41.0,1.0
-CZ,1468.0,7,7.0,4.0,4.0,4.0,6.0,6.0,3.0,2.0,49.0,1.0
-CZ,1469.0,7,5.0,3.0,4.0,5.0,5.0,4.0,3.0,2.0,80.0,2.0
-CZ,1470.0,7,4.0,5.0,5.0,5.0,5.0,3.0,3.0,2.0,52.0,2.0
-CZ,1471.0,7,5.0,0.0,0.0,0.0,4.0,3.0,2.0,1.0,41.0,2.0
-CZ,1472.0,7,3.0,0.0,5.0,2.0,5.0,6.0,5.0,1.0,27.0,2.0
-CZ,1473.0,7,1.0,0.0,0.0,0.0,4.0,2.0,3.0,1.0,59.0,1.0
-CZ,1474.0,7,1.0,0.0,0.0,0.0,5.0,2.0,3.0,2.0,30.0,2.0
-CZ,1475.0,7,2.0,0.0,0.0,0.0,5.0,5.0,3.0,1.0,21.0,2.0
-CZ,1476.0,7,3.0,0.0,0.0,0.0,6.0,3.0,4.0,2.0,36.0,2.0
-CZ,1477.0,7,6.0,4.0,4.0,3.0,8.0,7.0,3.0,2.0,20.0,2.0
-CZ,1478.0,7,5.0,2.0,4.0,4.0,10.0,3.0,1.0,1.0,43.0,1.0
-CZ,1479.0,7,6.0,3.0,6.0,3.0,10.0,6.0,4.0,1.0,22.0,2.0
-CZ,1480.0,7,6.0,1.0,3.0,2.0,5.0,2.0,1.0,2.0,51.0,1.0
-CZ,1481.0,7,5.0,2.0,5.0,0.0,8.0,6.0,3.0,1.0,24.0,2.0
-CZ,1482.0,7,6.0,7.0,4.0,5.0,8.0,6.0,3.0,1.0,25.0,2.0
-CZ,1483.0,7,7.0,4.0,7.0,7.0,7.0,4.0,3.0,1.0,70.0,1.0
-CZ,1485.0,7,7.0,7.0,5.0,7.0,9.0,6.0,4.0,1.0,20.0,2.0
-CZ,1486.0,7,4.0,8.0,9.0,9.0,9.0,1.0,1.0,1.0,17.0,2.0
-CZ,1487.0,7,7.0,8.0,7.0,7.0,8.0,4.0,3.0,2.0,27.0,2.0
-CZ,1488.0,7,4.0,8.0,3.0,8.0,8.0,4.0,3.0,1.0,39.0,1.0
-CZ,1489.0,7,7.0,3.0,6.0,4.0,8.0,4.0,3.0,2.0,53.0,1.0
-CZ,1490.0,7,0.0,6.0,3.0,7.0,8.0,4.0,3.0,1.0,57.0,1.0
-CZ,1491.0,7,6.0,3.0,4.0,2.0,8.0,2.0,1.0,2.0,78.0,2.0
-CZ,1492.0,7,4.0,5.0,5.0,5.0,5.0,4.0,2.0,2.0,36.0,1.0
-CZ,1493.0,7,4.0,9.0,8.0,10.0,7.0,6.0,2.0,2.0,35.0,1.0
-CZ,1494.0,7,2.0,5.0,5.0,5.0,8.0,4.0,3.0,1.0,46.0,2.0
-CZ,1495.0,7,5.0,2.0,1.0,7.0,8.0,6.0,4.0,1.0,41.0,1.0
-CZ,1496.0,7,5.0,0.0,3.0,5.0,8.0,5.0,4.0,2.0,52.0,1.0
-CZ,1497.0,7,1.0,1.0,4.0,0.0,8.0,3.0,2.0,1.0,53.0,1.0
-CZ,1498.0,7,3.0,6.0,8.0,9.0,8.0,7.0,5.0,2.0,19.0,2.0
-CZ,1499.0,7,5.0,8.0,8.0,8.0,7.0,1.0,1.0,1.0,68.0,1.0
-CZ,1500.0,7,5.0,0.0,0.0,1.0,10.0,6.0,4.0,2.0,19.0,2.0
-CZ,1501.0,7,3.0,8.0,5.0,7.0,8.0,7.0,4.0,1.0,17.0,2.0
-CZ,1502.0,7,5.0,8.0,9.0,9.0,10.0,6.0,4.0,1.0,17.0,2.0
-CZ,1503.0,7,5.0,7.0,7.0,8.0,10.0,3.0,3.0,2.0,42.0,
-CZ,1504.0,7,7.0,0.0,5.0,5.0,7.0,4.0,1.0,1.0,75.0,2.0
-CZ,1505.0,7,7.0,5.0,8.0,8.0,8.0,5.0,4.0,2.0,55.0,2.0
-CZ,1506.0,7,7.0,5.0,5.0,7.0,7.0,4.0,1.0,2.0,33.0,1.0
-CZ,1507.0,7,3.0,7.0,6.0,4.0,5.0,4.0,1.0,1.0,57.0,1.0
-CZ,1508.0,7,7.0,3.0,7.0,8.0,6.0,3.0,1.0,2.0,78.0,2.0
-CZ,1509.0,7,7.0,7.0,7.0,8.0,8.0,7.0,4.0,1.0,19.0,2.0
-CZ,1510.0,7,7.0,7.0,8.0,7.0,6.0,4.0,3.0,2.0,55.0,1.0
-CZ,1511.0,7,7.0,5.0,5.0,5.0,8.0,2.0,2.0,2.0,43.0,1.0
-CZ,1512.0,7,2.0,6.0,7.0,4.0,4.0,3.0,3.0,1.0,42.0,1.0
-CZ,1550.0,7,0.0,10.0,4.0,7.0,8.0,6.0,2.0,1.0,20.0,2.0
-CZ,1551.0,7,1.0,8.0,4.0,8.0,3.0,5.0,,1.0,21.0,2.0
-CZ,2001.0,7,5.0,5.0,5.0,5.0,9.0,4.0,3.0,1.0,43.0,1.0
-CZ,2002.0,7,7.0,7.0,7.0,7.0,8.0,4.0,3.0,,65.0,2.0
-CZ,2003.0,7,7.0,5.0,5.0,5.0,7.0,4.0,3.0,1.0,55.0,1.0
-CZ,2004.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,,69.0,2.0
-CZ,2005.0,7,5.0,5.0,5.0,5.0,10.0,5.0,3.0,2.0,21.0,2.0
-CZ,2006.0,7,7.0,5.0,6.0,6.0,9.0,4.0,3.0,1.0,,1.0
-CZ,2007.0,7,7.0,5.0,5.0,5.0,8.0,5.0,3.0,2.0,24.0,2.0
-CZ,2008.0,7,5.0,7.0,7.0,7.0,8.0,4.0,3.0,2.0,33.0,2.0
-CZ,2009.0,7,5.0,5.0,5.0,5.0,9.0,5.0,3.0,1.0,50.0,2.0
-CZ,2010.0,7,6.0,7.0,7.0,7.0,9.0,5.0,3.0,2.0,25.0,2.0
-CZ,2011.0,7,7.0,5.0,5.0,5.0,7.0,4.0,3.0,1.0,51.0,1.0
-CZ,2012.0,7,7.0,6.0,6.0,6.0,8.0,4.0,3.0,,82.0,2.0
-CZ,2013.0,7,3.0,6.0,5.0,5.0,8.0,3.0,3.0,,54.0,2.0
-CZ,2014.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,,74.0,2.0
-CZ,2015.0,7,7.0,8.0,8.0,8.0,8.0,4.0,3.0,2.0,64.0,2.0
-CZ,2016.0,7,7.0,6.0,6.0,6.0,8.0,4.0,3.0,1.0,62.0,2.0
-CZ,2017.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,,87.0,2.0
-CZ,2018.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,2.0,74.0,1.0
-CZ,2019.0,7,7.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,64.0,2.0
-CZ,2020.0,7,7.0,5.0,7.0,7.0,7.0,4.0,3.0,,84.0,2.0
-CZ,2021.0,7,7.0,6.0,7.0,7.0,8.0,4.0,3.0,1.0,59.0,1.0
-CZ,2022.0,7,7.0,6.0,7.0,7.0,8.0,4.0,3.0,1.0,54.0,1.0
-CZ,2023.0,7,7.0,4.0,5.0,5.0,8.0,5.0,3.0,1.0,26.0,1.0
-CZ,2024.0,7,7.0,5.0,5.0,5.0,7.0,4.0,3.0,1.0,24.0,2.0
-CZ,2025.0,7,7.0,5.0,5.0,6.0,8.0,6.0,2.0,2.0,37.0,1.0
-CZ,2026.0,7,4.0,3.0,2.0,2.0,6.0,7.0,2.0,2.0,43.0,1.0
-CZ,2027.0,7,5.0,7.0,6.0,4.0,8.0,7.0,3.0,2.0,60.0,2.0
-CZ,2028.0,7,7.0,2.0,5.0,3.0,5.0,2.0,1.0,2.0,67.0,2.0
-CZ,2029.0,7,7.0,1.0,1.0,5.0,5.0,7.0,4.0,1.0,65.0,1.0
-CZ,2030.0,7,7.0,3.0,3.0,3.0,6.0,7.0,3.0,1.0,41.0,2.0
-CZ,2031.0,7,2.0,4.0,3.0,5.0,7.0,6.0,3.0,2.0,55.0,1.0
-CZ,2032.0,7,6.0,5.0,5.0,5.0,8.0,3.0,3.0,2.0,45.0,1.0
-CZ,2033.0,7,4.0,0.0,5.0,2.0,5.0,2.0,3.0,1.0,56.0,1.0
-CZ,2034.0,7,5.0,2.0,3.0,3.0,8.0,4.0,3.0,2.0,35.0,1.0
-CZ,2035.0,7,6.0,5.0,4.0,6.0,7.0,5.0,3.0,2.0,50.0,1.0
-CZ,2036.0,7,4.0,5.0,10.0,5.0,5.0,6.0,2.0,2.0,58.0,1.0
-CZ,2037.0,7,3.0,0.0,5.0,5.0,9.0,4.0,3.0,2.0,37.0,1.0
-CZ,2038.0,7,3.0,1.0,6.0,3.0,6.0,7.0,2.0,1.0,39.0,2.0
-CZ,2039.0,7,7.0,0.0,0.0,0.0,4.0,7.0,3.0,2.0,60.0,1.0
-CZ,2040.0,7,5.0,5.0,5.0,5.0,8.0,6.0,4.0,2.0,52.0,1.0
-CZ,2041.0,7,6.0,2.0,2.0,2.0,8.0,4.0,3.0,1.0,39.0,2.0
-CZ,2042.0,7,6.0,5.0,5.0,5.0,9.0,4.0,3.0,1.0,25.0,1.0
-CZ,2043.0,7,7.0,5.0,6.0,7.0,9.0,4.0,3.0,1.0,71.0,1.0
-CZ,2044.0,7,7.0,6.0,6.0,6.0,8.0,4.0,3.0,1.0,64.0,2.0
-CZ,2045.0,7,4.0,5.0,5.0,5.0,9.0,4.0,3.0,2.0,29.0,1.0
-CZ,2046.0,7,3.0,5.0,5.0,6.0,10.0,5.0,3.0,1.0,22.0,2.0
-CZ,2047.0,7,6.0,5.0,5.0,5.0,8.0,4.0,3.0,1.0,45.0,2.0
-CZ,2048.0,7,5.0,8.0,8.0,8.0,9.0,5.0,3.0,2.0,24.0,2.0
-CZ,2049.0,7,6.0,5.0,5.0,6.0,8.0,4.0,3.0,1.0,50.0,2.0
-CZ,2050.0,7,7.0,6.0,6.0,6.0,8.0,4.0,3.0,1.0,65.0,1.0
-CZ,2051.0,7,5.0,5.0,5.0,5.0,9.0,5.0,3.0,1.0,22.0,2.0
-CZ,2052.0,7,6.0,4.0,4.0,4.0,8.0,4.0,3.0,1.0,40.0,2.0
-CZ,2053.0,7,5.0,6.0,6.0,6.0,8.0,4.0,3.0,1.0,41.0,1.0
-CZ,2054.0,7,5.0,7.0,7.0,7.0,9.0,4.0,3.0,2.0,45.0,1.0
-CZ,2055.0,7,2.0,5.0,5.0,3.0,10.0,5.0,3.0,2.0,22.0,2.0
-CZ,2056.0,7,6.0,5.0,5.0,5.0,7.0,4.0,3.0,2.0,40.0,1.0
-CZ,2057.0,7,7.0,4.0,4.0,4.0,7.0,4.0,3.0,1.0,51.0,2.0
-CZ,2058.0,7,6.0,5.0,5.0,5.0,8.0,4.0,3.0,1.0,53.0,1.0
-CZ,2059.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,,50.0,2.0
-CZ,2060.0,7,5.0,4.0,5.0,5.0,9.0,4.0,3.0,2.0,24.0,1.0
-CZ,2061.0,7,2.0,4.0,4.0,5.0,6.0,4.0,2.0,2.0,73.0,2.0
-CZ,2062.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,1.0,65.0,2.0
-CZ,2063.0,7,7.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,69.0,2.0
-CZ,2064.0,7,7.0,7.0,7.0,7.0,8.0,5.0,3.0,1.0,26.0,2.0
-CZ,2065.0,7,4.0,2.0,6.0,6.0,6.0,2.0,,1.0,55.0,1.0
-CZ,2066.0,7,1.0,3.0,7.0,2.0,7.0,5.0,1.0,1.0,31.0,2.0
-CZ,2067.0,7,2.0,6.0,5.0,3.0,7.0,6.0,2.0,1.0,52.0,1.0
-CZ,2068.0,7,2.0,5.0,5.0,5.0,10.0,3.0,2.0,2.0,35.0,2.0
-CZ,2069.0,7,6.0,7.0,5.0,7.0,7.0,4.0,3.0,2.0,52.0,2.0
-CZ,2070.0,7,6.0,0.0,0.0,2.0,3.0,3.0,3.0,2.0,45.0,1.0
-CZ,2071.0,7,7.0,5.0,5.0,5.0,7.0,6.0,1.0,2.0,59.0,1.0
-CZ,2072.0,7,3.0,3.0,2.0,2.0,9.0,6.0,2.0,2.0,40.0,1.0
-CZ,2073.0,7,3.0,5.0,2.0,2.0,5.0,6.0,3.0,1.0,48.0,2.0
-CZ,2074.0,7,3.0,1.0,1.0,3.0,10.0,6.0,2.0,1.0,28.0,1.0
-CZ,2075.0,7,7.0,8.0,8.0,7.0,7.0,4.0,1.0,1.0,36.0,2.0
-CZ,2076.0,7,5.0,5.0,5.0,5.0,8.0,5.0,3.0,2.0,27.0,2.0
-CZ,2077.0,7,5.0,3.0,3.0,4.0,7.0,3.0,4.0,2.0,62.0,1.0
-CZ,2078.0,7,4.0,6.0,5.0,5.0,7.0,3.0,1.0,2.0,54.0,1.0
-CZ,2079.0,7,3.0,10.0,9.0,7.0,9.0,6.0,4.0,2.0,51.0,1.0
-CZ,2080.0,7,6.0,3.0,5.0,5.0,6.0,5.0,4.0,2.0,58.0,1.0
-CZ,2081.0,7,2.0,7.0,7.0,5.0,8.0,7.0,4.0,2.0,28.0,2.0
-CZ,2082.0,7,5.0,4.0,4.0,3.0,6.0,4.0,2.0,1.0,46.0,1.0
-CZ,2083.0,7,3.0,7.0,7.0,4.0,9.0,6.0,4.0,1.0,59.0,1.0
-CZ,2084.0,7,4.0,6.0,6.0,7.0,8.0,7.0,2.0,2.0,53.0,1.0
-CZ,2085.0,7,4.0,5.0,6.0,5.0,10.0,3.0,3.0,2.0,57.0,1.0
-CZ,2086.0,7,6.0,3.0,6.0,5.0,8.0,7.0,5.0,2.0,55.0,1.0
-CZ,2087.0,7,3.0,6.0,8.0,4.0,9.0,2.0,3.0,2.0,55.0,2.0
-CZ,2088.0,7,1.0,7.0,5.0,3.0,9.0,6.0,1.0,1.0,42.0,1.0
-CZ,2089.0,7,4.0,3.0,3.0,1.0,5.0,6.0,1.0,2.0,68.0,2.0
-CZ,2090.0,7,4.0,3.0,3.0,2.0,9.0,6.0,4.0,2.0,58.0,2.0
-CZ,2091.0,7,4.0,5.0,3.0,2.0,9.0,7.0,2.0,2.0,20.0,2.0
-CZ,2092.0,7,7.0,2.0,1.0,1.0,3.0,4.0,1.0,2.0,,2.0
-CZ,2093.0,7,7.0,5.0,5.0,2.0,7.0,5.0,3.0,2.0,39.0,2.0
-CZ,2094.0,7,7.0,7.0,6.0,3.0,9.0,6.0,2.0,2.0,60.0,2.0
-CZ,2095.0,7,3.0,5.0,6.0,3.0,9.0,6.0,3.0,2.0,53.0,2.0
-CZ,2096.0,7,7.0,3.0,4.0,1.0,5.0,4.0,2.0,1.0,23.0,2.0
-CZ,2097.0,7,7.0,2.0,3.0,2.0,7.0,4.0,3.0,2.0,59.0,2.0
-CZ,2098.0,7,7.0,5.0,3.0,0.0,5.0,3.0,3.0,1.0,68.0,2.0
-CZ,2099.0,7,4.0,3.0,1.0,3.0,3.0,3.0,2.0,2.0,72.0,2.0
-CZ,2100.0,7,7.0,5.0,2.0,1.0,8.0,2.0,2.0,1.0,70.0,2.0
-CZ,2101.0,7,5.0,5.0,7.0,2.0,8.0,4.0,4.0,2.0,70.0,2.0
-CZ,2102.0,7,6.0,2.0,4.0,2.0,7.0,4.0,3.0,1.0,39.0,1.0
-CZ,2103.0,7,7.0,2.0,5.0,7.0,5.0,4.0,,1.0,52.0,1.0
-CZ,2104.0,7,1.0,7.0,3.0,4.0,6.0,4.0,3.0,2.0,35.0,2.0
-CZ,2105.0,7,7.0,6.0,6.0,4.0,7.0,5.0,3.0,2.0,34.0,1.0
-CZ,2106.0,7,6.0,3.0,1.0,1.0,7.0,5.0,3.0,1.0,35.0,1.0
-CZ,2107.0,7,5.0,3.0,4.0,3.0,7.0,5.0,2.0,1.0,56.0,1.0
-CZ,2108.0,7,7.0,4.0,4.0,3.0,6.0,5.0,2.0,2.0,31.0,1.0
-CZ,2109.0,7,4.0,3.0,6.0,5.0,7.0,4.0,3.0,1.0,41.0,2.0
-CZ,2110.0,7,7.0,2.0,3.0,3.0,7.0,4.0,3.0,2.0,29.0,1.0
-CZ,2111.0,7,7.0,5.0,6.0,3.0,7.0,4.0,3.0,2.0,24.0,1.0
-CZ,2112.0,7,7.0,6.0,5.0,6.0,6.0,4.0,3.0,1.0,44.0,1.0
-CZ,2113.0,7,0.0,4.0,5.0,4.0,6.0,4.0,3.0,1.0,32.0,2.0
-CZ,2114.0,7,7.0,10.0,5.0,3.0,3.0,5.0,3.0,1.0,71.0,2.0
-CZ,2115.0,7,4.0,7.0,6.0,7.0,4.0,3.0,2.0,2.0,64.0,1.0
-CZ,2116.0,7,5.0,6.0,1.0,4.0,7.0,4.0,2.0,1.0,45.0,2.0
-CZ,2117.0,7,6.0,1.0,2.0,4.0,6.0,5.0,3.0,2.0,62.0,2.0
-CZ,2118.0,7,3.0,1.0,2.0,1.0,5.0,4.0,3.0,1.0,40.0,2.0
-CZ,2119.0,7,7.0,0.0,0.0,5.0,2.0,7.0,1.0,2.0,52.0,2.0
-CZ,2120.0,7,6.0,2.0,4.0,4.0,6.0,3.0,1.0,2.0,40.0,1.0
-CZ,2121.0,7,7.0,5.0,3.0,1.0,5.0,6.0,4.0,2.0,28.0,1.0
-CZ,2122.0,7,2.0,5.0,3.0,4.0,0.0,3.0,1.0,2.0,31.0,1.0
-CZ,2123.0,7,7.0,2.0,4.0,1.0,8.0,5.0,1.0,2.0,56.0,1.0
-CZ,2124.0,7,6.0,4.0,3.0,2.0,5.0,4.0,2.0,1.0,58.0,1.0
-CZ,2125.0,7,7.0,3.0,3.0,5.0,7.0,6.0,5.0,2.0,27.0,1.0
-CZ,2126.0,7,7.0,5.0,5.0,4.0,2.0,4.0,2.0,2.0,69.0,2.0
-CZ,2127.0,7,4.0,2.0,0.0,5.0,4.0,6.0,5.0,2.0,58.0,1.0
-CZ,2128.0,7,4.0,4.0,4.0,6.0,6.0,4.0,1.0,2.0,33.0,2.0
-CZ,2129.0,7,7.0,4.0,2.0,3.0,4.0,4.0,3.0,2.0,58.0,1.0
-CZ,2130.0,7,7.0,5.0,3.0,4.0,4.0,4.0,3.0,2.0,25.0,1.0
-CZ,2131.0,7,7.0,1.0,7.0,7.0,6.0,6.0,4.0,2.0,68.0,2.0
-CZ,2132.0,7,4.0,2.0,2.0,2.0,6.0,4.0,3.0,2.0,48.0,2.0
-CZ,2133.0,7,3.0,8.0,7.0,8.0,8.0,7.0,3.0,2.0,21.0,2.0
-CZ,2134.0,7,4.0,0.0,1.0,2.0,6.0,6.0,4.0,2.0,29.0,1.0
-CZ,2135.0,7,7.0,3.0,3.0,4.0,5.0,5.0,4.0,1.0,37.0,1.0
-CZ,2136.0,7,6.0,4.0,5.0,5.0,6.0,4.0,3.0,1.0,22.0,2.0
-CZ,2137.0,7,2.0,5.0,5.0,5.0,9.0,5.0,3.0,2.0,29.0,1.0
-CZ,2138.0,7,7.0,5.0,4.0,3.0,7.0,5.0,3.0,2.0,58.0,2.0
-CZ,2139.0,7,7.0,6.0,5.0,4.0,10.0,6.0,4.0,2.0,20.0,1.0
-CZ,2140.0,7,7.0,2.0,1.0,0.0,2.0,6.0,3.0,2.0,35.0,2.0
-CZ,2141.0,7,4.0,2.0,8.0,2.0,3.0,6.0,3.0,1.0,22.0,2.0
-CZ,2142.0,7,7.0,2.0,2.0,2.0,6.0,3.0,3.0,1.0,73.0,1.0
-CZ,2143.0,7,7.0,4.0,4.0,3.0,7.0,4.0,3.0,2.0,53.0,1.0
-CZ,2144.0,7,7.0,2.0,7.0,6.0,6.0,4.0,3.0,2.0,26.0,1.0
-CZ,2145.0,7,7.0,5.0,2.0,3.0,6.0,5.0,3.0,2.0,23.0,2.0
-CZ,2146.0,7,7.0,7.0,7.0,4.0,6.0,7.0,5.0,1.0,61.0,2.0
-CZ,2147.0,7,7.0,4.0,5.0,4.0,7.0,6.0,3.0,2.0,22.0,1.0
-CZ,2148.0,7,6.0,3.0,5.0,4.0,10.0,5.0,1.0,1.0,25.0,2.0
-CZ,2149.0,7,7.0,5.0,7.0,2.0,8.0,5.0,2.0,2.0,68.0,2.0
-CZ,2150.0,7,5.0,5.0,5.0,5.0,9.0,4.0,3.0,1.0,40.0,1.0
-CZ,2151.0,7,2.0,5.0,5.0,5.0,5.0,5.0,4.0,2.0,73.0,2.0
-DE,11000031.0,6,2.0,3.0,8.0,8.0,8.0,4.0,3.0,2.0,51.0,1.0
-DE,11000041.0,6,7.0,7.0,7.0,6.0,8.0,5.0,3.0,1.0,75.0,1.0
-DE,11000071.0,6,4.0,5.0,6.0,5.0,6.0,4.0,2.0,1.0,50.0,2.0
-DE,11000091.0,6,7.0,8.0,6.0,5.0,7.0,5.0,2.0,1.0,71.0,1.0
-DE,11000131.0,6,5.0,7.0,,,9.0,6.0,2.0,1.0,27.0,1.0
-DE,11000181.0,6,2.0,5.0,5.0,5.0,8.0,6.0,3.0,2.0,34.0,2.0
-DE,11000251.0,6,7.0,5.0,3.0,8.0,8.0,4.0,4.0,2.0,55.0,2.0
-DE,11000291.0,6,6.0,4.0,3.0,6.0,6.0,6.0,4.0,2.0,59.0,2.0
-DE,11000341.0,6,4.0,4.0,5.0,5.0,9.0,4.0,3.0,2.0,74.0,1.0
-DE,11000421.0,6,1.0,7.0,7.0,4.0,8.0,5.0,3.0,1.0,33.0,1.0
-DE,11000971.0,6,6.0,3.0,4.0,3.0,5.0,3.0,2.0,2.0,62.0,1.0
-DE,11001031.0,6,4.0,5.0,8.0,3.0,8.0,6.0,5.0,2.0,59.0,1.0
-DE,11001401.0,6,7.0,5.0,5.0,2.0,4.0,6.0,1.0,1.0,53.0,2.0
-DE,11001431.0,6,7.0,5.0,7.0,5.0,10.0,6.0,3.0,2.0,26.0,1.0
-DE,11000031.0,7,1.0,2.0,5.0,3.0,8.0,4.0,4.0,2.0,49.0,1.0
-DE,11000041.0,7,2.0,6.0,7.0,5.0,7.0,4.0,2.0,1.0,57.0,1.0
-DE,11000071.0,7,4.0,7.0,6.0,6.0,9.0,6.0,3.0,1.0,52.0,1.0
-DE,11000091.0,7,5.0,4.0,7.0,7.0,8.0,4.0,2.0,2.0,71.0,1.0
-DE,11000131.0,7,4.0,7.0,7.0,7.0,7.0,4.0,3.0,1.0,67.0,1.0
-DE,11000181.0,7,2.0,2.0,2.0,2.0,8.0,5.0,3.0,1.0,41.0,1.0
-DE,11000251.0,7,1.0,8.0,7.0,5.0,8.0,5.0,3.0,2.0,65.0,1.0
-DE,11000291.0,7,0.0,10.0,10.0,7.0,8.0,5.0,3.0,1.0,54.0,1.0
-DE,11000341.0,7,2.0,6.0,6.0,4.0,8.0,3.0,3.0,2.0,36.0,1.0
-DE,11000421.0,7,4.0,5.0,7.0,5.0,5.0,5.0,3.0,2.0,56.0,1.0
-DE,11000971.0,7,4.0,5.0,8.0,5.0,9.0,4.0,3.0,1.0,65.0,1.0
-DE,11001031.0,7,7.0,8.0,10.0,10.0,10.0,5.0,1.0,2.0,85.0,2.0
-DE,11001401.0,7,1.0,3.0,5.0,8.0,6.0,4.0,2.0,2.0,49.0,1.0
-DE,11001431.0,7,6.0,2.0,7.0,8.0,9.0,4.0,3.0,2.0,89.0,2.0
-ES,1.0,6,7.0,3.0,3.0,3.0,9.0,7.0,3.0,2.0,70.0,2.0
-ES,3.0,6,6.0,7.0,6.0,6.0,7.0,5.0,2.0,2.0,54.0,2.0
-ES,5.0,6,4.0,5.0,7.0,5.0,10.0,6.0,1.0,2.0,38.0,1.0
-ES,6.0,6,5.0,6.0,5.0,6.0,8.0,4.0,2.0,2.0,35.0,2.0
-ES,8.0,6,7.0,7.0,5.0,3.0,7.0,7.0,1.0,2.0,46.0,1.0
-ES,10.0,6,2.0,7.0,7.0,5.0,9.0,5.0,3.0,1.0,38.0,1.0
-ES,15.0,6,4.0,3.0,3.0,5.0,7.0,4.0,2.0,2.0,52.0,1.0
-ES,18.0,6,2.0,4.0,3.0,3.0,3.0,5.0,3.0,1.0,18.0,2.0
-ES,19.0,6,7.0,3.0,2.0,2.0,8.0,5.0,2.0,1.0,56.0,1.0
-ES,22.0,6,3.0,6.0,5.0,3.0,6.0,6.0,4.0,2.0,69.0,2.0
-ES,23.0,6,5.0,8.0,8.0,8.0,6.0,6.0,2.0,1.0,55.0,2.0
-ES,25.0,6,3.0,7.0,7.0,7.0,7.0,6.0,3.0,2.0,32.0,2.0
-ES,27.0,6,6.0,6.0,2.0,4.0,7.0,7.0,2.0,1.0,61.0,1.0
-ES,28.0,6,2.0,4.0,4.0,5.0,8.0,6.0,3.0,2.0,47.0,1.0
-ES,33.0,6,3.0,4.0,5.0,4.0,10.0,7.0,3.0,1.0,48.0,1.0
-ES,34.0,6,5.0,6.0,5.0,6.0,5.0,3.0,2.0,1.0,45.0,1.0
-ES,36.0,6,2.0,2.0,2.0,0.0,8.0,7.0,3.0,1.0,44.0,1.0
-ES,38.0,6,2.0,8.0,7.0,6.0,9.0,6.0,3.0,2.0,60.0,1.0
-ES,39.0,6,7.0,8.0,8.0,8.0,10.0,6.0,4.0,2.0,73.0,1.0
-ES,41.0,6,5.0,5.0,7.0,3.0,8.0,7.0,3.0,1.0,30.0,2.0
-ES,44.0,6,0.0,5.0,5.0,2.0,10.0,4.0,4.0,1.0,28.0,2.0
-ES,45.0,6,2.0,6.0,6.0,6.0,10.0,4.0,3.0,1.0,34.0,1.0
-ES,46.0,6,4.0,5.0,8.0,3.0,9.0,6.0,3.0,2.0,61.0,1.0
-ES,47.0,6,7.0,6.0,6.0,6.0,7.0,4.0,3.0,1.0,76.0,1.0
-ES,48.0,6,3.0,7.0,7.0,6.0,6.0,6.0,3.0,2.0,47.0,1.0
-ES,50.0,6,7.0,3.0,3.0,3.0,8.0,5.0,4.0,2.0,27.0,1.0
-ES,52.0,6,5.0,4.0,5.0,4.0,8.0,6.0,3.0,1.0,45.0,2.0
-ES,53.0,6,3.0,4.0,3.0,5.0,6.0,5.0,4.0,1.0,51.0,1.0
-ES,55.0,6,3.0,5.0,5.0,5.0,6.0,7.0,1.0,2.0,26.0,2.0
-ES,56.0,6,5.0,4.0,5.0,4.0,6.0,6.0,3.0,2.0,56.0,1.0
-ES,61.0,6,7.0,3.0,5.0,5.0,5.0,7.0,3.0,2.0,69.0,2.0
-ES,62.0,6,5.0,5.0,6.0,9.0,9.0,7.0,3.0,2.0,36.0,1.0
-ES,64.0,6,0.0,7.0,7.0,3.0,7.0,3.0,4.0,1.0,34.0,1.0
-ES,70.0,6,2.0,8.0,7.0,7.0,8.0,7.0,2.0,2.0,44.0,2.0
-ES,71.0,6,2.0,5.0,5.0,5.0,10.0,6.0,1.0,2.0,57.0,1.0
-ES,75.0,6,6.0,5.0,2.0,7.0,10.0,3.0,1.0,2.0,27.0,1.0
-ES,78.0,6,7.0,5.0,4.0,7.0,5.0,5.0,2.0,2.0,57.0,2.0
-ES,79.0,6,2.0,7.0,5.0,2.0,8.0,5.0,4.0,2.0,32.0,1.0
-ES,80.0,6,2.0,10.0,4.0,,5.0,7.0,3.0,2.0,63.0,2.0
-ES,82.0,6,3.0,5.0,6.0,6.0,7.0,6.0,2.0,2.0,43.0,1.0
-ES,86.0,6,3.0,8.0,5.0,7.0,8.0,3.0,4.0,1.0,36.0,1.0
-ES,87.0,6,7.0,0.0,5.0,6.0,6.0,5.0,4.0,2.0,70.0,2.0
-ES,95.0,6,3.0,3.0,5.0,5.0,5.0,6.0,2.0,2.0,50.0,2.0
-ES,96.0,6,5.0,7.0,6.0,8.0,7.0,6.0,3.0,2.0,19.0,2.0
-ES,98.0,6,7.0,4.0,5.0,4.0,10.0,7.0,2.0,2.0,20.0,2.0
-ES,106.0,6,2.0,5.0,5.0,8.0,6.0,6.0,2.0,1.0,60.0,1.0
-ES,108.0,6,2.0,5.0,5.0,3.0,8.0,5.0,2.0,1.0,38.0,2.0
-ES,109.0,6,2.0,5.0,5.0,2.0,7.0,7.0,3.0,2.0,43.0,1.0
-ES,110.0,6,3.0,5.0,5.0,5.0,5.0,5.0,1.0,2.0,63.0,1.0
-ES,112.0,6,5.0,6.0,8.0,8.0,10.0,6.0,1.0,1.0,33.0,2.0
-ES,113.0,6,4.0,4.0,9.0,9.0,9.0,7.0,2.0,2.0,31.0,1.0
-ES,117.0,6,7.0,5.0,8.0,7.0,8.0,7.0,3.0,1.0,67.0,1.0
-ES,119.0,6,7.0,2.0,4.0,2.0,5.0,5.0,3.0,2.0,76.0,1.0
-ES,120.0,6,7.0,4.0,5.0,5.0,6.0,5.0,1.0,1.0,40.0,1.0
-ES,122.0,6,1.0,5.0,5.0,6.0,7.0,6.0,4.0,2.0,67.0,1.0
-ES,134.0,6,1.0,0.0,0.0,4.0,6.0,7.0,2.0,1.0,67.0,2.0
-ES,138.0,6,5.0,9.0,9.0,5.0,9.0,4.0,1.0,2.0,54.0,1.0
-ES,140.0,6,5.0,0.0,0.0,0.0,10.0,6.0,3.0,2.0,55.0,1.0
-ES,153.0,6,4.0,4.0,3.0,3.0,6.0,1.0,1.0,2.0,68.0,1.0
-ES,156.0,6,5.0,6.0,8.0,5.0,8.0,,3.0,2.0,57.0,1.0
-ES,159.0,6,2.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,36.0,1.0
-ES,160.0,6,5.0,6.0,7.0,0.0,8.0,6.0,3.0,2.0,30.0,1.0
-ES,171.0,6,2.0,5.0,4.0,5.0,6.0,7.0,2.0,2.0,47.0,1.0
-ES,172.0,6,6.0,7.0,6.0,6.0,10.0,7.0,2.0,2.0,17.0,2.0
-ES,173.0,6,7.0,5.0,5.0,6.0,7.0,5.0,4.0,2.0,60.0,1.0
-ES,176.0,6,4.0,10.0,7.0,6.0,7.0,7.0,4.0,2.0,23.0,2.0
-ES,180.0,6,4.0,3.0,3.0,5.0,7.0,5.0,3.0,1.0,42.0,2.0
-ES,181.0,6,1.0,1.0,5.0,2.0,7.0,4.0,1.0,1.0,32.0,1.0
-ES,183.0,6,1.0,0.0,0.0,0.0,10.0,7.0,5.0,2.0,21.0,2.0
-ES,184.0,6,2.0,6.0,7.0,7.0,7.0,5.0,2.0,2.0,46.0,1.0
-ES,188.0,6,5.0,6.0,7.0,3.0,5.0,5.0,2.0,1.0,30.0,1.0
-ES,189.0,6,5.0,6.0,7.0,8.0,6.0,6.0,3.0,1.0,21.0,2.0
-ES,190.0,6,4.0,6.0,5.0,5.0,8.0,7.0,3.0,2.0,41.0,1.0
-ES,194.0,6,2.0,5.0,2.0,3.0,5.0,5.0,1.0,2.0,29.0,1.0
-ES,202.0,6,5.0,6.0,5.0,5.0,8.0,6.0,1.0,2.0,,2.0
-ES,204.0,6,3.0,7.0,5.0,3.0,9.0,6.0,3.0,1.0,27.0,2.0
-ES,206.0,6,4.0,6.0,7.0,8.0,8.0,7.0,2.0,1.0,40.0,1.0
-ES,208.0,6,3.0,4.0,3.0,4.0,9.0,3.0,2.0,1.0,72.0,1.0
-ES,209.0,6,4.0,9.0,8.0,5.0,9.0,5.0,3.0,1.0,52.0,1.0
-ES,213.0,6,4.0,2.0,2.0,0.0,8.0,5.0,3.0,2.0,40.0,1.0
-ES,216.0,6,1.0,6.0,6.0,6.0,9.0,6.0,3.0,2.0,41.0,1.0
-ES,218.0,6,6.0,3.0,5.0,6.0,9.0,7.0,3.0,1.0,45.0,1.0
-ES,219.0,6,7.0,7.0,7.0,7.0,9.0,5.0,4.0,1.0,68.0,1.0
-ES,221.0,6,5.0,7.0,5.0,3.0,9.0,7.0,3.0,2.0,51.0,1.0
-ES,223.0,6,2.0,7.0,6.0,10.0,8.0,5.0,4.0,2.0,57.0,1.0
-ES,225.0,6,5.0,8.0,7.0,6.0,9.0,4.0,4.0,1.0,23.0,2.0
-ES,226.0,6,0.0,6.0,7.0,4.0,7.0,6.0,2.0,1.0,22.0,2.0
-ES,228.0,6,3.0,7.0,5.0,5.0,5.0,6.0,3.0,1.0,35.0,1.0
-ES,229.0,6,2.0,4.0,4.0,4.0,5.0,6.0,1.0,1.0,40.0,1.0
-ES,232.0,6,3.0,3.0,5.0,3.0,9.0,6.0,3.0,2.0,39.0,1.0
-ES,233.0,6,3.0,6.0,6.0,6.0,7.0,4.0,5.0,2.0,46.0,1.0
-ES,235.0,6,3.0,9.0,9.0,7.0,9.0,6.0,3.0,2.0,42.0,1.0
-ES,236.0,6,4.0,4.0,3.0,3.0,7.0,5.0,2.0,2.0,51.0,1.0
-ES,238.0,6,2.0,4.0,5.0,3.0,7.0,4.0,2.0,2.0,30.0,2.0
-ES,242.0,6,5.0,5.0,7.0,8.0,8.0,7.0,3.0,1.0,38.0,2.0
-ES,244.0,6,1.0,7.0,7.0,3.0,8.0,5.0,2.0,1.0,16.0,2.0
-ES,247.0,6,5.0,7.0,7.0,7.0,8.0,7.0,4.0,2.0,35.0,1.0
-ES,248.0,6,7.0,3.0,3.0,3.0,10.0,2.0,2.0,1.0,44.0,1.0
-ES,251.0,6,5.0,5.0,3.0,5.0,8.0,5.0,3.0,1.0,54.0,1.0
-ES,252.0,6,6.0,6.0,6.0,6.0,5.0,3.0,2.0,1.0,52.0,2.0
-ES,253.0,6,1.0,7.0,8.0,9.0,8.0,5.0,2.0,2.0,41.0,1.0
-ES,254.0,6,7.0,4.0,3.0,5.0,10.0,5.0,3.0,2.0,75.0,1.0
-ES,261.0,6,7.0,5.0,5.0,2.0,9.0,6.0,4.0,2.0,74.0,2.0
-ES,262.0,6,5.0,5.0,7.0,4.0,6.0,2.0,2.0,1.0,68.0,1.0
-ES,263.0,6,7.0,5.0,5.0,8.0,9.0,2.0,2.0,2.0,55.0,1.0
-ES,264.0,6,6.0,2.0,8.0,3.0,10.0,7.0,,2.0,,2.0
-ES,265.0,6,3.0,5.0,7.0,9.0,7.0,5.0,2.0,2.0,53.0,1.0
-ES,269.0,6,7.0,4.0,6.0,7.0,10.0,7.0,3.0,1.0,46.0,1.0
-ES,270.0,6,1.0,5.0,7.0,8.0,9.0,3.0,4.0,1.0,41.0,2.0
-ES,272.0,6,3.0,2.0,5.0,5.0,5.0,4.0,3.0,1.0,70.0,1.0
-ES,276.0,6,1.0,5.0,5.0,5.0,7.0,4.0,2.0,2.0,49.0,2.0
-ES,277.0,6,7.0,0.0,3.0,4.0,10.0,7.0,2.0,1.0,39.0,1.0
-ES,280.0,6,4.0,5.0,1.0,5.0,9.0,5.0,3.0,2.0,64.0,1.0
-ES,281.0,6,4.0,3.0,4.0,5.0,7.0,7.0,4.0,2.0,72.0,2.0
-ES,283.0,6,1.0,5.0,5.0,6.0,7.0,3.0,1.0,2.0,48.0,1.0
-ES,284.0,6,4.0,1.0,1.0,1.0,10.0,7.0,1.0,1.0,90.0,2.0
-ES,287.0,6,2.0,3.0,6.0,5.0,8.0,6.0,3.0,2.0,31.0,2.0
-ES,290.0,6,2.0,4.0,5.0,5.0,6.0,6.0,2.0,2.0,34.0,2.0
-ES,291.0,6,4.0,5.0,5.0,7.0,7.0,5.0,1.0,2.0,49.0,1.0
-ES,292.0,6,3.0,6.0,3.0,3.0,8.0,6.0,4.0,2.0,31.0,2.0
-ES,293.0,6,7.0,8.0,5.0,6.0,8.0,4.0,1.0,2.0,60.0,1.0
-ES,301.0,6,3.0,2.0,5.0,5.0,8.0,6.0,3.0,1.0,39.0,2.0
-ES,304.0,6,5.0,3.0,1.0,6.0,8.0,4.0,4.0,1.0,41.0,1.0
-ES,305.0,6,4.0,8.0,8.0,8.0,8.0,3.0,3.0,2.0,47.0,1.0
-ES,307.0,6,2.0,8.0,8.0,5.0,7.0,7.0,4.0,1.0,40.0,1.0
-ES,312.0,6,4.0,3.0,1.0,0.0,6.0,6.0,1.0,2.0,44.0,1.0
-ES,315.0,6,3.0,7.0,8.0,1.0,9.0,4.0,3.0,1.0,16.0,2.0
-ES,317.0,6,7.0,7.0,8.0,10.0,10.0,6.0,3.0,2.0,59.0,1.0
-ES,319.0,6,4.0,7.0,9.0,8.0,10.0,3.0,3.0,1.0,60.0,1.0
-ES,321.0,6,4.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,75.0,1.0
-ES,323.0,6,5.0,5.0,6.0,4.0,10.0,4.0,1.0,1.0,42.0,1.0
-ES,325.0,6,3.0,8.0,7.0,6.0,9.0,7.0,4.0,1.0,26.0,2.0
-ES,326.0,6,2.0,3.0,4.0,4.0,10.0,6.0,2.0,1.0,36.0,1.0
-ES,327.0,6,2.0,5.0,3.0,3.0,4.0,4.0,2.0,1.0,47.0,2.0
-ES,328.0,6,3.0,6.0,7.0,6.0,9.0,4.0,2.0,2.0,33.0,1.0
-ES,329.0,6,6.0,5.0,5.0,6.0,7.0,7.0,4.0,1.0,31.0,2.0
-ES,330.0,6,7.0,0.0,10.0,0.0,7.0,7.0,2.0,2.0,82.0,2.0
-ES,333.0,6,7.0,4.0,0.0,0.0,10.0,1.0,1.0,1.0,63.0,2.0
-ES,337.0,6,4.0,8.0,6.0,5.0,5.0,2.0,1.0,2.0,56.0,2.0
-ES,347.0,6,7.0,3.0,3.0,5.0,7.0,5.0,3.0,1.0,49.0,1.0
-ES,348.0,6,0.0,7.0,7.0,7.0,8.0,7.0,4.0,1.0,22.0,2.0
-ES,351.0,6,5.0,5.0,6.0,5.0,6.0,6.0,2.0,1.0,38.0,1.0
-ES,354.0,6,7.0,5.0,5.0,5.0,5.0,6.0,1.0,2.0,,1.0
-ES,356.0,6,7.0,7.0,2.0,4.0,7.0,6.0,3.0,2.0,,1.0
-ES,357.0,6,7.0,7.0,7.0,9.0,9.0,4.0,3.0,1.0,49.0,1.0
-ES,360.0,6,4.0,10.0,10.0,0.0,10.0,7.0,3.0,1.0,47.0,2.0
-ES,363.0,6,3.0,7.0,8.0,10.0,10.0,6.0,3.0,1.0,35.0,1.0
-ES,366.0,6,5.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,29.0,1.0
-ES,373.0,6,5.0,7.0,6.0,8.0,9.0,4.0,4.0,1.0,63.0,1.0
-ES,374.0,6,7.0,6.0,6.0,5.0,7.0,3.0,2.0,2.0,76.0,2.0
-ES,378.0,6,6.0,6.0,7.0,7.0,7.0,5.0,3.0,2.0,75.0,2.0
-ES,381.0,6,0.0,10.0,10.0,7.0,7.0,6.0,4.0,2.0,56.0,1.0
-ES,382.0,6,6.0,2.0,2.0,2.0,6.0,6.0,,2.0,46.0,1.0
-ES,383.0,6,4.0,3.0,3.0,3.0,4.0,2.0,1.0,1.0,51.0,2.0
-ES,385.0,6,7.0,3.0,0.0,0.0,7.0,1.0,2.0,2.0,35.0,1.0
-ES,386.0,6,2.0,7.0,7.0,7.0,7.0,6.0,3.0,2.0,18.0,2.0
-ES,387.0,6,1.0,3.0,3.0,2.0,10.0,7.0,3.0,2.0,21.0,2.0
-ES,389.0,6,5.0,5.0,8.0,3.0,9.0,5.0,2.0,1.0,46.0,1.0
-ES,395.0,6,7.0,6.0,6.0,7.0,7.0,4.0,2.0,1.0,30.0,2.0
-ES,396.0,6,5.0,5.0,6.0,6.0,7.0,5.0,1.0,1.0,,1.0
-ES,398.0,6,5.0,8.0,2.0,5.0,5.0,7.0,2.0,2.0,48.0,2.0
-ES,405.0,6,7.0,7.0,5.0,6.0,6.0,2.0,2.0,1.0,,1.0
-ES,406.0,6,4.0,3.0,4.0,3.0,7.0,1.0,1.0,2.0,71.0,2.0
-ES,407.0,6,3.0,4.0,4.0,5.0,8.0,7.0,3.0,2.0,,2.0
-ES,411.0,6,3.0,3.0,3.0,7.0,10.0,5.0,3.0,2.0,39.0,1.0
-ES,415.0,6,7.0,2.0,1.0,0.0,5.0,6.0,1.0,1.0,35.0,1.0
-ES,416.0,6,2.0,0.0,1.0,1.0,7.0,4.0,4.0,2.0,69.0,1.0
-ES,417.0,6,3.0,2.0,7.0,7.0,10.0,4.0,4.0,1.0,24.0,2.0
-ES,431.0,6,2.0,7.0,7.0,6.0,8.0,3.0,2.0,2.0,63.0,2.0
-ES,433.0,6,7.0,5.0,7.0,5.0,10.0,7.0,1.0,1.0,103.0,2.0
-ES,435.0,6,3.0,6.0,4.0,0.0,5.0,2.0,1.0,2.0,47.0,1.0
-ES,437.0,6,7.0,2.0,0.0,1.0,7.0,2.0,3.0,1.0,64.0,1.0
-ES,440.0,6,3.0,4.0,4.0,5.0,6.0,7.0,2.0,2.0,17.0,2.0
-ES,441.0,6,3.0,6.0,7.0,6.0,9.0,7.0,4.0,2.0,30.0,1.0
-ES,442.0,6,5.0,5.0,5.0,5.0,6.0,6.0,1.0,2.0,65.0,1.0
-ES,443.0,6,2.0,7.0,6.0,4.0,8.0,7.0,3.0,2.0,24.0,2.0
-ES,444.0,6,4.0,10.0,7.0,8.0,8.0,2.0,2.0,2.0,45.0,1.0
-ES,461.0,6,2.0,2.0,0.0,5.0,2.0,2.0,1.0,1.0,26.0,1.0
-ES,463.0,6,1.0,3.0,7.0,4.0,7.0,5.0,2.0,1.0,52.0,1.0
-ES,464.0,6,0.0,4.0,7.0,0.0,8.0,4.0,3.0,1.0,44.0,1.0
-ES,468.0,6,7.0,3.0,2.0,5.0,8.0,6.0,2.0,1.0,33.0,2.0
-ES,471.0,6,6.0,5.0,2.0,6.0,10.0,3.0,1.0,2.0,48.0,1.0
-ES,474.0,6,6.0,4.0,4.0,5.0,5.0,6.0,3.0,2.0,64.0,1.0
-ES,475.0,6,3.0,8.0,,,10.0,5.0,3.0,1.0,,1.0
-ES,482.0,6,7.0,8.0,5.0,8.0,8.0,1.0,2.0,2.0,,1.0
-ES,486.0,6,7.0,0.0,0.0,0.0,10.0,5.0,1.0,2.0,,2.0
-ES,489.0,6,6.0,3.0,4.0,5.0,8.0,7.0,3.0,2.0,73.0,1.0
-ES,492.0,6,5.0,7.0,4.0,5.0,6.0,7.0,3.0,1.0,45.0,2.0
-ES,499.0,6,3.0,5.0,5.0,5.0,6.0,4.0,4.0,1.0,38.0,1.0
-ES,501.0,6,3.0,4.0,5.0,4.0,6.0,6.0,2.0,2.0,64.0,2.0
-ES,503.0,6,6.0,7.0,7.0,7.0,9.0,7.0,5.0,2.0,73.0,2.0
-ES,508.0,6,7.0,4.0,5.0,1.0,6.0,6.0,1.0,1.0,33.0,2.0
-ES,514.0,6,0.0,8.0,8.0,4.0,8.0,6.0,3.0,1.0,32.0,2.0
-ES,520.0,6,3.0,5.0,3.0,5.0,9.0,4.0,1.0,1.0,78.0,2.0
-ES,523.0,6,5.0,7.0,8.0,7.0,9.0,6.0,3.0,1.0,56.0,1.0
-ES,525.0,6,1.0,4.0,3.0,4.0,8.0,2.0,1.0,2.0,22.0,2.0
-ES,532.0,6,0.0,8.0,8.0,3.0,8.0,1.0,1.0,2.0,53.0,1.0
-ES,540.0,6,7.0,0.0,10.0,0.0,8.0,5.0,2.0,1.0,,1.0
-ES,546.0,6,5.0,6.0,6.0,4.0,9.0,7.0,2.0,2.0,31.0,1.0
-ES,547.0,6,5.0,5.0,3.0,0.0,9.0,5.0,1.0,2.0,83.0,1.0
-ES,548.0,6,7.0,0.0,0.0,0.0,8.0,6.0,2.0,1.0,63.0,1.0
-ES,552.0,6,7.0,2.0,3.0,3.0,6.0,2.0,2.0,1.0,59.0,1.0
-ES,553.0,6,5.0,5.0,5.0,2.0,10.0,7.0,4.0,1.0,76.0,1.0
-ES,554.0,6,6.0,5.0,3.0,4.0,8.0,7.0,4.0,2.0,46.0,1.0
-ES,555.0,6,3.0,4.0,5.0,4.0,4.0,5.0,2.0,1.0,53.0,2.0
-ES,558.0,6,5.0,7.0,5.0,0.0,9.0,3.0,3.0,2.0,64.0,1.0
-ES,561.0,6,3.0,7.0,4.0,2.0,7.0,7.0,2.0,1.0,18.0,2.0
-ES,563.0,6,4.0,7.0,6.0,8.0,8.0,5.0,3.0,1.0,51.0,1.0
-ES,567.0,6,6.0,5.0,5.0,5.0,4.0,6.0,3.0,1.0,57.0,1.0
-ES,569.0,6,3.0,8.0,7.0,5.0,9.0,6.0,3.0,2.0,34.0,1.0
-ES,572.0,6,3.0,7.0,8.0,5.0,10.0,6.0,3.0,1.0,71.0,1.0
-ES,574.0,6,7.0,3.0,5.0,4.0,5.0,7.0,2.0,1.0,46.0,2.0
-ES,575.0,6,2.0,10.0,10.0,8.0,10.0,7.0,3.0,1.0,71.0,1.0
-ES,576.0,6,1.0,5.0,5.0,5.0,6.0,6.0,3.0,1.0,54.0,2.0
-ES,578.0,6,3.0,4.0,3.0,6.0,9.0,5.0,2.0,1.0,48.0,1.0
-ES,579.0,6,3.0,5.0,8.0,3.0,7.0,4.0,1.0,1.0,49.0,1.0
-ES,580.0,6,5.0,6.0,7.0,6.0,8.0,7.0,3.0,2.0,22.0,2.0
-ES,583.0,6,3.0,4.0,5.0,3.0,7.0,7.0,3.0,1.0,24.0,2.0
-ES,585.0,6,4.0,7.0,7.0,3.0,0.0,7.0,2.0,1.0,49.0,2.0
-ES,587.0,6,7.0,3.0,3.0,3.0,10.0,5.0,2.0,2.0,64.0,1.0
-ES,590.0,6,7.0,8.0,8.0,5.0,3.0,2.0,1.0,1.0,45.0,1.0
-ES,592.0,6,7.0,6.0,6.0,4.0,8.0,6.0,3.0,1.0,76.0,1.0
-ES,593.0,6,1.0,5.0,5.0,5.0,8.0,5.0,2.0,1.0,35.0,1.0
-ES,596.0,6,7.0,8.0,8.0,5.0,8.0,6.0,3.0,2.0,60.0,2.0
-ES,598.0,6,4.0,5.0,5.0,3.0,9.0,7.0,4.0,2.0,82.0,2.0
-ES,599.0,6,6.0,7.0,7.0,4.0,8.0,6.0,2.0,1.0,35.0,2.0
-ES,600.0,6,5.0,5.0,7.0,3.0,7.0,5.0,3.0,2.0,20.0,2.0
-ES,602.0,6,4.0,2.0,3.0,3.0,8.0,4.0,1.0,2.0,34.0,1.0
-ES,603.0,6,5.0,6.0,2.0,3.0,8.0,2.0,3.0,2.0,16.0,2.0
-ES,604.0,6,7.0,5.0,3.0,5.0,6.0,7.0,,1.0,52.0,1.0
-ES,605.0,6,2.0,4.0,4.0,5.0,10.0,3.0,1.0,1.0,33.0,1.0
-ES,608.0,6,5.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,48.0,1.0
-ES,613.0,6,7.0,5.0,8.0,3.0,7.0,4.0,,2.0,68.0,1.0
-ES,614.0,6,7.0,4.0,5.0,0.0,5.0,7.0,3.0,2.0,36.0,2.0
-ES,623.0,6,5.0,1.0,6.0,3.0,2.0,2.0,1.0,2.0,58.0,1.0
-ES,628.0,6,4.0,5.0,5.0,4.0,7.0,6.0,3.0,1.0,17.0,2.0
-ES,635.0,6,2.0,7.0,7.0,7.0,8.0,4.0,3.0,1.0,61.0,2.0
-ES,636.0,6,5.0,4.0,5.0,2.0,6.0,7.0,4.0,1.0,20.0,2.0
-ES,639.0,6,7.0,7.0,7.0,5.0,7.0,2.0,3.0,1.0,72.0,2.0
-ES,645.0,6,1.0,3.0,5.0,5.0,6.0,5.0,2.0,2.0,61.0,1.0
-ES,646.0,6,4.0,8.0,8.0,6.0,8.0,7.0,3.0,2.0,21.0,2.0
-ES,647.0,6,5.0,3.0,2.0,2.0,5.0,2.0,,2.0,70.0,2.0
-ES,650.0,6,7.0,3.0,3.0,1.0,8.0,7.0,3.0,1.0,32.0,2.0
-ES,651.0,6,5.0,3.0,5.0,4.0,8.0,6.0,1.0,1.0,67.0,2.0
-ES,652.0,6,7.0,10.0,9.0,2.0,10.0,3.0,3.0,2.0,72.0,1.0
-ES,653.0,6,2.0,2.0,5.0,5.0,10.0,4.0,3.0,2.0,48.0,1.0
-ES,654.0,6,6.0,6.0,8.0,3.0,8.0,5.0,3.0,1.0,52.0,1.0
-ES,655.0,6,2.0,5.0,3.0,5.0,8.0,4.0,3.0,1.0,70.0,1.0
-ES,656.0,6,7.0,8.0,8.0,9.0,8.0,5.0,3.0,1.0,64.0,2.0
-ES,660.0,6,1.0,0.0,5.0,6.0,8.0,5.0,3.0,2.0,76.0,2.0
-ES,662.0,6,2.0,2.0,2.0,2.0,8.0,5.0,4.0,2.0,64.0,1.0
-ES,663.0,6,0.0,8.0,6.0,5.0,7.0,4.0,3.0,1.0,50.0,1.0
-ES,665.0,6,7.0,3.0,4.0,7.0,6.0,6.0,2.0,2.0,79.0,2.0
-ES,666.0,6,2.0,6.0,7.0,6.0,10.0,6.0,4.0,2.0,80.0,1.0
-ES,667.0,6,7.0,6.0,8.0,6.0,9.0,5.0,3.0,1.0,30.0,1.0
-ES,670.0,6,0.0,9.0,4.0,5.0,9.0,6.0,2.0,2.0,43.0,1.0
-ES,673.0,6,3.0,5.0,5.0,7.0,8.0,5.0,2.0,2.0,52.0,1.0
-ES,676.0,6,6.0,5.0,5.0,7.0,9.0,6.0,3.0,1.0,41.0,1.0
-ES,678.0,6,4.0,7.0,8.0,5.0,7.0,6.0,3.0,2.0,70.0,2.0
-ES,686.0,6,5.0,7.0,6.0,5.0,9.0,6.0,3.0,2.0,,1.0
-ES,693.0,6,5.0,5.0,5.0,6.0,7.0,6.0,3.0,2.0,43.0,2.0
-ES,695.0,6,2.0,7.0,7.0,5.0,8.0,4.0,2.0,2.0,34.0,1.0
-ES,698.0,6,1.0,7.0,6.0,6.0,7.0,4.0,1.0,1.0,51.0,1.0
-ES,700.0,6,7.0,7.0,6.0,6.0,9.0,5.0,3.0,1.0,25.0,2.0
-ES,701.0,6,4.0,8.0,8.0,5.0,10.0,7.0,3.0,1.0,68.0,1.0
-ES,703.0,6,7.0,3.0,8.0,9.0,2.0,6.0,1.0,1.0,48.0,2.0
-ES,704.0,6,2.0,7.0,6.0,7.0,3.0,6.0,4.0,1.0,45.0,2.0
-ES,705.0,6,2.0,6.0,3.0,3.0,7.0,3.0,2.0,1.0,45.0,2.0
-ES,706.0,6,2.0,4.0,6.0,4.0,8.0,5.0,2.0,1.0,38.0,1.0
-ES,709.0,6,3.0,7.0,8.0,6.0,8.0,5.0,3.0,2.0,60.0,2.0
-ES,710.0,6,5.0,7.0,8.0,8.0,10.0,7.0,3.0,2.0,81.0,1.0
-ES,714.0,6,5.0,1.0,5.0,4.0,5.0,5.0,2.0,2.0,44.0,1.0
-ES,717.0,6,3.0,5.0,5.0,5.0,10.0,3.0,2.0,2.0,60.0,1.0
-ES,721.0,6,6.0,6.0,6.0,4.0,7.0,6.0,2.0,2.0,52.0,2.0
-ES,722.0,6,5.0,3.0,3.0,,9.0,1.0,1.0,2.0,83.0,1.0
-ES,723.0,6,7.0,5.0,2.0,9.0,10.0,7.0,2.0,2.0,33.0,2.0
-ES,726.0,6,5.0,0.0,5.0,5.0,8.0,5.0,3.0,2.0,90.0,1.0
-ES,727.0,6,4.0,5.0,6.0,5.0,8.0,4.0,3.0,1.0,57.0,1.0
-ES,728.0,6,1.0,7.0,7.0,6.0,9.0,3.0,3.0,1.0,38.0,1.0
-ES,729.0,6,3.0,9.0,6.0,1.0,9.0,4.0,1.0,2.0,41.0,1.0
-ES,731.0,6,1.0,7.0,7.0,6.0,7.0,7.0,3.0,1.0,36.0,2.0
-ES,734.0,6,6.0,6.0,5.0,5.0,5.0,5.0,2.0,1.0,53.0,1.0
-ES,742.0,6,6.0,3.0,5.0,2.0,8.0,6.0,5.0,1.0,25.0,2.0
-ES,743.0,6,0.0,7.0,9.0,4.0,9.0,6.0,3.0,2.0,42.0,1.0
-ES,744.0,6,3.0,7.0,8.0,2.0,8.0,6.0,2.0,1.0,33.0,1.0
-ES,746.0,6,5.0,0.0,0.0,0.0,8.0,7.0,2.0,1.0,51.0,1.0
-ES,747.0,6,4.0,6.0,5.0,6.0,7.0,4.0,3.0,2.0,49.0,1.0
-ES,748.0,6,5.0,3.0,4.0,3.0,4.0,2.0,1.0,1.0,64.0,1.0
-ES,751.0,6,4.0,6.0,6.0,7.0,1.0,2.0,3.0,2.0,72.0,2.0
-ES,763.0,6,4.0,1.0,4.0,4.0,6.0,5.0,3.0,2.0,39.0,1.0
-ES,767.0,6,4.0,0.0,5.0,5.0,7.0,6.0,3.0,2.0,58.0,1.0
-ES,768.0,6,5.0,2.0,2.0,9.0,10.0,7.0,2.0,1.0,80.0,1.0
-ES,770.0,6,3.0,6.0,6.0,8.0,8.0,4.0,1.0,1.0,59.0,1.0
-ES,771.0,6,3.0,3.0,7.0,6.0,10.0,7.0,5.0,1.0,65.0,1.0
-ES,778.0,6,2.0,8.0,8.0,7.0,7.0,4.0,3.0,2.0,47.0,2.0
-ES,781.0,6,7.0,5.0,4.0,6.0,4.0,2.0,3.0,1.0,36.0,2.0
-ES,783.0,6,3.0,7.0,8.0,7.0,7.0,6.0,2.0,2.0,31.0,1.0
-ES,788.0,6,5.0,6.0,6.0,5.0,8.0,5.0,2.0,1.0,50.0,1.0
-ES,792.0,6,1.0,3.0,7.0,2.0,5.0,4.0,2.0,1.0,22.0,2.0
-ES,798.0,6,7.0,6.0,8.0,5.0,7.0,5.0,3.0,1.0,41.0,1.0
-ES,799.0,6,0.0,8.0,7.0,3.0,10.0,5.0,2.0,2.0,57.0,1.0
-ES,802.0,6,1.0,4.0,7.0,1.0,7.0,7.0,2.0,2.0,41.0,1.0
-ES,806.0,6,2.0,3.0,3.0,3.0,9.0,7.0,3.0,2.0,34.0,1.0
-ES,807.0,6,4.0,1.0,0.0,5.0,5.0,4.0,1.0,1.0,38.0,1.0
-ES,812.0,6,4.0,5.0,8.0,5.0,7.0,6.0,3.0,1.0,16.0,2.0
-ES,813.0,6,2.0,6.0,6.0,6.0,7.0,3.0,2.0,2.0,62.0,1.0
-ES,814.0,6,7.0,6.0,7.0,4.0,8.0,7.0,3.0,2.0,51.0,1.0
-ES,815.0,6,6.0,4.0,5.0,7.0,6.0,6.0,2.0,1.0,64.0,1.0
-ES,818.0,6,3.0,8.0,7.0,8.0,8.0,6.0,4.0,2.0,22.0,2.0
-ES,821.0,6,3.0,7.0,6.0,6.0,8.0,5.0,4.0,1.0,61.0,1.0
-ES,824.0,6,2.0,7.0,5.0,3.0,6.0,7.0,3.0,1.0,70.0,1.0
-ES,827.0,6,5.0,5.0,6.0,6.0,10.0,4.0,2.0,1.0,62.0,1.0
-ES,833.0,6,2.0,7.0,10.0,8.0,0.0,7.0,1.0,1.0,48.0,2.0
-ES,836.0,6,7.0,5.0,5.0,5.0,5.0,5.0,3.0,2.0,34.0,2.0
-ES,837.0,6,5.0,5.0,7.0,5.0,8.0,5.0,3.0,1.0,41.0,1.0
-ES,842.0,6,3.0,3.0,7.0,5.0,7.0,4.0,5.0,2.0,71.0,2.0
-ES,846.0,6,5.0,5.0,5.0,5.0,9.0,7.0,3.0,2.0,50.0,1.0
-ES,847.0,6,5.0,6.0,5.0,7.0,6.0,6.0,2.0,2.0,17.0,2.0
-ES,851.0,6,7.0,8.0,6.0,7.0,8.0,4.0,3.0,1.0,95.0,1.0
-ES,853.0,6,2.0,3.0,4.0,2.0,10.0,3.0,1.0,2.0,38.0,1.0
-ES,854.0,6,0.0,5.0,4.0,3.0,7.0,4.0,3.0,2.0,21.0,2.0
-ES,855.0,6,7.0,8.0,8.0,7.0,8.0,6.0,3.0,2.0,69.0,1.0
-ES,856.0,6,3.0,5.0,7.0,6.0,6.0,4.0,3.0,1.0,39.0,2.0
-ES,857.0,6,7.0,7.0,6.0,4.0,8.0,6.0,3.0,2.0,74.0,1.0
-ES,858.0,6,3.0,5.0,5.0,5.0,9.0,5.0,3.0,1.0,58.0,1.0
-ES,865.0,6,4.0,8.0,6.0,3.0,8.0,5.0,2.0,2.0,32.0,2.0
-ES,867.0,6,3.0,5.0,5.0,5.0,10.0,7.0,3.0,1.0,19.0,2.0
-ES,872.0,6,3.0,2.0,5.0,5.0,9.0,7.0,3.0,1.0,17.0,2.0
-ES,874.0,6,1.0,8.0,8.0,7.0,7.0,5.0,2.0,1.0,30.0,2.0
-ES,876.0,6,4.0,6.0,6.0,4.0,8.0,4.0,3.0,1.0,42.0,2.0
-ES,879.0,6,6.0,7.0,5.0,6.0,10.0,7.0,1.0,2.0,,1.0
-ES,882.0,6,2.0,0.0,0.0,10.0,5.0,5.0,3.0,2.0,34.0,2.0
-ES,885.0,6,5.0,2.0,5.0,1.0,9.0,6.0,5.0,1.0,18.0,2.0
-ES,886.0,6,4.0,8.0,8.0,8.0,10.0,2.0,1.0,1.0,53.0,1.0
-ES,887.0,6,7.0,5.0,4.0,3.0,6.0,7.0,3.0,2.0,58.0,1.0
-ES,890.0,6,1.0,5.0,5.0,6.0,8.0,5.0,2.0,2.0,25.0,2.0
-ES,892.0,6,1.0,6.0,5.0,5.0,6.0,3.0,1.0,2.0,39.0,1.0
-ES,894.0,6,3.0,4.0,6.0,3.0,7.0,2.0,2.0,1.0,47.0,1.0
-ES,897.0,6,1.0,5.0,5.0,5.0,8.0,6.0,2.0,2.0,44.0,2.0
-ES,898.0,6,2.0,3.0,3.0,3.0,7.0,7.0,3.0,2.0,34.0,1.0
-ES,900.0,6,1.0,5.0,6.0,3.0,8.0,7.0,3.0,1.0,42.0,2.0
-ES,901.0,6,6.0,5.0,5.0,1.0,5.0,6.0,3.0,2.0,32.0,1.0
-ES,903.0,6,7.0,5.0,7.0,9.0,6.0,6.0,1.0,1.0,61.0,2.0
-ES,905.0,6,7.0,6.0,5.0,3.0,9.0,5.0,2.0,2.0,58.0,1.0
-ES,907.0,6,1.0,5.0,8.0,4.0,9.0,5.0,5.0,1.0,78.0,1.0
-ES,909.0,6,5.0,4.0,8.0,7.0,8.0,4.0,2.0,2.0,48.0,1.0
-ES,910.0,6,3.0,5.0,5.0,4.0,5.0,6.0,1.0,1.0,22.0,2.0
-ES,911.0,6,7.0,6.0,8.0,3.0,9.0,3.0,2.0,2.0,64.0,1.0
-ES,913.0,6,2.0,5.0,7.0,2.0,7.0,7.0,4.0,1.0,43.0,1.0
-ES,916.0,6,6.0,4.0,4.0,6.0,4.0,7.0,1.0,2.0,83.0,1.0
-ES,917.0,6,7.0,6.0,6.0,4.0,10.0,7.0,3.0,1.0,57.0,1.0
-ES,918.0,6,0.0,6.0,5.0,3.0,7.0,4.0,2.0,2.0,30.0,2.0
-ES,921.0,6,7.0,5.0,5.0,3.0,8.0,7.0,3.0,2.0,,1.0
-ES,923.0,6,1.0,5.0,4.0,6.0,6.0,6.0,3.0,1.0,43.0,1.0
-ES,924.0,6,2.0,2.0,2.0,9.0,8.0,7.0,1.0,2.0,61.0,1.0
-ES,925.0,6,3.0,7.0,2.0,4.0,8.0,6.0,3.0,1.0,36.0,1.0
-ES,926.0,6,3.0,4.0,3.0,3.0,7.0,6.0,2.0,2.0,38.0,1.0
-ES,927.0,6,5.0,2.0,3.0,2.0,7.0,5.0,2.0,1.0,,1.0
-ES,929.0,6,2.0,5.0,5.0,3.0,9.0,5.0,2.0,1.0,42.0,1.0
-ES,930.0,6,3.0,6.0,8.0,7.0,7.0,5.0,2.0,2.0,24.0,2.0
-ES,932.0,6,5.0,8.0,4.0,4.0,8.0,5.0,1.0,1.0,35.0,2.0
-ES,933.0,6,2.0,3.0,5.0,3.0,8.0,4.0,2.0,2.0,27.0,2.0
-ES,934.0,6,3.0,7.0,7.0,4.0,7.0,6.0,4.0,1.0,33.0,1.0
-ES,935.0,6,7.0,6.0,8.0,5.0,10.0,6.0,3.0,2.0,67.0,1.0
-ES,936.0,6,5.0,5.0,5.0,2.0,8.0,5.0,3.0,2.0,44.0,1.0
-ES,937.0,6,1.0,7.0,8.0,10.0,7.0,2.0,4.0,1.0,21.0,2.0
-ES,940.0,6,7.0,3.0,5.0,9.0,10.0,5.0,,2.0,44.0,2.0
-ES,941.0,6,4.0,8.0,8.0,8.0,9.0,7.0,3.0,2.0,18.0,2.0
-ES,942.0,6,7.0,6.0,4.0,7.0,6.0,4.0,1.0,2.0,57.0,2.0
-ES,943.0,6,4.0,7.0,4.0,2.0,8.0,7.0,3.0,2.0,41.0,1.0
-ES,945.0,6,6.0,5.0,6.0,3.0,7.0,6.0,3.0,1.0,59.0,2.0
-ES,946.0,6,7.0,5.0,0.0,1.0,7.0,1.0,2.0,2.0,41.0,1.0
-ES,947.0,6,5.0,2.0,2.0,2.0,3.0,4.0,2.0,2.0,62.0,2.0
-ES,949.0,6,7.0,10.0,10.0,,8.0,7.0,1.0,2.0,73.0,2.0
-ES,950.0,6,4.0,7.0,6.0,5.0,9.0,7.0,3.0,2.0,17.0,2.0
-ES,951.0,6,2.0,7.0,6.0,6.0,8.0,6.0,1.0,1.0,35.0,1.0
-ES,952.0,6,4.0,5.0,6.0,4.0,6.0,3.0,3.0,2.0,37.0,1.0
-ES,953.0,6,4.0,6.0,4.0,6.0,4.0,7.0,3.0,1.0,55.0,1.0
-ES,954.0,6,4.0,5.0,6.0,1.0,10.0,7.0,3.0,1.0,40.0,1.0
-ES,957.0,6,3.0,7.0,6.0,7.0,9.0,3.0,2.0,1.0,47.0,2.0
-ES,959.0,6,5.0,3.0,4.0,5.0,9.0,6.0,3.0,2.0,63.0,1.0
-ES,961.0,6,6.0,5.0,6.0,4.0,9.0,7.0,4.0,1.0,54.0,1.0
-ES,964.0,6,2.0,7.0,7.0,4.0,9.0,6.0,3.0,1.0,41.0,1.0
-ES,967.0,6,2.0,2.0,2.0,4.0,9.0,7.0,1.0,1.0,20.0,2.0
-ES,970.0,6,6.0,6.0,7.0,3.0,9.0,5.0,2.0,2.0,32.0,
-ES,971.0,6,2.0,6.0,5.0,3.0,4.0,5.0,3.0,2.0,27.0,1.0
-ES,972.0,6,6.0,6.0,7.0,6.0,8.0,6.0,3.0,2.0,33.0,1.0
-ES,973.0,6,5.0,1.0,2.0,3.0,2.0,5.0,2.0,1.0,29.0,2.0
-ES,974.0,6,3.0,5.0,1.0,7.0,10.0,7.0,2.0,2.0,54.0,1.0
-ES,975.0,6,4.0,4.0,4.0,5.0,9.0,5.0,3.0,1.0,43.0,1.0
-ES,976.0,6,2.0,5.0,5.0,5.0,10.0,4.0,2.0,2.0,64.0,2.0
-ES,983.0,6,4.0,6.0,6.0,7.0,7.0,6.0,3.0,2.0,18.0,2.0
-ES,984.0,6,3.0,6.0,9.0,5.0,10.0,5.0,4.0,1.0,79.0,1.0
-ES,987.0,6,0.0,6.0,8.0,5.0,9.0,6.0,4.0,2.0,16.0,2.0
-ES,992.0,6,3.0,7.0,6.0,3.0,5.0,4.0,2.0,2.0,40.0,1.0
-ES,993.0,6,7.0,0.0,0.0,0.0,10.0,7.0,1.0,2.0,76.0,1.0
-ES,994.0,6,0.0,7.0,8.0,8.0,9.0,4.0,2.0,2.0,45.0,1.0
-ES,996.0,6,1.0,5.0,5.0,4.0,9.0,7.0,2.0,2.0,17.0,2.0
-ES,1002.0,6,3.0,2.0,2.0,2.0,8.0,7.0,2.0,2.0,40.0,1.0
-ES,1003.0,6,6.0,5.0,5.0,5.0,8.0,7.0,2.0,1.0,74.0,1.0
-ES,1004.0,6,2.0,5.0,5.0,3.0,8.0,6.0,5.0,1.0,39.0,2.0
-ES,1007.0,6,7.0,3.0,4.0,5.0,10.0,7.0,3.0,1.0,65.0,1.0
-ES,1008.0,6,3.0,5.0,5.0,4.0,10.0,2.0,2.0,1.0,30.0,1.0
-ES,1009.0,6,0.0,2.0,2.0,3.0,6.0,5.0,1.0,2.0,97.0,2.0
-ES,1010.0,6,2.0,8.0,7.0,5.0,8.0,3.0,2.0,2.0,24.0,1.0
-ES,1011.0,6,7.0,9.0,8.0,5.0,3.0,7.0,1.0,2.0,54.0,1.0
-ES,1014.0,6,1.0,7.0,7.0,4.0,8.0,4.0,2.0,1.0,38.0,2.0
-ES,1016.0,6,6.0,5.0,5.0,5.0,7.0,4.0,3.0,2.0,51.0,2.0
-ES,1017.0,6,6.0,3.0,3.0,3.0,6.0,4.0,2.0,2.0,57.0,1.0
-ES,1019.0,6,2.0,6.0,6.0,6.0,7.0,7.0,2.0,2.0,50.0,1.0
-ES,1020.0,6,2.0,5.0,7.0,1.0,6.0,4.0,3.0,1.0,44.0,2.0
-ES,1023.0,6,2.0,8.0,6.0,7.0,6.0,7.0,2.0,2.0,90.0,2.0
-ES,1025.0,6,3.0,5.0,6.0,5.0,7.0,7.0,2.0,1.0,34.0,1.0
-ES,1027.0,6,7.0,0.0,2.0,5.0,0.0,6.0,1.0,2.0,84.0,2.0
-ES,1030.0,6,7.0,3.0,0.0,8.0,8.0,5.0,1.0,2.0,53.0,2.0
-ES,1033.0,6,0.0,8.0,5.0,8.0,10.0,7.0,3.0,2.0,29.0,1.0
-ES,1035.0,6,6.0,5.0,3.0,3.0,7.0,4.0,2.0,1.0,57.0,1.0
-ES,1036.0,6,0.0,7.0,8.0,4.0,7.0,6.0,3.0,1.0,37.0,2.0
-ES,1040.0,6,3.0,6.0,7.0,4.0,9.0,6.0,3.0,2.0,20.0,2.0
-ES,1042.0,6,4.0,6.0,6.0,3.0,6.0,6.0,3.0,2.0,44.0,1.0
-ES,1043.0,6,5.0,7.0,4.0,7.0,8.0,6.0,5.0,2.0,54.0,1.0
-ES,1045.0,6,4.0,7.0,7.0,7.0,7.0,6.0,3.0,2.0,43.0,2.0
-ES,1048.0,6,7.0,6.0,4.0,3.0,7.0,3.0,4.0,2.0,64.0,1.0
-ES,1054.0,6,1.0,5.0,7.0,3.0,7.0,6.0,5.0,2.0,74.0,1.0
-ES,1055.0,6,5.0,3.0,2.0,3.0,10.0,7.0,5.0,2.0,51.0,1.0
-ES,1057.0,6,4.0,7.0,7.0,6.0,8.0,7.0,3.0,2.0,33.0,1.0
-ES,1058.0,6,2.0,7.0,8.0,7.0,9.0,6.0,3.0,2.0,43.0,1.0
-ES,1059.0,6,6.0,8.0,7.0,7.0,8.0,6.0,2.0,1.0,72.0,1.0
-ES,1060.0,6,3.0,0.0,0.0,6.0,6.0,7.0,4.0,1.0,58.0,2.0
-ES,1062.0,6,3.0,5.0,5.0,6.0,5.0,6.0,3.0,2.0,69.0,2.0
-ES,1063.0,6,7.0,3.0,3.0,2.0,8.0,3.0,1.0,1.0,44.0,1.0
-ES,1071.0,6,5.0,5.0,1.0,6.0,6.0,6.0,3.0,1.0,33.0,1.0
-ES,1072.0,6,6.0,2.0,8.0,5.0,10.0,5.0,2.0,1.0,37.0,2.0
-ES,1075.0,6,6.0,5.0,5.0,3.0,8.0,3.0,3.0,2.0,55.0,1.0
-ES,1079.0,6,5.0,6.0,7.0,5.0,8.0,4.0,3.0,1.0,53.0,1.0
-ES,1080.0,6,5.0,5.0,5.0,5.0,5.0,6.0,2.0,2.0,73.0,1.0
-ES,1085.0,6,7.0,5.0,8.0,5.0,8.0,6.0,3.0,2.0,69.0,1.0
-ES,1087.0,6,1.0,5.0,5.0,7.0,7.0,6.0,4.0,1.0,45.0,1.0
-ES,1089.0,6,7.0,6.0,6.0,6.0,8.0,5.0,3.0,1.0,50.0,2.0
-ES,1092.0,6,3.0,10.0,10.0,0.0,10.0,2.0,2.0,2.0,68.0,2.0
-ES,1096.0,6,3.0,7.0,7.0,7.0,10.0,6.0,3.0,2.0,53.0,1.0
-ES,1097.0,6,7.0,0.0,0.0,10.0,10.0,5.0,2.0,1.0,51.0,1.0
-ES,1099.0,6,4.0,8.0,7.0,9.0,7.0,4.0,2.0,1.0,30.0,2.0
-ES,1100.0,6,2.0,3.0,8.0,4.0,9.0,5.0,3.0,2.0,16.0,2.0
-ES,1103.0,6,7.0,4.0,5.0,4.0,6.0,3.0,2.0,2.0,65.0,1.0
-ES,1105.0,6,7.0,5.0,5.0,6.0,9.0,6.0,2.0,1.0,73.0,1.0
-ES,1110.0,6,4.0,0.0,0.0,0.0,4.0,7.0,1.0,2.0,74.0,1.0
-ES,1117.0,6,2.0,5.0,5.0,4.0,7.0,5.0,2.0,2.0,45.0,1.0
-ES,1121.0,6,7.0,3.0,4.0,0.0,8.0,1.0,1.0,1.0,49.0,1.0
-ES,1122.0,6,3.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,52.0,1.0
-ES,1123.0,6,6.0,6.0,5.0,6.0,10.0,5.0,2.0,1.0,68.0,1.0
-ES,1125.0,6,7.0,5.0,7.0,4.0,7.0,4.0,4.0,2.0,30.0,1.0
-ES,1129.0,6,2.0,6.0,5.0,7.0,9.0,7.0,5.0,2.0,64.0,2.0
-ES,1130.0,6,5.0,5.0,3.0,3.0,9.0,6.0,3.0,2.0,51.0,1.0
-ES,1133.0,6,7.0,5.0,7.0,4.0,6.0,6.0,3.0,2.0,78.0,1.0
-ES,1135.0,6,2.0,4.0,10.0,10.0,7.0,5.0,2.0,1.0,41.0,1.0
-ES,1136.0,6,7.0,7.0,5.0,8.0,9.0,5.0,2.0,1.0,73.0,1.0
-ES,1139.0,6,6.0,7.0,7.0,5.0,10.0,5.0,3.0,2.0,64.0,1.0
-ES,1141.0,6,1.0,9.0,7.0,6.0,7.0,3.0,3.0,1.0,34.0,2.0
-ES,1142.0,6,4.0,5.0,5.0,3.0,10.0,6.0,3.0,1.0,41.0,1.0
-ES,1143.0,6,2.0,5.0,6.0,4.0,10.0,5.0,2.0,2.0,,1.0
-ES,1147.0,6,7.0,6.0,8.0,3.0,10.0,5.0,1.0,1.0,50.0,2.0
-ES,1151.0,6,1.0,6.0,3.0,3.0,5.0,7.0,1.0,2.0,,2.0
-ES,1152.0,6,0.0,5.0,6.0,8.0,5.0,4.0,1.0,2.0,34.0,1.0
-ES,1154.0,6,4.0,9.0,8.0,8.0,8.0,6.0,4.0,2.0,51.0,1.0
-ES,1158.0,6,7.0,5.0,5.0,4.0,10.0,5.0,2.0,2.0,31.0,1.0
-ES,1159.0,6,7.0,7.0,8.0,6.0,9.0,5.0,3.0,1.0,61.0,1.0
-ES,1160.0,6,3.0,2.0,2.0,1.0,7.0,6.0,2.0,1.0,60.0,1.0
-ES,1161.0,6,2.0,5.0,4.0,3.0,7.0,4.0,3.0,1.0,58.0,2.0
-ES,1162.0,6,2.0,9.0,7.0,4.0,9.0,7.0,1.0,2.0,18.0,2.0
-ES,1163.0,6,7.0,6.0,6.0,7.0,6.0,7.0,2.0,2.0,50.0,1.0
-ES,1165.0,6,3.0,6.0,5.0,6.0,7.0,5.0,3.0,1.0,37.0,1.0
-ES,1167.0,6,1.0,4.0,5.0,4.0,5.0,3.0,3.0,1.0,63.0,1.0
-ES,1168.0,6,1.0,0.0,2.0,0.0,10.0,7.0,4.0,1.0,19.0,2.0
-ES,1169.0,6,1.0,4.0,8.0,5.0,7.0,7.0,3.0,2.0,19.0,2.0
-ES,1173.0,6,5.0,3.0,1.0,4.0,8.0,3.0,1.0,2.0,43.0,1.0
-ES,1177.0,6,5.0,6.0,8.0,8.0,8.0,6.0,3.0,2.0,51.0,1.0
-ES,1178.0,6,6.0,6.0,9.0,5.0,7.0,4.0,2.0,2.0,65.0,1.0
-ES,1179.0,6,1.0,0.0,0.0,3.0,7.0,3.0,2.0,1.0,33.0,1.0
-ES,1181.0,6,5.0,7.0,4.0,5.0,0.0,5.0,1.0,1.0,51.0,2.0
-ES,1182.0,6,2.0,1.0,2.0,4.0,1.0,4.0,3.0,2.0,46.0,1.0
-ES,1184.0,6,5.0,5.0,5.0,5.0,8.0,5.0,1.0,2.0,51.0,2.0
-ES,1185.0,6,1.0,0.0,3.0,3.0,7.0,5.0,4.0,2.0,81.0,2.0
-ES,1191.0,6,7.0,6.0,8.0,7.0,7.0,3.0,3.0,2.0,86.0,2.0
-ES,1195.0,6,3.0,0.0,0.0,0.0,7.0,7.0,3.0,2.0,43.0,1.0
-ES,1197.0,6,4.0,3.0,7.0,7.0,2.0,5.0,1.0,2.0,53.0,1.0
-ES,1199.0,6,7.0,4.0,5.0,5.0,8.0,7.0,2.0,2.0,25.0,2.0
-ES,1200.0,6,1.0,4.0,5.0,5.0,8.0,3.0,1.0,1.0,49.0,1.0
-ES,1201.0,6,5.0,3.0,3.0,6.0,10.0,7.0,3.0,2.0,27.0,1.0
-ES,1204.0,6,3.0,6.0,7.0,6.0,8.0,3.0,5.0,1.0,37.0,1.0
-ES,1206.0,6,4.0,8.0,0.0,7.0,8.0,7.0,1.0,2.0,55.0,1.0
-ES,1207.0,6,7.0,5.0,5.0,5.0,7.0,6.0,3.0,2.0,89.0,2.0
-ES,1208.0,6,1.0,8.0,8.0,7.0,10.0,6.0,1.0,2.0,21.0,2.0
-ES,1209.0,6,5.0,8.0,8.0,5.0,9.0,5.0,4.0,2.0,64.0,1.0
-ES,1210.0,6,2.0,6.0,7.0,6.0,,7.0,3.0,2.0,52.0,2.0
-ES,1211.0,6,0.0,5.0,2.0,5.0,5.0,6.0,2.0,2.0,27.0,2.0
-ES,1213.0,6,7.0,1.0,9.0,2.0,4.0,2.0,1.0,2.0,58.0,1.0
-ES,1215.0,6,3.0,5.0,6.0,5.0,9.0,6.0,3.0,2.0,76.0,1.0
-ES,1218.0,6,3.0,0.0,0.0,0.0,8.0,7.0,3.0,1.0,74.0,2.0
-ES,1220.0,6,2.0,7.0,7.0,6.0,10.0,6.0,3.0,2.0,34.0,1.0
-ES,1226.0,6,7.0,5.0,0.0,4.0,10.0,5.0,2.0,1.0,64.0,1.0
-ES,1227.0,6,2.0,6.0,5.0,5.0,6.0,5.0,3.0,1.0,47.0,1.0
-ES,1228.0,6,5.0,5.0,8.0,5.0,10.0,6.0,5.0,2.0,20.0,2.0
-ES,1229.0,6,3.0,4.0,5.0,6.0,7.0,5.0,3.0,2.0,24.0,2.0
-ES,1230.0,6,4.0,7.0,6.0,6.0,7.0,2.0,2.0,2.0,41.0,1.0
-ES,1231.0,6,2.0,0.0,10.0,5.0,8.0,7.0,2.0,2.0,86.0,2.0
-ES,1232.0,6,4.0,4.0,4.0,5.0,9.0,5.0,2.0,1.0,34.0,2.0
-ES,1234.0,6,3.0,2.0,4.0,3.0,9.0,5.0,3.0,2.0,84.0,2.0
-ES,1236.0,6,3.0,7.0,8.0,7.0,7.0,6.0,3.0,1.0,43.0,1.0
-ES,1237.0,6,3.0,5.0,9.0,5.0,10.0,6.0,3.0,1.0,71.0,1.0
-ES,1239.0,6,1.0,7.0,7.0,3.0,5.0,6.0,2.0,1.0,33.0,2.0
-ES,1242.0,6,6.0,7.0,6.0,7.0,8.0,6.0,2.0,2.0,63.0,1.0
-ES,1245.0,6,1.0,8.0,8.0,5.0,9.0,7.0,2.0,2.0,20.0,2.0
-ES,1246.0,6,7.0,0.0,5.0,2.0,8.0,7.0,4.0,1.0,75.0,2.0
-ES,1247.0,6,2.0,6.0,7.0,3.0,8.0,6.0,2.0,1.0,44.0,2.0
-ES,1248.0,6,3.0,1.0,3.0,6.0,9.0,7.0,3.0,2.0,40.0,1.0
-ES,1251.0,6,6.0,4.0,5.0,3.0,6.0,4.0,1.0,1.0,17.0,2.0
-ES,1252.0,6,2.0,6.0,6.0,4.0,5.0,7.0,2.0,2.0,23.0,2.0
-ES,1253.0,6,2.0,1.0,1.0,1.0,5.0,7.0,3.0,1.0,25.0,2.0
-ES,1254.0,6,2.0,3.0,0.0,5.0,10.0,7.0,5.0,2.0,37.0,1.0
-ES,1257.0,6,3.0,7.0,6.0,6.0,5.0,,3.0,2.0,73.0,1.0
-ES,1260.0,6,7.0,5.0,5.0,3.0,5.0,6.0,2.0,2.0,54.0,2.0
-ES,1262.0,6,3.0,6.0,10.0,10.0,8.0,6.0,3.0,2.0,60.0,1.0
-ES,1265.0,6,6.0,0.0,0.0,,7.0,7.0,3.0,2.0,84.0,2.0
-ES,1268.0,6,5.0,6.0,7.0,10.0,10.0,2.0,2.0,2.0,50.0,1.0
-ES,1270.0,6,3.0,6.0,6.0,7.0,10.0,7.0,2.0,1.0,35.0,1.0
-ES,1272.0,6,3.0,6.0,5.0,7.0,7.0,5.0,2.0,1.0,21.0,2.0
-ES,1275.0,6,4.0,5.0,5.0,6.0,7.0,5.0,3.0,1.0,29.0,1.0
-ES,1280.0,6,3.0,4.0,3.0,3.0,8.0,7.0,3.0,2.0,49.0,1.0
-ES,1283.0,6,2.0,0.0,0.0,0.0,2.0,1.0,1.0,2.0,60.0,1.0
-ES,1285.0,6,2.0,5.0,5.0,6.0,8.0,5.0,3.0,2.0,17.0,2.0
-ES,1287.0,6,4.0,0.0,0.0,10.0,10.0,6.0,1.0,1.0,26.0,1.0
-ES,1293.0,6,7.0,6.0,6.0,4.0,7.0,5.0,3.0,2.0,39.0,
-ES,1294.0,6,5.0,2.0,7.0,2.0,7.0,5.0,3.0,1.0,52.0,1.0
-ES,1299.0,6,7.0,9.0,9.0,8.0,8.0,3.0,2.0,2.0,46.0,1.0
-ES,1306.0,6,2.0,1.0,1.0,3.0,9.0,7.0,2.0,1.0,25.0,2.0
-ES,1307.0,6,6.0,3.0,4.0,5.0,6.0,3.0,3.0,2.0,59.0,1.0
-ES,1308.0,6,7.0,4.0,7.0,4.0,8.0,7.0,1.0,2.0,83.0,1.0
-ES,1314.0,6,1.0,5.0,4.0,5.0,7.0,2.0,3.0,2.0,48.0,2.0
-ES,1316.0,6,2.0,3.0,6.0,3.0,8.0,4.0,3.0,2.0,25.0,1.0
-ES,1318.0,6,3.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,63.0,1.0
-ES,1319.0,6,7.0,6.0,4.0,7.0,8.0,3.0,1.0,1.0,36.0,1.0
-ES,1320.0,6,7.0,3.0,4.0,8.0,9.0,2.0,2.0,2.0,69.0,2.0
-ES,1324.0,6,3.0,5.0,8.0,2.0,5.0,5.0,3.0,1.0,60.0,1.0
-ES,1325.0,6,4.0,4.0,6.0,3.0,9.0,7.0,3.0,2.0,29.0,1.0
-ES,1326.0,6,7.0,0.0,5.0,9.0,8.0,7.0,1.0,2.0,79.0,1.0
-ES,1331.0,6,3.0,10.0,10.0,10.0,5.0,7.0,1.0,2.0,,2.0
-ES,1333.0,6,5.0,7.0,5.0,3.0,7.0,5.0,3.0,2.0,38.0,2.0
-ES,1335.0,6,2.0,7.0,7.0,6.0,8.0,4.0,4.0,1.0,48.0,1.0
-ES,1336.0,6,5.0,6.0,5.0,3.0,7.0,7.0,2.0,1.0,24.0,2.0
-ES,1340.0,6,2.0,7.0,7.0,6.0,8.0,4.0,4.0,1.0,47.0,1.0
-ES,1342.0,6,1.0,5.0,5.0,5.0,10.0,3.0,4.0,1.0,39.0,1.0
-ES,1345.0,6,6.0,5.0,7.0,4.0,10.0,5.0,4.0,1.0,62.0,1.0
-ES,1348.0,6,5.0,5.0,7.0,7.0,7.0,4.0,1.0,2.0,49.0,1.0
-ES,1350.0,6,6.0,7.0,5.0,5.0,6.0,1.0,2.0,2.0,85.0,2.0
-ES,1351.0,6,5.0,5.0,2.0,5.0,2.0,7.0,2.0,2.0,45.0,2.0
-ES,1352.0,6,2.0,6.0,6.0,5.0,9.0,6.0,3.0,2.0,43.0,2.0
-ES,1353.0,6,2.0,6.0,4.0,3.0,8.0,7.0,3.0,1.0,27.0,1.0
-ES,1354.0,6,7.0,0.0,5.0,5.0,5.0,1.0,2.0,2.0,34.0,1.0
-ES,1355.0,6,5.0,7.0,4.0,8.0,8.0,5.0,3.0,2.0,71.0,1.0
-ES,1356.0,6,0.0,2.0,8.0,4.0,10.0,6.0,2.0,2.0,41.0,2.0
-ES,1358.0,6,3.0,6.0,7.0,2.0,8.0,6.0,3.0,1.0,36.0,1.0
-ES,1361.0,6,6.0,0.0,3.0,5.0,5.0,4.0,4.0,2.0,69.0,1.0
-ES,1363.0,6,3.0,3.0,3.0,4.0,9.0,4.0,2.0,1.0,62.0,1.0
-ES,1364.0,6,4.0,7.0,5.0,7.0,9.0,5.0,3.0,2.0,29.0,1.0
-ES,1365.0,6,1.0,5.0,5.0,5.0,9.0,7.0,3.0,1.0,31.0,2.0
-ES,1366.0,6,5.0,5.0,7.0,5.0,10.0,7.0,4.0,2.0,34.0,1.0
-ES,1367.0,6,3.0,3.0,4.0,2.0,5.0,6.0,3.0,2.0,37.0,1.0
-ES,1374.0,6,7.0,6.0,6.0,8.0,8.0,6.0,3.0,1.0,39.0,1.0
-ES,1379.0,6,2.0,5.0,0.0,2.0,5.0,4.0,3.0,1.0,63.0,1.0
-ES,1380.0,6,6.0,7.0,5.0,5.0,10.0,6.0,4.0,1.0,78.0,1.0
-ES,1381.0,6,2.0,4.0,4.0,4.0,8.0,4.0,2.0,2.0,36.0,1.0
-ES,1382.0,6,4.0,8.0,8.0,6.0,9.0,6.0,3.0,1.0,36.0,1.0
-ES,1383.0,6,4.0,5.0,5.0,3.0,3.0,5.0,1.0,2.0,47.0,1.0
-ES,1384.0,6,4.0,5.0,10.0,0.0,10.0,3.0,3.0,2.0,72.0,1.0
-ES,1388.0,6,2.0,0.0,2.0,2.0,9.0,6.0,5.0,2.0,49.0,1.0
-ES,1393.0,6,2.0,6.0,7.0,8.0,9.0,6.0,4.0,1.0,67.0,1.0
-ES,1395.0,6,3.0,3.0,4.0,3.0,10.0,2.0,2.0,1.0,70.0,1.0
-ES,1396.0,6,3.0,6.0,4.0,5.0,8.0,7.0,3.0,1.0,19.0,2.0
-ES,1402.0,6,1.0,7.0,7.0,5.0,7.0,4.0,2.0,1.0,45.0,1.0
-ES,1405.0,6,7.0,5.0,5.0,8.0,8.0,6.0,4.0,1.0,74.0,
-ES,1406.0,6,3.0,4.0,5.0,3.0,8.0,6.0,3.0,2.0,33.0,1.0
-ES,1407.0,6,6.0,6.0,7.0,3.0,10.0,6.0,3.0,2.0,70.0,1.0
-ES,1408.0,6,3.0,7.0,5.0,3.0,6.0,6.0,3.0,1.0,37.0,1.0
-ES,1414.0,6,6.0,6.0,6.0,4.0,3.0,6.0,2.0,1.0,44.0,1.0
-ES,1418.0,6,0.0,5.0,5.0,5.0,10.0,5.0,3.0,2.0,28.0,1.0
-ES,1420.0,6,7.0,8.0,8.0,8.0,10.0,7.0,3.0,2.0,73.0,2.0
-ES,1424.0,6,7.0,0.0,2.0,5.0,0.0,7.0,,2.0,83.0,2.0
-ES,1426.0,6,1.0,4.0,5.0,5.0,8.0,3.0,2.0,1.0,48.0,1.0
-ES,1427.0,6,6.0,7.0,7.0,6.0,6.0,4.0,2.0,1.0,58.0,1.0
-ES,1428.0,6,7.0,6.0,4.0,5.0,8.0,4.0,3.0,2.0,61.0,2.0
-ES,1430.0,6,5.0,5.0,3.0,3.0,7.0,6.0,3.0,1.0,52.0,1.0
-ES,1431.0,6,0.0,6.0,6.0,5.0,8.0,6.0,2.0,1.0,28.0,2.0
-ES,1433.0,6,7.0,7.0,5.0,3.0,10.0,5.0,2.0,1.0,32.0,1.0
-ES,1434.0,6,1.0,7.0,9.0,6.0,10.0,7.0,3.0,2.0,56.0,1.0
-ES,1435.0,6,3.0,6.0,6.0,6.0,5.0,7.0,4.0,1.0,49.0,1.0
-ES,1438.0,6,3.0,5.0,0.0,0.0,8.0,4.0,3.0,2.0,65.0,1.0
-ES,1440.0,6,5.0,8.0,9.0,6.0,10.0,6.0,4.0,1.0,17.0,2.0
-ES,1442.0,6,4.0,5.0,5.0,5.0,6.0,6.0,3.0,1.0,49.0,2.0
-ES,1445.0,6,5.0,3.0,4.0,0.0,8.0,6.0,3.0,2.0,19.0,2.0
-ES,1446.0,6,6.0,6.0,8.0,5.0,7.0,5.0,3.0,1.0,62.0,1.0
-ES,1447.0,6,4.0,4.0,6.0,7.0,8.0,5.0,3.0,1.0,49.0,1.0
-ES,1448.0,6,4.0,5.0,6.0,7.0,5.0,4.0,2.0,2.0,58.0,1.0
-ES,1450.0,6,2.0,6.0,6.0,7.0,8.0,6.0,3.0,2.0,23.0,2.0
-ES,1452.0,6,1.0,5.0,6.0,2.0,5.0,5.0,2.0,1.0,60.0,2.0
-ES,1453.0,6,7.0,1.0,5.0,2.0,7.0,5.0,5.0,2.0,90.0,2.0
-ES,1456.0,6,2.0,7.0,8.0,7.0,9.0,7.0,2.0,2.0,19.0,2.0
-ES,1457.0,6,3.0,8.0,8.0,7.0,3.0,4.0,3.0,2.0,32.0,1.0
-ES,1462.0,6,7.0,0.0,0.0,3.0,7.0,7.0,2.0,1.0,51.0,1.0
-ES,1463.0,6,2.0,5.0,6.0,5.0,6.0,3.0,2.0,2.0,48.0,1.0
-ES,1464.0,6,4.0,5.0,7.0,6.0,5.0,7.0,3.0,2.0,73.0,2.0
-ES,1466.0,6,4.0,5.0,5.0,3.0,8.0,5.0,1.0,2.0,39.0,1.0
-ES,1467.0,6,2.0,7.0,6.0,5.0,7.0,7.0,3.0,2.0,23.0,2.0
-ES,1468.0,6,4.0,5.0,5.0,5.0,8.0,6.0,,1.0,25.0,2.0
-ES,1471.0,6,2.0,5.0,5.0,1.0,7.0,3.0,3.0,2.0,62.0,1.0
-ES,1473.0,6,4.0,8.0,8.0,6.0,10.0,6.0,2.0,2.0,28.0,1.0
-ES,1474.0,6,4.0,5.0,4.0,4.0,7.0,6.0,4.0,1.0,16.0,2.0
-ES,1478.0,6,2.0,7.0,5.0,3.0,9.0,5.0,3.0,1.0,16.0,2.0
-ES,1479.0,6,3.0,4.0,4.0,4.0,7.0,5.0,2.0,1.0,64.0,1.0
-ES,1480.0,6,6.0,5.0,5.0,7.0,10.0,5.0,1.0,2.0,28.0,1.0
-ES,1482.0,6,4.0,6.0,5.0,4.0,8.0,6.0,3.0,1.0,20.0,2.0
-ES,1486.0,6,4.0,4.0,7.0,1.0,7.0,2.0,2.0,1.0,42.0,1.0
-ES,1489.0,6,5.0,7.0,6.0,0.0,8.0,5.0,3.0,2.0,79.0,1.0
-ES,1491.0,6,2.0,5.0,8.0,3.0,3.0,5.0,3.0,1.0,59.0,1.0
-ES,1495.0,6,2.0,5.0,5.0,2.0,6.0,6.0,4.0,2.0,22.0,2.0
-ES,1496.0,6,2.0,6.0,8.0,4.0,7.0,6.0,3.0,2.0,26.0,2.0
-ES,1498.0,6,2.0,4.0,6.0,1.0,8.0,6.0,5.0,1.0,62.0,1.0
-ES,1500.0,6,5.0,6.0,4.0,4.0,7.0,6.0,3.0,2.0,,1.0
-ES,1501.0,6,4.0,5.0,3.0,8.0,10.0,5.0,3.0,1.0,75.0,1.0
-ES,1512.0,6,1.0,3.0,4.0,4.0,8.0,7.0,1.0,1.0,20.0,2.0
-ES,1513.0,6,2.0,7.0,7.0,6.0,8.0,5.0,3.0,1.0,43.0,1.0
-ES,1516.0,6,7.0,5.0,3.0,5.0,7.0,7.0,2.0,1.0,45.0,1.0
-ES,1517.0,6,2.0,8.0,8.0,6.0,8.0,6.0,2.0,1.0,28.0,2.0
-ES,1518.0,6,2.0,5.0,5.0,1.0,2.0,5.0,1.0,2.0,28.0,2.0
-ES,1528.0,6,2.0,4.0,7.0,6.0,7.0,5.0,2.0,2.0,62.0,1.0
-ES,1529.0,6,3.0,5.0,6.0,4.0,9.0,6.0,3.0,1.0,21.0,2.0
-ES,1530.0,6,2.0,7.0,7.0,6.0,8.0,3.0,2.0,2.0,83.0,2.0
-ES,1533.0,6,4.0,6.0,5.0,4.0,7.0,4.0,3.0,1.0,49.0,1.0
-ES,1534.0,6,7.0,5.0,7.0,7.0,8.0,7.0,3.0,1.0,,1.0
-ES,1535.0,6,7.0,3.0,3.0,3.0,6.0,4.0,1.0,1.0,70.0,1.0
-ES,1536.0,6,3.0,5.0,5.0,4.0,5.0,2.0,1.0,2.0,87.0,2.0
-ES,1538.0,6,2.0,2.0,2.0,4.0,6.0,4.0,2.0,2.0,30.0,1.0
-ES,1539.0,6,2.0,5.0,5.0,1.0,10.0,7.0,1.0,2.0,67.0,1.0
-ES,1542.0,6,1.0,6.0,4.0,2.0,9.0,6.0,4.0,1.0,36.0,2.0
-ES,1546.0,6,2.0,6.0,5.0,4.0,6.0,6.0,1.0,2.0,73.0,1.0
-ES,1548.0,6,4.0,5.0,6.0,6.0,8.0,5.0,4.0,1.0,52.0,1.0
-ES,1551.0,6,4.0,6.0,3.0,7.0,8.0,3.0,4.0,1.0,57.0,1.0
-ES,1552.0,6,5.0,4.0,7.0,3.0,9.0,6.0,3.0,2.0,56.0,1.0
-ES,1553.0,6,7.0,8.0,7.0,8.0,7.0,7.0,3.0,2.0,51.0,2.0
-ES,1557.0,6,4.0,7.0,7.0,4.0,9.0,6.0,4.0,1.0,44.0,1.0
-ES,1566.0,6,6.0,4.0,4.0,4.0,2.0,2.0,2.0,2.0,83.0,2.0
-ES,1570.0,6,1.0,3.0,5.0,5.0,8.0,6.0,4.0,1.0,41.0,1.0
-ES,1571.0,6,4.0,6.0,0.0,8.0,7.0,4.0,,1.0,63.0,1.0
-ES,1574.0,6,7.0,6.0,6.0,4.0,7.0,7.0,3.0,2.0,71.0,2.0
-ES,1576.0,6,2.0,4.0,5.0,6.0,9.0,6.0,3.0,2.0,20.0,2.0
-ES,1577.0,6,5.0,8.0,5.0,3.0,8.0,3.0,2.0,1.0,46.0,1.0
-ES,1578.0,6,4.0,8.0,8.0,6.0,7.0,5.0,4.0,1.0,35.0,1.0
-ES,1579.0,6,5.0,4.0,7.0,6.0,8.0,4.0,2.0,2.0,47.0,2.0
-ES,1581.0,6,2.0,5.0,5.0,4.0,7.0,6.0,2.0,1.0,23.0,2.0
-ES,1585.0,6,4.0,3.0,4.0,4.0,3.0,4.0,2.0,1.0,47.0,1.0
-ES,1591.0,6,7.0,5.0,5.0,2.0,10.0,7.0,4.0,1.0,62.0,1.0
-ES,1595.0,6,5.0,5.0,1.0,1.0,5.0,7.0,1.0,1.0,28.0,2.0
-ES,1598.0,6,2.0,4.0,3.0,3.0,6.0,5.0,3.0,2.0,49.0,1.0
-ES,1604.0,6,7.0,5.0,6.0,3.0,8.0,4.0,3.0,2.0,68.0,1.0
-ES,1608.0,6,5.0,6.0,2.0,3.0,5.0,7.0,2.0,1.0,65.0,2.0
-ES,1609.0,6,5.0,7.0,4.0,7.0,5.0,3.0,2.0,1.0,53.0,2.0
-ES,1610.0,6,3.0,6.0,7.0,6.0,6.0,6.0,3.0,1.0,63.0,2.0
-ES,1612.0,6,1.0,7.0,7.0,2.0,6.0,5.0,3.0,1.0,39.0,1.0
-ES,1621.0,6,4.0,2.0,3.0,4.0,7.0,6.0,3.0,2.0,87.0,2.0
-ES,1622.0,6,1.0,4.0,4.0,3.0,10.0,6.0,2.0,2.0,37.0,1.0
-ES,1623.0,6,2.0,4.0,5.0,7.0,8.0,2.0,1.0,2.0,35.0,1.0
-ES,1628.0,6,1.0,8.0,5.0,7.0,10.0,6.0,3.0,1.0,44.0,1.0
-ES,1629.0,6,3.0,7.0,8.0,6.0,9.0,2.0,5.0,2.0,58.0,1.0
-ES,1631.0,6,3.0,4.0,6.0,2.0,6.0,6.0,3.0,2.0,37.0,1.0
-ES,1635.0,6,3.0,6.0,7.0,8.0,8.0,6.0,2.0,2.0,39.0,1.0
-ES,1638.0,6,2.0,1.0,5.0,3.0,9.0,7.0,1.0,2.0,,2.0
-ES,1640.0,6,5.0,6.0,6.0,6.0,8.0,6.0,1.0,2.0,23.0,2.0
-ES,1641.0,6,7.0,5.0,5.0,5.0,5.0,4.0,2.0,2.0,76.0,2.0
-ES,1642.0,6,6.0,6.0,5.0,5.0,8.0,7.0,3.0,1.0,26.0,2.0
-ES,1645.0,6,5.0,6.0,3.0,5.0,5.0,6.0,3.0,1.0,29.0,2.0
-ES,1647.0,6,2.0,7.0,5.0,4.0,7.0,4.0,3.0,2.0,54.0,1.0
-ES,1648.0,6,2.0,3.0,3.0,4.0,7.0,7.0,3.0,1.0,16.0,2.0
-ES,1653.0,6,7.0,5.0,5.0,4.0,9.0,4.0,1.0,2.0,56.0,1.0
-ES,1654.0,6,2.0,6.0,5.0,9.0,8.0,5.0,1.0,2.0,40.0,1.0
-ES,1656.0,6,1.0,3.0,6.0,4.0,7.0,7.0,1.0,2.0,28.0,2.0
-ES,1657.0,6,7.0,6.0,5.0,4.0,4.0,5.0,1.0,2.0,31.0,1.0
-ES,1658.0,6,0.0,8.0,5.0,5.0,8.0,6.0,1.0,2.0,36.0,1.0
-ES,1659.0,6,2.0,5.0,5.0,4.0,9.0,2.0,2.0,1.0,76.0,1.0
-ES,1660.0,6,5.0,6.0,8.0,5.0,8.0,3.0,2.0,2.0,,1.0
-ES,1663.0,6,5.0,6.0,3.0,2.0,1.0,2.0,3.0,2.0,83.0,2.0
-ES,1666.0,6,4.0,7.0,7.0,5.0,6.0,6.0,3.0,1.0,61.0,1.0
-ES,1667.0,6,5.0,3.0,3.0,3.0,6.0,7.0,3.0,2.0,40.0,1.0
-ES,1669.0,6,0.0,7.0,7.0,5.0,9.0,7.0,3.0,1.0,74.0,2.0
-ES,1671.0,6,4.0,2.0,5.0,4.0,8.0,6.0,4.0,1.0,36.0,1.0
-ES,1672.0,6,1.0,9.0,5.0,2.0,5.0,4.0,2.0,2.0,28.0,2.0
-ES,1673.0,6,3.0,6.0,6.0,6.0,9.0,4.0,3.0,1.0,47.0,1.0
-ES,1678.0,6,7.0,4.0,4.0,5.0,9.0,5.0,3.0,2.0,,1.0
-ES,1680.0,6,4.0,5.0,7.0,8.0,5.0,5.0,3.0,2.0,46.0,1.0
-ES,1683.0,6,5.0,5.0,8.0,7.0,10.0,4.0,2.0,1.0,62.0,1.0
-ES,1685.0,6,4.0,7.0,10.0,0.0,7.0,4.0,2.0,2.0,57.0,1.0
-ES,1686.0,6,4.0,4.0,5.0,5.0,9.0,6.0,2.0,1.0,22.0,2.0
-ES,1688.0,6,3.0,5.0,7.0,7.0,5.0,5.0,3.0,2.0,52.0,1.0
-ES,1689.0,6,4.0,6.0,6.0,6.0,8.0,4.0,2.0,2.0,42.0,1.0
-ES,1693.0,6,5.0,3.0,4.0,2.0,7.0,6.0,2.0,1.0,38.0,2.0
-ES,1694.0,6,6.0,5.0,5.0,5.0,7.0,4.0,1.0,1.0,,2.0
-ES,1701.0,6,5.0,6.0,7.0,4.0,6.0,4.0,3.0,2.0,44.0,1.0
-ES,1706.0,6,2.0,1.0,2.0,1.0,0.0,5.0,,1.0,58.0,2.0
-ES,1713.0,6,2.0,7.0,8.0,8.0,9.0,3.0,3.0,2.0,,1.0
-ES,1715.0,6,2.0,6.0,7.0,4.0,6.0,4.0,2.0,2.0,54.0,1.0
-ES,1719.0,6,2.0,10.0,9.0,10.0,8.0,5.0,3.0,2.0,53.0,1.0
-ES,1722.0,6,7.0,5.0,5.0,5.0,8.0,4.0,2.0,2.0,65.0,1.0
-ES,1726.0,6,3.0,7.0,7.0,3.0,9.0,7.0,3.0,1.0,32.0,1.0
-ES,1727.0,6,4.0,0.0,0.0,4.0,5.0,2.0,1.0,1.0,48.0,2.0
-ES,1729.0,6,2.0,7.0,7.0,5.0,8.0,5.0,3.0,2.0,59.0,1.0
-ES,1730.0,6,4.0,6.0,6.0,4.0,10.0,5.0,4.0,2.0,37.0,1.0
-ES,1732.0,6,3.0,3.0,5.0,1.0,9.0,6.0,3.0,1.0,26.0,2.0
-ES,1735.0,6,4.0,7.0,7.0,6.0,8.0,7.0,3.0,1.0,21.0,2.0
-ES,1737.0,6,3.0,4.0,4.0,2.0,5.0,3.0,2.0,1.0,40.0,1.0
-ES,1738.0,6,4.0,5.0,7.0,5.0,7.0,4.0,3.0,2.0,53.0,1.0
-ES,1740.0,6,2.0,6.0,5.0,5.0,8.0,6.0,3.0,2.0,44.0,1.0
-ES,1742.0,6,1.0,8.0,8.0,7.0,9.0,4.0,3.0,2.0,42.0,1.0
-ES,1744.0,6,7.0,4.0,3.0,5.0,8.0,5.0,4.0,1.0,71.0,1.0
-ES,1746.0,6,5.0,3.0,5.0,0.0,8.0,7.0,3.0,1.0,27.0,2.0
-ES,1747.0,6,0.0,8.0,8.0,8.0,8.0,7.0,3.0,1.0,35.0,2.0
-ES,1750.0,6,2.0,4.0,5.0,0.0,8.0,3.0,2.0,1.0,36.0,1.0
-ES,1751.0,6,4.0,2.0,6.0,4.0,7.0,6.0,2.0,2.0,89.0,2.0
-ES,1752.0,6,2.0,5.0,6.0,6.0,6.0,5.0,3.0,1.0,61.0,1.0
-ES,1753.0,6,2.0,1.0,6.0,9.0,10.0,6.0,3.0,2.0,17.0,2.0
-ES,1761.0,6,2.0,5.0,5.0,4.0,5.0,3.0,3.0,2.0,57.0,2.0
-ES,1763.0,6,5.0,9.0,9.0,9.0,10.0,7.0,1.0,2.0,48.0,2.0
-ES,1764.0,6,2.0,7.0,7.0,5.0,8.0,5.0,2.0,2.0,40.0,1.0
-ES,1765.0,6,7.0,5.0,4.0,4.0,10.0,2.0,2.0,1.0,63.0,1.0
-ES,1766.0,6,6.0,6.0,6.0,6.0,7.0,5.0,3.0,1.0,27.0,2.0
-ES,1769.0,6,1.0,6.0,5.0,10.0,10.0,7.0,2.0,2.0,41.0,2.0
-ES,1771.0,6,1.0,6.0,6.0,7.0,8.0,7.0,3.0,1.0,21.0,2.0
-ES,1776.0,6,5.0,6.0,7.0,8.0,7.0,4.0,1.0,1.0,71.0,1.0
-ES,1781.0,6,7.0,0.0,0.0,0.0,6.0,6.0,3.0,2.0,55.0,2.0
-ES,1782.0,6,3.0,3.0,3.0,6.0,6.0,4.0,3.0,2.0,35.0,1.0
-ES,1784.0,6,2.0,2.0,2.0,5.0,8.0,4.0,2.0,1.0,55.0,1.0
-ES,1790.0,6,0.0,5.0,5.0,3.0,8.0,4.0,2.0,2.0,34.0,1.0
-ES,1792.0,6,7.0,0.0,10.0,5.0,7.0,7.0,1.0,2.0,79.0,2.0
-ES,1797.0,6,6.0,8.0,6.0,5.0,5.0,6.0,2.0,1.0,59.0,1.0
-ES,1799.0,6,3.0,6.0,6.0,6.0,8.0,5.0,2.0,2.0,23.0,2.0
-ES,1807.0,6,1.0,7.0,7.0,2.0,8.0,5.0,4.0,1.0,30.0,2.0
-ES,1812.0,6,5.0,2.0,10.0,8.0,10.0,6.0,1.0,2.0,45.0,2.0
-ES,1813.0,6,3.0,9.0,4.0,4.0,9.0,4.0,1.0,2.0,30.0,2.0
-ES,1814.0,6,7.0,3.0,4.0,5.0,7.0,4.0,2.0,2.0,80.0,1.0
-ES,1817.0,6,6.0,4.0,6.0,6.0,7.0,7.0,1.0,2.0,79.0,1.0
-ES,1820.0,6,2.0,5.0,3.0,4.0,6.0,7.0,4.0,2.0,17.0,2.0
-ES,1821.0,6,2.0,4.0,3.0,4.0,8.0,7.0,3.0,2.0,20.0,2.0
-ES,1829.0,6,5.0,7.0,6.0,3.0,9.0,6.0,3.0,1.0,36.0,1.0
-ES,1832.0,6,2.0,7.0,6.0,7.0,7.0,7.0,4.0,1.0,53.0,2.0
-ES,1835.0,6,7.0,10.0,8.0,9.0,5.0,6.0,1.0,1.0,87.0,2.0
-ES,1837.0,6,4.0,6.0,7.0,6.0,7.0,5.0,3.0,2.0,44.0,1.0
-ES,1838.0,6,5.0,2.0,5.0,3.0,5.0,5.0,3.0,2.0,56.0,1.0
-ES,1839.0,6,7.0,2.0,7.0,3.0,7.0,6.0,3.0,2.0,78.0,1.0
-ES,1840.0,6,0.0,2.0,2.0,2.0,7.0,3.0,2.0,1.0,48.0,1.0
-ES,1849.0,6,7.0,4.0,3.0,0.0,10.0,1.0,3.0,2.0,74.0,1.0
-ES,1853.0,6,7.0,8.0,8.0,7.0,8.0,6.0,2.0,1.0,72.0,1.0
-ES,1856.0,6,6.0,5.0,7.0,7.0,8.0,4.0,3.0,2.0,70.0,1.0
-ES,1861.0,6,2.0,5.0,5.0,5.0,10.0,6.0,5.0,1.0,40.0,1.0
-ES,1862.0,6,5.0,2.0,2.0,2.0,5.0,5.0,4.0,2.0,53.0,1.0
-ES,1863.0,6,6.0,6.0,5.0,3.0,7.0,4.0,3.0,1.0,51.0,1.0
-ES,1866.0,6,7.0,7.0,7.0,4.0,8.0,6.0,3.0,1.0,17.0,2.0
-ES,1867.0,6,1.0,2.0,1.0,5.0,2.0,2.0,1.0,2.0,44.0,1.0
-ES,1868.0,6,4.0,7.0,7.0,8.0,7.0,6.0,3.0,1.0,35.0,2.0
-ES,1869.0,6,3.0,7.0,3.0,5.0,6.0,3.0,4.0,1.0,69.0,2.0
-ES,1870.0,6,4.0,4.0,3.0,3.0,8.0,5.0,2.0,2.0,62.0,1.0
-ES,1875.0,6,6.0,9.0,1.0,5.0,10.0,7.0,3.0,1.0,64.0,1.0
-ES,1877.0,6,1.0,7.0,5.0,4.0,8.0,6.0,3.0,2.0,39.0,1.0
-ES,1878.0,6,3.0,5.0,4.0,2.0,9.0,7.0,4.0,1.0,56.0,2.0
-ES,1879.0,6,1.0,6.0,5.0,5.0,8.0,7.0,3.0,1.0,17.0,2.0
-ES,1881.0,6,7.0,6.0,7.0,5.0,8.0,7.0,3.0,2.0,56.0,1.0
-ES,1887.0,6,3.0,6.0,6.0,6.0,8.0,5.0,4.0,1.0,67.0,2.0
-ES,1888.0,6,4.0,6.0,6.0,6.0,8.0,3.0,1.0,2.0,54.0,1.0
-ES,1889.0,6,3.0,8.0,8.0,8.0,8.0,5.0,3.0,2.0,51.0,2.0
-ES,1891.0,6,3.0,3.0,3.0,5.0,5.0,7.0,1.0,2.0,65.0,2.0
-ES,1892.0,6,2.0,6.0,6.0,7.0,8.0,6.0,4.0,1.0,32.0,1.0
-ES,1893.0,6,4.0,5.0,5.0,5.0,10.0,6.0,2.0,1.0,27.0,2.0
-ES,1894.0,6,4.0,7.0,6.0,3.0,9.0,4.0,4.0,2.0,60.0,1.0
-ES,1898.0,6,2.0,6.0,6.0,4.0,7.0,5.0,3.0,2.0,39.0,1.0
-ES,1899.0,6,5.0,8.0,8.0,8.0,9.0,6.0,1.0,2.0,38.0,1.0
-ES,1901.0,6,2.0,5.0,3.0,3.0,8.0,6.0,3.0,1.0,31.0,1.0
-ES,1903.0,6,6.0,7.0,5.0,7.0,8.0,6.0,3.0,2.0,46.0,1.0
-ES,1904.0,6,3.0,4.0,4.0,4.0,4.0,4.0,2.0,2.0,42.0,1.0
-ES,1905.0,6,2.0,7.0,6.0,2.0,7.0,5.0,4.0,1.0,46.0,1.0
-ES,1906.0,6,0.0,6.0,6.0,2.0,4.0,6.0,2.0,1.0,43.0,1.0
-ES,1908.0,6,5.0,7.0,3.0,3.0,8.0,5.0,1.0,2.0,45.0,1.0
-ES,1921.0,6,3.0,7.0,8.0,4.0,8.0,6.0,4.0,1.0,17.0,2.0
-ES,1922.0,6,4.0,5.0,7.0,3.0,6.0,6.0,5.0,2.0,31.0,1.0
-ES,1928.0,6,2.0,7.0,7.0,6.0,10.0,6.0,4.0,2.0,37.0,2.0
-ES,1929.0,6,7.0,0.0,0.0,0.0,10.0,3.0,1.0,2.0,68.0,1.0
-ES,1930.0,6,3.0,3.0,4.0,4.0,8.0,7.0,3.0,1.0,18.0,2.0
-ES,1931.0,6,2.0,8.0,7.0,7.0,10.0,7.0,3.0,1.0,80.0,1.0
-ES,1932.0,6,3.0,6.0,7.0,3.0,8.0,6.0,3.0,1.0,20.0,2.0
-ES,1933.0,6,0.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,26.0,2.0
-ES,1934.0,6,4.0,3.0,3.0,4.0,5.0,6.0,3.0,1.0,50.0,1.0
-ES,1935.0,6,2.0,7.0,7.0,7.0,9.0,5.0,2.0,1.0,40.0,1.0
-ES,1936.0,6,4.0,6.0,7.0,6.0,7.0,6.0,3.0,1.0,26.0,2.0
-ES,1940.0,6,2.0,8.0,8.0,5.0,10.0,6.0,2.0,2.0,68.0,1.0
-ES,1944.0,6,1.0,5.0,7.0,7.0,8.0,7.0,3.0,1.0,18.0,2.0
-ES,1946.0,6,6.0,5.0,7.0,4.0,4.0,5.0,2.0,2.0,34.0,2.0
-ES,1949.0,6,7.0,6.0,5.0,7.0,7.0,5.0,3.0,1.0,53.0,2.0
-ES,1954.0,6,3.0,5.0,8.0,7.0,9.0,3.0,3.0,2.0,57.0,1.0
-ES,1955.0,6,1.0,3.0,2.0,4.0,6.0,7.0,4.0,2.0,52.0,1.0
-ES,1957.0,6,7.0,3.0,4.0,5.0,9.0,7.0,1.0,2.0,85.0,2.0
-ES,1961.0,6,5.0,5.0,3.0,3.0,7.0,4.0,3.0,2.0,54.0,1.0
-ES,1962.0,6,5.0,5.0,5.0,5.0,8.0,7.0,3.0,1.0,71.0,1.0
-ES,1968.0,6,6.0,8.0,6.0,9.0,8.0,7.0,1.0,1.0,64.0,1.0
-ES,1969.0,6,2.0,4.0,5.0,1.0,6.0,5.0,3.0,1.0,51.0,1.0
-ES,1971.0,6,4.0,5.0,5.0,5.0,10.0,7.0,2.0,1.0,54.0,1.0
-ES,1972.0,6,3.0,3.0,5.0,5.0,9.0,6.0,3.0,2.0,21.0,2.0
-ES,1973.0,6,7.0,3.0,3.0,4.0,7.0,7.0,1.0,1.0,56.0,1.0
-ES,1979.0,6,5.0,5.0,5.0,5.0,8.0,4.0,2.0,1.0,43.0,1.0
-ES,1981.0,6,6.0,6.0,6.0,6.0,8.0,6.0,2.0,1.0,23.0,2.0
-ES,1982.0,6,6.0,5.0,6.0,8.0,4.0,2.0,2.0,2.0,42.0,2.0
-ES,1983.0,6,2.0,6.0,7.0,7.0,7.0,6.0,2.0,1.0,23.0,2.0
-ES,1985.0,6,3.0,7.0,7.0,7.0,9.0,4.0,3.0,1.0,16.0,2.0
-ES,1986.0,6,3.0,3.0,2.0,3.0,9.0,7.0,1.0,2.0,60.0,1.0
-ES,1987.0,6,6.0,7.0,7.0,5.0,7.0,6.0,3.0,1.0,27.0,2.0
-ES,1988.0,6,5.0,0.0,5.0,7.0,7.0,7.0,1.0,2.0,23.0,1.0
-ES,1992.0,6,0.0,0.0,4.0,10.0,10.0,6.0,2.0,2.0,56.0,2.0
-ES,1993.0,6,7.0,7.0,8.0,7.0,10.0,5.0,2.0,1.0,40.0,1.0
-ES,1994.0,6,4.0,6.0,7.0,5.0,8.0,7.0,3.0,2.0,53.0,1.0
-ES,1997.0,6,2.0,1.0,2.0,4.0,10.0,6.0,3.0,1.0,,1.0
-ES,1998.0,6,5.0,0.0,2.0,5.0,7.0,3.0,3.0,2.0,53.0,2.0
-ES,2006.0,6,3.0,4.0,7.0,5.0,8.0,4.0,3.0,1.0,75.0,1.0
-ES,2011.0,6,5.0,2.0,6.0,0.0,2.0,6.0,3.0,1.0,39.0,1.0
-ES,2012.0,6,4.0,3.0,7.0,5.0,3.0,3.0,1.0,2.0,44.0,1.0
-ES,2013.0,6,2.0,6.0,5.0,6.0,8.0,6.0,3.0,2.0,25.0,2.0
-ES,2014.0,6,2.0,7.0,6.0,2.0,7.0,6.0,3.0,2.0,33.0,2.0
-ES,2015.0,6,3.0,5.0,4.0,6.0,4.0,6.0,4.0,1.0,51.0,2.0
-ES,2021.0,6,2.0,8.0,8.0,5.0,8.0,5.0,1.0,1.0,33.0,1.0
-ES,2022.0,6,0.0,3.0,6.0,10.0,9.0,6.0,3.0,1.0,21.0,2.0
-ES,2024.0,6,7.0,7.0,6.0,7.0,7.0,5.0,3.0,2.0,17.0,2.0
-ES,2025.0,6,6.0,10.0,8.0,5.0,10.0,4.0,2.0,1.0,68.0,1.0
-ES,2026.0,6,0.0,10.0,10.0,10.0,8.0,6.0,3.0,1.0,54.0,1.0
-ES,2028.0,6,5.0,7.0,7.0,6.0,7.0,4.0,4.0,1.0,73.0,1.0
-ES,2029.0,6,5.0,0.0,5.0,5.0,5.0,1.0,2.0,2.0,39.0,1.0
-ES,2032.0,6,1.0,6.0,7.0,7.0,9.0,3.0,2.0,2.0,32.0,1.0
-ES,2035.0,6,3.0,0.0,0.0,9.0,10.0,5.0,3.0,2.0,49.0,1.0
-ES,2036.0,6,2.0,4.0,7.0,3.0,7.0,7.0,3.0,1.0,20.0,2.0
-ES,2037.0,6,3.0,6.0,7.0,7.0,8.0,7.0,3.0,2.0,39.0,2.0
-ES,2040.0,6,3.0,5.0,1.0,4.0,8.0,5.0,2.0,1.0,45.0,1.0
-ES,2041.0,6,0.0,5.0,3.0,5.0,7.0,7.0,2.0,1.0,19.0,2.0
-ES,2047.0,6,0.0,1.0,6.0,4.0,9.0,5.0,3.0,2.0,34.0,1.0
-ES,2048.0,6,6.0,6.0,6.0,7.0,9.0,4.0,2.0,1.0,81.0,1.0
-ES,2049.0,6,5.0,3.0,5.0,2.0,3.0,3.0,2.0,1.0,35.0,1.0
-ES,2052.0,6,2.0,6.0,7.0,5.0,7.0,4.0,3.0,2.0,54.0,1.0
-ES,2055.0,6,7.0,3.0,7.0,5.0,9.0,7.0,1.0,2.0,78.0,2.0
-ES,2058.0,6,3.0,5.0,3.0,2.0,7.0,5.0,4.0,1.0,40.0,2.0
-ES,2059.0,6,2.0,4.0,4.0,5.0,9.0,5.0,2.0,2.0,54.0,2.0
-ES,2060.0,6,7.0,7.0,1.0,3.0,7.0,7.0,2.0,1.0,41.0,2.0
-ES,2063.0,6,5.0,5.0,6.0,6.0,8.0,7.0,3.0,1.0,63.0,1.0
-ES,2064.0,6,4.0,7.0,5.0,7.0,7.0,4.0,3.0,1.0,32.0,2.0
-ES,2070.0,6,3.0,6.0,7.0,7.0,8.0,3.0,4.0,1.0,36.0,1.0
-ES,2071.0,6,4.0,5.0,5.0,5.0,8.0,6.0,3.0,2.0,31.0,1.0
-ES,2072.0,6,3.0,9.0,7.0,6.0,7.0,4.0,5.0,2.0,63.0,1.0
-ES,2073.0,6,6.0,4.0,4.0,4.0,7.0,6.0,3.0,1.0,37.0,1.0
-ES,2074.0,6,3.0,7.0,7.0,6.0,8.0,2.0,2.0,1.0,65.0,1.0
-ES,2075.0,6,2.0,6.0,6.0,3.0,10.0,6.0,2.0,1.0,82.0,1.0
-ES,2076.0,6,2.0,7.0,7.0,7.0,9.0,5.0,3.0,1.0,30.0,2.0
-ES,2077.0,6,4.0,4.0,4.0,4.0,7.0,7.0,1.0,1.0,76.0,1.0
-ES,2078.0,6,2.0,2.0,3.0,1.0,3.0,6.0,5.0,1.0,27.0,2.0
-ES,2079.0,6,7.0,8.0,8.0,3.0,8.0,4.0,3.0,2.0,73.0,1.0
-ES,2080.0,6,4.0,0.0,0.0,2.0,10.0,7.0,1.0,2.0,56.0,1.0
-ES,2086.0,6,3.0,4.0,5.0,5.0,6.0,6.0,3.0,1.0,52.0,1.0
-ES,2087.0,6,5.0,6.0,10.0,5.0,10.0,7.0,2.0,1.0,69.0,2.0
-ES,2088.0,6,2.0,5.0,2.0,3.0,8.0,4.0,4.0,2.0,64.0,2.0
-ES,2092.0,6,2.0,2.0,2.0,3.0,8.0,4.0,3.0,1.0,44.0,1.0
-ES,2093.0,6,5.0,3.0,5.0,5.0,9.0,5.0,3.0,1.0,72.0,1.0
-ES,2097.0,6,7.0,5.0,4.0,5.0,8.0,7.0,2.0,1.0,21.0,2.0
-ES,2099.0,6,5.0,5.0,5.0,5.0,8.0,4.0,2.0,2.0,34.0,1.0
-ES,2102.0,6,5.0,6.0,7.0,7.0,8.0,7.0,2.0,2.0,36.0,1.0
-ES,2104.0,6,7.0,1.0,9.0,0.0,3.0,4.0,5.0,1.0,61.0,2.0
-ES,2105.0,6,5.0,5.0,5.0,3.0,10.0,5.0,3.0,2.0,61.0,1.0
-ES,2106.0,6,4.0,7.0,8.0,5.0,8.0,6.0,4.0,2.0,47.0,1.0
-ES,2107.0,6,5.0,4.0,3.0,3.0,9.0,6.0,3.0,1.0,72.0,2.0
-ES,2110.0,6,4.0,7.0,7.0,7.0,10.0,7.0,3.0,1.0,55.0,1.0
-ES,2112.0,6,4.0,2.0,7.0,8.0,3.0,3.0,1.0,2.0,44.0,2.0
-ES,2115.0,6,1.0,3.0,4.0,5.0,7.0,5.0,4.0,1.0,59.0,1.0
-ES,2116.0,6,4.0,6.0,5.0,4.0,7.0,5.0,2.0,2.0,22.0,2.0
-ES,2119.0,6,2.0,5.0,5.0,3.0,8.0,5.0,3.0,2.0,51.0,1.0
-ES,2121.0,6,3.0,0.0,4.0,5.0,6.0,4.0,3.0,2.0,52.0,1.0
-ES,2122.0,6,6.0,7.0,2.0,9.0,2.0,6.0,1.0,1.0,,1.0
-ES,2124.0,6,7.0,0.0,0.0,0.0,10.0,1.0,1.0,1.0,90.0,1.0
-ES,2125.0,6,7.0,4.0,2.0,4.0,5.0,6.0,3.0,1.0,31.0,1.0
-ES,2127.0,6,3.0,6.0,7.0,7.0,8.0,7.0,3.0,1.0,57.0,1.0
-ES,2129.0,6,6.0,2.0,3.0,4.0,9.0,3.0,2.0,1.0,52.0,1.0
-ES,2134.0,6,3.0,7.0,7.0,5.0,5.0,4.0,1.0,2.0,73.0,1.0
-ES,2135.0,6,7.0,0.0,4.0,5.0,9.0,7.0,3.0,1.0,,2.0
-ES,2139.0,6,3.0,7.0,9.0,7.0,7.0,5.0,2.0,2.0,32.0,1.0
-ES,2143.0,6,2.0,8.0,8.0,5.0,10.0,6.0,3.0,1.0,43.0,1.0
-ES,2144.0,6,1.0,1.0,2.0,1.0,9.0,5.0,4.0,2.0,33.0,1.0
-ES,2145.0,6,7.0,4.0,1.0,3.0,10.0,4.0,3.0,1.0,69.0,1.0
-ES,2148.0,6,7.0,4.0,4.0,4.0,3.0,6.0,2.0,2.0,24.0,2.0
-ES,2152.0,6,2.0,10.0,10.0,10.0,10.0,7.0,2.0,1.0,63.0,2.0
-ES,2154.0,6,2.0,4.0,4.0,3.0,10.0,6.0,3.0,1.0,50.0,1.0
-ES,2155.0,6,7.0,8.0,8.0,9.0,10.0,7.0,3.0,2.0,17.0,2.0
-ES,2159.0,6,4.0,5.0,6.0,6.0,10.0,7.0,3.0,2.0,53.0,1.0
-ES,2160.0,6,4.0,2.0,2.0,2.0,7.0,7.0,4.0,1.0,37.0,1.0
-ES,2162.0,6,4.0,7.0,5.0,6.0,7.0,4.0,2.0,2.0,51.0,1.0
-ES,2163.0,6,4.0,5.0,6.0,10.0,10.0,6.0,1.0,2.0,73.0,1.0
-ES,2164.0,6,5.0,7.0,7.0,6.0,9.0,6.0,1.0,1.0,35.0,1.0
-ES,2165.0,6,5.0,7.0,7.0,5.0,7.0,5.0,3.0,2.0,53.0,1.0
-ES,2166.0,6,5.0,4.0,4.0,4.0,6.0,6.0,3.0,1.0,52.0,1.0
-ES,2167.0,6,3.0,6.0,6.0,6.0,7.0,6.0,3.0,2.0,41.0,1.0
-ES,2170.0,6,0.0,0.0,0.0,0.0,8.0,7.0,1.0,1.0,69.0,1.0
-ES,2171.0,6,7.0,5.0,5.0,8.0,0.0,2.0,1.0,2.0,67.0,1.0
-ES,2175.0,6,3.0,7.0,7.0,3.0,7.0,5.0,2.0,1.0,60.0,1.0
-ES,2179.0,6,6.0,5.0,4.0,2.0,8.0,5.0,2.0,1.0,70.0,1.0
-ES,2180.0,6,7.0,6.0,7.0,6.0,8.0,5.0,2.0,2.0,37.0,1.0
-ES,2183.0,6,5.0,5.0,6.0,3.0,9.0,6.0,3.0,2.0,20.0,2.0
-ES,2185.0,6,1.0,5.0,4.0,5.0,8.0,5.0,1.0,1.0,83.0,2.0
-ES,2188.0,6,2.0,5.0,5.0,5.0,8.0,5.0,2.0,1.0,38.0,1.0
-ES,2189.0,6,2.0,6.0,7.0,4.0,7.0,4.0,2.0,1.0,40.0,2.0
-ES,2190.0,6,3.0,9.0,7.0,3.0,9.0,4.0,4.0,1.0,49.0,1.0
-ES,2193.0,6,1.0,5.0,2.0,2.0,8.0,2.0,1.0,2.0,54.0,1.0
-ES,2194.0,6,3.0,6.0,7.0,6.0,7.0,5.0,3.0,1.0,40.0,1.0
-ES,2195.0,6,2.0,8.0,7.0,8.0,10.0,7.0,1.0,2.0,39.0,1.0
-ES,2196.0,6,3.0,6.0,7.0,2.0,8.0,5.0,3.0,2.0,65.0,1.0
-ES,2197.0,6,5.0,1.0,2.0,2.0,5.0,4.0,2.0,2.0,74.0,1.0
-ES,2202.0,6,3.0,6.0,5.0,7.0,6.0,3.0,1.0,2.0,68.0,1.0
-ES,2205.0,6,2.0,7.0,5.0,5.0,4.0,7.0,2.0,2.0,54.0,2.0
-ES,2206.0,6,1.0,3.0,0.0,5.0,10.0,4.0,2.0,1.0,25.0,2.0
-ES,2207.0,6,4.0,4.0,6.0,6.0,7.0,6.0,3.0,2.0,31.0,2.0
-ES,2209.0,6,5.0,3.0,3.0,2.0,9.0,4.0,3.0,1.0,30.0,1.0
-ES,2210.0,6,6.0,10.0,5.0,5.0,10.0,5.0,5.0,1.0,33.0,2.0
-ES,2211.0,6,7.0,5.0,,4.0,7.0,5.0,2.0,1.0,41.0,1.0
-ES,2212.0,6,3.0,7.0,6.0,4.0,8.0,6.0,3.0,1.0,22.0,2.0
-ES,2218.0,6,5.0,7.0,5.0,3.0,7.0,3.0,1.0,2.0,65.0,1.0
-ES,2220.0,6,1.0,9.0,3.0,5.0,10.0,4.0,5.0,1.0,53.0,1.0
-ES,2222.0,6,7.0,0.0,0.0,5.0,5.0,7.0,2.0,1.0,54.0,1.0
-ES,2223.0,6,5.0,4.0,4.0,5.0,6.0,5.0,3.0,1.0,55.0,2.0
-ES,2224.0,6,6.0,6.0,5.0,6.0,8.0,6.0,3.0,2.0,41.0,1.0
-ES,2225.0,6,5.0,8.0,7.0,7.0,9.0,2.0,2.0,1.0,,1.0
-ES,2227.0,6,7.0,5.0,8.0,9.0,8.0,5.0,1.0,1.0,69.0,1.0
-ES,2228.0,6,2.0,5.0,8.0,6.0,3.0,7.0,4.0,1.0,46.0,1.0
-ES,2229.0,6,7.0,5.0,6.0,8.0,8.0,6.0,3.0,2.0,32.0,2.0
-ES,2230.0,6,1.0,5.0,7.0,1.0,8.0,7.0,3.0,2.0,20.0,2.0
-ES,2232.0,6,0.0,8.0,8.0,4.0,8.0,5.0,2.0,1.0,54.0,1.0
-ES,2236.0,6,4.0,5.0,5.0,5.0,10.0,6.0,3.0,1.0,63.0,1.0
-ES,2237.0,6,7.0,4.0,3.0,5.0,7.0,7.0,3.0,1.0,,2.0
-ES,2239.0,6,7.0,7.0,8.0,7.0,10.0,7.0,3.0,1.0,69.0,1.0
-ES,2241.0,6,6.0,7.0,10.0,10.0,10.0,7.0,3.0,2.0,93.0,2.0
-ES,2242.0,6,3.0,4.0,7.0,7.0,9.0,5.0,3.0,2.0,41.0,1.0
-ES,2244.0,6,5.0,4.0,7.0,5.0,5.0,4.0,3.0,2.0,53.0,1.0
-ES,2245.0,6,3.0,7.0,5.0,2.0,8.0,5.0,2.0,2.0,62.0,2.0
-ES,2246.0,6,1.0,5.0,5.0,5.0,5.0,6.0,2.0,2.0,34.0,1.0
-ES,2247.0,6,6.0,8.0,7.0,1.0,1.0,2.0,1.0,1.0,39.0,2.0
-ES,2249.0,6,3.0,7.0,3.0,9.0,3.0,3.0,2.0,1.0,31.0,1.0
-ES,2252.0,6,2.0,4.0,4.0,5.0,7.0,6.0,3.0,2.0,48.0,1.0
-ES,2260.0,6,7.0,7.0,7.0,8.0,7.0,6.0,3.0,1.0,34.0,1.0
-ES,2266.0,6,1.0,5.0,6.0,6.0,8.0,5.0,4.0,1.0,54.0,2.0
-ES,2269.0,6,6.0,5.0,5.0,5.0,7.0,4.0,2.0,2.0,63.0,1.0
-ES,2270.0,6,4.0,2.0,5.0,2.0,7.0,7.0,2.0,1.0,33.0,2.0
-ES,2274.0,6,7.0,0.0,0.0,0.0,10.0,6.0,4.0,2.0,73.0,1.0
-ES,2275.0,6,4.0,7.0,8.0,8.0,10.0,6.0,4.0,2.0,53.0,1.0
-ES,2281.0,6,3.0,8.0,8.0,2.0,7.0,4.0,1.0,2.0,48.0,1.0
-ES,2286.0,6,7.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,47.0,1.0
-ES,2288.0,6,7.0,8.0,8.0,10.0,5.0,3.0,3.0,1.0,35.0,2.0
-ES,2289.0,6,5.0,7.0,0.0,4.0,8.0,7.0,3.0,1.0,18.0,2.0
-ES,2291.0,6,2.0,4.0,7.0,3.0,9.0,6.0,2.0,2.0,62.0,1.0
-ES,2295.0,6,2.0,7.0,7.0,5.0,9.0,7.0,3.0,1.0,24.0,2.0
-ES,2298.0,6,4.0,5.0,5.0,2.0,10.0,4.0,3.0,1.0,33.0,1.0
-ES,2299.0,6,3.0,5.0,5.0,8.0,8.0,6.0,3.0,1.0,34.0,1.0
-ES,2300.0,6,7.0,5.0,6.0,3.0,10.0,7.0,3.0,1.0,64.0,2.0
-ES,2303.0,6,7.0,0.0,5.0,3.0,5.0,4.0,1.0,2.0,54.0,1.0
-ES,2304.0,6,7.0,3.0,3.0,5.0,6.0,7.0,3.0,2.0,85.0,2.0
-ES,2306.0,6,0.0,5.0,5.0,1.0,8.0,3.0,1.0,1.0,45.0,1.0
-ES,2309.0,6,3.0,5.0,6.0,2.0,7.0,4.0,2.0,1.0,38.0,1.0
-ES,2310.0,6,1.0,8.0,8.0,8.0,9.0,6.0,3.0,2.0,46.0,1.0
-ES,2316.0,6,7.0,3.0,5.0,3.0,7.0,1.0,1.0,1.0,79.0,1.0
-ES,2323.0,6,4.0,7.0,6.0,8.0,9.0,5.0,3.0,2.0,41.0,1.0
-ES,2325.0,6,5.0,2.0,4.0,2.0,6.0,4.0,2.0,1.0,39.0,2.0
-ES,2328.0,6,5.0,5.0,8.0,8.0,9.0,6.0,2.0,2.0,68.0,1.0
-ES,2329.0,6,2.0,2.0,2.0,2.0,10.0,6.0,3.0,1.0,,2.0
-ES,2334.0,6,3.0,8.0,8.0,7.0,7.0,5.0,3.0,1.0,85.0,1.0
-ES,2339.0,6,3.0,6.0,6.0,5.0,10.0,6.0,4.0,1.0,32.0,1.0
-ES,2341.0,6,3.0,7.0,9.0,7.0,8.0,3.0,2.0,2.0,36.0,1.0
-ES,2344.0,6,3.0,5.0,6.0,7.0,9.0,2.0,2.0,1.0,40.0,1.0
-ES,2348.0,6,3.0,5.0,5.0,3.0,7.0,4.0,3.0,1.0,75.0,2.0
-ES,2352.0,6,4.0,8.0,7.0,7.0,9.0,7.0,4.0,1.0,65.0,1.0
-ES,2354.0,6,4.0,6.0,4.0,1.0,10.0,1.0,3.0,1.0,54.0,1.0
-ES,2355.0,6,3.0,5.0,5.0,5.0,8.0,6.0,3.0,2.0,52.0,1.0
-ES,2357.0,6,2.0,5.0,2.0,2.0,3.0,5.0,2.0,2.0,19.0,2.0
-ES,2358.0,6,2.0,7.0,7.0,0.0,10.0,7.0,3.0,1.0,40.0,1.0
-ES,2359.0,6,4.0,7.0,6.0,2.0,10.0,7.0,3.0,2.0,21.0,2.0
-ES,2360.0,6,1.0,7.0,4.0,7.0,8.0,6.0,3.0,2.0,50.0,1.0
-ES,2361.0,6,5.0,5.0,6.0,4.0,5.0,6.0,4.0,2.0,70.0,1.0
-ES,2362.0,6,4.0,4.0,6.0,3.0,8.0,6.0,2.0,2.0,23.0,2.0
-ES,2366.0,6,3.0,5.0,8.0,9.0,10.0,3.0,3.0,2.0,44.0,1.0
-ES,2368.0,6,4.0,3.0,3.0,5.0,9.0,7.0,1.0,1.0,21.0,2.0
-ES,2370.0,6,7.0,5.0,5.0,5.0,7.0,5.0,3.0,1.0,46.0,1.0
-ES,2371.0,6,7.0,6.0,5.0,5.0,10.0,6.0,3.0,1.0,65.0,1.0
-ES,2373.0,6,3.0,6.0,5.0,5.0,8.0,4.0,4.0,1.0,,1.0
-ES,2374.0,6,4.0,8.0,6.0,6.0,7.0,4.0,3.0,1.0,70.0,1.0
-ES,2375.0,6,7.0,6.0,7.0,6.0,9.0,5.0,3.0,2.0,73.0,1.0
-ES,2378.0,6,4.0,5.0,5.0,7.0,10.0,6.0,2.0,2.0,32.0,1.0
-ES,2380.0,6,6.0,7.0,8.0,6.0,10.0,6.0,2.0,2.0,45.0,1.0
-ES,2383.0,6,1.0,1.0,0.0,1.0,7.0,5.0,3.0,1.0,50.0,1.0
-ES,2384.0,6,2.0,7.0,7.0,5.0,7.0,4.0,3.0,1.0,46.0,1.0
-ES,2385.0,6,2.0,5.0,4.0,3.0,5.0,2.0,2.0,2.0,46.0,1.0
-ES,2386.0,6,3.0,5.0,5.0,5.0,9.0,4.0,3.0,1.0,39.0,1.0
-ES,2387.0,6,3.0,6.0,5.0,5.0,7.0,5.0,2.0,1.0,34.0,1.0
-ES,2389.0,6,3.0,3.0,6.0,3.0,7.0,5.0,4.0,1.0,36.0,1.0
-ES,2393.0,6,4.0,4.0,6.0,8.0,10.0,1.0,1.0,2.0,64.0,1.0
-ES,2394.0,6,4.0,4.0,4.0,5.0,5.0,6.0,3.0,2.0,70.0,2.0
-ES,2396.0,6,7.0,5.0,5.0,5.0,0.0,7.0,3.0,1.0,45.0,2.0
-ES,2399.0,6,4.0,3.0,5.0,3.0,7.0,7.0,3.0,2.0,39.0,2.0
-ES,2400.0,6,7.0,5.0,6.0,1.0,10.0,3.0,1.0,2.0,23.0,1.0
-ES,2401.0,6,4.0,8.0,7.0,5.0,7.0,6.0,2.0,2.0,29.0,1.0
-ES,2403.0,6,4.0,5.0,7.0,2.0,8.0,6.0,4.0,1.0,37.0,2.0
-ES,2404.0,6,3.0,5.0,4.0,5.0,10.0,6.0,2.0,1.0,29.0,2.0
-ES,2405.0,6,5.0,8.0,8.0,2.0,9.0,6.0,1.0,1.0,39.0,1.0
-ES,2406.0,6,3.0,7.0,5.0,8.0,8.0,7.0,1.0,2.0,18.0,2.0
-ES,2408.0,6,2.0,3.0,5.0,0.0,10.0,6.0,4.0,2.0,17.0,2.0
-ES,2409.0,6,5.0,5.0,5.0,5.0,8.0,2.0,2.0,1.0,34.0,2.0
-ES,2412.0,6,1.0,8.0,8.0,8.0,5.0,2.0,2.0,2.0,30.0,1.0
-ES,2414.0,6,3.0,0.0,0.0,2.0,9.0,7.0,4.0,2.0,21.0,2.0
-ES,2420.0,6,5.0,4.0,3.0,5.0,9.0,7.0,3.0,2.0,41.0,1.0
-ES,2422.0,6,3.0,5.0,5.0,2.0,7.0,6.0,3.0,1.0,36.0,2.0
-ES,2426.0,6,0.0,5.0,7.0,4.0,10.0,4.0,1.0,2.0,35.0,2.0
-ES,2429.0,6,2.0,7.0,5.0,5.0,8.0,2.0,2.0,1.0,40.0,1.0
-ES,2430.0,6,7.0,0.0,10.0,0.0,10.0,6.0,3.0,2.0,81.0,2.0
-ES,2433.0,6,3.0,0.0,0.0,0.0,8.0,6.0,2.0,2.0,42.0,2.0
-ES,2434.0,6,4.0,8.0,8.0,8.0,8.0,6.0,4.0,2.0,76.0,1.0
-ES,2436.0,6,4.0,7.0,5.0,2.0,9.0,3.0,3.0,1.0,78.0,1.0
-ES,2439.0,6,6.0,8.0,6.0,5.0,9.0,6.0,3.0,1.0,32.0,2.0
-ES,2440.0,6,7.0,8.0,8.0,4.0,10.0,6.0,3.0,1.0,73.0,1.0
-ES,2443.0,6,5.0,5.0,5.0,1.0,6.0,4.0,2.0,2.0,47.0,1.0
-ES,2446.0,6,4.0,4.0,5.0,8.0,8.0,2.0,1.0,2.0,52.0,1.0
-ES,2448.0,6,7.0,6.0,3.0,2.0,8.0,6.0,2.0,1.0,58.0,1.0
-ES,2450.0,6,3.0,5.0,6.0,5.0,7.0,5.0,3.0,1.0,48.0,1.0
-ES,2452.0,6,7.0,3.0,2.0,3.0,3.0,7.0,2.0,1.0,55.0,1.0
-ES,2453.0,6,4.0,6.0,8.0,7.0,10.0,6.0,3.0,2.0,52.0,1.0
-ES,2454.0,6,2.0,3.0,7.0,5.0,9.0,7.0,3.0,2.0,35.0,1.0
-ES,2456.0,6,4.0,7.0,6.0,1.0,7.0,6.0,3.0,1.0,55.0,1.0
-ES,2457.0,6,5.0,6.0,7.0,7.0,8.0,6.0,3.0,1.0,68.0,1.0
-ES,2458.0,6,3.0,5.0,7.0,5.0,8.0,6.0,3.0,1.0,79.0,1.0
-ES,2461.0,6,2.0,5.0,5.0,3.0,10.0,6.0,3.0,1.0,70.0,1.0
-ES,2462.0,6,6.0,7.0,7.0,5.0,10.0,5.0,3.0,2.0,60.0,1.0
-ES,2465.0,6,6.0,7.0,6.0,9.0,9.0,7.0,1.0,2.0,44.0,1.0
-ES,2467.0,6,7.0,4.0,5.0,6.0,4.0,5.0,1.0,2.0,,1.0
-ES,2470.0,6,6.0,3.0,6.0,7.0,8.0,7.0,4.0,1.0,69.0,1.0
-ES,2471.0,6,2.0,5.0,6.0,2.0,8.0,7.0,1.0,1.0,47.0,2.0
-ES,2474.0,6,3.0,5.0,6.0,5.0,6.0,2.0,3.0,2.0,44.0,2.0
-ES,2477.0,6,2.0,5.0,7.0,9.0,10.0,4.0,1.0,1.0,41.0,1.0
-ES,2489.0,6,3.0,3.0,0.0,0.0,9.0,4.0,2.0,1.0,37.0,1.0
-ES,2490.0,6,4.0,10.0,9.0,6.0,8.0,6.0,4.0,1.0,31.0,1.0
-ES,2493.0,6,3.0,5.0,5.0,6.0,6.0,4.0,1.0,2.0,68.0,1.0
-ES,2497.0,6,5.0,7.0,5.0,7.0,1.0,6.0,3.0,2.0,48.0,1.0
-ES,2499.0,6,4.0,6.0,6.0,4.0,7.0,4.0,2.0,2.0,55.0,1.0
-ES,2503.0,6,2.0,6.0,6.0,8.0,8.0,7.0,3.0,1.0,21.0,2.0
-ES,2508.0,6,7.0,6.0,5.0,6.0,8.0,7.0,3.0,2.0,80.0,2.0
-ES,2509.0,6,4.0,0.0,0.0,0.0,6.0,3.0,3.0,2.0,42.0,1.0
-ES,2511.0,6,7.0,5.0,7.0,4.0,7.0,6.0,3.0,1.0,27.0,2.0
-ES,2514.0,6,7.0,7.0,6.0,7.0,10.0,7.0,3.0,1.0,24.0,2.0
-ES,2515.0,6,7.0,4.0,5.0,0.0,10.0,7.0,1.0,1.0,45.0,2.0
-ES,2516.0,6,7.0,7.0,7.0,6.0,6.0,7.0,3.0,2.0,53.0,1.0
-ES,2517.0,6,7.0,7.0,1.0,6.0,10.0,7.0,5.0,2.0,80.0,2.0
-ES,2520.0,6,7.0,0.0,5.0,0.0,10.0,6.0,2.0,1.0,79.0,1.0
-ES,2522.0,6,7.0,0.0,0.0,0.0,10.0,7.0,2.0,1.0,64.0,1.0
-ES,2523.0,6,4.0,5.0,5.0,5.0,6.0,3.0,2.0,2.0,44.0,1.0
-ES,2525.0,6,7.0,4.0,8.0,5.0,8.0,5.0,3.0,2.0,86.0,1.0
-ES,2526.0,6,7.0,5.0,3.0,2.0,8.0,4.0,3.0,1.0,53.0,1.0
-ES,2527.0,6,3.0,4.0,7.0,4.0,9.0,6.0,3.0,1.0,71.0,1.0
-ES,2532.0,6,6.0,6.0,8.0,3.0,7.0,4.0,2.0,1.0,31.0,2.0
-ES,2534.0,6,1.0,7.0,7.0,5.0,8.0,7.0,5.0,2.0,40.0,2.0
-ES,2540.0,6,6.0,7.0,10.0,5.0,8.0,6.0,3.0,2.0,37.0,1.0
-ES,2541.0,6,6.0,6.0,5.0,6.0,8.0,7.0,3.0,1.0,42.0,2.0
-ES,2542.0,6,2.0,5.0,8.0,7.0,10.0,6.0,3.0,1.0,40.0,1.0
-ES,2543.0,6,3.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,32.0,1.0
-ES,2544.0,6,2.0,7.0,7.0,3.0,8.0,7.0,3.0,2.0,36.0,1.0
-ES,2545.0,6,7.0,5.0,6.0,9.0,6.0,3.0,2.0,2.0,63.0,2.0
-ES,2549.0,6,7.0,4.0,3.0,3.0,8.0,6.0,3.0,2.0,43.0,1.0
-ES,2551.0,6,1.0,5.0,7.0,2.0,9.0,5.0,3.0,2.0,60.0,1.0
-ES,2554.0,6,5.0,5.0,6.0,6.0,7.0,5.0,2.0,1.0,34.0,1.0
-ES,2555.0,6,2.0,4.0,5.0,6.0,8.0,4.0,2.0,1.0,17.0,2.0
-ES,2556.0,6,3.0,4.0,7.0,4.0,4.0,6.0,2.0,2.0,33.0,2.0
-ES,2558.0,6,0.0,5.0,6.0,3.0,7.0,6.0,2.0,1.0,26.0,2.0
-ES,2559.0,6,2.0,6.0,8.0,8.0,9.0,4.0,3.0,2.0,43.0,1.0
-ES,2564.0,6,3.0,5.0,6.0,3.0,7.0,6.0,3.0,1.0,32.0,2.0
-ES,2565.0,6,3.0,6.0,6.0,8.0,8.0,5.0,3.0,1.0,26.0,2.0
-ES,2566.0,6,5.0,5.0,5.0,8.0,7.0,2.0,1.0,1.0,41.0,1.0
-ES,2568.0,6,3.0,5.0,10.0,8.0,10.0,6.0,3.0,2.0,86.0,2.0
-ES,2571.0,6,7.0,3.0,5.0,5.0,9.0,3.0,1.0,2.0,53.0,2.0
-ES,2575.0,6,3.0,7.0,3.0,4.0,7.0,6.0,2.0,1.0,35.0,1.0
-ES,2578.0,6,6.0,9.0,9.0,7.0,8.0,6.0,4.0,2.0,61.0,2.0
-ES,2579.0,6,2.0,5.0,8.0,7.0,8.0,1.0,2.0,2.0,41.0,1.0
-ES,2581.0,6,4.0,8.0,8.0,7.0,9.0,7.0,3.0,1.0,16.0,2.0
-ES,2586.0,6,2.0,9.0,8.0,8.0,8.0,4.0,3.0,2.0,55.0,1.0
-ES,2590.0,6,7.0,9.0,8.0,7.0,5.0,6.0,1.0,1.0,38.0,2.0
-ES,2592.0,6,1.0,7.0,7.0,5.0,10.0,6.0,4.0,2.0,27.0,2.0
-ES,2596.0,6,1.0,6.0,9.0,8.0,10.0,6.0,5.0,1.0,56.0,1.0
-ES,2597.0,6,3.0,7.0,7.0,5.0,9.0,4.0,2.0,1.0,38.0,1.0
-ES,2598.0,6,3.0,4.0,2.0,1.0,8.0,6.0,1.0,1.0,39.0,2.0
-ES,2600.0,6,5.0,7.0,7.0,7.0,8.0,4.0,2.0,1.0,56.0,1.0
-ES,2602.0,6,7.0,8.0,7.0,3.0,7.0,7.0,2.0,2.0,40.0,1.0
-ES,2607.0,6,5.0,3.0,4.0,3.0,7.0,4.0,1.0,2.0,61.0,1.0
-ES,2608.0,6,2.0,5.0,7.0,5.0,9.0,6.0,3.0,2.0,52.0,1.0
-ES,2609.0,6,5.0,7.0,8.0,7.0,9.0,7.0,3.0,1.0,79.0,1.0
-ES,2613.0,6,7.0,5.0,6.0,4.0,3.0,5.0,2.0,2.0,83.0,2.0
-ES,2615.0,6,3.0,4.0,4.0,3.0,9.0,7.0,4.0,1.0,58.0,1.0
-ES,2618.0,6,2.0,2.0,6.0,1.0,8.0,7.0,2.0,1.0,20.0,2.0
-ES,2620.0,6,5.0,6.0,7.0,5.0,6.0,6.0,2.0,1.0,35.0,2.0
-ES,2623.0,6,3.0,6.0,7.0,7.0,8.0,6.0,3.0,1.0,30.0,2.0
-ES,2626.0,6,7.0,5.0,7.0,7.0,8.0,5.0,3.0,2.0,54.0,1.0
-ES,2627.0,6,7.0,7.0,8.0,5.0,8.0,5.0,3.0,1.0,52.0,2.0
-ES,2629.0,6,2.0,5.0,3.0,2.0,10.0,7.0,4.0,1.0,23.0,2.0
-ES,2631.0,6,7.0,2.0,4.0,3.0,7.0,6.0,3.0,2.0,73.0,1.0
-ES,2635.0,6,7.0,2.0,2.0,5.0,10.0,3.0,1.0,2.0,76.0,1.0
-ES,2636.0,6,6.0,3.0,7.0,5.0,5.0,3.0,2.0,2.0,58.0,1.0
-ES,2637.0,6,5.0,5.0,5.0,5.0,10.0,7.0,3.0,1.0,,1.0
-ES,2639.0,6,7.0,0.0,6.0,4.0,8.0,7.0,3.0,1.0,61.0,1.0
-ES,2642.0,6,5.0,7.0,8.0,6.0,7.0,6.0,3.0,2.0,55.0,1.0
-ES,2644.0,6,7.0,6.0,6.0,5.0,6.0,6.0,3.0,2.0,76.0,1.0
-ES,2647.0,6,7.0,10.0,8.0,5.0,10.0,4.0,5.0,2.0,44.0,1.0
-ES,2648.0,6,1.0,7.0,7.0,7.0,7.0,5.0,3.0,1.0,36.0,2.0
-ES,2650.0,6,1.0,7.0,6.0,5.0,9.0,3.0,2.0,1.0,50.0,1.0
-ES,2651.0,6,7.0,5.0,3.0,4.0,5.0,6.0,2.0,1.0,24.0,2.0
-ES,2653.0,6,6.0,5.0,7.0,8.0,10.0,7.0,4.0,2.0,61.0,1.0
-ES,2658.0,6,2.0,5.0,6.0,4.0,8.0,7.0,2.0,2.0,29.0,1.0
-ES,2661.0,6,7.0,2.0,2.0,5.0,9.0,6.0,1.0,1.0,70.0,1.0
-ES,2662.0,6,4.0,8.0,7.0,5.0,9.0,4.0,3.0,1.0,64.0,1.0
-ES,2663.0,6,5.0,0.0,5.0,3.0,10.0,5.0,3.0,1.0,58.0,1.0
-ES,2668.0,6,3.0,8.0,3.0,8.0,5.0,4.0,4.0,2.0,61.0,1.0
-ES,2669.0,6,7.0,6.0,4.0,3.0,7.0,5.0,1.0,1.0,39.0,2.0
-ES,2670.0,6,7.0,0.0,0.0,0.0,7.0,6.0,2.0,1.0,34.0,1.0
-ES,2671.0,6,2.0,5.0,2.0,8.0,7.0,3.0,3.0,1.0,35.0,1.0
-ES,2672.0,6,5.0,0.0,0.0,0.0,8.0,5.0,1.0,1.0,82.0,1.0
-ES,2674.0,6,4.0,5.0,7.0,4.0,8.0,6.0,2.0,2.0,26.0,2.0
-ES,2678.0,6,3.0,5.0,8.0,5.0,8.0,6.0,3.0,1.0,35.0,1.0
-ES,2683.0,6,0.0,7.0,4.0,6.0,8.0,6.0,1.0,1.0,36.0,2.0
-ES,2685.0,6,5.0,7.0,5.0,4.0,5.0,7.0,1.0,2.0,55.0,1.0
-ES,2686.0,6,4.0,5.0,6.0,3.0,8.0,5.0,2.0,1.0,42.0,1.0
-ES,2688.0,6,4.0,5.0,3.0,4.0,7.0,2.0,2.0,2.0,44.0,1.0
-ES,2689.0,6,7.0,4.0,4.0,7.0,9.0,5.0,1.0,2.0,76.0,1.0
-ES,2690.0,6,5.0,5.0,3.0,5.0,4.0,5.0,2.0,1.0,34.0,2.0
-ES,2692.0,6,7.0,5.0,5.0,3.0,6.0,6.0,2.0,1.0,70.0,1.0
-ES,2693.0,6,3.0,5.0,8.0,2.0,8.0,6.0,4.0,2.0,40.0,1.0
-ES,2694.0,6,4.0,7.0,7.0,7.0,8.0,7.0,2.0,2.0,63.0,1.0
-ES,2698.0,6,2.0,7.0,4.0,6.0,7.0,5.0,3.0,2.0,29.0,1.0
-ES,2700.0,6,4.0,2.0,2.0,5.0,9.0,2.0,2.0,1.0,65.0,1.0
-ES,2703.0,6,1.0,5.0,2.0,2.0,9.0,6.0,1.0,1.0,40.0,1.0
-ES,2705.0,6,6.0,7.0,5.0,4.0,5.0,4.0,2.0,2.0,64.0,1.0
-ES,2707.0,6,4.0,5.0,3.0,4.0,7.0,7.0,2.0,1.0,51.0,1.0
-ES,2709.0,6,6.0,8.0,9.0,7.0,10.0,6.0,1.0,2.0,68.0,1.0
-ES,2713.0,6,5.0,8.0,7.0,8.0,7.0,5.0,3.0,2.0,64.0,1.0
-ES,2714.0,6,6.0,2.0,3.0,0.0,8.0,3.0,5.0,1.0,35.0,1.0
-ES,2715.0,6,7.0,7.0,8.0,5.0,9.0,6.0,3.0,2.0,75.0,2.0
-ES,2720.0,6,1.0,6.0,6.0,9.0,7.0,3.0,2.0,1.0,49.0,1.0
-ES,2721.0,6,3.0,7.0,7.0,7.0,8.0,4.0,3.0,2.0,44.0,1.0
-ES,2722.0,6,2.0,6.0,5.0,6.0,9.0,3.0,3.0,1.0,45.0,1.0
-ES,2729.0,6,6.0,5.0,5.0,5.0,5.0,5.0,1.0,1.0,36.0,1.0
-ES,2731.0,6,3.0,5.0,6.0,7.0,9.0,3.0,5.0,1.0,57.0,1.0
-ES,2732.0,6,3.0,6.0,7.0,7.0,8.0,6.0,3.0,2.0,54.0,1.0
-ES,2733.0,6,5.0,8.0,9.0,9.0,10.0,6.0,3.0,2.0,38.0,1.0
-ES,2735.0,6,1.0,7.0,7.0,6.0,6.0,7.0,3.0,2.0,52.0,2.0
-ES,2736.0,6,7.0,2.0,1.0,1.0,6.0,7.0,1.0,2.0,41.0,1.0
-ES,2739.0,6,5.0,0.0,10.0,10.0,0.0,6.0,1.0,1.0,44.0,2.0
-ES,2740.0,6,1.0,7.0,8.0,7.0,8.0,6.0,4.0,2.0,38.0,1.0
-ES,2743.0,6,7.0,5.0,7.0,6.0,8.0,2.0,1.0,1.0,80.0,2.0
-ES,2747.0,6,3.0,5.0,3.0,3.0,7.0,5.0,3.0,1.0,26.0,2.0
-ES,2749.0,6,4.0,6.0,7.0,6.0,10.0,7.0,3.0,2.0,42.0,1.0
-ES,2751.0,6,1.0,6.0,4.0,6.0,8.0,7.0,3.0,2.0,36.0,1.0
-ES,2752.0,6,7.0,5.0,7.0,5.0,10.0,2.0,2.0,2.0,36.0,2.0
-ES,2755.0,6,7.0,5.0,9.0,6.0,9.0,7.0,2.0,2.0,32.0,2.0
-ES,2758.0,6,3.0,5.0,6.0,6.0,9.0,4.0,2.0,1.0,19.0,2.0
-ES,2760.0,6,2.0,5.0,5.0,5.0,6.0,7.0,3.0,2.0,28.0,1.0
-ES,2764.0,6,3.0,7.0,3.0,6.0,8.0,4.0,2.0,2.0,37.0,1.0
-ES,2765.0,6,7.0,6.0,7.0,3.0,3.0,6.0,3.0,1.0,65.0,2.0
-ES,2770.0,6,2.0,3.0,3.0,3.0,5.0,7.0,2.0,1.0,41.0,1.0
-ES,2773.0,6,3.0,5.0,5.0,6.0,8.0,5.0,2.0,2.0,56.0,1.0
-ES,2777.0,6,7.0,0.0,0.0,0.0,8.0,6.0,3.0,2.0,82.0,2.0
-ES,2778.0,6,4.0,7.0,9.0,7.0,9.0,6.0,3.0,1.0,41.0,1.0
-ES,2782.0,6,5.0,3.0,5.0,1.0,7.0,6.0,1.0,1.0,34.0,2.0
-ES,2786.0,6,3.0,1.0,0.0,0.0,4.0,5.0,3.0,1.0,26.0,2.0
-ES,2788.0,6,5.0,6.0,4.0,3.0,5.0,6.0,3.0,2.0,80.0,2.0
-ES,2789.0,6,5.0,6.0,6.0,4.0,7.0,4.0,2.0,1.0,43.0,1.0
-ES,2791.0,6,4.0,3.0,4.0,5.0,7.0,4.0,2.0,2.0,55.0,1.0
-ES,2793.0,6,7.0,5.0,5.0,5.0,5.0,4.0,2.0,2.0,41.0,1.0
-ES,2794.0,6,4.0,6.0,5.0,6.0,7.0,7.0,3.0,2.0,44.0,2.0
-ES,2795.0,6,4.0,3.0,3.0,5.0,8.0,7.0,3.0,1.0,23.0,2.0
-ES,2797.0,6,6.0,6.0,6.0,3.0,7.0,6.0,4.0,2.0,27.0,2.0
-ES,2798.0,6,1.0,8.0,5.0,5.0,9.0,5.0,3.0,2.0,29.0,2.0
-ES,2799.0,6,3.0,6.0,3.0,2.0,6.0,4.0,2.0,1.0,30.0,1.0
-ES,2800.0,6,3.0,8.0,8.0,8.0,9.0,7.0,4.0,2.0,47.0,1.0
-ES,2806.0,6,4.0,7.0,7.0,5.0,7.0,4.0,3.0,2.0,55.0,2.0
-ES,2808.0,6,7.0,0.0,0.0,3.0,8.0,2.0,1.0,1.0,59.0,1.0
-ES,2811.0,6,3.0,6.0,5.0,5.0,10.0,5.0,2.0,1.0,63.0,1.0
-ES,2813.0,6,3.0,5.0,7.0,3.0,9.0,7.0,4.0,2.0,48.0,1.0
-ES,2817.0,6,4.0,6.0,6.0,6.0,7.0,4.0,3.0,2.0,41.0,1.0
-ES,2818.0,6,6.0,5.0,5.0,5.0,2.0,7.0,2.0,1.0,36.0,2.0
-ES,2819.0,6,6.0,8.0,5.0,6.0,8.0,6.0,4.0,2.0,23.0,2.0
-ES,2820.0,6,2.0,4.0,4.0,7.0,7.0,2.0,3.0,1.0,46.0,2.0
-ES,2826.0,6,2.0,8.0,5.0,3.0,10.0,5.0,3.0,1.0,29.0,1.0
-ES,2828.0,6,4.0,5.0,9.0,9.0,10.0,7.0,4.0,1.0,80.0,1.0
-ES,2829.0,6,3.0,3.0,3.0,2.0,5.0,5.0,2.0,2.0,65.0,1.0
-ES,2830.0,6,0.0,6.0,7.0,3.0,7.0,7.0,3.0,2.0,27.0,2.0
-ES,2831.0,6,2.0,0.0,1.0,3.0,8.0,7.0,4.0,1.0,42.0,1.0
-ES,2835.0,6,3.0,3.0,3.0,4.0,7.0,5.0,2.0,2.0,65.0,1.0
-ES,2836.0,6,4.0,0.0,5.0,2.0,9.0,4.0,2.0,2.0,48.0,2.0
-ES,2837.0,6,3.0,5.0,5.0,3.0,5.0,7.0,2.0,1.0,86.0,1.0
-ES,2841.0,6,2.0,4.0,4.0,6.0,7.0,6.0,3.0,2.0,34.0,2.0
-ES,2845.0,6,3.0,7.0,7.0,5.0,8.0,5.0,3.0,1.0,37.0,1.0
-ES,2847.0,6,4.0,7.0,8.0,4.0,8.0,5.0,3.0,1.0,,2.0
-ES,2848.0,6,2.0,5.0,5.0,4.0,5.0,2.0,2.0,2.0,52.0,1.0
-ES,2850.0,6,3.0,9.0,7.0,7.0,9.0,4.0,2.0,1.0,52.0,1.0
-ES,2857.0,6,7.0,4.0,9.0,4.0,5.0,4.0,1.0,1.0,37.0,2.0
-ES,2859.0,6,7.0,8.0,9.0,2.0,10.0,7.0,1.0,2.0,48.0,1.0
-ES,2861.0,6,3.0,7.0,7.0,4.0,10.0,3.0,3.0,1.0,48.0,1.0
-ES,2865.0,6,6.0,5.0,5.0,3.0,6.0,4.0,2.0,1.0,70.0,2.0
-ES,1.0,7,2.0,6.0,6.0,3.0,7.0,7.0,3.0,2.0,34.0,2.0
-ES,3.0,7,2.0,6.0,6.0,8.0,9.0,2.0,2.0,1.0,59.0,1.0
-ES,5.0,7,2.0,7.0,7.0,6.0,8.0,7.0,3.0,1.0,46.0,1.0
-ES,6.0,7,5.0,10.0,10.0,6.0,5.0,7.0,3.0,2.0,67.0,1.0
-ES,8.0,7,7.0,2.0,8.0,0.0,6.0,7.0,2.0,2.0,61.0,1.0
-ES,10.0,7,6.0,2.0,8.0,0.0,9.0,3.0,3.0,2.0,61.0,1.0
-ES,15.0,7,4.0,0.0,5.0,5.0,7.0,6.0,1.0,1.0,55.0,2.0
-ES,18.0,7,2.0,1.0,3.0,4.0,8.0,6.0,1.0,1.0,37.0,1.0
-ES,19.0,7,0.0,6.0,6.0,5.0,10.0,7.0,3.0,2.0,20.0,2.0
-ES,22.0,7,5.0,3.0,6.0,6.0,9.0,6.0,4.0,2.0,72.0,1.0
-ES,23.0,7,3.0,2.0,5.0,2.0,5.0,6.0,3.0,1.0,36.0,2.0
-ES,25.0,7,0.0,7.0,6.0,2.0,9.0,6.0,5.0,1.0,28.0,2.0
-ES,27.0,7,7.0,7.0,2.0,4.0,2.0,4.0,1.0,2.0,52.0,2.0
-ES,28.0,7,5.0,2.0,2.0,2.0,7.0,5.0,,1.0,71.0,1.0
-ES,33.0,7,4.0,5.0,8.0,4.0,9.0,6.0,3.0,2.0,17.0,2.0
-ES,34.0,7,2.0,4.0,2.0,4.0,1.0,6.0,2.0,1.0,80.0,1.0
-ES,36.0,7,7.0,7.0,,6.0,6.0,5.0,1.0,1.0,37.0,2.0
-ES,38.0,7,7.0,4.0,3.0,5.0,9.0,6.0,3.0,2.0,45.0,1.0
-ES,39.0,7,4.0,0.0,5.0,0.0,10.0,7.0,3.0,2.0,31.0,1.0
-ES,41.0,7,3.0,3.0,6.0,0.0,8.0,5.0,2.0,1.0,39.0,1.0
-ES,44.0,7,7.0,5.0,8.0,3.0,4.0,5.0,1.0,1.0,81.0,2.0
-ES,45.0,7,6.0,6.0,5.0,6.0,8.0,6.0,4.0,1.0,65.0,2.0
-ES,46.0,7,7.0,5.0,6.0,3.0,10.0,7.0,3.0,2.0,50.0,1.0
-ES,47.0,7,1.0,4.0,7.0,5.0,8.0,5.0,2.0,2.0,20.0,2.0
-ES,48.0,7,7.0,3.0,,5.0,10.0,7.0,,2.0,82.0,1.0
-ES,50.0,7,7.0,5.0,4.0,2.0,1.0,4.0,1.0,1.0,49.0,2.0
-ES,52.0,7,3.0,5.0,6.0,3.0,6.0,5.0,3.0,2.0,37.0,1.0
-ES,53.0,7,3.0,8.0,6.0,6.0,8.0,6.0,3.0,2.0,19.0,2.0
-ES,55.0,7,5.0,5.0,8.0,5.0,9.0,4.0,2.0,2.0,47.0,2.0
-ES,56.0,7,2.0,7.0,4.0,7.0,7.0,4.0,3.0,2.0,17.0,2.0
-ES,61.0,7,3.0,5.0,3.0,2.0,7.0,6.0,5.0,1.0,65.0,1.0
-ES,62.0,7,2.0,5.0,4.0,6.0,5.0,6.0,3.0,2.0,26.0,2.0
-ES,64.0,7,3.0,5.0,6.0,5.0,9.0,3.0,3.0,1.0,72.0,2.0
-ES,70.0,7,3.0,7.0,6.0,5.0,8.0,6.0,4.0,2.0,62.0,2.0
-ES,71.0,7,4.0,5.0,5.0,5.0,7.0,6.0,3.0,1.0,39.0,2.0
-ES,75.0,7,6.0,8.0,6.0,6.0,5.0,4.0,,2.0,84.0,2.0
-ES,78.0,7,6.0,5.0,8.0,4.0,8.0,6.0,3.0,2.0,24.0,2.0
-ES,79.0,7,4.0,1.0,5.0,1.0,8.0,6.0,3.0,2.0,60.0,1.0
-ES,80.0,7,7.0,5.0,5.0,1.0,9.0,6.0,2.0,2.0,46.0,2.0
-ES,82.0,7,4.0,0.0,1.0,1.0,7.0,7.0,1.0,2.0,75.0,1.0
-ES,86.0,7,2.0,5.0,8.0,3.0,9.0,7.0,3.0,1.0,21.0,2.0
-ES,87.0,7,3.0,3.0,5.0,5.0,7.0,6.0,2.0,1.0,16.0,2.0
-ES,95.0,7,6.0,3.0,3.0,3.0,7.0,2.0,3.0,1.0,63.0,1.0
-ES,96.0,7,3.0,10.0,10.0,8.0,7.0,7.0,2.0,1.0,44.0,1.0
-ES,98.0,7,5.0,5.0,5.0,3.0,7.0,3.0,3.0,1.0,45.0,1.0
-ES,106.0,7,3.0,7.0,5.0,7.0,7.0,2.0,1.0,1.0,60.0,2.0
-ES,108.0,7,4.0,4.0,5.0,6.0,9.0,5.0,4.0,1.0,54.0,1.0
-ES,109.0,7,2.0,6.0,4.0,6.0,8.0,4.0,2.0,1.0,50.0,1.0
-ES,110.0,7,3.0,7.0,8.0,5.0,8.0,5.0,2.0,1.0,16.0,2.0
-ES,112.0,7,2.0,5.0,5.0,5.0,7.0,7.0,3.0,2.0,33.0,2.0
-ES,113.0,7,4.0,4.0,5.0,4.0,7.0,4.0,3.0,1.0,18.0,2.0
-ES,117.0,7,3.0,5.0,5.0,2.0,5.0,3.0,1.0,1.0,46.0,2.0
-ES,119.0,7,3.0,6.0,6.0,6.0,9.0,7.0,4.0,1.0,67.0,1.0
-ES,120.0,7,2.0,3.0,7.0,5.0,6.0,5.0,2.0,1.0,56.0,1.0
-ES,122.0,7,7.0,6.0,4.0,6.0,8.0,7.0,2.0,2.0,53.0,1.0
-ES,134.0,7,5.0,7.0,7.0,7.0,7.0,5.0,3.0,2.0,35.0,1.0
-ES,138.0,7,5.0,7.0,5.0,10.0,6.0,5.0,3.0,1.0,56.0,1.0
-ES,140.0,7,7.0,6.0,5.0,6.0,6.0,5.0,3.0,1.0,38.0,1.0
-ES,153.0,7,7.0,2.0,2.0,3.0,4.0,2.0,4.0,2.0,47.0,1.0
-ES,156.0,7,5.0,3.0,5.0,6.0,8.0,5.0,3.0,2.0,,1.0
-ES,159.0,7,4.0,3.0,3.0,5.0,8.0,7.0,3.0,2.0,47.0,1.0
-ES,160.0,7,4.0,3.0,3.0,5.0,9.0,7.0,4.0,2.0,68.0,2.0
-ES,171.0,7,3.0,5.0,7.0,6.0,8.0,4.0,2.0,2.0,35.0,2.0
-ES,172.0,7,6.0,5.0,4.0,6.0,9.0,7.0,2.0,1.0,23.0,2.0
-ES,173.0,7,4.0,0.0,8.0,5.0,10.0,7.0,,1.0,61.0,1.0
-ES,176.0,7,3.0,8.0,8.0,0.0,8.0,1.0,2.0,2.0,48.0,1.0
-ES,180.0,7,3.0,7.0,7.0,4.0,6.0,2.0,3.0,2.0,34.0,1.0
-ES,181.0,7,0.0,5.0,6.0,2.0,8.0,5.0,3.0,2.0,40.0,1.0
-ES,183.0,7,1.0,5.0,3.0,5.0,4.0,2.0,1.0,2.0,34.0,1.0
-ES,184.0,7,5.0,8.0,9.0,7.0,5.0,7.0,3.0,2.0,89.0,2.0
-ES,188.0,7,2.0,1.0,1.0,5.0,10.0,5.0,3.0,2.0,29.0,1.0
-ES,189.0,7,7.0,8.0,5.0,2.0,10.0,7.0,4.0,1.0,45.0,2.0
-ES,190.0,7,3.0,1.0,8.0,7.0,0.0,1.0,1.0,2.0,,2.0
-ES,194.0,7,3.0,0.0,4.0,3.0,10.0,6.0,3.0,2.0,43.0,1.0
-ES,202.0,7,1.0,4.0,4.0,4.0,10.0,4.0,2.0,2.0,37.0,1.0
-ES,204.0,7,7.0,5.0,5.0,5.0,5.0,1.0,2.0,2.0,46.0,1.0
-ES,206.0,7,1.0,5.0,6.0,8.0,10.0,4.0,4.0,1.0,60.0,1.0
-ES,208.0,7,7.0,5.0,5.0,3.0,1.0,6.0,1.0,1.0,40.0,1.0
-ES,209.0,7,4.0,3.0,5.0,7.0,8.0,4.0,1.0,2.0,34.0,1.0
-ES,213.0,7,5.0,2.0,2.0,3.0,4.0,5.0,2.0,1.0,53.0,1.0
-ES,216.0,7,,6.0,6.0,5.0,8.0,6.0,3.0,1.0,34.0,1.0
-ES,218.0,7,2.0,5.0,7.0,3.0,9.0,7.0,1.0,2.0,23.0,2.0
-ES,219.0,7,0.0,4.0,4.0,2.0,7.0,4.0,3.0,2.0,25.0,2.0
-ES,221.0,7,3.0,0.0,1.0,0.0,9.0,7.0,3.0,1.0,84.0,1.0
-ES,223.0,7,1.0,6.0,5.0,3.0,8.0,6.0,3.0,1.0,34.0,1.0
-ES,225.0,7,1.0,5.0,5.0,2.0,7.0,5.0,3.0,2.0,23.0,2.0
-ES,226.0,7,3.0,6.0,6.0,7.0,7.0,4.0,2.0,1.0,50.0,1.0
-ES,228.0,7,2.0,7.0,1.0,5.0,8.0,5.0,1.0,2.0,22.0,2.0
-ES,229.0,7,4.0,5.0,6.0,6.0,8.0,6.0,3.0,2.0,51.0,1.0
-ES,232.0,7,2.0,5.0,5.0,8.0,8.0,6.0,4.0,1.0,33.0,2.0
-ES,233.0,7,1.0,8.0,7.0,7.0,3.0,1.0,1.0,2.0,85.0,2.0
-ES,235.0,7,2.0,8.0,8.0,8.0,2.0,5.0,1.0,2.0,80.0,1.0
-ES,236.0,7,2.0,5.0,9.0,8.0,9.0,7.0,1.0,2.0,73.0,1.0
-ES,238.0,7,3.0,5.0,5.0,2.0,8.0,3.0,4.0,2.0,27.0,1.0
-ES,242.0,7,3.0,6.0,4.0,6.0,6.0,6.0,1.0,2.0,27.0,2.0
-ES,244.0,7,5.0,8.0,7.0,4.0,7.0,5.0,1.0,1.0,20.0,2.0
-ES,247.0,7,7.0,3.0,3.0,2.0,7.0,4.0,3.0,2.0,74.0,1.0
-ES,248.0,7,2.0,5.0,8.0,2.0,7.0,7.0,3.0,2.0,33.0,1.0
-ES,251.0,7,3.0,6.0,6.0,2.0,8.0,4.0,3.0,2.0,34.0,1.0
-ES,252.0,7,3.0,8.0,8.0,5.0,10.0,6.0,3.0,1.0,33.0,1.0
-ES,253.0,7,1.0,2.0,3.0,2.0,9.0,7.0,2.0,1.0,33.0,1.0
-ES,254.0,7,5.0,6.0,7.0,6.0,9.0,6.0,3.0,2.0,51.0,1.0
-ES,261.0,7,3.0,5.0,5.0,2.0,8.0,6.0,3.0,1.0,28.0,2.0
-ES,262.0,7,1.0,4.0,2.0,5.0,8.0,4.0,3.0,2.0,44.0,1.0
-ES,263.0,7,4.0,1.0,2.0,4.0,7.0,6.0,3.0,2.0,17.0,2.0
-ES,264.0,7,4.0,7.0,6.0,6.0,8.0,6.0,3.0,2.0,40.0,1.0
-ES,265.0,7,1.0,5.0,4.0,2.0,8.0,4.0,3.0,2.0,41.0,2.0
-ES,269.0,7,1.0,2.0,2.0,1.0,8.0,4.0,3.0,2.0,36.0,1.0
-ES,270.0,7,5.0,7.0,5.0,4.0,10.0,7.0,3.0,2.0,52.0,1.0
-ES,272.0,7,5.0,7.0,5.0,4.0,9.0,6.0,3.0,1.0,39.0,1.0
-ES,276.0,7,3.0,5.0,5.0,3.0,8.0,4.0,3.0,1.0,48.0,1.0
-ES,277.0,7,6.0,2.0,5.0,5.0,9.0,7.0,5.0,1.0,73.0,1.0
-ES,280.0,7,5.0,4.0,5.0,6.0,9.0,5.0,4.0,2.0,70.0,1.0
-ES,281.0,7,3.0,4.0,6.0,4.0,7.0,5.0,2.0,1.0,51.0,1.0
-ES,283.0,7,6.0,2.0,3.0,5.0,9.0,4.0,3.0,1.0,56.0,1.0
-ES,284.0,7,4.0,3.0,5.0,3.0,8.0,5.0,3.0,1.0,39.0,1.0
-ES,287.0,7,5.0,5.0,5.0,5.0,5.0,5.0,2.0,1.0,52.0,1.0
-ES,290.0,7,6.0,4.0,3.0,2.0,7.0,6.0,3.0,2.0,35.0,1.0
-ES,291.0,7,7.0,4.0,6.0,6.0,8.0,6.0,2.0,2.0,19.0,2.0
-ES,292.0,7,2.0,2.0,2.0,4.0,8.0,7.0,1.0,1.0,69.0,1.0
-ES,293.0,7,2.0,3.0,3.0,5.0,8.0,5.0,2.0,1.0,75.0,1.0
-ES,301.0,7,1.0,2.0,5.0,3.0,6.0,5.0,3.0,1.0,25.0,2.0
-ES,304.0,7,4.0,5.0,5.0,5.0,10.0,4.0,4.0,1.0,41.0,1.0
-ES,305.0,7,2.0,6.0,5.0,5.0,10.0,4.0,3.0,1.0,40.0,1.0
-ES,307.0,7,1.0,5.0,6.0,2.0,6.0,3.0,2.0,2.0,39.0,1.0
-ES,312.0,7,3.0,3.0,4.0,5.0,6.0,5.0,3.0,2.0,46.0,1.0
-ES,315.0,7,2.0,6.0,5.0,2.0,8.0,7.0,4.0,1.0,25.0,2.0
-ES,317.0,7,1.0,7.0,,6.0,5.0,1.0,1.0,2.0,86.0,2.0
-ES,319.0,7,7.0,5.0,5.0,1.0,10.0,7.0,1.0,2.0,83.0,2.0
-ES,321.0,7,4.0,10.0,9.0,10.0,10.0,6.0,1.0,2.0,21.0,2.0
-ES,323.0,7,4.0,8.0,7.0,8.0,10.0,7.0,3.0,1.0,69.0,2.0
-ES,325.0,7,2.0,4.0,5.0,6.0,5.0,6.0,2.0,2.0,47.0,1.0
-ES,326.0,7,0.0,5.0,5.0,6.0,5.0,6.0,3.0,2.0,51.0,2.0
-ES,327.0,7,6.0,5.0,4.0,4.0,8.0,5.0,1.0,1.0,74.0,1.0
-ES,328.0,7,3.0,8.0,8.0,2.0,9.0,6.0,3.0,2.0,39.0,1.0
-ES,329.0,7,1.0,5.0,4.0,5.0,5.0,6.0,1.0,1.0,25.0,2.0
-ES,330.0,7,2.0,5.0,5.0,7.0,5.0,2.0,3.0,2.0,63.0,2.0
-ES,333.0,7,7.0,7.0,6.0,7.0,6.0,7.0,3.0,2.0,58.0,1.0
-ES,337.0,7,2.0,4.0,6.0,0.0,7.0,5.0,3.0,2.0,52.0,1.0
-ES,347.0,7,3.0,9.0,5.0,7.0,5.0,5.0,,1.0,33.0,2.0
-ES,348.0,7,2.0,3.0,3.0,5.0,8.0,2.0,2.0,2.0,64.0,1.0
-ES,351.0,7,6.0,5.0,5.0,7.0,5.0,6.0,3.0,1.0,54.0,2.0
-ES,354.0,7,2.0,3.0,5.0,5.0,10.0,6.0,3.0,2.0,19.0,2.0
-ES,356.0,7,0.0,6.0,4.0,4.0,10.0,7.0,3.0,2.0,32.0,1.0
-ES,357.0,7,2.0,9.0,8.0,6.0,9.0,6.0,4.0,1.0,34.0,2.0
-ES,360.0,7,5.0,6.0,4.0,4.0,7.0,7.0,2.0,1.0,73.0,1.0
-ES,363.0,7,2.0,6.0,5.0,6.0,7.0,6.0,2.0,1.0,20.0,2.0
-ES,366.0,7,4.0,5.0,7.0,5.0,8.0,2.0,3.0,2.0,56.0,1.0
-ES,373.0,7,1.0,5.0,7.0,5.0,8.0,6.0,2.0,2.0,38.0,2.0
-ES,374.0,7,5.0,5.0,6.0,5.0,9.0,6.0,3.0,2.0,58.0,1.0
-ES,378.0,7,7.0,5.0,8.0,5.0,10.0,6.0,2.0,1.0,75.0,1.0
-ES,381.0,7,6.0,6.0,8.0,4.0,6.0,7.0,3.0,2.0,26.0,2.0
-ES,382.0,7,2.0,5.0,3.0,4.0,5.0,5.0,2.0,1.0,65.0,2.0
-ES,383.0,7,3.0,5.0,0.0,0.0,7.0,6.0,4.0,2.0,58.0,1.0
-ES,385.0,7,7.0,7.0,7.0,6.0,8.0,5.0,3.0,2.0,68.0,1.0
-ES,386.0,7,4.0,6.0,6.0,5.0,8.0,7.0,4.0,1.0,49.0,1.0
-ES,387.0,7,7.0,7.0,7.0,6.0,6.0,3.0,3.0,2.0,60.0,1.0
-ES,389.0,7,5.0,8.0,4.0,4.0,8.0,5.0,4.0,2.0,37.0,1.0
-ES,395.0,7,2.0,5.0,8.0,2.0,8.0,6.0,2.0,1.0,32.0,1.0
-ES,396.0,7,0.0,2.0,6.0,2.0,10.0,7.0,2.0,2.0,42.0,1.0
-ES,398.0,7,5.0,3.0,5.0,5.0,8.0,2.0,3.0,2.0,63.0,1.0
-ES,405.0,7,6.0,3.0,7.0,3.0,4.0,5.0,2.0,2.0,80.0,2.0
-ES,406.0,7,3.0,3.0,5.0,2.0,6.0,6.0,4.0,1.0,62.0,2.0
-ES,407.0,7,3.0,7.0,7.0,4.0,7.0,4.0,3.0,1.0,36.0,2.0
-ES,411.0,7,2.0,4.0,6.0,8.0,8.0,6.0,4.0,2.0,32.0,2.0
-ES,415.0,7,7.0,7.0,9.0,7.0,9.0,6.0,3.0,1.0,54.0,1.0
-ES,416.0,7,3.0,8.0,8.0,6.0,6.0,6.0,3.0,2.0,50.0,2.0
-ES,417.0,7,7.0,1.0,2.0,5.0,4.0,4.0,2.0,2.0,83.0,2.0
-ES,431.0,7,7.0,0.0,2.0,0.0,10.0,5.0,2.0,1.0,51.0,2.0
-ES,433.0,7,6.0,2.0,8.0,7.0,5.0,7.0,4.0,2.0,58.0,2.0
-ES,435.0,7,6.0,8.0,9.0,5.0,9.0,6.0,3.0,2.0,27.0,2.0
-ES,437.0,7,3.0,9.0,9.0,7.0,10.0,6.0,4.0,2.0,63.0,1.0
-ES,440.0,7,4.0,6.0,5.0,4.0,8.0,6.0,4.0,2.0,60.0,1.0
-ES,441.0,7,5.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,57.0,1.0
-ES,442.0,7,1.0,2.0,1.0,1.0,2.0,2.0,1.0,1.0,38.0,2.0
-ES,443.0,7,5.0,6.0,6.0,4.0,8.0,5.0,2.0,1.0,48.0,1.0
-ES,444.0,7,7.0,3.0,6.0,3.0,8.0,6.0,2.0,2.0,67.0,2.0
-ES,461.0,7,0.0,5.0,5.0,3.0,7.0,4.0,3.0,1.0,34.0,1.0
-ES,463.0,7,1.0,7.0,7.0,6.0,7.0,5.0,3.0,2.0,50.0,1.0
-ES,464.0,7,3.0,4.0,6.0,4.0,8.0,4.0,3.0,2.0,48.0,1.0
-ES,468.0,7,0.0,6.0,6.0,3.0,7.0,7.0,4.0,2.0,70.0,2.0
-ES,471.0,7,3.0,4.0,4.0,5.0,6.0,1.0,1.0,2.0,57.0,2.0
-ES,474.0,7,7.0,5.0,5.0,6.0,9.0,6.0,3.0,2.0,16.0,2.0
-ES,475.0,7,2.0,3.0,3.0,3.0,7.0,5.0,3.0,1.0,37.0,1.0
-ES,482.0,7,3.0,1.0,5.0,5.0,8.0,6.0,2.0,2.0,29.0,1.0
-ES,486.0,7,5.0,6.0,9.0,2.0,4.0,2.0,2.0,2.0,69.0,1.0
-ES,489.0,7,3.0,5.0,5.0,7.0,8.0,5.0,3.0,2.0,28.0,1.0
-ES,492.0,7,4.0,9.0,8.0,6.0,9.0,7.0,3.0,2.0,43.0,1.0
-ES,499.0,7,4.0,5.0,5.0,10.0,9.0,6.0,1.0,1.0,57.0,1.0
-ES,501.0,7,7.0,5.0,8.0,5.0,8.0,2.0,1.0,2.0,26.0,2.0
-ES,503.0,7,1.0,7.0,6.0,4.0,7.0,7.0,2.0,2.0,24.0,1.0
-ES,508.0,7,2.0,7.0,2.0,4.0,6.0,5.0,4.0,1.0,24.0,2.0
-ES,514.0,7,5.0,10.0,9.0,0.0,10.0,6.0,4.0,1.0,32.0,1.0
-ES,520.0,7,4.0,3.0,2.0,4.0,9.0,3.0,2.0,2.0,50.0,1.0
-ES,523.0,7,2.0,3.0,0.0,3.0,4.0,5.0,2.0,1.0,33.0,1.0
-ES,525.0,7,2.0,3.0,5.0,6.0,8.0,6.0,2.0,1.0,20.0,1.0
-ES,532.0,7,1.0,7.0,3.0,3.0,6.0,7.0,4.0,1.0,49.0,1.0
-ES,540.0,7,3.0,7.0,4.0,2.0,9.0,6.0,4.0,2.0,59.0,1.0
-ES,546.0,7,3.0,5.0,6.0,4.0,8.0,4.0,3.0,1.0,69.0,1.0
-ES,547.0,7,4.0,8.0,8.0,6.0,9.0,5.0,3.0,1.0,19.0,2.0
-ES,548.0,7,7.0,0.0,5.0,5.0,5.0,6.0,3.0,1.0,78.0,1.0
-ES,552.0,7,6.0,5.0,7.0,6.0,8.0,6.0,3.0,1.0,50.0,1.0
-ES,553.0,7,2.0,7.0,8.0,5.0,8.0,7.0,4.0,2.0,28.0,2.0
-ES,554.0,7,3.0,7.0,7.0,8.0,7.0,5.0,2.0,2.0,24.0,1.0
-ES,555.0,7,2.0,10.0,5.0,5.0,10.0,5.0,2.0,2.0,30.0,1.0
-ES,558.0,7,4.0,9.0,6.0,5.0,8.0,3.0,2.0,1.0,57.0,2.0
-ES,561.0,7,2.0,4.0,5.0,3.0,7.0,6.0,4.0,2.0,19.0,2.0
-ES,563.0,7,7.0,5.0,3.0,3.0,8.0,4.0,3.0,1.0,60.0,1.0
-ES,567.0,7,6.0,0.0,5.0,1.0,4.0,4.0,2.0,1.0,33.0,
-ES,569.0,7,3.0,6.0,5.0,5.0,8.0,6.0,3.0,1.0,48.0,2.0
-ES,572.0,7,2.0,7.0,7.0,8.0,8.0,6.0,2.0,1.0,45.0,2.0
-ES,574.0,7,7.0,7.0,7.0,8.0,7.0,6.0,2.0,2.0,67.0,1.0
-ES,575.0,7,7.0,7.0,6.0,5.0,6.0,7.0,2.0,1.0,63.0,2.0
-ES,576.0,7,7.0,6.0,6.0,5.0,8.0,7.0,2.0,1.0,20.0,2.0
-ES,578.0,7,7.0,7.0,7.0,4.0,7.0,7.0,2.0,1.0,69.0,1.0
-ES,579.0,7,4.0,6.0,6.0,2.0,7.0,3.0,3.0,1.0,46.0,1.0
-ES,580.0,7,4.0,3.0,6.0,4.0,8.0,7.0,2.0,2.0,72.0,1.0
-ES,583.0,7,2.0,6.0,6.0,6.0,8.0,7.0,3.0,1.0,18.0,2.0
-ES,585.0,7,5.0,5.0,6.0,6.0,9.0,5.0,4.0,1.0,47.0,1.0
-ES,587.0,7,2.0,8.0,8.0,5.0,8.0,5.0,3.0,1.0,43.0,1.0
-ES,590.0,7,5.0,3.0,6.0,3.0,10.0,5.0,1.0,1.0,40.0,1.0
-ES,592.0,7,2.0,7.0,7.0,6.0,8.0,6.0,4.0,1.0,40.0,1.0
-ES,593.0,7,5.0,1.0,8.0,1.0,9.0,4.0,2.0,1.0,62.0,1.0
-ES,596.0,7,1.0,8.0,8.0,7.0,8.0,6.0,4.0,1.0,46.0,1.0
-ES,598.0,7,6.0,5.0,7.0,3.0,9.0,7.0,2.0,1.0,75.0,1.0
-ES,599.0,7,7.0,4.0,5.0,3.0,6.0,6.0,3.0,1.0,21.0,1.0
-ES,600.0,7,2.0,3.0,4.0,4.0,9.0,6.0,2.0,2.0,17.0,2.0
-ES,602.0,7,0.0,8.0,5.0,2.0,9.0,5.0,2.0,2.0,18.0,2.0
-ES,603.0,7,4.0,6.0,7.0,6.0,9.0,7.0,2.0,1.0,45.0,1.0
-ES,604.0,7,4.0,6.0,6.0,3.0,6.0,3.0,3.0,1.0,61.0,1.0
-ES,605.0,7,0.0,5.0,7.0,3.0,10.0,5.0,2.0,1.0,19.0,2.0
-ES,608.0,7,4.0,9.0,6.0,5.0,10.0,3.0,3.0,1.0,45.0,1.0
-ES,613.0,7,4.0,6.0,4.0,5.0,7.0,6.0,3.0,1.0,30.0,2.0
-ES,614.0,7,7.0,3.0,7.0,3.0,7.0,6.0,2.0,1.0,35.0,1.0
-ES,623.0,7,2.0,7.0,7.0,6.0,8.0,5.0,3.0,2.0,45.0,1.0
-ES,628.0,7,7.0,6.0,8.0,3.0,5.0,6.0,5.0,2.0,50.0,2.0
-ES,635.0,7,7.0,3.0,3.0,5.0,5.0,5.0,2.0,1.0,61.0,2.0
-ES,636.0,7,7.0,5.0,3.0,5.0,9.0,6.0,1.0,2.0,72.0,2.0
-ES,639.0,7,3.0,4.0,4.0,5.0,7.0,4.0,2.0,1.0,76.0,1.0
-ES,645.0,7,2.0,6.0,5.0,6.0,7.0,7.0,4.0,2.0,53.0,1.0
-ES,646.0,7,3.0,4.0,,3.0,8.0,7.0,2.0,2.0,80.0,1.0
-ES,647.0,7,4.0,5.0,5.0,5.0,6.0,6.0,3.0,1.0,40.0,1.0
-ES,650.0,7,7.0,1.0,1.0,5.0,7.0,7.0,1.0,2.0,16.0,2.0
-ES,651.0,7,4.0,4.0,7.0,3.0,6.0,4.0,2.0,2.0,54.0,2.0
-ES,652.0,7,3.0,4.0,3.0,3.0,7.0,5.0,3.0,1.0,53.0,1.0
-ES,653.0,7,6.0,2.0,3.0,1.0,9.0,6.0,2.0,2.0,41.0,1.0
-ES,654.0,7,2.0,6.0,6.0,2.0,7.0,5.0,3.0,2.0,22.0,2.0
-ES,655.0,7,2.0,5.0,7.0,2.0,8.0,4.0,4.0,1.0,65.0,1.0
-ES,656.0,7,3.0,6.0,6.0,3.0,6.0,6.0,3.0,2.0,52.0,1.0
-ES,660.0,7,6.0,7.0,6.0,0.0,5.0,5.0,4.0,2.0,50.0,1.0
-ES,662.0,7,3.0,4.0,6.0,2.0,7.0,7.0,3.0,1.0,93.0,1.0
-ES,663.0,7,4.0,8.0,6.0,3.0,9.0,7.0,4.0,1.0,65.0,1.0
-ES,665.0,7,5.0,4.0,6.0,1.0,6.0,6.0,2.0,2.0,81.0,1.0
-ES,666.0,7,3.0,3.0,5.0,2.0,5.0,5.0,2.0,1.0,55.0,1.0
-ES,667.0,7,3.0,6.0,6.0,2.0,10.0,5.0,3.0,1.0,63.0,1.0
-ES,670.0,7,4.0,2.0,3.0,3.0,8.0,7.0,4.0,2.0,69.0,1.0
-ES,673.0,7,4.0,6.0,8.0,5.0,7.0,2.0,2.0,1.0,29.0,1.0
-ES,676.0,7,2.0,6.0,7.0,6.0,8.0,5.0,4.0,1.0,32.0,1.0
-ES,678.0,7,7.0,8.0,8.0,7.0,10.0,6.0,2.0,1.0,,1.0
-ES,686.0,7,4.0,9.0,5.0,6.0,10.0,7.0,2.0,2.0,31.0,1.0
-ES,693.0,7,7.0,5.0,6.0,4.0,8.0,6.0,3.0,1.0,57.0,1.0
-ES,695.0,7,4.0,4.0,5.0,5.0,4.0,7.0,3.0,1.0,75.0,1.0
-ES,698.0,7,5.0,4.0,5.0,5.0,10.0,5.0,3.0,2.0,17.0,2.0
-ES,700.0,7,5.0,8.0,5.0,5.0,7.0,4.0,2.0,1.0,50.0,1.0
-ES,701.0,7,0.0,5.0,5.0,5.0,7.0,4.0,5.0,1.0,59.0,2.0
-ES,703.0,7,5.0,8.0,6.0,7.0,10.0,6.0,3.0,1.0,49.0,1.0
-ES,704.0,7,5.0,7.0,3.0,7.0,8.0,7.0,4.0,2.0,58.0,2.0
-ES,705.0,7,6.0,5.0,5.0,2.0,2.0,7.0,3.0,2.0,35.0,2.0
-ES,706.0,7,5.0,7.0,6.0,3.0,7.0,6.0,3.0,1.0,59.0,1.0
-ES,709.0,7,5.0,6.0,7.0,8.0,9.0,4.0,4.0,2.0,73.0,1.0
-ES,710.0,7,4.0,8.0,9.0,8.0,6.0,7.0,1.0,1.0,71.0,2.0
-ES,714.0,7,2.0,0.0,0.0,0.0,4.0,5.0,2.0,2.0,54.0,1.0
-ES,717.0,7,4.0,4.0,6.0,6.0,7.0,6.0,3.0,1.0,60.0,1.0
-ES,721.0,7,6.0,5.0,5.0,5.0,5.0,6.0,2.0,1.0,49.0,2.0
-ES,722.0,7,4.0,7.0,7.0,4.0,9.0,7.0,3.0,1.0,20.0,2.0
-ES,723.0,7,2.0,6.0,5.0,7.0,8.0,7.0,1.0,1.0,63.0,2.0
-ES,726.0,7,7.0,8.0,8.0,5.0,6.0,7.0,3.0,1.0,35.0,1.0
-ES,727.0,7,3.0,6.0,4.0,5.0,7.0,4.0,4.0,2.0,38.0,1.0
-ES,728.0,7,7.0,7.0,8.0,9.0,7.0,5.0,,2.0,63.0,1.0
-ES,729.0,7,7.0,6.0,6.0,7.0,7.0,2.0,2.0,1.0,,1.0
-ES,731.0,7,7.0,8.0,9.0,9.0,9.0,6.0,4.0,2.0,,2.0
-ES,734.0,7,2.0,4.0,4.0,7.0,7.0,5.0,3.0,2.0,52.0,2.0
-ES,742.0,7,2.0,3.0,4.0,3.0,7.0,5.0,3.0,1.0,29.0,1.0
-ES,743.0,7,6.0,5.0,5.0,4.0,9.0,6.0,3.0,1.0,18.0,2.0
-ES,744.0,7,6.0,6.0,7.0,6.0,7.0,7.0,3.0,2.0,58.0,1.0
-ES,746.0,7,6.0,5.0,5.0,8.0,10.0,7.0,1.0,2.0,22.0,2.0
-ES,747.0,7,6.0,8.0,8.0,5.0,2.0,4.0,2.0,2.0,80.0,2.0
-ES,748.0,7,7.0,2.0,5.0,7.0,8.0,5.0,2.0,2.0,82.0,2.0
-ES,751.0,7,6.0,1.0,2.0,4.0,5.0,7.0,2.0,1.0,50.0,1.0
-ES,763.0,7,2.0,1.0,5.0,2.0,8.0,7.0,3.0,2.0,38.0,2.0
-ES,767.0,7,7.0,5.0,2.0,6.0,10.0,6.0,2.0,1.0,49.0,1.0
-ES,768.0,7,2.0,2.0,2.0,7.0,9.0,7.0,1.0,2.0,87.0,2.0
-ES,770.0,7,7.0,0.0,4.0,6.0,7.0,5.0,3.0,2.0,69.0,1.0
-ES,771.0,7,5.0,8.0,8.0,3.0,7.0,5.0,1.0,1.0,38.0,1.0
-ES,778.0,7,5.0,5.0,5.0,5.0,3.0,4.0,3.0,1.0,56.0,2.0
-ES,781.0,7,3.0,8.0,5.0,5.0,5.0,6.0,3.0,2.0,30.0,2.0
-ES,783.0,7,0.0,2.0,2.0,2.0,10.0,5.0,1.0,2.0,46.0,1.0
-ES,788.0,7,5.0,0.0,1.0,4.0,5.0,1.0,,2.0,80.0,1.0
-ES,792.0,7,7.0,7.0,5.0,6.0,10.0,7.0,3.0,2.0,22.0,2.0
-ES,798.0,7,2.0,1.0,7.0,2.0,10.0,4.0,4.0,2.0,45.0,1.0
-ES,799.0,7,6.0,8.0,8.0,8.0,8.0,3.0,4.0,2.0,72.0,1.0
-ES,802.0,7,7.0,5.0,7.0,3.0,10.0,5.0,3.0,1.0,69.0,1.0
-ES,806.0,7,3.0,4.0,7.0,6.0,9.0,7.0,4.0,1.0,30.0,1.0
-ES,807.0,7,2.0,4.0,5.0,5.0,9.0,7.0,4.0,2.0,17.0,2.0
-ES,812.0,7,4.0,0.0,0.0,10.0,8.0,5.0,2.0,2.0,46.0,2.0
-ES,813.0,7,1.0,6.0,6.0,5.0,8.0,4.0,3.0,1.0,41.0,1.0
-ES,814.0,7,7.0,,5.0,5.0,8.0,7.0,1.0,2.0,80.0,2.0
-ES,815.0,7,5.0,5.0,7.0,7.0,8.0,6.0,3.0,1.0,42.0,1.0
-ES,818.0,7,7.0,2.0,8.0,5.0,6.0,7.0,1.0,2.0,73.0,2.0
-ES,821.0,7,5.0,7.0,6.0,3.0,7.0,6.0,3.0,1.0,60.0,1.0
-ES,824.0,7,7.0,3.0,5.0,5.0,10.0,7.0,3.0,2.0,,1.0
-ES,827.0,7,2.0,5.0,5.0,5.0,7.0,6.0,3.0,2.0,36.0,1.0
-ES,833.0,7,7.0,4.0,7.0,3.0,9.0,7.0,3.0,1.0,29.0,2.0
-ES,836.0,7,5.0,3.0,5.0,5.0,8.0,4.0,3.0,2.0,74.0,1.0
-ES,837.0,7,5.0,6.0,7.0,4.0,5.0,7.0,3.0,2.0,26.0,2.0
-ES,842.0,7,4.0,5.0,6.0,5.0,8.0,4.0,2.0,2.0,59.0,1.0
-ES,846.0,7,6.0,5.0,4.0,5.0,7.0,5.0,4.0,1.0,72.0,1.0
-ES,847.0,7,4.0,8.0,6.0,4.0,7.0,6.0,3.0,2.0,49.0,1.0
-ES,851.0,7,4.0,7.0,7.0,2.0,10.0,6.0,2.0,1.0,43.0,1.0
-ES,853.0,7,3.0,8.0,7.0,7.0,8.0,5.0,3.0,1.0,32.0,2.0
-ES,854.0,7,5.0,5.0,3.0,5.0,5.0,4.0,1.0,2.0,76.0,1.0
-ES,855.0,7,2.0,5.0,3.0,5.0,0.0,7.0,3.0,1.0,52.0,2.0
-ES,856.0,7,3.0,3.0,3.0,3.0,6.0,7.0,3.0,2.0,40.0,1.0
-ES,857.0,7,2.0,4.0,5.0,4.0,10.0,7.0,3.0,2.0,22.0,2.0
-ES,858.0,7,4.0,7.0,9.0,0.0,3.0,7.0,3.0,2.0,61.0,2.0
-ES,865.0,7,4.0,5.0,8.0,5.0,6.0,5.0,2.0,2.0,44.0,1.0
-ES,867.0,7,1.0,6.0,6.0,3.0,8.0,5.0,4.0,1.0,20.0,2.0
-ES,872.0,7,6.0,1.0,5.0,2.0,5.0,5.0,2.0,2.0,56.0,1.0
-ES,874.0,7,2.0,7.0,9.0,3.0,7.0,7.0,2.0,1.0,20.0,2.0
-ES,876.0,7,5.0,3.0,5.0,3.0,6.0,5.0,4.0,2.0,47.0,1.0
-ES,879.0,7,4.0,7.0,5.0,5.0,10.0,5.0,3.0,1.0,39.0,1.0
-ES,882.0,7,4.0,5.0,7.0,5.0,7.0,7.0,2.0,2.0,18.0,2.0
-ES,885.0,7,4.0,3.0,3.0,,,6.0,1.0,2.0,,2.0
-ES,886.0,7,4.0,5.0,5.0,5.0,5.0,1.0,3.0,1.0,,1.0
-ES,887.0,7,4.0,5.0,4.0,2.0,10.0,6.0,3.0,2.0,22.0,2.0
-ES,890.0,7,5.0,6.0,6.0,6.0,6.0,5.0,3.0,1.0,61.0,1.0
-ES,892.0,7,6.0,7.0,7.0,8.0,7.0,7.0,3.0,1.0,43.0,1.0
-ES,894.0,7,5.0,6.0,8.0,6.0,6.0,6.0,1.0,2.0,65.0,2.0
-ES,897.0,7,5.0,6.0,6.0,2.0,5.0,6.0,2.0,2.0,33.0,2.0
-ES,898.0,7,5.0,10.0,10.0,7.0,8.0,3.0,1.0,1.0,58.0,1.0
-ES,900.0,7,6.0,6.0,8.0,9.0,9.0,6.0,4.0,2.0,,1.0
-ES,901.0,7,3.0,1.0,2.0,4.0,8.0,5.0,2.0,2.0,43.0,1.0
-ES,903.0,7,4.0,3.0,6.0,4.0,3.0,5.0,1.0,2.0,52.0,1.0
-ES,905.0,7,1.0,8.0,3.0,4.0,5.0,1.0,1.0,2.0,62.0,1.0
-ES,907.0,7,1.0,8.0,5.0,2.0,1.0,3.0,2.0,2.0,50.0,1.0
-ES,909.0,7,7.0,3.0,6.0,3.0,7.0,6.0,1.0,2.0,78.0,1.0
-ES,910.0,7,7.0,4.0,2.0,5.0,6.0,6.0,1.0,1.0,70.0,2.0
-ES,911.0,7,5.0,5.0,5.0,6.0,6.0,6.0,4.0,1.0,45.0,2.0
-ES,913.0,7,3.0,4.0,4.0,1.0,9.0,3.0,3.0,2.0,42.0,1.0
-ES,916.0,7,7.0,2.0,3.0,6.0,10.0,7.0,3.0,1.0,80.0,1.0
-ES,917.0,7,7.0,5.0,5.0,5.0,8.0,4.0,2.0,1.0,80.0,1.0
-ES,918.0,7,0.0,5.0,8.0,7.0,10.0,6.0,3.0,2.0,24.0,2.0
-ES,921.0,7,2.0,4.0,7.0,2.0,7.0,,2.0,2.0,34.0,1.0
-ES,923.0,7,1.0,1.0,9.0,9.0,7.0,7.0,2.0,1.0,41.0,1.0
-ES,924.0,7,2.0,8.0,7.0,3.0,7.0,6.0,1.0,2.0,35.0,2.0
-ES,925.0,7,5.0,6.0,8.0,4.0,7.0,7.0,3.0,1.0,80.0,2.0
-ES,926.0,7,0.0,1.0,2.0,2.0,9.0,6.0,2.0,1.0,45.0,1.0
-ES,927.0,7,0.0,6.0,6.0,5.0,5.0,2.0,1.0,1.0,50.0,1.0
-ES,929.0,7,2.0,8.0,4.0,6.0,6.0,2.0,4.0,1.0,51.0,1.0
-ES,930.0,7,7.0,3.0,4.0,8.0,8.0,2.0,4.0,2.0,60.0,1.0
-ES,932.0,7,7.0,4.0,6.0,8.0,7.0,7.0,2.0,1.0,49.0,2.0
-ES,933.0,7,4.0,6.0,7.0,6.0,9.0,6.0,2.0,1.0,71.0,1.0
-ES,934.0,7,5.0,8.0,1.0,7.0,7.0,7.0,1.0,2.0,86.0,2.0
-ES,935.0,7,4.0,7.0,5.0,7.0,8.0,6.0,3.0,2.0,71.0,2.0
-ES,936.0,7,2.0,7.0,4.0,6.0,9.0,6.0,2.0,1.0,44.0,1.0
-ES,937.0,7,5.0,8.0,8.0,5.0,7.0,6.0,3.0,1.0,53.0,1.0
-ES,940.0,7,2.0,5.0,6.0,6.0,8.0,6.0,3.0,1.0,21.0,2.0
-ES,941.0,7,2.0,3.0,2.0,1.0,5.0,4.0,2.0,2.0,53.0,1.0
-ES,942.0,7,3.0,6.0,6.0,5.0,4.0,4.0,2.0,2.0,45.0,1.0
-ES,943.0,7,4.0,2.0,2.0,3.0,7.0,4.0,3.0,2.0,55.0,1.0
-ES,945.0,7,4.0,5.0,8.0,6.0,8.0,6.0,2.0,2.0,35.0,1.0
-ES,946.0,7,5.0,2.0,2.0,5.0,7.0,7.0,4.0,2.0,17.0,2.0
-ES,947.0,7,1.0,2.0,3.0,3.0,6.0,6.0,3.0,1.0,68.0,1.0
-ES,949.0,7,5.0,6.0,6.0,5.0,8.0,6.0,4.0,2.0,19.0,2.0
-ES,950.0,7,1.0,6.0,9.0,5.0,9.0,5.0,3.0,2.0,17.0,2.0
-ES,951.0,7,2.0,5.0,2.0,5.0,10.0,4.0,3.0,2.0,38.0,1.0
-ES,952.0,7,5.0,2.0,3.0,2.0,7.0,6.0,3.0,2.0,,1.0
-ES,953.0,7,7.0,3.0,5.0,6.0,8.0,7.0,1.0,2.0,57.0,2.0
-ES,954.0,7,6.0,4.0,4.0,3.0,8.0,6.0,4.0,1.0,63.0,1.0
-ES,957.0,7,3.0,5.0,6.0,4.0,7.0,6.0,3.0,1.0,23.0,2.0
-ES,959.0,7,3.0,7.0,8.0,5.0,9.0,6.0,4.0,2.0,22.0,2.0
-ES,961.0,7,2.0,3.0,5.0,1.0,9.0,6.0,1.0,1.0,56.0,1.0
-ES,964.0,7,2.0,6.0,6.0,4.0,10.0,7.0,3.0,1.0,70.0,1.0
-ES,967.0,7,4.0,6.0,7.0,6.0,8.0,6.0,2.0,2.0,45.0,1.0
-ES,970.0,7,2.0,6.0,5.0,6.0,8.0,4.0,1.0,2.0,33.0,1.0
-ES,971.0,7,7.0,4.0,4.0,4.0,9.0,6.0,2.0,2.0,31.0,1.0
-ES,972.0,7,2.0,5.0,3.0,2.0,7.0,2.0,2.0,1.0,37.0,1.0
-ES,973.0,7,0.0,8.0,3.0,0.0,0.0,6.0,1.0,1.0,37.0,1.0
-ES,974.0,7,4.0,5.0,5.0,6.0,7.0,5.0,3.0,2.0,43.0,1.0
-ES,975.0,7,6.0,5.0,7.0,7.0,9.0,6.0,3.0,1.0,69.0,1.0
-ES,976.0,7,2.0,5.0,6.0,7.0,7.0,6.0,3.0,1.0,24.0,2.0
-ES,983.0,7,1.0,5.0,5.0,3.0,7.0,6.0,3.0,1.0,21.0,2.0
-ES,984.0,7,3.0,3.0,5.0,4.0,8.0,7.0,2.0,2.0,41.0,1.0
-ES,987.0,7,4.0,0.0,2.0,7.0,8.0,4.0,2.0,1.0,52.0,1.0
-ES,992.0,7,1.0,8.0,8.0,5.0,8.0,6.0,4.0,2.0,41.0,2.0
-ES,993.0,7,3.0,7.0,7.0,4.0,8.0,6.0,3.0,1.0,23.0,2.0
-ES,994.0,7,1.0,5.0,5.0,3.0,8.0,6.0,3.0,2.0,30.0,1.0
-ES,996.0,7,2.0,8.0,8.0,5.0,8.0,6.0,1.0,1.0,80.0,1.0
-ES,1002.0,7,6.0,4.0,4.0,4.0,10.0,6.0,2.0,1.0,34.0,2.0
-ES,1003.0,7,4.0,6.0,2.0,1.0,8.0,7.0,1.0,2.0,85.0,2.0
-ES,1004.0,7,7.0,1.0,6.0,3.0,7.0,7.0,2.0,1.0,63.0,1.0
-ES,1007.0,7,2.0,7.0,7.0,8.0,9.0,7.0,5.0,2.0,58.0,2.0
-ES,1008.0,7,1.0,7.0,5.0,3.0,10.0,6.0,3.0,1.0,30.0,
-ES,1009.0,7,1.0,2.0,0.0,10.0,8.0,5.0,3.0,1.0,38.0,2.0
-ES,1010.0,7,0.0,1.0,7.0,2.0,8.0,5.0,3.0,1.0,53.0,1.0
-ES,1011.0,7,7.0,5.0,7.0,8.0,8.0,7.0,3.0,1.0,61.0,2.0
-ES,1014.0,7,3.0,6.0,8.0,9.0,9.0,7.0,4.0,1.0,56.0,1.0
-ES,1016.0,7,4.0,3.0,8.0,7.0,8.0,3.0,3.0,2.0,20.0,2.0
-ES,1017.0,7,3.0,7.0,7.0,6.0,1.0,5.0,,1.0,62.0,1.0
-ES,1019.0,7,6.0,5.0,5.0,5.0,7.0,7.0,3.0,1.0,39.0,1.0
-ES,1020.0,7,7.0,4.0,5.0,5.0,5.0,6.0,2.0,1.0,48.0,1.0
-ES,1023.0,7,7.0,3.0,5.0,6.0,7.0,1.0,1.0,1.0,73.0,1.0
-ES,1025.0,7,2.0,8.0,6.0,6.0,6.0,,2.0,2.0,18.0,2.0
-ES,1027.0,7,3.0,5.0,5.0,7.0,8.0,7.0,3.0,1.0,72.0,1.0
-ES,1030.0,7,5.0,6.0,4.0,4.0,8.0,5.0,3.0,2.0,75.0,1.0
-ES,1033.0,7,7.0,2.0,7.0,9.0,9.0,6.0,3.0,2.0,47.0,1.0
-ES,1035.0,7,5.0,7.0,4.0,5.0,10.0,6.0,2.0,2.0,16.0,2.0
-ES,1036.0,7,3.0,1.0,5.0,1.0,7.0,6.0,3.0,2.0,,1.0
-ES,1040.0,7,6.0,7.0,7.0,4.0,9.0,5.0,4.0,2.0,43.0,1.0
-ES,1042.0,7,3.0,3.0,4.0,4.0,7.0,4.0,4.0,2.0,55.0,1.0
-ES,1043.0,7,5.0,5.0,4.0,5.0,5.0,6.0,4.0,2.0,17.0,2.0
-ES,1045.0,7,3.0,6.0,4.0,1.0,10.0,5.0,3.0,2.0,44.0,1.0
-ES,1048.0,7,7.0,5.0,5.0,5.0,10.0,7.0,3.0,2.0,33.0,1.0
-ES,1054.0,7,6.0,5.0,5.0,5.0,5.0,4.0,3.0,1.0,45.0,1.0
-ES,1055.0,7,5.0,4.0,5.0,5.0,7.0,6.0,3.0,1.0,54.0,2.0
-ES,1057.0,7,3.0,3.0,7.0,1.0,9.0,4.0,3.0,1.0,30.0,1.0
-ES,1058.0,7,4.0,1.0,7.0,1.0,10.0,6.0,3.0,2.0,67.0,1.0
-ES,1059.0,7,5.0,2.0,2.0,0.0,3.0,5.0,3.0,2.0,69.0,2.0
-ES,1060.0,7,2.0,5.0,4.0,1.0,9.0,7.0,2.0,2.0,25.0,1.0
-ES,1062.0,7,1.0,5.0,7.0,3.0,9.0,6.0,3.0,2.0,21.0,2.0
-ES,1063.0,7,7.0,10.0,10.0,5.0,8.0,7.0,4.0,1.0,76.0,2.0
-ES,1071.0,7,4.0,5.0,5.0,7.0,6.0,6.0,3.0,1.0,40.0,1.0
-ES,1072.0,7,0.0,6.0,2.0,3.0,8.0,6.0,4.0,2.0,28.0,2.0
-ES,1075.0,7,6.0,8.0,8.0,4.0,7.0,6.0,2.0,2.0,58.0,2.0
-ES,1079.0,7,2.0,8.0,5.0,4.0,7.0,1.0,1.0,2.0,71.0,2.0
-ES,1080.0,7,5.0,5.0,8.0,5.0,8.0,3.0,2.0,2.0,61.0,1.0
-ES,1085.0,7,5.0,3.0,5.0,1.0,4.0,6.0,3.0,2.0,24.0,2.0
-ES,1087.0,7,6.0,3.0,4.0,4.0,5.0,5.0,3.0,1.0,52.0,1.0
-ES,1089.0,7,4.0,3.0,5.0,3.0,8.0,6.0,4.0,2.0,32.0,1.0
-ES,1092.0,7,7.0,5.0,5.0,3.0,6.0,4.0,2.0,1.0,35.0,1.0
-ES,1096.0,7,6.0,8.0,5.0,2.0,4.0,6.0,4.0,2.0,51.0,1.0
-ES,1097.0,7,3.0,6.0,6.0,5.0,7.0,5.0,2.0,2.0,36.0,2.0
-ES,1099.0,7,0.0,8.0,8.0,8.0,8.0,5.0,3.0,1.0,76.0,1.0
-ES,1100.0,7,5.0,6.0,6.0,5.0,8.0,7.0,3.0,2.0,42.0,1.0
-ES,1103.0,7,7.0,1.0,1.0,2.0,10.0,6.0,3.0,2.0,25.0,1.0
-ES,1105.0,7,7.0,3.0,5.0,5.0,7.0,6.0,1.0,2.0,29.0,1.0
-ES,1110.0,7,7.0,2.0,3.0,3.0,5.0,6.0,1.0,2.0,22.0,2.0
-ES,1117.0,7,6.0,4.0,2.0,3.0,8.0,7.0,2.0,1.0,54.0,2.0
-ES,1121.0,7,4.0,4.0,7.0,4.0,9.0,6.0,3.0,2.0,,2.0
-ES,1122.0,7,5.0,7.0,7.0,5.0,8.0,7.0,2.0,2.0,69.0,2.0
-ES,1123.0,7,1.0,7.0,7.0,6.0,8.0,5.0,3.0,1.0,56.0,2.0
-ES,1125.0,7,4.0,4.0,4.0,5.0,6.0,5.0,3.0,1.0,31.0,1.0
-ES,1129.0,7,3.0,6.0,8.0,3.0,8.0,6.0,4.0,1.0,54.0,1.0
-ES,1130.0,7,5.0,2.0,2.0,2.0,3.0,4.0,3.0,2.0,46.0,1.0
-ES,1133.0,7,2.0,3.0,4.0,5.0,6.0,3.0,2.0,1.0,55.0,1.0
-ES,1135.0,7,4.0,7.0,7.0,5.0,8.0,7.0,3.0,1.0,64.0,1.0
-ES,1136.0,7,4.0,3.0,8.0,0.0,10.0,7.0,3.0,1.0,25.0,1.0
-ES,1139.0,7,2.0,6.0,7.0,9.0,8.0,7.0,4.0,1.0,50.0,1.0
-ES,1141.0,7,5.0,4.0,4.0,3.0,7.0,7.0,3.0,1.0,54.0,1.0
-ES,1142.0,7,7.0,1.0,2.0,1.0,8.0,7.0,3.0,2.0,56.0,1.0
-ES,1143.0,7,6.0,1.0,0.0,0.0,10.0,7.0,3.0,1.0,80.0,2.0
-ES,1147.0,7,4.0,4.0,5.0,1.0,9.0,7.0,3.0,2.0,29.0,1.0
-ES,1151.0,7,2.0,5.0,5.0,3.0,7.0,6.0,3.0,2.0,36.0,2.0
-ES,1152.0,7,2.0,0.0,0.0,1.0,9.0,7.0,2.0,1.0,53.0,1.0
-ES,1154.0,7,0.0,5.0,8.0,6.0,9.0,7.0,3.0,2.0,18.0,2.0
-ES,1158.0,7,3.0,7.0,6.0,4.0,7.0,7.0,3.0,2.0,51.0,1.0
-ES,1159.0,7,4.0,0.0,5.0,0.0,5.0,3.0,3.0,2.0,36.0,1.0
-ES,1160.0,7,4.0,5.0,8.0,6.0,8.0,7.0,3.0,2.0,36.0,2.0
-ES,1161.0,7,1.0,6.0,4.0,5.0,6.0,7.0,4.0,1.0,20.0,2.0
-ES,1162.0,7,7.0,5.0,4.0,5.0,3.0,7.0,2.0,2.0,87.0,2.0
-ES,1163.0,7,4.0,7.0,7.0,3.0,8.0,6.0,5.0,1.0,50.0,1.0
-ES,1165.0,7,0.0,7.0,5.0,6.0,10.0,5.0,3.0,1.0,18.0,2.0
-ES,1167.0,7,2.0,6.0,6.0,6.0,7.0,7.0,3.0,1.0,30.0,2.0
-ES,1168.0,7,1.0,8.0,8.0,8.0,9.0,7.0,4.0,1.0,27.0,2.0
-ES,1169.0,7,2.0,6.0,6.0,3.0,2.0,6.0,3.0,2.0,27.0,2.0
-ES,1173.0,7,4.0,9.0,7.0,3.0,4.0,4.0,3.0,2.0,45.0,1.0
-ES,1177.0,7,5.0,7.0,6.0,5.0,9.0,6.0,3.0,1.0,62.0,1.0
-ES,1178.0,7,5.0,8.0,8.0,6.0,7.0,5.0,2.0,2.0,41.0,2.0
-ES,1179.0,7,4.0,7.0,7.0,7.0,9.0,6.0,3.0,1.0,34.0,2.0
-ES,1181.0,7,6.0,8.0,7.0,8.0,9.0,6.0,3.0,2.0,35.0,2.0
-ES,1182.0,7,6.0,9.0,8.0,9.0,10.0,7.0,3.0,2.0,17.0,2.0
-ES,1184.0,7,5.0,5.0,2.0,5.0,8.0,7.0,,1.0,25.0,2.0
-ES,1185.0,7,2.0,2.0,5.0,5.0,7.0,2.0,1.0,1.0,52.0,1.0
-ES,1191.0,7,4.0,7.0,5.0,5.0,8.0,6.0,3.0,1.0,52.0,1.0
-ES,1195.0,7,7.0,5.0,7.0,5.0,6.0,3.0,1.0,1.0,58.0,2.0
-ES,1197.0,7,4.0,6.0,3.0,5.0,8.0,6.0,4.0,2.0,62.0,1.0
-ES,1199.0,7,5.0,5.0,5.0,4.0,8.0,5.0,3.0,1.0,44.0,1.0
-ES,1200.0,7,2.0,4.0,5.0,2.0,6.0,7.0,3.0,1.0,71.0,1.0
-ES,1201.0,7,5.0,2.0,3.0,1.0,7.0,6.0,2.0,1.0,70.0,1.0
-ES,1204.0,7,6.0,4.0,3.0,2.0,7.0,6.0,3.0,1.0,67.0,1.0
-ES,1206.0,7,4.0,5.0,9.0,5.0,6.0,1.0,3.0,2.0,39.0,1.0
-ES,1207.0,7,7.0,7.0,5.0,2.0,8.0,6.0,1.0,2.0,76.0,2.0
-ES,1208.0,7,5.0,5.0,9.0,5.0,7.0,6.0,5.0,1.0,48.0,2.0
-ES,1209.0,7,4.0,5.0,6.0,6.0,8.0,5.0,3.0,2.0,35.0,2.0
-ES,1210.0,7,4.0,4.0,3.0,1.0,7.0,6.0,3.0,2.0,40.0,2.0
-ES,1211.0,7,7.0,7.0,0.0,3.0,5.0,7.0,2.0,2.0,63.0,2.0
-ES,1213.0,7,2.0,6.0,7.0,6.0,8.0,6.0,3.0,2.0,54.0,1.0
-ES,1215.0,7,7.0,4.0,5.0,3.0,7.0,7.0,2.0,2.0,70.0,2.0
-ES,1218.0,7,6.0,2.0,3.0,1.0,5.0,4.0,2.0,2.0,47.0,2.0
-ES,1220.0,7,7.0,6.0,8.0,7.0,9.0,1.0,1.0,2.0,73.0,2.0
-ES,1226.0,7,6.0,2.0,2.0,2.0,7.0,6.0,3.0,1.0,21.0,2.0
-ES,1227.0,7,3.0,7.0,7.0,8.0,9.0,7.0,3.0,2.0,59.0,2.0
-ES,1228.0,7,3.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,23.0,2.0
-ES,1229.0,7,5.0,5.0,5.0,4.0,10.0,7.0,4.0,1.0,75.0,1.0
-ES,1230.0,7,2.0,9.0,10.0,3.0,7.0,4.0,2.0,1.0,33.0,1.0
-ES,1231.0,7,3.0,4.0,7.0,3.0,9.0,6.0,3.0,1.0,53.0,1.0
-ES,1232.0,7,5.0,5.0,8.0,7.0,10.0,2.0,3.0,1.0,40.0,1.0
-ES,1234.0,7,6.0,6.0,6.0,5.0,7.0,6.0,3.0,1.0,59.0,1.0
-ES,1236.0,7,5.0,5.0,5.0,6.0,4.0,5.0,2.0,2.0,31.0,2.0
-ES,1237.0,7,6.0,4.0,4.0,6.0,7.0,4.0,4.0,2.0,57.0,1.0
-ES,1239.0,7,7.0,2.0,2.0,4.0,8.0,6.0,3.0,1.0,30.0,1.0
-ES,1242.0,7,7.0,3.0,7.0,7.0,8.0,6.0,2.0,1.0,75.0,1.0
-ES,1245.0,7,7.0,7.0,4.0,7.0,8.0,6.0,2.0,1.0,55.0,1.0
-ES,1246.0,7,5.0,7.0,7.0,5.0,8.0,6.0,1.0,2.0,57.0,1.0
-ES,1247.0,7,6.0,8.0,1.0,1.0,6.0,5.0,4.0,2.0,55.0,1.0
-ES,1248.0,7,4.0,4.0,7.0,6.0,8.0,7.0,3.0,2.0,33.0,2.0
-ES,1251.0,7,5.0,7.0,1.0,3.0,3.0,7.0,1.0,2.0,57.0,1.0
-ES,1252.0,7,3.0,8.0,6.0,6.0,8.0,6.0,3.0,2.0,36.0,1.0
-ES,1253.0,7,7.0,9.0,9.0,9.0,7.0,7.0,4.0,2.0,76.0,1.0
-ES,1254.0,7,5.0,5.0,5.0,6.0,8.0,6.0,3.0,1.0,20.0,2.0
-ES,1257.0,7,7.0,2.0,4.0,5.0,5.0,2.0,2.0,1.0,81.0,2.0
-ES,1260.0,7,7.0,3.0,3.0,5.0,7.0,2.0,1.0,2.0,40.0,2.0
-ES,1262.0,7,4.0,2.0,2.0,1.0,7.0,2.0,1.0,2.0,52.0,1.0
-ES,1265.0,7,2.0,2.0,1.0,1.0,10.0,5.0,2.0,2.0,24.0,2.0
-ES,1268.0,7,6.0,3.0,3.0,1.0,8.0,6.0,4.0,2.0,68.0,2.0
-ES,1270.0,7,7.0,5.0,1.0,1.0,5.0,7.0,,1.0,45.0,2.0
-ES,1272.0,7,3.0,5.0,6.0,7.0,7.0,3.0,1.0,1.0,51.0,1.0
-ES,1275.0,7,3.0,4.0,5.0,2.0,7.0,6.0,3.0,1.0,39.0,2.0
-ES,1280.0,7,2.0,7.0,7.0,7.0,7.0,7.0,1.0,2.0,61.0,1.0
-ES,1283.0,7,5.0,5.0,8.0,2.0,9.0,5.0,2.0,2.0,59.0,1.0
-ES,1285.0,7,5.0,6.0,6.0,1.0,9.0,5.0,1.0,2.0,42.0,1.0
-ES,1287.0,7,4.0,5.0,2.0,0.0,9.0,7.0,2.0,1.0,50.0,1.0
-ES,1293.0,7,6.0,4.0,2.0,0.0,5.0,1.0,1.0,1.0,56.0,2.0
-ES,1294.0,7,2.0,1.0,5.0,3.0,7.0,6.0,1.0,1.0,34.0,2.0
-ES,1299.0,7,2.0,6.0,3.0,5.0,7.0,2.0,2.0,1.0,53.0,1.0
-ES,1306.0,7,1.0,7.0,6.0,1.0,5.0,7.0,1.0,2.0,22.0,2.0
-ES,1307.0,7,7.0,6.0,6.0,7.0,7.0,4.0,3.0,2.0,65.0,2.0
-ES,1308.0,7,7.0,7.0,5.0,2.0,7.0,6.0,2.0,2.0,65.0,1.0
-ES,1314.0,7,6.0,8.0,8.0,9.0,10.0,6.0,4.0,2.0,79.0,2.0
-ES,1316.0,7,0.0,4.0,6.0,7.0,8.0,5.0,3.0,2.0,37.0,1.0
-ES,1318.0,7,4.0,5.0,5.0,4.0,5.0,6.0,1.0,2.0,68.0,1.0
-ES,1319.0,7,2.0,5.0,5.0,8.0,7.0,4.0,4.0,2.0,41.0,1.0
-ES,1320.0,7,7.0,3.0,5.0,3.0,8.0,2.0,2.0,1.0,72.0,1.0
-ES,1324.0,7,4.0,8.0,7.0,5.0,9.0,6.0,2.0,1.0,46.0,2.0
-ES,1325.0,7,2.0,5.0,2.0,4.0,6.0,5.0,4.0,1.0,39.0,2.0
-ES,1326.0,7,3.0,6.0,6.0,5.0,8.0,6.0,3.0,1.0,70.0,1.0
-ES,1331.0,7,5.0,7.0,7.0,7.0,7.0,6.0,3.0,2.0,44.0,2.0
-ES,1333.0,7,2.0,5.0,5.0,5.0,7.0,4.0,3.0,2.0,50.0,1.0
-ES,1335.0,7,6.0,5.0,5.0,2.0,8.0,5.0,1.0,1.0,80.0,1.0
-ES,1336.0,7,2.0,1.0,4.0,1.0,5.0,6.0,1.0,1.0,65.0,1.0
-ES,1340.0,7,1.0,9.0,8.0,7.0,7.0,3.0,1.0,2.0,75.0,1.0
-ES,1342.0,7,6.0,3.0,5.0,4.0,7.0,5.0,3.0,1.0,30.0,2.0
-ES,1345.0,7,3.0,5.0,5.0,5.0,10.0,4.0,3.0,1.0,26.0,1.0
-ES,1348.0,7,2.0,8.0,8.0,6.0,8.0,5.0,2.0,2.0,48.0,1.0
-ES,1350.0,7,4.0,5.0,8.0,8.0,7.0,6.0,3.0,1.0,17.0,2.0
-ES,1351.0,7,3.0,9.0,10.0,6.0,10.0,7.0,1.0,1.0,17.0,2.0
-ES,1352.0,7,2.0,1.0,5.0,1.0,9.0,4.0,2.0,1.0,45.0,1.0
-ES,1353.0,7,2.0,5.0,5.0,3.0,9.0,4.0,2.0,2.0,43.0,1.0
-ES,1354.0,7,7.0,4.0,2.0,1.0,10.0,6.0,2.0,2.0,80.0,2.0
-ES,1355.0,7,2.0,8.0,5.0,5.0,8.0,5.0,2.0,2.0,43.0,1.0
-ES,1356.0,7,2.0,5.0,5.0,3.0,5.0,5.0,2.0,2.0,46.0,1.0
-ES,1358.0,7,1.0,2.0,5.0,6.0,9.0,7.0,3.0,1.0,79.0,1.0
-ES,1361.0,7,3.0,3.0,4.0,4.0,7.0,6.0,2.0,1.0,29.0,2.0
-ES,1363.0,7,5.0,2.0,4.0,2.0,5.0,5.0,1.0,1.0,57.0,1.0
-ES,1364.0,7,5.0,5.0,6.0,5.0,7.0,5.0,3.0,1.0,69.0,1.0
-ES,1365.0,7,6.0,5.0,5.0,3.0,2.0,2.0,1.0,1.0,87.0,1.0
-ES,1366.0,7,1.0,6.0,7.0,6.0,8.0,6.0,3.0,2.0,28.0,2.0
-ES,1367.0,7,6.0,7.0,7.0,7.0,8.0,5.0,3.0,2.0,39.0,1.0
-ES,1374.0,7,3.0,8.0,5.0,3.0,7.0,6.0,2.0,2.0,48.0,1.0
-ES,1379.0,7,6.0,8.0,5.0,3.0,8.0,3.0,3.0,1.0,52.0,1.0
-ES,1380.0,7,4.0,7.0,0.0,6.0,8.0,3.0,1.0,2.0,49.0,1.0
-ES,1381.0,7,5.0,3.0,3.0,3.0,9.0,5.0,1.0,2.0,36.0,2.0
-ES,1382.0,7,4.0,0.0,5.0,7.0,5.0,5.0,1.0,2.0,,2.0
-ES,1383.0,7,2.0,5.0,5.0,2.0,8.0,6.0,2.0,1.0,49.0,1.0
-ES,1384.0,7,2.0,5.0,5.0,7.0,8.0,4.0,3.0,1.0,70.0,1.0
-ES,1388.0,7,7.0,5.0,5.0,7.0,5.0,6.0,3.0,2.0,27.0,2.0
-ES,1393.0,7,7.0,8.0,7.0,8.0,7.0,4.0,3.0,2.0,70.0,1.0
-ES,1395.0,7,2.0,4.0,5.0,4.0,8.0,5.0,3.0,2.0,59.0,1.0
-ES,1396.0,7,3.0,8.0,6.0,6.0,8.0,6.0,3.0,1.0,34.0,2.0
-ES,1402.0,7,6.0,8.0,8.0,5.0,10.0,7.0,2.0,1.0,58.0,1.0
-ES,1405.0,7,6.0,7.0,6.0,5.0,5.0,7.0,3.0,1.0,67.0,1.0
-ES,1406.0,7,7.0,7.0,7.0,3.0,7.0,4.0,2.0,1.0,58.0,1.0
-ES,1407.0,7,4.0,5.0,5.0,4.0,7.0,4.0,3.0,2.0,40.0,1.0
-ES,1408.0,7,3.0,8.0,5.0,5.0,7.0,7.0,4.0,2.0,87.0,1.0
-ES,1414.0,7,2.0,8.0,5.0,2.0,8.0,6.0,2.0,2.0,22.0,2.0
-ES,1418.0,7,4.0,1.0,2.0,2.0,5.0,5.0,2.0,1.0,52.0,2.0
-ES,1420.0,7,6.0,7.0,6.0,8.0,8.0,5.0,3.0,1.0,40.0,1.0
-ES,1424.0,7,2.0,4.0,2.0,2.0,5.0,6.0,2.0,1.0,63.0,1.0
-ES,1426.0,7,4.0,4.0,4.0,3.0,1.0,5.0,1.0,2.0,62.0,2.0
-ES,1427.0,7,3.0,5.0,5.0,7.0,8.0,7.0,3.0,2.0,17.0,2.0
-ES,1428.0,7,1.0,3.0,3.0,5.0,9.0,5.0,1.0,1.0,24.0,2.0
-ES,1430.0,7,7.0,7.0,7.0,6.0,9.0,6.0,2.0,2.0,32.0,1.0
-ES,1431.0,7,2.0,6.0,7.0,6.0,8.0,5.0,3.0,2.0,45.0,2.0
-ES,1433.0,7,6.0,4.0,5.0,4.0,4.0,5.0,2.0,2.0,54.0,1.0
-ES,1434.0,7,2.0,5.0,5.0,0.0,5.0,5.0,3.0,1.0,45.0,1.0
-ES,1435.0,7,3.0,6.0,6.0,6.0,6.0,4.0,3.0,1.0,59.0,1.0
-ES,1438.0,7,6.0,5.0,7.0,4.0,6.0,4.0,2.0,1.0,68.0,1.0
-ES,1440.0,7,5.0,3.0,5.0,3.0,7.0,5.0,1.0,2.0,33.0,1.0
-ES,1442.0,7,0.0,5.0,0.0,10.0,8.0,4.0,2.0,2.0,50.0,1.0
-ES,1445.0,7,2.0,6.0,5.0,7.0,7.0,6.0,3.0,1.0,63.0,1.0
-ES,1446.0,7,7.0,3.0,4.0,6.0,6.0,6.0,3.0,2.0,34.0,2.0
-ES,1447.0,7,3.0,6.0,8.0,8.0,9.0,4.0,2.0,2.0,24.0,2.0
-ES,1448.0,7,4.0,7.0,7.0,7.0,8.0,3.0,2.0,2.0,60.0,1.0
-ES,1450.0,7,2.0,7.0,9.0,4.0,7.0,3.0,2.0,2.0,47.0,1.0
-ES,1452.0,7,5.0,6.0,7.0,7.0,8.0,6.0,3.0,1.0,46.0,1.0
-ES,1453.0,7,1.0,4.0,3.0,3.0,7.0,7.0,2.0,1.0,18.0,2.0
-ES,1456.0,7,4.0,6.0,5.0,3.0,8.0,4.0,3.0,2.0,39.0,1.0
-ES,1457.0,7,5.0,7.0,6.0,6.0,6.0,4.0,3.0,1.0,42.0,1.0
-ES,1462.0,7,7.0,8.0,2.0,6.0,8.0,4.0,3.0,1.0,90.0,1.0
-ES,1463.0,7,7.0,5.0,2.0,2.0,7.0,3.0,3.0,1.0,67.0,1.0
-ES,1464.0,7,3.0,7.0,8.0,3.0,7.0,7.0,5.0,1.0,28.0,2.0
-ES,1466.0,7,5.0,5.0,5.0,10.0,10.0,5.0,2.0,2.0,25.0,2.0
-ES,1467.0,7,1.0,7.0,4.0,0.0,10.0,5.0,2.0,1.0,48.0,1.0
-ES,1468.0,7,4.0,5.0,6.0,2.0,8.0,5.0,2.0,2.0,31.0,2.0
-ES,1471.0,7,6.0,5.0,5.0,2.0,6.0,5.0,4.0,2.0,82.0,2.0
-ES,1473.0,7,4.0,6.0,4.0,7.0,9.0,6.0,3.0,2.0,32.0,1.0
-ES,1474.0,7,4.0,5.0,,0.0,0.0,1.0,1.0,1.0,85.0,2.0
-ES,1478.0,7,6.0,7.0,7.0,5.0,10.0,6.0,3.0,2.0,49.0,1.0
-ES,1479.0,7,7.0,3.0,5.0,7.0,5.0,6.0,4.0,1.0,76.0,1.0
-ES,1480.0,7,5.0,4.0,5.0,9.0,10.0,6.0,3.0,2.0,79.0,1.0
-ES,1482.0,7,7.0,2.0,9.0,2.0,8.0,7.0,,1.0,61.0,1.0
-ES,1486.0,7,3.0,7.0,7.0,6.0,9.0,5.0,3.0,1.0,28.0,1.0
-ES,1489.0,7,2.0,7.0,8.0,2.0,8.0,4.0,3.0,1.0,68.0,1.0
-ES,1491.0,7,4.0,5.0,6.0,3.0,9.0,5.0,3.0,2.0,57.0,1.0
-ES,1495.0,7,5.0,5.0,6.0,4.0,8.0,6.0,4.0,2.0,27.0,1.0
-ES,1496.0,7,6.0,4.0,2.0,9.0,5.0,7.0,3.0,2.0,21.0,2.0
-ES,1498.0,7,2.0,5.0,7.0,7.0,7.0,2.0,3.0,2.0,49.0,2.0
-ES,1500.0,7,3.0,2.0,3.0,3.0,7.0,3.0,2.0,2.0,52.0,2.0
-ES,1501.0,7,2.0,3.0,6.0,6.0,9.0,7.0,4.0,2.0,23.0,2.0
-ES,1512.0,7,1.0,9.0,8.0,8.0,10.0,7.0,4.0,1.0,70.0,1.0
-ES,1513.0,7,5.0,7.0,5.0,3.0,7.0,4.0,4.0,2.0,62.0,2.0
-ES,1516.0,7,7.0,8.0,5.0,2.0,6.0,7.0,,1.0,81.0,1.0
-ES,1517.0,7,7.0,5.0,5.0,5.0,10.0,2.0,3.0,2.0,72.0,1.0
-ES,1518.0,7,1.0,6.0,5.0,7.0,10.0,3.0,3.0,1.0,31.0,1.0
-ES,1528.0,7,2.0,4.0,8.0,3.0,7.0,6.0,3.0,2.0,20.0,2.0
-ES,1529.0,7,2.0,5.0,5.0,6.0,6.0,5.0,2.0,2.0,46.0,2.0
-ES,1530.0,7,7.0,5.0,,6.0,9.0,2.0,1.0,2.0,84.0,1.0
-ES,1533.0,7,2.0,8.0,8.0,7.0,10.0,6.0,4.0,2.0,26.0,2.0
-ES,1534.0,7,4.0,4.0,3.0,6.0,8.0,7.0,3.0,1.0,,1.0
-ES,1535.0,7,7.0,7.0,5.0,3.0,7.0,6.0,1.0,2.0,,1.0
-ES,1536.0,7,5.0,0.0,0.0,7.0,10.0,5.0,1.0,2.0,76.0,1.0
-ES,1538.0,7,7.0,9.0,9.0,9.0,9.0,7.0,2.0,2.0,89.0,2.0
-ES,1539.0,7,3.0,6.0,5.0,6.0,8.0,7.0,2.0,1.0,28.0,2.0
-ES,1542.0,7,5.0,7.0,5.0,5.0,8.0,6.0,3.0,1.0,25.0,2.0
-ES,1546.0,7,3.0,7.0,7.0,6.0,7.0,6.0,3.0,2.0,101.0,2.0
-ES,1548.0,7,6.0,6.0,7.0,5.0,8.0,5.0,3.0,2.0,47.0,1.0
-ES,1551.0,7,2.0,6.0,6.0,3.0,7.0,6.0,3.0,2.0,29.0,1.0
-ES,1552.0,7,2.0,8.0,6.0,5.0,7.0,5.0,3.0,2.0,46.0,1.0
-ES,1553.0,7,2.0,5.0,5.0,8.0,9.0,7.0,4.0,2.0,45.0,1.0
-ES,1557.0,7,0.0,0.0,2.0,1.0,10.0,3.0,1.0,2.0,50.0,1.0
-ES,1566.0,7,7.0,8.0,5.0,5.0,8.0,5.0,3.0,2.0,,1.0
-ES,1570.0,7,7.0,7.0,8.0,4.0,7.0,6.0,3.0,1.0,71.0,1.0
-ES,1571.0,7,5.0,7.0,7.0,8.0,9.0,4.0,2.0,2.0,21.0,2.0
-ES,1574.0,7,7.0,6.0,5.0,6.0,6.0,6.0,,1.0,43.0,2.0
-ES,1576.0,7,3.0,3.0,0.0,0.0,5.0,4.0,1.0,2.0,37.0,2.0
-ES,1577.0,7,7.0,6.0,7.0,8.0,10.0,6.0,3.0,2.0,65.0,1.0
-ES,1578.0,7,5.0,5.0,5.0,5.0,5.0,5.0,3.0,1.0,65.0,1.0
-ES,1579.0,7,2.0,6.0,6.0,6.0,5.0,4.0,2.0,1.0,59.0,2.0
-ES,1581.0,7,2.0,0.0,0.0,0.0,2.0,5.0,3.0,2.0,64.0,1.0
-ES,1585.0,7,4.0,4.0,4.0,3.0,8.0,6.0,3.0,2.0,19.0,2.0
-ES,1591.0,7,3.0,4.0,4.0,4.0,2.0,4.0,4.0,1.0,42.0,2.0
-ES,1595.0,7,4.0,5.0,7.0,3.0,5.0,7.0,3.0,2.0,57.0,1.0
-ES,1598.0,7,7.0,2.0,2.0,2.0,7.0,4.0,2.0,2.0,69.0,1.0
-ES,1604.0,7,4.0,4.0,6.0,4.0,6.0,6.0,3.0,1.0,64.0,2.0
-ES,1608.0,7,5.0,0.0,0.0,0.0,7.0,6.0,1.0,2.0,55.0,1.0
-ES,1609.0,7,5.0,5.0,6.0,3.0,5.0,4.0,2.0,1.0,30.0,2.0
-ES,1610.0,7,7.0,7.0,7.0,7.0,7.0,5.0,2.0,1.0,62.0,1.0
-ES,1612.0,7,2.0,3.0,7.0,5.0,8.0,5.0,,1.0,86.0,1.0
-ES,1621.0,7,2.0,3.0,5.0,2.0,6.0,6.0,1.0,1.0,59.0,1.0
-ES,1622.0,7,3.0,4.0,3.0,4.0,1.0,4.0,1.0,1.0,62.0,2.0
-ES,1623.0,7,5.0,7.0,4.0,5.0,6.0,3.0,2.0,1.0,63.0,1.0
-ES,1628.0,7,7.0,2.0,1.0,3.0,5.0,5.0,3.0,2.0,76.0,2.0
-ES,1629.0,7,2.0,6.0,6.0,6.0,7.0,3.0,4.0,1.0,56.0,1.0
-ES,1631.0,7,5.0,7.0,7.0,6.0,9.0,5.0,4.0,1.0,75.0,2.0
-ES,1635.0,7,1.0,3.0,5.0,2.0,5.0,3.0,2.0,2.0,42.0,1.0
-ES,1638.0,7,3.0,6.0,7.0,4.0,8.0,6.0,3.0,1.0,53.0,1.0
-ES,1640.0,7,6.0,5.0,5.0,5.0,5.0,4.0,3.0,1.0,43.0,1.0
-ES,1641.0,7,3.0,7.0,7.0,6.0,7.0,3.0,3.0,1.0,51.0,1.0
-ES,1642.0,7,3.0,7.0,8.0,6.0,8.0,5.0,3.0,1.0,35.0,1.0
-ES,1645.0,7,3.0,5.0,8.0,8.0,7.0,7.0,1.0,2.0,70.0,2.0
-ES,1647.0,7,7.0,2.0,2.0,3.0,10.0,6.0,1.0,1.0,69.0,1.0
-ES,1648.0,7,3.0,3.0,3.0,3.0,8.0,6.0,1.0,1.0,47.0,1.0
-ES,1653.0,7,3.0,5.0,7.0,5.0,6.0,6.0,3.0,2.0,49.0,2.0
-ES,1654.0,7,2.0,7.0,5.0,7.0,8.0,4.0,4.0,1.0,18.0,2.0
-ES,1656.0,7,4.0,5.0,7.0,5.0,8.0,6.0,4.0,2.0,41.0,1.0
-ES,1657.0,7,5.0,7.0,6.0,6.0,7.0,5.0,4.0,2.0,34.0,1.0
-ES,1658.0,7,4.0,5.0,5.0,6.0,9.0,4.0,3.0,2.0,42.0,1.0
-ES,1659.0,7,1.0,6.0,5.0,4.0,6.0,6.0,4.0,1.0,18.0,2.0
-ES,1660.0,7,7.0,8.0,3.0,3.0,7.0,7.0,3.0,1.0,60.0,1.0
-ES,1663.0,7,4.0,2.0,5.0,3.0,7.0,4.0,3.0,2.0,38.0,2.0
-ES,1666.0,7,7.0,8.0,7.0,7.0,7.0,5.0,3.0,1.0,46.0,1.0
-ES,1667.0,7,6.0,6.0,5.0,4.0,7.0,4.0,5.0,1.0,69.0,1.0
-ES,1669.0,7,6.0,3.0,2.0,3.0,8.0,7.0,2.0,1.0,75.0,1.0
-ES,1671.0,7,1.0,3.0,3.0,2.0,5.0,7.0,2.0,1.0,23.0,2.0
-ES,1672.0,7,3.0,2.0,9.0,0.0,10.0,6.0,5.0,1.0,23.0,2.0
-ES,1673.0,7,5.0,6.0,7.0,5.0,8.0,6.0,2.0,1.0,75.0,1.0
-ES,1678.0,7,7.0,0.0,3.0,3.0,7.0,5.0,1.0,2.0,90.0,1.0
-ES,1680.0,7,2.0,6.0,2.0,3.0,8.0,5.0,3.0,1.0,20.0,2.0
-ES,1683.0,7,2.0,5.0,5.0,4.0,8.0,5.0,2.0,2.0,35.0,1.0
-ES,1685.0,7,4.0,7.0,7.0,5.0,7.0,6.0,2.0,1.0,33.0,2.0
-ES,1686.0,7,6.0,2.0,,2.0,8.0,5.0,3.0,2.0,37.0,1.0
-ES,1688.0,7,7.0,2.0,3.0,3.0,4.0,5.0,2.0,2.0,43.0,2.0
-ES,1689.0,7,5.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,24.0,2.0
-ES,1693.0,7,7.0,8.0,8.0,5.0,7.0,5.0,3.0,1.0,40.0,1.0
-ES,1694.0,7,7.0,5.0,5.0,7.0,8.0,4.0,3.0,1.0,40.0,1.0
-ES,1701.0,7,1.0,6.0,6.0,7.0,6.0,3.0,4.0,1.0,27.0,2.0
-ES,1706.0,7,4.0,5.0,5.0,5.0,8.0,4.0,,2.0,54.0,1.0
-ES,1713.0,7,5.0,6.0,6.0,7.0,8.0,4.0,2.0,2.0,17.0,2.0
-ES,1715.0,7,4.0,5.0,4.0,5.0,10.0,6.0,3.0,2.0,85.0,1.0
-ES,1719.0,7,2.0,6.0,6.0,7.0,7.0,6.0,3.0,1.0,18.0,2.0
-ES,1722.0,7,7.0,6.0,7.0,5.0,8.0,6.0,3.0,2.0,19.0,2.0
-ES,1726.0,7,4.0,7.0,6.0,3.0,8.0,5.0,2.0,1.0,34.0,1.0
-ES,1727.0,7,3.0,7.0,5.0,5.0,8.0,3.0,3.0,1.0,42.0,1.0
-ES,1729.0,7,3.0,3.0,2.0,3.0,8.0,4.0,3.0,1.0,51.0,1.0
-ES,1730.0,7,1.0,7.0,6.0,6.0,7.0,4.0,4.0,2.0,37.0,1.0
-ES,1732.0,7,2.0,8.0,8.0,5.0,6.0,4.0,2.0,1.0,26.0,2.0
-ES,1735.0,7,5.0,3.0,7.0,6.0,9.0,7.0,2.0,1.0,42.0,1.0
-ES,1737.0,7,2.0,5.0,5.0,5.0,10.0,7.0,3.0,2.0,29.0,2.0
-ES,1738.0,7,6.0,5.0,2.0,5.0,5.0,7.0,2.0,1.0,67.0,1.0
-ES,1740.0,7,3.0,2.0,4.0,4.0,6.0,6.0,1.0,1.0,32.0,2.0
-ES,1742.0,7,7.0,1.0,0.0,0.0,10.0,6.0,2.0,1.0,79.0,1.0
-ES,1744.0,7,7.0,0.0,5.0,6.0,5.0,7.0,2.0,2.0,75.0,2.0
-ES,1746.0,7,4.0,7.0,5.0,6.0,9.0,6.0,3.0,1.0,22.0,2.0
-ES,1747.0,7,2.0,2.0,1.0,1.0,8.0,5.0,2.0,2.0,39.0,1.0
-ES,1750.0,7,2.0,5.0,4.0,7.0,10.0,6.0,3.0,2.0,39.0,2.0
-ES,1751.0,7,7.0,5.0,10.0,10.0,7.0,4.0,2.0,2.0,44.0,1.0
-ES,1752.0,7,6.0,3.0,7.0,0.0,5.0,1.0,1.0,1.0,58.0,1.0
-ES,1753.0,7,3.0,6.0,7.0,5.0,5.0,7.0,2.0,1.0,41.0,2.0
-ES,1761.0,7,7.0,2.0,2.0,1.0,8.0,4.0,2.0,2.0,41.0,1.0
-ES,1763.0,7,7.0,1.0,3.0,2.0,6.0,5.0,2.0,2.0,32.0,1.0
-ES,1764.0,7,5.0,6.0,3.0,3.0,7.0,5.0,3.0,1.0,39.0,1.0
-ES,1765.0,7,0.0,5.0,4.0,3.0,8.0,7.0,3.0,1.0,23.0,2.0
-ES,1766.0,7,7.0,9.0,6.0,4.0,7.0,5.0,1.0,1.0,39.0,2.0
-ES,1769.0,7,3.0,7.0,6.0,5.0,9.0,5.0,3.0,1.0,17.0,2.0
-ES,1771.0,7,4.0,7.0,7.0,5.0,8.0,5.0,3.0,1.0,53.0,1.0
-ES,1776.0,7,3.0,5.0,6.0,9.0,9.0,4.0,2.0,1.0,42.0,1.0
-ES,1781.0,7,5.0,3.0,4.0,2.0,9.0,6.0,2.0,2.0,46.0,1.0
-ES,1782.0,7,7.0,5.0,3.0,7.0,5.0,7.0,4.0,1.0,68.0,2.0
-ES,1784.0,7,7.0,6.0,2.0,5.0,9.0,7.0,2.0,2.0,82.0,1.0
-ES,1790.0,7,5.0,6.0,8.0,3.0,7.0,4.0,2.0,1.0,56.0,1.0
-ES,1792.0,7,3.0,1.0,4.0,4.0,8.0,7.0,2.0,2.0,35.0,1.0
-ES,1797.0,7,5.0,4.0,6.0,7.0,9.0,5.0,3.0,1.0,36.0,1.0
-ES,1799.0,7,2.0,4.0,7.0,6.0,8.0,2.0,1.0,2.0,35.0,1.0
-ES,1807.0,7,5.0,2.0,5.0,7.0,5.0,1.0,1.0,2.0,51.0,1.0
-ES,1812.0,7,5.0,4.0,5.0,2.0,8.0,6.0,2.0,2.0,64.0,2.0
-ES,1813.0,7,7.0,2.0,1.0,5.0,5.0,5.0,1.0,2.0,90.0,2.0
-ES,1814.0,7,5.0,7.0,0.0,0.0,8.0,4.0,4.0,2.0,35.0,1.0
-ES,1817.0,7,7.0,6.0,5.0,7.0,7.0,5.0,3.0,2.0,75.0,1.0
-ES,1820.0,7,7.0,4.0,5.0,3.0,10.0,7.0,3.0,1.0,21.0,2.0
-ES,1821.0,7,2.0,5.0,5.0,10.0,8.0,6.0,3.0,2.0,23.0,2.0
-ES,1829.0,7,0.0,7.0,8.0,4.0,9.0,6.0,4.0,1.0,43.0,1.0
-ES,1832.0,7,6.0,5.0,7.0,5.0,8.0,4.0,4.0,2.0,43.0,1.0
-ES,1835.0,7,5.0,2.0,3.0,2.0,8.0,1.0,2.0,1.0,73.0,1.0
-ES,1837.0,7,7.0,8.0,6.0,4.0,9.0,3.0,2.0,1.0,64.0,1.0
-ES,1838.0,7,5.0,3.0,7.0,8.0,5.0,6.0,3.0,1.0,42.0,2.0
-ES,1839.0,7,7.0,5.0,5.0,4.0,10.0,4.0,3.0,1.0,64.0,1.0
-ES,1840.0,7,2.0,5.0,6.0,2.0,8.0,4.0,2.0,1.0,61.0,1.0
-ES,1849.0,7,7.0,5.0,5.0,5.0,8.0,4.0,3.0,1.0,41.0,1.0
-ES,1853.0,7,7.0,3.0,4.0,4.0,8.0,4.0,3.0,1.0,42.0,1.0
-ES,1856.0,7,3.0,3.0,3.0,2.0,8.0,6.0,3.0,1.0,51.0,1.0
-ES,1861.0,7,7.0,5.0,5.0,4.0,8.0,6.0,3.0,1.0,63.0,1.0
-ES,1862.0,7,7.0,6.0,7.0,2.0,10.0,3.0,3.0,1.0,49.0,1.0
-ES,1863.0,7,2.0,5.0,6.0,6.0,9.0,5.0,3.0,2.0,38.0,1.0
-ES,1866.0,7,2.0,6.0,7.0,4.0,7.0,6.0,2.0,2.0,44.0,2.0
-ES,1867.0,7,5.0,2.0,2.0,2.0,8.0,4.0,3.0,2.0,39.0,1.0
-ES,1868.0,7,5.0,2.0,8.0,2.0,9.0,7.0,3.0,2.0,27.0,1.0
-ES,1869.0,7,2.0,8.0,8.0,5.0,8.0,5.0,3.0,1.0,42.0,1.0
-ES,1870.0,7,7.0,5.0,1.0,1.0,1.0,2.0,1.0,2.0,20.0,2.0
-ES,1875.0,7,7.0,5.0,7.0,1.0,9.0,5.0,3.0,1.0,28.0,2.0
-ES,1877.0,7,6.0,3.0,5.0,8.0,10.0,7.0,3.0,1.0,16.0,2.0
-ES,1878.0,7,6.0,5.0,0.0,4.0,2.0,5.0,2.0,2.0,54.0,2.0
-ES,1879.0,7,4.0,5.0,0.0,5.0,5.0,5.0,2.0,1.0,46.0,1.0
-ES,1881.0,7,5.0,6.0,6.0,3.0,8.0,7.0,3.0,1.0,47.0,1.0
-ES,1887.0,7,6.0,1.0,0.0,0.0,0.0,6.0,2.0,1.0,74.0,1.0
-ES,1888.0,7,5.0,2.0,3.0,0.0,0.0,7.0,1.0,2.0,82.0,2.0
-ES,1889.0,7,4.0,5.0,5.0,0.0,7.0,7.0,2.0,1.0,18.0,2.0
-ES,1891.0,7,3.0,7.0,8.0,5.0,9.0,3.0,3.0,1.0,57.0,1.0
-ES,1892.0,7,3.0,7.0,3.0,3.0,7.0,5.0,3.0,1.0,16.0,2.0
-ES,1893.0,7,3.0,5.0,0.0,5.0,10.0,7.0,3.0,2.0,45.0,1.0
-ES,1894.0,7,7.0,6.0,7.0,4.0,8.0,7.0,2.0,1.0,29.0,2.0
-ES,1898.0,7,5.0,4.0,5.0,6.0,8.0,7.0,2.0,2.0,82.0,1.0
-ES,1899.0,7,7.0,8.0,8.0,7.0,3.0,7.0,3.0,1.0,83.0,1.0
-ES,1901.0,7,7.0,3.0,7.0,2.0,5.0,6.0,3.0,2.0,73.0,1.0
-ES,1903.0,7,1.0,4.0,3.0,2.0,9.0,6.0,4.0,1.0,17.0,2.0
-ES,1904.0,7,4.0,5.0,6.0,6.0,8.0,6.0,2.0,2.0,29.0,1.0
-ES,1905.0,7,1.0,5.0,4.0,3.0,8.0,6.0,3.0,2.0,19.0,2.0
-ES,1906.0,7,4.0,5.0,7.0,5.0,8.0,4.0,3.0,1.0,50.0,1.0
-ES,1908.0,7,5.0,2.0,5.0,2.0,8.0,2.0,1.0,1.0,61.0,1.0
-ES,1921.0,7,1.0,,4.0,4.0,7.0,6.0,3.0,2.0,33.0,2.0
-ES,1922.0,7,2.0,6.0,7.0,5.0,10.0,5.0,2.0,2.0,48.0,1.0
-ES,1928.0,7,3.0,3.0,8.0,6.0,8.0,6.0,2.0,2.0,40.0,1.0
-ES,1929.0,7,7.0,5.0,4.0,5.0,9.0,6.0,3.0,1.0,,2.0
-ES,1930.0,7,3.0,0.0,5.0,0.0,5.0,4.0,2.0,1.0,38.0,1.0
-ES,1931.0,7,3.0,7.0,0.0,6.0,10.0,5.0,4.0,1.0,32.0,1.0
-ES,1932.0,7,7.0,5.0,6.0,7.0,9.0,6.0,1.0,2.0,42.0,1.0
-ES,1933.0,7,7.0,5.0,7.0,0.0,6.0,7.0,,2.0,,2.0
-ES,1934.0,7,3.0,8.0,8.0,3.0,9.0,7.0,4.0,2.0,55.0,2.0
-ES,1935.0,7,7.0,7.0,7.0,3.0,9.0,5.0,1.0,2.0,89.0,2.0
-ES,1936.0,7,4.0,6.0,6.0,3.0,9.0,5.0,5.0,1.0,52.0,1.0
-ES,1940.0,7,2.0,3.0,4.0,4.0,7.0,5.0,4.0,2.0,46.0,2.0
-ES,1944.0,7,3.0,5.0,7.0,8.0,10.0,6.0,3.0,1.0,35.0,1.0
-ES,1946.0,7,7.0,5.0,5.0,7.0,9.0,6.0,3.0,1.0,64.0,1.0
-ES,1949.0,7,5.0,2.0,2.0,5.0,8.0,2.0,1.0,1.0,44.0,1.0
-ES,1954.0,7,7.0,5.0,,3.0,7.0,7.0,3.0,1.0,79.0,2.0
-ES,1955.0,7,4.0,2.0,2.0,1.0,8.0,5.0,3.0,1.0,51.0,1.0
-ES,1957.0,7,2.0,2.0,2.0,2.0,8.0,5.0,2.0,1.0,23.0,2.0
-ES,1961.0,7,5.0,2.0,5.0,4.0,10.0,5.0,3.0,2.0,52.0,1.0
-ES,1962.0,7,4.0,1.0,5.0,6.0,6.0,6.0,1.0,1.0,78.0,2.0
-ES,1968.0,7,7.0,7.0,5.0,7.0,10.0,7.0,2.0,1.0,24.0,2.0
-ES,1969.0,7,5.0,8.0,5.0,2.0,10.0,5.0,3.0,2.0,51.0,1.0
-ES,1971.0,7,4.0,8.0,6.0,6.0,9.0,6.0,3.0,1.0,33.0,1.0
-ES,1972.0,7,2.0,1.0,1.0,1.0,8.0,6.0,2.0,1.0,71.0,1.0
-ES,1973.0,7,6.0,5.0,7.0,3.0,10.0,6.0,3.0,1.0,24.0,2.0
-ES,1979.0,7,3.0,6.0,6.0,2.0,9.0,7.0,2.0,1.0,20.0,2.0
-ES,1981.0,7,4.0,3.0,5.0,6.0,9.0,5.0,3.0,2.0,22.0,2.0
-ES,1982.0,7,7.0,5.0,5.0,1.0,7.0,7.0,2.0,1.0,50.0,1.0
-ES,1983.0,7,7.0,7.0,7.0,3.0,9.0,7.0,2.0,2.0,53.0,1.0
-ES,1985.0,7,2.0,2.0,5.0,2.0,10.0,5.0,1.0,2.0,29.0,1.0
-ES,1986.0,7,6.0,2.0,3.0,2.0,4.0,6.0,2.0,1.0,31.0,1.0
-ES,1987.0,7,6.0,1.0,1.0,1.0,10.0,6.0,3.0,1.0,76.0,1.0
-ES,1988.0,7,4.0,1.0,1.0,1.0,10.0,5.0,2.0,1.0,56.0,1.0
-ES,1992.0,7,5.0,6.0,8.0,8.0,8.0,4.0,3.0,1.0,59.0,1.0
-ES,1993.0,7,3.0,0.0,6.0,5.0,4.0,6.0,2.0,2.0,75.0,2.0
-ES,1994.0,7,3.0,8.0,8.0,5.0,10.0,6.0,3.0,1.0,82.0,2.0
-ES,1997.0,7,1.0,5.0,,5.0,8.0,6.0,2.0,1.0,16.0,2.0
-ES,1998.0,7,4.0,5.0,7.0,6.0,10.0,4.0,3.0,2.0,46.0,2.0
-ES,2006.0,7,7.0,8.0,8.0,3.0,8.0,6.0,4.0,2.0,38.0,1.0
-ES,2011.0,7,2.0,3.0,4.0,3.0,9.0,2.0,3.0,1.0,40.0,1.0
-ES,2012.0,7,5.0,3.0,3.0,4.0,8.0,4.0,1.0,2.0,73.0,1.0
-ES,2013.0,7,4.0,5.0,8.0,3.0,7.0,2.0,2.0,2.0,54.0,1.0
-ES,2014.0,7,3.0,3.0,3.0,3.0,9.0,3.0,2.0,1.0,69.0,2.0
-ES,2015.0,7,6.0,4.0,5.0,5.0,7.0,5.0,2.0,2.0,54.0,1.0
-ES,2021.0,7,3.0,6.0,7.0,6.0,5.0,6.0,3.0,2.0,56.0,1.0
-ES,2022.0,7,0.0,7.0,6.0,3.0,9.0,6.0,3.0,1.0,56.0,1.0
-ES,2024.0,7,3.0,4.0,3.0,2.0,8.0,6.0,3.0,2.0,54.0,2.0
-ES,2025.0,7,5.0,5.0,5.0,5.0,6.0,2.0,1.0,2.0,89.0,2.0
-ES,2026.0,7,7.0,2.0,2.0,6.0,5.0,5.0,1.0,1.0,84.0,2.0
-ES,2028.0,7,2.0,1.0,3.0,3.0,5.0,1.0,1.0,1.0,,2.0
-ES,2029.0,7,0.0,6.0,8.0,3.0,8.0,6.0,1.0,1.0,50.0,1.0
-ES,2032.0,7,4.0,8.0,8.0,7.0,5.0,4.0,2.0,1.0,48.0,1.0
-ES,2035.0,7,3.0,6.0,6.0,5.0,7.0,5.0,3.0,1.0,59.0,1.0
-ES,2036.0,7,4.0,8.0,5.0,8.0,10.0,5.0,2.0,2.0,76.0,1.0
-ES,2037.0,7,4.0,5.0,5.0,5.0,8.0,5.0,4.0,2.0,52.0,1.0
-ES,2040.0,7,5.0,6.0,6.0,5.0,10.0,7.0,2.0,1.0,69.0,1.0
-ES,2041.0,7,2.0,5.0,7.0,6.0,7.0,6.0,3.0,1.0,41.0,2.0
-ES,2047.0,7,7.0,2.0,2.0,2.0,3.0,4.0,3.0,1.0,,1.0
-ES,2048.0,7,7.0,2.0,1.0,1.0,4.0,4.0,2.0,2.0,89.0,2.0
-ES,2049.0,7,5.0,3.0,3.0,2.0,4.0,3.0,3.0,1.0,33.0,2.0
-ES,2052.0,7,7.0,4.0,3.0,1.0,5.0,3.0,2.0,1.0,43.0,1.0
-ES,2055.0,7,4.0,3.0,4.0,3.0,3.0,5.0,2.0,2.0,25.0,2.0
-ES,2058.0,7,2.0,3.0,3.0,4.0,6.0,6.0,3.0,2.0,40.0,2.0
-ES,2059.0,7,6.0,4.0,2.0,2.0,5.0,3.0,3.0,1.0,44.0,1.0
-ES,2060.0,7,4.0,3.0,3.0,2.0,8.0,4.0,3.0,1.0,33.0,2.0
-ES,2063.0,7,4.0,2.0,3.0,2.0,6.0,4.0,4.0,2.0,37.0,1.0
-ES,2064.0,7,3.0,5.0,6.0,6.0,5.0,4.0,3.0,1.0,31.0,1.0
-ES,2070.0,7,4.0,4.0,3.0,3.0,7.0,5.0,1.0,1.0,84.0,1.0
-ES,2071.0,7,7.0,2.0,2.0,2.0,6.0,7.0,,1.0,68.0,1.0
-ES,2072.0,7,3.0,4.0,3.0,3.0,8.0,6.0,3.0,1.0,19.0,2.0
-ES,2073.0,7,4.0,4.0,,2.0,10.0,7.0,3.0,1.0,16.0,2.0
-ES,2074.0,7,3.0,4.0,6.0,4.0,8.0,5.0,3.0,1.0,80.0,1.0
-ES,2075.0,7,5.0,2.0,6.0,2.0,7.0,6.0,,2.0,65.0,1.0
-ES,2076.0,7,7.0,2.0,6.0,2.0,8.0,7.0,,1.0,84.0,1.0
-ES,2077.0,7,3.0,5.0,8.0,7.0,9.0,6.0,3.0,1.0,22.0,2.0
-ES,2078.0,7,3.0,6.0,8.0,5.0,9.0,6.0,2.0,2.0,64.0,2.0
-ES,2079.0,7,1.0,1.0,3.0,1.0,8.0,4.0,3.0,2.0,26.0,2.0
-ES,2080.0,7,6.0,2.0,3.0,3.0,5.0,5.0,2.0,1.0,,1.0
-ES,2086.0,7,3.0,6.0,6.0,5.0,8.0,6.0,3.0,2.0,47.0,1.0
-ES,2087.0,7,2.0,3.0,6.0,1.0,8.0,3.0,3.0,2.0,54.0,1.0
-ES,2088.0,7,2.0,7.0,5.0,8.0,10.0,5.0,2.0,1.0,55.0,1.0
-ES,2092.0,7,4.0,4.0,7.0,5.0,6.0,5.0,3.0,2.0,49.0,2.0
-ES,2093.0,7,6.0,5.0,6.0,4.0,9.0,4.0,2.0,2.0,31.0,1.0
-ES,2097.0,7,7.0,4.0,3.0,4.0,7.0,5.0,1.0,1.0,35.0,2.0
-ES,2099.0,7,2.0,6.0,3.0,4.0,9.0,5.0,4.0,1.0,47.0,1.0
-ES,2102.0,7,7.0,2.0,2.0,2.0,4.0,5.0,2.0,1.0,64.0,1.0
-ES,2104.0,7,7.0,2.0,2.0,2.0,5.0,6.0,2.0,1.0,80.0,1.0
-ES,2105.0,7,7.0,2.0,2.0,2.0,7.0,3.0,3.0,1.0,,1.0
-ES,2106.0,7,1.0,2.0,2.0,2.0,5.0,6.0,3.0,2.0,24.0,
-ES,2107.0,7,6.0,3.0,3.0,4.0,7.0,5.0,1.0,2.0,68.0,1.0
-ES,2110.0,7,5.0,7.0,3.0,1.0,9.0,5.0,2.0,1.0,35.0,2.0
-ES,2112.0,7,3.0,5.0,1.0,1.0,9.0,5.0,,1.0,22.0,2.0
-ES,2115.0,7,1.0,5.0,9.0,1.0,10.0,4.0,3.0,2.0,46.0,2.0
-ES,2116.0,7,7.0,2.0,2.0,2.0,7.0,3.0,3.0,2.0,43.0,2.0
-ES,2119.0,7,4.0,2.0,2.0,2.0,7.0,6.0,3.0,1.0,34.0,2.0
-ES,2121.0,7,3.0,6.0,8.0,4.0,8.0,6.0,3.0,2.0,18.0,2.0
-ES,2122.0,7,5.0,2.0,2.0,2.0,8.0,2.0,2.0,2.0,60.0,2.0
-ES,2124.0,7,2.0,1.0,2.0,2.0,8.0,3.0,,2.0,79.0,1.0
-ES,2125.0,7,2.0,6.0,8.0,4.0,6.0,5.0,3.0,2.0,25.0,2.0
-ES,2127.0,7,1.0,8.0,5.0,5.0,9.0,4.0,2.0,1.0,49.0,1.0
-ES,2129.0,7,5.0,4.0,6.0,4.0,5.0,7.0,1.0,2.0,80.0,1.0
-ES,2134.0,7,4.0,3.0,5.0,5.0,3.0,4.0,2.0,1.0,39.0,1.0
-ES,2135.0,7,3.0,10.0,8.0,6.0,10.0,6.0,4.0,1.0,48.0,2.0
-ES,2139.0,7,5.0,5.0,8.0,5.0,10.0,4.0,3.0,2.0,31.0,1.0
-ES,2143.0,7,4.0,6.0,7.0,5.0,7.0,5.0,,2.0,58.0,1.0
-ES,2144.0,7,4.0,6.0,8.0,6.0,7.0,6.0,3.0,1.0,30.0,2.0
-ES,2145.0,7,2.0,3.0,4.0,4.0,9.0,4.0,5.0,2.0,44.0,2.0
-ES,2148.0,7,3.0,8.0,6.0,6.0,9.0,6.0,4.0,2.0,54.0,1.0
-ES,2152.0,7,4.0,0.0,0.0,0.0,9.0,5.0,2.0,1.0,61.0,1.0
-ES,2154.0,7,7.0,7.0,6.0,4.0,10.0,6.0,4.0,1.0,67.0,1.0
-ES,2155.0,7,2.0,2.0,3.0,4.0,8.0,6.0,3.0,1.0,46.0,1.0
-ES,2159.0,7,0.0,6.0,2.0,5.0,8.0,6.0,5.0,1.0,48.0,1.0
-ES,2160.0,7,7.0,8.0,8.0,5.0,8.0,3.0,2.0,1.0,23.0,1.0
-ES,2162.0,7,2.0,0.0,10.0,10.0,5.0,7.0,3.0,2.0,37.0,2.0
-ES,2163.0,7,0.0,6.0,8.0,4.0,10.0,4.0,3.0,2.0,35.0,1.0
-ES,2164.0,7,5.0,4.0,5.0,5.0,5.0,5.0,1.0,2.0,79.0,2.0
-ES,2165.0,7,2.0,3.0,4.0,2.0,8.0,6.0,2.0,1.0,25.0,1.0
-ES,2166.0,7,4.0,5.0,5.0,7.0,6.0,4.0,1.0,2.0,70.0,1.0
-ES,2167.0,7,2.0,5.0,6.0,2.0,7.0,6.0,2.0,2.0,25.0,2.0
-ES,2170.0,7,2.0,2.0,4.0,6.0,8.0,6.0,1.0,2.0,70.0,1.0
-ES,2171.0,7,2.0,8.0,8.0,1.0,3.0,5.0,1.0,2.0,60.0,1.0
-ES,2175.0,7,3.0,4.0,5.0,0.0,8.0,7.0,2.0,1.0,20.0,2.0
-ES,2179.0,7,2.0,6.0,5.0,4.0,6.0,4.0,2.0,1.0,48.0,1.0
-ES,2180.0,7,5.0,1.0,4.0,5.0,7.0,2.0,1.0,2.0,58.0,1.0
-ES,2183.0,7,3.0,5.0,9.0,7.0,9.0,7.0,2.0,2.0,62.0,1.0
-ES,2185.0,7,7.0,6.0,,3.0,9.0,6.0,1.0,2.0,79.0,2.0
-ES,2188.0,7,5.0,4.0,2.0,2.0,7.0,6.0,1.0,2.0,89.0,2.0
-ES,2189.0,7,7.0,6.0,7.0,2.0,8.0,6.0,3.0,1.0,16.0,2.0
-ES,2190.0,7,5.0,9.0,3.0,2.0,8.0,5.0,,2.0,84.0,1.0
-ES,2193.0,7,3.0,2.0,3.0,3.0,7.0,2.0,2.0,1.0,58.0,1.0
-ES,2194.0,7,5.0,2.0,3.0,3.0,7.0,5.0,2.0,1.0,37.0,1.0
-ES,2195.0,7,4.0,1.0,2.0,2.0,8.0,5.0,2.0,1.0,51.0,1.0
-ES,2196.0,7,2.0,4.0,3.0,3.0,6.0,6.0,3.0,1.0,22.0,2.0
-ES,2197.0,7,7.0,2.0,2.0,3.0,8.0,6.0,2.0,2.0,43.0,1.0
-ES,2202.0,7,2.0,2.0,4.0,2.0,7.0,6.0,3.0,2.0,55.0,1.0
-ES,2205.0,7,6.0,2.0,3.0,3.0,5.0,5.0,1.0,2.0,68.0,2.0
-ES,2206.0,7,1.0,2.0,3.0,2.0,7.0,5.0,2.0,1.0,36.0,1.0
-ES,2207.0,7,3.0,1.0,3.0,3.0,7.0,2.0,3.0,2.0,,1.0
-ES,2209.0,7,5.0,3.0,,,7.0,7.0,3.0,1.0,16.0,2.0
-ES,2210.0,7,5.0,2.0,3.0,3.0,6.0,6.0,3.0,1.0,31.0,2.0
-ES,2211.0,7,7.0,2.0,7.0,2.0,7.0,5.0,2.0,2.0,45.0,1.0
-ES,2212.0,7,4.0,3.0,3.0,2.0,5.0,7.0,3.0,1.0,59.0,2.0
-ES,2218.0,7,3.0,3.0,5.0,8.0,8.0,4.0,2.0,1.0,52.0,1.0
-ES,2220.0,7,2.0,4.0,5.0,5.0,7.0,4.0,3.0,1.0,23.0,2.0
-ES,2222.0,7,1.0,4.0,8.0,1.0,9.0,4.0,3.0,2.0,27.0,2.0
-ES,2223.0,7,2.0,6.0,8.0,3.0,8.0,6.0,5.0,1.0,34.0,1.0
-ES,2224.0,7,4.0,5.0,5.0,4.0,7.0,5.0,3.0,2.0,41.0,1.0
-ES,2225.0,7,3.0,7.0,7.0,6.0,10.0,6.0,3.0,2.0,44.0,1.0
-ES,2227.0,7,5.0,4.0,4.0,6.0,6.0,5.0,3.0,2.0,52.0,1.0
-ES,2228.0,7,7.0,5.0,5.0,5.0,7.0,2.0,3.0,1.0,36.0,2.0
-ES,2229.0,7,6.0,1.0,6.0,3.0,8.0,4.0,3.0,1.0,31.0,1.0
-ES,2230.0,7,7.0,4.0,6.0,6.0,8.0,7.0,3.0,1.0,,1.0
-ES,2232.0,7,7.0,2.0,5.0,4.0,7.0,7.0,3.0,2.0,65.0,2.0
-ES,2236.0,7,3.0,7.0,8.0,6.0,8.0,6.0,4.0,1.0,60.0,2.0
-ES,2237.0,7,7.0,5.0,7.0,3.0,7.0,6.0,5.0,2.0,72.0,2.0
-ES,2239.0,7,3.0,5.0,6.0,3.0,9.0,6.0,3.0,2.0,46.0,1.0
-ES,2241.0,7,7.0,8.0,9.0,8.0,9.0,2.0,2.0,1.0,61.0,1.0
-ES,2242.0,7,3.0,4.0,6.0,0.0,8.0,6.0,2.0,1.0,47.0,1.0
-ES,2244.0,7,5.0,7.0,6.0,5.0,6.0,7.0,2.0,2.0,85.0,2.0
-ES,2245.0,7,6.0,2.0,5.0,7.0,8.0,7.0,5.0,1.0,74.0,1.0
-ES,2246.0,7,7.0,2.0,7.0,7.0,7.0,6.0,2.0,2.0,,2.0
-ES,2247.0,7,5.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,28.0,2.0
-ES,2249.0,7,4.0,2.0,5.0,3.0,9.0,5.0,3.0,1.0,54.0,1.0
-ES,2252.0,7,2.0,6.0,5.0,7.0,8.0,4.0,3.0,1.0,45.0,1.0
-ES,2260.0,7,5.0,1.0,5.0,3.0,10.0,7.0,2.0,2.0,64.0,2.0
-ES,2266.0,7,6.0,7.0,3.0,2.0,10.0,2.0,3.0,2.0,78.0,1.0
-ES,2269.0,7,1.0,3.0,5.0,2.0,10.0,4.0,3.0,2.0,48.0,1.0
-ES,2270.0,7,4.0,6.0,8.0,7.0,8.0,7.0,3.0,1.0,46.0,2.0
-ES,2274.0,7,6.0,5.0,7.0,4.0,5.0,6.0,2.0,1.0,61.0,1.0
-ES,2275.0,7,3.0,4.0,7.0,1.0,10.0,6.0,2.0,2.0,23.0,2.0
-ES,2281.0,7,1.0,5.0,5.0,5.0,8.0,5.0,3.0,2.0,69.0,1.0
-ES,2286.0,7,2.0,2.0,2.0,2.0,9.0,6.0,3.0,1.0,60.0,1.0
-ES,2288.0,7,3.0,6.0,3.0,2.0,9.0,5.0,3.0,1.0,64.0,2.0
-ES,2289.0,7,1.0,6.0,6.0,6.0,8.0,7.0,3.0,2.0,47.0,2.0
-ES,2291.0,7,4.0,2.0,9.0,8.0,10.0,4.0,1.0,2.0,83.0,2.0
-ES,2295.0,7,2.0,6.0,6.0,5.0,7.0,2.0,1.0,2.0,34.0,1.0
-ES,2298.0,7,3.0,7.0,7.0,3.0,7.0,3.0,4.0,1.0,45.0,1.0
-ES,2299.0,7,0.0,6.0,6.0,2.0,10.0,5.0,3.0,1.0,36.0,2.0
-ES,2300.0,7,1.0,2.0,2.0,2.0,2.0,2.0,3.0,2.0,39.0,1.0
-ES,2303.0,7,1.0,6.0,5.0,4.0,7.0,7.0,1.0,1.0,25.0,2.0
-ES,2304.0,7,4.0,5.0,7.0,3.0,7.0,3.0,3.0,1.0,49.0,1.0
-ES,2306.0,7,2.0,7.0,7.0,6.0,7.0,6.0,5.0,2.0,30.0,1.0
-ES,2309.0,7,4.0,6.0,7.0,7.0,8.0,7.0,1.0,1.0,53.0,1.0
-ES,2310.0,7,4.0,4.0,3.0,2.0,6.0,3.0,2.0,1.0,44.0,1.0
-ES,2316.0,7,2.0,5.0,9.0,3.0,8.0,4.0,4.0,1.0,55.0,1.0
-ES,2323.0,7,6.0,3.0,8.0,2.0,8.0,6.0,5.0,2.0,27.0,2.0
-ES,2325.0,7,4.0,6.0,5.0,2.0,9.0,7.0,2.0,1.0,21.0,2.0
-ES,2328.0,7,6.0,5.0,7.0,5.0,8.0,7.0,3.0,2.0,21.0,2.0
-ES,2329.0,7,6.0,3.0,7.0,5.0,7.0,4.0,1.0,2.0,16.0,2.0
-ES,2334.0,7,2.0,4.0,5.0,7.0,8.0,6.0,3.0,2.0,22.0,2.0
-ES,2339.0,7,3.0,2.0,5.0,0.0,6.0,4.0,3.0,2.0,30.0,1.0
-ES,2341.0,7,1.0,5.0,7.0,3.0,8.0,5.0,2.0,1.0,30.0,1.0
-ES,2344.0,7,2.0,5.0,5.0,3.0,10.0,7.0,5.0,1.0,28.0,2.0
-ES,2348.0,7,1.0,5.0,5.0,0.0,10.0,7.0,3.0,1.0,18.0,2.0
-ES,2352.0,7,4.0,7.0,5.0,6.0,7.0,4.0,,1.0,61.0,1.0
-ES,2354.0,7,4.0,7.0,7.0,5.0,8.0,7.0,,1.0,45.0,1.0
-ES,2355.0,7,5.0,3.0,8.0,5.0,8.0,6.0,2.0,2.0,45.0,1.0
-ES,2357.0,7,3.0,8.0,10.0,9.0,7.0,4.0,4.0,2.0,37.0,1.0
-ES,2358.0,7,1.0,7.0,3.0,3.0,7.0,7.0,4.0,2.0,23.0,2.0
-ES,2359.0,7,4.0,6.0,7.0,7.0,6.0,2.0,3.0,1.0,53.0,1.0
-ES,2360.0,7,2.0,5.0,5.0,2.0,8.0,2.0,2.0,1.0,55.0,1.0
-ES,2361.0,7,3.0,2.0,5.0,5.0,10.0,6.0,,1.0,69.0,1.0
-ES,2362.0,7,2.0,4.0,4.0,1.0,8.0,3.0,3.0,2.0,45.0,1.0
-ES,2366.0,7,2.0,5.0,5.0,7.0,8.0,3.0,3.0,1.0,71.0,1.0
-ES,2368.0,7,7.0,6.0,8.0,6.0,5.0,2.0,1.0,1.0,81.0,1.0
-ES,2370.0,7,4.0,5.0,5.0,5.0,7.0,5.0,3.0,1.0,38.0,1.0
-ES,2371.0,7,5.0,1.0,5.0,7.0,7.0,2.0,2.0,1.0,43.0,1.0
-ES,2373.0,7,2.0,8.0,3.0,4.0,5.0,1.0,3.0,2.0,44.0,1.0
-ES,2374.0,7,4.0,6.0,5.0,8.0,7.0,4.0,3.0,2.0,53.0,2.0
-ES,2375.0,7,2.0,10.0,9.0,1.0,9.0,5.0,3.0,1.0,37.0,1.0
-ES,2378.0,7,4.0,6.0,6.0,7.0,5.0,3.0,4.0,2.0,57.0,1.0
-ES,2380.0,7,1.0,6.0,5.0,8.0,8.0,4.0,4.0,2.0,60.0,1.0
-ES,2383.0,7,2.0,8.0,5.0,7.0,8.0,6.0,3.0,1.0,26.0,2.0
-ES,2384.0,7,6.0,4.0,5.0,4.0,6.0,6.0,3.0,2.0,54.0,1.0
-ES,2385.0,7,2.0,6.0,8.0,0.0,9.0,7.0,3.0,1.0,46.0,1.0
-ES,2386.0,7,6.0,6.0,8.0,2.0,5.0,5.0,3.0,2.0,32.0,2.0
-ES,2387.0,7,6.0,8.0,5.0,2.0,6.0,4.0,3.0,1.0,73.0,1.0
-ES,2389.0,7,4.0,6.0,7.0,3.0,8.0,6.0,2.0,1.0,35.0,1.0
-ES,2393.0,7,3.0,5.0,5.0,0.0,8.0,6.0,5.0,1.0,51.0,1.0
-ES,2394.0,7,5.0,7.0,6.0,7.0,5.0,6.0,3.0,2.0,55.0,1.0
-ES,2396.0,7,2.0,4.0,3.0,3.0,6.0,7.0,4.0,2.0,30.0,2.0
-ES,2399.0,7,3.0,8.0,8.0,9.0,9.0,4.0,3.0,2.0,62.0,1.0
-ES,2400.0,7,0.0,5.0,5.0,5.0,8.0,5.0,4.0,1.0,33.0,2.0
-ES,2401.0,7,3.0,5.0,3.0,4.0,7.0,6.0,2.0,1.0,19.0,2.0
-ES,2403.0,7,6.0,3.0,4.0,,0.0,7.0,1.0,2.0,81.0,2.0
-ES,2404.0,7,6.0,5.0,4.0,4.0,5.0,6.0,2.0,1.0,37.0,2.0
-ES,2405.0,7,6.0,5.0,7.0,4.0,9.0,7.0,2.0,1.0,43.0,1.0
-ES,2406.0,7,4.0,7.0,7.0,7.0,7.0,6.0,3.0,1.0,53.0,1.0
-ES,2408.0,7,4.0,4.0,5.0,5.0,6.0,5.0,2.0,1.0,22.0,2.0
-ES,2409.0,7,1.0,5.0,7.0,2.0,10.0,5.0,3.0,2.0,43.0,2.0
-ES,2412.0,7,4.0,8.0,9.0,6.0,9.0,7.0,3.0,2.0,63.0,1.0
-ES,2414.0,7,6.0,6.0,7.0,5.0,8.0,4.0,3.0,2.0,51.0,1.0
-ES,2420.0,7,2.0,3.0,3.0,2.0,8.0,6.0,4.0,2.0,34.0,1.0
-ES,2422.0,7,7.0,5.0,8.0,8.0,8.0,7.0,1.0,1.0,82.0,1.0
-ES,2426.0,7,3.0,0.0,8.0,9.0,9.0,4.0,3.0,1.0,18.0,2.0
-ES,2429.0,7,2.0,5.0,6.0,7.0,8.0,4.0,2.0,1.0,44.0,1.0
-ES,2430.0,7,7.0,3.0,3.0,3.0,6.0,6.0,3.0,1.0,72.0,1.0
-ES,2433.0,7,4.0,2.0,2.0,2.0,7.0,7.0,4.0,2.0,33.0,1.0
-ES,2434.0,7,6.0,7.0,3.0,7.0,8.0,5.0,3.0,1.0,71.0,1.0
-ES,2436.0,7,7.0,2.0,0.0,1.0,7.0,7.0,3.0,2.0,75.0,2.0
-ES,2439.0,7,5.0,6.0,8.0,2.0,9.0,5.0,3.0,2.0,38.0,1.0
-ES,2440.0,7,2.0,7.0,5.0,4.0,9.0,7.0,4.0,1.0,62.0,1.0
-ES,2443.0,7,4.0,4.0,5.0,3.0,8.0,4.0,2.0,1.0,27.0,1.0
-ES,2446.0,7,4.0,3.0,5.0,5.0,5.0,6.0,2.0,1.0,43.0,2.0
-ES,2448.0,7,3.0,5.0,5.0,3.0,9.0,6.0,2.0,1.0,32.0,2.0
-ES,2450.0,7,6.0,2.0,8.0,5.0,8.0,6.0,3.0,2.0,39.0,1.0
-ES,2452.0,7,5.0,5.0,5.0,3.0,5.0,6.0,2.0,2.0,52.0,2.0
-ES,2453.0,7,4.0,6.0,7.0,8.0,8.0,7.0,2.0,1.0,56.0,1.0
-ES,2454.0,7,7.0,4.0,4.0,5.0,7.0,6.0,2.0,1.0,21.0,2.0
-ES,2456.0,7,5.0,2.0,2.0,4.0,3.0,2.0,2.0,2.0,55.0,1.0
-ES,2457.0,7,6.0,5.0,8.0,3.0,8.0,7.0,3.0,1.0,31.0,1.0
-ES,2458.0,7,4.0,5.0,4.0,6.0,5.0,5.0,4.0,2.0,48.0,2.0
-ES,2461.0,7,2.0,7.0,7.0,5.0,9.0,5.0,3.0,1.0,38.0,1.0
-ES,2462.0,7,4.0,5.0,6.0,7.0,8.0,5.0,3.0,2.0,36.0,1.0
-ES,2465.0,7,4.0,7.0,8.0,2.0,10.0,7.0,3.0,1.0,25.0,2.0
-ES,2467.0,7,7.0,3.0,5.0,2.0,9.0,5.0,3.0,2.0,,1.0
-ES,2470.0,7,7.0,2.0,4.0,8.0,7.0,6.0,2.0,2.0,58.0,1.0
-ES,2471.0,7,6.0,2.0,4.0,0.0,6.0,6.0,2.0,1.0,71.0,1.0
-ES,2474.0,7,5.0,5.0,5.0,7.0,8.0,6.0,1.0,2.0,24.0,2.0
-ES,2477.0,7,3.0,7.0,6.0,5.0,7.0,5.0,2.0,2.0,49.0,1.0
-ES,2489.0,7,3.0,6.0,5.0,4.0,8.0,7.0,5.0,1.0,48.0,1.0
-ES,2490.0,7,3.0,7.0,8.0,5.0,4.0,4.0,1.0,2.0,64.0,2.0
-ES,2493.0,7,4.0,3.0,5.0,0.0,10.0,6.0,2.0,1.0,72.0,1.0
-ES,2497.0,7,7.0,3.0,0.0,5.0,10.0,5.0,4.0,2.0,73.0,2.0
-ES,2499.0,7,5.0,5.0,4.0,5.0,7.0,6.0,4.0,1.0,54.0,1.0
-ES,2503.0,7,4.0,8.0,8.0,8.0,9.0,5.0,2.0,1.0,63.0,1.0
-ES,2508.0,7,2.0,3.0,8.0,2.0,8.0,7.0,3.0,2.0,39.0,2.0
-ES,2509.0,7,7.0,7.0,5.0,2.0,5.0,6.0,3.0,1.0,54.0,1.0
-ES,2511.0,7,7.0,5.0,2.0,5.0,7.0,7.0,3.0,1.0,58.0,1.0
-ES,2514.0,7,0.0,5.0,5.0,8.0,10.0,3.0,1.0,2.0,52.0,1.0
-ES,2515.0,7,0.0,5.0,5.0,3.0,3.0,5.0,2.0,1.0,46.0,1.0
-ES,2516.0,7,7.0,4.0,7.0,5.0,7.0,6.0,1.0,1.0,34.0,2.0
-ES,2517.0,7,7.0,6.0,8.0,5.0,10.0,7.0,5.0,1.0,82.0,2.0
-ES,2520.0,7,3.0,3.0,5.0,4.0,7.0,6.0,2.0,1.0,46.0,1.0
-ES,2522.0,7,7.0,3.0,3.0,2.0,8.0,7.0,3.0,1.0,67.0,1.0
-ES,2523.0,7,7.0,2.0,8.0,3.0,8.0,2.0,3.0,2.0,44.0,1.0
-ES,2525.0,7,4.0,5.0,8.0,5.0,8.0,6.0,3.0,2.0,51.0,1.0
-ES,2526.0,7,6.0,4.0,7.0,6.0,9.0,6.0,3.0,1.0,17.0,2.0
-ES,2527.0,7,4.0,2.0,7.0,3.0,2.0,5.0,3.0,2.0,81.0,2.0
-ES,2532.0,7,7.0,4.0,10.0,10.0,10.0,5.0,1.0,2.0,17.0,2.0
-ES,2534.0,7,2.0,4.0,6.0,4.0,6.0,2.0,1.0,1.0,42.0,1.0
-ES,2540.0,7,6.0,7.0,8.0,6.0,8.0,5.0,1.0,2.0,67.0,1.0
-ES,2541.0,7,2.0,6.0,8.0,6.0,10.0,5.0,5.0,2.0,50.0,1.0
-ES,2542.0,7,6.0,7.0,8.0,6.0,10.0,4.0,1.0,2.0,25.0,1.0
-ES,2543.0,7,5.0,5.0,2.0,2.0,8.0,4.0,2.0,1.0,59.0,2.0
-ES,2544.0,7,5.0,7.0,5.0,8.0,10.0,4.0,3.0,1.0,38.0,2.0
-ES,2545.0,7,2.0,5.0,7.0,0.0,7.0,4.0,5.0,2.0,53.0,2.0
-ES,2549.0,7,3.0,7.0,6.0,7.0,8.0,5.0,2.0,1.0,61.0,1.0
-ES,2551.0,7,3.0,3.0,4.0,1.0,7.0,6.0,5.0,1.0,28.0,1.0
-ES,2554.0,7,3.0,6.0,7.0,2.0,6.0,3.0,3.0,2.0,32.0,1.0
-ES,2555.0,7,5.0,7.0,10.0,5.0,8.0,4.0,2.0,2.0,64.0,2.0
-ES,2556.0,7,2.0,10.0,10.0,5.0,10.0,6.0,3.0,2.0,41.0,2.0
-ES,2558.0,7,4.0,1.0,1.0,1.0,6.0,6.0,4.0,1.0,34.0,2.0
-ES,2559.0,7,5.0,7.0,7.0,8.0,9.0,6.0,4.0,2.0,56.0,2.0
-ES,2564.0,7,2.0,3.0,6.0,3.0,8.0,3.0,3.0,2.0,46.0,1.0
-ES,2565.0,7,1.0,0.0,5.0,0.0,5.0,7.0,1.0,1.0,72.0,1.0
-ES,2566.0,7,3.0,3.0,5.0,3.0,4.0,3.0,3.0,1.0,49.0,2.0
-ES,2568.0,7,3.0,4.0,9.0,1.0,9.0,4.0,3.0,2.0,46.0,1.0
-ES,2571.0,7,5.0,8.0,8.0,6.0,8.0,6.0,3.0,1.0,51.0,1.0
-ES,2575.0,7,4.0,6.0,7.0,4.0,9.0,7.0,2.0,2.0,18.0,2.0
-ES,2578.0,7,1.0,3.0,3.0,3.0,8.0,7.0,3.0,1.0,45.0,2.0
-ES,2579.0,7,3.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,60.0,1.0
-ES,2581.0,7,2.0,4.0,5.0,6.0,8.0,7.0,2.0,1.0,29.0,2.0
-ES,2586.0,7,3.0,3.0,10.0,10.0,9.0,5.0,2.0,1.0,42.0,1.0
-ES,2590.0,7,2.0,6.0,7.0,6.0,8.0,7.0,2.0,2.0,43.0,1.0
-ES,2592.0,7,7.0,5.0,3.0,2.0,10.0,5.0,2.0,1.0,51.0,1.0
-ES,2596.0,7,7.0,5.0,5.0,0.0,10.0,1.0,2.0,1.0,46.0,1.0
-ES,2597.0,7,7.0,7.0,2.0,7.0,6.0,3.0,2.0,1.0,59.0,2.0
-ES,2598.0,7,7.0,7.0,8.0,2.0,10.0,6.0,3.0,1.0,87.0,1.0
-ES,2600.0,7,2.0,7.0,7.0,3.0,6.0,6.0,2.0,2.0,41.0,1.0
-ES,2602.0,7,3.0,5.0,6.0,7.0,10.0,5.0,3.0,1.0,54.0,1.0
-ES,2607.0,7,2.0,7.0,5.0,0.0,9.0,3.0,2.0,2.0,26.0,2.0
-ES,2608.0,7,5.0,4.0,3.0,8.0,7.0,7.0,2.0,1.0,75.0,2.0
-ES,2609.0,7,3.0,7.0,7.0,7.0,8.0,2.0,4.0,1.0,,1.0
-ES,2613.0,7,7.0,0.0,0.0,0.0,10.0,6.0,1.0,2.0,81.0,2.0
-ES,2615.0,7,3.0,5.0,5.0,6.0,9.0,7.0,4.0,1.0,47.0,1.0
-ES,2618.0,7,3.0,5.0,5.0,5.0,5.0,5.0,2.0,1.0,43.0,2.0
-ES,2620.0,7,7.0,7.0,7.0,2.0,9.0,6.0,3.0,1.0,78.0,1.0
-ES,2623.0,7,2.0,5.0,8.0,5.0,10.0,5.0,1.0,2.0,45.0,1.0
-ES,2626.0,7,5.0,6.0,5.0,4.0,8.0,7.0,2.0,2.0,21.0,2.0
-ES,2627.0,7,4.0,5.0,8.0,8.0,7.0,5.0,1.0,2.0,52.0,1.0
-ES,2629.0,7,2.0,3.0,8.0,5.0,10.0,3.0,4.0,2.0,42.0,1.0
-ES,2631.0,7,3.0,5.0,7.0,2.0,8.0,5.0,2.0,2.0,47.0,1.0
-ES,2635.0,7,5.0,4.0,4.0,2.0,6.0,5.0,5.0,1.0,55.0,1.0
-ES,2636.0,7,1.0,8.0,7.0,4.0,6.0,6.0,2.0,1.0,59.0,2.0
-ES,2637.0,7,5.0,2.0,5.0,3.0,2.0,5.0,2.0,2.0,17.0,2.0
-ES,2639.0,7,5.0,5.0,7.0,4.0,8.0,5.0,3.0,2.0,27.0,1.0
-ES,2642.0,7,3.0,7.0,6.0,7.0,7.0,5.0,3.0,1.0,62.0,1.0
-ES,2644.0,7,3.0,9.0,8.0,5.0,10.0,6.0,1.0,1.0,57.0,1.0
-ES,2647.0,7,5.0,7.0,5.0,2.0,6.0,6.0,3.0,1.0,29.0,2.0
-ES,2648.0,7,5.0,7.0,8.0,5.0,8.0,5.0,4.0,1.0,40.0,2.0
-ES,2650.0,7,5.0,5.0,10.0,3.0,5.0,6.0,3.0,1.0,57.0,1.0
-ES,2651.0,7,1.0,1.0,5.0,0.0,8.0,4.0,1.0,2.0,60.0,1.0
-ES,2653.0,7,1.0,5.0,6.0,6.0,8.0,7.0,3.0,2.0,20.0,2.0
-ES,2658.0,7,7.0,8.0,6.0,5.0,8.0,7.0,3.0,2.0,74.0,1.0
-ES,2661.0,7,4.0,6.0,7.0,4.0,6.0,5.0,3.0,2.0,25.0,2.0
-ES,2662.0,7,7.0,8.0,7.0,4.0,3.0,6.0,1.0,2.0,54.0,2.0
-ES,2663.0,7,3.0,6.0,4.0,7.0,5.0,6.0,3.0,1.0,39.0,2.0
-ES,2668.0,7,7.0,7.0,6.0,2.0,5.0,4.0,2.0,2.0,84.0,2.0
-ES,2669.0,7,2.0,7.0,7.0,5.0,8.0,6.0,4.0,1.0,45.0,1.0
-ES,2670.0,7,3.0,7.0,7.0,4.0,7.0,4.0,3.0,1.0,56.0,1.0
-ES,2671.0,7,5.0,8.0,5.0,2.0,8.0,6.0,4.0,1.0,25.0,2.0
-ES,2672.0,7,1.0,8.0,7.0,4.0,8.0,6.0,3.0,1.0,48.0,1.0
-ES,2674.0,7,1.0,3.0,5.0,2.0,5.0,6.0,4.0,1.0,16.0,2.0
-ES,2678.0,7,1.0,6.0,7.0,5.0,6.0,6.0,2.0,1.0,47.0,1.0
-ES,2683.0,7,6.0,4.0,5.0,8.0,7.0,4.0,2.0,2.0,79.0,1.0
-ES,2685.0,7,3.0,8.0,8.0,2.0,7.0,3.0,3.0,2.0,42.0,2.0
-ES,2686.0,7,2.0,5.0,6.0,4.0,8.0,5.0,3.0,2.0,46.0,2.0
-ES,2688.0,7,1.0,6.0,7.0,4.0,10.0,7.0,3.0,2.0,87.0,2.0
-ES,2689.0,7,4.0,5.0,4.0,3.0,7.0,5.0,3.0,2.0,62.0,1.0
-ES,2690.0,7,2.0,6.0,7.0,7.0,8.0,5.0,2.0,2.0,27.0,2.0
-ES,2692.0,7,7.0,2.0,,7.0,6.0,1.0,1.0,1.0,,2.0
-ES,2693.0,7,3.0,7.0,5.0,3.0,7.0,4.0,2.0,1.0,51.0,1.0
-ES,2694.0,7,4.0,5.0,6.0,4.0,8.0,6.0,4.0,2.0,59.0,1.0
-ES,2698.0,7,3.0,3.0,5.0,2.0,8.0,5.0,4.0,2.0,45.0,1.0
-ES,2700.0,7,3.0,5.0,5.0,5.0,10.0,7.0,4.0,2.0,56.0,2.0
-ES,2703.0,7,6.0,5.0,7.0,7.0,7.0,6.0,4.0,2.0,46.0,1.0
-ES,2705.0,7,1.0,8.0,5.0,4.0,7.0,7.0,3.0,1.0,25.0,2.0
-ES,2707.0,7,4.0,0.0,5.0,5.0,7.0,5.0,3.0,2.0,60.0,1.0
-ES,2709.0,7,3.0,7.0,5.0,3.0,8.0,7.0,3.0,1.0,50.0,1.0
-ES,2713.0,7,7.0,0.0,10.0,8.0,10.0,4.0,3.0,2.0,78.0,2.0
-ES,2714.0,7,3.0,6.0,8.0,5.0,7.0,5.0,4.0,1.0,46.0,1.0
-ES,2715.0,7,3.0,6.0,7.0,8.0,7.0,6.0,3.0,2.0,19.0,2.0
-ES,2720.0,7,7.0,8.0,6.0,3.0,10.0,6.0,1.0,1.0,,1.0
-ES,2721.0,7,3.0,7.0,4.0,2.0,7.0,5.0,2.0,1.0,47.0,2.0
-ES,2722.0,7,3.0,3.0,4.0,2.0,7.0,7.0,2.0,1.0,18.0,2.0
-ES,2729.0,7,4.0,5.0,4.0,4.0,8.0,7.0,3.0,2.0,52.0,1.0
-ES,2731.0,7,1.0,6.0,7.0,8.0,7.0,6.0,3.0,2.0,25.0,2.0
-ES,2732.0,7,3.0,7.0,5.0,9.0,8.0,6.0,4.0,1.0,65.0,2.0
-ES,2733.0,7,6.0,4.0,0.0,5.0,6.0,7.0,3.0,2.0,64.0,2.0
-ES,2735.0,7,6.0,7.0,5.0,5.0,9.0,7.0,3.0,1.0,82.0,1.0
-ES,2736.0,7,4.0,5.0,7.0,8.0,10.0,6.0,3.0,1.0,57.0,1.0
-ES,2739.0,7,1.0,6.0,5.0,6.0,7.0,6.0,3.0,1.0,32.0,2.0
-ES,2740.0,7,1.0,4.0,6.0,5.0,9.0,6.0,2.0,1.0,21.0,2.0
-ES,2743.0,7,5.0,6.0,6.0,5.0,8.0,5.0,2.0,1.0,67.0,1.0
-ES,2747.0,7,4.0,4.0,5.0,0.0,9.0,1.0,1.0,1.0,45.0,1.0
-ES,2749.0,7,3.0,7.0,7.0,6.0,10.0,6.0,3.0,2.0,62.0,1.0
-ES,2751.0,7,6.0,4.0,3.0,1.0,7.0,5.0,4.0,2.0,72.0,1.0
-ES,2752.0,7,0.0,5.0,2.0,2.0,6.0,4.0,5.0,2.0,63.0,1.0
-ES,2755.0,7,5.0,3.0,7.0,3.0,10.0,2.0,2.0,1.0,53.0,1.0
-ES,2758.0,7,2.0,5.0,5.0,2.0,8.0,5.0,2.0,2.0,50.0,1.0
-ES,2760.0,7,7.0,3.0,5.0,1.0,6.0,6.0,2.0,1.0,80.0,2.0
-ES,2764.0,7,4.0,6.0,4.0,5.0,8.0,6.0,2.0,1.0,36.0,1.0
-ES,2765.0,7,3.0,5.0,2.0,1.0,3.0,7.0,4.0,2.0,56.0,2.0
-ES,2770.0,7,7.0,5.0,7.0,0.0,10.0,7.0,3.0,2.0,,2.0
-ES,2773.0,7,6.0,2.0,,2.0,4.0,6.0,,1.0,76.0,2.0
-ES,2777.0,7,3.0,7.0,8.0,6.0,4.0,4.0,2.0,2.0,33.0,2.0
-ES,2778.0,7,5.0,5.0,6.0,4.0,8.0,6.0,3.0,2.0,32.0,2.0
-ES,2782.0,7,1.0,5.0,7.0,7.0,10.0,4.0,3.0,2.0,35.0,1.0
-ES,2786.0,7,5.0,6.0,7.0,5.0,9.0,7.0,3.0,1.0,,1.0
-ES,2788.0,7,1.0,5.0,7.0,2.0,8.0,3.0,2.0,1.0,32.0,1.0
-ES,2789.0,7,7.0,5.0,8.0,5.0,6.0,7.0,3.0,2.0,65.0,1.0
-ES,2791.0,7,7.0,0.0,0.0,0.0,5.0,7.0,2.0,1.0,83.0,1.0
-ES,2793.0,7,2.0,6.0,6.0,3.0,9.0,6.0,3.0,1.0,32.0,1.0
-ES,2794.0,7,2.0,4.0,4.0,5.0,10.0,2.0,2.0,1.0,70.0,1.0
-ES,2795.0,7,3.0,0.0,5.0,5.0,8.0,5.0,3.0,1.0,48.0,2.0
-ES,2797.0,7,4.0,4.0,7.0,5.0,10.0,6.0,3.0,1.0,64.0,1.0
-ES,2798.0,7,4.0,5.0,5.0,6.0,7.0,5.0,3.0,2.0,16.0,2.0
-ES,2799.0,7,2.0,5.0,8.0,8.0,9.0,5.0,2.0,2.0,56.0,1.0
-ES,2800.0,7,4.0,5.0,7.0,5.0,8.0,5.0,2.0,2.0,20.0,2.0
-ES,2806.0,7,7.0,1.0,10.0,,6.0,6.0,1.0,2.0,65.0,2.0
-ES,2808.0,7,7.0,5.0,5.0,8.0,8.0,4.0,3.0,2.0,74.0,1.0
-ES,2811.0,7,4.0,7.0,8.0,3.0,8.0,5.0,1.0,1.0,63.0,1.0
-ES,2813.0,7,7.0,0.0,0.0,0.0,10.0,4.0,1.0,2.0,82.0,2.0
-ES,2817.0,7,1.0,7.0,8.0,8.0,8.0,5.0,3.0,1.0,26.0,2.0
-ES,2818.0,7,2.0,6.0,9.0,6.0,8.0,6.0,2.0,2.0,17.0,2.0
-ES,2819.0,7,2.0,4.0,3.0,3.0,8.0,5.0,3.0,1.0,33.0,1.0
-ES,2820.0,7,3.0,5.0,5.0,8.0,8.0,4.0,3.0,2.0,50.0,2.0
-ES,2826.0,7,2.0,3.0,2.0,2.0,8.0,4.0,3.0,1.0,44.0,1.0
-ES,2828.0,7,4.0,6.0,5.0,2.0,7.0,4.0,2.0,2.0,43.0,1.0
-ES,2829.0,7,6.0,4.0,8.0,4.0,5.0,4.0,2.0,1.0,57.0,1.0
-ES,2830.0,7,7.0,8.0,8.0,2.0,8.0,6.0,3.0,1.0,62.0,1.0
-ES,2831.0,7,2.0,3.0,7.0,5.0,7.0,5.0,3.0,1.0,61.0,1.0
-ES,2835.0,7,3.0,7.0,8.0,6.0,8.0,4.0,2.0,2.0,53.0,2.0
-ES,2836.0,7,0.0,3.0,5.0,2.0,5.0,2.0,1.0,2.0,34.0,1.0
-ES,2837.0,7,3.0,5.0,10.0,8.0,10.0,6.0,2.0,1.0,72.0,1.0
-ES,2841.0,7,2.0,5.0,3.0,7.0,10.0,6.0,3.0,1.0,17.0,2.0
-ES,2845.0,7,7.0,3.0,4.0,1.0,7.0,6.0,,2.0,80.0,1.0
-ES,2847.0,7,5.0,5.0,5.0,3.0,8.0,7.0,3.0,1.0,73.0,1.0
-ES,2848.0,7,4.0,2.0,2.0,2.0,7.0,4.0,1.0,2.0,61.0,1.0
-ES,2850.0,7,2.0,5.0,5.0,4.0,6.0,5.0,3.0,1.0,49.0,2.0
-ES,2857.0,7,3.0,5.0,5.0,5.0,10.0,6.0,3.0,1.0,32.0,1.0
-ES,2859.0,7,7.0,7.0,7.0,5.0,7.0,7.0,4.0,2.0,53.0,1.0
-ES,2861.0,7,4.0,6.0,6.0,6.0,7.0,6.0,5.0,2.0,46.0,1.0
-ES,2865.0,7,4.0,5.0,7.0,4.0,10.0,5.0,2.0,1.0,32.0,2.0
-NO,6312.0,6,4.0,7.0,8.0,7.0,8.0,6.0,3.0,1.0,49.0,1.0
-NO,6342.0,6,4.0,7.0,8.0,5.0,8.0,5.0,3.0,2.0,32.0,1.0
-NO,6360.0,6,5.0,8.0,8.0,9.0,10.0,5.0,3.0,2.0,75.0,1.0
-NO,6390.0,6,6.0,9.0,9.0,10.0,9.0,6.0,3.0,2.0,68.0,1.0
-NO,6396.0,6,4.0,5.0,7.0,8.0,10.0,3.0,2.0,2.0,57.0,1.0
-NO,6420.0,6,2.0,6.0,6.0,4.0,8.0,6.0,4.0,1.0,15.0,2.0
-NO,6444.0,6,7.0,7.0,8.0,7.0,9.0,6.0,3.0,1.0,69.0,1.0
-NO,6468.0,6,4.0,2.0,5.0,7.0,7.0,5.0,2.0,1.0,36.0,1.0
-NO,6474.0,6,5.0,5.0,8.0,1.0,9.0,6.0,3.0,2.0,47.0,1.0
-NO,6540.0,6,4.0,8.0,8.0,7.0,9.0,5.0,3.0,2.0,38.0,2.0
-NO,6576.0,6,7.0,3.0,5.0,5.0,7.0,3.0,2.0,1.0,41.0,1.0
-NO,6582.0,6,7.0,5.0,8.0,8.0,10.0,6.0,2.0,2.0,75.0,1.0
-NO,6594.0,6,6.0,7.0,8.0,8.0,8.0,6.0,3.0,2.0,41.0,2.0
-NO,6636.0,6,5.0,4.0,4.0,7.0,8.0,5.0,3.0,2.0,34.0,1.0
-NO,6648.0,6,5.0,3.0,3.0,1.0,0.0,2.0,1.0,2.0,46.0,2.0
-NO,6672.0,6,5.0,9.0,9.0,7.0,9.0,4.0,3.0,2.0,48.0,1.0
-NO,6684.0,6,5.0,5.0,8.0,3.0,8.0,6.0,3.0,2.0,,1.0
-NO,6708.0,6,3.0,8.0,9.0,5.0,9.0,4.0,3.0,1.0,18.0,2.0
-NO,6732.0,6,0.0,5.0,1.0,5.0,7.0,6.0,3.0,1.0,22.0,1.0
-NO,6750.0,6,1.0,3.0,5.0,1.0,9.0,6.0,2.0,1.0,32.0,1.0
-NO,6756.0,6,0.0,9.0,9.0,6.0,10.0,7.0,3.0,2.0,22.0,1.0
-NO,6774.0,6,2.0,7.0,7.0,7.0,8.0,4.0,4.0,2.0,42.0,1.0
-NO,6792.0,6,5.0,8.0,6.0,4.0,10.0,6.0,2.0,2.0,28.0,2.0
-NO,6798.0,6,3.0,8.0,6.0,7.0,9.0,4.0,2.0,1.0,28.0,1.0
-NO,6816.0,6,7.0,4.0,6.0,7.0,9.0,4.0,3.0,2.0,68.0,1.0
-NO,6846.0,6,0.0,8.0,8.0,6.0,8.0,7.0,3.0,1.0,26.0,2.0
-NO,6870.0,6,2.0,5.0,7.0,3.0,8.0,7.0,3.0,1.0,30.0,1.0
-NO,6882.0,6,7.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,32.0,1.0
-NO,6888.0,6,3.0,8.0,8.0,6.0,7.0,7.0,3.0,1.0,39.0,2.0
-NO,6918.0,6,3.0,7.0,7.0,6.0,8.0,5.0,4.0,1.0,29.0,2.0
-NO,6936.0,6,1.0,8.0,8.0,7.0,7.0,7.0,3.0,1.0,33.0,2.0
-NO,6966.0,6,4.0,8.0,7.0,7.0,7.0,6.0,4.0,2.0,39.0,2.0
-NO,6984.0,6,1.0,8.0,6.0,5.0,8.0,6.0,3.0,1.0,56.0,2.0
-NO,7002.0,6,2.0,10.0,10.0,9.0,10.0,7.0,4.0,1.0,64.0,1.0
-NO,7020.0,6,5.0,7.0,5.0,5.0,8.0,5.0,3.0,2.0,64.0,2.0
-NO,7062.0,6,3.0,8.0,8.0,10.0,10.0,4.0,3.0,1.0,75.0,1.0
-NO,7104.0,6,1.0,5.0,8.0,2.0,10.0,7.0,3.0,1.0,25.0,1.0
-NO,7116.0,6,4.0,6.0,8.0,7.0,8.0,5.0,3.0,1.0,54.0,1.0
-NO,7134.0,6,3.0,5.0,7.0,5.0,7.0,6.0,3.0,1.0,27.0,2.0
-NO,7170.0,6,7.0,8.0,8.0,7.0,9.0,7.0,4.0,1.0,31.0,1.0
-NO,7182.0,6,4.0,4.0,5.0,4.0,7.0,3.0,2.0,1.0,44.0,1.0
-NO,7188.0,6,6.0,7.0,5.0,6.0,7.0,5.0,3.0,1.0,26.0,1.0
-NO,7200.0,6,4.0,7.0,7.0,5.0,8.0,4.0,3.0,2.0,60.0,2.0
-NO,7206.0,6,1.0,6.0,5.0,8.0,8.0,6.0,3.0,1.0,31.0,2.0
-NO,7230.0,6,5.0,9.0,8.0,8.0,7.0,6.0,3.0,2.0,69.0,2.0
-NO,7242.0,6,6.0,7.0,10.0,9.0,8.0,5.0,3.0,2.0,27.0,1.0
-NO,7254.0,6,2.0,9.0,8.0,5.0,8.0,5.0,4.0,1.0,45.0,1.0
-NO,7290.0,6,3.0,10.0,10.0,7.0,8.0,4.0,3.0,1.0,50.0,2.0
-NO,7296.0,6,2.0,7.0,3.0,6.0,8.0,7.0,3.0,2.0,18.0,2.0
-NO,7302.0,6,1.0,4.0,5.0,5.0,5.0,7.0,4.0,2.0,44.0,1.0
-NO,7326.0,6,2.0,8.0,8.0,7.0,10.0,6.0,3.0,2.0,31.0,1.0
-NO,7338.0,6,3.0,7.0,8.0,4.0,8.0,5.0,3.0,1.0,57.0,1.0
-NO,7344.0,6,0.0,5.0,5.0,7.0,10.0,7.0,3.0,1.0,31.0,2.0
-NO,7356.0,6,4.0,5.0,6.0,1.0,8.0,5.0,2.0,1.0,56.0,1.0
-NO,7362.0,6,2.0,8.0,7.0,6.0,5.0,6.0,3.0,1.0,27.0,2.0
-NO,7374.0,6,3.0,0.0,6.0,8.0,10.0,1.0,1.0,1.0,70.0,1.0
-NO,7380.0,6,6.0,8.0,7.0,6.0,9.0,7.0,3.0,2.0,82.0,2.0
-NO,7410.0,6,4.0,7.0,8.0,7.0,9.0,6.0,3.0,2.0,29.0,1.0
-NO,7428.0,6,4.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,29.0,1.0
-NO,7452.0,6,2.0,5.0,6.0,5.0,9.0,6.0,3.0,2.0,24.0,1.0
-NO,7458.0,6,4.0,6.0,7.0,6.0,8.0,6.0,3.0,1.0,35.0,1.0
-NO,7464.0,6,7.0,4.0,6.0,5.0,8.0,7.0,3.0,1.0,22.0,1.0
-NO,7506.0,6,2.0,7.0,6.0,4.0,9.0,7.0,3.0,1.0,22.0,2.0
-NO,7524.0,6,1.0,8.0,6.0,5.0,9.0,7.0,3.0,1.0,15.0,2.0
-NO,7530.0,6,5.0,7.0,8.0,5.0,7.0,6.0,3.0,2.0,78.0,2.0
-NO,7548.0,6,3.0,8.0,10.0,7.0,9.0,6.0,3.0,2.0,24.0,1.0
-NO,7554.0,6,0.0,7.0,7.0,7.0,5.0,5.0,3.0,2.0,62.0,2.0
-NO,7590.0,6,2.0,4.0,5.0,5.0,7.0,7.0,3.0,1.0,24.0,2.0
-NO,7644.0,6,3.0,7.0,3.0,7.0,7.0,7.0,3.0,2.0,22.0,2.0
-NO,7650.0,6,6.0,7.0,7.0,8.0,9.0,5.0,2.0,2.0,29.0,1.0
-NO,7716.0,6,3.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,41.0,1.0
-NO,7734.0,6,1.0,8.0,5.0,6.0,8.0,6.0,4.0,1.0,39.0,1.0
-NO,7746.0,6,3.0,5.0,8.0,7.0,9.0,6.0,3.0,2.0,54.0,1.0
-NO,7764.0,6,2.0,9.0,9.0,7.0,9.0,6.0,2.0,1.0,42.0,1.0
-NO,7776.0,6,2.0,7.0,9.0,6.0,8.0,4.0,2.0,1.0,41.0,1.0
-NO,7806.0,6,6.0,8.0,9.0,8.0,9.0,7.0,3.0,1.0,47.0,1.0
-NO,7818.0,6,6.0,7.0,8.0,8.0,9.0,6.0,3.0,2.0,57.0,2.0
-NO,7830.0,6,4.0,7.0,6.0,4.0,8.0,5.0,2.0,1.0,29.0,2.0
-NO,7842.0,6,7.0,1.0,4.0,7.0,8.0,6.0,4.0,2.0,24.0,2.0
-NO,7854.0,6,2.0,6.0,7.0,7.0,9.0,5.0,2.0,1.0,34.0,1.0
-NO,7878.0,6,1.0,7.0,7.0,7.0,4.0,6.0,2.0,1.0,32.0,1.0
-NO,7908.0,6,5.0,8.0,9.0,8.0,8.0,7.0,3.0,2.0,34.0,2.0
-NO,7914.0,6,3.0,7.0,7.0,8.0,7.0,6.0,3.0,2.0,36.0,1.0
-NO,7932.0,6,2.0,8.0,8.0,8.0,10.0,7.0,2.0,1.0,39.0,2.0
-NO,7938.0,6,2.0,3.0,5.0,7.0,10.0,4.0,3.0,2.0,30.0,1.0
-NO,7944.0,6,1.0,8.0,9.0,8.0,8.0,5.0,3.0,2.0,55.0,2.0
-NO,7950.0,6,5.0,5.0,5.0,5.0,10.0,7.0,3.0,1.0,43.0,1.0
-NO,7968.0,6,3.0,6.0,6.0,3.0,7.0,6.0,4.0,1.0,41.0,2.0
-NO,7980.0,6,1.0,5.0,8.0,3.0,10.0,3.0,4.0,2.0,68.0,1.0
-NO,7992.0,6,2.0,7.0,7.0,5.0,8.0,6.0,4.0,1.0,52.0,1.0
-NO,8010.0,6,7.0,3.0,9.0,8.0,8.0,5.0,2.0,2.0,81.0,1.0
-NO,8052.0,6,4.0,7.0,0.0,2.0,10.0,1.0,1.0,2.0,74.0,2.0
-NO,8076.0,6,2.0,6.0,6.0,4.0,7.0,7.0,5.0,1.0,53.0,1.0
-NO,8112.0,6,2.0,7.0,8.0,5.0,8.0,4.0,3.0,1.0,61.0,1.0
-NO,8118.0,6,1.0,5.0,4.0,4.0,6.0,6.0,2.0,1.0,46.0,2.0
-NO,8190.0,6,6.0,7.0,8.0,7.0,4.0,5.0,3.0,1.0,64.0,1.0
-NO,8202.0,6,2.0,8.0,8.0,8.0,8.0,3.0,2.0,2.0,40.0,1.0
-NO,8226.0,6,1.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,58.0,1.0
-NO,8250.0,6,0.0,6.0,5.0,5.0,7.0,7.0,1.0,1.0,37.0,1.0
-NO,8274.0,6,7.0,5.0,5.0,6.0,10.0,7.0,4.0,1.0,17.0,2.0
-NO,8286.0,6,5.0,6.0,7.0,6.0,7.0,4.0,2.0,2.0,53.0,2.0
-NO,8292.0,6,1.0,7.0,8.0,5.0,10.0,1.0,1.0,2.0,75.0,2.0
-NO,8322.0,6,3.0,9.0,9.0,7.0,9.0,6.0,4.0,2.0,48.0,2.0
-NO,8340.0,6,7.0,9.0,8.0,8.0,7.0,5.0,2.0,1.0,59.0,2.0
-NO,8364.0,6,2.0,7.0,7.0,6.0,7.0,6.0,3.0,2.0,48.0,2.0
-NO,8376.0,6,1.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,24.0,2.0
-NO,8412.0,6,1.0,8.0,6.0,4.0,10.0,7.0,4.0,1.0,58.0,1.0
-NO,8478.0,6,7.0,4.0,7.0,5.0,7.0,4.0,3.0,1.0,38.0,2.0
-NO,8496.0,6,6.0,8.0,9.0,6.0,7.0,6.0,2.0,2.0,51.0,2.0
-NO,8532.0,6,7.0,6.0,6.0,7.0,4.0,4.0,2.0,2.0,52.0,1.0
-NO,8568.0,6,5.0,8.0,8.0,7.0,4.0,4.0,2.0,1.0,44.0,1.0
-NO,8586.0,6,5.0,8.0,6.0,5.0,7.0,7.0,4.0,2.0,22.0,2.0
-NO,8592.0,6,2.0,7.0,8.0,7.0,10.0,6.0,3.0,2.0,40.0,1.0
-NO,8598.0,6,5.0,5.0,4.0,2.0,4.0,5.0,2.0,2.0,46.0,2.0
-NO,8604.0,6,3.0,4.0,6.0,3.0,8.0,7.0,3.0,2.0,19.0,2.0
-NO,8616.0,6,4.0,8.0,8.0,7.0,8.0,7.0,3.0,1.0,65.0,1.0
-NO,8622.0,6,5.0,4.0,6.0,4.0,5.0,4.0,2.0,1.0,53.0,2.0
-NO,8628.0,6,6.0,7.0,7.0,6.0,8.0,7.0,3.0,2.0,65.0,2.0
-NO,8658.0,6,3.0,7.0,7.0,5.0,9.0,7.0,3.0,1.0,15.0,2.0
-NO,8724.0,6,2.0,7.0,6.0,3.0,3.0,6.0,3.0,1.0,37.0,1.0
-NO,8742.0,6,4.0,8.0,8.0,5.0,8.0,5.0,3.0,1.0,43.0,2.0
-NO,8796.0,6,7.0,9.0,9.0,8.0,8.0,6.0,3.0,2.0,68.0,1.0
-NO,8820.0,6,4.0,6.0,6.0,3.0,9.0,6.0,3.0,1.0,67.0,1.0
-NO,8826.0,6,6.0,8.0,8.0,7.0,8.0,7.0,2.0,1.0,81.0,1.0
-NO,8838.0,6,5.0,6.0,7.0,5.0,9.0,4.0,3.0,1.0,52.0,1.0
-NO,8886.0,6,7.0,7.0,7.0,8.0,10.0,7.0,5.0,1.0,46.0,1.0
-NO,8916.0,6,7.0,7.0,10.0,8.0,10.0,5.0,3.0,2.0,67.0,2.0
-NO,8922.0,6,5.0,8.0,8.0,5.0,8.0,6.0,3.0,2.0,78.0,2.0
-NO,8952.0,6,2.0,5.0,7.0,6.0,9.0,6.0,2.0,2.0,20.0,1.0
-NO,8988.0,6,6.0,6.0,6.0,7.0,9.0,6.0,4.0,1.0,67.0,1.0
-NO,9006.0,6,7.0,8.0,8.0,6.0,9.0,6.0,3.0,1.0,30.0,2.0
-NO,9018.0,6,1.0,7.0,7.0,7.0,10.0,6.0,4.0,2.0,50.0,2.0
-NO,9024.0,6,4.0,8.0,8.0,5.0,10.0,3.0,2.0,2.0,43.0,1.0
-NO,9042.0,6,3.0,7.0,7.0,4.0,7.0,6.0,3.0,1.0,38.0,2.0
-NO,9054.0,6,3.0,6.0,6.0,7.0,9.0,6.0,4.0,2.0,20.0,2.0
-NO,9072.0,6,5.0,7.0,8.0,5.0,8.0,5.0,4.0,1.0,70.0,1.0
-NO,9090.0,6,5.0,9.0,9.0,8.0,9.0,4.0,2.0,2.0,38.0,1.0
-NO,9108.0,6,5.0,6.0,6.0,5.0,8.0,7.0,4.0,2.0,57.0,1.0
-NO,9114.0,6,4.0,7.0,8.0,9.0,8.0,7.0,3.0,1.0,37.0,2.0
-NO,9144.0,6,3.0,8.0,8.0,6.0,8.0,6.0,2.0,1.0,46.0,1.0
-NO,9168.0,6,4.0,6.0,8.0,8.0,9.0,6.0,3.0,2.0,,2.0
-NO,9180.0,6,4.0,6.0,7.0,5.0,8.0,7.0,4.0,1.0,22.0,1.0
-NO,9222.0,6,1.0,9.0,8.0,6.0,9.0,2.0,3.0,2.0,30.0,1.0
-NO,9276.0,6,2.0,7.0,6.0,5.0,7.0,7.0,3.0,1.0,45.0,2.0
-NO,9294.0,6,4.0,8.0,8.0,7.0,7.0,3.0,3.0,1.0,60.0,1.0
-NO,9300.0,6,4.0,7.0,7.0,5.0,8.0,6.0,5.0,2.0,70.0,1.0
-NO,9390.0,6,7.0,5.0,4.0,10.0,10.0,7.0,3.0,1.0,42.0,1.0
-NO,9396.0,6,5.0,8.0,8.0,4.0,8.0,6.0,4.0,1.0,71.0,1.0
-NO,9438.0,6,2.0,9.0,9.0,6.0,10.0,7.0,3.0,1.0,20.0,2.0
-NO,9492.0,6,7.0,5.0,5.0,4.0,6.0,7.0,3.0,1.0,27.0,2.0
-NO,9528.0,6,2.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,46.0,2.0
-NO,9660.0,6,6.0,8.0,7.0,6.0,8.0,7.0,3.0,2.0,22.0,2.0
-NO,9702.0,6,1.0,4.0,3.0,9.0,8.0,4.0,2.0,2.0,36.0,2.0
-NO,9714.0,6,2.0,7.0,7.0,6.0,9.0,3.0,3.0,2.0,49.0,1.0
-NO,9726.0,6,3.0,3.0,4.0,3.0,6.0,7.0,3.0,1.0,31.0,1.0
-NO,9732.0,6,2.0,8.0,8.0,10.0,8.0,6.0,3.0,1.0,46.0,1.0
-NO,9738.0,6,4.0,8.0,7.0,5.0,7.0,2.0,2.0,2.0,56.0,1.0
-NO,9750.0,6,5.0,6.0,6.0,6.0,9.0,3.0,2.0,1.0,63.0,1.0
-NO,9762.0,6,7.0,4.0,5.0,5.0,9.0,6.0,3.0,1.0,39.0,1.0
-NO,9768.0,6,5.0,8.0,8.0,7.0,8.0,5.0,4.0,1.0,75.0,1.0
-NO,9792.0,6,3.0,7.0,9.0,7.0,9.0,4.0,4.0,2.0,48.0,2.0
-NO,9798.0,6,5.0,7.0,6.0,6.0,9.0,3.0,3.0,1.0,54.0,1.0
-NO,9840.0,6,4.0,7.0,8.0,6.0,7.0,6.0,2.0,2.0,56.0,1.0
-NO,9846.0,6,7.0,2.0,5.0,2.0,,6.0,2.0,2.0,22.0,1.0
-NO,9852.0,6,4.0,5.0,4.0,4.0,8.0,6.0,4.0,1.0,33.0,1.0
-NO,9858.0,6,5.0,7.0,8.0,5.0,8.0,5.0,4.0,2.0,76.0,1.0
-NO,9876.0,6,4.0,5.0,5.0,7.0,8.0,7.0,4.0,1.0,22.0,2.0
-NO,9966.0,6,6.0,9.0,8.0,7.0,8.0,6.0,3.0,2.0,21.0,2.0
-NO,9996.0,6,6.0,8.0,7.0,6.0,8.0,6.0,4.0,2.0,71.0,1.0
-NO,10020.0,6,2.0,7.0,6.0,6.0,8.0,7.0,2.0,2.0,56.0,1.0
-NO,10032.0,6,5.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,31.0,1.0
-NO,10050.0,6,4.0,8.0,9.0,4.0,9.0,4.0,3.0,1.0,45.0,1.0
-NO,10128.0,6,4.0,7.0,9.0,8.0,9.0,7.0,3.0,2.0,54.0,1.0
-NO,10134.0,6,7.0,7.0,7.0,5.0,6.0,5.0,2.0,1.0,72.0,2.0
-NO,10188.0,6,3.0,7.0,7.0,7.0,9.0,6.0,4.0,1.0,58.0,1.0
-NO,10200.0,6,7.0,7.0,6.0,3.0,3.0,6.0,3.0,1.0,49.0,2.0
-NO,10206.0,6,4.0,8.0,9.0,8.0,9.0,6.0,2.0,1.0,86.0,1.0
-NO,10212.0,6,4.0,9.0,9.0,5.0,8.0,4.0,3.0,2.0,59.0,2.0
-NO,10218.0,6,6.0,7.0,8.0,6.0,7.0,6.0,3.0,2.0,49.0,1.0
-NO,10266.0,6,4.0,6.0,6.0,6.0,8.0,7.0,4.0,1.0,68.0,2.0
-NO,10284.0,6,4.0,8.0,7.0,6.0,9.0,5.0,3.0,1.0,48.0,1.0
-NO,10314.0,6,2.0,5.0,7.0,7.0,8.0,5.0,4.0,2.0,63.0,1.0
-NO,10332.0,6,2.0,7.0,7.0,7.0,7.0,5.0,3.0,2.0,46.0,1.0
-NO,10362.0,6,7.0,6.0,4.0,2.0,5.0,6.0,3.0,2.0,78.0,2.0
-NO,10368.0,6,1.0,7.0,8.0,8.0,10.0,7.0,4.0,2.0,23.0,2.0
-NO,10386.0,6,1.0,5.0,5.0,5.0,7.0,6.0,2.0,2.0,50.0,2.0
-NO,10416.0,6,2.0,7.0,7.0,8.0,8.0,7.0,3.0,2.0,35.0,2.0
-NO,10440.0,6,4.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,55.0,1.0
-NO,10464.0,6,4.0,8.0,7.0,3.0,7.0,5.0,3.0,1.0,46.0,2.0
-NO,10470.0,6,4.0,8.0,8.0,8.0,9.0,7.0,3.0,2.0,43.0,1.0
-NO,10512.0,6,5.0,4.0,5.0,6.0,9.0,6.0,3.0,2.0,61.0,1.0
-NO,10530.0,6,5.0,5.0,5.0,6.0,9.0,6.0,2.0,2.0,20.0,2.0
-NO,10536.0,6,3.0,8.0,8.0,8.0,9.0,7.0,4.0,1.0,50.0,1.0
-NO,10590.0,6,7.0,5.0,7.0,8.0,10.0,4.0,3.0,2.0,30.0,1.0
-NO,10596.0,6,4.0,8.0,6.0,4.0,8.0,7.0,4.0,1.0,16.0,2.0
-NO,10638.0,6,4.0,7.0,7.0,8.0,9.0,4.0,3.0,1.0,49.0,2.0
-NO,10644.0,6,0.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,48.0,2.0
-NO,10674.0,6,4.0,5.0,8.0,8.0,8.0,7.0,4.0,2.0,18.0,2.0
-NO,10698.0,6,4.0,6.0,6.0,4.0,8.0,4.0,2.0,2.0,57.0,1.0
-NO,10716.0,6,2.0,6.0,2.0,3.0,7.0,6.0,2.0,1.0,22.0,2.0
-NO,10788.0,6,4.0,4.0,5.0,8.0,8.0,6.0,2.0,2.0,25.0,1.0
-NO,10794.0,6,1.0,5.0,8.0,4.0,7.0,6.0,4.0,2.0,62.0,2.0
-NO,10800.0,6,2.0,8.0,8.0,7.0,10.0,7.0,3.0,1.0,22.0,1.0
-NO,10824.0,6,1.0,8.0,8.0,7.0,8.0,5.0,3.0,2.0,52.0,2.0
-NO,10830.0,6,6.0,8.0,7.0,7.0,9.0,7.0,3.0,1.0,33.0,1.0
-NO,10836.0,6,3.0,,,,,6.0,3.0,1.0,80.0,1.0
-NO,10872.0,6,4.0,8.0,7.0,7.0,9.0,5.0,3.0,2.0,41.0,1.0
-NO,10884.0,6,3.0,6.0,5.0,3.0,8.0,2.0,2.0,2.0,,1.0
-NO,10890.0,6,1.0,7.0,6.0,7.0,8.0,7.0,4.0,2.0,22.0,2.0
-NO,10896.0,6,2.0,7.0,8.0,3.0,9.0,6.0,3.0,1.0,29.0,2.0
-NO,10914.0,6,3.0,6.0,5.0,6.0,9.0,7.0,3.0,1.0,17.0,2.0
-NO,10932.0,6,3.0,5.0,3.0,3.0,9.0,6.0,3.0,1.0,62.0,1.0
-NO,10938.0,6,7.0,3.0,8.0,6.0,10.0,7.0,4.0,1.0,78.0,2.0
-NO,10950.0,6,1.0,8.0,8.0,6.0,9.0,6.0,3.0,1.0,46.0,1.0
-NO,10974.0,6,7.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,46.0,1.0
-NO,10986.0,6,5.0,6.0,7.0,7.0,8.0,4.0,3.0,1.0,72.0,1.0
-NO,11016.0,6,3.0,7.0,7.0,6.0,8.0,7.0,3.0,1.0,27.0,1.0
-NO,11052.0,6,7.0,4.0,9.0,4.0,7.0,6.0,3.0,2.0,16.0,2.0
-NO,11058.0,6,6.0,8.0,8.0,9.0,10.0,7.0,3.0,2.0,22.0,1.0
-NO,11064.0,6,5.0,5.0,4.0,5.0,7.0,6.0,3.0,1.0,64.0,1.0
-NO,11070.0,6,4.0,5.0,5.0,8.0,9.0,4.0,4.0,2.0,78.0,2.0
-NO,11118.0,6,3.0,4.0,2.0,5.0,5.0,4.0,3.0,2.0,27.0,2.0
-NO,11130.0,6,2.0,3.0,3.0,2.0,9.0,6.0,4.0,1.0,54.0,1.0
-NO,11160.0,6,3.0,5.0,0.0,3.0,10.0,3.0,2.0,1.0,23.0,1.0
-NO,11178.0,6,4.0,7.0,8.0,2.0,7.0,7.0,5.0,1.0,42.0,1.0
-NO,11184.0,6,2.0,7.0,9.0,5.0,8.0,7.0,4.0,1.0,20.0,2.0
-NO,11190.0,6,1.0,5.0,7.0,6.0,8.0,7.0,4.0,2.0,18.0,2.0
-NO,11196.0,6,5.0,8.0,8.0,5.0,8.0,5.0,3.0,2.0,52.0,1.0
-NO,11298.0,6,4.0,6.0,8.0,5.0,8.0,4.0,3.0,2.0,61.0,1.0
-NO,11304.0,6,4.0,5.0,7.0,4.0,5.0,4.0,3.0,2.0,,2.0
-NO,11316.0,6,2.0,10.0,10.0,7.0,6.0,3.0,1.0,2.0,84.0,2.0
-NO,11322.0,6,7.0,7.0,7.0,3.0,8.0,6.0,3.0,2.0,38.0,2.0
-NO,11340.0,6,2.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,58.0,1.0
-NO,11346.0,6,0.0,5.0,9.0,6.0,9.0,7.0,5.0,2.0,28.0,2.0
-NO,11352.0,6,7.0,7.0,8.0,5.0,8.0,4.0,2.0,2.0,70.0,1.0
-NO,11382.0,6,7.0,6.0,8.0,5.0,5.0,4.0,3.0,1.0,72.0,1.0
-NO,11388.0,6,2.0,7.0,7.0,8.0,8.0,6.0,4.0,1.0,43.0,2.0
-NO,11412.0,6,6.0,7.0,6.0,7.0,9.0,4.0,3.0,1.0,53.0,1.0
-NO,11430.0,6,6.0,7.0,8.0,8.0,9.0,7.0,4.0,1.0,22.0,2.0
-NO,11454.0,6,4.0,8.0,5.0,5.0,9.0,5.0,2.0,1.0,38.0,1.0
-NO,11466.0,6,2.0,8.0,8.0,7.0,8.0,6.0,5.0,2.0,60.0,1.0
-NO,11478.0,6,2.0,7.0,7.0,5.0,9.0,6.0,4.0,1.0,47.0,2.0
-NO,11484.0,6,7.0,8.0,8.0,7.0,8.0,5.0,2.0,1.0,69.0,1.0
-NO,11562.0,6,7.0,4.0,4.0,3.0,2.0,4.0,1.0,2.0,24.0,1.0
-NO,11568.0,6,4.0,7.0,7.0,5.0,8.0,6.0,2.0,1.0,34.0,1.0
-NO,11586.0,6,6.0,4.0,6.0,6.0,10.0,4.0,4.0,2.0,45.0,1.0
-NO,11598.0,6,7.0,10.0,7.0,4.0,4.0,6.0,3.0,2.0,54.0,2.0
-NO,11604.0,6,4.0,8.0,8.0,7.0,10.0,7.0,3.0,1.0,40.0,1.0
-NO,11622.0,6,6.0,8.0,8.0,5.0,8.0,6.0,3.0,1.0,45.0,1.0
-NO,11628.0,6,3.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,53.0,1.0
-NO,11640.0,6,7.0,7.0,7.0,5.0,8.0,3.0,2.0,1.0,,1.0
-NO,11676.0,6,3.0,5.0,7.0,6.0,4.0,6.0,3.0,2.0,51.0,2.0
-NO,11694.0,6,4.0,9.0,8.0,8.0,8.0,6.0,3.0,2.0,43.0,1.0
-NO,11718.0,6,2.0,6.0,7.0,5.0,8.0,6.0,3.0,1.0,18.0,2.0
-NO,11724.0,6,3.0,8.0,8.0,5.0,9.0,6.0,4.0,1.0,61.0,2.0
-NO,11730.0,6,6.0,7.0,9.0,7.0,9.0,6.0,3.0,2.0,57.0,2.0
-NO,11742.0,6,3.0,8.0,8.0,8.0,9.0,6.0,3.0,2.0,19.0,2.0
-NO,11790.0,6,7.0,6.0,5.0,3.0,8.0,6.0,3.0,2.0,25.0,1.0
-NO,11820.0,6,7.0,7.0,9.0,5.0,7.0,7.0,4.0,2.0,34.0,2.0
-NO,11832.0,6,3.0,7.0,5.0,5.0,9.0,6.0,3.0,1.0,46.0,1.0
-NO,11850.0,6,6.0,7.0,7.0,6.0,9.0,4.0,3.0,1.0,57.0,1.0
-NO,11874.0,6,4.0,8.0,8.0,9.0,9.0,5.0,3.0,2.0,65.0,1.0
-NO,11898.0,6,2.0,7.0,7.0,5.0,8.0,7.0,4.0,1.0,42.0,1.0
-NO,11940.0,6,4.0,6.0,6.0,9.0,9.0,4.0,3.0,2.0,93.0,2.0
-NO,11958.0,6,3.0,9.0,9.0,5.0,10.0,6.0,3.0,1.0,16.0,2.0
-NO,11964.0,6,3.0,8.0,8.0,4.0,10.0,3.0,3.0,1.0,62.0,1.0
-NO,11982.0,6,6.0,7.0,6.0,3.0,8.0,5.0,3.0,2.0,24.0,1.0
-NO,12006.0,6,4.0,5.0,5.0,6.0,8.0,6.0,3.0,2.0,69.0,2.0
-NO,12024.0,6,4.0,7.0,6.0,7.0,8.0,5.0,3.0,2.0,33.0,1.0
-NO,12060.0,6,1.0,5.0,5.0,2.0,9.0,3.0,3.0,1.0,67.0,2.0
-NO,12096.0,6,7.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,62.0,1.0
-NO,12102.0,6,7.0,5.0,8.0,3.0,8.0,6.0,3.0,2.0,53.0,1.0
-NO,12132.0,6,4.0,8.0,8.0,6.0,10.0,5.0,5.0,2.0,73.0,1.0
-NO,12156.0,6,3.0,3.0,6.0,5.0,10.0,6.0,3.0,2.0,27.0,1.0
-NO,12198.0,6,4.0,7.0,8.0,6.0,6.0,6.0,2.0,2.0,65.0,1.0
-NO,12228.0,6,6.0,8.0,9.0,5.0,5.0,4.0,2.0,2.0,80.0,
-NO,12240.0,6,7.0,7.0,7.0,5.0,5.0,3.0,1.0,1.0,44.0,2.0
-NO,12264.0,6,4.0,8.0,6.0,7.0,8.0,3.0,3.0,1.0,49.0,1.0
-NO,12270.0,6,3.0,7.0,7.0,8.0,8.0,6.0,3.0,2.0,24.0,2.0
-NO,12300.0,6,3.0,8.0,8.0,5.0,10.0,6.0,3.0,2.0,46.0,1.0
-NO,12306.0,6,2.0,8.0,8.0,6.0,9.0,7.0,4.0,1.0,61.0,1.0
-NO,12318.0,6,7.0,7.0,7.0,5.0,7.0,4.0,2.0,2.0,37.0,2.0
-NO,12324.0,6,6.0,10.0,6.0,7.0,7.0,7.0,5.0,2.0,60.0,2.0
-NO,12330.0,6,5.0,9.0,8.0,6.0,10.0,7.0,3.0,1.0,19.0,1.0
-NO,12372.0,6,3.0,8.0,8.0,5.0,8.0,6.0,2.0,2.0,37.0,1.0
-NO,12402.0,6,7.0,8.0,6.0,5.0,6.0,6.0,3.0,2.0,34.0,2.0
-NO,12426.0,6,3.0,5.0,6.0,7.0,8.0,6.0,3.0,1.0,28.0,2.0
-NO,12516.0,6,2.0,8.0,8.0,7.0,9.0,6.0,4.0,1.0,61.0,1.0
-NO,12570.0,6,4.0,7.0,7.0,5.0,8.0,6.0,3.0,2.0,40.0,1.0
-NO,12594.0,6,7.0,7.0,7.0,8.0,6.0,4.0,3.0,1.0,40.0,2.0
-NO,12606.0,6,4.0,5.0,5.0,7.0,7.0,6.0,1.0,2.0,55.0,1.0
-NO,12612.0,6,5.0,8.0,8.0,5.0,7.0,5.0,2.0,1.0,40.0,1.0
-NO,12618.0,6,2.0,6.0,5.0,7.0,9.0,7.0,4.0,2.0,18.0,2.0
-NO,12648.0,6,7.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,76.0,1.0
-NO,12654.0,6,1.0,9.0,9.0,8.0,9.0,7.0,5.0,1.0,51.0,1.0
-NO,12678.0,6,2.0,9.0,8.0,7.0,8.0,5.0,3.0,1.0,44.0,1.0
-NO,12690.0,6,3.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,57.0,1.0
-NO,12714.0,6,1.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,45.0,1.0
-NO,12762.0,6,1.0,8.0,7.0,5.0,8.0,6.0,2.0,2.0,26.0,1.0
-NO,12774.0,6,5.0,8.0,8.0,7.0,9.0,4.0,3.0,2.0,63.0,1.0
-NO,12798.0,6,3.0,5.0,6.0,8.0,8.0,4.0,2.0,1.0,75.0,1.0
-NO,12810.0,6,4.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,,1.0
-NO,12822.0,6,2.0,5.0,5.0,4.0,10.0,7.0,3.0,2.0,42.0,1.0
-NO,12828.0,6,7.0,5.0,7.0,7.0,9.0,3.0,3.0,2.0,74.0,2.0
-NO,12840.0,6,3.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,50.0,1.0
-NO,12846.0,6,3.0,8.0,8.0,8.0,7.0,6.0,3.0,2.0,49.0,2.0
-NO,12924.0,6,5.0,8.0,7.0,8.0,9.0,6.0,4.0,2.0,80.0,1.0
-NO,12984.0,6,5.0,0.0,0.0,0.0,9.0,7.0,4.0,1.0,34.0,1.0
-NO,13008.0,6,5.0,6.0,7.0,6.0,7.0,6.0,3.0,2.0,67.0,2.0
-NO,13044.0,6,5.0,10.0,10.0,5.0,10.0,6.0,3.0,2.0,51.0,1.0
-NO,13128.0,6,0.0,9.0,9.0,6.0,9.0,7.0,3.0,1.0,18.0,2.0
-NO,13146.0,6,4.0,2.0,2.0,4.0,8.0,7.0,5.0,1.0,48.0,1.0
-NO,13158.0,6,3.0,8.0,7.0,5.0,10.0,4.0,3.0,1.0,76.0,1.0
-NO,13218.0,6,5.0,8.0,8.0,7.0,9.0,6.0,4.0,1.0,35.0,1.0
-NO,13230.0,6,3.0,7.0,6.0,7.0,9.0,6.0,4.0,1.0,64.0,1.0
-NO,13248.0,6,4.0,5.0,5.0,6.0,8.0,5.0,2.0,2.0,38.0,1.0
-NO,13338.0,6,6.0,8.0,7.0,8.0,8.0,6.0,2.0,1.0,67.0,1.0
-NO,13344.0,6,4.0,3.0,7.0,6.0,9.0,7.0,3.0,1.0,53.0,2.0
-NO,13422.0,6,4.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,73.0,1.0
-NO,13440.0,6,4.0,7.0,8.0,5.0,9.0,5.0,3.0,1.0,28.0,2.0
-NO,13464.0,6,4.0,6.0,5.0,3.0,8.0,7.0,3.0,1.0,32.0,1.0
-NO,13470.0,6,3.0,7.0,8.0,7.0,8.0,6.0,4.0,2.0,60.0,1.0
-NO,13482.0,6,2.0,7.0,7.0,7.0,7.0,6.0,2.0,2.0,43.0,1.0
-NO,13488.0,6,5.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,24.0,2.0
-NO,13524.0,6,3.0,7.0,7.0,7.0,8.0,5.0,3.0,1.0,35.0,1.0
-NO,13542.0,6,3.0,8.0,8.0,7.0,10.0,6.0,4.0,2.0,29.0,1.0
-NO,13548.0,6,1.0,5.0,6.0,3.0,8.0,7.0,4.0,1.0,26.0,1.0
-NO,13584.0,6,7.0,6.0,6.0,2.0,9.0,4.0,4.0,1.0,,2.0
-NO,13638.0,6,0.0,7.0,8.0,7.0,9.0,4.0,3.0,2.0,37.0,2.0
-NO,13650.0,6,6.0,7.0,6.0,6.0,10.0,7.0,3.0,2.0,24.0,2.0
-NO,13680.0,6,7.0,8.0,8.0,7.0,8.0,6.0,3.0,1.0,26.0,1.0
-NO,13704.0,6,2.0,3.0,4.0,7.0,10.0,6.0,4.0,1.0,51.0,1.0
-NO,13734.0,6,6.0,3.0,6.0,3.0,8.0,6.0,3.0,1.0,68.0,1.0
-NO,13746.0,6,4.0,8.0,5.0,6.0,8.0,7.0,4.0,1.0,62.0,1.0
-NO,13752.0,6,3.0,8.0,8.0,6.0,8.0,5.0,4.0,2.0,80.0,2.0
-NO,13758.0,6,1.0,8.0,8.0,6.0,7.0,6.0,3.0,2.0,57.0,1.0
-NO,13782.0,6,3.0,9.0,9.0,9.0,10.0,6.0,3.0,2.0,70.0,1.0
-NO,13788.0,6,4.0,8.0,7.0,7.0,8.0,4.0,3.0,2.0,49.0,1.0
-NO,13794.0,6,4.0,8.0,8.0,5.0,8.0,7.0,4.0,1.0,55.0,1.0
-NO,13800.0,6,2.0,7.0,4.0,4.0,9.0,7.0,3.0,1.0,24.0,1.0
-NO,13812.0,6,5.0,5.0,6.0,3.0,8.0,6.0,4.0,2.0,67.0,2.0
-NO,13824.0,6,7.0,7.0,7.0,4.0,8.0,6.0,3.0,2.0,69.0,1.0
-NO,13830.0,6,2.0,9.0,8.0,6.0,8.0,6.0,3.0,1.0,46.0,1.0
-NO,13842.0,6,4.0,6.0,7.0,4.0,9.0,5.0,3.0,2.0,18.0,2.0
-NO,13848.0,6,1.0,6.0,10.0,3.0,7.0,6.0,3.0,1.0,64.0,1.0
-NO,13866.0,6,7.0,4.0,3.0,5.0,6.0,5.0,2.0,1.0,67.0,1.0
-NO,13902.0,6,3.0,5.0,5.0,8.0,6.0,4.0,3.0,1.0,87.0,2.0
-NO,13908.0,6,2.0,7.0,7.0,3.0,8.0,3.0,2.0,1.0,44.0,1.0
-NO,13920.0,6,2.0,6.0,8.0,,7.0,5.0,,1.0,43.0,2.0
-NO,13926.0,6,0.0,4.0,6.0,3.0,7.0,5.0,2.0,1.0,33.0,1.0
-NO,13932.0,6,3.0,7.0,8.0,7.0,9.0,5.0,3.0,1.0,33.0,1.0
-NO,13944.0,6,3.0,8.0,9.0,9.0,8.0,6.0,3.0,1.0,76.0,1.0
-NO,13950.0,6,3.0,8.0,8.0,8.0,9.0,4.0,4.0,2.0,90.0,2.0
-NO,13962.0,6,4.0,7.0,7.0,8.0,9.0,5.0,3.0,1.0,49.0,1.0
-NO,13968.0,6,4.0,4.0,6.0,6.0,6.0,6.0,3.0,1.0,75.0,1.0
-NO,13980.0,6,4.0,5.0,5.0,4.0,10.0,6.0,4.0,1.0,32.0,2.0
-NO,13986.0,6,4.0,7.0,3.0,5.0,9.0,6.0,2.0,2.0,27.0,1.0
-NO,14004.0,6,5.0,7.0,7.0,8.0,9.0,6.0,3.0,2.0,45.0,1.0
-NO,14076.0,6,3.0,5.0,6.0,7.0,7.0,4.0,3.0,2.0,51.0,1.0
-NO,14124.0,6,7.0,9.0,5.0,5.0,9.0,7.0,2.0,2.0,20.0,2.0
-NO,14148.0,6,1.0,9.0,9.0,9.0,9.0,4.0,3.0,1.0,40.0,1.0
-NO,14160.0,6,7.0,8.0,8.0,8.0,7.0,5.0,4.0,1.0,48.0,2.0
-NO,14166.0,6,6.0,8.0,9.0,8.0,10.0,3.0,2.0,2.0,86.0,2.0
-NO,14214.0,6,4.0,7.0,8.0,9.0,9.0,7.0,3.0,2.0,16.0,2.0
-NO,14310.0,6,2.0,8.0,7.0,7.0,10.0,7.0,4.0,2.0,33.0,1.0
-NO,14346.0,6,3.0,7.0,8.0,2.0,9.0,3.0,2.0,1.0,61.0,1.0
-NO,14412.0,6,5.0,8.0,10.0,10.0,8.0,3.0,3.0,1.0,35.0,1.0
-NO,14418.0,6,4.0,9.0,8.0,6.0,8.0,6.0,1.0,2.0,39.0,1.0
-NO,14424.0,6,3.0,7.0,6.0,5.0,7.0,7.0,3.0,2.0,51.0,1.0
-NO,14436.0,6,2.0,8.0,8.0,9.0,10.0,2.0,2.0,1.0,39.0,1.0
-NO,14448.0,6,1.0,8.0,8.0,5.0,8.0,6.0,4.0,1.0,46.0,1.0
-NO,14460.0,6,3.0,7.0,8.0,8.0,9.0,6.0,3.0,1.0,,1.0
-NO,14466.0,6,4.0,8.0,8.0,9.0,8.0,7.0,3.0,2.0,38.0,1.0
-NO,14472.0,6,4.0,8.0,7.0,6.0,8.0,7.0,5.0,1.0,27.0,1.0
-NO,14484.0,6,3.0,7.0,7.0,6.0,9.0,6.0,3.0,1.0,54.0,1.0
-NO,14508.0,6,7.0,8.0,8.0,9.0,9.0,4.0,3.0,2.0,47.0,1.0
-NO,14514.0,6,6.0,7.0,7.0,5.0,10.0,6.0,3.0,1.0,27.0,1.0
-NO,14556.0,6,6.0,7.0,7.0,7.0,8.0,6.0,3.0,1.0,60.0,1.0
-NO,14586.0,6,2.0,7.0,9.0,7.0,8.0,6.0,3.0,1.0,18.0,2.0
-NO,14646.0,6,4.0,5.0,6.0,6.0,10.0,7.0,2.0,2.0,26.0,1.0
-NO,14652.0,6,5.0,7.0,7.0,7.0,8.0,6.0,3.0,1.0,73.0,1.0
-NO,14658.0,6,5.0,7.0,5.0,6.0,9.0,4.0,3.0,2.0,42.0,1.0
-NO,14682.0,6,4.0,8.0,9.0,8.0,8.0,4.0,3.0,1.0,25.0,1.0
-NO,14730.0,6,5.0,6.0,6.0,5.0,9.0,7.0,3.0,1.0,19.0,2.0
-NO,14754.0,6,4.0,7.0,7.0,8.0,8.0,6.0,3.0,1.0,63.0,1.0
-NO,14766.0,6,4.0,9.0,8.0,7.0,10.0,7.0,2.0,2.0,39.0,1.0
-NO,14784.0,6,6.0,8.0,7.0,8.0,9.0,4.0,3.0,1.0,71.0,1.0
-NO,14808.0,6,5.0,8.0,9.0,8.0,8.0,7.0,3.0,2.0,56.0,1.0
-NO,14814.0,6,6.0,7.0,7.0,5.0,8.0,4.0,3.0,2.0,,2.0
-NO,14838.0,6,3.0,7.0,8.0,8.0,9.0,4.0,3.0,1.0,37.0,1.0
-NO,14862.0,6,7.0,9.0,7.0,5.0,,7.0,3.0,2.0,76.0,1.0
-NO,14904.0,6,3.0,8.0,8.0,3.0,5.0,4.0,2.0,2.0,49.0,1.0
-NO,14994.0,6,2.0,9.0,8.0,8.0,9.0,6.0,3.0,1.0,62.0,1.0
-NO,15012.0,6,1.0,8.0,6.0,6.0,7.0,4.0,2.0,1.0,37.0,1.0
-NO,15024.0,6,7.0,10.0,10.0,9.0,10.0,6.0,3.0,2.0,53.0,1.0
-NO,15030.0,6,0.0,9.0,8.0,8.0,9.0,6.0,3.0,1.0,33.0,1.0
-NO,15072.0,6,5.0,8.0,8.0,7.0,7.0,6.0,4.0,1.0,51.0,1.0
-NO,15078.0,6,1.0,8.0,8.0,7.0,8.0,6.0,3.0,1.0,40.0,1.0
-NO,15084.0,6,5.0,8.0,8.0,7.0,8.0,5.0,,1.0,62.0,1.0
-NO,15096.0,6,4.0,6.0,5.0,5.0,10.0,6.0,3.0,2.0,24.0,1.0
-NO,15108.0,6,2.0,6.0,7.0,8.0,9.0,7.0,3.0,1.0,15.0,2.0
-NO,15144.0,6,2.0,3.0,3.0,3.0,4.0,5.0,3.0,2.0,57.0,2.0
-NO,15150.0,6,4.0,8.0,6.0,4.0,9.0,5.0,2.0,1.0,47.0,1.0
-NO,15168.0,6,2.0,3.0,6.0,7.0,10.0,2.0,2.0,1.0,37.0,1.0
-NO,15210.0,6,2.0,9.0,8.0,6.0,8.0,7.0,3.0,2.0,51.0,1.0
-NO,15282.0,6,5.0,8.0,5.0,7.0,8.0,7.0,3.0,1.0,19.0,2.0
-NO,15318.0,6,7.0,5.0,8.0,5.0,7.0,7.0,2.0,2.0,78.0,2.0
-NO,15330.0,6,5.0,7.0,7.0,5.0,6.0,5.0,3.0,2.0,48.0,2.0
-NO,15372.0,6,3.0,7.0,7.0,5.0,8.0,5.0,3.0,1.0,62.0,1.0
-NO,15402.0,6,4.0,5.0,6.0,6.0,6.0,6.0,4.0,2.0,73.0,2.0
-NO,15456.0,6,7.0,7.0,7.0,5.0,8.0,6.0,4.0,1.0,38.0,1.0
-NO,15474.0,6,7.0,4.0,8.0,8.0,6.0,7.0,3.0,2.0,30.0,1.0
-NO,15480.0,6,4.0,6.0,6.0,5.0,7.0,6.0,4.0,1.0,49.0,1.0
-NO,15516.0,6,2.0,7.0,6.0,7.0,8.0,4.0,4.0,2.0,56.0,2.0
-NO,15534.0,6,6.0,5.0,8.0,8.0,8.0,6.0,4.0,1.0,74.0,1.0
-NO,15558.0,6,2.0,7.0,9.0,8.0,10.0,7.0,2.0,1.0,22.0,1.0
-NO,15588.0,6,3.0,6.0,4.0,6.0,10.0,7.0,4.0,1.0,17.0,2.0
-NO,15630.0,6,4.0,8.0,7.0,6.0,8.0,7.0,3.0,1.0,38.0,1.0
-NO,15636.0,6,3.0,5.0,7.0,4.0,9.0,7.0,3.0,2.0,17.0,2.0
-NO,15642.0,6,3.0,5.0,10.0,6.0,10.0,7.0,5.0,2.0,22.0,2.0
-NO,15660.0,6,7.0,2.0,4.0,5.0,10.0,6.0,2.0,1.0,50.0,1.0
-NO,15672.0,6,3.0,7.0,5.0,7.0,7.0,6.0,3.0,1.0,38.0,1.0
-NO,15684.0,6,3.0,7.0,6.0,6.0,10.0,7.0,3.0,2.0,37.0,1.0
-NO,15696.0,6,5.0,8.0,6.0,3.0,7.0,5.0,4.0,1.0,57.0,1.0
-NO,15702.0,6,2.0,7.0,7.0,7.0,8.0,5.0,2.0,2.0,63.0,1.0
-NO,15720.0,6,2.0,8.0,7.0,7.0,8.0,6.0,3.0,2.0,17.0,2.0
-NO,15738.0,6,1.0,0.0,0.0,1.0,4.0,1.0,4.0,1.0,41.0,2.0
-NO,15768.0,6,6.0,7.0,5.0,6.0,9.0,6.0,3.0,1.0,23.0,1.0
-NO,15804.0,6,6.0,6.0,7.0,5.0,5.0,6.0,2.0,1.0,33.0,2.0
-NO,15810.0,6,2.0,7.0,9.0,5.0,9.0,4.0,3.0,1.0,63.0,1.0
-NO,15816.0,6,2.0,6.0,9.0,5.0,8.0,3.0,3.0,2.0,87.0,1.0
-NO,15876.0,6,7.0,9.0,8.0,7.0,8.0,6.0,1.0,1.0,68.0,1.0
-NO,15906.0,6,3.0,3.0,6.0,8.0,9.0,6.0,1.0,1.0,19.0,1.0
-NO,15912.0,6,7.0,5.0,5.0,5.0,8.0,2.0,3.0,2.0,45.0,1.0
-NO,15936.0,6,4.0,7.0,7.0,8.0,8.0,6.0,3.0,2.0,49.0,1.0
-NO,15996.0,6,7.0,8.0,7.0,5.0,7.0,6.0,2.0,1.0,59.0,1.0
-NO,16002.0,6,3.0,7.0,7.0,2.0,8.0,6.0,2.0,1.0,41.0,1.0
-NO,16044.0,6,2.0,7.0,8.0,6.0,8.0,6.0,3.0,1.0,49.0,1.0
-NO,16068.0,6,4.0,6.0,6.0,7.0,7.0,6.0,3.0,1.0,65.0,1.0
-NO,16092.0,6,3.0,9.0,6.0,8.0,10.0,4.0,3.0,1.0,62.0,1.0
-NO,16098.0,6,2.0,4.0,6.0,6.0,8.0,7.0,3.0,1.0,30.0,2.0
-NO,16200.0,6,2.0,8.0,7.0,8.0,9.0,6.0,3.0,1.0,46.0,1.0
-NO,16206.0,6,2.0,8.0,9.0,8.0,9.0,6.0,3.0,1.0,39.0,1.0
-NO,16284.0,6,6.0,5.0,8.0,7.0,10.0,3.0,4.0,2.0,71.0,1.0
-NO,16290.0,6,7.0,1.0,1.0,5.0,9.0,6.0,2.0,1.0,24.0,1.0
-NO,16308.0,6,5.0,8.0,5.0,7.0,7.0,4.0,2.0,2.0,62.0,1.0
-NO,16320.0,6,2.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,37.0,1.0
-NO,16350.0,6,2.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,45.0,1.0
-NO,16356.0,6,4.0,6.0,7.0,7.0,8.0,6.0,3.0,1.0,38.0,1.0
-NO,16374.0,6,4.0,7.0,7.0,3.0,9.0,6.0,3.0,2.0,48.0,1.0
-NO,16422.0,6,6.0,8.0,7.0,4.0,3.0,5.0,3.0,1.0,64.0,2.0
-NO,16470.0,6,5.0,7.0,9.0,8.0,9.0,3.0,5.0,1.0,,1.0
-NO,16488.0,6,2.0,9.0,8.0,8.0,10.0,7.0,4.0,1.0,31.0,1.0
-NO,16500.0,6,3.0,7.0,8.0,7.0,8.0,7.0,3.0,2.0,54.0,1.0
-NO,16506.0,6,2.0,6.0,6.0,7.0,9.0,6.0,3.0,1.0,30.0,1.0
-NO,16512.0,6,2.0,8.0,8.0,7.0,10.0,6.0,4.0,1.0,31.0,1.0
-NO,16518.0,6,3.0,7.0,7.0,6.0,8.0,6.0,4.0,1.0,70.0,1.0
-NO,16524.0,6,1.0,6.0,8.0,6.0,10.0,4.0,3.0,2.0,31.0,1.0
-NO,16548.0,6,3.0,7.0,9.0,6.0,8.0,6.0,3.0,1.0,46.0,2.0
-NO,16566.0,6,2.0,6.0,6.0,6.0,8.0,7.0,3.0,2.0,63.0,1.0
-NO,16572.0,6,3.0,8.0,7.0,8.0,4.0,4.0,2.0,1.0,49.0,2.0
-NO,16584.0,6,4.0,7.0,7.0,8.0,7.0,4.0,3.0,2.0,45.0,1.0
-NO,16638.0,6,2.0,8.0,8.0,4.0,8.0,6.0,2.0,1.0,50.0,1.0
-NO,16644.0,6,2.0,8.0,9.0,7.0,8.0,7.0,4.0,2.0,17.0,2.0
-NO,16680.0,6,2.0,4.0,6.0,8.0,5.0,7.0,2.0,1.0,23.0,2.0
-NO,16692.0,6,7.0,8.0,7.0,8.0,5.0,5.0,2.0,1.0,71.0,1.0
-NO,16698.0,6,5.0,6.0,6.0,3.0,10.0,4.0,1.0,1.0,59.0,1.0
-NO,16740.0,6,1.0,7.0,9.0,4.0,8.0,6.0,3.0,1.0,37.0,1.0
-NO,16746.0,6,4.0,4.0,8.0,5.0,6.0,5.0,3.0,1.0,48.0,1.0
-NO,16770.0,6,2.0,6.0,5.0,7.0,8.0,5.0,4.0,2.0,48.0,2.0
-NO,16776.0,6,5.0,6.0,5.0,5.0,5.0,5.0,3.0,1.0,63.0,1.0
-NO,16824.0,6,2.0,6.0,5.0,4.0,8.0,4.0,3.0,1.0,59.0,1.0
-NO,16836.0,6,4.0,7.0,7.0,5.0,9.0,5.0,3.0,1.0,35.0,1.0
-NO,16860.0,6,5.0,5.0,6.0,10.0,10.0,7.0,3.0,2.0,16.0,2.0
-NO,16950.0,6,1.0,5.0,6.0,6.0,10.0,5.0,3.0,2.0,40.0,1.0
-NO,16968.0,6,5.0,5.0,4.0,2.0,10.0,5.0,3.0,1.0,79.0,1.0
-NO,16974.0,6,2.0,7.0,7.0,8.0,8.0,6.0,3.0,1.0,49.0,1.0
-NO,16980.0,6,2.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,41.0,1.0
-NO,16986.0,6,5.0,7.0,8.0,5.0,10.0,7.0,4.0,1.0,61.0,1.0
-NO,17064.0,6,3.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,41.0,1.0
-NO,17070.0,6,3.0,8.0,7.0,5.0,8.0,4.0,3.0,1.0,54.0,2.0
-NO,17082.0,6,4.0,7.0,7.0,8.0,6.0,5.0,3.0,2.0,65.0,1.0
-NO,17118.0,6,4.0,7.0,6.0,5.0,9.0,6.0,2.0,1.0,29.0,1.0
-NO,17142.0,6,6.0,7.0,7.0,4.0,10.0,6.0,3.0,1.0,70.0,1.0
-NO,17154.0,6,4.0,4.0,3.0,7.0,8.0,7.0,4.0,1.0,38.0,1.0
-NO,17190.0,6,2.0,9.0,9.0,8.0,9.0,6.0,4.0,2.0,73.0,1.0
-NO,17208.0,6,4.0,7.0,7.0,4.0,9.0,4.0,3.0,1.0,49.0,1.0
-NO,17214.0,6,3.0,7.0,6.0,5.0,8.0,4.0,3.0,1.0,46.0,1.0
-NO,17220.0,6,2.0,9.0,9.0,8.0,9.0,5.0,3.0,2.0,34.0,1.0
-NO,17286.0,6,3.0,2.0,2.0,2.0,9.0,4.0,3.0,2.0,56.0,1.0
-NO,17310.0,6,4.0,3.0,6.0,8.0,8.0,6.0,4.0,1.0,60.0,1.0
-NO,17328.0,6,2.0,8.0,8.0,4.0,9.0,6.0,3.0,1.0,47.0,2.0
-NO,17334.0,6,2.0,8.0,9.0,8.0,9.0,7.0,3.0,2.0,43.0,1.0
-NO,17412.0,6,2.0,6.0,8.0,10.0,7.0,5.0,3.0,2.0,75.0,2.0
-NO,17436.0,6,3.0,8.0,8.0,7.0,10.0,7.0,3.0,2.0,43.0,1.0
-NO,17448.0,6,5.0,8.0,8.0,4.0,9.0,6.0,3.0,1.0,43.0,1.0
-NO,17460.0,6,7.0,8.0,,8.0,10.0,7.0,,1.0,55.0,
-NO,17466.0,6,2.0,7.0,5.0,8.0,7.0,6.0,2.0,1.0,47.0,2.0
-NO,17484.0,6,5.0,7.0,10.0,5.0,8.0,3.0,3.0,1.0,74.0,1.0
-NO,17508.0,6,3.0,8.0,7.0,5.0,7.0,5.0,3.0,1.0,31.0,2.0
-NO,17520.0,6,7.0,6.0,8.0,5.0,5.0,3.0,2.0,2.0,59.0,2.0
-NO,17544.0,6,4.0,6.0,6.0,4.0,8.0,7.0,2.0,1.0,38.0,2.0
-NO,17550.0,6,4.0,7.0,7.0,7.0,9.0,7.0,2.0,2.0,37.0,1.0
-NO,17556.0,6,5.0,6.0,8.0,8.0,8.0,6.0,2.0,1.0,42.0,1.0
-NO,17634.0,6,3.0,1.0,1.0,2.0,10.0,6.0,5.0,1.0,47.0,2.0
-NO,17688.0,6,2.0,7.0,8.0,5.0,10.0,6.0,4.0,1.0,38.0,2.0
-NO,17742.0,6,2.0,9.0,9.0,8.0,9.0,5.0,3.0,2.0,46.0,1.0
-NO,17754.0,6,1.0,8.0,8.0,9.0,8.0,6.0,3.0,2.0,41.0,1.0
-NO,17766.0,6,3.0,5.0,4.0,7.0,7.0,7.0,3.0,1.0,26.0,1.0
-NO,17790.0,6,3.0,6.0,6.0,5.0,8.0,4.0,3.0,1.0,32.0,1.0
-NO,17802.0,6,4.0,7.0,9.0,7.0,9.0,3.0,3.0,2.0,60.0,2.0
-NO,17808.0,6,4.0,2.0,5.0,5.0,10.0,4.0,3.0,1.0,51.0,1.0
-NO,17826.0,6,2.0,8.0,8.0,7.0,9.0,4.0,3.0,2.0,64.0,1.0
-NO,17832.0,6,5.0,3.0,4.0,5.0,7.0,3.0,2.0,1.0,23.0,1.0
-NO,17856.0,6,6.0,8.0,8.0,6.0,8.0,6.0,3.0,1.0,30.0,1.0
-NO,17874.0,6,5.0,8.0,8.0,7.0,8.0,5.0,2.0,1.0,42.0,2.0
-NO,17880.0,6,7.0,7.0,7.0,6.0,8.0,5.0,3.0,1.0,61.0,1.0
-NO,17886.0,6,4.0,5.0,5.0,5.0,9.0,6.0,3.0,2.0,60.0,1.0
-NO,17916.0,6,1.0,5.0,5.0,8.0,5.0,7.0,3.0,2.0,29.0,2.0
-NO,17922.0,6,5.0,7.0,7.0,5.0,8.0,6.0,3.0,2.0,44.0,1.0
-NO,17940.0,6,2.0,5.0,5.0,5.0,10.0,3.0,,1.0,81.0,1.0
-NO,17976.0,6,5.0,10.0,10.0,8.0,8.0,7.0,3.0,2.0,41.0,1.0
-NO,18000.0,6,3.0,7.0,5.0,6.0,5.0,6.0,2.0,1.0,45.0,2.0
-NO,18006.0,6,5.0,5.0,4.0,8.0,9.0,4.0,3.0,1.0,72.0,1.0
-NO,18024.0,6,7.0,7.0,7.0,5.0,9.0,5.0,2.0,2.0,61.0,1.0
-NO,18066.0,6,2.0,5.0,2.0,4.0,9.0,6.0,3.0,2.0,31.0,1.0
-NO,18090.0,6,1.0,9.0,9.0,8.0,9.0,6.0,3.0,2.0,43.0,1.0
-NO,18096.0,6,3.0,8.0,8.0,7.0,10.0,7.0,3.0,1.0,19.0,2.0
-NO,18120.0,6,1.0,8.0,8.0,6.0,8.0,7.0,3.0,1.0,18.0,2.0
-NO,18162.0,6,2.0,6.0,6.0,8.0,10.0,7.0,3.0,2.0,46.0,1.0
-NO,18198.0,6,6.0,1.0,5.0,0.0,10.0,6.0,3.0,2.0,75.0,2.0
-NO,18204.0,6,2.0,7.0,7.0,7.0,7.0,6.0,3.0,1.0,36.0,1.0
-NO,18210.0,6,5.0,8.0,10.0,8.0,7.0,6.0,3.0,2.0,52.0,2.0
-NO,18216.0,6,7.0,8.0,9.0,5.0,7.0,2.0,,1.0,86.0,2.0
-NO,18222.0,6,3.0,5.0,8.0,7.0,9.0,6.0,3.0,2.0,23.0,1.0
-NO,18240.0,6,7.0,7.0,10.0,10.0,10.0,4.0,5.0,1.0,46.0,1.0
-NO,18270.0,6,5.0,7.0,7.0,8.0,9.0,6.0,3.0,2.0,32.0,1.0
-NO,18306.0,6,7.0,5.0,5.0,8.0,8.0,7.0,3.0,2.0,58.0,2.0
-NO,18336.0,6,2.0,3.0,5.0,7.0,9.0,7.0,3.0,1.0,16.0,2.0
-NO,18360.0,6,6.0,7.0,8.0,6.0,9.0,4.0,3.0,1.0,21.0,2.0
-NO,18390.0,6,4.0,5.0,7.0,6.0,7.0,6.0,3.0,2.0,54.0,2.0
-NO,18396.0,6,2.0,9.0,9.0,8.0,9.0,6.0,4.0,2.0,83.0,1.0
-NO,18438.0,6,3.0,8.0,7.0,8.0,8.0,6.0,3.0,2.0,79.0,1.0
-NO,18480.0,6,3.0,10.0,8.0,4.0,10.0,3.0,3.0,1.0,52.0,1.0
-NO,18486.0,6,4.0,5.0,7.0,6.0,9.0,6.0,3.0,2.0,35.0,1.0
-NO,18498.0,6,2.0,7.0,7.0,5.0,7.0,6.0,2.0,1.0,67.0,1.0
-NO,18540.0,6,4.0,6.0,9.0,5.0,8.0,6.0,2.0,2.0,39.0,1.0
-NO,18546.0,6,1.0,5.0,4.0,2.0,10.0,6.0,4.0,2.0,19.0,1.0
-NO,18570.0,6,7.0,10.0,10.0,9.0,9.0,6.0,3.0,1.0,82.0,2.0
-NO,18576.0,6,2.0,9.0,9.0,7.0,10.0,7.0,3.0,2.0,47.0,1.0
-NO,18600.0,6,4.0,7.0,7.0,7.0,8.0,6.0,2.0,1.0,32.0,1.0
-NO,18606.0,6,3.0,10.0,10.0,6.0,10.0,6.0,5.0,2.0,79.0,2.0
-NO,18618.0,6,4.0,9.0,9.0,9.0,10.0,7.0,3.0,1.0,65.0,1.0
-NO,18630.0,6,3.0,6.0,7.0,6.0,8.0,7.0,3.0,2.0,51.0,1.0
-NO,18648.0,6,4.0,8.0,8.0,8.0,9.0,6.0,3.0,2.0,61.0,1.0
-NO,18678.0,6,3.0,8.0,8.0,9.0,8.0,6.0,3.0,2.0,26.0,1.0
-NO,18684.0,6,7.0,7.0,7.0,5.0,9.0,7.0,3.0,1.0,70.0,2.0
-NO,18696.0,6,6.0,6.0,7.0,6.0,8.0,6.0,2.0,1.0,28.0,1.0
-NO,18720.0,6,2.0,8.0,8.0,6.0,10.0,6.0,3.0,2.0,59.0,1.0
-NO,18732.0,6,5.0,4.0,3.0,6.0,9.0,7.0,3.0,2.0,20.0,2.0
-NO,18744.0,6,6.0,10.0,5.0,10.0,10.0,6.0,2.0,2.0,24.0,1.0
-NO,18750.0,6,1.0,8.0,7.0,7.0,8.0,7.0,4.0,1.0,20.0,2.0
-NO,18762.0,6,5.0,6.0,8.0,6.0,8.0,6.0,3.0,2.0,74.0,1.0
-NO,18774.0,6,0.0,5.0,9.0,6.0,9.0,4.0,3.0,1.0,43.0,2.0
-NO,18786.0,6,2.0,3.0,3.0,2.0,8.0,7.0,3.0,1.0,50.0,1.0
-NO,18792.0,6,0.0,10.0,8.0,7.0,10.0,7.0,3.0,1.0,24.0,2.0
-NO,18798.0,6,7.0,1.0,4.0,5.0,8.0,6.0,3.0,1.0,46.0,1.0
-NO,18822.0,6,2.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,45.0,1.0
-NO,18834.0,6,2.0,8.0,8.0,7.0,8.0,6.0,3.0,2.0,27.0,1.0
-NO,18846.0,6,2.0,5.0,6.0,8.0,7.0,5.0,3.0,1.0,18.0,2.0
-NO,18858.0,6,7.0,10.0,9.0,10.0,9.0,6.0,3.0,1.0,82.0,2.0
-NO,18876.0,6,5.0,3.0,1.0,5.0,9.0,6.0,3.0,1.0,26.0,2.0
-NO,18894.0,6,4.0,7.0,7.0,6.0,5.0,5.0,2.0,1.0,42.0,2.0
-NO,18900.0,6,3.0,4.0,5.0,6.0,9.0,6.0,3.0,2.0,36.0,1.0
-NO,18912.0,6,4.0,7.0,8.0,7.0,8.0,7.0,3.0,1.0,23.0,2.0
-NO,18918.0,6,6.0,8.0,6.0,7.0,8.0,6.0,2.0,1.0,59.0,1.0
-NO,18942.0,6,2.0,8.0,8.0,9.0,9.0,6.0,3.0,1.0,40.0,1.0
-NO,19014.0,6,5.0,2.0,5.0,7.0,7.0,7.0,4.0,2.0,18.0,2.0
-NO,19020.0,6,2.0,8.0,8.0,7.0,8.0,5.0,2.0,1.0,51.0,1.0
-NO,19038.0,6,3.0,7.0,7.0,8.0,10.0,7.0,3.0,1.0,22.0,2.0
-NO,19056.0,6,5.0,6.0,4.0,7.0,8.0,4.0,3.0,1.0,67.0,1.0
-NO,19068.0,6,4.0,5.0,5.0,6.0,8.0,7.0,1.0,2.0,48.0,1.0
-NO,19092.0,6,6.0,6.0,4.0,8.0,10.0,4.0,3.0,2.0,,1.0
-NO,19104.0,6,5.0,7.0,8.0,5.0,9.0,4.0,4.0,1.0,41.0,1.0
-NO,19122.0,6,4.0,8.0,7.0,7.0,7.0,4.0,3.0,1.0,61.0,1.0
-NO,19140.0,6,2.0,6.0,8.0,7.0,8.0,7.0,3.0,2.0,68.0,1.0
-NO,19146.0,6,1.0,9.0,10.0,8.0,10.0,3.0,2.0,1.0,64.0,1.0
-NO,19152.0,6,1.0,6.0,7.0,6.0,7.0,6.0,3.0,2.0,34.0,1.0
-NO,19170.0,6,4.0,7.0,9.0,8.0,9.0,7.0,3.0,2.0,16.0,2.0
-NO,19218.0,6,2.0,7.0,5.0,4.0,8.0,7.0,3.0,2.0,17.0,2.0
-NO,19254.0,6,6.0,8.0,6.0,4.0,8.0,6.0,2.0,1.0,82.0,1.0
-NO,19278.0,6,2.0,3.0,7.0,7.0,10.0,3.0,3.0,2.0,49.0,1.0
-NO,19284.0,6,7.0,7.0,10.0,10.0,10.0,6.0,4.0,1.0,47.0,1.0
-NO,19308.0,6,3.0,5.0,7.0,3.0,9.0,6.0,3.0,1.0,73.0,1.0
-NO,19320.0,6,5.0,8.0,8.0,8.0,8.0,4.0,3.0,1.0,63.0,1.0
-NO,19326.0,6,2.0,8.0,9.0,9.0,9.0,2.0,3.0,2.0,29.0,1.0
-NO,19332.0,6,6.0,8.0,8.0,8.0,10.0,4.0,2.0,1.0,64.0,1.0
-NO,19404.0,6,7.0,8.0,8.0,6.0,10.0,6.0,3.0,2.0,32.0,1.0
-NO,19416.0,6,5.0,7.0,7.0,7.0,10.0,7.0,4.0,1.0,22.0,2.0
-NO,19422.0,6,6.0,6.0,8.0,6.0,9.0,3.0,3.0,1.0,57.0,1.0
-NO,19464.0,6,1.0,7.0,7.0,6.0,8.0,4.0,4.0,1.0,50.0,1.0
-NO,19500.0,6,5.0,8.0,7.0,7.0,7.0,6.0,3.0,2.0,63.0,1.0
-NO,19524.0,6,2.0,7.0,8.0,6.0,9.0,6.0,3.0,1.0,61.0,1.0
-NO,19548.0,6,2.0,5.0,8.0,4.0,8.0,4.0,4.0,2.0,68.0,1.0
-NO,19596.0,6,5.0,7.0,8.0,5.0,9.0,7.0,3.0,1.0,46.0,1.0
-NO,19626.0,6,3.0,7.0,7.0,7.0,7.0,4.0,2.0,2.0,58.0,1.0
-NO,19638.0,6,4.0,8.0,9.0,9.0,10.0,7.0,3.0,1.0,15.0,2.0
-NO,19656.0,6,7.0,3.0,5.0,6.0,8.0,4.0,3.0,1.0,72.0,1.0
-NO,19662.0,6,3.0,5.0,9.0,9.0,10.0,6.0,3.0,1.0,48.0,1.0
-NO,19680.0,6,1.0,5.0,7.0,5.0,4.0,3.0,2.0,2.0,58.0,1.0
-NO,19686.0,6,6.0,8.0,6.0,5.0,10.0,7.0,3.0,1.0,56.0,1.0
-NO,19704.0,6,2.0,5.0,8.0,8.0,9.0,6.0,3.0,1.0,48.0,1.0
-NO,19710.0,6,4.0,7.0,7.0,5.0,8.0,4.0,3.0,2.0,69.0,1.0
-NO,19716.0,6,6.0,5.0,7.0,4.0,7.0,5.0,2.0,2.0,40.0,1.0
-NO,19734.0,6,6.0,7.0,9.0,5.0,9.0,4.0,3.0,1.0,62.0,1.0
-NO,19752.0,6,1.0,8.0,10.0,7.0,10.0,3.0,1.0,2.0,54.0,2.0
-NO,19758.0,6,0.0,8.0,5.0,5.0,9.0,6.0,4.0,1.0,52.0,1.0
-NO,19764.0,6,6.0,5.0,6.0,3.0,8.0,5.0,2.0,2.0,69.0,1.0
-NO,19776.0,6,7.0,5.0,6.0,6.0,8.0,4.0,2.0,2.0,52.0,2.0
-NO,19824.0,6,5.0,8.0,6.0,3.0,8.0,6.0,2.0,1.0,33.0,2.0
-NO,19836.0,6,4.0,8.0,8.0,7.0,8.0,6.0,3.0,2.0,70.0,2.0
-NO,19842.0,6,4.0,4.0,5.0,4.0,9.0,7.0,3.0,2.0,18.0,2.0
-NO,19872.0,6,3.0,7.0,5.0,5.0,9.0,7.0,3.0,2.0,58.0,1.0
-NO,19884.0,6,7.0,5.0,5.0,6.0,6.0,2.0,2.0,1.0,73.0,1.0
-NO,19890.0,6,4.0,6.0,8.0,8.0,9.0,4.0,4.0,1.0,51.0,1.0
-NO,19896.0,6,6.0,8.0,8.0,7.0,8.0,4.0,2.0,2.0,46.0,2.0
-NO,19902.0,6,4.0,7.0,8.0,6.0,9.0,5.0,3.0,2.0,58.0,1.0
-NO,19908.0,6,7.0,8.0,7.0,8.0,10.0,4.0,1.0,2.0,84.0,1.0
-NO,19950.0,6,2.0,1.0,10.0,0.0,8.0,7.0,2.0,1.0,21.0,2.0
-NO,19968.0,6,5.0,9.0,9.0,8.0,8.0,6.0,3.0,1.0,46.0,2.0
-NO,19980.0,6,2.0,5.0,8.0,8.0,8.0,6.0,3.0,2.0,44.0,1.0
-NO,19998.0,6,4.0,8.0,7.0,9.0,8.0,7.0,3.0,1.0,54.0,1.0
-NO,20022.0,6,3.0,6.0,7.0,6.0,8.0,4.0,3.0,1.0,40.0,1.0
-NO,20034.0,6,4.0,9.0,8.0,7.0,8.0,6.0,4.0,2.0,47.0,2.0
-NO,20076.0,6,4.0,7.0,6.0,6.0,,1.0,3.0,1.0,76.0,2.0
-NO,20088.0,6,5.0,4.0,7.0,5.0,8.0,7.0,2.0,2.0,33.0,1.0
-NO,20142.0,6,5.0,7.0,7.0,7.0,9.0,7.0,3.0,2.0,23.0,1.0
-NO,20154.0,6,4.0,5.0,7.0,4.0,10.0,7.0,5.0,1.0,16.0,2.0
-NO,20166.0,6,4.0,9.0,9.0,7.0,8.0,6.0,2.0,1.0,36.0,2.0
-NO,20262.0,6,3.0,5.0,7.0,7.0,9.0,4.0,2.0,2.0,42.0,1.0
-NO,20286.0,6,5.0,7.0,7.0,8.0,7.0,5.0,3.0,1.0,43.0,1.0
-NO,20316.0,6,5.0,8.0,8.0,6.0,8.0,5.0,3.0,1.0,35.0,2.0
-NO,20328.0,6,0.0,10.0,10.0,10.0,10.0,6.0,3.0,1.0,70.0,1.0
-NO,20352.0,6,2.0,3.0,4.0,2.0,9.0,6.0,4.0,2.0,44.0,1.0
-NO,20358.0,6,5.0,7.0,8.0,9.0,8.0,5.0,4.0,1.0,37.0,1.0
-NO,20370.0,6,7.0,9.0,9.0,8.0,9.0,6.0,3.0,1.0,,2.0
-NO,20394.0,6,5.0,5.0,6.0,5.0,7.0,6.0,3.0,2.0,17.0,2.0
-NO,20400.0,6,5.0,8.0,8.0,7.0,9.0,7.0,3.0,1.0,23.0,2.0
-NO,20412.0,6,5.0,7.0,8.0,8.0,10.0,4.0,2.0,2.0,58.0,1.0
-NO,20418.0,6,4.0,7.0,8.0,8.0,8.0,4.0,3.0,2.0,52.0,1.0
-NO,20424.0,6,5.0,8.0,8.0,6.0,10.0,6.0,3.0,1.0,58.0,1.0
-NO,20436.0,6,2.0,5.0,5.0,7.0,10.0,3.0,2.0,1.0,44.0,2.0
-NO,20442.0,6,2.0,2.0,4.0,0.0,8.0,6.0,3.0,1.0,43.0,2.0
-NO,20448.0,6,0.0,8.0,7.0,9.0,10.0,6.0,4.0,1.0,26.0,2.0
-NO,20460.0,6,1.0,6.0,8.0,7.0,9.0,7.0,3.0,2.0,63.0,1.0
-NO,20466.0,6,5.0,5.0,8.0,6.0,10.0,4.0,2.0,2.0,59.0,1.0
-NO,20478.0,6,5.0,7.0,7.0,5.0,8.0,7.0,3.0,1.0,46.0,1.0
-NO,20484.0,6,6.0,8.0,6.0,6.0,2.0,5.0,2.0,2.0,68.0,2.0
-NO,20496.0,6,3.0,8.0,7.0,7.0,10.0,6.0,3.0,2.0,39.0,1.0
-NO,20508.0,6,2.0,10.0,10.0,10.0,9.0,6.0,3.0,1.0,52.0,1.0
-NO,20514.0,6,7.0,5.0,3.0,5.0,9.0,4.0,3.0,2.0,62.0,1.0
-NO,20526.0,6,5.0,3.0,3.0,2.0,3.0,4.0,2.0,2.0,61.0,2.0
-NO,20568.0,6,1.0,5.0,5.0,5.0,10.0,7.0,2.0,1.0,55.0,1.0
-NO,20580.0,6,4.0,5.0,3.0,5.0,7.0,5.0,3.0,2.0,78.0,2.0
-NO,20586.0,6,3.0,4.0,5.0,4.0,9.0,6.0,3.0,1.0,47.0,1.0
-NO,20640.0,6,3.0,4.0,9.0,4.0,9.0,7.0,2.0,2.0,18.0,2.0
-NO,20646.0,6,7.0,5.0,7.0,6.0,9.0,7.0,3.0,2.0,69.0,1.0
-NO,20688.0,6,3.0,5.0,6.0,8.0,10.0,7.0,3.0,1.0,21.0,2.0
-NO,20730.0,6,6.0,8.0,8.0,5.0,10.0,6.0,3.0,1.0,44.0,1.0
-NO,20742.0,6,6.0,8.0,8.0,6.0,8.0,6.0,3.0,2.0,62.0,1.0
-NO,20772.0,6,4.0,6.0,8.0,8.0,9.0,4.0,2.0,1.0,32.0,1.0
-NO,20778.0,6,7.0,6.0,5.0,3.0,8.0,6.0,3.0,1.0,18.0,2.0
-NO,20808.0,6,7.0,7.0,9.0,5.0,6.0,6.0,3.0,2.0,18.0,2.0
-NO,20862.0,6,4.0,8.0,7.0,7.0,9.0,4.0,2.0,2.0,55.0,1.0
-NO,20892.0,6,2.0,9.0,8.0,8.0,9.0,7.0,5.0,1.0,25.0,2.0
-NO,20910.0,6,4.0,8.0,8.0,8.0,9.0,6.0,3.0,1.0,45.0,1.0
-NO,20922.0,6,5.0,8.0,8.0,8.0,10.0,7.0,4.0,1.0,67.0,2.0
-NO,20928.0,6,5.0,5.0,7.0,5.0,8.0,5.0,3.0,2.0,47.0,1.0
-NO,20934.0,6,6.0,7.0,7.0,4.0,8.0,4.0,3.0,2.0,58.0,1.0
-NO,20970.0,6,2.0,7.0,7.0,3.0,10.0,2.0,3.0,1.0,42.0,1.0
-NO,20988.0,6,1.0,9.0,9.0,5.0,10.0,6.0,5.0,1.0,54.0,1.0
-NO,20994.0,6,5.0,7.0,7.0,4.0,7.0,4.0,3.0,2.0,43.0,1.0
-NO,21042.0,6,0.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,35.0,1.0
-NO,21114.0,6,3.0,5.0,5.0,3.0,7.0,5.0,2.0,1.0,76.0,1.0
-NO,21168.0,6,6.0,7.0,7.0,6.0,8.0,6.0,4.0,2.0,73.0,1.0
-NO,21210.0,6,3.0,6.0,6.0,7.0,9.0,4.0,4.0,2.0,54.0,1.0
-NO,21228.0,6,5.0,7.0,5.0,5.0,7.0,6.0,4.0,1.0,16.0,2.0
-NO,21234.0,6,3.0,7.0,7.0,7.0,7.0,3.0,3.0,2.0,48.0,2.0
-NO,21282.0,6,3.0,8.0,8.0,7.0,9.0,4.0,3.0,2.0,47.0,2.0
-NO,21306.0,6,4.0,9.0,9.0,9.0,7.0,7.0,4.0,2.0,45.0,2.0
-NO,21312.0,6,2.0,7.0,7.0,8.0,8.0,6.0,3.0,2.0,50.0,2.0
-NO,21318.0,6,2.0,8.0,7.0,6.0,9.0,5.0,4.0,1.0,48.0,1.0
-NO,21402.0,6,6.0,5.0,7.0,7.0,8.0,6.0,3.0,2.0,67.0,1.0
-NO,21414.0,6,5.0,7.0,8.0,8.0,9.0,6.0,4.0,1.0,62.0,2.0
-NO,21462.0,6,2.0,5.0,5.0,5.0,10.0,7.0,3.0,1.0,75.0,1.0
-NO,21468.0,6,4.0,7.0,5.0,4.0,8.0,6.0,3.0,1.0,47.0,2.0
-NO,21492.0,6,5.0,8.0,8.0,7.0,1.0,7.0,3.0,2.0,57.0,1.0
-NO,21540.0,6,1.0,5.0,8.0,7.0,9.0,7.0,2.0,2.0,52.0,2.0
-NO,21564.0,6,0.0,6.0,9.0,8.0,10.0,6.0,4.0,2.0,54.0,1.0
-NO,21576.0,6,7.0,4.0,7.0,5.0,8.0,6.0,2.0,2.0,45.0,1.0
-NO,21582.0,6,6.0,3.0,3.0,3.0,6.0,5.0,2.0,1.0,64.0,1.0
-NO,21594.0,6,4.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,54.0,2.0
-NO,21606.0,6,3.0,7.0,7.0,8.0,9.0,5.0,3.0,2.0,40.0,1.0
-NO,21696.0,6,2.0,5.0,7.0,3.0,7.0,7.0,3.0,2.0,20.0,2.0
-NO,21726.0,6,3.0,5.0,5.0,5.0,10.0,7.0,3.0,2.0,22.0,2.0
-NO,21738.0,6,4.0,9.0,9.0,8.0,9.0,4.0,4.0,2.0,71.0,1.0
-NO,21768.0,6,5.0,5.0,4.0,5.0,9.0,6.0,3.0,2.0,43.0,1.0
-NO,21774.0,6,2.0,6.0,7.0,6.0,8.0,6.0,3.0,1.0,63.0,1.0
-NO,21798.0,6,7.0,5.0,6.0,5.0,8.0,6.0,2.0,1.0,23.0,1.0
-NO,21804.0,6,4.0,4.0,7.0,5.0,8.0,6.0,2.0,2.0,35.0,1.0
-NO,21816.0,6,4.0,7.0,9.0,10.0,10.0,6.0,3.0,2.0,17.0,2.0
-NO,21822.0,6,6.0,5.0,4.0,5.0,9.0,6.0,3.0,1.0,51.0,1.0
-NO,21840.0,6,4.0,5.0,7.0,8.0,8.0,6.0,3.0,2.0,17.0,2.0
-NO,21852.0,6,4.0,7.0,7.0,8.0,8.0,4.0,3.0,1.0,52.0,1.0
-NO,21882.0,6,5.0,7.0,7.0,8.0,9.0,6.0,3.0,2.0,55.0,1.0
-NO,21930.0,6,0.0,9.0,5.0,4.0,7.0,3.0,1.0,2.0,18.0,2.0
-NO,21978.0,6,4.0,8.0,8.0,4.0,9.0,7.0,3.0,2.0,70.0,2.0
-NO,21984.0,6,3.0,5.0,7.0,6.0,10.0,6.0,3.0,2.0,26.0,1.0
-NO,22038.0,6,5.0,4.0,5.0,4.0,9.0,6.0,2.0,2.0,21.0,2.0
-NO,22068.0,6,5.0,6.0,4.0,4.0,10.0,6.0,3.0,1.0,73.0,1.0
-NO,22074.0,6,6.0,8.0,5.0,7.0,8.0,6.0,4.0,1.0,67.0,1.0
-NO,22158.0,6,5.0,5.0,6.0,6.0,8.0,3.0,2.0,2.0,49.0,1.0
-NO,22170.0,6,4.0,6.0,7.0,5.0,7.0,4.0,3.0,2.0,39.0,1.0
-NO,22176.0,6,0.0,6.0,5.0,7.0,8.0,6.0,1.0,1.0,22.0,2.0
-NO,22224.0,6,5.0,8.0,9.0,8.0,9.0,4.0,2.0,1.0,,1.0
-NO,22260.0,6,6.0,7.0,10.0,7.0,9.0,4.0,1.0,2.0,23.0,2.0
-NO,22266.0,6,7.0,6.0,8.0,3.0,6.0,6.0,2.0,1.0,81.0,2.0
-NO,22290.0,6,6.0,6.0,8.0,7.0,8.0,6.0,2.0,2.0,34.0,1.0
-NO,22362.0,6,6.0,6.0,7.0,5.0,8.0,5.0,3.0,1.0,59.0,1.0
-NO,22386.0,6,4.0,7.0,5.0,6.0,9.0,6.0,2.0,1.0,68.0,1.0
-NO,22428.0,6,5.0,6.0,5.0,5.0,7.0,6.0,2.0,2.0,38.0,1.0
-NO,6312.0,7,4.0,5.0,7.0,7.0,5.0,6.0,4.0,2.0,46.0,2.0
-NO,6342.0,7,7.0,9.0,8.0,4.0,7.0,2.0,1.0,1.0,74.0,1.0
-NO,6360.0,7,5.0,8.0,7.0,7.0,8.0,4.0,2.0,2.0,82.0,1.0
-NO,6390.0,7,6.0,3.0,5.0,5.0,7.0,3.0,2.0,2.0,64.0,1.0
-NO,6396.0,7,2.0,5.0,8.0,6.0,10.0,4.0,3.0,2.0,43.0,1.0
-NO,6420.0,7,7.0,4.0,7.0,4.0,9.0,4.0,3.0,1.0,59.0,1.0
-NO,6444.0,7,2.0,5.0,5.0,6.0,10.0,6.0,3.0,2.0,21.0,2.0
-NO,6468.0,7,4.0,7.0,5.0,5.0,8.0,7.0,3.0,2.0,52.0,2.0
-NO,6474.0,7,4.0,6.0,7.0,8.0,10.0,4.0,3.0,2.0,63.0,1.0
-NO,6540.0,7,2.0,7.0,7.0,6.0,7.0,2.0,2.0,1.0,44.0,1.0
-NO,6576.0,7,1.0,8.0,6.0,4.0,8.0,7.0,3.0,1.0,26.0,2.0
-NO,6582.0,7,1.0,8.0,8.0,6.0,8.0,6.0,4.0,1.0,33.0,1.0
-NO,6594.0,7,0.0,8.0,7.0,8.0,8.0,5.0,3.0,2.0,58.0,1.0
-NO,6636.0,7,7.0,8.0,7.0,6.0,7.0,4.0,3.0,2.0,73.0,1.0
-NO,6648.0,7,5.0,8.0,8.0,8.0,9.0,6.0,3.0,2.0,58.0,2.0
-NO,6672.0,7,2.0,3.0,7.0,4.0,7.0,6.0,3.0,1.0,23.0,2.0
-NO,6684.0,7,3.0,8.0,7.0,6.0,8.0,5.0,3.0,1.0,56.0,1.0
-NO,6708.0,7,2.0,8.0,8.0,9.0,7.0,6.0,4.0,2.0,25.0,2.0
-NO,6732.0,7,2.0,2.0,7.0,6.0,9.0,6.0,3.0,1.0,23.0,2.0
-NO,6750.0,7,2.0,7.0,6.0,6.0,5.0,7.0,2.0,2.0,19.0,2.0
-NO,6756.0,7,2.0,5.0,6.0,6.0,5.0,7.0,3.0,2.0,20.0,2.0
-NO,6774.0,7,1.0,7.0,5.0,4.0,10.0,4.0,1.0,1.0,33.0,1.0
-NO,6792.0,7,4.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,22.0,2.0
-NO,6798.0,7,6.0,7.0,6.0,5.0,8.0,5.0,3.0,2.0,54.0,1.0
-NO,6816.0,7,6.0,5.0,5.0,6.0,8.0,2.0,2.0,1.0,69.0,2.0
-NO,6846.0,7,0.0,7.0,6.0,5.0,4.0,6.0,2.0,1.0,38.0,2.0
-NO,6870.0,7,5.0,5.0,7.0,3.0,9.0,4.0,4.0,2.0,70.0,1.0
-NO,6882.0,7,3.0,5.0,8.0,4.0,8.0,6.0,4.0,1.0,52.0,1.0
-NO,6888.0,7,3.0,6.0,5.0,8.0,10.0,4.0,3.0,2.0,39.0,1.0
-NO,6918.0,7,5.0,5.0,3.0,4.0,8.0,6.0,4.0,1.0,53.0,1.0
-NO,6936.0,7,0.0,5.0,5.0,3.0,8.0,6.0,5.0,1.0,21.0,2.0
-NO,6966.0,7,7.0,3.0,5.0,5.0,5.0,4.0,2.0,2.0,30.0,1.0
-NO,6984.0,7,3.0,7.0,7.0,8.0,8.0,4.0,3.0,1.0,81.0,2.0
-NO,7002.0,7,4.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,62.0,1.0
-NO,7020.0,7,4.0,8.0,8.0,8.0,5.0,5.0,2.0,2.0,68.0,1.0
-NO,7062.0,7,5.0,4.0,7.0,3.0,9.0,6.0,3.0,1.0,85.0,1.0
-NO,7104.0,7,2.0,9.0,9.0,5.0,9.0,7.0,3.0,1.0,37.0,1.0
-NO,7116.0,7,7.0,5.0,7.0,5.0,8.0,6.0,2.0,1.0,67.0,2.0
-NO,7134.0,7,4.0,7.0,6.0,4.0,10.0,5.0,3.0,1.0,17.0,2.0
-NO,7170.0,7,5.0,8.0,8.0,8.0,8.0,4.0,3.0,1.0,58.0,1.0
-NO,7182.0,7,6.0,5.0,8.0,6.0,8.0,4.0,3.0,2.0,64.0,1.0
-NO,7188.0,7,7.0,6.0,6.0,3.0,7.0,7.0,5.0,1.0,17.0,2.0
-NO,7200.0,7,3.0,7.0,7.0,7.0,8.0,4.0,3.0,2.0,25.0,2.0
-NO,7206.0,7,1.0,10.0,10.0,5.0,8.0,5.0,3.0,2.0,60.0,1.0
-NO,7230.0,7,6.0,6.0,7.0,4.0,8.0,5.0,2.0,1.0,71.0,1.0
-NO,7242.0,7,4.0,5.0,7.0,7.0,8.0,4.0,3.0,2.0,,1.0
-NO,7254.0,7,1.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,18.0,2.0
-NO,7290.0,7,2.0,7.0,7.0,7.0,6.0,4.0,3.0,2.0,24.0,2.0
-NO,7296.0,7,4.0,7.0,7.0,7.0,10.0,7.0,4.0,2.0,79.0,2.0
-NO,7302.0,7,5.0,5.0,7.0,7.0,7.0,4.0,3.0,2.0,33.0,2.0
-NO,7326.0,7,4.0,6.0,7.0,6.0,10.0,4.0,3.0,1.0,42.0,1.0
-NO,7338.0,7,6.0,7.0,6.0,5.0,9.0,4.0,2.0,1.0,65.0,1.0
-NO,7344.0,7,2.0,6.0,8.0,6.0,8.0,4.0,3.0,2.0,50.0,1.0
-NO,7356.0,7,7.0,2.0,8.0,7.0,3.0,6.0,1.0,2.0,91.0,2.0
-NO,7362.0,7,2.0,6.0,6.0,8.0,8.0,7.0,3.0,1.0,21.0,2.0
-NO,7374.0,7,5.0,5.0,8.0,5.0,9.0,6.0,5.0,1.0,,1.0
-NO,7380.0,7,0.0,6.0,8.0,5.0,9.0,4.0,4.0,2.0,33.0,1.0
-NO,7410.0,7,4.0,7.0,7.0,9.0,7.0,4.0,2.0,2.0,58.0,2.0
-NO,7428.0,7,3.0,7.0,7.0,7.0,8.0,5.0,3.0,2.0,67.0,1.0
-NO,7452.0,7,6.0,7.0,5.0,9.0,9.0,6.0,2.0,1.0,37.0,1.0
-NO,7458.0,7,2.0,8.0,8.0,9.0,10.0,6.0,4.0,2.0,42.0,1.0
-NO,7464.0,7,4.0,6.0,6.0,7.0,7.0,6.0,5.0,2.0,17.0,2.0
-NO,7506.0,7,3.0,6.0,9.0,7.0,8.0,4.0,2.0,1.0,43.0,2.0
-NO,7524.0,7,4.0,7.0,7.0,6.0,10.0,7.0,3.0,2.0,49.0,1.0
-NO,7530.0,7,4.0,8.0,8.0,6.0,8.0,6.0,3.0,2.0,86.0,2.0
-NO,7548.0,7,2.0,8.0,8.0,6.0,10.0,4.0,3.0,1.0,64.0,1.0
-NO,7554.0,7,3.0,5.0,8.0,8.0,7.0,4.0,3.0,2.0,30.0,2.0
-NO,7590.0,7,7.0,8.0,9.0,5.0,9.0,6.0,4.0,2.0,82.0,1.0
-NO,7644.0,7,2.0,7.0,7.0,7.0,9.0,6.0,3.0,2.0,40.0,1.0
-NO,7650.0,7,4.0,8.0,8.0,5.0,10.0,6.0,4.0,1.0,68.0,1.0
-NO,7716.0,7,2.0,5.0,8.0,6.0,10.0,4.0,3.0,2.0,42.0,1.0
-NO,7734.0,7,3.0,5.0,4.0,4.0,6.0,3.0,1.0,2.0,50.0,2.0
-NO,7746.0,7,3.0,7.0,6.0,6.0,9.0,5.0,3.0,1.0,34.0,1.0
-NO,7764.0,7,3.0,7.0,8.0,5.0,7.0,6.0,3.0,1.0,44.0,1.0
-NO,7776.0,7,2.0,8.0,8.0,7.0,9.0,4.0,3.0,2.0,46.0,1.0
-NO,7806.0,7,3.0,7.0,7.0,7.0,9.0,5.0,3.0,1.0,33.0,1.0
-NO,7818.0,7,5.0,3.0,3.0,6.0,9.0,4.0,2.0,1.0,58.0,1.0
-NO,7830.0,7,3.0,7.0,7.0,7.0,7.0,3.0,3.0,1.0,,1.0
-NO,7842.0,7,3.0,7.0,7.0,3.0,7.0,4.0,3.0,1.0,65.0,1.0
-NO,7854.0,7,2.0,8.0,8.0,6.0,9.0,5.0,3.0,2.0,51.0,1.0
-NO,7878.0,7,1.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,,1.0
-NO,7908.0,7,4.0,8.0,8.0,7.0,9.0,6.0,4.0,1.0,58.0,1.0
-NO,7914.0,7,3.0,8.0,9.0,8.0,9.0,6.0,3.0,1.0,68.0,1.0
-NO,7932.0,7,3.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,28.0,1.0
-NO,7938.0,7,2.0,8.0,7.0,4.0,8.0,6.0,4.0,1.0,67.0,1.0
-NO,7944.0,7,1.0,7.0,8.0,5.0,8.0,4.0,3.0,1.0,48.0,1.0
-NO,7950.0,7,7.0,7.0,7.0,7.0,9.0,5.0,3.0,2.0,68.0,1.0
-NO,7968.0,7,3.0,6.0,5.0,5.0,9.0,5.0,3.0,2.0,56.0,1.0
-NO,7980.0,7,2.0,8.0,8.0,7.0,7.0,5.0,4.0,2.0,42.0,1.0
-NO,7992.0,7,4.0,5.0,7.0,6.0,9.0,6.0,3.0,1.0,39.0,1.0
-NO,8010.0,7,3.0,8.0,8.0,7.0,8.0,5.0,3.0,2.0,55.0,2.0
-NO,8052.0,7,5.0,6.0,6.0,4.0,8.0,4.0,2.0,1.0,32.0,1.0
-NO,8076.0,7,3.0,9.0,8.0,3.0,9.0,4.0,3.0,1.0,53.0,2.0
-NO,8112.0,7,2.0,8.0,8.0,7.0,9.0,7.0,3.0,1.0,16.0,2.0
-NO,8118.0,7,2.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,50.0,1.0
-NO,8190.0,7,2.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,23.0,2.0
-NO,8202.0,7,2.0,3.0,5.0,3.0,9.0,5.0,2.0,2.0,22.0,1.0
-NO,8226.0,7,4.0,5.0,8.0,7.0,9.0,4.0,3.0,1.0,71.0,1.0
-NO,8250.0,7,3.0,7.0,7.0,8.0,9.0,6.0,4.0,1.0,63.0,1.0
-NO,8274.0,7,4.0,5.0,5.0,4.0,8.0,4.0,3.0,1.0,38.0,2.0
-NO,8286.0,7,2.0,7.0,8.0,6.0,6.0,7.0,3.0,2.0,48.0,2.0
-NO,8292.0,7,3.0,4.0,5.0,3.0,9.0,6.0,3.0,1.0,55.0,2.0
-NO,8322.0,7,7.0,2.0,2.0,2.0,5.0,2.0,1.0,2.0,29.0,1.0
-NO,8340.0,7,2.0,9.0,8.0,6.0,7.0,6.0,3.0,1.0,54.0,2.0
-NO,8364.0,7,4.0,8.0,8.0,8.0,10.0,2.0,3.0,2.0,61.0,1.0
-NO,8376.0,7,7.0,3.0,7.0,7.0,6.0,4.0,3.0,1.0,74.0,1.0
-NO,8412.0,7,6.0,8.0,8.0,7.0,5.0,5.0,3.0,1.0,76.0,2.0
-NO,8478.0,7,2.0,10.0,10.0,6.0,8.0,5.0,3.0,2.0,42.0,1.0
-NO,8496.0,7,3.0,8.0,8.0,5.0,8.0,6.0,4.0,2.0,38.0,2.0
-NO,8532.0,7,1.0,4.0,7.0,9.0,7.0,4.0,2.0,1.0,47.0,1.0
-NO,8568.0,7,3.0,4.0,6.0,3.0,9.0,6.0,3.0,1.0,37.0,2.0
-NO,8586.0,7,4.0,5.0,5.0,5.0,5.0,6.0,5.0,1.0,23.0,2.0
-NO,8592.0,7,3.0,7.0,7.0,4.0,4.0,4.0,2.0,1.0,32.0,2.0
-NO,8598.0,7,1.0,7.0,5.0,6.0,10.0,4.0,2.0,2.0,36.0,1.0
-NO,8604.0,7,5.0,5.0,3.0,6.0,6.0,6.0,3.0,1.0,40.0,2.0
-NO,8616.0,7,7.0,2.0,6.0,3.0,8.0,5.0,3.0,2.0,71.0,1.0
-NO,8622.0,7,6.0,8.0,3.0,3.0,8.0,5.0,4.0,1.0,31.0,1.0
-NO,8628.0,7,4.0,5.0,5.0,4.0,8.0,5.0,1.0,2.0,17.0,2.0
-NO,8658.0,7,3.0,9.0,3.0,0.0,4.0,3.0,2.0,1.0,37.0,2.0
-NO,8724.0,7,5.0,5.0,0.0,6.0,8.0,5.0,3.0,1.0,33.0,2.0
-NO,8742.0,7,3.0,8.0,9.0,3.0,6.0,6.0,2.0,1.0,18.0,2.0
-NO,8796.0,7,5.0,8.0,10.0,8.0,8.0,2.0,2.0,2.0,52.0,1.0
-NO,8820.0,7,5.0,8.0,8.0,8.0,9.0,6.0,4.0,1.0,37.0,1.0
-NO,8826.0,7,4.0,7.0,5.0,7.0,9.0,5.0,3.0,2.0,51.0,1.0
-NO,8838.0,7,6.0,4.0,2.0,3.0,6.0,4.0,1.0,1.0,59.0,1.0
-NO,8886.0,7,3.0,7.0,6.0,8.0,5.0,4.0,2.0,2.0,39.0,1.0
-NO,8916.0,7,2.0,5.0,8.0,6.0,10.0,5.0,5.0,2.0,18.0,2.0
-NO,8922.0,7,6.0,5.0,7.0,5.0,8.0,7.0,4.0,1.0,71.0,1.0
-NO,8952.0,7,7.0,7.0,7.0,5.0,9.0,4.0,2.0,2.0,39.0,1.0
-NO,8988.0,7,6.0,9.0,6.0,7.0,7.0,6.0,2.0,1.0,17.0,2.0
-NO,9006.0,7,6.0,7.0,8.0,5.0,8.0,5.0,2.0,1.0,65.0,1.0
-NO,9018.0,7,3.0,6.0,6.0,7.0,9.0,3.0,2.0,1.0,23.0,1.0
-NO,9024.0,7,1.0,6.0,5.0,5.0,7.0,7.0,3.0,1.0,24.0,2.0
-NO,9042.0,7,5.0,8.0,9.0,8.0,9.0,6.0,4.0,1.0,34.0,1.0
-NO,9054.0,7,7.0,8.0,6.0,3.0,9.0,4.0,2.0,2.0,22.0,2.0
-NO,9072.0,7,4.0,9.0,9.0,7.0,9.0,6.0,5.0,2.0,60.0,2.0
-NO,9090.0,7,1.0,7.0,7.0,3.0,4.0,4.0,3.0,2.0,41.0,1.0
-NO,9108.0,7,7.0,7.0,6.0,5.0,7.0,6.0,3.0,1.0,32.0,2.0
-NO,9114.0,7,3.0,7.0,7.0,8.0,9.0,7.0,3.0,2.0,28.0,1.0
-NO,9144.0,7,2.0,8.0,8.0,8.0,9.0,7.0,3.0,2.0,34.0,1.0
-NO,9168.0,7,2.0,4.0,2.0,3.0,8.0,7.0,4.0,1.0,58.0,1.0
-NO,9180.0,7,4.0,9.0,9.0,5.0,10.0,6.0,3.0,2.0,69.0,1.0
-NO,9222.0,7,4.0,8.0,9.0,9.0,8.0,5.0,3.0,2.0,72.0,1.0
-NO,9276.0,7,2.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,39.0,1.0
-NO,9294.0,7,3.0,9.0,9.0,7.0,9.0,6.0,4.0,2.0,36.0,1.0
-NO,9300.0,7,7.0,5.0,3.0,10.0,8.0,6.0,2.0,1.0,68.0,2.0
-NO,9390.0,7,2.0,8.0,7.0,7.0,8.0,6.0,3.0,1.0,37.0,2.0
-NO,9396.0,7,6.0,7.0,6.0,4.0,10.0,7.0,4.0,1.0,39.0,2.0
-NO,9438.0,7,3.0,9.0,9.0,6.0,9.0,4.0,3.0,2.0,43.0,1.0
-NO,9492.0,7,3.0,8.0,8.0,8.0,8.0,6.0,3.0,2.0,49.0,1.0
-NO,9528.0,7,7.0,8.0,8.0,4.0,7.0,6.0,3.0,2.0,26.0,2.0
-NO,9660.0,7,7.0,8.0,8.0,9.0,9.0,3.0,2.0,1.0,40.0,1.0
-NO,9702.0,7,3.0,6.0,7.0,5.0,7.0,6.0,3.0,2.0,47.0,2.0
-NO,9714.0,7,2.0,7.0,8.0,8.0,8.0,3.0,3.0,1.0,64.0,1.0
-NO,9726.0,7,7.0,8.0,8.0,10.0,8.0,6.0,4.0,1.0,67.0,2.0
-NO,9732.0,7,1.0,8.0,7.0,5.0,6.0,7.0,4.0,1.0,27.0,2.0
-NO,9738.0,7,3.0,8.0,7.0,7.0,8.0,6.0,3.0,1.0,37.0,2.0
-NO,9750.0,7,2.0,5.0,8.0,6.0,7.0,6.0,3.0,1.0,67.0,1.0
-NO,9762.0,7,4.0,5.0,7.0,2.0,7.0,2.0,2.0,1.0,24.0,2.0
-NO,9768.0,7,1.0,10.0,8.0,3.0,8.0,4.0,2.0,1.0,34.0,2.0
-NO,9792.0,7,2.0,9.0,7.0,8.0,8.0,7.0,4.0,2.0,31.0,1.0
-NO,9798.0,7,7.0,6.0,6.0,7.0,9.0,6.0,2.0,1.0,34.0,1.0
-NO,9840.0,7,2.0,8.0,6.0,4.0,10.0,6.0,3.0,2.0,30.0,1.0
-NO,9846.0,7,2.0,5.0,5.0,0.0,10.0,6.0,4.0,1.0,24.0,2.0
-NO,9852.0,7,3.0,9.0,8.0,4.0,10.0,4.0,4.0,1.0,35.0,1.0
-NO,9858.0,7,2.0,8.0,7.0,8.0,7.0,6.0,4.0,2.0,32.0,2.0
-NO,9876.0,7,6.0,8.0,7.0,7.0,7.0,7.0,3.0,1.0,42.0,2.0
-NO,9966.0,7,3.0,5.0,7.0,5.0,8.0,4.0,2.0,2.0,67.0,1.0
-NO,9996.0,7,4.0,6.0,7.0,6.0,7.0,4.0,3.0,1.0,31.0,1.0
-NO,10020.0,7,2.0,8.0,9.0,7.0,8.0,6.0,2.0,2.0,46.0,1.0
-NO,10032.0,7,1.0,6.0,7.0,5.0,7.0,6.0,3.0,2.0,19.0,2.0
-NO,10050.0,7,2.0,5.0,4.0,4.0,8.0,6.0,2.0,2.0,41.0,1.0
-NO,10128.0,7,5.0,6.0,8.0,5.0,9.0,6.0,4.0,1.0,41.0,2.0
-NO,10134.0,7,5.0,4.0,6.0,4.0,6.0,2.0,2.0,2.0,32.0,1.0
-NO,10188.0,7,5.0,7.0,7.0,7.0,9.0,5.0,3.0,1.0,26.0,1.0
-NO,10200.0,7,5.0,7.0,7.0,8.0,8.0,5.0,3.0,2.0,30.0,1.0
-NO,10206.0,7,2.0,8.0,7.0,8.0,8.0,5.0,2.0,2.0,53.0,1.0
-NO,10212.0,7,2.0,8.0,8.0,5.0,9.0,7.0,3.0,2.0,20.0,2.0
-NO,10218.0,7,5.0,7.0,8.0,7.0,8.0,4.0,3.0,2.0,58.0,1.0
-NO,10266.0,7,5.0,6.0,6.0,3.0,9.0,4.0,3.0,2.0,33.0,1.0
-NO,10284.0,7,2.0,3.0,5.0,2.0,4.0,4.0,2.0,1.0,36.0,1.0
-NO,10314.0,7,5.0,10.0,10.0,10.0,10.0,7.0,3.0,2.0,46.0,1.0
-NO,10332.0,7,1.0,8.0,9.0,7.0,9.0,4.0,3.0,1.0,37.0,1.0
-NO,10362.0,7,4.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,52.0,2.0
-NO,10368.0,7,1.0,7.0,7.0,5.0,7.0,6.0,3.0,1.0,45.0,1.0
-NO,10386.0,7,0.0,9.0,8.0,7.0,8.0,6.0,2.0,2.0,33.0,2.0
-NO,10416.0,7,4.0,9.0,8.0,7.0,8.0,7.0,2.0,1.0,44.0,1.0
-NO,10440.0,7,3.0,6.0,6.0,6.0,8.0,6.0,3.0,2.0,71.0,2.0
-NO,10464.0,7,3.0,7.0,3.0,6.0,7.0,6.0,3.0,1.0,28.0,2.0
-NO,10470.0,7,5.0,1.0,5.0,5.0,7.0,4.0,2.0,1.0,67.0,1.0
-NO,10512.0,7,4.0,4.0,5.0,3.0,8.0,6.0,3.0,1.0,59.0,2.0
-NO,10530.0,7,0.0,8.0,8.0,5.0,9.0,7.0,3.0,1.0,22.0,2.0
-NO,10536.0,7,4.0,6.0,8.0,5.0,9.0,6.0,5.0,2.0,83.0,2.0
-NO,10590.0,7,1.0,5.0,3.0,7.0,8.0,3.0,3.0,2.0,56.0,1.0
-NO,10596.0,7,4.0,7.0,8.0,5.0,7.0,6.0,3.0,2.0,28.0,2.0
-NO,10638.0,7,2.0,4.0,5.0,3.0,5.0,4.0,3.0,1.0,45.0,2.0
-NO,10644.0,7,7.0,8.0,7.0,8.0,8.0,7.0,4.0,1.0,36.0,2.0
-NO,10674.0,7,2.0,7.0,6.0,5.0,8.0,3.0,3.0,1.0,47.0,1.0
-NO,10698.0,7,3.0,6.0,7.0,7.0,7.0,4.0,3.0,2.0,61.0,2.0
-NO,10716.0,7,6.0,7.0,8.0,4.0,7.0,7.0,3.0,1.0,19.0,2.0
-NO,10788.0,7,1.0,8.0,4.0,7.0,5.0,3.0,1.0,1.0,53.0,2.0
-NO,10794.0,7,6.0,6.0,7.0,7.0,8.0,6.0,3.0,2.0,44.0,2.0
-NO,10800.0,7,1.0,7.0,5.0,8.0,6.0,6.0,2.0,1.0,18.0,2.0
-NO,10824.0,7,3.0,6.0,8.0,9.0,9.0,5.0,3.0,2.0,61.0,1.0
-NO,10830.0,7,6.0,8.0,7.0,7.0,9.0,6.0,3.0,2.0,63.0,1.0
-NO,10836.0,7,2.0,6.0,5.0,4.0,6.0,6.0,3.0,2.0,19.0,2.0
-NO,10872.0,7,3.0,7.0,7.0,6.0,7.0,6.0,3.0,1.0,48.0,1.0
-NO,10884.0,7,5.0,7.0,6.0,8.0,8.0,4.0,3.0,1.0,70.0,1.0
-NO,10890.0,7,2.0,9.0,9.0,6.0,9.0,7.0,3.0,1.0,21.0,2.0
-NO,10896.0,7,3.0,10.0,8.0,8.0,10.0,6.0,2.0,1.0,52.0,1.0
-NO,10914.0,7,3.0,7.0,7.0,3.0,9.0,7.0,4.0,1.0,33.0,1.0
-NO,10932.0,7,2.0,7.0,7.0,8.0,8.0,3.0,2.0,1.0,44.0,1.0
-NO,10938.0,7,2.0,10.0,7.0,4.0,0.0,7.0,5.0,2.0,41.0,1.0
-NO,10950.0,7,3.0,3.0,4.0,1.0,5.0,6.0,3.0,2.0,19.0,2.0
-NO,10974.0,7,2.0,9.0,8.0,7.0,9.0,6.0,3.0,2.0,56.0,1.0
-NO,10986.0,7,3.0,7.0,8.0,4.0,10.0,6.0,4.0,2.0,22.0,2.0
-NO,11016.0,7,4.0,6.0,6.0,6.0,9.0,4.0,3.0,2.0,56.0,1.0
-NO,11052.0,7,7.0,7.0,7.0,7.0,9.0,6.0,1.0,1.0,68.0,1.0
-NO,11058.0,7,2.0,7.0,7.0,7.0,8.0,7.0,3.0,2.0,46.0,1.0
-NO,11064.0,7,6.0,3.0,8.0,6.0,4.0,6.0,3.0,2.0,19.0,2.0
-NO,11070.0,7,3.0,8.0,8.0,8.0,8.0,6.0,3.0,2.0,44.0,1.0
-NO,11118.0,7,7.0,7.0,8.0,3.0,9.0,6.0,4.0,1.0,69.0,1.0
-NO,11130.0,7,4.0,8.0,8.0,6.0,8.0,7.0,3.0,1.0,67.0,1.0
-NO,11160.0,7,3.0,6.0,7.0,7.0,8.0,5.0,2.0,2.0,15.0,2.0
-NO,11178.0,7,5.0,7.0,8.0,5.0,9.0,5.0,3.0,2.0,28.0,1.0
-NO,11184.0,7,4.0,7.0,7.0,8.0,10.0,6.0,3.0,1.0,37.0,1.0
-NO,11190.0,7,2.0,5.0,5.0,4.0,5.0,4.0,3.0,2.0,71.0,1.0
-NO,11196.0,7,7.0,8.0,7.0,8.0,10.0,5.0,3.0,2.0,55.0,1.0
-NO,11298.0,7,1.0,6.0,5.0,5.0,7.0,7.0,2.0,2.0,51.0,1.0
-NO,11304.0,7,7.0,5.0,8.0,7.0,7.0,6.0,2.0,1.0,71.0,2.0
-NO,11316.0,7,1.0,6.0,6.0,2.0,8.0,6.0,3.0,1.0,55.0,1.0
-NO,11322.0,7,6.0,9.0,8.0,6.0,9.0,7.0,4.0,2.0,23.0,2.0
-NO,11340.0,7,2.0,4.0,8.0,3.0,9.0,6.0,3.0,2.0,53.0,1.0
-NO,11346.0,7,2.0,7.0,7.0,3.0,8.0,7.0,3.0,1.0,47.0,1.0
-NO,11352.0,7,2.0,7.0,9.0,7.0,8.0,5.0,3.0,2.0,43.0,1.0
-NO,11382.0,7,7.0,7.0,3.0,1.0,8.0,6.0,3.0,1.0,49.0,1.0
-NO,11388.0,7,6.0,6.0,7.0,8.0,8.0,7.0,3.0,1.0,40.0,1.0
-NO,11412.0,7,4.0,8.0,9.0,8.0,9.0,7.0,3.0,2.0,58.0,1.0
-NO,11430.0,7,3.0,7.0,5.0,6.0,8.0,6.0,3.0,1.0,22.0,2.0
-NO,11454.0,7,5.0,7.0,,7.0,8.0,6.0,3.0,2.0,90.0,2.0
-NO,11466.0,7,5.0,7.0,8.0,6.0,9.0,6.0,3.0,1.0,35.0,1.0
-NO,11478.0,7,4.0,5.0,10.0,3.0,10.0,5.0,4.0,1.0,48.0,1.0
-NO,11484.0,7,7.0,7.0,8.0,10.0,9.0,6.0,3.0,2.0,52.0,2.0
-NO,11562.0,7,7.0,7.0,7.0,5.0,9.0,7.0,3.0,1.0,46.0,2.0
-NO,11568.0,7,4.0,8.0,8.0,7.0,9.0,7.0,3.0,1.0,37.0,1.0
-NO,11586.0,7,3.0,7.0,4.0,5.0,9.0,7.0,3.0,2.0,17.0,2.0
-NO,11598.0,7,4.0,6.0,7.0,3.0,9.0,4.0,3.0,1.0,52.0,1.0
-NO,11604.0,7,4.0,3.0,8.0,8.0,8.0,7.0,3.0,1.0,47.0,1.0
-NO,11622.0,7,1.0,9.0,6.0,8.0,6.0,7.0,3.0,1.0,78.0,2.0
-NO,11628.0,7,5.0,5.0,8.0,2.0,7.0,5.0,4.0,1.0,62.0,1.0
-NO,11640.0,7,2.0,8.0,9.0,5.0,7.0,7.0,3.0,2.0,36.0,1.0
-NO,11676.0,7,4.0,9.0,8.0,7.0,8.0,7.0,3.0,2.0,56.0,1.0
-NO,11694.0,7,5.0,8.0,10.0,9.0,8.0,6.0,4.0,2.0,69.0,2.0
-NO,11718.0,7,3.0,7.0,7.0,6.0,8.0,7.0,3.0,1.0,54.0,2.0
-NO,11724.0,7,3.0,6.0,7.0,7.0,7.0,6.0,3.0,2.0,16.0,2.0
-NO,11730.0,7,5.0,8.0,8.0,5.0,8.0,6.0,3.0,2.0,34.0,1.0
-NO,11742.0,7,1.0,7.0,6.0,8.0,8.0,6.0,4.0,1.0,44.0,1.0
-NO,11790.0,7,4.0,7.0,6.0,7.0,9.0,5.0,3.0,1.0,56.0,1.0
-NO,11820.0,7,2.0,10.0,10.0,7.0,8.0,6.0,4.0,1.0,74.0,2.0
-NO,11832.0,7,1.0,8.0,8.0,4.0,7.0,7.0,4.0,1.0,22.0,2.0
-NO,11850.0,7,7.0,7.0,7.0,8.0,8.0,6.0,2.0,2.0,64.0,1.0
-NO,11874.0,7,3.0,1.0,4.0,4.0,8.0,6.0,3.0,2.0,68.0,2.0
-NO,11898.0,7,4.0,6.0,8.0,7.0,9.0,4.0,3.0,2.0,58.0,1.0
-NO,11940.0,7,5.0,6.0,3.0,4.0,7.0,6.0,3.0,1.0,64.0,2.0
-NO,11958.0,7,2.0,6.0,8.0,4.0,8.0,7.0,4.0,1.0,16.0,2.0
-NO,11964.0,7,5.0,7.0,7.0,7.0,5.0,5.0,3.0,1.0,73.0,2.0
-NO,11982.0,7,2.0,7.0,6.0,9.0,10.0,6.0,3.0,1.0,48.0,1.0
-NO,12006.0,7,4.0,8.0,5.0,7.0,6.0,4.0,3.0,1.0,43.0,1.0
-NO,12024.0,7,3.0,8.0,7.0,6.0,8.0,6.0,3.0,2.0,40.0,2.0
-NO,12060.0,7,3.0,7.0,8.0,8.0,7.0,6.0,4.0,2.0,80.0,2.0
-NO,12096.0,7,1.0,8.0,9.0,8.0,9.0,7.0,3.0,1.0,16.0,2.0
-NO,12102.0,7,7.0,6.0,6.0,6.0,9.0,4.0,2.0,2.0,70.0,1.0
-NO,12132.0,7,6.0,7.0,7.0,5.0,5.0,4.0,2.0,2.0,56.0,1.0
-NO,12156.0,7,3.0,9.0,8.0,5.0,10.0,4.0,2.0,1.0,71.0,2.0
-NO,12198.0,7,4.0,5.0,9.0,3.0,10.0,6.0,2.0,2.0,70.0,1.0
-NO,12228.0,7,5.0,7.0,7.0,8.0,9.0,6.0,4.0,1.0,43.0,1.0
-NO,12240.0,7,2.0,5.0,7.0,5.0,8.0,7.0,3.0,1.0,53.0,1.0
-NO,12264.0,7,2.0,9.0,8.0,4.0,8.0,4.0,3.0,2.0,56.0,1.0
-NO,12270.0,7,7.0,10.0,10.0,6.0,10.0,6.0,4.0,1.0,87.0,1.0
-NO,12300.0,7,1.0,7.0,8.0,7.0,8.0,4.0,3.0,2.0,34.0,1.0
-NO,12306.0,7,6.0,5.0,5.0,3.0,8.0,6.0,3.0,2.0,24.0,2.0
-NO,12318.0,7,6.0,8.0,8.0,5.0,9.0,6.0,3.0,2.0,67.0,1.0
-NO,12324.0,7,4.0,3.0,3.0,6.0,7.0,5.0,2.0,1.0,39.0,2.0
-NO,12330.0,7,4.0,8.0,9.0,6.0,9.0,6.0,3.0,1.0,46.0,1.0
-NO,12372.0,7,1.0,7.0,8.0,6.0,8.0,7.0,3.0,1.0,47.0,1.0
-NO,12402.0,7,3.0,5.0,5.0,8.0,8.0,7.0,3.0,1.0,41.0,1.0
-NO,12426.0,7,6.0,5.0,9.0,3.0,8.0,4.0,2.0,2.0,32.0,1.0
-NO,12516.0,7,4.0,7.0,7.0,8.0,9.0,4.0,2.0,2.0,41.0,2.0
-NO,12570.0,7,2.0,8.0,8.0,7.0,10.0,7.0,4.0,1.0,69.0,1.0
-NO,12594.0,7,0.0,10.0,10.0,8.0,10.0,7.0,5.0,1.0,65.0,2.0
-NO,12606.0,7,6.0,8.0,7.0,9.0,8.0,6.0,3.0,1.0,48.0,1.0
-NO,12612.0,7,5.0,8.0,8.0,9.0,8.0,4.0,3.0,2.0,47.0,2.0
-NO,12618.0,7,5.0,5.0,4.0,6.0,9.0,2.0,2.0,2.0,35.0,2.0
-NO,12648.0,7,4.0,5.0,10.0,8.0,6.0,2.0,2.0,2.0,43.0,1.0
-NO,12654.0,7,2.0,10.0,9.0,7.0,10.0,4.0,2.0,1.0,49.0,1.0
-NO,12678.0,7,3.0,5.0,8.0,8.0,7.0,4.0,2.0,1.0,78.0,2.0
-NO,12690.0,7,5.0,6.0,6.0,6.0,5.0,2.0,2.0,2.0,52.0,2.0
-NO,12714.0,7,1.0,9.0,9.0,5.0,8.0,3.0,3.0,1.0,57.0,1.0
-NO,12762.0,7,1.0,7.0,9.0,7.0,8.0,1.0,3.0,1.0,45.0,1.0
-NO,12774.0,7,4.0,8.0,7.0,6.0,9.0,6.0,2.0,1.0,60.0,1.0
-NO,12798.0,7,6.0,2.0,0.0,10.0,3.0,4.0,3.0,2.0,74.0,2.0
-NO,12810.0,7,2.0,10.0,8.0,8.0,9.0,6.0,4.0,2.0,69.0,2.0
-NO,12822.0,7,2.0,5.0,4.0,6.0,7.0,7.0,3.0,2.0,47.0,1.0
-NO,12828.0,7,0.0,5.0,5.0,3.0,10.0,6.0,2.0,1.0,41.0,1.0
-NO,12840.0,7,7.0,6.0,5.0,3.0,4.0,4.0,2.0,2.0,59.0,1.0
-NO,12846.0,7,4.0,8.0,6.0,8.0,9.0,7.0,3.0,2.0,18.0,2.0
-NO,12924.0,7,3.0,5.0,7.0,7.0,8.0,4.0,3.0,1.0,44.0,2.0
-NO,12984.0,7,4.0,5.0,6.0,7.0,8.0,7.0,4.0,1.0,64.0,1.0
-NO,13008.0,7,2.0,8.0,8.0,9.0,7.0,5.0,2.0,1.0,53.0,2.0
-NO,13044.0,7,2.0,8.0,8.0,7.0,10.0,6.0,3.0,1.0,59.0,1.0
-NO,13128.0,7,4.0,7.0,5.0,6.0,7.0,4.0,2.0,1.0,34.0,1.0
-NO,13146.0,7,1.0,5.0,7.0,8.0,10.0,7.0,2.0,2.0,50.0,2.0
-NO,13158.0,7,5.0,5.0,6.0,6.0,8.0,6.0,3.0,2.0,53.0,2.0
-NO,13218.0,7,2.0,8.0,7.0,7.0,6.0,7.0,3.0,2.0,23.0,1.0
-NO,13230.0,7,5.0,7.0,5.0,6.0,5.0,5.0,2.0,1.0,63.0,1.0
-NO,13248.0,7,4.0,6.0,6.0,8.0,8.0,7.0,4.0,2.0,56.0,2.0
-NO,13338.0,7,3.0,7.0,9.0,7.0,9.0,6.0,2.0,1.0,38.0,1.0
-NO,13344.0,7,4.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,42.0,1.0
-NO,13422.0,7,5.0,7.0,6.0,4.0,10.0,5.0,3.0,1.0,67.0,1.0
-NO,13440.0,7,5.0,7.0,7.0,4.0,9.0,5.0,3.0,2.0,19.0,2.0
-NO,13464.0,7,6.0,10.0,10.0,3.0,8.0,6.0,4.0,1.0,47.0,1.0
-NO,13470.0,7,1.0,7.0,7.0,7.0,5.0,7.0,3.0,1.0,16.0,2.0
-NO,13482.0,7,3.0,7.0,8.0,10.0,7.0,6.0,3.0,1.0,46.0,2.0
-NO,13488.0,7,2.0,7.0,7.0,3.0,10.0,7.0,3.0,1.0,21.0,2.0
-NO,13524.0,7,5.0,5.0,7.0,7.0,8.0,7.0,3.0,2.0,16.0,2.0
-NO,13542.0,7,3.0,8.0,8.0,4.0,8.0,3.0,2.0,1.0,52.0,1.0
-NO,13548.0,7,0.0,3.0,7.0,5.0,7.0,3.0,2.0,1.0,31.0,1.0
-NO,13584.0,7,2.0,9.0,8.0,9.0,10.0,7.0,3.0,1.0,18.0,2.0
-NO,13638.0,7,2.0,8.0,8.0,5.0,5.0,5.0,2.0,1.0,21.0,2.0
-NO,13650.0,7,3.0,4.0,2.0,6.0,7.0,3.0,1.0,2.0,60.0,1.0
-NO,13680.0,7,2.0,5.0,2.0,6.0,9.0,6.0,4.0,1.0,75.0,1.0
-NO,13704.0,7,4.0,7.0,8.0,7.0,5.0,6.0,3.0,2.0,17.0,2.0
-NO,13734.0,7,6.0,5.0,3.0,4.0,7.0,6.0,2.0,1.0,19.0,2.0
-NO,13746.0,7,5.0,7.0,9.0,8.0,9.0,6.0,2.0,2.0,68.0,2.0
-NO,13752.0,7,2.0,9.0,9.0,9.0,10.0,7.0,3.0,2.0,62.0,1.0
-NO,13758.0,7,2.0,8.0,8.0,7.0,6.0,4.0,3.0,2.0,39.0,1.0
-NO,13782.0,7,7.0,6.0,8.0,4.0,6.0,6.0,4.0,1.0,18.0,2.0
-NO,13788.0,7,3.0,8.0,8.0,8.0,7.0,6.0,5.0,2.0,52.0,1.0
-NO,13794.0,7,5.0,8.0,6.0,7.0,8.0,7.0,3.0,2.0,20.0,2.0
-NO,13800.0,7,4.0,4.0,4.0,3.0,6.0,4.0,4.0,1.0,44.0,2.0
-NO,13812.0,7,4.0,8.0,7.0,3.0,9.0,6.0,3.0,2.0,71.0,1.0
-NO,13824.0,7,6.0,8.0,10.0,5.0,10.0,4.0,1.0,2.0,47.0,2.0
-NO,13830.0,7,3.0,7.0,7.0,6.0,7.0,6.0,3.0,1.0,49.0,1.0
-NO,13842.0,7,1.0,8.0,9.0,8.0,8.0,4.0,3.0,1.0,72.0,1.0
-NO,13848.0,7,1.0,9.0,9.0,6.0,9.0,6.0,4.0,2.0,53.0,2.0
-NO,13866.0,7,3.0,8.0,9.0,8.0,7.0,4.0,3.0,2.0,62.0,1.0
-NO,13902.0,7,0.0,9.0,9.0,10.0,10.0,7.0,3.0,1.0,21.0,2.0
-NO,13908.0,7,4.0,8.0,8.0,9.0,9.0,6.0,3.0,2.0,48.0,1.0
-NO,13920.0,7,5.0,7.0,7.0,8.0,8.0,4.0,3.0,2.0,42.0,1.0
-NO,13926.0,7,1.0,7.0,7.0,7.0,9.0,4.0,2.0,1.0,44.0,1.0
-NO,13932.0,7,0.0,7.0,8.0,6.0,6.0,7.0,4.0,1.0,24.0,2.0
-NO,13944.0,7,2.0,9.0,8.0,8.0,10.0,6.0,3.0,2.0,44.0,1.0
-NO,13950.0,7,3.0,9.0,9.0,9.0,8.0,6.0,3.0,1.0,58.0,1.0
-NO,13962.0,7,0.0,6.0,6.0,7.0,10.0,3.0,2.0,2.0,36.0,2.0
-NO,13968.0,7,6.0,9.0,7.0,8.0,7.0,7.0,4.0,2.0,67.0,2.0
-NO,13980.0,7,5.0,6.0,9.0,5.0,7.0,6.0,3.0,2.0,28.0,1.0
-NO,13986.0,7,7.0,6.0,6.0,7.0,8.0,7.0,4.0,1.0,17.0,2.0
-NO,14004.0,7,7.0,4.0,6.0,5.0,3.0,6.0,2.0,2.0,19.0,2.0
-NO,14076.0,7,4.0,5.0,8.0,6.0,8.0,6.0,3.0,2.0,21.0,2.0
-NO,14124.0,7,4.0,8.0,8.0,6.0,8.0,4.0,3.0,2.0,78.0,2.0
-NO,14148.0,7,2.0,7.0,8.0,5.0,7.0,5.0,3.0,2.0,43.0,1.0
-NO,14160.0,7,3.0,5.0,4.0,6.0,7.0,6.0,3.0,1.0,38.0,1.0
-NO,14166.0,7,4.0,10.0,9.0,7.0,9.0,7.0,3.0,1.0,44.0,1.0
-NO,14214.0,7,5.0,7.0,7.0,5.0,7.0,5.0,3.0,1.0,57.0,1.0
-NO,14310.0,7,2.0,7.0,7.0,5.0,8.0,6.0,3.0,2.0,71.0,1.0
-NO,14346.0,7,1.0,9.0,7.0,8.0,7.0,4.0,2.0,2.0,50.0,2.0
-NO,14412.0,7,4.0,8.0,8.0,8.0,7.0,6.0,5.0,1.0,63.0,1.0
-NO,14418.0,7,1.0,6.0,10.0,5.0,7.0,4.0,2.0,1.0,55.0,1.0
-NO,14424.0,7,3.0,5.0,7.0,7.0,10.0,7.0,3.0,1.0,49.0,1.0
-NO,14436.0,7,5.0,10.0,9.0,9.0,9.0,5.0,2.0,2.0,71.0,1.0
-NO,14448.0,7,1.0,5.0,3.0,3.0,8.0,7.0,4.0,2.0,43.0,1.0
-NO,14460.0,7,1.0,9.0,7.0,9.0,9.0,5.0,2.0,1.0,54.0,1.0
-NO,14466.0,7,2.0,8.0,7.0,8.0,9.0,7.0,3.0,1.0,42.0,1.0
-NO,14472.0,7,6.0,7.0,7.0,6.0,7.0,4.0,2.0,1.0,55.0,1.0
-NO,14484.0,7,7.0,7.0,7.0,8.0,8.0,4.0,3.0,2.0,69.0,2.0
-NO,14508.0,7,3.0,6.0,9.0,7.0,7.0,7.0,3.0,2.0,17.0,2.0
-NO,14514.0,7,4.0,5.0,8.0,5.0,7.0,3.0,2.0,1.0,56.0,1.0
-NO,14556.0,7,4.0,7.0,3.0,7.0,10.0,6.0,1.0,1.0,48.0,1.0
-NO,14586.0,7,7.0,9.0,10.0,7.0,8.0,5.0,2.0,2.0,67.0,1.0
-NO,14646.0,7,3.0,8.0,8.0,5.0,4.0,5.0,3.0,2.0,35.0,1.0
-NO,14652.0,7,4.0,5.0,3.0,5.0,5.0,4.0,3.0,1.0,,1.0
-NO,14658.0,7,6.0,8.0,8.0,7.0,9.0,5.0,3.0,2.0,47.0,1.0
-NO,14682.0,7,3.0,8.0,8.0,9.0,9.0,4.0,3.0,2.0,41.0,1.0
-NO,14730.0,7,4.0,4.0,3.0,3.0,4.0,6.0,1.0,2.0,46.0,1.0
-NO,14754.0,7,2.0,7.0,8.0,4.0,8.0,6.0,2.0,1.0,27.0,1.0
-NO,14766.0,7,0.0,5.0,8.0,9.0,9.0,5.0,3.0,1.0,49.0,1.0
-NO,14784.0,7,0.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,93.0,1.0
-NO,14808.0,7,2.0,7.0,5.0,8.0,9.0,6.0,3.0,1.0,21.0,2.0
-NO,14814.0,7,6.0,8.0,8.0,8.0,8.0,3.0,2.0,2.0,63.0,1.0
-NO,14838.0,7,3.0,5.0,6.0,6.0,10.0,5.0,4.0,1.0,40.0,1.0
-NO,14862.0,7,0.0,7.0,10.0,3.0,10.0,4.0,4.0,2.0,74.0,2.0
-NO,14904.0,7,1.0,5.0,5.0,7.0,6.0,6.0,2.0,1.0,43.0,1.0
-NO,14994.0,7,7.0,6.0,5.0,7.0,8.0,6.0,1.0,2.0,,2.0
-NO,15012.0,7,6.0,0.0,2.0,2.0,8.0,6.0,4.0,2.0,61.0,2.0
-NO,15024.0,7,3.0,4.0,7.0,5.0,9.0,7.0,3.0,1.0,33.0,2.0
-NO,15030.0,7,0.0,6.0,6.0,5.0,8.0,6.0,4.0,1.0,56.0,1.0
-NO,15072.0,7,4.0,8.0,8.0,7.0,5.0,6.0,4.0,2.0,,1.0
-NO,15078.0,7,5.0,9.0,9.0,5.0,8.0,7.0,3.0,2.0,61.0,2.0
-NO,15084.0,7,3.0,9.0,9.0,6.0,9.0,6.0,4.0,1.0,65.0,1.0
-NO,15096.0,7,5.0,8.0,8.0,6.0,7.0,7.0,2.0,2.0,40.0,1.0
-NO,15108.0,7,4.0,7.0,7.0,7.0,8.0,3.0,2.0,1.0,55.0,1.0
-NO,15144.0,7,1.0,6.0,0.0,3.0,10.0,7.0,5.0,2.0,48.0,2.0
-NO,15150.0,7,7.0,7.0,8.0,7.0,10.0,4.0,2.0,1.0,72.0,1.0
-NO,15168.0,7,5.0,8.0,7.0,8.0,8.0,6.0,3.0,1.0,43.0,1.0
-NO,15210.0,7,2.0,7.0,7.0,6.0,8.0,6.0,3.0,1.0,40.0,1.0
-NO,15282.0,7,1.0,6.0,7.0,5.0,6.0,6.0,3.0,1.0,48.0,1.0
-NO,15318.0,7,6.0,7.0,7.0,7.0,9.0,4.0,2.0,1.0,50.0,2.0
-NO,15330.0,7,3.0,8.0,8.0,8.0,9.0,6.0,3.0,1.0,22.0,2.0
-NO,15372.0,7,2.0,8.0,9.0,9.0,8.0,7.0,3.0,1.0,53.0,1.0
-NO,15402.0,7,2.0,5.0,6.0,6.0,9.0,4.0,3.0,1.0,73.0,1.0
-NO,15456.0,7,4.0,8.0,9.0,5.0,7.0,4.0,3.0,1.0,54.0,2.0
-NO,15474.0,7,6.0,7.0,5.0,8.0,8.0,5.0,3.0,1.0,39.0,1.0
-NO,15480.0,7,3.0,8.0,8.0,7.0,8.0,6.0,3.0,2.0,34.0,1.0
-NO,15516.0,7,4.0,3.0,6.0,6.0,8.0,6.0,3.0,1.0,50.0,2.0
-NO,15534.0,7,5.0,7.0,7.0,4.0,8.0,6.0,3.0,2.0,59.0,1.0
-NO,15558.0,7,5.0,8.0,7.0,5.0,8.0,6.0,3.0,2.0,26.0,2.0
-NO,15588.0,7,1.0,6.0,7.0,6.0,9.0,6.0,3.0,2.0,29.0,1.0
-NO,15630.0,7,7.0,1.0,5.0,2.0,9.0,3.0,5.0,1.0,69.0,1.0
-NO,15636.0,7,6.0,5.0,5.0,3.0,8.0,7.0,4.0,2.0,29.0,1.0
-NO,15642.0,7,3.0,7.0,5.0,5.0,8.0,7.0,5.0,2.0,19.0,2.0
-NO,15660.0,7,3.0,7.0,7.0,7.0,8.0,5.0,3.0,1.0,42.0,1.0
-NO,15672.0,7,6.0,8.0,8.0,5.0,8.0,5.0,3.0,1.0,63.0,1.0
-NO,15684.0,7,3.0,7.0,6.0,6.0,8.0,7.0,4.0,2.0,18.0,2.0
-NO,15696.0,7,7.0,9.0,6.0,8.0,7.0,6.0,1.0,2.0,47.0,
-NO,15702.0,7,2.0,4.0,4.0,3.0,6.0,4.0,3.0,1.0,31.0,1.0
-NO,15720.0,7,4.0,5.0,7.0,6.0,9.0,5.0,3.0,2.0,53.0,1.0
-NO,15738.0,7,5.0,8.0,9.0,8.0,8.0,6.0,3.0,1.0,67.0,2.0
-NO,15768.0,7,7.0,9.0,7.0,5.0,9.0,7.0,3.0,1.0,24.0,2.0
-NO,15804.0,7,3.0,6.0,5.0,4.0,8.0,6.0,4.0,1.0,39.0,1.0
-NO,15810.0,7,1.0,4.0,6.0,4.0,7.0,5.0,2.0,2.0,59.0,1.0
-NO,15816.0,7,1.0,9.0,9.0,7.0,9.0,6.0,4.0,2.0,33.0,1.0
-NO,15876.0,7,3.0,3.0,5.0,7.0,7.0,2.0,1.0,1.0,49.0,1.0
-NO,15906.0,7,0.0,5.0,5.0,3.0,9.0,6.0,2.0,1.0,22.0,2.0
-NO,15912.0,7,3.0,7.0,7.0,,7.0,4.0,2.0,1.0,51.0,1.0
-NO,15936.0,7,0.0,8.0,8.0,9.0,8.0,6.0,2.0,2.0,40.0,1.0
-NO,15996.0,7,7.0,5.0,3.0,7.0,1.0,7.0,3.0,2.0,17.0,2.0
-NO,16002.0,7,1.0,7.0,7.0,5.0,8.0,4.0,2.0,2.0,42.0,1.0
-NO,16044.0,7,4.0,7.0,6.0,6.0,8.0,7.0,2.0,1.0,31.0,2.0
-NO,16068.0,7,2.0,6.0,6.0,5.0,8.0,6.0,4.0,1.0,42.0,1.0
-NO,16092.0,7,4.0,8.0,7.0,3.0,8.0,4.0,4.0,1.0,53.0,1.0
-NO,16098.0,7,5.0,6.0,6.0,5.0,8.0,3.0,3.0,1.0,73.0,1.0
-NO,16200.0,7,7.0,3.0,5.0,5.0,10.0,6.0,2.0,2.0,15.0,2.0
-NO,16206.0,7,4.0,8.0,8.0,4.0,8.0,5.0,2.0,2.0,84.0,1.0
-NO,16284.0,7,1.0,5.0,6.0,4.0,6.0,7.0,3.0,1.0,17.0,2.0
-NO,16290.0,7,7.0,9.0,9.0,9.0,9.0,7.0,3.0,1.0,56.0,1.0
-NO,16308.0,7,7.0,8.0,8.0,6.0,8.0,6.0,2.0,2.0,33.0,1.0
-NO,16320.0,7,2.0,1.0,7.0,5.0,6.0,7.0,3.0,1.0,25.0,2.0
-NO,16350.0,7,5.0,5.0,6.0,3.0,7.0,4.0,2.0,1.0,42.0,1.0
-NO,16356.0,7,3.0,10.0,10.0,0.0,10.0,6.0,2.0,1.0,26.0,1.0
-NO,16374.0,7,4.0,8.0,8.0,7.0,7.0,6.0,3.0,1.0,60.0,1.0
-NO,16422.0,7,5.0,0.0,0.0,5.0,0.0,1.0,1.0,1.0,47.0,2.0
-NO,16470.0,7,3.0,7.0,8.0,5.0,8.0,4.0,4.0,1.0,68.0,1.0
-NO,16488.0,7,2.0,5.0,7.0,,7.0,5.0,2.0,1.0,40.0,1.0
-NO,16500.0,7,5.0,8.0,9.0,3.0,9.0,6.0,3.0,2.0,24.0,1.0
-NO,16506.0,7,6.0,5.0,8.0,5.0,7.0,5.0,2.0,1.0,55.0,1.0
-NO,16512.0,7,6.0,8.0,8.0,5.0,8.0,3.0,2.0,1.0,39.0,1.0
-NO,16518.0,7,3.0,7.0,7.0,8.0,9.0,6.0,3.0,1.0,47.0,1.0
-NO,16524.0,7,3.0,9.0,9.0,9.0,8.0,4.0,2.0,2.0,51.0,1.0
-NO,16548.0,7,2.0,8.0,8.0,7.0,7.0,6.0,4.0,2.0,57.0,1.0
-NO,16566.0,7,6.0,8.0,5.0,7.0,6.0,6.0,3.0,1.0,52.0,1.0
-NO,16572.0,7,6.0,7.0,8.0,7.0,8.0,6.0,2.0,2.0,60.0,1.0
-NO,16584.0,7,4.0,8.0,9.0,8.0,7.0,6.0,4.0,1.0,74.0,1.0
-NO,16638.0,7,4.0,5.0,6.0,4.0,8.0,6.0,2.0,2.0,63.0,2.0
-NO,16644.0,7,5.0,7.0,8.0,6.0,8.0,6.0,5.0,1.0,26.0,1.0
-NO,16680.0,7,4.0,5.0,5.0,6.0,7.0,6.0,3.0,1.0,52.0,1.0
-NO,16692.0,7,3.0,8.0,8.0,5.0,7.0,7.0,3.0,2.0,42.0,1.0
-NO,16698.0,7,5.0,7.0,7.0,7.0,10.0,6.0,3.0,2.0,57.0,1.0
-NO,16740.0,7,5.0,7.0,7.0,7.0,10.0,4.0,5.0,1.0,74.0,1.0
-NO,16746.0,7,3.0,8.0,7.0,6.0,8.0,5.0,2.0,1.0,26.0,2.0
-NO,16770.0,7,6.0,5.0,6.0,3.0,8.0,4.0,2.0,1.0,35.0,1.0
-NO,16776.0,7,2.0,7.0,6.0,6.0,7.0,6.0,3.0,1.0,44.0,1.0
-NO,16824.0,7,7.0,7.0,7.0,7.0,9.0,5.0,2.0,2.0,81.0,2.0
-NO,16836.0,7,5.0,7.0,8.0,5.0,10.0,4.0,3.0,2.0,82.0,1.0
-NO,16860.0,7,1.0,8.0,9.0,5.0,9.0,7.0,3.0,1.0,27.0,2.0
-NO,16950.0,7,7.0,4.0,6.0,3.0,7.0,7.0,4.0,2.0,26.0,1.0
-NO,16968.0,7,4.0,7.0,5.0,7.0,9.0,5.0,1.0,1.0,62.0,1.0
-NO,16974.0,7,2.0,8.0,9.0,6.0,8.0,4.0,3.0,2.0,50.0,1.0
-NO,16980.0,7,7.0,8.0,8.0,5.0,8.0,4.0,3.0,1.0,57.0,1.0
-NO,16986.0,7,5.0,10.0,10.0,8.0,8.0,5.0,3.0,2.0,63.0,2.0
-NO,17064.0,7,4.0,8.0,8.0,5.0,9.0,5.0,3.0,1.0,19.0,2.0
-NO,17070.0,7,2.0,9.0,8.0,6.0,9.0,4.0,3.0,1.0,64.0,1.0
-NO,17082.0,7,2.0,4.0,7.0,5.0,5.0,6.0,3.0,2.0,17.0,2.0
-NO,17118.0,7,3.0,7.0,7.0,8.0,9.0,5.0,3.0,1.0,63.0,1.0
-NO,17142.0,7,2.0,8.0,6.0,6.0,8.0,4.0,2.0,2.0,41.0,1.0
-NO,17154.0,7,3.0,4.0,4.0,5.0,6.0,7.0,5.0,2.0,17.0,2.0
-NO,17190.0,7,5.0,8.0,7.0,5.0,8.0,3.0,2.0,2.0,60.0,2.0
-NO,17208.0,7,4.0,7.0,8.0,7.0,9.0,4.0,4.0,1.0,49.0,1.0
-NO,17214.0,7,2.0,7.0,5.0,5.0,9.0,4.0,3.0,1.0,19.0,2.0
-NO,17220.0,7,5.0,7.0,7.0,7.0,9.0,7.0,3.0,2.0,68.0,1.0
-NO,17286.0,7,2.0,9.0,9.0,9.0,7.0,5.0,4.0,1.0,40.0,1.0
-NO,17310.0,7,7.0,5.0,7.0,9.0,8.0,4.0,2.0,1.0,55.0,1.0
-NO,17328.0,7,7.0,5.0,8.0,5.0,6.0,6.0,3.0,2.0,94.0,2.0
-NO,17334.0,7,1.0,4.0,2.0,3.0,7.0,6.0,3.0,2.0,20.0,2.0
-NO,17412.0,7,5.0,6.0,8.0,3.0,3.0,2.0,1.0,2.0,20.0,1.0
-NO,17436.0,7,6.0,8.0,7.0,8.0,8.0,6.0,2.0,2.0,47.0,1.0
-NO,17448.0,7,7.0,8.0,6.0,7.0,8.0,6.0,3.0,1.0,70.0,1.0
-NO,17460.0,7,5.0,7.0,8.0,7.0,8.0,5.0,2.0,2.0,61.0,1.0
-NO,17466.0,7,4.0,8.0,7.0,8.0,9.0,6.0,4.0,2.0,,1.0
-NO,17484.0,7,5.0,7.0,7.0,7.0,7.0,6.0,3.0,1.0,51.0,1.0
-NO,17508.0,7,3.0,7.0,7.0,6.0,10.0,4.0,3.0,1.0,65.0,1.0
-NO,17520.0,7,4.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,46.0,1.0
-NO,17544.0,7,3.0,9.0,9.0,8.0,8.0,6.0,3.0,2.0,20.0,2.0
-NO,17550.0,7,5.0,5.0,5.0,3.0,8.0,2.0,2.0,1.0,53.0,1.0
-NO,17556.0,7,6.0,8.0,10.0,9.0,10.0,6.0,4.0,1.0,80.0,1.0
-NO,17634.0,7,5.0,5.0,8.0,7.0,10.0,5.0,3.0,2.0,65.0,1.0
-NO,17688.0,7,5.0,8.0,7.0,8.0,9.0,7.0,4.0,1.0,17.0,2.0
-NO,17742.0,7,7.0,8.0,7.0,7.0,9.0,6.0,2.0,2.0,62.0,1.0
-NO,17754.0,7,1.0,9.0,7.0,4.0,10.0,4.0,2.0,2.0,38.0,1.0
-NO,17766.0,7,5.0,7.0,7.0,8.0,8.0,4.0,2.0,1.0,63.0,2.0
-NO,17790.0,7,1.0,7.0,5.0,7.0,10.0,6.0,3.0,1.0,23.0,1.0
-NO,17802.0,7,1.0,6.0,9.0,4.0,9.0,7.0,3.0,1.0,54.0,1.0
-NO,17808.0,7,5.0,5.0,7.0,7.0,7.0,4.0,3.0,1.0,54.0,1.0
-NO,17826.0,7,5.0,7.0,7.0,5.0,8.0,3.0,2.0,1.0,35.0,1.0
-NO,17832.0,7,3.0,8.0,8.0,7.0,9.0,7.0,5.0,2.0,44.0,1.0
-NO,17856.0,7,6.0,7.0,5.0,6.0,9.0,6.0,3.0,2.0,76.0,1.0
-NO,17874.0,7,4.0,5.0,9.0,8.0,8.0,2.0,2.0,1.0,44.0,2.0
-NO,17880.0,7,7.0,3.0,5.0,8.0,7.0,6.0,3.0,2.0,73.0,2.0
-NO,17886.0,7,6.0,5.0,8.0,10.0,8.0,4.0,3.0,1.0,92.0,1.0
-NO,17916.0,7,2.0,6.0,6.0,3.0,10.0,5.0,3.0,1.0,28.0,2.0
-NO,17922.0,7,4.0,7.0,7.0,8.0,10.0,4.0,2.0,2.0,42.0,1.0
-NO,17940.0,7,7.0,8.0,10.0,9.0,8.0,6.0,3.0,2.0,32.0,2.0
-NO,17976.0,7,3.0,7.0,7.0,6.0,9.0,6.0,3.0,2.0,64.0,1.0
-NO,18000.0,7,6.0,7.0,7.0,4.0,4.0,4.0,2.0,2.0,44.0,1.0
-NO,18006.0,7,3.0,7.0,7.0,7.0,8.0,3.0,3.0,1.0,43.0,1.0
-NO,18024.0,7,2.0,8.0,7.0,9.0,9.0,6.0,3.0,1.0,17.0,2.0
-NO,18066.0,7,5.0,7.0,7.0,7.0,8.0,5.0,3.0,1.0,62.0,2.0
-NO,18090.0,7,5.0,5.0,5.0,8.0,8.0,6.0,4.0,2.0,38.0,2.0
-NO,18096.0,7,2.0,9.0,9.0,7.0,7.0,5.0,3.0,2.0,45.0,1.0
-NO,18120.0,7,3.0,9.0,9.0,8.0,9.0,6.0,3.0,1.0,16.0,2.0
-NO,18162.0,7,7.0,6.0,7.0,5.0,9.0,5.0,4.0,1.0,69.0,1.0
-NO,18198.0,7,2.0,5.0,8.0,5.0,9.0,7.0,3.0,1.0,17.0,2.0
-NO,18204.0,7,3.0,7.0,8.0,6.0,8.0,6.0,4.0,1.0,73.0,2.0
-NO,18210.0,7,3.0,9.0,7.0,8.0,7.0,7.0,3.0,1.0,34.0,2.0
-NO,18216.0,7,2.0,6.0,7.0,3.0,9.0,6.0,3.0,1.0,15.0,2.0
-NO,18222.0,7,1.0,8.0,5.0,8.0,7.0,7.0,2.0,2.0,49.0,1.0
-NO,18240.0,7,2.0,6.0,8.0,5.0,7.0,3.0,1.0,1.0,75.0,2.0
-NO,18270.0,7,1.0,7.0,5.0,3.0,8.0,5.0,2.0,1.0,45.0,2.0
-NO,18306.0,7,4.0,3.0,5.0,5.0,7.0,4.0,2.0,1.0,22.0,2.0
-NO,18336.0,7,2.0,5.0,5.0,5.0,9.0,6.0,3.0,1.0,62.0,1.0
-NO,18360.0,7,5.0,5.0,9.0,7.0,8.0,5.0,3.0,1.0,40.0,1.0
-NO,18390.0,7,3.0,10.0,10.0,10.0,9.0,6.0,3.0,1.0,45.0,1.0
-NO,18396.0,7,1.0,8.0,9.0,8.0,8.0,5.0,3.0,2.0,45.0,1.0
-NO,18438.0,7,7.0,8.0,7.0,7.0,6.0,3.0,1.0,1.0,58.0,1.0
-NO,18480.0,7,3.0,8.0,8.0,8.0,8.0,6.0,4.0,2.0,63.0,1.0
-NO,18486.0,7,6.0,5.0,7.0,4.0,10.0,6.0,2.0,2.0,21.0,2.0
-NO,18498.0,7,3.0,7.0,8.0,8.0,7.0,4.0,3.0,1.0,60.0,2.0
-NO,18540.0,7,3.0,5.0,5.0,5.0,5.0,2.0,1.0,1.0,45.0,1.0
-NO,18546.0,7,5.0,5.0,7.0,6.0,6.0,6.0,2.0,1.0,45.0,1.0
-NO,18570.0,7,4.0,4.0,4.0,5.0,9.0,4.0,3.0,1.0,50.0,2.0
-NO,18576.0,7,3.0,8.0,8.0,8.0,7.0,7.0,3.0,1.0,55.0,1.0
-NO,18600.0,7,5.0,7.0,7.0,7.0,6.0,3.0,2.0,1.0,60.0,2.0
-NO,18606.0,7,4.0,7.0,7.0,5.0,10.0,5.0,2.0,1.0,87.0,1.0
-NO,18618.0,7,2.0,5.0,5.0,5.0,9.0,6.0,3.0,2.0,42.0,1.0
-NO,18630.0,7,6.0,7.0,4.0,6.0,8.0,7.0,2.0,1.0,18.0,2.0
-NO,18648.0,7,3.0,7.0,8.0,7.0,8.0,6.0,4.0,1.0,48.0,1.0
-NO,18678.0,7,4.0,,10.0,,9.0,7.0,4.0,2.0,90.0,2.0
-NO,18684.0,7,3.0,10.0,8.0,10.0,10.0,4.0,2.0,2.0,45.0,1.0
-NO,18696.0,7,4.0,9.0,9.0,9.0,8.0,6.0,3.0,1.0,67.0,2.0
-NO,18720.0,7,2.0,5.0,8.0,5.0,8.0,7.0,3.0,1.0,18.0,2.0
-NO,18732.0,7,5.0,8.0,8.0,7.0,9.0,5.0,3.0,2.0,,2.0
-NO,18744.0,7,4.0,8.0,9.0,7.0,7.0,7.0,3.0,2.0,23.0,2.0
-NO,18750.0,7,5.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,25.0,1.0
-NO,18762.0,7,4.0,5.0,5.0,3.0,8.0,7.0,3.0,2.0,42.0,1.0
-NO,18774.0,7,6.0,8.0,9.0,6.0,10.0,7.0,3.0,2.0,59.0,1.0
-NO,18786.0,7,0.0,6.0,9.0,8.0,10.0,7.0,3.0,2.0,20.0,2.0
-NO,18792.0,7,6.0,4.0,6.0,5.0,4.0,6.0,2.0,1.0,21.0,2.0
-NO,18798.0,7,1.0,8.0,5.0,6.0,9.0,4.0,3.0,1.0,27.0,1.0
-NO,18822.0,7,7.0,4.0,5.0,6.0,8.0,2.0,1.0,1.0,,2.0
-NO,18834.0,7,2.0,8.0,6.0,6.0,9.0,6.0,3.0,2.0,46.0,1.0
-NO,18846.0,7,2.0,7.0,5.0,4.0,8.0,7.0,4.0,2.0,18.0,2.0
-NO,18858.0,7,2.0,5.0,6.0,5.0,10.0,7.0,3.0,1.0,15.0,2.0
-NO,18876.0,7,4.0,5.0,4.0,3.0,10.0,6.0,2.0,2.0,22.0,1.0
-NO,18894.0,7,4.0,5.0,7.0,4.0,7.0,5.0,2.0,1.0,22.0,2.0
-NO,18900.0,7,5.0,2.0,3.0,2.0,10.0,6.0,3.0,1.0,27.0,1.0
-NO,18912.0,7,1.0,7.0,7.0,6.0,8.0,7.0,4.0,1.0,49.0,2.0
-NO,18918.0,7,3.0,4.0,7.0,4.0,6.0,7.0,3.0,2.0,19.0,2.0
-NO,18942.0,7,3.0,5.0,6.0,6.0,9.0,7.0,3.0,1.0,45.0,1.0
-NO,19014.0,7,7.0,6.0,8.0,8.0,10.0,5.0,3.0,2.0,89.0,1.0
-NO,19020.0,7,7.0,4.0,5.0,4.0,9.0,7.0,4.0,1.0,23.0,1.0
-NO,19038.0,7,4.0,6.0,6.0,6.0,8.0,5.0,2.0,1.0,32.0,1.0
-NO,19056.0,7,2.0,8.0,9.0,8.0,10.0,6.0,3.0,2.0,75.0,1.0
-NO,19068.0,7,4.0,3.0,4.0,3.0,5.0,4.0,3.0,2.0,63.0,1.0
-NO,19092.0,7,2.0,7.0,4.0,7.0,7.0,3.0,3.0,1.0,52.0,1.0
-NO,19104.0,7,2.0,5.0,8.0,6.0,7.0,6.0,3.0,1.0,38.0,1.0
-NO,19122.0,7,4.0,5.0,7.0,5.0,6.0,4.0,3.0,2.0,49.0,1.0
-NO,19140.0,7,0.0,8.0,5.0,4.0,8.0,4.0,3.0,1.0,43.0,1.0
-NO,19146.0,7,2.0,0.0,0.0,3.0,10.0,2.0,2.0,1.0,37.0,1.0
-NO,19152.0,7,2.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,60.0,1.0
-NO,19170.0,7,5.0,5.0,7.0,5.0,8.0,6.0,3.0,1.0,16.0,2.0
-NO,19218.0,7,4.0,9.0,8.0,8.0,6.0,4.0,4.0,2.0,51.0,1.0
-NO,19254.0,7,5.0,5.0,6.0,8.0,9.0,6.0,4.0,2.0,84.0,2.0
-NO,19278.0,7,2.0,8.0,6.0,8.0,8.0,7.0,3.0,1.0,55.0,2.0
-NO,19284.0,7,3.0,4.0,5.0,0.0,7.0,6.0,3.0,1.0,82.0,2.0
-NO,19308.0,7,6.0,7.0,10.0,8.0,10.0,4.0,3.0,2.0,29.0,1.0
-NO,19320.0,7,5.0,8.0,7.0,7.0,10.0,6.0,3.0,1.0,47.0,1.0
-NO,19326.0,7,3.0,3.0,5.0,5.0,9.0,7.0,1.0,2.0,38.0,1.0
-NO,19332.0,7,5.0,8.0,8.0,6.0,8.0,5.0,2.0,1.0,,2.0
-NO,19404.0,7,1.0,5.0,4.0,6.0,8.0,6.0,2.0,1.0,15.0,2.0
-NO,19416.0,7,2.0,7.0,7.0,6.0,7.0,4.0,3.0,1.0,62.0,1.0
-NO,19422.0,7,2.0,8.0,7.0,5.0,8.0,3.0,3.0,1.0,33.0,1.0
-NO,19464.0,7,4.0,8.0,9.0,4.0,9.0,7.0,5.0,1.0,18.0,2.0
-NO,19500.0,7,5.0,7.0,10.0,9.0,10.0,7.0,3.0,1.0,55.0,2.0
-NO,19524.0,7,7.0,8.0,8.0,1.0,7.0,4.0,2.0,2.0,83.0,1.0
-NO,19548.0,7,5.0,7.0,7.0,6.0,7.0,2.0,3.0,1.0,53.0,1.0
-NO,19596.0,7,7.0,8.0,7.0,6.0,5.0,4.0,2.0,1.0,56.0,2.0
-NO,19626.0,7,3.0,7.0,5.0,3.0,9.0,4.0,3.0,1.0,55.0,1.0
-NO,19638.0,7,0.0,9.0,8.0,8.0,9.0,7.0,3.0,2.0,55.0,1.0
-NO,19656.0,7,5.0,6.0,6.0,8.0,7.0,4.0,2.0,2.0,74.0,1.0
-NO,19662.0,7,2.0,6.0,5.0,6.0,8.0,4.0,2.0,1.0,23.0,2.0
-NO,19680.0,7,2.0,7.0,5.0,8.0,9.0,6.0,5.0,1.0,36.0,2.0
-NO,19686.0,7,5.0,7.0,8.0,7.0,4.0,6.0,5.0,1.0,40.0,1.0
-NO,19704.0,7,5.0,7.0,7.0,5.0,6.0,6.0,4.0,1.0,25.0,2.0
-NO,19710.0,7,4.0,8.0,7.0,6.0,7.0,4.0,3.0,1.0,76.0,1.0
-NO,19716.0,7,3.0,7.0,5.0,6.0,8.0,6.0,2.0,1.0,62.0,1.0
-NO,19734.0,7,4.0,3.0,4.0,3.0,7.0,7.0,3.0,2.0,22.0,2.0
-NO,19752.0,7,2.0,6.0,5.0,6.0,10.0,2.0,1.0,2.0,60.0,2.0
-NO,19758.0,7,7.0,5.0,5.0,4.0,2.0,5.0,1.0,2.0,45.0,2.0
-NO,19764.0,7,6.0,7.0,9.0,9.0,10.0,6.0,4.0,2.0,71.0,2.0
-NO,19776.0,7,5.0,5.0,8.0,8.0,9.0,3.0,1.0,1.0,84.0,1.0
-NO,19824.0,7,2.0,5.0,4.0,6.0,8.0,7.0,3.0,2.0,21.0,2.0
-NO,19836.0,7,2.0,9.0,8.0,8.0,9.0,6.0,3.0,2.0,55.0,1.0
-NO,19842.0,7,4.0,6.0,8.0,8.0,9.0,4.0,2.0,1.0,52.0,1.0
-NO,19872.0,7,0.0,4.0,5.0,4.0,7.0,4.0,3.0,2.0,18.0,2.0
-NO,19884.0,7,4.0,3.0,5.0,5.0,3.0,5.0,2.0,2.0,49.0,2.0
-NO,19890.0,7,6.0,8.0,6.0,4.0,8.0,6.0,4.0,2.0,86.0,2.0
-NO,19896.0,7,6.0,6.0,5.0,7.0,6.0,4.0,3.0,1.0,73.0,2.0
-NO,19902.0,7,2.0,7.0,7.0,5.0,10.0,4.0,4.0,1.0,57.0,1.0
-NO,19908.0,7,1.0,8.0,8.0,7.0,9.0,6.0,2.0,1.0,53.0,2.0
-NO,19950.0,7,4.0,8.0,9.0,9.0,10.0,5.0,3.0,1.0,65.0,1.0
-NO,19968.0,7,7.0,3.0,5.0,5.0,7.0,6.0,3.0,2.0,65.0,2.0
-NO,19980.0,7,5.0,8.0,6.0,7.0,9.0,6.0,3.0,1.0,37.0,1.0
-NO,19998.0,7,2.0,8.0,9.0,7.0,9.0,6.0,3.0,1.0,26.0,1.0
-NO,20022.0,7,3.0,6.0,4.0,6.0,7.0,6.0,1.0,2.0,22.0,1.0
-NO,20034.0,7,4.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,47.0,1.0
-NO,20076.0,7,7.0,8.0,6.0,6.0,8.0,4.0,2.0,1.0,61.0,1.0
-NO,20088.0,7,7.0,3.0,6.0,5.0,10.0,6.0,3.0,1.0,74.0,1.0
-NO,20142.0,7,5.0,7.0,8.0,5.0,9.0,6.0,3.0,2.0,30.0,1.0
-NO,20154.0,7,7.0,3.0,5.0,5.0,5.0,2.0,1.0,2.0,69.0,2.0
-NO,20166.0,7,7.0,5.0,,6.0,7.0,2.0,2.0,1.0,52.0,1.0
-NO,20262.0,7,2.0,5.0,6.0,0.0,9.0,4.0,3.0,1.0,57.0,1.0
-NO,20286.0,7,3.0,3.0,3.0,5.0,4.0,2.0,1.0,2.0,16.0,2.0
-NO,20316.0,7,5.0,7.0,7.0,5.0,7.0,5.0,4.0,2.0,,1.0
-NO,20328.0,7,5.0,7.0,7.0,6.0,8.0,5.0,2.0,1.0,52.0,1.0
-NO,20352.0,7,5.0,5.0,9.0,5.0,6.0,4.0,3.0,1.0,72.0,1.0
-NO,20358.0,7,3.0,7.0,9.0,7.0,9.0,5.0,3.0,2.0,65.0,1.0
-NO,20370.0,7,1.0,8.0,8.0,8.0,10.0,3.0,3.0,2.0,44.0,1.0
-NO,20394.0,7,1.0,7.0,7.0,7.0,7.0,7.0,3.0,1.0,24.0,2.0
-NO,20400.0,7,7.0,7.0,8.0,5.0,8.0,4.0,1.0,2.0,70.0,2.0
-NO,20412.0,7,5.0,8.0,8.0,8.0,8.0,2.0,1.0,1.0,78.0,1.0
-NO,20418.0,7,3.0,6.0,5.0,4.0,8.0,6.0,3.0,2.0,18.0,2.0
-NO,20424.0,7,4.0,2.0,10.0,6.0,8.0,2.0,3.0,2.0,64.0,2.0
-NO,20436.0,7,5.0,8.0,7.0,8.0,9.0,6.0,4.0,2.0,75.0,2.0
-NO,20442.0,7,7.0,8.0,5.0,4.0,8.0,6.0,2.0,1.0,56.0,1.0
-NO,20448.0,7,3.0,4.0,5.0,7.0,6.0,6.0,3.0,2.0,29.0,1.0
-NO,20460.0,7,5.0,8.0,8.0,5.0,10.0,6.0,2.0,2.0,44.0,1.0
-NO,20466.0,7,2.0,5.0,5.0,5.0,10.0,6.0,3.0,1.0,53.0,1.0
-NO,20478.0,7,7.0,8.0,5.0,7.0,8.0,6.0,2.0,1.0,72.0,2.0
-NO,20484.0,7,6.0,6.0,8.0,6.0,7.0,7.0,3.0,1.0,27.0,1.0
-NO,20496.0,7,5.0,4.0,5.0,6.0,10.0,4.0,3.0,2.0,62.0,1.0
-NO,20508.0,7,0.0,7.0,7.0,7.0,7.0,3.0,2.0,1.0,84.0,2.0
-NO,20514.0,7,3.0,7.0,8.0,9.0,6.0,5.0,2.0,1.0,39.0,1.0
-NO,20526.0,7,2.0,9.0,4.0,2.0,8.0,5.0,2.0,1.0,21.0,2.0
-NO,20568.0,7,5.0,7.0,7.0,6.0,8.0,4.0,3.0,2.0,61.0,1.0
-NO,20580.0,7,3.0,7.0,7.0,7.0,9.0,6.0,2.0,1.0,48.0,1.0
-NO,20586.0,7,6.0,7.0,7.0,3.0,10.0,4.0,3.0,1.0,78.0,1.0
-NO,20640.0,7,4.0,7.0,8.0,7.0,8.0,4.0,3.0,1.0,65.0,1.0
-NO,20646.0,7,3.0,8.0,7.0,4.0,8.0,6.0,3.0,1.0,23.0,1.0
-NO,20688.0,7,3.0,7.0,6.0,7.0,6.0,6.0,4.0,1.0,35.0,2.0
-NO,20730.0,7,7.0,6.0,6.0,5.0,6.0,4.0,2.0,1.0,46.0,1.0
-NO,20742.0,7,2.0,5.0,7.0,5.0,5.0,3.0,2.0,2.0,37.0,2.0
-NO,20772.0,7,2.0,7.0,8.0,7.0,9.0,6.0,3.0,2.0,65.0,1.0
-NO,20778.0,7,4.0,8.0,8.0,8.0,7.0,6.0,3.0,1.0,67.0,1.0
-NO,20808.0,7,4.0,7.0,8.0,8.0,9.0,5.0,3.0,2.0,51.0,2.0
-NO,20862.0,7,3.0,9.0,8.0,8.0,8.0,6.0,2.0,2.0,24.0,2.0
-NO,20892.0,7,5.0,7.0,9.0,7.0,9.0,4.0,4.0,1.0,70.0,1.0
-NO,20910.0,7,6.0,5.0,6.0,3.0,8.0,7.0,2.0,2.0,39.0,1.0
-NO,20922.0,7,5.0,3.0,3.0,4.0,9.0,6.0,4.0,2.0,72.0,2.0
-NO,20928.0,7,4.0,8.0,8.0,7.0,7.0,7.0,4.0,1.0,29.0,2.0
-NO,20934.0,7,7.0,0.0,4.0,5.0,9.0,6.0,3.0,2.0,44.0,1.0
-NO,20970.0,7,5.0,7.0,8.0,7.0,7.0,6.0,3.0,1.0,82.0,1.0
-NO,20988.0,7,4.0,7.0,6.0,4.0,9.0,3.0,2.0,1.0,39.0,1.0
-NO,20994.0,7,3.0,3.0,4.0,6.0,10.0,6.0,3.0,1.0,60.0,1.0
-NO,21042.0,7,6.0,7.0,7.0,6.0,8.0,7.0,3.0,2.0,25.0,1.0
-NO,21114.0,7,2.0,1.0,4.0,9.0,10.0,7.0,3.0,1.0,21.0,2.0
-NO,21168.0,7,1.0,8.0,8.0,7.0,8.0,6.0,3.0,1.0,36.0,2.0
-NO,21210.0,7,3.0,8.0,7.0,9.0,8.0,3.0,2.0,1.0,46.0,1.0
-NO,21228.0,7,4.0,6.0,6.0,4.0,7.0,4.0,3.0,2.0,43.0,1.0
-NO,21234.0,7,5.0,7.0,7.0,5.0,7.0,6.0,2.0,1.0,51.0,1.0
-NO,21282.0,7,7.0,8.0,10.0,10.0,10.0,7.0,4.0,2.0,81.0,2.0
-NO,21306.0,7,0.0,8.0,7.0,7.0,5.0,6.0,2.0,2.0,22.0,2.0
-NO,21312.0,7,3.0,6.0,8.0,5.0,9.0,7.0,3.0,2.0,,1.0
-NO,21318.0,7,2.0,7.0,9.0,7.0,8.0,6.0,4.0,2.0,51.0,1.0
-NO,21402.0,7,2.0,10.0,8.0,7.0,9.0,4.0,3.0,1.0,47.0,1.0
-NO,21414.0,7,7.0,7.0,10.0,9.0,10.0,6.0,2.0,1.0,82.0,1.0
-NO,21462.0,7,3.0,6.0,7.0,7.0,3.0,4.0,2.0,2.0,48.0,2.0
-NO,21468.0,7,4.0,6.0,8.0,5.0,3.0,4.0,2.0,2.0,40.0,2.0
-NO,21492.0,7,2.0,9.0,9.0,6.0,9.0,6.0,3.0,2.0,53.0,1.0
-NO,21540.0,7,6.0,4.0,7.0,3.0,4.0,7.0,3.0,2.0,18.0,1.0
-NO,21564.0,7,6.0,3.0,2.0,7.0,8.0,3.0,2.0,1.0,70.0,1.0
-NO,21576.0,7,4.0,7.0,7.0,6.0,7.0,7.0,3.0,2.0,58.0,1.0
-NO,21582.0,7,0.0,5.0,5.0,7.0,5.0,3.0,2.0,1.0,69.0,2.0
-NO,21594.0,7,3.0,5.0,7.0,6.0,9.0,7.0,2.0,1.0,16.0,2.0
-NO,21606.0,7,3.0,5.0,5.0,5.0,10.0,6.0,3.0,1.0,34.0,1.0
-NO,21696.0,7,7.0,6.0,6.0,5.0,10.0,4.0,3.0,2.0,31.0,1.0
-NO,21726.0,7,1.0,5.0,7.0,6.0,9.0,6.0,2.0,1.0,32.0,1.0
-NO,21738.0,7,7.0,4.0,6.0,2.0,5.0,3.0,2.0,1.0,42.0,2.0
-NO,21768.0,7,3.0,7.0,7.0,5.0,7.0,5.0,4.0,1.0,41.0,1.0
-NO,21774.0,7,2.0,3.0,5.0,5.0,9.0,7.0,2.0,2.0,51.0,2.0
-NO,21798.0,7,7.0,8.0,8.0,8.0,9.0,4.0,2.0,1.0,54.0,1.0
-NO,21804.0,7,1.0,7.0,5.0,5.0,9.0,7.0,1.0,2.0,25.0,2.0
-NO,21816.0,7,5.0,4.0,5.0,7.0,3.0,7.0,3.0,2.0,39.0,2.0
-NO,21822.0,7,4.0,7.0,7.0,6.0,8.0,6.0,2.0,1.0,19.0,2.0
-NO,21840.0,7,6.0,5.0,6.0,9.0,10.0,6.0,3.0,2.0,67.0,1.0
-NO,21852.0,7,5.0,5.0,7.0,5.0,6.0,6.0,3.0,1.0,20.0,1.0
-NO,21882.0,7,4.0,8.0,8.0,4.0,8.0,6.0,3.0,1.0,18.0,2.0
-NO,21930.0,7,4.0,7.0,7.0,7.0,9.0,4.0,3.0,2.0,55.0,1.0
-NO,21978.0,7,5.0,7.0,8.0,5.0,7.0,5.0,2.0,2.0,80.0,1.0
-NO,21984.0,7,3.0,6.0,7.0,6.0,10.0,6.0,3.0,2.0,63.0,1.0
-NO,22038.0,7,7.0,8.0,8.0,5.0,7.0,5.0,2.0,1.0,55.0,2.0
-NO,22068.0,7,4.0,3.0,3.0,4.0,8.0,4.0,3.0,2.0,48.0,1.0
-NO,22074.0,7,7.0,1.0,6.0,5.0,9.0,6.0,1.0,1.0,55.0,1.0
-NO,22158.0,7,2.0,7.0,5.0,5.0,5.0,4.0,1.0,2.0,32.0,1.0
-NO,22170.0,7,3.0,3.0,3.0,5.0,1.0,7.0,3.0,2.0,61.0,2.0
-NO,22176.0,7,3.0,6.0,6.0,6.0,7.0,6.0,3.0,2.0,54.0,1.0
-NO,22224.0,7,4.0,9.0,8.0,6.0,8.0,6.0,4.0,1.0,51.0,2.0
-NO,22260.0,7,1.0,8.0,8.0,5.0,8.0,4.0,2.0,1.0,15.0,2.0
-NO,22266.0,7,4.0,5.0,4.0,4.0,10.0,5.0,3.0,2.0,51.0,1.0
-NO,22290.0,7,5.0,8.0,7.0,8.0,7.0,6.0,2.0,2.0,68.0,2.0
-NO,22362.0,7,3.0,8.0,9.0,6.0,7.0,3.0,2.0,2.0,61.0,1.0
-NO,22386.0,7,4.0,5.0,4.0,6.0,9.0,6.0,4.0,2.0,70.0,1.0
-NO,22428.0,7,2.0,8.0,7.0,3.0,8.0,6.0,3.0,1.0,16.0,2.0
-SE,7.0,6,3.0,7.0,7.0,10.0,5.0,6.0,2.0,2.0,96.0,2.0
-SE,13.0,6,1.0,10.0,10.0,10.0,10.0,5.0,3.0,1.0,92.0,1.0
-SE,22.0,6,2.0,6.0,6.0,5.0,9.0,4.0,4.0,1.0,92.0,1.0
-SE,30.0,6,7.0,6.0,8.0,8.0,9.0,7.0,4.0,1.0,90.0,2.0
-SE,39.0,6,6.0,6.0,8.0,8.0,9.0,5.0,2.0,1.0,90.0,2.0
-SE,58.0,6,4.0,6.0,8.0,8.0,7.0,6.0,2.0,1.0,,1.0
-SE,79.0,6,7.0,2.0,2.0,5.0,10.0,7.0,4.0,2.0,87.0,2.0
-SE,97.0,6,7.0,5.0,5.0,4.0,8.0,5.0,1.0,1.0,86.0,1.0
-SE,102.0,6,4.0,7.0,5.0,5.0,8.0,6.0,1.0,2.0,85.0,2.0
-SE,105.0,6,3.0,0.0,,0.0,4.0,2.0,,2.0,86.0,2.0
-SE,106.0,6,5.0,8.0,5.0,8.0,6.0,3.0,2.0,2.0,85.0,2.0
-SE,107.0,6,4.0,8.0,8.0,6.0,9.0,6.0,2.0,1.0,85.0,1.0
-SE,109.0,6,3.0,5.0,3.0,4.0,8.0,5.0,1.0,1.0,86.0,1.0
-SE,112.0,6,6.0,7.0,8.0,6.0,3.0,4.0,2.0,1.0,85.0,1.0
-SE,116.0,6,5.0,0.0,0.0,10.0,10.0,7.0,5.0,1.0,85.0,2.0
-SE,120.0,6,3.0,9.0,9.0,8.0,6.0,5.0,4.0,1.0,84.0,1.0
-SE,122.0,6,2.0,10.0,8.0,5.0,4.0,2.0,3.0,1.0,84.0,1.0
-SE,130.0,6,3.0,6.0,7.0,6.0,9.0,7.0,4.0,1.0,84.0,2.0
-SE,134.0,6,7.0,5.0,7.0,5.0,10.0,2.0,2.0,1.0,84.0,1.0
-SE,148.0,6,6.0,4.0,9.0,7.0,9.0,6.0,3.0,2.0,83.0,2.0
-SE,154.0,6,6.0,5.0,7.0,8.0,8.0,6.0,5.0,2.0,83.0,2.0
-SE,160.0,6,0.0,5.0,7.0,8.0,9.0,2.0,1.0,1.0,82.0,2.0
-SE,165.0,6,7.0,5.0,8.0,9.0,7.0,5.0,3.0,2.0,82.0,2.0
-SE,170.0,6,5.0,5.0,5.0,5.0,5.0,5.0,2.0,1.0,81.0,2.0
-SE,177.0,6,2.0,8.0,8.0,8.0,8.0,4.0,3.0,2.0,81.0,2.0
-SE,178.0,6,7.0,8.0,5.0,5.0,5.0,1.0,1.0,1.0,81.0,1.0
-SE,180.0,6,7.0,8.0,10.0,6.0,8.0,6.0,2.0,1.0,81.0,2.0
-SE,192.0,6,0.0,5.0,8.0,10.0,8.0,6.0,4.0,1.0,80.0,2.0
-SE,198.0,6,6.0,5.0,8.0,6.0,5.0,6.0,4.0,2.0,80.0,2.0
-SE,199.0,6,5.0,4.0,8.0,5.0,10.0,4.0,3.0,2.0,81.0,2.0
-SE,201.0,6,3.0,3.0,6.0,6.0,9.0,6.0,2.0,1.0,80.0,1.0
-SE,206.0,6,4.0,5.0,7.0,7.0,10.0,4.0,2.0,1.0,81.0,1.0
-SE,216.0,6,3.0,2.0,2.0,4.0,7.0,5.0,3.0,1.0,80.0,1.0
-SE,221.0,6,4.0,3.0,7.0,6.0,8.0,4.0,3.0,2.0,79.0,2.0
-SE,225.0,6,6.0,10.0,8.0,10.0,10.0,6.0,1.0,1.0,80.0,2.0
-SE,226.0,6,4.0,6.0,8.0,9.0,9.0,6.0,3.0,2.0,80.0,1.0
-SE,228.0,6,4.0,5.0,8.0,5.0,8.0,7.0,5.0,2.0,79.0,2.0
-SE,231.0,6,4.0,9.0,9.0,5.0,10.0,6.0,4.0,2.0,79.0,1.0
-SE,237.0,6,7.0,6.0,8.0,8.0,8.0,6.0,3.0,2.0,78.0,2.0
-SE,242.0,6,5.0,6.0,3.0,8.0,8.0,2.0,2.0,1.0,78.0,2.0
-SE,246.0,6,6.0,5.0,6.0,8.0,10.0,6.0,4.0,2.0,78.0,1.0
-SE,247.0,6,4.0,8.0,8.0,7.0,8.0,3.0,3.0,1.0,78.0,1.0
-SE,252.0,6,4.0,4.0,3.0,7.0,7.0,3.0,2.0,1.0,78.0,1.0
-SE,254.0,6,2.0,8.0,4.0,7.0,8.0,4.0,2.0,1.0,78.0,2.0
-SE,259.0,6,4.0,8.0,8.0,7.0,7.0,6.0,3.0,2.0,78.0,2.0
-SE,260.0,6,3.0,4.0,7.0,5.0,8.0,4.0,2.0,2.0,78.0,1.0
-SE,262.0,6,5.0,6.0,8.0,7.0,8.0,4.0,4.0,1.0,78.0,1.0
-SE,265.0,6,7.0,10.0,8.0,8.0,7.0,3.0,1.0,1.0,78.0,1.0
-SE,269.0,6,1.0,5.0,7.0,8.0,5.0,5.0,4.0,2.0,,1.0
-SE,270.0,6,7.0,5.0,5.0,7.0,9.0,4.0,2.0,1.0,,1.0
-SE,273.0,6,2.0,6.0,9.0,5.0,9.0,7.0,4.0,1.0,,2.0
-SE,282.0,6,5.0,7.0,8.0,8.0,10.0,6.0,4.0,1.0,,1.0
-SE,290.0,6,5.0,4.0,3.0,3.0,9.0,4.0,3.0,2.0,78.0,1.0
-SE,292.0,6,6.0,5.0,8.0,5.0,4.0,7.0,3.0,1.0,78.0,2.0
-SE,293.0,6,5.0,8.0,9.0,8.0,7.0,6.0,3.0,2.0,,1.0
-SE,295.0,6,5.0,3.0,10.0,5.0,8.0,7.0,1.0,1.0,,2.0
-SE,298.0,6,7.0,4.0,4.0,4.0,9.0,5.0,2.0,1.0,78.0,1.0
-SE,302.0,6,2.0,3.0,7.0,6.0,8.0,5.0,4.0,1.0,,1.0
-SE,303.0,6,6.0,10.0,8.0,7.0,9.0,4.0,3.0,1.0,,1.0
-SE,305.0,6,4.0,4.0,7.0,3.0,8.0,6.0,4.0,2.0,76.0,2.0
-SE,312.0,6,3.0,8.0,7.0,8.0,10.0,6.0,3.0,2.0,,2.0
-SE,321.0,6,3.0,7.0,5.0,8.0,8.0,2.0,2.0,1.0,76.0,1.0
-SE,323.0,6,5.0,5.0,5.0,5.0,7.0,4.0,3.0,1.0,,1.0
-SE,325.0,6,4.0,8.0,8.0,6.0,5.0,6.0,4.0,1.0,,2.0
-SE,328.0,6,6.0,8.0,5.0,4.0,5.0,4.0,4.0,1.0,,2.0
-SE,331.0,6,2.0,7.0,6.0,6.0,8.0,7.0,4.0,2.0,76.0,1.0
-SE,332.0,6,4.0,5.0,4.0,7.0,7.0,5.0,3.0,2.0,76.0,2.0
-SE,334.0,6,4.0,6.0,8.0,5.0,3.0,6.0,4.0,1.0,76.0,2.0
-SE,335.0,6,3.0,6.0,7.0,7.0,10.0,7.0,5.0,2.0,76.0,1.0
-SE,336.0,6,4.0,7.0,8.0,6.0,9.0,4.0,4.0,1.0,,1.0
-SE,346.0,6,6.0,6.0,6.0,8.0,10.0,6.0,4.0,1.0,75.0,1.0
-SE,347.0,6,5.0,5.0,5.0,5.0,9.0,7.0,4.0,1.0,75.0,1.0
-SE,349.0,6,2.0,6.0,6.0,7.0,10.0,6.0,5.0,1.0,75.0,1.0
-SE,350.0,6,7.0,10.0,10.0,5.0,5.0,5.0,3.0,1.0,75.0,2.0
-SE,351.0,6,7.0,4.0,9.0,6.0,10.0,2.0,1.0,2.0,75.0,1.0
-SE,353.0,6,5.0,6.0,6.0,6.0,7.0,6.0,1.0,1.0,75.0,2.0
-SE,357.0,6,3.0,5.0,6.0,6.0,10.0,6.0,3.0,1.0,76.0,1.0
-SE,360.0,6,2.0,1.0,5.0,3.0,7.0,4.0,3.0,1.0,76.0,1.0
-SE,369.0,6,1.0,5.0,8.0,7.0,10.0,7.0,3.0,1.0,74.0,2.0
-SE,371.0,6,5.0,8.0,4.0,6.0,9.0,6.0,4.0,2.0,74.0,2.0
-SE,377.0,6,7.0,8.0,8.0,8.0,8.0,4.0,3.0,2.0,75.0,2.0
-SE,379.0,6,3.0,8.0,9.0,9.0,9.0,6.0,3.0,1.0,74.0,1.0
-SE,381.0,6,3.0,7.0,7.0,8.0,9.0,4.0,3.0,2.0,74.0,1.0
-SE,383.0,6,7.0,7.0,8.0,7.0,6.0,6.0,3.0,1.0,74.0,1.0
-SE,385.0,6,7.0,5.0,5.0,9.0,8.0,5.0,3.0,2.0,75.0,1.0
-SE,386.0,6,5.0,6.0,6.0,4.0,8.0,5.0,5.0,2.0,74.0,1.0
-SE,389.0,6,3.0,8.0,8.0,9.0,9.0,5.0,3.0,2.0,74.0,2.0
-SE,390.0,6,5.0,3.0,4.0,7.0,4.0,3.0,2.0,1.0,74.0,2.0
-SE,396.0,6,7.0,0.0,0.0,0.0,1.0,1.0,1.0,1.0,74.0,2.0
-SE,399.0,6,2.0,3.0,4.0,4.0,8.0,2.0,1.0,1.0,73.0,1.0
-SE,405.0,6,2.0,3.0,7.0,2.0,5.0,6.0,2.0,1.0,74.0,2.0
-SE,409.0,6,7.0,6.0,10.0,8.0,8.0,2.0,3.0,1.0,73.0,1.0
-SE,410.0,6,6.0,0.0,7.0,6.0,8.0,4.0,3.0,2.0,73.0,1.0
-SE,412.0,6,7.0,10.0,7.0,10.0,10.0,6.0,2.0,1.0,73.0,2.0
-SE,413.0,6,7.0,5.0,8.0,6.0,7.0,4.0,4.0,2.0,74.0,2.0
-SE,414.0,6,3.0,8.0,8.0,8.0,10.0,6.0,3.0,1.0,73.0,1.0
-SE,415.0,6,2.0,0.0,0.0,0.0,5.0,2.0,2.0,2.0,74.0,2.0
-SE,416.0,6,3.0,7.0,7.0,8.0,8.0,4.0,4.0,1.0,74.0,1.0
-SE,418.0,6,2.0,9.0,10.0,6.0,9.0,6.0,4.0,1.0,74.0,1.0
-SE,422.0,6,7.0,5.0,7.0,8.0,10.0,5.0,2.0,2.0,74.0,1.0
-SE,423.0,6,6.0,5.0,6.0,4.0,8.0,6.0,2.0,2.0,74.0,1.0
-SE,433.0,6,3.0,4.0,6.0,7.0,7.0,7.0,1.0,1.0,73.0,2.0
-SE,434.0,6,1.0,8.0,10.0,7.0,9.0,6.0,5.0,2.0,72.0,1.0
-SE,438.0,6,5.0,7.0,9.0,9.0,10.0,6.0,3.0,2.0,73.0,1.0
-SE,439.0,6,5.0,5.0,5.0,6.0,8.0,4.0,4.0,1.0,73.0,1.0
-SE,447.0,6,7.0,5.0,5.0,5.0,6.0,3.0,2.0,1.0,72.0,1.0
-SE,450.0,6,6.0,5.0,5.0,7.0,10.0,4.0,3.0,1.0,72.0,1.0
-SE,452.0,6,5.0,8.0,9.0,8.0,10.0,7.0,4.0,2.0,72.0,1.0
-SE,457.0,6,7.0,10.0,10.0,10.0,10.0,7.0,1.0,1.0,73.0,1.0
-SE,458.0,6,4.0,5.0,7.0,8.0,10.0,5.0,2.0,1.0,72.0,1.0
-SE,459.0,6,7.0,2.0,3.0,3.0,4.0,5.0,2.0,2.0,72.0,2.0
-SE,463.0,6,7.0,6.0,6.0,4.0,8.0,7.0,3.0,1.0,72.0,1.0
-SE,465.0,6,7.0,4.0,8.0,5.0,9.0,3.0,2.0,1.0,73.0,1.0
-SE,469.0,6,4.0,7.0,3.0,6.0,8.0,4.0,3.0,1.0,72.0,1.0
-SE,470.0,6,5.0,1.0,2.0,1.0,9.0,6.0,1.0,1.0,72.0,1.0
-SE,471.0,6,6.0,8.0,10.0,8.0,8.0,6.0,4.0,2.0,71.0,1.0
-SE,474.0,6,4.0,9.0,8.0,4.0,9.0,7.0,3.0,2.0,72.0,2.0
-SE,475.0,6,4.0,5.0,8.0,6.0,8.0,4.0,3.0,2.0,71.0,1.0
-SE,479.0,6,6.0,0.0,5.0,2.0,10.0,4.0,3.0,2.0,71.0,1.0
-SE,480.0,6,5.0,7.0,5.0,5.0,10.0,7.0,4.0,2.0,71.0,1.0
-SE,481.0,6,4.0,9.0,9.0,8.0,9.0,4.0,2.0,2.0,71.0,1.0
-SE,494.0,6,2.0,5.0,5.0,3.0,10.0,3.0,2.0,1.0,72.0,1.0
-SE,495.0,6,4.0,7.0,8.0,7.0,7.0,4.0,1.0,1.0,71.0,1.0
-SE,498.0,6,5.0,6.0,7.0,3.0,7.0,5.0,2.0,2.0,71.0,1.0
-SE,499.0,6,4.0,,10.0,8.0,9.0,6.0,3.0,2.0,71.0,1.0
-SE,502.0,6,5.0,6.0,6.0,7.0,9.0,4.0,3.0,1.0,71.0,1.0
-SE,504.0,6,4.0,4.0,8.0,6.0,4.0,6.0,2.0,2.0,72.0,2.0
-SE,505.0,6,2.0,5.0,5.0,5.0,8.0,6.0,4.0,2.0,71.0,1.0
-SE,507.0,6,4.0,7.0,7.0,5.0,8.0,4.0,3.0,1.0,71.0,1.0
-SE,510.0,6,5.0,5.0,7.0,5.0,10.0,6.0,3.0,1.0,72.0,1.0
-SE,513.0,6,4.0,7.0,6.0,8.0,10.0,5.0,3.0,2.0,71.0,1.0
-SE,518.0,6,7.0,7.0,7.0,6.0,7.0,7.0,4.0,1.0,71.0,1.0
-SE,519.0,6,5.0,5.0,9.0,8.0,8.0,5.0,3.0,1.0,71.0,1.0
-SE,520.0,6,2.0,7.0,8.0,8.0,9.0,6.0,4.0,1.0,71.0,1.0
-SE,522.0,6,3.0,3.0,5.0,5.0,5.0,5.0,3.0,1.0,71.0,1.0
-SE,524.0,6,6.0,5.0,5.0,8.0,8.0,6.0,3.0,2.0,70.0,2.0
-SE,527.0,6,5.0,5.0,5.0,5.0,8.0,5.0,3.0,1.0,70.0,1.0
-SE,530.0,6,3.0,7.0,7.0,6.0,8.0,5.0,3.0,2.0,70.0,1.0
-SE,535.0,6,7.0,3.0,3.0,5.0,7.0,3.0,2.0,1.0,70.0,1.0
-SE,537.0,6,3.0,7.0,8.0,9.0,9.0,4.0,1.0,1.0,70.0,2.0
-SE,538.0,6,7.0,9.0,9.0,8.0,9.0,6.0,3.0,1.0,70.0,2.0
-SE,545.0,6,5.0,7.0,7.0,6.0,8.0,4.0,3.0,2.0,70.0,2.0
-SE,552.0,6,3.0,6.0,5.0,5.0,8.0,4.0,2.0,2.0,70.0,1.0
-SE,554.0,6,7.0,7.0,6.0,7.0,10.0,4.0,3.0,2.0,71.0,1.0
-SE,559.0,6,6.0,8.0,8.0,7.0,8.0,6.0,2.0,1.0,70.0,1.0
-SE,561.0,6,5.0,6.0,6.0,5.0,8.0,6.0,4.0,1.0,70.0,2.0
-SE,569.0,6,5.0,8.0,8.0,8.0,8.0,4.0,4.0,1.0,70.0,1.0
-SE,573.0,6,5.0,6.0,5.0,7.0,10.0,7.0,4.0,2.0,70.0,2.0
-SE,576.0,6,6.0,8.0,8.0,8.0,10.0,6.0,4.0,2.0,70.0,1.0
-SE,577.0,6,4.0,3.0,8.0,2.0,8.0,5.0,3.0,1.0,70.0,1.0
-SE,578.0,6,7.0,8.0,7.0,8.0,5.0,3.0,2.0,1.0,69.0,1.0
-SE,579.0,6,7.0,7.0,8.0,8.0,8.0,4.0,3.0,1.0,69.0,2.0
-SE,580.0,6,5.0,3.0,5.0,3.0,8.0,5.0,3.0,2.0,69.0,1.0
-SE,582.0,6,4.0,8.0,7.0,8.0,9.0,5.0,3.0,1.0,69.0,1.0
-SE,585.0,6,6.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,69.0,2.0
-SE,588.0,6,4.0,0.0,4.0,8.0,8.0,4.0,3.0,1.0,69.0,2.0
-SE,590.0,6,5.0,8.0,7.0,8.0,8.0,4.0,3.0,1.0,69.0,1.0
-SE,593.0,6,3.0,8.0,8.0,7.0,10.0,6.0,2.0,1.0,69.0,1.0
-SE,596.0,6,4.0,7.0,7.0,7.0,7.0,7.0,4.0,2.0,70.0,2.0
-SE,600.0,6,6.0,5.0,3.0,6.0,8.0,2.0,3.0,1.0,70.0,2.0
-SE,606.0,6,1.0,4.0,7.0,9.0,9.0,4.0,5.0,1.0,70.0,1.0
-SE,608.0,6,6.0,8.0,8.0,8.0,10.0,5.0,3.0,1.0,69.0,1.0
-SE,610.0,6,4.0,4.0,7.0,7.0,10.0,3.0,5.0,1.0,69.0,1.0
-SE,611.0,6,5.0,5.0,2.0,8.0,8.0,4.0,3.0,1.0,69.0,1.0
-SE,614.0,6,4.0,7.0,7.0,4.0,8.0,6.0,2.0,2.0,69.0,1.0
-SE,615.0,6,7.0,5.0,5.0,5.0,9.0,5.0,2.0,2.0,69.0,1.0
-SE,617.0,6,6.0,5.0,5.0,5.0,5.0,5.0,2.0,1.0,70.0,2.0
-SE,618.0,6,5.0,8.0,8.0,5.0,8.0,6.0,3.0,1.0,69.0,1.0
-SE,624.0,6,4.0,7.0,8.0,9.0,9.0,5.0,1.0,1.0,68.0,1.0
-SE,630.0,6,3.0,5.0,5.0,5.0,7.0,6.0,3.0,2.0,68.0,1.0
-SE,635.0,6,6.0,7.0,9.0,5.0,9.0,4.0,3.0,2.0,68.0,1.0
-SE,640.0,6,4.0,8.0,10.0,7.0,10.0,7.0,3.0,2.0,68.0,1.0
-SE,641.0,6,7.0,4.0,5.0,5.0,8.0,6.0,3.0,2.0,69.0,2.0
-SE,644.0,6,5.0,2.0,5.0,7.0,9.0,4.0,4.0,1.0,68.0,1.0
-SE,647.0,6,5.0,9.0,8.0,8.0,8.0,4.0,3.0,2.0,68.0,2.0
-SE,648.0,6,3.0,6.0,6.0,8.0,9.0,6.0,3.0,1.0,69.0,1.0
-SE,649.0,6,6.0,7.0,8.0,8.0,8.0,5.0,3.0,2.0,69.0,1.0
-SE,654.0,6,7.0,7.0,6.0,5.0,8.0,3.0,1.0,1.0,68.0,1.0
-SE,656.0,6,3.0,6.0,8.0,7.0,10.0,5.0,3.0,1.0,69.0,1.0
-SE,657.0,6,7.0,8.0,7.0,7.0,6.0,6.0,3.0,2.0,68.0,2.0
-SE,664.0,6,5.0,7.0,8.0,10.0,8.0,3.0,2.0,1.0,68.0,1.0
-SE,665.0,6,3.0,7.0,7.0,6.0,8.0,3.0,1.0,1.0,68.0,2.0
-SE,670.0,6,6.0,8.0,6.0,5.0,10.0,6.0,2.0,1.0,67.0,2.0
-SE,672.0,6,5.0,4.0,7.0,8.0,8.0,2.0,2.0,2.0,68.0,2.0
-SE,673.0,6,1.0,0.0,0.0,0.0,7.0,7.0,3.0,2.0,68.0,1.0
-SE,676.0,6,3.0,7.0,6.0,5.0,9.0,6.0,2.0,2.0,67.0,1.0
-SE,677.0,6,4.0,7.0,8.0,7.0,8.0,6.0,4.0,1.0,67.0,1.0
-SE,680.0,6,4.0,9.0,8.0,9.0,9.0,6.0,3.0,1.0,68.0,1.0
-SE,681.0,6,4.0,6.0,4.0,4.0,8.0,5.0,4.0,1.0,68.0,1.0
-SE,682.0,6,5.0,5.0,7.0,6.0,9.0,5.0,3.0,2.0,67.0,1.0
-SE,684.0,6,2.0,8.0,7.0,8.0,9.0,7.0,3.0,2.0,67.0,1.0
-SE,685.0,6,4.0,4.0,4.0,5.0,7.0,4.0,2.0,1.0,68.0,2.0
-SE,687.0,6,4.0,5.0,9.0,9.0,10.0,6.0,3.0,1.0,68.0,1.0
-SE,690.0,6,4.0,7.0,8.0,7.0,9.0,7.0,3.0,1.0,67.0,1.0
-SE,691.0,6,3.0,1.0,5.0,4.0,6.0,4.0,3.0,2.0,67.0,1.0
-SE,692.0,6,7.0,6.0,7.0,6.0,9.0,7.0,4.0,2.0,67.0,2.0
-SE,694.0,6,7.0,5.0,8.0,7.0,9.0,6.0,2.0,2.0,68.0,1.0
-SE,697.0,6,3.0,9.0,9.0,8.0,9.0,7.0,5.0,2.0,67.0,1.0
-SE,703.0,6,3.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,67.0,1.0
-SE,708.0,6,4.0,8.0,8.0,8.0,8.0,2.0,2.0,1.0,67.0,1.0
-SE,709.0,6,2.0,5.0,9.0,5.0,8.0,6.0,4.0,2.0,67.0,2.0
-SE,712.0,6,3.0,5.0,8.0,8.0,8.0,6.0,3.0,2.0,68.0,2.0
-SE,718.0,6,2.0,8.0,7.0,7.0,8.0,6.0,3.0,1.0,68.0,1.0
-SE,719.0,6,7.0,7.0,8.0,4.0,7.0,6.0,5.0,2.0,67.0,2.0
-SE,720.0,6,3.0,7.0,7.0,6.0,7.0,6.0,3.0,2.0,,2.0
-SE,723.0,6,7.0,7.0,7.0,7.0,9.0,6.0,4.0,1.0,67.0,1.0
-SE,726.0,6,3.0,9.0,10.0,7.0,10.0,4.0,2.0,1.0,,1.0
-SE,728.0,6,4.0,5.0,4.0,7.0,10.0,4.0,3.0,1.0,67.0,1.0
-SE,740.0,6,5.0,7.0,7.0,5.0,8.0,4.0,3.0,1.0,,1.0
-SE,741.0,6,6.0,10.0,8.0,8.0,8.0,6.0,4.0,1.0,,1.0
-SE,742.0,6,5.0,8.0,8.0,7.0,9.0,7.0,4.0,1.0,,1.0
-SE,744.0,6,4.0,7.0,8.0,5.0,9.0,5.0,2.0,1.0,,1.0
-SE,746.0,6,4.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,,1.0
-SE,748.0,6,6.0,8.0,9.0,8.0,10.0,7.0,4.0,1.0,,2.0
-SE,750.0,6,6.0,8.0,5.0,5.0,8.0,4.0,3.0,1.0,,1.0
-SE,753.0,6,7.0,8.0,9.0,9.0,10.0,7.0,4.0,1.0,,1.0
-SE,756.0,6,2.0,6.0,6.0,5.0,7.0,5.0,4.0,2.0,,2.0
-SE,761.0,6,2.0,8.0,8.0,9.0,10.0,4.0,4.0,2.0,,1.0
-SE,764.0,6,2.0,8.0,8.0,7.0,8.0,3.0,2.0,1.0,,1.0
-SE,767.0,6,3.0,5.0,5.0,5.0,6.0,6.0,2.0,1.0,,1.0
-SE,769.0,6,5.0,4.0,7.0,3.0,8.0,4.0,3.0,2.0,67.0,1.0
-SE,770.0,6,5.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,,1.0
-SE,777.0,6,4.0,6.0,7.0,7.0,8.0,6.0,3.0,1.0,67.0,2.0
-SE,778.0,6,4.0,6.0,7.0,7.0,9.0,4.0,4.0,1.0,,1.0
-SE,779.0,6,4.0,5.0,8.0,5.0,10.0,6.0,2.0,2.0,,1.0
-SE,780.0,6,3.0,8.0,8.0,7.0,9.0,6.0,4.0,2.0,67.0,1.0
-SE,787.0,6,1.0,8.0,8.0,8.0,8.0,5.0,3.0,1.0,67.0,1.0
-SE,789.0,6,5.0,6.0,8.0,7.0,8.0,7.0,2.0,2.0,,1.0
-SE,793.0,6,0.0,0.0,10.0,8.0,9.0,5.0,3.0,1.0,65.0,1.0
-SE,796.0,6,5.0,3.0,10.0,5.0,10.0,4.0,2.0,2.0,65.0,1.0
-SE,798.0,6,6.0,7.0,7.0,8.0,8.0,4.0,2.0,1.0,65.0,1.0
-SE,802.0,6,5.0,4.0,8.0,8.0,9.0,4.0,3.0,2.0,65.0,1.0
-SE,803.0,6,6.0,8.0,10.0,8.0,9.0,3.0,2.0,2.0,65.0,1.0
-SE,806.0,6,5.0,7.0,7.0,2.0,8.0,4.0,2.0,1.0,65.0,1.0
-SE,807.0,6,5.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,65.0,1.0
-SE,808.0,6,6.0,7.0,7.0,7.0,10.0,4.0,3.0,2.0,65.0,1.0
-SE,810.0,6,1.0,8.0,8.0,5.0,9.0,7.0,3.0,2.0,65.0,1.0
-SE,817.0,6,6.0,2.0,6.0,6.0,10.0,4.0,3.0,1.0,65.0,1.0
-SE,818.0,6,4.0,7.0,7.0,6.0,6.0,6.0,2.0,2.0,65.0,1.0
-SE,823.0,6,7.0,7.0,4.0,5.0,10.0,6.0,2.0,2.0,,1.0
-SE,824.0,6,7.0,4.0,2.0,9.0,6.0,6.0,3.0,2.0,65.0,1.0
-SE,827.0,6,4.0,9.0,9.0,8.0,8.0,7.0,4.0,2.0,65.0,2.0
-SE,832.0,6,2.0,8.0,8.0,8.0,9.0,6.0,3.0,1.0,65.0,1.0
-SE,834.0,6,6.0,5.0,6.0,9.0,9.0,6.0,4.0,2.0,,1.0
-SE,837.0,6,2.0,6.0,6.0,3.0,7.0,4.0,4.0,1.0,65.0,1.0
-SE,838.0,6,7.0,9.0,7.0,5.0,8.0,4.0,2.0,2.0,,2.0
-SE,839.0,6,1.0,0.0,7.0,5.0,6.0,5.0,4.0,2.0,,2.0
-SE,840.0,6,7.0,4.0,7.0,6.0,9.0,4.0,3.0,1.0,65.0,1.0
-SE,841.0,6,3.0,5.0,7.0,6.0,5.0,7.0,3.0,1.0,,1.0
-SE,846.0,6,4.0,6.0,9.0,8.0,9.0,6.0,4.0,2.0,65.0,1.0
-SE,847.0,6,7.0,5.0,7.0,8.0,10.0,4.0,3.0,2.0,65.0,1.0
-SE,855.0,6,4.0,5.0,6.0,3.0,9.0,3.0,1.0,1.0,65.0,1.0
-SE,878.0,6,3.0,8.0,8.0,7.0,9.0,4.0,3.0,2.0,64.0,2.0
-SE,880.0,6,2.0,7.0,7.0,7.0,6.0,6.0,3.0,1.0,64.0,1.0
-SE,886.0,6,7.0,0.0,3.0,3.0,1.0,7.0,1.0,2.0,65.0,2.0
-SE,887.0,6,3.0,3.0,5.0,3.0,7.0,7.0,3.0,2.0,65.0,1.0
-SE,888.0,6,7.0,6.0,7.0,7.0,9.0,5.0,1.0,1.0,64.0,1.0
-SE,889.0,6,0.0,8.0,9.0,9.0,10.0,5.0,3.0,2.0,64.0,1.0
-SE,890.0,6,3.0,6.0,8.0,7.0,9.0,7.0,2.0,1.0,64.0,1.0
-SE,891.0,6,2.0,5.0,7.0,7.0,7.0,6.0,4.0,2.0,64.0,1.0
-SE,893.0,6,4.0,5.0,6.0,6.0,5.0,4.0,2.0,2.0,65.0,1.0
-SE,899.0,6,4.0,4.0,5.0,3.0,5.0,7.0,3.0,1.0,64.0,1.0
-SE,904.0,6,0.0,3.0,4.0,4.0,7.0,1.0,3.0,1.0,63.0,2.0
-SE,905.0,6,6.0,8.0,7.0,7.0,6.0,6.0,2.0,1.0,63.0,1.0
-SE,908.0,6,4.0,5.0,4.0,5.0,10.0,5.0,2.0,1.0,64.0,1.0
-SE,915.0,6,6.0,7.0,9.0,7.0,8.0,6.0,2.0,2.0,64.0,1.0
-SE,916.0,6,6.0,0.0,5.0,5.0,7.0,4.0,3.0,2.0,64.0,2.0
-SE,918.0,6,4.0,6.0,5.0,6.0,8.0,6.0,3.0,1.0,64.0,2.0
-SE,922.0,6,4.0,8.0,8.0,8.0,8.0,3.0,3.0,2.0,63.0,1.0
-SE,926.0,6,3.0,8.0,8.0,4.0,7.0,7.0,2.0,2.0,63.0,2.0
-SE,934.0,6,4.0,5.0,5.0,7.0,7.0,3.0,2.0,1.0,63.0,1.0
-SE,936.0,6,4.0,7.0,7.0,8.0,7.0,6.0,3.0,2.0,63.0,2.0
-SE,938.0,6,2.0,0.0,10.0,9.0,8.0,7.0,4.0,2.0,63.0,2.0
-SE,940.0,6,5.0,7.0,8.0,7.0,8.0,5.0,2.0,1.0,63.0,1.0
-SE,945.0,6,4.0,1.0,8.0,7.0,10.0,4.0,4.0,2.0,64.0,1.0
-SE,947.0,6,5.0,5.0,8.0,6.0,9.0,4.0,2.0,2.0,63.0,1.0
-SE,952.0,6,3.0,1.0,5.0,5.0,10.0,6.0,3.0,2.0,63.0,1.0
-SE,954.0,6,1.0,10.0,10.0,8.0,9.0,7.0,3.0,2.0,63.0,2.0
-SE,959.0,6,4.0,6.0,8.0,9.0,9.0,3.0,1.0,1.0,63.0,1.0
-SE,962.0,6,4.0,7.0,8.0,8.0,8.0,4.0,3.0,1.0,63.0,1.0
-SE,963.0,6,3.0,9.0,9.0,6.0,9.0,3.0,4.0,1.0,63.0,2.0
-SE,967.0,6,5.0,7.0,3.0,7.0,8.0,6.0,3.0,1.0,64.0,2.0
-SE,973.0,6,5.0,7.0,8.0,7.0,4.0,7.0,3.0,2.0,63.0,2.0
-SE,975.0,6,3.0,7.0,4.0,8.0,10.0,6.0,4.0,2.0,62.0,1.0
-SE,979.0,6,6.0,8.0,8.0,5.0,8.0,6.0,1.0,2.0,62.0,1.0
-SE,985.0,6,4.0,4.0,5.0,6.0,7.0,6.0,4.0,2.0,63.0,1.0
-SE,987.0,6,5.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,62.0,1.0
-SE,989.0,6,1.0,3.0,5.0,5.0,6.0,6.0,3.0,2.0,63.0,2.0
-SE,990.0,6,5.0,8.0,8.0,7.0,8.0,6.0,3.0,1.0,63.0,1.0
-SE,991.0,6,5.0,7.0,8.0,7.0,8.0,5.0,2.0,1.0,63.0,1.0
-SE,993.0,6,2.0,6.0,7.0,8.0,7.0,3.0,2.0,1.0,62.0,2.0
-SE,995.0,6,2.0,8.0,6.0,6.0,7.0,2.0,3.0,2.0,63.0,2.0
-SE,996.0,6,4.0,7.0,7.0,7.0,7.0,6.0,3.0,2.0,62.0,2.0
-SE,997.0,6,4.0,10.0,0.0,6.0,8.0,6.0,4.0,2.0,62.0,2.0
-SE,1000.0,6,2.0,8.0,8.0,9.0,10.0,7.0,2.0,1.0,62.0,1.0
-SE,1001.0,6,4.0,8.0,7.0,5.0,9.0,5.0,4.0,2.0,62.0,1.0
-SE,1007.0,6,7.0,5.0,10.0,10.0,10.0,3.0,5.0,1.0,62.0,1.0
-SE,1014.0,6,4.0,8.0,6.0,10.0,9.0,6.0,4.0,1.0,63.0,1.0
-SE,1017.0,6,6.0,6.0,6.0,6.0,9.0,5.0,2.0,2.0,62.0,1.0
-SE,1018.0,6,3.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,63.0,1.0
-SE,1021.0,6,6.0,8.0,9.0,5.0,9.0,7.0,,2.0,62.0,2.0
-SE,1025.0,6,5.0,8.0,9.0,6.0,10.0,6.0,2.0,1.0,62.0,1.0
-SE,1026.0,6,3.0,8.0,8.0,7.0,9.0,6.0,3.0,1.0,62.0,1.0
-SE,1032.0,6,6.0,3.0,6.0,4.0,9.0,3.0,3.0,1.0,62.0,1.0
-SE,1035.0,6,4.0,7.0,7.0,6.0,8.0,6.0,1.0,1.0,61.0,1.0
-SE,1037.0,6,2.0,5.0,5.0,7.0,4.0,7.0,2.0,2.0,62.0,2.0
-SE,1038.0,6,3.0,2.0,4.0,3.0,6.0,7.0,3.0,1.0,61.0,1.0
-SE,1041.0,6,3.0,5.0,7.0,8.0,8.0,7.0,3.0,2.0,62.0,1.0
-SE,1047.0,6,5.0,7.0,8.0,6.0,8.0,6.0,3.0,1.0,61.0,1.0
-SE,1050.0,6,2.0,8.0,7.0,7.0,8.0,6.0,3.0,1.0,61.0,2.0
-SE,1051.0,6,1.0,7.0,8.0,6.0,8.0,7.0,4.0,2.0,61.0,1.0
-SE,1053.0,6,5.0,8.0,7.0,7.0,9.0,5.0,2.0,1.0,61.0,1.0
-SE,1057.0,6,6.0,4.0,8.0,8.0,10.0,3.0,5.0,1.0,61.0,2.0
-SE,1067.0,6,6.0,7.0,6.0,4.0,5.0,4.0,1.0,1.0,61.0,1.0
-SE,1069.0,6,7.0,7.0,2.0,10.0,8.0,3.0,1.0,2.0,62.0,1.0
-SE,1075.0,6,3.0,5.0,8.0,4.0,7.0,7.0,3.0,2.0,61.0,1.0
-SE,1078.0,6,4.0,9.0,10.0,10.0,7.0,6.0,3.0,2.0,60.0,1.0
-SE,1085.0,6,5.0,3.0,5.0,7.0,8.0,4.0,3.0,1.0,60.0,2.0
-SE,1086.0,6,3.0,7.0,8.0,8.0,7.0,4.0,4.0,1.0,60.0,1.0
-SE,1090.0,6,4.0,3.0,5.0,5.0,6.0,7.0,3.0,2.0,61.0,2.0
-SE,1092.0,6,7.0,5.0,4.0,6.0,7.0,4.0,4.0,1.0,60.0,1.0
-SE,1095.0,6,2.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,61.0,1.0
-SE,1096.0,6,4.0,5.0,7.0,8.0,7.0,3.0,3.0,1.0,60.0,1.0
-SE,1103.0,6,4.0,8.0,8.0,7.0,7.0,5.0,3.0,1.0,60.0,2.0
-SE,1106.0,6,4.0,5.0,7.0,6.0,7.0,7.0,3.0,2.0,60.0,2.0
-SE,1107.0,6,4.0,7.0,7.0,5.0,8.0,4.0,3.0,2.0,60.0,2.0
-SE,1110.0,6,2.0,8.0,8.0,5.0,7.0,7.0,1.0,1.0,61.0,1.0
-SE,1113.0,6,7.0,7.0,7.0,7.0,8.0,6.0,4.0,2.0,60.0,2.0
-SE,1114.0,6,6.0,5.0,5.0,5.0,10.0,6.0,3.0,1.0,61.0,1.0
-SE,1115.0,6,4.0,7.0,6.0,5.0,8.0,7.0,3.0,2.0,61.0,1.0
-SE,1118.0,6,6.0,4.0,6.0,6.0,8.0,4.0,3.0,2.0,61.0,1.0
-SE,1119.0,6,5.0,3.0,5.0,5.0,7.0,6.0,4.0,1.0,61.0,2.0
-SE,1120.0,6,5.0,4.0,3.0,5.0,6.0,7.0,4.0,2.0,60.0,2.0
-SE,1131.0,6,3.0,5.0,5.0,3.0,8.0,4.0,3.0,1.0,60.0,1.0
-SE,1134.0,6,5.0,5.0,3.0,5.0,8.0,3.0,1.0,2.0,59.0,1.0
-SE,1140.0,6,3.0,4.0,5.0,5.0,9.0,6.0,3.0,2.0,60.0,1.0
-SE,1143.0,6,6.0,9.0,10.0,10.0,10.0,7.0,3.0,2.0,59.0,1.0
-SE,1155.0,6,2.0,8.0,8.0,8.0,10.0,7.0,4.0,1.0,59.0,1.0
-SE,1162.0,6,3.0,8.0,9.0,7.0,8.0,5.0,2.0,2.0,59.0,1.0
-SE,1167.0,6,4.0,8.0,9.0,6.0,9.0,5.0,4.0,2.0,59.0,1.0
-SE,1175.0,6,3.0,7.0,5.0,7.0,7.0,4.0,4.0,1.0,58.0,1.0
-SE,1183.0,6,4.0,3.0,3.0,2.0,7.0,5.0,1.0,2.0,59.0,2.0
-SE,1187.0,6,4.0,4.0,5.0,4.0,8.0,5.0,3.0,1.0,58.0,1.0
-SE,1196.0,6,4.0,3.0,5.0,6.0,7.0,7.0,3.0,2.0,59.0,2.0
-SE,1197.0,6,4.0,8.0,8.0,7.0,9.0,7.0,2.0,1.0,58.0,1.0
-SE,1208.0,6,2.0,8.0,8.0,7.0,8.0,7.0,4.0,2.0,58.0,1.0
-SE,1211.0,6,1.0,10.0,10.0,10.0,9.0,6.0,3.0,2.0,,1.0
-SE,1214.0,6,2.0,7.0,8.0,5.0,9.0,4.0,3.0,2.0,59.0,1.0
-SE,1215.0,6,3.0,7.0,7.0,5.0,8.0,5.0,3.0,2.0,58.0,2.0
-SE,1217.0,6,3.0,7.0,7.0,7.0,7.0,7.0,2.0,1.0,58.0,1.0
-SE,1220.0,6,6.0,8.0,5.0,9.0,8.0,7.0,3.0,1.0,58.0,1.0
-SE,1221.0,6,4.0,8.0,7.0,4.0,8.0,7.0,4.0,2.0,58.0,2.0
-SE,1225.0,6,2.0,7.0,10.0,8.0,7.0,5.0,3.0,2.0,57.0,1.0
-SE,1228.0,6,2.0,5.0,8.0,5.0,9.0,4.0,3.0,2.0,57.0,1.0
-SE,1231.0,6,3.0,9.0,7.0,9.0,10.0,7.0,3.0,2.0,58.0,1.0
-SE,1236.0,6,2.0,5.0,5.0,6.0,7.0,6.0,3.0,1.0,58.0,1.0
-SE,1238.0,6,2.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,57.0,1.0
-SE,1240.0,6,4.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,57.0,1.0
-SE,1243.0,6,4.0,1.0,5.0,5.0,9.0,4.0,3.0,1.0,58.0,1.0
-SE,1244.0,6,5.0,2.0,5.0,3.0,9.0,6.0,1.0,2.0,57.0,1.0
-SE,1246.0,6,3.0,6.0,7.0,7.0,10.0,7.0,4.0,1.0,57.0,1.0
-SE,1247.0,6,7.0,2.0,5.0,0.0,10.0,7.0,2.0,2.0,57.0,1.0
-SE,1248.0,6,3.0,7.0,7.0,7.0,8.0,3.0,3.0,1.0,57.0,1.0
-SE,1251.0,6,4.0,6.0,6.0,3.0,7.0,6.0,3.0,1.0,57.0,1.0
-SE,1252.0,6,3.0,8.0,7.0,3.0,7.0,7.0,2.0,2.0,58.0,2.0
-SE,1253.0,6,4.0,5.0,5.0,2.0,8.0,4.0,2.0,1.0,58.0,1.0
-SE,1256.0,6,6.0,5.0,7.0,4.0,10.0,5.0,5.0,1.0,57.0,1.0
-SE,1258.0,6,3.0,7.0,5.0,2.0,9.0,6.0,3.0,2.0,57.0,1.0
-SE,1259.0,6,3.0,7.0,7.0,8.0,8.0,6.0,2.0,2.0,58.0,2.0
-SE,1263.0,6,4.0,7.0,6.0,5.0,7.0,4.0,2.0,2.0,57.0,1.0
-SE,1264.0,6,3.0,7.0,9.0,5.0,9.0,5.0,3.0,1.0,57.0,1.0
-SE,1271.0,6,2.0,9.0,9.0,7.0,8.0,6.0,3.0,2.0,57.0,1.0
-SE,1274.0,6,4.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,56.0,2.0
-SE,1279.0,6,3.0,6.0,6.0,4.0,5.0,4.0,3.0,2.0,57.0,1.0
-SE,1286.0,6,5.0,6.0,6.0,6.0,5.0,4.0,2.0,2.0,57.0,1.0
-SE,1287.0,6,2.0,8.0,8.0,5.0,7.0,6.0,4.0,1.0,56.0,1.0
-SE,1298.0,6,6.0,4.0,6.0,7.0,9.0,7.0,3.0,1.0,56.0,1.0
-SE,1302.0,6,4.0,6.0,4.0,3.0,8.0,7.0,4.0,1.0,56.0,1.0
-SE,1314.0,6,2.0,6.0,5.0,7.0,6.0,7.0,3.0,2.0,57.0,1.0
-SE,1315.0,6,1.0,7.0,5.0,5.0,6.0,3.0,2.0,1.0,56.0,1.0
-SE,1316.0,6,1.0,7.0,8.0,5.0,7.0,4.0,3.0,2.0,56.0,1.0
-SE,1318.0,6,2.0,3.0,3.0,3.0,7.0,4.0,2.0,2.0,57.0,2.0
-SE,1321.0,6,2.0,8.0,8.0,7.0,9.0,6.0,2.0,2.0,56.0,2.0
-SE,1325.0,6,5.0,4.0,6.0,6.0,6.0,6.0,3.0,1.0,56.0,1.0
-SE,1334.0,6,5.0,6.0,7.0,7.0,7.0,6.0,3.0,2.0,55.0,2.0
-SE,1336.0,6,3.0,3.0,3.0,3.0,10.0,7.0,3.0,2.0,55.0,1.0
-SE,1341.0,6,4.0,8.0,6.0,8.0,7.0,7.0,3.0,1.0,55.0,2.0
-SE,1343.0,6,2.0,7.0,8.0,5.0,7.0,6.0,2.0,1.0,55.0,1.0
-SE,1344.0,6,4.0,8.0,8.0,8.0,8.0,6.0,3.0,2.0,55.0,1.0
-SE,1345.0,6,1.0,8.0,7.0,5.0,7.0,4.0,3.0,1.0,55.0,1.0
-SE,1348.0,6,2.0,8.0,7.0,7.0,8.0,6.0,3.0,1.0,56.0,1.0
-SE,1353.0,6,2.0,8.0,9.0,9.0,9.0,2.0,2.0,2.0,55.0,1.0
-SE,1358.0,6,6.0,5.0,7.0,4.0,5.0,6.0,2.0,1.0,55.0,1.0
-SE,1360.0,6,2.0,8.0,8.0,5.0,8.0,6.0,3.0,1.0,56.0,1.0
-SE,1361.0,6,3.0,7.0,7.0,10.0,10.0,6.0,3.0,2.0,55.0,1.0
-SE,1365.0,6,7.0,5.0,5.0,7.0,8.0,7.0,2.0,1.0,56.0,1.0
-SE,1366.0,6,5.0,5.0,5.0,5.0,8.0,6.0,2.0,1.0,55.0,1.0
-SE,1370.0,6,2.0,8.0,8.0,5.0,7.0,5.0,3.0,1.0,55.0,1.0
-SE,1371.0,6,2.0,3.0,7.0,7.0,8.0,4.0,2.0,1.0,56.0,1.0
-SE,1385.0,6,4.0,8.0,8.0,6.0,8.0,4.0,2.0,1.0,54.0,1.0
-SE,1394.0,6,3.0,2.0,5.0,3.0,7.0,6.0,2.0,1.0,54.0,2.0
-SE,1400.0,6,1.0,7.0,7.0,7.0,9.0,7.0,5.0,2.0,55.0,2.0
-SE,1405.0,6,4.0,8.0,8.0,8.0,9.0,6.0,3.0,2.0,54.0,1.0
-SE,1408.0,6,7.0,6.0,4.0,8.0,10.0,5.0,3.0,2.0,54.0,2.0
-SE,1412.0,6,2.0,3.0,3.0,5.0,5.0,7.0,2.0,1.0,54.0,1.0
-SE,1413.0,6,3.0,8.0,7.0,7.0,9.0,7.0,2.0,1.0,54.0,1.0
-SE,1416.0,6,1.0,9.0,8.0,6.0,10.0,7.0,4.0,1.0,54.0,1.0
-SE,1418.0,6,5.0,2.0,4.0,4.0,7.0,7.0,3.0,1.0,55.0,2.0
-SE,1425.0,6,3.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,54.0,1.0
-SE,1429.0,6,2.0,7.0,7.0,6.0,6.0,6.0,3.0,2.0,54.0,2.0
-SE,1430.0,6,2.0,3.0,3.0,2.0,10.0,2.0,1.0,1.0,55.0,1.0
-SE,1431.0,6,7.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,54.0,1.0
-SE,1432.0,6,3.0,5.0,3.0,2.0,7.0,4.0,3.0,2.0,54.0,2.0
-SE,1435.0,6,3.0,3.0,4.0,6.0,5.0,6.0,2.0,2.0,54.0,2.0
-SE,1439.0,6,5.0,4.0,7.0,7.0,8.0,7.0,3.0,2.0,53.0,1.0
-SE,1440.0,6,3.0,9.0,9.0,9.0,8.0,6.0,3.0,1.0,53.0,1.0
-SE,1442.0,6,3.0,7.0,7.0,6.0,8.0,3.0,2.0,2.0,53.0,1.0
-SE,1444.0,6,2.0,5.0,6.0,5.0,7.0,7.0,3.0,1.0,53.0,1.0
-SE,1445.0,6,2.0,6.0,6.0,6.0,7.0,7.0,3.0,2.0,54.0,1.0
-SE,1448.0,6,2.0,7.0,7.0,7.0,5.0,4.0,2.0,2.0,54.0,2.0
-SE,1453.0,6,1.0,1.0,7.0,3.0,10.0,4.0,3.0,1.0,53.0,1.0
-SE,1455.0,6,1.0,9.0,8.0,3.0,9.0,4.0,3.0,2.0,53.0,2.0
-SE,1463.0,6,2.0,9.0,10.0,9.0,9.0,4.0,,2.0,53.0,1.0
-SE,1468.0,6,3.0,8.0,8.0,6.0,10.0,6.0,3.0,2.0,53.0,1.0
-SE,1473.0,6,7.0,6.0,8.0,7.0,9.0,6.0,2.0,1.0,53.0,1.0
-SE,1479.0,6,3.0,3.0,3.0,3.0,9.0,7.0,5.0,1.0,54.0,1.0
-SE,1484.0,6,5.0,7.0,8.0,8.0,9.0,4.0,1.0,2.0,53.0,1.0
-SE,1487.0,6,5.0,5.0,5.0,5.0,2.0,3.0,2.0,2.0,54.0,2.0
-SE,1488.0,6,0.0,8.0,4.0,8.0,8.0,6.0,3.0,1.0,53.0,1.0
-SE,1491.0,6,2.0,7.0,8.0,9.0,7.0,6.0,3.0,1.0,54.0,2.0
-SE,1492.0,6,4.0,8.0,8.0,5.0,8.0,4.0,2.0,1.0,43.0,1.0
-SE,1494.0,6,1.0,0.0,5.0,5.0,,7.0,2.0,2.0,53.0,2.0
-SE,1497.0,6,7.0,10.0,10.0,6.0,10.0,6.0,3.0,2.0,54.0,1.0
-SE,1498.0,6,1.0,2.0,3.0,3.0,5.0,2.0,2.0,2.0,52.0,2.0
-SE,1499.0,6,5.0,7.0,4.0,6.0,9.0,7.0,4.0,1.0,52.0,2.0
-SE,1500.0,6,2.0,8.0,8.0,8.0,9.0,6.0,3.0,1.0,53.0,1.0
-SE,1511.0,6,3.0,6.0,5.0,6.0,7.0,2.0,2.0,1.0,53.0,1.0
-SE,1514.0,6,1.0,8.0,8.0,8.0,9.0,7.0,5.0,2.0,52.0,1.0
-SE,1526.0,6,1.0,5.0,4.0,7.0,6.0,6.0,4.0,2.0,52.0,1.0
-SE,1528.0,6,4.0,7.0,5.0,8.0,8.0,5.0,3.0,1.0,52.0,1.0
-SE,1534.0,6,3.0,7.0,5.0,4.0,9.0,6.0,3.0,2.0,52.0,1.0
-SE,1535.0,6,3.0,7.0,6.0,7.0,9.0,3.0,2.0,1.0,53.0,1.0
-SE,1539.0,6,2.0,9.0,7.0,9.0,8.0,5.0,3.0,1.0,53.0,1.0
-SE,1549.0,6,4.0,0.0,5.0,7.0,4.0,7.0,3.0,1.0,53.0,2.0
-SE,1554.0,6,5.0,8.0,,,5.0,5.0,,1.0,53.0,2.0
-SE,1557.0,6,0.0,8.0,8.0,6.0,9.0,6.0,3.0,2.0,51.0,1.0
-SE,1559.0,6,6.0,7.0,5.0,3.0,9.0,7.0,2.0,2.0,51.0,1.0
-SE,1560.0,6,5.0,5.0,7.0,5.0,7.0,2.0,2.0,1.0,51.0,2.0
-SE,1561.0,6,2.0,8.0,9.0,7.0,8.0,6.0,2.0,1.0,52.0,1.0
-SE,1565.0,6,4.0,5.0,9.0,7.0,10.0,5.0,4.0,1.0,52.0,1.0
-SE,1570.0,6,1.0,8.0,7.0,7.0,9.0,7.0,4.0,1.0,52.0,2.0
-SE,1572.0,6,6.0,4.0,8.0,5.0,10.0,7.0,3.0,2.0,52.0,1.0
-SE,1577.0,6,3.0,6.0,9.0,5.0,6.0,3.0,2.0,1.0,51.0,2.0
-SE,1584.0,6,3.0,6.0,9.0,8.0,10.0,4.0,3.0,2.0,52.0,1.0
-SE,1586.0,6,1.0,6.0,7.0,5.0,9.0,4.0,2.0,2.0,51.0,2.0
-SE,1587.0,6,3.0,6.0,6.0,8.0,8.0,6.0,3.0,2.0,52.0,1.0
-SE,1596.0,6,2.0,8.0,8.0,6.0,8.0,7.0,4.0,1.0,52.0,1.0
-SE,1597.0,6,2.0,9.0,9.0,8.0,8.0,7.0,3.0,2.0,51.0,1.0
-SE,1601.0,6,4.0,3.0,5.0,3.0,7.0,6.0,3.0,1.0,52.0,1.0
-SE,1609.0,6,6.0,5.0,7.0,5.0,7.0,7.0,5.0,1.0,51.0,2.0
-SE,1610.0,6,5.0,7.0,5.0,6.0,7.0,6.0,2.0,1.0,51.0,1.0
-SE,1621.0,6,2.0,7.0,9.0,6.0,9.0,6.0,3.0,2.0,51.0,1.0
-SE,1624.0,6,3.0,3.0,6.0,8.0,8.0,7.0,3.0,2.0,51.0,1.0
-SE,1628.0,6,1.0,9.0,7.0,8.0,7.0,6.0,3.0,2.0,50.0,2.0
-SE,1632.0,6,3.0,7.0,6.0,4.0,8.0,6.0,2.0,1.0,51.0,1.0
-SE,1638.0,6,4.0,8.0,7.0,7.0,9.0,7.0,4.0,2.0,50.0,1.0
-SE,1644.0,6,4.0,3.0,,7.0,8.0,2.0,1.0,1.0,51.0,1.0
-SE,1658.0,6,6.0,4.0,3.0,7.0,9.0,6.0,3.0,1.0,50.0,2.0
-SE,1660.0,6,3.0,7.0,7.0,7.0,5.0,5.0,2.0,2.0,50.0,1.0
-SE,1663.0,6,6.0,5.0,7.0,6.0,9.0,6.0,4.0,1.0,51.0,1.0
-SE,1664.0,6,7.0,7.0,7.0,7.0,8.0,7.0,2.0,2.0,50.0,1.0
-SE,1671.0,6,1.0,8.0,7.0,6.0,7.0,4.0,2.0,1.0,51.0,1.0
-SE,1677.0,6,2.0,9.0,9.0,7.0,8.0,7.0,3.0,2.0,50.0,1.0
-SE,1682.0,6,3.0,4.0,6.0,4.0,8.0,6.0,3.0,1.0,50.0,1.0
-SE,1705.0,6,4.0,8.0,6.0,5.0,9.0,6.0,3.0,2.0,50.0,1.0
-SE,1706.0,6,7.0,5.0,4.0,7.0,10.0,7.0,1.0,2.0,49.0,1.0
-SE,1710.0,6,2.0,5.0,6.0,5.0,8.0,6.0,,1.0,50.0,1.0
-SE,1714.0,6,4.0,3.0,5.0,4.0,6.0,6.0,4.0,2.0,50.0,1.0
-SE,1719.0,6,2.0,6.0,6.0,4.0,8.0,7.0,3.0,1.0,49.0,1.0
-SE,1727.0,6,5.0,6.0,6.0,7.0,7.0,7.0,4.0,1.0,49.0,1.0
-SE,1733.0,6,4.0,5.0,3.0,7.0,9.0,5.0,2.0,1.0,49.0,1.0
-SE,1738.0,6,4.0,8.0,8.0,7.0,7.0,5.0,3.0,2.0,50.0,1.0
-SE,1739.0,6,2.0,4.0,5.0,7.0,7.0,6.0,2.0,2.0,50.0,2.0
-SE,1740.0,6,4.0,3.0,7.0,7.0,8.0,7.0,3.0,2.0,49.0,2.0
-SE,1743.0,6,2.0,7.0,7.0,5.0,9.0,6.0,3.0,2.0,48.0,2.0
-SE,1746.0,6,5.0,6.0,8.0,8.0,5.0,6.0,4.0,1.0,48.0,2.0
-SE,1748.0,6,0.0,3.0,6.0,8.0,8.0,7.0,3.0,2.0,49.0,1.0
-SE,1749.0,6,7.0,7.0,7.0,0.0,5.0,7.0,3.0,1.0,49.0,2.0
-SE,1750.0,6,2.0,4.0,5.0,5.0,8.0,7.0,3.0,2.0,49.0,2.0
-SE,1759.0,6,3.0,4.0,7.0,4.0,7.0,6.0,3.0,2.0,49.0,1.0
-SE,1763.0,6,7.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,48.0,2.0
-SE,1764.0,6,2.0,7.0,8.0,7.0,8.0,6.0,3.0,2.0,49.0,1.0
-SE,1770.0,6,6.0,3.0,8.0,9.0,6.0,2.0,5.0,1.0,49.0,1.0
-SE,1772.0,6,3.0,7.0,1.0,7.0,7.0,3.0,4.0,2.0,48.0,2.0
-SE,1780.0,6,3.0,7.0,6.0,5.0,7.0,6.0,3.0,1.0,49.0,1.0
-SE,1787.0,6,1.0,8.0,8.0,7.0,8.0,6.0,4.0,1.0,49.0,1.0
-SE,1789.0,6,2.0,5.0,9.0,7.0,8.0,4.0,2.0,2.0,49.0,1.0
-SE,1799.0,6,3.0,5.0,6.0,5.0,7.0,5.0,3.0,1.0,48.0,1.0
-SE,1801.0,6,5.0,4.0,7.0,8.0,8.0,6.0,3.0,2.0,48.0,1.0
-SE,1808.0,6,3.0,8.0,8.0,5.0,9.0,7.0,2.0,2.0,48.0,1.0
-SE,1809.0,6,1.0,7.0,5.0,5.0,8.0,6.0,4.0,2.0,47.0,2.0
-SE,1812.0,6,3.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,48.0,1.0
-SE,1817.0,6,5.0,7.0,7.0,6.0,7.0,6.0,2.0,2.0,48.0,1.0
-SE,1820.0,6,1.0,5.0,5.0,5.0,9.0,4.0,3.0,1.0,48.0,1.0
-SE,1823.0,6,3.0,7.0,8.0,8.0,10.0,7.0,5.0,1.0,47.0,1.0
-SE,1826.0,6,2.0,9.0,8.0,8.0,10.0,6.0,3.0,2.0,48.0,1.0
-SE,1827.0,6,1.0,8.0,8.0,7.0,7.0,4.0,3.0,1.0,48.0,1.0
-SE,1828.0,6,2.0,8.0,8.0,8.0,8.0,7.0,3.0,1.0,47.0,1.0
-SE,1831.0,6,5.0,8.0,9.0,5.0,8.0,6.0,4.0,2.0,47.0,1.0
-SE,1833.0,6,3.0,7.0,6.0,7.0,10.0,4.0,3.0,1.0,47.0,1.0
-SE,1834.0,6,3.0,5.0,5.0,5.0,5.0,7.0,3.0,1.0,48.0,1.0
-SE,1845.0,6,3.0,3.0,3.0,5.0,7.0,5.0,1.0,2.0,48.0,1.0
-SE,1856.0,6,1.0,8.0,8.0,7.0,8.0,5.0,4.0,1.0,47.0,1.0
-SE,1860.0,6,0.0,6.0,6.0,6.0,5.0,3.0,4.0,2.0,47.0,2.0
-SE,1870.0,6,3.0,6.0,6.0,3.0,5.0,2.0,2.0,1.0,46.0,2.0
-SE,1873.0,6,0.0,8.0,7.0,5.0,2.0,7.0,2.0,2.0,47.0,2.0
-SE,1874.0,6,2.0,2.0,4.0,5.0,8.0,6.0,4.0,1.0,46.0,2.0
-SE,1881.0,6,2.0,7.0,7.0,7.0,9.0,7.0,3.0,2.0,46.0,1.0
-SE,1883.0,6,2.0,9.0,8.0,8.0,8.0,7.0,3.0,2.0,47.0,1.0
-SE,1886.0,6,5.0,7.0,5.0,8.0,7.0,7.0,3.0,1.0,47.0,2.0
-SE,1890.0,6,3.0,7.0,7.0,8.0,8.0,5.0,3.0,2.0,47.0,1.0
-SE,1892.0,6,2.0,7.0,7.0,7.0,8.0,6.0,4.0,1.0,47.0,1.0
-SE,1899.0,6,4.0,3.0,6.0,3.0,5.0,6.0,3.0,1.0,46.0,2.0
-SE,1900.0,6,5.0,6.0,8.0,8.0,7.0,6.0,3.0,2.0,47.0,1.0
-SE,1905.0,6,1.0,5.0,5.0,2.0,9.0,7.0,3.0,2.0,46.0,2.0
-SE,1906.0,6,1.0,8.0,8.0,9.0,9.0,7.0,3.0,2.0,46.0,1.0
-SE,1914.0,6,2.0,8.0,7.0,7.0,9.0,6.0,3.0,2.0,47.0,1.0
-SE,1927.0,6,5.0,5.0,8.0,8.0,8.0,3.0,2.0,1.0,46.0,1.0
-SE,1933.0,6,5.0,7.0,7.0,8.0,6.0,4.0,3.0,2.0,46.0,1.0
-SE,1935.0,6,7.0,8.0,8.0,5.0,7.0,7.0,3.0,1.0,46.0,2.0
-SE,1936.0,6,2.0,7.0,7.0,7.0,8.0,7.0,5.0,2.0,47.0,1.0
-SE,1939.0,6,2.0,8.0,8.0,8.0,8.0,5.0,3.0,2.0,45.0,1.0
-SE,1953.0,6,3.0,6.0,7.0,7.0,8.0,7.0,4.0,2.0,45.0,1.0
-SE,1955.0,6,5.0,6.0,6.0,6.0,7.0,4.0,2.0,2.0,46.0,1.0
-SE,1956.0,6,6.0,7.0,8.0,6.0,6.0,3.0,2.0,1.0,46.0,2.0
-SE,1957.0,6,3.0,0.0,0.0,0.0,8.0,6.0,3.0,1.0,46.0,1.0
-SE,1960.0,6,4.0,5.0,3.0,7.0,8.0,7.0,3.0,1.0,46.0,1.0
-SE,1961.0,6,5.0,7.0,8.0,6.0,8.0,4.0,3.0,1.0,46.0,1.0
-SE,1966.0,6,1.0,9.0,9.0,9.0,8.0,7.0,3.0,2.0,46.0,1.0
-SE,1969.0,6,4.0,8.0,8.0,8.0,9.0,3.0,2.0,2.0,46.0,1.0
-SE,1972.0,6,4.0,8.0,8.0,5.0,8.0,6.0,3.0,1.0,45.0,1.0
-SE,1977.0,6,2.0,7.0,6.0,8.0,9.0,4.0,3.0,2.0,46.0,2.0
-SE,1982.0,6,4.0,8.0,8.0,8.0,9.0,6.0,3.0,1.0,45.0,1.0
-SE,1984.0,6,6.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,46.0,2.0
-SE,1988.0,6,5.0,3.0,8.0,4.0,9.0,7.0,3.0,1.0,46.0,1.0
-SE,1991.0,6,1.0,5.0,6.0,7.0,8.0,3.0,2.0,1.0,45.0,1.0
-SE,2009.0,6,4.0,5.0,7.0,3.0,8.0,3.0,1.0,1.0,44.0,1.0
-SE,2010.0,6,5.0,8.0,8.0,4.0,9.0,4.0,4.0,1.0,44.0,1.0
-SE,2016.0,6,3.0,7.0,8.0,8.0,9.0,5.0,3.0,2.0,45.0,1.0
-SE,2017.0,6,1.0,10.0,0.0,10.0,7.0,4.0,2.0,1.0,45.0,2.0
-SE,2039.0,6,5.0,5.0,5.0,1.0,5.0,4.0,2.0,1.0,45.0,2.0
-SE,2042.0,6,0.0,8.0,8.0,6.0,7.0,6.0,4.0,2.0,44.0,1.0
-SE,2046.0,6,3.0,9.0,9.0,6.0,9.0,4.0,2.0,2.0,44.0,1.0
-SE,2061.0,6,2.0,2.0,4.0,4.0,9.0,6.0,2.0,2.0,44.0,1.0
-SE,2077.0,6,4.0,8.0,8.0,9.0,10.0,7.0,4.0,1.0,43.0,1.0
-SE,2079.0,6,3.0,6.0,7.0,7.0,7.0,4.0,3.0,2.0,44.0,1.0
-SE,2102.0,6,5.0,7.0,7.0,6.0,7.0,6.0,3.0,1.0,44.0,2.0
-SE,2104.0,6,3.0,7.0,7.0,8.0,8.0,6.0,4.0,1.0,43.0,1.0
-SE,2105.0,6,4.0,8.0,7.0,7.0,7.0,7.0,4.0,1.0,43.0,2.0
-SE,2119.0,6,2.0,5.0,7.0,5.0,9.0,5.0,1.0,2.0,43.0,2.0
-SE,2126.0,6,5.0,8.0,9.0,0.0,6.0,7.0,3.0,1.0,42.0,2.0
-SE,2141.0,6,3.0,8.0,8.0,9.0,8.0,7.0,3.0,2.0,42.0,1.0
-SE,2146.0,6,1.0,5.0,5.0,5.0,8.0,4.0,1.0,2.0,42.0,1.0
-SE,2153.0,6,4.0,6.0,6.0,4.0,7.0,4.0,2.0,1.0,42.0,1.0
-SE,2161.0,6,0.0,7.0,7.0,5.0,8.0,4.0,2.0,2.0,43.0,2.0
-SE,2164.0,6,1.0,7.0,7.0,7.0,9.0,4.0,3.0,2.0,42.0,1.0
-SE,2166.0,6,4.0,8.0,8.0,8.0,8.0,7.0,2.0,2.0,42.0,1.0
-SE,2169.0,6,5.0,8.0,8.0,6.0,10.0,6.0,5.0,1.0,43.0,1.0
-SE,2175.0,6,3.0,3.0,4.0,5.0,7.0,7.0,3.0,1.0,42.0,1.0
-SE,2187.0,6,1.0,5.0,8.0,7.0,8.0,5.0,2.0,2.0,41.0,2.0
-SE,2188.0,6,2.0,8.0,8.0,8.0,8.0,4.0,4.0,1.0,42.0,1.0
-SE,2191.0,6,2.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,41.0,1.0
-SE,2196.0,6,3.0,4.0,4.0,4.0,7.0,7.0,3.0,2.0,42.0,1.0
-SE,2197.0,6,2.0,4.0,7.0,6.0,9.0,7.0,4.0,1.0,42.0,1.0
-SE,2200.0,6,3.0,6.0,6.0,8.0,9.0,3.0,2.0,2.0,41.0,1.0
-SE,2201.0,6,1.0,8.0,9.0,7.0,7.0,7.0,2.0,1.0,42.0,1.0
-SE,2207.0,6,7.0,5.0,5.0,5.0,10.0,4.0,3.0,1.0,42.0,1.0
-SE,2210.0,6,5.0,4.0,8.0,5.0,7.0,7.0,4.0,1.0,42.0,1.0
-SE,2216.0,6,1.0,5.0,6.0,5.0,7.0,6.0,2.0,1.0,42.0,2.0
-SE,2219.0,6,4.0,7.0,6.0,7.0,6.0,7.0,4.0,1.0,42.0,2.0
-SE,2221.0,6,0.0,6.0,7.0,6.0,3.0,4.0,2.0,1.0,42.0,2.0
-SE,2225.0,6,1.0,5.0,7.0,3.0,9.0,7.0,3.0,2.0,41.0,2.0
-SE,2227.0,6,3.0,4.0,5.0,6.0,7.0,7.0,3.0,2.0,42.0,1.0
-SE,2232.0,6,3.0,6.0,8.0,7.0,8.0,6.0,2.0,1.0,41.0,2.0
-SE,2236.0,6,1.0,8.0,7.0,6.0,8.0,4.0,3.0,1.0,40.0,1.0
-SE,2238.0,6,4.0,10.0,9.0,10.0,8.0,6.0,3.0,1.0,40.0,2.0
-SE,2244.0,6,4.0,5.0,8.0,7.0,10.0,6.0,2.0,2.0,40.0,2.0
-SE,2245.0,6,4.0,6.0,7.0,4.0,7.0,4.0,3.0,2.0,41.0,1.0
-SE,2250.0,6,4.0,7.0,6.0,6.0,7.0,7.0,4.0,1.0,41.0,2.0
-SE,2251.0,6,2.0,0.0,5.0,8.0,9.0,7.0,3.0,1.0,41.0,1.0
-SE,2252.0,6,7.0,3.0,0.0,4.0,10.0,6.0,2.0,1.0,40.0,1.0
-SE,2260.0,6,4.0,7.0,10.0,9.0,9.0,7.0,2.0,1.0,41.0,1.0
-SE,2265.0,6,2.0,8.0,9.0,8.0,9.0,7.0,3.0,1.0,41.0,1.0
-SE,2268.0,6,5.0,8.0,7.0,6.0,8.0,5.0,3.0,1.0,41.0,1.0
-SE,2274.0,6,2.0,7.0,7.0,7.0,10.0,6.0,3.0,1.0,40.0,1.0
-SE,2275.0,6,5.0,7.0,7.0,5.0,7.0,4.0,2.0,1.0,41.0,1.0
-SE,2282.0,6,1.0,8.0,7.0,5.0,6.0,7.0,5.0,2.0,40.0,1.0
-SE,2288.0,6,2.0,3.0,4.0,4.0,7.0,7.0,4.0,2.0,41.0,1.0
-SE,2294.0,6,2.0,5.0,8.0,7.0,7.0,6.0,1.0,2.0,40.0,1.0
-SE,2301.0,6,2.0,7.0,6.0,6.0,9.0,7.0,4.0,2.0,40.0,1.0
-SE,2313.0,6,3.0,7.0,7.0,3.0,8.0,5.0,2.0,1.0,40.0,1.0
-SE,2315.0,6,3.0,8.0,8.0,8.0,9.0,7.0,4.0,2.0,40.0,1.0
-SE,2317.0,6,4.0,6.0,4.0,3.0,8.0,4.0,3.0,1.0,39.0,1.0
-SE,2320.0,6,2.0,6.0,6.0,7.0,4.0,6.0,3.0,2.0,39.0,1.0
-SE,2329.0,6,4.0,4.0,5.0,7.0,4.0,7.0,2.0,2.0,40.0,2.0
-SE,2336.0,6,5.0,7.0,7.0,6.0,6.0,5.0,3.0,2.0,39.0,1.0
-SE,2346.0,6,3.0,4.0,6.0,7.0,7.0,7.0,3.0,2.0,39.0,2.0
-SE,2350.0,6,4.0,7.0,7.0,4.0,8.0,6.0,3.0,1.0,38.0,1.0
-SE,2357.0,6,2.0,5.0,8.0,7.0,7.0,4.0,2.0,2.0,39.0,1.0
-SE,2359.0,6,3.0,6.0,8.0,4.0,6.0,5.0,3.0,1.0,39.0,1.0
-SE,2363.0,6,7.0,10.0,8.0,8.0,10.0,4.0,1.0,2.0,38.0,2.0
-SE,2365.0,6,2.0,4.0,7.0,7.0,8.0,6.0,3.0,1.0,38.0,2.0
-SE,2368.0,6,4.0,8.0,8.0,7.0,7.0,4.0,3.0,1.0,38.0,1.0
-SE,2372.0,6,6.0,5.0,5.0,5.0,7.0,5.0,1.0,2.0,39.0,1.0
-SE,2374.0,6,4.0,5.0,7.0,7.0,10.0,5.0,3.0,1.0,39.0,2.0
-SE,2380.0,6,5.0,3.0,2.0,3.0,8.0,2.0,3.0,1.0,38.0,1.0
-SE,2383.0,6,5.0,6.0,7.0,7.0,7.0,5.0,2.0,2.0,38.0,1.0
-SE,2393.0,6,1.0,8.0,7.0,8.0,8.0,7.0,4.0,2.0,38.0,1.0
-SE,2415.0,6,2.0,9.0,8.0,6.0,8.0,6.0,3.0,2.0,38.0,1.0
-SE,2422.0,6,5.0,5.0,5.0,5.0,3.0,5.0,3.0,2.0,37.0,2.0
-SE,2423.0,6,3.0,7.0,7.0,5.0,6.0,7.0,3.0,1.0,37.0,2.0
-SE,2432.0,6,2.0,5.0,3.0,8.0,7.0,3.0,4.0,2.0,38.0,1.0
-SE,2433.0,6,2.0,7.0,5.0,7.0,9.0,7.0,3.0,1.0,38.0,1.0
-SE,2435.0,6,0.0,8.0,7.0,6.0,10.0,6.0,3.0,1.0,37.0,1.0
-SE,2437.0,6,2.0,8.0,7.0,8.0,9.0,6.0,3.0,2.0,37.0,1.0
-SE,2438.0,6,1.0,7.0,5.0,5.0,10.0,7.0,3.0,2.0,38.0,1.0
-SE,2440.0,6,3.0,4.0,5.0,5.0,5.0,5.0,3.0,1.0,37.0,1.0
-SE,2441.0,6,3.0,8.0,7.0,9.0,8.0,7.0,2.0,1.0,38.0,1.0
-SE,2452.0,6,5.0,9.0,3.0,7.0,9.0,7.0,4.0,1.0,38.0,1.0
-SE,2459.0,6,2.0,2.0,2.0,0.0,8.0,7.0,,1.0,38.0,2.0
-SE,2461.0,6,1.0,8.0,8.0,7.0,7.0,6.0,5.0,2.0,37.0,1.0
-SE,2466.0,6,3.0,3.0,4.0,3.0,7.0,2.0,1.0,2.0,38.0,1.0
-SE,2467.0,6,0.0,8.0,5.0,4.0,9.0,4.0,2.0,1.0,37.0,1.0
-SE,2469.0,6,1.0,7.0,7.0,9.0,9.0,7.0,4.0,2.0,37.0,1.0
-SE,2471.0,6,4.0,3.0,4.0,4.0,7.0,4.0,3.0,1.0,38.0,1.0
-SE,2472.0,6,5.0,8.0,8.0,7.0,8.0,5.0,4.0,2.0,38.0,1.0
-SE,2473.0,6,2.0,7.0,8.0,6.0,9.0,6.0,3.0,2.0,38.0,1.0
-SE,2476.0,6,2.0,7.0,8.0,7.0,7.0,6.0,3.0,1.0,37.0,1.0
-SE,2484.0,6,2.0,8.0,8.0,9.0,7.0,3.0,3.0,1.0,36.0,1.0
-SE,2485.0,6,4.0,7.0,7.0,5.0,8.0,5.0,3.0,2.0,36.0,1.0
-SE,2486.0,6,3.0,7.0,7.0,4.0,8.0,6.0,3.0,2.0,36.0,1.0
-SE,2488.0,6,4.0,5.0,6.0,7.0,10.0,6.0,3.0,2.0,37.0,1.0
-SE,2493.0,6,4.0,3.0,5.0,5.0,7.0,7.0,4.0,2.0,37.0,1.0
-SE,2500.0,6,2.0,7.0,7.0,7.0,8.0,7.0,4.0,1.0,37.0,1.0
-SE,2508.0,6,4.0,5.0,5.0,6.0,9.0,2.0,3.0,2.0,36.0,1.0
-SE,2511.0,6,5.0,7.0,4.0,7.0,7.0,5.0,3.0,1.0,37.0,1.0
-SE,2515.0,6,0.0,9.0,9.0,3.0,9.0,5.0,1.0,1.0,36.0,2.0
-SE,2526.0,6,3.0,7.0,6.0,6.0,6.0,4.0,2.0,1.0,37.0,1.0
-SE,2528.0,6,4.0,8.0,8.0,3.0,9.0,7.0,3.0,2.0,36.0,1.0
-SE,2549.0,6,3.0,3.0,7.0,8.0,8.0,7.0,3.0,2.0,36.0,1.0
-SE,2561.0,6,6.0,6.0,6.0,7.0,9.0,5.0,2.0,1.0,35.0,1.0
-SE,2564.0,6,5.0,7.0,8.0,7.0,10.0,4.0,3.0,1.0,35.0,1.0
-SE,2567.0,6,5.0,5.0,8.0,5.0,10.0,6.0,3.0,2.0,36.0,1.0
-SE,2587.0,6,2.0,5.0,1.0,2.0,6.0,3.0,1.0,2.0,36.0,1.0
-SE,2590.0,6,3.0,7.0,5.0,7.0,9.0,6.0,2.0,1.0,35.0,1.0
-SE,2591.0,6,6.0,6.0,4.0,3.0,8.0,5.0,3.0,2.0,34.0,1.0
-SE,2593.0,6,7.0,5.0,8.0,7.0,9.0,6.0,2.0,1.0,35.0,1.0
-SE,2597.0,6,3.0,3.0,6.0,6.0,8.0,7.0,4.0,2.0,35.0,2.0
-SE,2602.0,6,4.0,5.0,6.0,6.0,8.0,6.0,2.0,2.0,34.0,1.0
-SE,2605.0,6,1.0,7.0,8.0,7.0,8.0,4.0,2.0,1.0,35.0,1.0
-SE,2622.0,6,1.0,3.0,5.0,4.0,6.0,6.0,3.0,1.0,35.0,2.0
-SE,2624.0,6,3.0,8.0,8.0,8.0,9.0,5.0,2.0,1.0,35.0,1.0
-SE,2625.0,6,4.0,4.0,4.0,5.0,7.0,4.0,3.0,2.0,35.0,1.0
-SE,2628.0,6,5.0,6.0,5.0,7.0,8.0,6.0,4.0,2.0,34.0,1.0
-SE,2632.0,6,3.0,6.0,7.0,5.0,7.0,6.0,5.0,2.0,34.0,1.0
-SE,2633.0,6,5.0,5.0,8.0,6.0,9.0,5.0,2.0,1.0,34.0,1.0
-SE,2637.0,6,6.0,7.0,5.0,6.0,8.0,4.0,4.0,2.0,34.0,1.0
-SE,2641.0,6,4.0,4.0,6.0,6.0,7.0,7.0,4.0,1.0,35.0,2.0
-SE,2644.0,6,6.0,7.0,5.0,3.0,9.0,6.0,4.0,1.0,35.0,1.0
-SE,2659.0,6,6.0,8.0,7.0,6.0,8.0,5.0,2.0,1.0,34.0,1.0
-SE,2663.0,6,3.0,6.0,6.0,5.0,7.0,7.0,4.0,1.0,34.0,2.0
-SE,2679.0,6,4.0,5.0,5.0,7.0,8.0,7.0,3.0,2.0,34.0,2.0
-SE,2683.0,6,4.0,5.0,7.0,8.0,6.0,5.0,2.0,2.0,33.0,1.0
-SE,2689.0,6,3.0,8.0,8.0,7.0,7.0,7.0,3.0,1.0,33.0,2.0
-SE,2697.0,6,4.0,7.0,5.0,4.0,8.0,5.0,4.0,1.0,34.0,1.0
-SE,2700.0,6,5.0,5.0,4.0,3.0,8.0,5.0,2.0,1.0,34.0,2.0
-SE,2714.0,6,5.0,5.0,7.0,3.0,5.0,2.0,3.0,2.0,32.0,1.0
-SE,2716.0,6,4.0,7.0,7.0,6.0,7.0,5.0,3.0,1.0,33.0,1.0
-SE,2724.0,6,3.0,7.0,7.0,6.0,8.0,3.0,3.0,1.0,32.0,1.0
-SE,2729.0,6,5.0,4.0,5.0,6.0,7.0,6.0,2.0,1.0,33.0,2.0
-SE,2732.0,6,1.0,7.0,4.0,3.0,9.0,7.0,3.0,2.0,33.0,1.0
-SE,2739.0,6,4.0,3.0,6.0,3.0,8.0,7.0,4.0,1.0,33.0,1.0
-SE,2743.0,6,3.0,7.0,7.0,8.0,6.0,6.0,3.0,2.0,32.0,2.0
-SE,2748.0,6,2.0,6.0,5.0,4.0,8.0,6.0,2.0,2.0,33.0,2.0
-SE,2749.0,6,4.0,6.0,7.0,7.0,8.0,7.0,3.0,2.0,33.0,1.0
-SE,2768.0,6,5.0,7.0,7.0,8.0,9.0,6.0,3.0,2.0,31.0,1.0
-SE,2777.0,6,5.0,7.0,9.0,8.0,9.0,5.0,2.0,1.0,32.0,1.0
-SE,2780.0,6,2.0,7.0,7.0,4.0,8.0,4.0,4.0,1.0,31.0,1.0
-SE,2788.0,6,3.0,10.0,10.0,7.0,9.0,6.0,3.0,2.0,31.0,2.0
-SE,2790.0,6,3.0,8.0,7.0,7.0,9.0,7.0,4.0,1.0,32.0,1.0
-SE,2794.0,6,4.0,8.0,8.0,5.0,7.0,5.0,3.0,1.0,31.0,2.0
-SE,2796.0,6,0.0,4.0,4.0,5.0,5.0,7.0,2.0,1.0,31.0,2.0
-SE,2799.0,6,5.0,4.0,6.0,6.0,7.0,7.0,4.0,2.0,32.0,1.0
-SE,2800.0,6,2.0,7.0,4.0,3.0,6.0,6.0,2.0,1.0,32.0,2.0
-SE,2801.0,6,4.0,6.0,8.0,5.0,8.0,6.0,4.0,1.0,32.0,2.0
-SE,2813.0,6,4.0,7.0,5.0,2.0,5.0,6.0,2.0,2.0,32.0,2.0
-SE,2816.0,6,5.0,7.0,7.0,7.0,9.0,7.0,3.0,1.0,32.0,1.0
-SE,2832.0,6,7.0,7.0,7.0,7.0,10.0,6.0,3.0,1.0,31.0,1.0
-SE,2836.0,6,7.0,5.0,8.0,8.0,10.0,6.0,3.0,2.0,31.0,1.0
-SE,2838.0,6,2.0,8.0,7.0,7.0,10.0,7.0,3.0,1.0,31.0,1.0
-SE,2839.0,6,2.0,6.0,7.0,6.0,7.0,6.0,4.0,1.0,32.0,1.0
-SE,2840.0,6,2.0,2.0,5.0,3.0,7.0,4.0,2.0,1.0,30.0,2.0
-SE,2841.0,6,3.0,7.0,7.0,6.0,10.0,6.0,3.0,2.0,31.0,1.0
-SE,2844.0,6,5.0,7.0,7.0,5.0,10.0,6.0,2.0,2.0,31.0,1.0
-SE,2847.0,6,4.0,6.0,8.0,8.0,10.0,4.0,4.0,2.0,30.0,1.0
-SE,2851.0,6,7.0,5.0,5.0,6.0,10.0,3.0,1.0,2.0,31.0,1.0
-SE,2868.0,6,3.0,5.0,8.0,8.0,7.0,5.0,3.0,1.0,31.0,2.0
-SE,2875.0,6,3.0,7.0,7.0,5.0,7.0,6.0,3.0,1.0,31.0,1.0
-SE,2879.0,6,4.0,7.0,7.0,6.0,8.0,7.0,3.0,1.0,31.0,1.0
-SE,2880.0,6,1.0,6.0,6.0,6.0,7.0,6.0,2.0,2.0,31.0,2.0
-SE,2893.0,6,2.0,7.0,7.0,6.0,8.0,5.0,2.0,1.0,29.0,1.0
-SE,2903.0,6,1.0,3.0,3.0,5.0,7.0,6.0,2.0,2.0,30.0,2.0
-SE,2905.0,6,5.0,6.0,5.0,5.0,5.0,3.0,3.0,2.0,30.0,1.0
-SE,2912.0,6,1.0,7.0,7.0,7.0,10.0,5.0,2.0,1.0,29.0,1.0
-SE,2929.0,6,1.0,8.0,5.0,8.0,10.0,7.0,4.0,1.0,30.0,2.0
-SE,2931.0,6,1.0,7.0,7.0,6.0,6.0,7.0,3.0,2.0,30.0,1.0
-SE,2939.0,6,3.0,7.0,6.0,4.0,10.0,6.0,5.0,2.0,29.0,2.0
-SE,2948.0,6,3.0,4.0,4.0,3.0,10.0,4.0,2.0,1.0,29.0,1.0
-SE,2951.0,6,4.0,6.0,6.0,5.0,8.0,6.0,3.0,1.0,29.0,1.0
-SE,2956.0,6,3.0,7.0,7.0,7.0,9.0,6.0,3.0,2.0,28.0,1.0
-SE,2957.0,6,3.0,10.0,9.0,8.0,9.0,6.0,3.0,2.0,29.0,1.0
-SE,2960.0,6,4.0,7.0,7.0,6.0,8.0,6.0,3.0,2.0,28.0,1.0
-SE,2968.0,6,1.0,10.0,8.0,8.0,9.0,6.0,2.0,1.0,28.0,1.0
-SE,2969.0,6,3.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,28.0,1.0
-SE,2970.0,6,6.0,3.0,4.0,4.0,3.0,7.0,3.0,1.0,29.0,2.0
-SE,2974.0,6,3.0,7.0,6.0,3.0,9.0,6.0,4.0,1.0,28.0,1.0
-SE,2992.0,6,3.0,4.0,8.0,7.0,7.0,6.0,3.0,1.0,29.0,2.0
-SE,2994.0,6,4.0,5.0,5.0,3.0,8.0,6.0,3.0,2.0,29.0,1.0
-SE,3004.0,6,3.0,5.0,4.0,4.0,9.0,7.0,2.0,1.0,27.0,1.0
-SE,3008.0,6,4.0,4.0,4.0,4.0,8.0,7.0,2.0,2.0,28.0,1.0
-SE,3012.0,6,4.0,4.0,7.0,6.0,7.0,7.0,3.0,2.0,28.0,1.0
-SE,3016.0,6,1.0,4.0,6.0,8.0,9.0,6.0,3.0,1.0,28.0,1.0
-SE,3017.0,6,4.0,4.0,5.0,6.0,6.0,6.0,4.0,1.0,28.0,2.0
-SE,3022.0,6,2.0,3.0,4.0,4.0,5.0,6.0,3.0,2.0,28.0,2.0
-SE,3031.0,6,7.0,5.0,5.0,2.0,2.0,3.0,1.0,1.0,27.0,2.0
-SE,3033.0,6,2.0,7.0,8.0,5.0,5.0,7.0,4.0,1.0,27.0,2.0
-SE,3034.0,6,2.0,8.0,8.0,6.0,7.0,5.0,3.0,2.0,27.0,1.0
-SE,3041.0,6,2.0,8.0,7.0,6.0,9.0,6.0,3.0,1.0,27.0,1.0
-SE,3046.0,6,0.0,4.0,7.0,7.0,9.0,7.0,4.0,1.0,27.0,2.0
-SE,3047.0,6,1.0,5.0,5.0,4.0,8.0,6.0,3.0,1.0,28.0,1.0
-SE,3054.0,6,2.0,2.0,1.0,4.0,8.0,7.0,3.0,1.0,28.0,2.0
-SE,3059.0,6,1.0,8.0,8.0,5.0,6.0,5.0,3.0,1.0,27.0,2.0
-SE,3080.0,6,1.0,2.0,5.0,7.0,7.0,7.0,1.0,1.0,26.0,2.0
-SE,3089.0,6,2.0,8.0,8.0,7.0,9.0,7.0,2.0,2.0,27.0,2.0
-SE,3090.0,6,5.0,9.0,9.0,7.0,7.0,7.0,3.0,1.0,26.0,1.0
-SE,3096.0,6,6.0,0.0,5.0,0.0,8.0,7.0,1.0,1.0,26.0,2.0
-SE,3098.0,6,4.0,6.0,3.0,2.0,8.0,7.0,3.0,2.0,26.0,2.0
-SE,3099.0,6,6.0,7.0,4.0,6.0,6.0,5.0,4.0,2.0,26.0,1.0
-SE,3114.0,6,5.0,8.0,7.0,5.0,9.0,6.0,2.0,2.0,25.0,1.0
-SE,3116.0,6,4.0,2.0,6.0,7.0,7.0,7.0,3.0,2.0,26.0,2.0
-SE,3120.0,6,3.0,4.0,6.0,6.0,7.0,7.0,4.0,1.0,26.0,1.0
-SE,3124.0,6,5.0,7.0,8.0,8.0,8.0,4.0,2.0,1.0,25.0,1.0
-SE,3133.0,6,2.0,7.0,9.0,7.0,8.0,6.0,3.0,2.0,25.0,2.0
-SE,3140.0,6,3.0,6.0,6.0,7.0,6.0,7.0,2.0,2.0,26.0,1.0
-SE,3143.0,6,5.0,7.0,8.0,5.0,9.0,6.0,2.0,2.0,25.0,1.0
-SE,3144.0,6,1.0,5.0,8.0,5.0,8.0,7.0,5.0,1.0,26.0,2.0
-SE,3145.0,6,7.0,8.0,6.0,6.0,9.0,7.0,3.0,2.0,25.0,1.0
-SE,3148.0,6,5.0,5.0,5.0,3.0,8.0,5.0,4.0,2.0,26.0,2.0
-SE,3151.0,6,4.0,8.0,8.0,7.0,7.0,7.0,4.0,1.0,26.0,2.0
-SE,3153.0,6,4.0,6.0,6.0,3.0,8.0,6.0,3.0,2.0,26.0,2.0
-SE,3155.0,6,6.0,5.0,7.0,3.0,6.0,4.0,4.0,2.0,25.0,2.0
-SE,3156.0,6,1.0,7.0,6.0,7.0,8.0,6.0,3.0,2.0,26.0,2.0
-SE,3157.0,6,2.0,4.0,7.0,7.0,8.0,7.0,3.0,2.0,26.0,1.0
-SE,3163.0,6,5.0,8.0,1.0,5.0,10.0,6.0,3.0,2.0,25.0,1.0
-SE,3170.0,6,2.0,4.0,7.0,7.0,10.0,4.0,2.0,1.0,25.0,1.0
-SE,3172.0,6,5.0,3.0,5.0,2.0,8.0,1.0,2.0,2.0,25.0,1.0
-SE,3176.0,6,4.0,0.0,5.0,2.0,7.0,7.0,3.0,1.0,25.0,2.0
-SE,3183.0,6,0.0,6.0,6.0,2.0,8.0,6.0,2.0,1.0,25.0,2.0
-SE,3185.0,6,3.0,5.0,5.0,6.0,7.0,4.0,2.0,2.0,24.0,1.0
-SE,3186.0,6,4.0,6.0,6.0,3.0,7.0,7.0,3.0,2.0,24.0,2.0
-SE,3189.0,6,2.0,2.0,1.0,5.0,8.0,6.0,4.0,1.0,25.0,2.0
-SE,3197.0,6,2.0,5.0,5.0,8.0,8.0,6.0,4.0,1.0,25.0,2.0
-SE,3205.0,6,4.0,6.0,7.0,9.0,10.0,2.0,2.0,1.0,25.0,1.0
-SE,3206.0,6,4.0,7.0,7.0,4.0,8.0,7.0,3.0,2.0,25.0,2.0
-SE,3214.0,6,5.0,6.0,6.0,7.0,7.0,5.0,3.0,2.0,25.0,1.0
-SE,3216.0,6,5.0,6.0,6.0,7.0,5.0,7.0,3.0,1.0,25.0,2.0
-SE,3220.0,6,2.0,7.0,6.0,3.0,10.0,7.0,3.0,1.0,24.0,1.0
-SE,3226.0,6,3.0,7.0,7.0,6.0,8.0,7.0,3.0,2.0,25.0,1.0
-SE,3235.0,6,2.0,6.0,6.0,7.0,9.0,5.0,2.0,2.0,25.0,1.0
-SE,3237.0,6,4.0,8.0,6.0,6.0,9.0,6.0,3.0,1.0,25.0,2.0
-SE,3238.0,6,4.0,7.0,7.0,8.0,7.0,6.0,3.0,2.0,24.0,2.0
-SE,3245.0,6,4.0,8.0,1.0,5.0,9.0,7.0,5.0,1.0,24.0,1.0
-SE,3246.0,6,3.0,7.0,7.0,8.0,8.0,6.0,3.0,1.0,24.0,1.0
-SE,3251.0,6,3.0,7.0,8.0,6.0,8.0,7.0,4.0,2.0,23.0,2.0
-SE,3252.0,6,2.0,7.0,7.0,5.0,8.0,6.0,3.0,2.0,24.0,2.0
-SE,3255.0,6,4.0,7.0,7.0,8.0,9.0,6.0,4.0,1.0,23.0,1.0
-SE,3256.0,6,1.0,8.0,7.0,6.0,8.0,7.0,3.0,2.0,24.0,2.0
-SE,3265.0,6,3.0,8.0,8.0,7.0,8.0,7.0,2.0,2.0,23.0,2.0
-SE,3272.0,6,4.0,4.0,6.0,6.0,6.0,7.0,3.0,2.0,23.0,1.0
-SE,3275.0,6,4.0,5.0,5.0,5.0,9.0,6.0,2.0,2.0,24.0,2.0
-SE,3277.0,6,5.0,6.0,4.0,5.0,10.0,6.0,3.0,2.0,24.0,1.0
-SE,3280.0,6,5.0,8.0,4.0,2.0,8.0,7.0,4.0,1.0,24.0,2.0
-SE,3287.0,6,7.0,4.0,5.0,8.0,8.0,6.0,3.0,1.0,23.0,1.0
-SE,3295.0,6,1.0,7.0,9.0,7.0,6.0,4.0,1.0,1.0,22.0,2.0
-SE,3296.0,6,2.0,7.0,6.0,7.0,7.0,6.0,3.0,2.0,23.0,2.0
-SE,3297.0,6,5.0,8.0,7.0,5.0,9.0,6.0,3.0,1.0,22.0,1.0
-SE,3306.0,6,4.0,7.0,6.0,3.0,8.0,5.0,4.0,1.0,50.0,1.0
-SE,3307.0,6,5.0,6.0,7.0,4.0,9.0,6.0,4.0,1.0,23.0,2.0
-SE,3309.0,6,0.0,8.0,7.0,7.0,7.0,6.0,3.0,1.0,22.0,2.0
-SE,3311.0,6,3.0,8.0,5.0,9.0,9.0,7.0,3.0,1.0,23.0,2.0
-SE,3313.0,6,0.0,7.0,7.0,6.0,10.0,,3.0,1.0,22.0,1.0
-SE,3320.0,6,6.0,5.0,5.0,7.0,8.0,6.0,2.0,2.0,23.0,2.0
-SE,3322.0,6,1.0,7.0,7.0,6.0,7.0,4.0,1.0,1.0,22.0,2.0
-SE,3323.0,6,2.0,6.0,7.0,7.0,8.0,7.0,4.0,1.0,22.0,2.0
-SE,3329.0,6,3.0,7.0,6.0,6.0,7.0,7.0,3.0,2.0,23.0,2.0
-SE,3332.0,6,1.0,8.0,6.0,7.0,9.0,6.0,3.0,1.0,22.0,2.0
-SE,3333.0,6,4.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,22.0,1.0
-SE,3336.0,6,3.0,7.0,5.0,5.0,6.0,7.0,2.0,1.0,23.0,1.0
-SE,3354.0,6,2.0,7.0,7.0,5.0,5.0,6.0,2.0,2.0,23.0,1.0
-SE,3355.0,6,4.0,7.0,7.0,7.0,9.0,7.0,3.0,2.0,23.0,2.0
-SE,3359.0,6,4.0,2.0,5.0,4.0,4.0,6.0,4.0,2.0,22.0,2.0
-SE,3364.0,6,4.0,6.0,6.0,6.0,8.0,6.0,4.0,2.0,22.0,2.0
-SE,3365.0,6,1.0,9.0,9.0,7.0,9.0,7.0,4.0,2.0,22.0,2.0
-SE,3366.0,6,5.0,7.0,7.0,8.0,8.0,6.0,3.0,1.0,22.0,2.0
-SE,3367.0,6,3.0,8.0,7.0,5.0,10.0,7.0,3.0,2.0,22.0,1.0
-SE,3368.0,6,2.0,7.0,8.0,6.0,6.0,6.0,3.0,1.0,22.0,2.0
-SE,3374.0,6,1.0,5.0,6.0,3.0,8.0,6.0,2.0,1.0,22.0,2.0
-SE,3382.0,6,2.0,7.0,6.0,6.0,7.0,6.0,2.0,1.0,22.0,2.0
-SE,3390.0,6,4.0,5.0,6.0,7.0,7.0,7.0,4.0,1.0,22.0,2.0
-SE,3411.0,6,3.0,7.0,8.0,7.0,7.0,6.0,3.0,1.0,21.0,2.0
-SE,3415.0,6,7.0,4.0,3.0,0.0,4.0,6.0,2.0,1.0,21.0,2.0
-SE,3425.0,6,3.0,5.0,5.0,5.0,8.0,7.0,4.0,2.0,22.0,2.0
-SE,3426.0,6,1.0,8.0,7.0,6.0,9.0,7.0,3.0,2.0,21.0,2.0
-SE,3427.0,6,4.0,6.0,4.0,6.0,9.0,7.0,3.0,1.0,21.0,2.0
-SE,3428.0,6,5.0,5.0,5.0,3.0,10.0,6.0,3.0,1.0,22.0,1.0
-SE,3433.0,6,6.0,6.0,5.0,6.0,6.0,7.0,2.0,1.0,20.0,2.0
-SE,3447.0,6,5.0,5.0,5.0,5.0,6.0,6.0,3.0,1.0,21.0,2.0
-SE,3450.0,6,3.0,7.0,8.0,8.0,6.0,7.0,3.0,1.0,21.0,2.0
-SE,3452.0,6,5.0,7.0,7.0,3.0,8.0,7.0,4.0,1.0,20.0,2.0
-SE,3466.0,6,4.0,8.0,8.0,2.0,8.0,7.0,3.0,1.0,20.0,2.0
-SE,3478.0,6,4.0,4.0,5.0,3.0,5.0,4.0,4.0,2.0,20.0,2.0
-SE,3479.0,6,7.0,6.0,8.0,5.0,8.0,7.0,4.0,1.0,20.0,2.0
-SE,3481.0,6,3.0,6.0,6.0,7.0,8.0,7.0,3.0,2.0,21.0,2.0
-SE,3484.0,6,2.0,6.0,7.0,6.0,5.0,6.0,3.0,2.0,20.0,2.0
-SE,3488.0,6,2.0,2.0,2.0,5.0,7.0,7.0,2.0,1.0,20.0,2.0
-SE,3496.0,6,3.0,7.0,7.0,5.0,9.0,6.0,2.0,2.0,19.0,1.0
-SE,3497.0,6,5.0,7.0,7.0,7.0,6.0,7.0,3.0,2.0,20.0,2.0
-SE,3513.0,6,5.0,8.0,7.0,6.0,8.0,7.0,4.0,1.0,19.0,2.0
-SE,3514.0,6,5.0,3.0,4.0,4.0,3.0,6.0,3.0,2.0,20.0,2.0
-SE,3522.0,6,5.0,8.0,8.0,5.0,7.0,7.0,4.0,1.0,20.0,2.0
-SE,3524.0,6,2.0,6.0,5.0,4.0,9.0,6.0,3.0,1.0,19.0,2.0
-SE,3525.0,6,3.0,5.0,7.0,6.0,10.0,6.0,4.0,1.0,20.0,2.0
-SE,3526.0,6,4.0,7.0,7.0,6.0,8.0,7.0,3.0,2.0,19.0,2.0
-SE,3529.0,6,7.0,1.0,5.0,3.0,10.0,4.0,3.0,1.0,20.0,2.0
-SE,3532.0,6,0.0,0.0,0.0,0.0,3.0,7.0,3.0,1.0,18.0,2.0
-SE,3535.0,6,2.0,6.0,8.0,7.0,8.0,6.0,4.0,1.0,19.0,2.0
-SE,3550.0,6,1.0,7.0,7.0,6.0,8.0,7.0,3.0,2.0,19.0,2.0
-SE,3551.0,6,7.0,7.0,7.0,5.0,8.0,6.0,4.0,1.0,19.0,2.0
-SE,3553.0,6,5.0,7.0,8.0,7.0,7.0,7.0,4.0,1.0,20.0,2.0
-SE,3561.0,6,7.0,,10.0,0.0,5.0,7.0,3.0,2.0,19.0,2.0
-SE,3564.0,6,2.0,8.0,8.0,6.0,8.0,7.0,3.0,2.0,19.0,2.0
-SE,3569.0,6,5.0,4.0,6.0,5.0,8.0,7.0,4.0,1.0,18.0,2.0
-SE,3571.0,6,2.0,6.0,7.0,3.0,9.0,7.0,4.0,1.0,18.0,2.0
-SE,3579.0,6,0.0,3.0,8.0,3.0,8.0,6.0,4.0,1.0,18.0,2.0
-SE,3581.0,6,4.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,19.0,2.0
-SE,3584.0,6,5.0,8.0,7.0,8.0,8.0,7.0,3.0,2.0,19.0,2.0
-SE,3589.0,6,3.0,8.0,6.0,5.0,8.0,6.0,4.0,1.0,19.0,2.0
-SE,3592.0,6,3.0,7.0,8.0,7.0,10.0,7.0,3.0,2.0,18.0,2.0
-SE,3594.0,6,2.0,5.0,8.0,5.0,9.0,6.0,5.0,1.0,19.0,2.0
-SE,3599.0,6,5.0,7.0,8.0,6.0,10.0,7.0,4.0,1.0,19.0,2.0
-SE,3603.0,6,6.0,6.0,7.0,7.0,8.0,4.0,4.0,1.0,68.0,1.0
-SE,3605.0,6,2.0,5.0,8.0,9.0,9.0,7.0,4.0,1.0,18.0,2.0
-SE,3606.0,6,5.0,7.0,7.0,3.0,8.0,7.0,2.0,1.0,19.0,2.0
-SE,3608.0,6,1.0,7.0,7.0,7.0,7.0,6.0,2.0,2.0,19.0,2.0
-SE,3613.0,6,2.0,5.0,4.0,6.0,9.0,6.0,3.0,2.0,19.0,2.0
-SE,3616.0,6,0.0,5.0,5.0,10.0,7.0,7.0,4.0,1.0,19.0,2.0
-SE,3618.0,6,4.0,3.0,4.0,2.0,7.0,6.0,4.0,2.0,18.0,2.0
-SE,3620.0,6,0.0,7.0,8.0,7.0,7.0,6.0,3.0,1.0,18.0,2.0
-SE,3623.0,6,2.0,8.0,8.0,8.0,10.0,7.0,3.0,2.0,18.0,2.0
-SE,3628.0,6,2.0,4.0,7.0,5.0,8.0,7.0,3.0,2.0,18.0,2.0
-SE,3631.0,6,0.0,7.0,6.0,7.0,8.0,6.0,2.0,2.0,17.0,2.0
-SE,3633.0,6,5.0,3.0,6.0,7.0,8.0,6.0,3.0,2.0,18.0,2.0
-SE,3636.0,6,5.0,7.0,8.0,5.0,9.0,7.0,3.0,1.0,17.0,2.0
-SE,3647.0,6,7.0,10.0,10.0,10.0,10.0,7.0,5.0,2.0,18.0,2.0
-SE,3648.0,6,3.0,6.0,9.0,4.0,9.0,6.0,3.0,1.0,18.0,2.0
-SE,3649.0,6,2.0,5.0,7.0,7.0,8.0,6.0,3.0,2.0,17.0,2.0
-SE,3650.0,6,5.0,7.0,7.0,7.0,7.0,7.0,3.0,1.0,18.0,2.0
-SE,3655.0,6,2.0,7.0,6.0,3.0,8.0,6.0,4.0,1.0,18.0,2.0
-SE,3659.0,6,2.0,8.0,6.0,7.0,7.0,6.0,2.0,1.0,18.0,2.0
-SE,3661.0,6,0.0,7.0,8.0,6.0,9.0,7.0,1.0,2.0,17.0,2.0
-SE,3662.0,6,3.0,5.0,6.0,4.0,10.0,6.0,3.0,2.0,17.0,2.0
-SE,3665.0,6,3.0,3.0,6.0,3.0,4.0,4.0,3.0,2.0,17.0,2.0
-SE,3666.0,6,2.0,5.0,5.0,7.0,9.0,7.0,4.0,2.0,17.0,2.0
-SE,3668.0,6,3.0,7.0,4.0,2.0,10.0,7.0,3.0,1.0,16.0,2.0
-SE,3670.0,6,7.0,5.0,5.0,6.0,9.0,7.0,3.0,1.0,16.0,2.0
-SE,3671.0,6,2.0,3.0,5.0,6.0,6.0,7.0,4.0,2.0,16.0,2.0
-SE,3682.0,6,7.0,6.0,8.0,6.0,7.0,6.0,3.0,1.0,17.0,2.0
-SE,3684.0,6,4.0,4.0,5.0,6.0,8.0,7.0,3.0,2.0,16.0,2.0
-SE,3687.0,6,5.0,4.0,5.0,7.0,9.0,5.0,3.0,2.0,16.0,2.0
-SE,3689.0,6,4.0,6.0,6.0,5.0,7.0,7.0,3.0,1.0,17.0,2.0
-SE,3690.0,6,5.0,9.0,8.0,8.0,10.0,7.0,3.0,2.0,16.0,2.0
-SE,3692.0,6,3.0,7.0,6.0,5.0,8.0,2.0,1.0,1.0,16.0,2.0
-SE,3696.0,6,2.0,8.0,8.0,7.0,9.0,7.0,4.0,1.0,17.0,2.0
-SE,3700.0,6,0.0,8.0,5.0,6.0,8.0,7.0,3.0,1.0,16.0,2.0
-SE,3702.0,6,3.0,5.0,7.0,6.0,8.0,7.0,3.0,1.0,16.0,2.0
-SE,3703.0,6,1.0,6.0,9.0,7.0,8.0,6.0,3.0,1.0,16.0,2.0
-SE,3707.0,6,7.0,7.0,7.0,5.0,7.0,7.0,1.0,2.0,16.0,2.0
-SE,3708.0,6,3.0,6.0,7.0,8.0,9.0,6.0,3.0,2.0,16.0,2.0
-SE,3709.0,6,1.0,6.0,8.0,8.0,10.0,7.0,5.0,2.0,17.0,2.0
-SE,3712.0,6,3.0,5.0,9.0,8.0,9.0,7.0,4.0,1.0,16.0,2.0
-SE,3716.0,6,3.0,3.0,7.0,9.0,8.0,7.0,2.0,1.0,17.0,2.0
-SE,3720.0,6,5.0,5.0,3.0,7.0,7.0,5.0,2.0,2.0,16.0,2.0
-SE,3727.0,6,5.0,3.0,4.0,2.0,7.0,7.0,3.0,2.0,15.0,2.0
-SE,3729.0,6,1.0,5.0,5.0,7.0,7.0,7.0,4.0,2.0,15.0,2.0
-SE,3732.0,6,3.0,3.0,7.0,7.0,5.0,6.0,2.0,2.0,16.0,2.0
-SE,3743.0,6,4.0,6.0,6.0,5.0,7.0,6.0,4.0,1.0,15.0,2.0
-SE,3744.0,6,0.0,6.0,7.0,2.0,9.0,7.0,3.0,2.0,15.0,2.0
-SE,3746.0,6,7.0,5.0,10.0,6.0,10.0,3.0,2.0,2.0,15.0,2.0
-SE,7.0,7,3.0,0.0,5.0,7.0,9.0,4.0,4.0,2.0,95.0,2.0
-SE,13.0,7,2.0,6.0,,8.0,6.0,7.0,4.0,2.0,94.0,2.0
-SE,22.0,7,5.0,5.0,5.0,8.0,5.0,7.0,2.0,1.0,93.0,2.0
-SE,30.0,7,7.0,7.0,7.0,8.0,10.0,7.0,3.0,1.0,91.0,1.0
-SE,39.0,7,7.0,5.0,9.0,8.0,8.0,6.0,2.0,2.0,91.0,2.0
-SE,58.0,7,7.0,5.0,7.0,4.0,5.0,3.0,2.0,1.0,89.0,2.0
-SE,79.0,7,6.0,4.0,10.0,5.0,8.0,6.0,3.0,1.0,87.0,2.0
-SE,97.0,7,7.0,4.0,8.0,10.0,10.0,4.0,5.0,2.0,86.0,2.0
-SE,102.0,7,5.0,10.0,8.0,8.0,8.0,5.0,3.0,2.0,86.0,1.0
-SE,105.0,7,6.0,6.0,8.0,8.0,10.0,4.0,2.0,1.0,85.0,1.0
-SE,106.0,7,5.0,4.0,8.0,8.0,7.0,3.0,1.0,2.0,85.0,1.0
-SE,107.0,7,7.0,7.0,7.0,4.0,9.0,3.0,4.0,1.0,85.0,1.0
-SE,109.0,7,1.0,5.0,5.0,5.0,3.0,6.0,1.0,2.0,85.0,2.0
-SE,112.0,7,6.0,3.0,3.0,2.0,10.0,4.0,2.0,2.0,85.0,1.0
-SE,116.0,7,7.0,8.0,10.0,9.0,8.0,6.0,3.0,2.0,85.0,2.0
-SE,120.0,7,3.0,6.0,8.0,8.0,8.0,4.0,4.0,2.0,85.0,1.0
-SE,122.0,7,5.0,7.0,8.0,9.0,7.0,7.0,4.0,1.0,85.0,2.0
-SE,130.0,7,5.0,4.0,4.0,5.0,5.0,5.0,3.0,2.0,85.0,2.0
-SE,134.0,7,6.0,6.0,4.0,6.0,8.0,7.0,2.0,2.0,84.0,2.0
-SE,148.0,7,4.0,4.0,7.0,7.0,8.0,5.0,2.0,1.0,84.0,2.0
-SE,154.0,7,5.0,8.0,10.0,5.0,9.0,6.0,1.0,2.0,84.0,2.0
-SE,160.0,7,2.0,4.0,8.0,9.0,8.0,3.0,4.0,1.0,83.0,2.0
-SE,165.0,7,5.0,8.0,10.0,5.0,,6.0,2.0,2.0,83.0,2.0
-SE,170.0,7,2.0,3.0,3.0,3.0,8.0,3.0,3.0,1.0,83.0,2.0
-SE,177.0,7,4.0,5.0,5.0,5.0,8.0,7.0,3.0,2.0,83.0,2.0
-SE,178.0,7,7.0,7.0,7.0,5.0,8.0,4.0,2.0,2.0,83.0,1.0
-SE,180.0,7,3.0,7.0,7.0,7.0,8.0,4.0,2.0,2.0,83.0,2.0
-SE,192.0,7,7.0,6.0,8.0,,8.0,5.0,2.0,2.0,82.0,2.0
-SE,198.0,7,5.0,7.0,2.0,8.0,7.0,2.0,1.0,1.0,82.0,1.0
-SE,199.0,7,4.0,8.0,3.0,8.0,9.0,6.0,3.0,1.0,82.0,1.0
-SE,201.0,7,7.0,5.0,8.0,8.0,7.0,5.0,4.0,1.0,82.0,2.0
-SE,206.0,7,7.0,7.0,8.0,4.0,8.0,4.0,2.0,1.0,82.0,1.0
-SE,216.0,7,5.0,5.0,7.0,6.0,5.0,6.0,3.0,2.0,81.0,2.0
-SE,221.0,7,6.0,9.0,9.0,9.0,8.0,6.0,3.0,1.0,81.0,1.0
-SE,225.0,7,4.0,3.0,5.0,6.0,8.0,6.0,4.0,2.0,81.0,2.0
-SE,226.0,7,1.0,0.0,10.0,0.0,9.0,4.0,3.0,1.0,81.0,1.0
-SE,228.0,7,5.0,6.0,6.0,7.0,6.0,6.0,1.0,2.0,81.0,2.0
-SE,231.0,7,6.0,6.0,7.0,5.0,8.0,4.0,3.0,1.0,81.0,2.0
-SE,237.0,7,7.0,5.0,5.0,6.0,10.0,7.0,2.0,1.0,80.0,1.0
-SE,242.0,7,5.0,6.0,10.0,6.0,8.0,2.0,2.0,2.0,80.0,2.0
-SE,246.0,7,4.0,6.0,8.0,8.0,8.0,5.0,3.0,2.0,80.0,1.0
-SE,247.0,7,5.0,8.0,9.0,9.0,10.0,7.0,3.0,2.0,80.0,1.0
-SE,252.0,7,3.0,8.0,9.0,7.0,,4.0,3.0,2.0,80.0,2.0
-SE,254.0,7,6.0,3.0,5.0,8.0,10.0,6.0,3.0,1.0,80.0,1.0
-SE,259.0,7,7.0,5.0,8.0,5.0,8.0,2.0,2.0,2.0,79.0,1.0
-SE,260.0,7,7.0,5.0,8.0,8.0,8.0,3.0,1.0,2.0,79.0,1.0
-SE,262.0,7,7.0,5.0,5.0,7.0,8.0,4.0,3.0,2.0,79.0,1.0
-SE,265.0,7,1.0,7.0,3.0,8.0,7.0,3.0,2.0,1.0,79.0,2.0
-SE,269.0,7,5.0,5.0,8.0,8.0,9.0,6.0,3.0,2.0,79.0,2.0
-SE,270.0,7,3.0,5.0,6.0,5.0,7.0,6.0,3.0,1.0,83.0,1.0
-SE,273.0,7,5.0,3.0,7.0,8.0,8.0,6.0,4.0,1.0,79.0,1.0
-SE,282.0,7,4.0,8.0,7.0,7.0,9.0,6.0,4.0,2.0,79.0,1.0
-SE,290.0,7,5.0,8.0,8.0,5.0,8.0,6.0,3.0,2.0,78.0,1.0
-SE,292.0,7,5.0,7.0,7.0,7.0,8.0,6.0,3.0,1.0,78.0,1.0
-SE,293.0,7,7.0,9.0,9.0,8.0,6.0,5.0,1.0,1.0,78.0,2.0
-SE,295.0,7,3.0,7.0,7.0,5.0,8.0,6.0,4.0,1.0,78.0,1.0
-SE,298.0,7,7.0,0.0,5.0,8.0,10.0,4.0,2.0,1.0,78.0,1.0
-SE,302.0,7,5.0,7.0,7.0,5.0,8.0,5.0,3.0,1.0,78.0,1.0
-SE,303.0,7,5.0,6.0,8.0,7.0,7.0,5.0,3.0,2.0,78.0,1.0
-SE,305.0,7,6.0,3.0,5.0,6.0,9.0,4.0,2.0,2.0,78.0,1.0
-SE,312.0,7,6.0,9.0,9.0,9.0,7.0,4.0,3.0,2.0,78.0,2.0
-SE,321.0,7,5.0,8.0,10.0,9.0,8.0,6.0,5.0,2.0,,2.0
-SE,323.0,7,0.0,8.0,8.0,8.0,8.0,4.0,4.0,1.0,,1.0
-SE,325.0,7,2.0,7.0,7.0,6.0,8.0,5.0,3.0,2.0,,1.0
-SE,328.0,7,6.0,7.0,7.0,7.0,10.0,7.0,3.0,2.0,,1.0
-SE,331.0,7,4.0,9.0,7.0,5.0,6.0,5.0,3.0,1.0,,1.0
-SE,332.0,7,2.0,5.0,7.0,9.0,10.0,5.0,3.0,2.0,,2.0
-SE,334.0,7,5.0,6.0,8.0,8.0,8.0,4.0,1.0,2.0,,1.0
-SE,335.0,7,5.0,7.0,7.0,6.0,7.0,7.0,4.0,2.0,,2.0
-SE,336.0,7,4.0,10.0,10.0,5.0,10.0,6.0,4.0,1.0,,1.0
-SE,346.0,7,3.0,6.0,7.0,7.0,8.0,7.0,4.0,2.0,76.0,1.0
-SE,347.0,7,7.0,8.0,8.0,10.0,10.0,6.0,4.0,2.0,76.0,2.0
-SE,349.0,7,7.0,7.0,9.0,7.0,10.0,3.0,3.0,2.0,76.0,1.0
-SE,350.0,7,5.0,8.0,7.0,5.0,9.0,6.0,4.0,2.0,76.0,1.0
-SE,351.0,7,4.0,5.0,5.0,6.0,7.0,4.0,3.0,1.0,76.0,1.0
-SE,353.0,7,2.0,9.0,8.0,9.0,10.0,2.0,3.0,1.0,76.0,1.0
-SE,357.0,7,3.0,6.0,7.0,5.0,8.0,5.0,3.0,1.0,76.0,1.0
-SE,360.0,7,7.0,8.0,5.0,8.0,8.0,3.0,3.0,1.0,76.0,1.0
-SE,369.0,7,5.0,7.0,8.0,8.0,10.0,5.0,3.0,2.0,76.0,1.0
-SE,371.0,7,6.0,8.0,8.0,7.0,7.0,6.0,3.0,2.0,76.0,2.0
-SE,377.0,7,7.0,8.0,9.0,6.0,10.0,4.0,2.0,1.0,75.0,1.0
-SE,379.0,7,3.0,6.0,8.0,8.0,8.0,4.0,3.0,1.0,75.0,1.0
-SE,381.0,7,6.0,3.0,6.0,6.0,5.0,5.0,1.0,2.0,75.0,1.0
-SE,383.0,7,4.0,6.0,7.0,6.0,7.0,5.0,4.0,2.0,75.0,2.0
-SE,385.0,7,6.0,8.0,8.0,7.0,10.0,6.0,3.0,1.0,75.0,1.0
-SE,386.0,7,5.0,6.0,6.0,6.0,5.0,5.0,3.0,1.0,75.0,2.0
-SE,389.0,7,4.0,3.0,2.0,5.0,9.0,5.0,3.0,1.0,75.0,1.0
-SE,390.0,7,7.0,5.0,5.0,4.0,6.0,4.0,2.0,2.0,75.0,2.0
-SE,396.0,7,7.0,7.0,8.0,7.0,8.0,6.0,2.0,1.0,75.0,1.0
-SE,399.0,7,6.0,5.0,8.0,7.0,8.0,6.0,3.0,2.0,75.0,1.0
-SE,405.0,7,6.0,6.0,7.0,8.0,5.0,4.0,2.0,1.0,75.0,1.0
-SE,409.0,7,4.0,5.0,6.0,7.0,7.0,5.0,3.0,1.0,74.0,1.0
-SE,410.0,7,5.0,8.0,9.0,9.0,7.0,7.0,5.0,2.0,74.0,1.0
-SE,412.0,7,7.0,5.0,5.0,5.0,8.0,6.0,3.0,2.0,74.0,1.0
-SE,413.0,7,5.0,7.0,8.0,8.0,9.0,5.0,2.0,2.0,74.0,1.0
-SE,414.0,7,3.0,2.0,3.0,5.0,8.0,4.0,4.0,2.0,74.0,1.0
-SE,415.0,7,7.0,3.0,5.0,7.0,5.0,4.0,3.0,2.0,74.0,1.0
-SE,416.0,7,4.0,5.0,5.0,5.0,8.0,6.0,4.0,1.0,74.0,2.0
-SE,418.0,7,2.0,8.0,9.0,9.0,9.0,6.0,4.0,2.0,74.0,2.0
-SE,422.0,7,6.0,9.0,9.0,8.0,8.0,3.0,2.0,2.0,74.0,2.0
-SE,423.0,7,5.0,6.0,7.0,7.0,8.0,3.0,5.0,1.0,74.0,1.0
-SE,433.0,7,4.0,9.0,9.0,5.0,6.0,4.0,3.0,1.0,74.0,1.0
-SE,434.0,7,5.0,9.0,9.0,9.0,10.0,6.0,4.0,1.0,74.0,1.0
-SE,438.0,7,3.0,5.0,3.0,2.0,10.0,3.0,3.0,2.0,,1.0
-SE,439.0,7,5.0,5.0,5.0,5.0,8.0,7.0,3.0,2.0,74.0,2.0
-SE,447.0,7,3.0,7.0,8.0,6.0,4.0,6.0,4.0,1.0,73.0,2.0
-SE,450.0,7,5.0,6.0,7.0,5.0,8.0,4.0,3.0,1.0,73.0,2.0
-SE,452.0,7,6.0,7.0,8.0,7.0,8.0,5.0,3.0,2.0,73.0,1.0
-SE,457.0,7,7.0,2.0,5.0,7.0,9.0,6.0,3.0,2.0,73.0,2.0
-SE,458.0,7,6.0,5.0,5.0,5.0,8.0,2.0,3.0,1.0,73.0,1.0
-SE,459.0,7,7.0,6.0,10.0,10.0,10.0,6.0,3.0,2.0,73.0,1.0
-SE,463.0,7,4.0,8.0,9.0,6.0,10.0,6.0,4.0,1.0,73.0,1.0
-SE,465.0,7,4.0,7.0,7.0,5.0,6.0,6.0,3.0,1.0,73.0,2.0
-SE,469.0,7,4.0,8.0,7.0,7.0,8.0,5.0,4.0,1.0,73.0,1.0
-SE,470.0,7,2.0,9.0,9.0,8.0,10.0,6.0,4.0,1.0,73.0,1.0
-SE,471.0,7,4.0,7.0,7.0,6.0,7.0,7.0,2.0,1.0,73.0,1.0
-SE,474.0,7,7.0,0.0,5.0,5.0,4.0,5.0,3.0,1.0,73.0,1.0
-SE,475.0,7,7.0,5.0,7.0,5.0,9.0,6.0,3.0,1.0,73.0,1.0
-SE,479.0,7,4.0,5.0,7.0,3.0,6.0,4.0,2.0,2.0,73.0,2.0
-SE,480.0,7,5.0,7.0,10.0,8.0,8.0,6.0,3.0,2.0,73.0,2.0
-SE,481.0,7,2.0,5.0,5.0,7.0,8.0,5.0,3.0,1.0,73.0,1.0
-SE,494.0,7,5.0,7.0,7.0,7.0,9.0,4.0,3.0,1.0,72.0,1.0
-SE,495.0,7,2.0,6.0,5.0,7.0,6.0,5.0,2.0,1.0,72.0,1.0
-SE,498.0,7,4.0,4.0,8.0,3.0,9.0,4.0,3.0,2.0,72.0,1.0
-SE,499.0,7,2.0,8.0,7.0,7.0,9.0,6.0,3.0,2.0,72.0,1.0
-SE,502.0,7,6.0,6.0,4.0,7.0,7.0,4.0,3.0,1.0,72.0,2.0
-SE,504.0,7,2.0,3.0,5.0,5.0,9.0,5.0,3.0,2.0,72.0,1.0
-SE,505.0,7,5.0,0.0,3.0,1.0,5.0,5.0,2.0,1.0,72.0,2.0
-SE,507.0,7,7.0,6.0,4.0,2.0,9.0,6.0,2.0,2.0,72.0,1.0
-SE,510.0,7,4.0,5.0,4.0,5.0,8.0,3.0,3.0,1.0,83.0,1.0
-SE,513.0,7,4.0,8.0,7.0,8.0,8.0,5.0,4.0,2.0,72.0,1.0
-SE,518.0,7,5.0,7.0,8.0,8.0,8.0,5.0,3.0,2.0,72.0,1.0
-SE,519.0,7,4.0,7.0,7.0,5.0,7.0,7.0,4.0,1.0,72.0,1.0
-SE,520.0,7,2.0,8.0,8.0,5.0,7.0,4.0,4.0,1.0,72.0,1.0
-SE,522.0,7,6.0,7.0,7.0,3.0,6.0,2.0,3.0,1.0,72.0,2.0
-SE,524.0,7,4.0,9.0,9.0,8.0,9.0,6.0,3.0,2.0,72.0,1.0
-SE,527.0,7,7.0,10.0,10.0,7.0,8.0,6.0,3.0,1.0,72.0,1.0
-SE,530.0,7,7.0,5.0,8.0,8.0,9.0,6.0,3.0,1.0,71.0,1.0
-SE,535.0,7,7.0,10.0,6.0,8.0,10.0,4.0,5.0,2.0,71.0,1.0
-SE,537.0,7,6.0,7.0,8.0,6.0,8.0,4.0,3.0,1.0,71.0,1.0
-SE,538.0,7,3.0,9.0,8.0,8.0,9.0,7.0,5.0,1.0,71.0,2.0
-SE,545.0,7,3.0,8.0,8.0,3.0,8.0,4.0,1.0,1.0,71.0,1.0
-SE,552.0,7,4.0,7.0,7.0,8.0,8.0,4.0,4.0,1.0,71.0,1.0
-SE,554.0,7,2.0,1.0,2.0,5.0,10.0,7.0,3.0,1.0,71.0,1.0
-SE,559.0,7,5.0,3.0,3.0,8.0,8.0,6.0,2.0,2.0,71.0,1.0
-SE,561.0,7,6.0,3.0,5.0,5.0,9.0,4.0,5.0,1.0,71.0,1.0
-SE,569.0,7,5.0,8.0,7.0,8.0,9.0,7.0,3.0,2.0,71.0,1.0
-SE,573.0,7,5.0,6.0,8.0,6.0,5.0,6.0,3.0,2.0,71.0,1.0
-SE,576.0,7,7.0,5.0,8.0,8.0,6.0,6.0,1.0,1.0,71.0,1.0
-SE,577.0,7,4.0,8.0,8.0,5.0,9.0,5.0,3.0,1.0,71.0,1.0
-SE,578.0,7,3.0,8.0,8.0,8.0,9.0,6.0,3.0,1.0,71.0,1.0
-SE,579.0,7,4.0,7.0,7.0,5.0,8.0,4.0,3.0,1.0,71.0,1.0
-SE,580.0,7,5.0,5.0,5.0,3.0,8.0,5.0,2.0,1.0,71.0,1.0
-SE,582.0,7,1.0,8.0,8.0,8.0,8.0,6.0,1.0,2.0,70.0,2.0
-SE,585.0,7,5.0,5.0,8.0,8.0,9.0,6.0,3.0,1.0,70.0,1.0
-SE,588.0,7,4.0,8.0,7.0,8.0,10.0,6.0,4.0,1.0,70.0,1.0
-SE,590.0,7,3.0,8.0,8.0,8.0,8.0,4.0,3.0,1.0,70.0,1.0
-SE,593.0,7,5.0,5.0,8.0,6.0,9.0,5.0,2.0,1.0,70.0,1.0
-SE,596.0,7,7.0,9.0,9.0,9.0,9.0,7.0,3.0,1.0,70.0,1.0
-SE,600.0,7,3.0,6.0,6.0,6.0,4.0,2.0,1.0,1.0,70.0,1.0
-SE,606.0,7,2.0,8.0,7.0,7.0,8.0,6.0,4.0,2.0,70.0,1.0
-SE,608.0,7,4.0,1.0,0.0,2.0,3.0,4.0,1.0,2.0,70.0,2.0
-SE,610.0,7,5.0,7.0,7.0,7.0,10.0,4.0,3.0,1.0,70.0,1.0
-SE,611.0,7,5.0,4.0,3.0,6.0,7.0,5.0,3.0,2.0,70.0,1.0
-SE,614.0,7,4.0,7.0,7.0,5.0,8.0,4.0,2.0,1.0,70.0,1.0
-SE,615.0,7,5.0,8.0,7.0,4.0,7.0,5.0,2.0,1.0,70.0,1.0
-SE,617.0,7,5.0,3.0,7.0,5.0,5.0,6.0,3.0,2.0,70.0,1.0
-SE,618.0,7,4.0,4.0,6.0,3.0,9.0,3.0,4.0,1.0,70.0,1.0
-SE,624.0,7,5.0,10.0,5.0,10.0,6.0,7.0,3.0,1.0,70.0,2.0
-SE,630.0,7,4.0,8.0,7.0,7.0,7.0,6.0,3.0,1.0,69.0,2.0
-SE,635.0,7,2.0,8.0,8.0,7.0,8.0,6.0,4.0,1.0,69.0,1.0
-SE,640.0,7,4.0,9.0,9.0,7.0,9.0,5.0,4.0,1.0,69.0,1.0
-SE,641.0,7,2.0,8.0,8.0,8.0,8.0,6.0,3.0,2.0,69.0,1.0
-SE,644.0,7,4.0,3.0,8.0,8.0,9.0,6.0,4.0,1.0,69.0,1.0
-SE,647.0,7,5.0,7.0,5.0,8.0,9.0,6.0,3.0,2.0,69.0,1.0
-SE,648.0,7,5.0,8.0,8.0,9.0,8.0,6.0,2.0,1.0,69.0,1.0
-SE,649.0,7,6.0,6.0,7.0,7.0,7.0,6.0,3.0,1.0,69.0,1.0
-SE,654.0,7,2.0,9.0,8.0,8.0,9.0,5.0,3.0,2.0,69.0,1.0
-SE,656.0,7,3.0,5.0,4.0,7.0,9.0,5.0,4.0,1.0,69.0,1.0
-SE,657.0,7,2.0,9.0,8.0,4.0,10.0,4.0,3.0,2.0,69.0,1.0
-SE,664.0,7,7.0,5.0,5.0,5.0,8.0,6.0,3.0,1.0,69.0,2.0
-SE,665.0,7,4.0,6.0,6.0,6.0,8.0,6.0,2.0,2.0,69.0,1.0
-SE,670.0,7,5.0,8.0,8.0,7.0,9.0,6.0,3.0,2.0,69.0,1.0
-SE,672.0,7,5.0,4.0,4.0,3.0,8.0,4.0,3.0,1.0,69.0,1.0
-SE,673.0,7,3.0,4.0,8.0,4.0,8.0,6.0,3.0,1.0,69.0,2.0
-SE,676.0,7,6.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,69.0,1.0
-SE,677.0,7,6.0,5.0,8.0,8.0,9.0,6.0,5.0,2.0,69.0,1.0
-SE,680.0,7,3.0,6.0,7.0,5.0,7.0,5.0,3.0,2.0,69.0,1.0
-SE,681.0,7,5.0,7.0,6.0,6.0,8.0,6.0,3.0,1.0,69.0,2.0
-SE,682.0,7,4.0,8.0,9.0,8.0,7.0,4.0,2.0,1.0,69.0,2.0
-SE,684.0,7,7.0,10.0,10.0,3.0,8.0,4.0,2.0,2.0,69.0,2.0
-SE,685.0,7,7.0,8.0,8.0,9.0,8.0,4.0,2.0,1.0,68.0,1.0
-SE,687.0,7,4.0,2.0,7.0,8.0,10.0,5.0,3.0,1.0,68.0,1.0
-SE,690.0,7,6.0,5.0,7.0,4.0,6.0,6.0,4.0,2.0,68.0,2.0
-SE,691.0,7,4.0,6.0,6.0,7.0,8.0,6.0,5.0,1.0,68.0,1.0
-SE,692.0,7,7.0,6.0,6.0,5.0,7.0,4.0,3.0,2.0,68.0,1.0
-SE,694.0,7,3.0,7.0,7.0,7.0,9.0,7.0,4.0,1.0,68.0,1.0
-SE,697.0,7,7.0,7.0,7.0,6.0,9.0,4.0,3.0,2.0,68.0,1.0
-SE,703.0,7,2.0,7.0,7.0,5.0,7.0,4.0,3.0,1.0,68.0,1.0
-SE,708.0,7,2.0,4.0,4.0,5.0,8.0,4.0,2.0,1.0,68.0,2.0
-SE,709.0,7,6.0,7.0,9.0,8.0,8.0,6.0,3.0,2.0,68.0,2.0
-SE,712.0,7,2.0,6.0,6.0,6.0,9.0,5.0,3.0,2.0,68.0,1.0
-SE,718.0,7,2.0,1.0,5.0,5.0,9.0,5.0,1.0,1.0,68.0,1.0
-SE,719.0,7,3.0,5.0,8.0,6.0,6.0,3.0,1.0,1.0,68.0,1.0
-SE,720.0,7,7.0,6.0,7.0,7.0,8.0,4.0,2.0,1.0,68.0,1.0
-SE,723.0,7,7.0,5.0,7.0,7.0,9.0,6.0,3.0,2.0,68.0,1.0
-SE,726.0,7,3.0,3.0,7.0,5.0,8.0,4.0,3.0,2.0,68.0,1.0
-SE,728.0,7,2.0,9.0,9.0,9.0,8.0,6.0,3.0,2.0,68.0,2.0
-SE,740.0,7,3.0,5.0,5.0,7.0,7.0,3.0,1.0,1.0,67.0,1.0
-SE,741.0,7,4.0,8.0,8.0,9.0,8.0,7.0,3.0,2.0,67.0,1.0
-SE,742.0,7,7.0,7.0,8.0,7.0,9.0,5.0,4.0,2.0,67.0,1.0
-SE,744.0,7,3.0,8.0,8.0,6.0,8.0,6.0,5.0,1.0,67.0,1.0
-SE,746.0,7,2.0,4.0,7.0,5.0,8.0,4.0,5.0,1.0,67.0,1.0
-SE,748.0,7,3.0,7.0,7.0,6.0,6.0,7.0,3.0,1.0,67.0,2.0
-SE,750.0,7,2.0,5.0,6.0,8.0,4.0,2.0,2.0,1.0,67.0,1.0
-SE,753.0,7,6.0,4.0,8.0,3.0,9.0,5.0,3.0,2.0,67.0,1.0
-SE,756.0,7,3.0,7.0,8.0,6.0,9.0,4.0,3.0,2.0,67.0,1.0
-SE,761.0,7,7.0,3.0,5.0,5.0,10.0,3.0,3.0,2.0,67.0,1.0
-SE,764.0,7,4.0,9.0,9.0,7.0,7.0,5.0,3.0,2.0,67.0,2.0
-SE,767.0,7,3.0,7.0,7.0,6.0,9.0,7.0,3.0,2.0,67.0,2.0
-SE,769.0,7,6.0,7.0,8.0,7.0,9.0,6.0,4.0,1.0,67.0,1.0
-SE,770.0,7,7.0,5.0,7.0,3.0,7.0,6.0,3.0,1.0,67.0,1.0
-SE,777.0,7,3.0,4.0,10.0,1.0,9.0,5.0,3.0,1.0,67.0,1.0
-SE,778.0,7,3.0,3.0,7.0,4.0,8.0,5.0,3.0,1.0,67.0,2.0
-SE,779.0,7,2.0,6.0,4.0,4.0,9.0,4.0,4.0,1.0,67.0,1.0
-SE,780.0,7,2.0,2.0,3.0,4.0,5.0,7.0,3.0,2.0,67.0,2.0
-SE,787.0,7,5.0,2.0,7.0,3.0,,6.0,3.0,2.0,67.0,2.0
-SE,789.0,7,4.0,8.0,9.0,8.0,9.0,6.0,3.0,1.0,67.0,1.0
-SE,793.0,7,4.0,5.0,8.0,5.0,9.0,5.0,2.0,2.0,67.0,1.0
-SE,796.0,7,0.0,8.0,7.0,8.0,8.0,4.0,3.0,2.0,67.0,1.0
-SE,798.0,7,1.0,8.0,8.0,8.0,9.0,5.0,3.0,2.0,67.0,1.0
-SE,802.0,7,2.0,5.0,4.0,6.0,8.0,4.0,3.0,1.0,,1.0
-SE,803.0,7,4.0,6.0,8.0,8.0,9.0,5.0,3.0,1.0,,1.0
-SE,806.0,7,5.0,10.0,10.0,10.0,7.0,7.0,1.0,1.0,,2.0
-SE,807.0,7,6.0,9.0,9.0,9.0,8.0,5.0,2.0,1.0,,1.0
-SE,808.0,7,4.0,7.0,7.0,4.0,8.0,7.0,3.0,1.0,,1.0
-SE,810.0,7,3.0,7.0,8.0,7.0,8.0,5.0,3.0,2.0,,1.0
-SE,817.0,7,5.0,9.0,9.0,7.0,8.0,6.0,3.0,2.0,,1.0
-SE,818.0,7,3.0,8.0,8.0,6.0,7.0,6.0,2.0,1.0,,1.0
-SE,823.0,7,2.0,5.0,5.0,7.0,7.0,6.0,2.0,1.0,,2.0
-SE,824.0,7,3.0,10.0,10.0,8.0,9.0,2.0,4.0,1.0,,1.0
-SE,827.0,7,4.0,5.0,8.0,5.0,9.0,5.0,3.0,1.0,,1.0
-SE,832.0,7,2.0,5.0,8.0,7.0,8.0,4.0,3.0,1.0,,1.0
-SE,834.0,7,5.0,3.0,3.0,2.0,7.0,5.0,4.0,1.0,,1.0
-SE,837.0,7,5.0,7.0,7.0,5.0,8.0,6.0,3.0,2.0,,1.0
-SE,838.0,7,7.0,5.0,8.0,,8.0,3.0,2.0,2.0,,1.0
-SE,839.0,7,7.0,6.0,3.0,6.0,8.0,3.0,3.0,1.0,,2.0
-SE,840.0,7,6.0,5.0,4.0,5.0,4.0,2.0,2.0,1.0,,1.0
-SE,841.0,7,3.0,8.0,6.0,7.0,8.0,4.0,3.0,2.0,,1.0
-SE,846.0,7,3.0,7.0,6.0,5.0,8.0,4.0,3.0,2.0,,1.0
-SE,847.0,7,4.0,4.0,7.0,8.0,8.0,6.0,4.0,1.0,,2.0
-SE,855.0,7,7.0,8.0,8.0,5.0,8.0,7.0,3.0,1.0,65.0,1.0
-SE,878.0,7,5.0,8.0,8.0,6.0,8.0,4.0,3.0,2.0,65.0,2.0
-SE,880.0,7,3.0,7.0,7.0,3.0,5.0,7.0,3.0,2.0,65.0,2.0
-SE,886.0,7,3.0,7.0,7.0,8.0,8.0,6.0,4.0,1.0,65.0,1.0
-SE,887.0,7,6.0,3.0,8.0,5.0,7.0,5.0,2.0,2.0,65.0,1.0
-SE,888.0,7,3.0,7.0,7.0,5.0,7.0,4.0,3.0,1.0,65.0,1.0
-SE,889.0,7,4.0,7.0,8.0,7.0,9.0,4.0,3.0,2.0,65.0,1.0
-SE,890.0,7,4.0,3.0,3.0,3.0,8.0,4.0,2.0,1.0,65.0,2.0
-SE,891.0,7,3.0,5.0,6.0,5.0,10.0,4.0,3.0,1.0,65.0,1.0
-SE,893.0,7,7.0,8.0,8.0,6.0,10.0,5.0,2.0,2.0,65.0,1.0
-SE,899.0,7,2.0,7.0,7.0,4.0,8.0,5.0,2.0,1.0,65.0,1.0
-SE,904.0,7,3.0,3.0,5.0,5.0,9.0,4.0,2.0,2.0,64.0,1.0
-SE,905.0,7,2.0,5.0,4.0,4.0,7.0,5.0,3.0,2.0,64.0,1.0
-SE,908.0,7,2.0,6.0,8.0,6.0,8.0,7.0,4.0,1.0,64.0,2.0
-SE,915.0,7,7.0,9.0,9.0,8.0,8.0,6.0,4.0,1.0,64.0,2.0
-SE,916.0,7,2.0,6.0,7.0,7.0,8.0,5.0,3.0,2.0,64.0,1.0
-SE,918.0,7,2.0,8.0,7.0,8.0,8.0,7.0,2.0,1.0,64.0,1.0
-SE,922.0,7,3.0,8.0,8.0,9.0,9.0,6.0,3.0,2.0,64.0,1.0
-SE,926.0,7,2.0,5.0,5.0,3.0,10.0,5.0,3.0,1.0,64.0,1.0
-SE,934.0,7,7.0,7.0,5.0,5.0,9.0,6.0,4.0,1.0,64.0,1.0
-SE,936.0,7,2.0,9.0,7.0,8.0,9.0,4.0,3.0,1.0,64.0,2.0
-SE,938.0,7,2.0,10.0,9.0,5.0,9.0,2.0,2.0,1.0,64.0,1.0
-SE,940.0,7,4.0,4.0,7.0,6.0,10.0,7.0,3.0,2.0,64.0,1.0
-SE,945.0,7,4.0,4.0,5.0,7.0,5.0,3.0,3.0,2.0,64.0,1.0
-SE,947.0,7,7.0,5.0,5.0,5.0,7.0,6.0,3.0,2.0,64.0,1.0
-SE,952.0,7,5.0,5.0,8.0,8.0,9.0,6.0,3.0,2.0,64.0,1.0
-SE,954.0,7,6.0,5.0,3.0,3.0,10.0,5.0,3.0,2.0,64.0,1.0
-SE,959.0,7,4.0,7.0,8.0,7.0,9.0,6.0,4.0,2.0,63.0,1.0
-SE,962.0,7,7.0,7.0,2.0,7.0,5.0,6.0,4.0,2.0,63.0,2.0
-SE,963.0,7,7.0,6.0,8.0,5.0,8.0,6.0,4.0,2.0,63.0,2.0
-SE,967.0,7,3.0,8.0,8.0,5.0,8.0,6.0,3.0,2.0,63.0,1.0
-SE,973.0,7,4.0,8.0,7.0,9.0,7.0,4.0,4.0,2.0,63.0,1.0
-SE,975.0,7,4.0,8.0,8.0,7.0,8.0,4.0,2.0,1.0,63.0,1.0
-SE,979.0,7,6.0,3.0,5.0,6.0,9.0,6.0,4.0,1.0,63.0,2.0
-SE,985.0,7,3.0,8.0,6.0,7.0,9.0,4.0,3.0,1.0,63.0,1.0
-SE,987.0,7,0.0,8.0,7.0,8.0,9.0,6.0,4.0,2.0,63.0,2.0
-SE,989.0,7,5.0,8.0,8.0,7.0,8.0,5.0,3.0,1.0,63.0,1.0
-SE,990.0,7,3.0,6.0,7.0,7.0,8.0,6.0,2.0,1.0,63.0,1.0
-SE,991.0,7,4.0,7.0,8.0,7.0,8.0,4.0,2.0,1.0,63.0,1.0
-SE,993.0,7,2.0,5.0,9.0,8.0,9.0,4.0,3.0,2.0,63.0,1.0
-SE,995.0,7,3.0,7.0,6.0,6.0,8.0,4.0,2.0,2.0,63.0,1.0
-SE,996.0,7,3.0,5.0,8.0,3.0,6.0,6.0,2.0,2.0,63.0,1.0
-SE,997.0,7,2.0,6.0,9.0,9.0,10.0,4.0,3.0,1.0,63.0,1.0
-SE,1000.0,7,7.0,6.0,7.0,6.0,8.0,4.0,3.0,2.0,63.0,1.0
-SE,1001.0,7,6.0,7.0,10.0,7.0,8.0,6.0,3.0,1.0,62.0,1.0
-SE,1007.0,7,4.0,0.0,1.0,0.0,5.0,4.0,4.0,2.0,62.0,2.0
-SE,1014.0,7,4.0,5.0,8.0,7.0,10.0,6.0,3.0,2.0,62.0,1.0
-SE,1017.0,7,4.0,2.0,5.0,4.0,9.0,4.0,2.0,2.0,62.0,1.0
-SE,1018.0,7,2.0,4.0,8.0,1.0,9.0,4.0,4.0,1.0,62.0,1.0
-SE,1021.0,7,3.0,7.0,7.0,7.0,10.0,6.0,3.0,2.0,62.0,1.0
-SE,1025.0,7,4.0,3.0,3.0,2.0,9.0,3.0,3.0,2.0,62.0,1.0
-SE,1026.0,7,6.0,3.0,5.0,5.0,8.0,6.0,3.0,2.0,62.0,1.0
-SE,1032.0,7,2.0,8.0,7.0,8.0,8.0,7.0,3.0,1.0,62.0,2.0
-SE,1035.0,7,5.0,6.0,8.0,8.0,8.0,5.0,2.0,1.0,62.0,1.0
-SE,1037.0,7,3.0,9.0,8.0,6.0,8.0,4.0,4.0,1.0,62.0,1.0
-SE,1038.0,7,4.0,8.0,3.0,3.0,8.0,6.0,2.0,2.0,62.0,2.0
-SE,1041.0,7,0.0,8.0,8.0,6.0,9.0,6.0,4.0,2.0,62.0,1.0
-SE,1047.0,7,1.0,9.0,9.0,8.0,9.0,7.0,3.0,2.0,62.0,1.0
-SE,1050.0,7,7.0,8.0,9.0,9.0,8.0,4.0,1.0,1.0,62.0,1.0
-SE,1051.0,7,2.0,5.0,5.0,4.0,7.0,6.0,3.0,2.0,62.0,2.0
-SE,1053.0,7,0.0,0.0,8.0,10.0,5.0,5.0,3.0,2.0,62.0,2.0
-SE,1057.0,7,3.0,5.0,8.0,5.0,10.0,7.0,3.0,1.0,62.0,1.0
-SE,1067.0,7,3.0,9.0,8.0,5.0,8.0,7.0,3.0,1.0,61.0,2.0
-SE,1069.0,7,4.0,8.0,8.0,8.0,9.0,4.0,3.0,2.0,61.0,1.0
-SE,1075.0,7,5.0,6.0,4.0,6.0,9.0,2.0,2.0,1.0,61.0,1.0
-SE,1078.0,7,4.0,5.0,5.0,5.0,6.0,4.0,3.0,1.0,61.0,2.0
-SE,1085.0,7,2.0,4.0,6.0,6.0,3.0,4.0,3.0,2.0,61.0,2.0
-SE,1086.0,7,6.0,2.0,6.0,4.0,10.0,6.0,3.0,2.0,61.0,1.0
-SE,1090.0,7,3.0,8.0,8.0,7.0,8.0,4.0,3.0,2.0,61.0,1.0
-SE,1092.0,7,2.0,7.0,9.0,8.0,9.0,7.0,3.0,1.0,61.0,2.0
-SE,1095.0,7,2.0,5.0,5.0,7.0,7.0,5.0,3.0,1.0,61.0,1.0
-SE,1096.0,7,2.0,5.0,8.0,8.0,7.0,7.0,3.0,1.0,61.0,2.0
-SE,1103.0,7,6.0,6.0,6.0,5.0,5.0,5.0,3.0,1.0,61.0,1.0
-SE,1106.0,7,4.0,8.0,8.0,7.0,7.0,7.0,3.0,1.0,61.0,2.0
-SE,1107.0,7,3.0,5.0,8.0,8.0,9.0,6.0,3.0,2.0,61.0,1.0
-SE,1110.0,7,3.0,7.0,3.0,5.0,10.0,6.0,4.0,1.0,61.0,1.0
-SE,1113.0,7,6.0,10.0,4.0,4.0,5.0,5.0,2.0,2.0,60.0,2.0
-SE,1114.0,7,2.0,2.0,8.0,6.0,9.0,6.0,3.0,1.0,60.0,1.0
-SE,1115.0,7,6.0,8.0,7.0,7.0,9.0,6.0,3.0,1.0,60.0,1.0
-SE,1118.0,7,2.0,7.0,6.0,7.0,7.0,5.0,4.0,1.0,60.0,1.0
-SE,1119.0,7,5.0,8.0,8.0,9.0,10.0,2.0,2.0,1.0,60.0,2.0
-SE,1120.0,7,1.0,5.0,8.0,2.0,10.0,7.0,3.0,1.0,60.0,1.0
-SE,1131.0,7,0.0,7.0,8.0,7.0,9.0,7.0,4.0,2.0,60.0,1.0
-SE,1134.0,7,4.0,6.0,5.0,3.0,7.0,5.0,3.0,2.0,60.0,1.0
-SE,1140.0,7,5.0,8.0,9.0,7.0,10.0,5.0,3.0,1.0,62.0,1.0
-SE,1143.0,7,0.0,10.0,10.0,5.0,6.0,4.0,1.0,2.0,60.0,1.0
-SE,1155.0,7,5.0,6.0,6.0,7.0,7.0,6.0,3.0,2.0,60.0,1.0
-SE,1162.0,7,2.0,7.0,8.0,5.0,8.0,6.0,4.0,2.0,60.0,1.0
-SE,1167.0,7,1.0,8.0,8.0,5.0,10.0,5.0,3.0,2.0,59.0,1.0
-SE,1175.0,7,7.0,5.0,4.0,5.0,9.0,4.0,3.0,2.0,59.0,1.0
-SE,1183.0,7,4.0,9.0,9.0,9.0,8.0,7.0,3.0,1.0,59.0,1.0
-SE,1187.0,7,5.0,7.0,8.0,5.0,5.0,7.0,2.0,1.0,59.0,1.0
-SE,1196.0,7,2.0,7.0,7.0,5.0,7.0,4.0,3.0,2.0,59.0,1.0
-SE,1197.0,7,7.0,5.0,8.0,10.0,9.0,7.0,5.0,2.0,59.0,2.0
-SE,1208.0,7,7.0,8.0,8.0,8.0,7.0,4.0,2.0,2.0,59.0,2.0
-SE,1211.0,7,1.0,5.0,7.0,4.0,7.0,4.0,2.0,1.0,59.0,2.0
-SE,1214.0,7,7.0,4.0,8.0,5.0,8.0,5.0,2.0,1.0,59.0,1.0
-SE,1215.0,7,1.0,8.0,8.0,7.0,9.0,4.0,3.0,1.0,61.0,1.0
-SE,1217.0,7,5.0,9.0,8.0,9.0,10.0,7.0,1.0,2.0,59.0,1.0
-SE,1220.0,7,2.0,7.0,7.0,6.0,9.0,6.0,4.0,1.0,59.0,2.0
-SE,1221.0,7,5.0,7.0,7.0,5.0,8.0,5.0,2.0,1.0,59.0,1.0
-SE,1225.0,7,6.0,7.0,8.0,5.0,8.0,6.0,2.0,1.0,58.0,2.0
-SE,1228.0,7,2.0,5.0,6.0,4.0,8.0,5.0,2.0,1.0,58.0,2.0
-SE,1231.0,7,4.0,8.0,8.0,8.0,9.0,7.0,4.0,2.0,58.0,1.0
-SE,1236.0,7,3.0,4.0,6.0,6.0,10.0,7.0,3.0,1.0,58.0,1.0
-SE,1238.0,7,4.0,1.0,8.0,3.0,9.0,7.0,3.0,1.0,58.0,1.0
-SE,1240.0,7,1.0,4.0,5.0,4.0,6.0,2.0,2.0,1.0,58.0,1.0
-SE,1243.0,7,6.0,8.0,8.0,6.0,4.0,2.0,2.0,2.0,58.0,2.0
-SE,1244.0,7,2.0,8.0,10.0,5.0,10.0,7.0,1.0,2.0,58.0,2.0
-SE,1246.0,7,3.0,5.0,5.0,5.0,6.0,6.0,4.0,1.0,58.0,2.0
-SE,1247.0,7,4.0,6.0,6.0,5.0,8.0,5.0,2.0,2.0,58.0,1.0
-SE,1248.0,7,4.0,0.0,3.0,7.0,8.0,2.0,1.0,1.0,58.0,2.0
-SE,1251.0,7,2.0,7.0,7.0,8.0,7.0,7.0,4.0,2.0,58.0,1.0
-SE,1252.0,7,5.0,4.0,7.0,7.0,7.0,6.0,3.0,2.0,58.0,2.0
-SE,1253.0,7,2.0,7.0,3.0,5.0,9.0,7.0,4.0,2.0,58.0,1.0
-SE,1256.0,7,4.0,4.0,3.0,3.0,6.0,6.0,2.0,2.0,58.0,2.0
-SE,1258.0,7,7.0,7.0,8.0,6.0,8.0,7.0,2.0,2.0,58.0,2.0
-SE,1259.0,7,7.0,3.0,5.0,5.0,4.0,5.0,2.0,1.0,58.0,2.0
-SE,1263.0,7,2.0,8.0,3.0,9.0,7.0,7.0,5.0,2.0,58.0,2.0
-SE,1264.0,7,1.0,7.0,8.0,8.0,10.0,2.0,1.0,1.0,58.0,2.0
-SE,1271.0,7,5.0,6.0,5.0,6.0,7.0,6.0,2.0,2.0,57.0,1.0
-SE,1274.0,7,5.0,8.0,8.0,9.0,9.0,6.0,2.0,2.0,57.0,1.0
-SE,1279.0,7,6.0,8.0,8.0,4.0,10.0,4.0,2.0,2.0,57.0,1.0
-SE,1286.0,7,2.0,9.0,9.0,7.0,8.0,4.0,3.0,2.0,57.0,1.0
-SE,1287.0,7,5.0,7.0,7.0,7.0,7.0,7.0,3.0,1.0,57.0,1.0
-SE,1298.0,7,5.0,6.0,5.0,4.0,7.0,7.0,3.0,1.0,57.0,1.0
-SE,1302.0,7,4.0,3.0,4.0,3.0,7.0,7.0,4.0,2.0,58.0,2.0
-SE,1314.0,7,2.0,4.0,7.0,7.0,8.0,4.0,2.0,2.0,56.0,1.0
-SE,1315.0,7,2.0,7.0,9.0,8.0,7.0,6.0,3.0,2.0,56.0,2.0
-SE,1316.0,7,7.0,2.0,8.0,7.0,7.0,6.0,2.0,1.0,56.0,2.0
-SE,1318.0,7,7.0,7.0,5.0,8.0,6.0,7.0,1.0,1.0,56.0,2.0
-SE,1321.0,7,2.0,7.0,10.0,7.0,8.0,5.0,2.0,2.0,56.0,2.0
-SE,1325.0,7,4.0,10.0,9.0,7.0,8.0,7.0,3.0,2.0,56.0,1.0
-SE,1334.0,7,4.0,10.0,8.0,8.0,9.0,6.0,4.0,1.0,56.0,1.0
-SE,1336.0,7,7.0,2.0,2.0,5.0,6.0,7.0,2.0,2.0,56.0,2.0
-SE,1341.0,7,4.0,7.0,7.0,7.0,9.0,6.0,3.0,2.0,56.0,1.0
-SE,1343.0,7,5.0,3.0,3.0,5.0,5.0,6.0,3.0,2.0,56.0,2.0
-SE,1344.0,7,3.0,0.0,0.0,0.0,5.0,2.0,4.0,1.0,56.0,1.0
-SE,1345.0,7,2.0,0.0,6.0,4.0,7.0,6.0,2.0,1.0,56.0,1.0
-SE,1348.0,7,6.0,7.0,7.0,3.0,8.0,5.0,3.0,1.0,56.0,1.0
-SE,1353.0,7,4.0,8.0,8.0,8.0,9.0,7.0,3.0,2.0,56.0,1.0
-SE,1358.0,7,2.0,6.0,7.0,3.0,9.0,4.0,3.0,1.0,56.0,1.0
-SE,1360.0,7,5.0,5.0,7.0,8.0,10.0,4.0,1.0,2.0,56.0,2.0
-SE,1361.0,7,2.0,8.0,8.0,7.0,7.0,5.0,4.0,1.0,56.0,1.0
-SE,1365.0,7,4.0,2.0,5.0,5.0,7.0,7.0,3.0,2.0,56.0,1.0
-SE,1366.0,7,3.0,7.0,8.0,7.0,7.0,3.0,2.0,1.0,56.0,1.0
-SE,1370.0,7,3.0,6.0,7.0,7.0,7.0,7.0,2.0,2.0,56.0,1.0
-SE,1371.0,7,2.0,3.0,2.0,5.0,6.0,7.0,3.0,2.0,56.0,2.0
-SE,1385.0,7,1.0,8.0,8.0,7.0,8.0,4.0,3.0,1.0,55.0,1.0
-SE,1394.0,7,3.0,9.0,8.0,6.0,6.0,6.0,3.0,1.0,55.0,1.0
-SE,1400.0,7,2.0,8.0,6.0,3.0,8.0,7.0,3.0,2.0,55.0,2.0
-SE,1405.0,7,1.0,7.0,7.0,5.0,7.0,7.0,3.0,1.0,55.0,1.0
-SE,1408.0,7,4.0,7.0,7.0,8.0,7.0,5.0,3.0,2.0,55.0,1.0
-SE,1412.0,7,3.0,8.0,8.0,5.0,8.0,6.0,3.0,1.0,55.0,1.0
-SE,1413.0,7,0.0,5.0,7.0,6.0,8.0,3.0,3.0,1.0,55.0,1.0
-SE,1416.0,7,6.0,3.0,2.0,7.0,10.0,2.0,2.0,1.0,55.0,1.0
-SE,1418.0,7,7.0,4.0,5.0,5.0,5.0,6.0,1.0,2.0,55.0,2.0
-SE,1425.0,7,5.0,5.0,5.0,7.0,7.0,4.0,3.0,1.0,55.0,1.0
-SE,1429.0,7,5.0,7.0,7.0,7.0,9.0,4.0,4.0,2.0,55.0,1.0
-SE,1430.0,7,4.0,8.0,8.0,8.0,8.0,7.0,3.0,1.0,55.0,1.0
-SE,1431.0,7,4.0,5.0,6.0,5.0,9.0,4.0,2.0,1.0,55.0,1.0
-SE,1432.0,7,4.0,8.0,8.0,7.0,9.0,5.0,3.0,1.0,55.0,1.0
-SE,1435.0,7,3.0,5.0,5.0,4.0,7.0,7.0,3.0,2.0,54.0,1.0
-SE,1439.0,7,2.0,4.0,5.0,5.0,8.0,6.0,2.0,1.0,54.0,1.0
-SE,1440.0,7,6.0,4.0,4.0,6.0,8.0,6.0,4.0,2.0,54.0,2.0
-SE,1442.0,7,3.0,5.0,6.0,7.0,8.0,7.0,3.0,2.0,54.0,1.0
-SE,1444.0,7,3.0,8.0,8.0,5.0,8.0,7.0,4.0,1.0,54.0,2.0
-SE,1445.0,7,5.0,6.0,10.0,7.0,9.0,6.0,3.0,2.0,54.0,2.0
-SE,1448.0,7,3.0,5.0,6.0,5.0,8.0,6.0,3.0,2.0,54.0,1.0
-SE,1453.0,7,4.0,8.0,7.0,8.0,9.0,6.0,4.0,2.0,54.0,1.0
-SE,1455.0,7,6.0,5.0,7.0,7.0,9.0,6.0,2.0,2.0,54.0,1.0
-SE,1463.0,7,1.0,5.0,7.0,4.0,8.0,7.0,4.0,1.0,54.0,2.0
-SE,1468.0,7,4.0,5.0,5.0,7.0,8.0,4.0,2.0,2.0,54.0,1.0
-SE,1473.0,7,7.0,7.0,7.0,7.0,7.0,6.0,3.0,1.0,54.0,1.0
-SE,1479.0,7,4.0,8.0,8.0,8.0,9.0,7.0,2.0,2.0,54.0,1.0
-SE,1484.0,7,4.0,8.0,8.0,7.0,8.0,5.0,4.0,1.0,54.0,1.0
-SE,1487.0,7,2.0,8.0,8.0,8.0,9.0,4.0,3.0,1.0,54.0,2.0
-SE,1488.0,7,3.0,7.0,7.0,7.0,6.0,3.0,3.0,2.0,54.0,1.0
-SE,1491.0,7,1.0,7.0,6.0,4.0,6.0,5.0,3.0,1.0,53.0,1.0
-SE,1492.0,7,2.0,8.0,8.0,6.0,7.0,5.0,2.0,2.0,53.0,2.0
-SE,1494.0,7,4.0,7.0,7.0,5.0,7.0,6.0,3.0,2.0,53.0,2.0
-SE,1497.0,7,4.0,6.0,7.0,6.0,10.0,3.0,2.0,2.0,53.0,1.0
-SE,1498.0,7,3.0,8.0,8.0,7.0,9.0,5.0,3.0,2.0,53.0,2.0
-SE,1499.0,7,2.0,9.0,9.0,7.0,8.0,7.0,3.0,2.0,53.0,1.0
-SE,1500.0,7,3.0,8.0,8.0,8.0,8.0,7.0,3.0,2.0,53.0,1.0
-SE,1511.0,7,5.0,5.0,2.0,3.0,8.0,7.0,2.0,1.0,53.0,1.0
-SE,1514.0,7,7.0,9.0,7.0,7.0,10.0,6.0,3.0,1.0,53.0,1.0
-SE,1526.0,7,3.0,8.0,7.0,7.0,8.0,5.0,3.0,1.0,53.0,1.0
-SE,1528.0,7,2.0,7.0,8.0,7.0,8.0,4.0,2.0,2.0,53.0,2.0
-SE,1534.0,7,2.0,7.0,7.0,7.0,8.0,5.0,2.0,1.0,53.0,2.0
-SE,1535.0,7,6.0,7.0,7.0,7.0,9.0,6.0,3.0,1.0,54.0,1.0
-SE,1539.0,7,4.0,6.0,8.0,6.0,9.0,6.0,4.0,2.0,53.0,2.0
-SE,1549.0,7,7.0,5.0,8.0,3.0,5.0,6.0,4.0,2.0,52.0,1.0
-SE,1554.0,7,2.0,3.0,8.0,7.0,8.0,4.0,2.0,1.0,52.0,1.0
-SE,1557.0,7,3.0,8.0,8.0,8.0,9.0,7.0,2.0,1.0,52.0,1.0
-SE,1559.0,7,4.0,7.0,7.0,5.0,8.0,4.0,3.0,2.0,52.0,1.0
-SE,1560.0,7,4.0,5.0,9.0,4.0,8.0,6.0,3.0,1.0,52.0,1.0
-SE,1561.0,7,4.0,8.0,5.0,5.0,8.0,7.0,4.0,1.0,52.0,2.0
-SE,1565.0,7,4.0,9.0,9.0,9.0,6.0,7.0,2.0,2.0,52.0,2.0
-SE,1570.0,7,4.0,5.0,4.0,3.0,6.0,7.0,3.0,2.0,52.0,2.0
-SE,1572.0,7,3.0,8.0,7.0,6.0,8.0,5.0,3.0,1.0,52.0,1.0
-SE,1577.0,7,1.0,5.0,8.0,9.0,9.0,3.0,2.0,1.0,52.0,1.0
-SE,1584.0,7,2.0,6.0,4.0,5.0,8.0,7.0,5.0,2.0,52.0,1.0
-SE,1586.0,7,2.0,7.0,8.0,5.0,10.0,5.0,4.0,2.0,52.0,1.0
-SE,1587.0,7,5.0,9.0,8.0,8.0,8.0,7.0,1.0,1.0,52.0,1.0
-SE,1596.0,7,7.0,5.0,4.0,5.0,6.0,3.0,2.0,1.0,51.0,1.0
-SE,1597.0,7,2.0,5.0,7.0,4.0,9.0,7.0,3.0,1.0,51.0,1.0
-SE,1601.0,7,3.0,8.0,8.0,8.0,6.0,4.0,2.0,1.0,51.0,1.0
-SE,1609.0,7,4.0,8.0,8.0,7.0,7.0,2.0,2.0,2.0,51.0,1.0
-SE,1610.0,7,3.0,5.0,7.0,7.0,4.0,3.0,3.0,2.0,51.0,1.0
-SE,1621.0,7,2.0,9.0,9.0,7.0,10.0,6.0,4.0,2.0,51.0,2.0
-SE,1624.0,7,2.0,8.0,8.0,8.0,9.0,4.0,3.0,2.0,51.0,1.0
-SE,1628.0,7,7.0,7.0,8.0,8.0,8.0,7.0,1.0,2.0,51.0,2.0
-SE,1632.0,7,4.0,7.0,7.0,8.0,7.0,6.0,2.0,1.0,51.0,1.0
-SE,1638.0,7,4.0,7.0,8.0,6.0,8.0,6.0,4.0,1.0,51.0,1.0
-SE,1644.0,7,2.0,8.0,8.0,7.0,6.0,4.0,3.0,2.0,51.0,2.0
-SE,1658.0,7,4.0,8.0,8.0,7.0,9.0,7.0,3.0,1.0,50.0,1.0
-SE,1660.0,7,2.0,7.0,7.0,6.0,7.0,3.0,2.0,1.0,50.0,1.0
-SE,1663.0,7,4.0,8.0,8.0,7.0,5.0,3.0,2.0,2.0,50.0,1.0
-SE,1664.0,7,6.0,8.0,7.0,3.0,9.0,4.0,2.0,1.0,50.0,1.0
-SE,1671.0,7,3.0,7.0,7.0,6.0,9.0,5.0,4.0,1.0,50.0,1.0
-SE,1677.0,7,2.0,4.0,3.0,5.0,7.0,4.0,2.0,2.0,50.0,1.0
-SE,1682.0,7,5.0,7.0,7.0,7.0,8.0,4.0,2.0,1.0,50.0,1.0
-SE,1705.0,7,4.0,5.0,5.0,5.0,8.0,7.0,3.0,1.0,50.0,1.0
-SE,1706.0,7,7.0,6.0,9.0,7.0,9.0,3.0,2.0,2.0,50.0,1.0
-SE,1710.0,7,1.0,8.0,7.0,7.0,9.0,7.0,4.0,2.0,50.0,1.0
-SE,1714.0,7,1.0,9.0,9.0,9.0,6.0,3.0,2.0,1.0,49.0,1.0
-SE,1719.0,7,2.0,4.0,8.0,8.0,8.0,7.0,3.0,2.0,49.0,1.0
-SE,1727.0,7,1.0,7.0,7.0,3.0,9.0,6.0,4.0,1.0,50.0,1.0
-SE,1733.0,7,3.0,8.0,9.0,7.0,9.0,5.0,4.0,1.0,49.0,1.0
-SE,1738.0,7,6.0,8.0,7.0,8.0,10.0,4.0,3.0,2.0,49.0,1.0
-SE,1739.0,7,2.0,3.0,,6.0,7.0,6.0,,1.0,49.0,1.0
-SE,1740.0,7,4.0,9.0,9.0,6.0,9.0,6.0,4.0,1.0,49.0,2.0
-SE,1743.0,7,4.0,5.0,6.0,8.0,10.0,6.0,3.0,2.0,49.0,2.0
-SE,1746.0,7,5.0,5.0,6.0,6.0,8.0,7.0,4.0,2.0,49.0,2.0
-SE,1748.0,7,2.0,8.0,7.0,5.0,4.0,4.0,1.0,2.0,49.0,2.0
-SE,1749.0,7,2.0,5.0,4.0,5.0,8.0,2.0,1.0,2.0,51.0,1.0
-SE,1750.0,7,3.0,5.0,4.0,6.0,9.0,7.0,3.0,2.0,49.0,1.0
-SE,1759.0,7,7.0,4.0,4.0,7.0,8.0,6.0,2.0,2.0,49.0,2.0
-SE,1763.0,7,1.0,3.0,3.0,1.0,8.0,6.0,4.0,1.0,49.0,2.0
-SE,1764.0,7,4.0,8.0,8.0,8.0,7.0,4.0,5.0,2.0,49.0,2.0
-SE,1770.0,7,4.0,8.0,8.0,8.0,8.0,6.0,2.0,2.0,49.0,1.0
-SE,1772.0,7,2.0,7.0,10.0,4.0,10.0,6.0,3.0,2.0,49.0,1.0
-SE,1780.0,7,7.0,8.0,8.0,6.0,8.0,6.0,3.0,1.0,49.0,1.0
-SE,1787.0,7,3.0,5.0,5.0,5.0,4.0,4.0,2.0,1.0,48.0,1.0
-SE,1789.0,7,2.0,8.0,8.0,8.0,8.0,7.0,3.0,2.0,48.0,1.0
-SE,1799.0,7,3.0,8.0,7.0,4.0,6.0,2.0,2.0,1.0,48.0,2.0
-SE,1801.0,7,1.0,8.0,6.0,5.0,10.0,7.0,2.0,1.0,114.0,2.0
-SE,1808.0,7,3.0,7.0,7.0,7.0,7.0,6.0,2.0,1.0,48.0,1.0
-SE,1809.0,7,7.0,8.0,8.0,6.0,8.0,7.0,3.0,2.0,48.0,1.0
-SE,1812.0,7,3.0,8.0,8.0,5.0,7.0,7.0,2.0,1.0,48.0,2.0
-SE,1817.0,7,5.0,7.0,8.0,9.0,9.0,7.0,4.0,1.0,48.0,1.0
-SE,1820.0,7,4.0,3.0,8.0,4.0,10.0,2.0,1.0,2.0,48.0,1.0
-SE,1823.0,7,7.0,8.0,8.0,8.0,7.0,4.0,1.0,1.0,48.0,1.0
-SE,1826.0,7,3.0,4.0,6.0,6.0,7.0,6.0,3.0,2.0,48.0,2.0
-SE,1827.0,7,1.0,9.0,9.0,9.0,10.0,7.0,,2.0,48.0,1.0
-SE,1828.0,7,2.0,5.0,3.0,5.0,10.0,7.0,3.0,2.0,48.0,1.0
-SE,1831.0,7,3.0,7.0,7.0,8.0,8.0,6.0,3.0,1.0,48.0,1.0
-SE,1833.0,7,4.0,7.0,7.0,7.0,7.0,4.0,3.0,1.0,48.0,1.0
-SE,1834.0,7,1.0,5.0,7.0,3.0,8.0,4.0,2.0,1.0,48.0,1.0
-SE,1845.0,7,5.0,2.0,2.0,3.0,7.0,4.0,2.0,1.0,47.0,1.0
-SE,1856.0,7,4.0,3.0,3.0,5.0,4.0,6.0,3.0,1.0,47.0,1.0
-SE,1860.0,7,4.0,8.0,8.0,9.0,7.0,5.0,2.0,1.0,47.0,2.0
-SE,1870.0,7,4.0,9.0,9.0,7.0,9.0,6.0,2.0,2.0,47.0,2.0
-SE,1873.0,7,3.0,9.0,8.0,8.0,8.0,6.0,3.0,1.0,47.0,1.0
-SE,1874.0,7,2.0,7.0,5.0,1.0,6.0,6.0,2.0,1.0,47.0,1.0
-SE,1881.0,7,2.0,8.0,9.0,6.0,8.0,7.0,3.0,2.0,47.0,1.0
-SE,1883.0,7,5.0,8.0,6.0,7.0,7.0,2.0,2.0,1.0,47.0,1.0
-SE,1886.0,7,5.0,7.0,8.0,8.0,9.0,7.0,4.0,1.0,47.0,2.0
-SE,1890.0,7,6.0,5.0,0.0,5.0,9.0,5.0,3.0,2.0,47.0,1.0
-SE,1892.0,7,4.0,9.0,9.0,4.0,7.0,6.0,3.0,2.0,47.0,1.0
-SE,1899.0,7,1.0,8.0,8.0,9.0,9.0,5.0,3.0,1.0,47.0,1.0
-SE,1900.0,7,2.0,9.0,10.0,9.0,10.0,6.0,2.0,2.0,47.0,1.0
-SE,1905.0,7,4.0,8.0,5.0,4.0,8.0,4.0,4.0,1.0,47.0,1.0
-SE,1906.0,7,2.0,8.0,8.0,8.0,6.0,4.0,2.0,1.0,47.0,1.0
-SE,1914.0,7,1.0,9.0,9.0,9.0,9.0,6.0,3.0,2.0,47.0,1.0
-SE,1927.0,7,2.0,9.0,9.0,8.0,8.0,6.0,4.0,1.0,46.0,1.0
-SE,1933.0,7,0.0,5.0,5.0,3.0,7.0,5.0,2.0,1.0,46.0,2.0
-SE,1935.0,7,4.0,5.0,8.0,3.0,10.0,4.0,4.0,1.0,46.0,1.0
-SE,1936.0,7,1.0,7.0,7.0,6.0,8.0,7.0,3.0,1.0,46.0,2.0
-SE,1939.0,7,5.0,4.0,7.0,7.0,4.0,6.0,3.0,1.0,46.0,1.0
-SE,1953.0,7,4.0,7.0,7.0,4.0,9.0,7.0,3.0,1.0,46.0,1.0
-SE,1955.0,7,4.0,7.0,6.0,7.0,8.0,3.0,1.0,2.0,46.0,1.0
-SE,1956.0,7,2.0,8.0,8.0,6.0,8.0,6.0,4.0,1.0,46.0,1.0
-SE,1957.0,7,3.0,4.0,7.0,4.0,8.0,3.0,3.0,2.0,46.0,2.0
-SE,1960.0,7,4.0,4.0,6.0,5.0,5.0,7.0,2.0,2.0,46.0,2.0
-SE,1961.0,7,2.0,8.0,8.0,7.0,8.0,7.0,3.0,2.0,46.0,2.0
-SE,1966.0,7,3.0,5.0,5.0,5.0,9.0,7.0,4.0,2.0,46.0,1.0
-SE,1969.0,7,2.0,6.0,3.0,5.0,8.0,4.0,3.0,2.0,46.0,1.0
-SE,1972.0,7,1.0,6.0,7.0,7.0,10.0,7.0,3.0,2.0,46.0,1.0
-SE,1977.0,7,2.0,6.0,7.0,8.0,4.0,3.0,2.0,2.0,46.0,2.0
-SE,1982.0,7,6.0,8.0,7.0,5.0,9.0,6.0,3.0,1.0,45.0,1.0
-SE,1984.0,7,2.0,8.0,9.0,8.0,10.0,5.0,3.0,2.0,45.0,1.0
-SE,1988.0,7,4.0,6.0,7.0,4.0,8.0,6.0,5.0,2.0,45.0,1.0
-SE,1991.0,7,6.0,7.0,7.0,8.0,7.0,6.0,3.0,1.0,45.0,2.0
-SE,2009.0,7,1.0,8.0,8.0,8.0,9.0,6.0,1.0,2.0,45.0,1.0
-SE,2010.0,7,5.0,7.0,7.0,7.0,7.0,7.0,2.0,1.0,45.0,2.0
-SE,2016.0,7,4.0,10.0,8.0,7.0,8.0,6.0,4.0,2.0,45.0,1.0
-SE,2017.0,7,2.0,7.0,5.0,8.0,7.0,4.0,3.0,2.0,45.0,1.0
-SE,2039.0,7,4.0,6.0,8.0,6.0,8.0,7.0,2.0,2.0,44.0,2.0
-SE,2042.0,7,3.0,9.0,8.0,9.0,9.0,7.0,3.0,2.0,44.0,1.0
-SE,2046.0,7,4.0,5.0,7.0,5.0,7.0,7.0,3.0,2.0,44.0,2.0
-SE,2061.0,7,2.0,7.0,8.0,7.0,7.0,6.0,4.0,2.0,44.0,1.0
-SE,2077.0,7,1.0,10.0,10.0,7.0,8.0,5.0,2.0,2.0,44.0,2.0
-SE,2079.0,7,5.0,7.0,7.0,7.0,9.0,6.0,3.0,1.0,44.0,1.0
-SE,2102.0,7,2.0,9.0,9.0,5.0,9.0,5.0,3.0,2.0,43.0,1.0
-SE,2104.0,7,2.0,1.0,1.0,5.0,8.0,7.0,2.0,1.0,43.0,1.0
-SE,2105.0,7,4.0,6.0,4.0,4.0,5.0,5.0,4.0,2.0,43.0,2.0
-SE,2119.0,7,2.0,7.0,7.0,8.0,8.0,6.0,3.0,1.0,43.0,1.0
-SE,2126.0,7,2.0,8.0,9.0,5.0,9.0,7.0,4.0,2.0,43.0,1.0
-SE,2141.0,7,5.0,7.0,8.0,5.0,10.0,2.0,2.0,1.0,43.0,1.0
-SE,2146.0,7,4.0,5.0,5.0,4.0,7.0,4.0,3.0,2.0,43.0,1.0
-SE,2153.0,7,4.0,8.0,8.0,8.0,7.0,7.0,4.0,1.0,42.0,1.0
-SE,2161.0,7,6.0,8.0,4.0,3.0,10.0,2.0,5.0,2.0,42.0,1.0
-SE,2164.0,7,2.0,7.0,7.0,7.0,7.0,7.0,2.0,1.0,42.0,2.0
-SE,2166.0,7,5.0,7.0,8.0,6.0,5.0,6.0,3.0,2.0,42.0,2.0
-SE,2169.0,7,5.0,5.0,7.0,6.0,8.0,3.0,2.0,2.0,42.0,1.0
-SE,2175.0,7,6.0,7.0,4.0,8.0,8.0,7.0,4.0,1.0,42.0,1.0
-SE,2187.0,7,1.0,6.0,8.0,2.0,5.0,7.0,3.0,2.0,42.0,1.0
-SE,2188.0,7,3.0,8.0,7.0,3.0,6.0,7.0,3.0,2.0,42.0,1.0
-SE,2191.0,7,2.0,7.0,7.0,7.0,9.0,7.0,4.0,1.0,42.0,1.0
-SE,2196.0,7,1.0,7.0,7.0,7.0,9.0,7.0,3.0,2.0,42.0,1.0
-SE,2197.0,7,5.0,7.0,9.0,8.0,10.0,6.0,3.0,1.0,42.0,1.0
-SE,2200.0,7,2.0,7.0,7.0,7.0,7.0,4.0,2.0,2.0,42.0,1.0
-SE,2201.0,7,1.0,8.0,7.0,6.0,10.0,7.0,4.0,1.0,42.0,1.0
-SE,2207.0,7,6.0,5.0,5.0,5.0,3.0,2.0,1.0,2.0,42.0,2.0
-SE,2210.0,7,3.0,6.0,7.0,7.0,8.0,5.0,2.0,2.0,47.0,1.0
-SE,2216.0,7,6.0,8.0,7.0,7.0,9.0,4.0,3.0,1.0,42.0,1.0
-SE,2219.0,7,3.0,5.0,5.0,5.0,7.0,6.0,2.0,2.0,42.0,2.0
-SE,2221.0,7,2.0,8.0,7.0,5.0,8.0,6.0,3.0,1.0,42.0,1.0
-SE,2225.0,7,3.0,8.0,7.0,7.0,8.0,4.0,4.0,2.0,41.0,1.0
-SE,2227.0,7,4.0,9.0,10.0,8.0,8.0,6.0,3.0,2.0,41.0,1.0
-SE,2232.0,7,2.0,8.0,8.0,8.0,9.0,5.0,3.0,2.0,41.0,1.0
-SE,2236.0,7,1.0,9.0,8.0,6.0,9.0,4.0,3.0,2.0,41.0,1.0
-SE,2238.0,7,2.0,8.0,9.0,6.0,9.0,5.0,4.0,2.0,41.0,1.0
-SE,2244.0,7,4.0,5.0,8.0,4.0,7.0,4.0,3.0,2.0,41.0,1.0
-SE,2245.0,7,2.0,7.0,7.0,3.0,9.0,7.0,5.0,2.0,41.0,1.0
-SE,2250.0,7,5.0,5.0,6.0,6.0,7.0,6.0,2.0,1.0,41.0,2.0
-SE,2251.0,7,3.0,7.0,8.0,5.0,8.0,2.0,3.0,1.0,41.0,1.0
-SE,2252.0,7,3.0,8.0,8.0,4.0,7.0,4.0,3.0,1.0,41.0,1.0
-SE,2260.0,7,3.0,7.0,6.0,6.0,8.0,6.0,3.0,1.0,41.0,1.0
-SE,2265.0,7,0.0,7.0,8.0,5.0,8.0,3.0,1.0,2.0,41.0,1.0
-SE,2268.0,7,2.0,8.0,7.0,7.0,8.0,6.0,2.0,2.0,41.0,1.0
-SE,2274.0,7,7.0,5.0,7.0,7.0,7.0,4.0,2.0,1.0,41.0,2.0
-SE,2275.0,7,2.0,7.0,7.0,5.0,7.0,4.0,3.0,2.0,41.0,1.0
-SE,2282.0,7,4.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,41.0,1.0
-SE,2288.0,7,3.0,1.0,9.0,4.0,10.0,3.0,3.0,1.0,40.0,1.0
-SE,2294.0,7,2.0,7.0,8.0,6.0,8.0,4.0,2.0,1.0,40.0,1.0
-SE,2301.0,7,4.0,7.0,9.0,8.0,8.0,6.0,4.0,1.0,40.0,2.0
-SE,2313.0,7,4.0,8.0,7.0,6.0,8.0,6.0,3.0,1.0,40.0,2.0
-SE,2315.0,7,5.0,3.0,3.0,2.0,5.0,6.0,3.0,1.0,40.0,2.0
-SE,2317.0,7,2.0,8.0,8.0,7.0,9.0,7.0,3.0,1.0,40.0,1.0
-SE,2320.0,7,3.0,6.0,6.0,6.0,5.0,6.0,3.0,1.0,40.0,2.0
-SE,2329.0,7,3.0,8.0,8.0,7.0,9.0,5.0,3.0,1.0,40.0,1.0
-SE,2336.0,7,1.0,8.0,8.0,8.0,9.0,6.0,4.0,2.0,40.0,1.0
-SE,2346.0,7,5.0,8.0,8.0,7.0,8.0,6.0,3.0,2.0,39.0,1.0
-SE,2350.0,7,2.0,7.0,7.0,6.0,8.0,4.0,3.0,2.0,39.0,1.0
-SE,2357.0,7,4.0,10.0,8.0,7.0,9.0,7.0,3.0,2.0,39.0,2.0
-SE,2359.0,7,2.0,7.0,9.0,8.0,8.0,6.0,3.0,2.0,39.0,1.0
-SE,2363.0,7,2.0,4.0,5.0,8.0,8.0,7.0,3.0,2.0,39.0,1.0
-SE,2365.0,7,0.0,8.0,9.0,8.0,8.0,6.0,3.0,2.0,39.0,1.0
-SE,2368.0,7,7.0,2.0,0.0,2.0,10.0,6.0,2.0,1.0,39.0,1.0
-SE,2372.0,7,2.0,2.0,5.0,2.0,7.0,6.0,1.0,1.0,39.0,1.0
-SE,2374.0,7,2.0,5.0,8.0,5.0,10.0,6.0,3.0,2.0,39.0,1.0
-SE,2380.0,7,6.0,3.0,5.0,7.0,5.0,4.0,2.0,1.0,39.0,1.0
-SE,2383.0,7,1.0,1.0,5.0,6.0,9.0,6.0,3.0,2.0,38.0,1.0
-SE,2393.0,7,2.0,8.0,8.0,8.0,9.0,6.0,3.0,1.0,38.0,1.0
-SE,2415.0,7,3.0,6.0,7.0,6.0,9.0,7.0,4.0,1.0,38.0,1.0
-SE,2422.0,7,1.0,3.0,0.0,0.0,8.0,6.0,3.0,1.0,38.0,2.0
-SE,2423.0,7,3.0,8.0,10.0,7.0,7.0,6.0,2.0,1.0,38.0,1.0
-SE,2432.0,7,3.0,8.0,7.0,8.0,9.0,5.0,1.0,2.0,38.0,2.0
-SE,2433.0,7,3.0,6.0,9.0,8.0,6.0,7.0,2.0,2.0,38.0,1.0
-SE,2435.0,7,4.0,8.0,8.0,8.0,8.0,6.0,2.0,1.0,38.0,2.0
-SE,2437.0,7,2.0,8.0,7.0,3.0,7.0,7.0,3.0,2.0,38.0,1.0
-SE,2438.0,7,2.0,4.0,6.0,5.0,8.0,7.0,3.0,2.0,38.0,1.0
-SE,2440.0,7,4.0,8.0,8.0,4.0,6.0,7.0,4.0,1.0,38.0,1.0
-SE,2441.0,7,3.0,8.0,7.0,5.0,9.0,6.0,3.0,1.0,38.0,1.0
-SE,2452.0,7,0.0,5.0,5.0,6.0,8.0,5.0,3.0,2.0,37.0,2.0
-SE,2459.0,7,4.0,0.0,8.0,6.0,7.0,7.0,2.0,2.0,37.0,2.0
-SE,2461.0,7,1.0,10.0,9.0,9.0,8.0,6.0,4.0,2.0,37.0,1.0
-SE,2466.0,7,2.0,5.0,5.0,4.0,10.0,5.0,2.0,2.0,37.0,1.0
-SE,2467.0,7,2.0,9.0,7.0,9.0,9.0,7.0,2.0,2.0,37.0,1.0
-SE,2469.0,7,4.0,7.0,7.0,7.0,7.0,7.0,4.0,1.0,37.0,1.0
-SE,2471.0,7,4.0,6.0,6.0,7.0,9.0,5.0,2.0,1.0,37.0,1.0
-SE,2472.0,7,3.0,8.0,7.0,7.0,9.0,6.0,3.0,2.0,37.0,1.0
-SE,2473.0,7,5.0,5.0,7.0,6.0,7.0,5.0,2.0,2.0,37.0,2.0
-SE,2476.0,7,2.0,10.0,10.0,9.0,10.0,7.0,3.0,2.0,37.0,1.0
-SE,2484.0,7,1.0,7.0,7.0,6.0,7.0,7.0,4.0,2.0,37.0,1.0
-SE,2485.0,7,1.0,8.0,8.0,8.0,9.0,6.0,2.0,2.0,37.0,1.0
-SE,2486.0,7,2.0,7.0,8.0,5.0,8.0,6.0,3.0,2.0,37.0,1.0
-SE,2488.0,7,4.0,9.0,9.0,7.0,10.0,6.0,3.0,2.0,37.0,1.0
-SE,2493.0,7,0.0,7.0,7.0,6.0,9.0,7.0,3.0,2.0,37.0,1.0
-SE,2500.0,7,0.0,6.0,7.0,3.0,6.0,7.0,2.0,1.0,37.0,2.0
-SE,2508.0,7,1.0,6.0,7.0,4.0,7.0,4.0,3.0,2.0,36.0,2.0
-SE,2511.0,7,4.0,6.0,5.0,6.0,8.0,6.0,3.0,2.0,36.0,1.0
-SE,2515.0,7,1.0,5.0,4.0,6.0,6.0,2.0,2.0,1.0,36.0,1.0
-SE,2526.0,7,0.0,6.0,3.0,4.0,7.0,2.0,2.0,2.0,36.0,1.0
-SE,2528.0,7,3.0,7.0,7.0,7.0,8.0,6.0,3.0,2.0,36.0,1.0
-SE,2549.0,7,2.0,5.0,4.0,6.0,10.0,6.0,3.0,1.0,36.0,1.0
-SE,2561.0,7,0.0,0.0,5.0,3.0,9.0,7.0,5.0,1.0,35.0,1.0
-SE,2564.0,7,1.0,4.0,5.0,5.0,5.0,7.0,3.0,1.0,35.0,1.0
-SE,2567.0,7,2.0,6.0,7.0,6.0,8.0,7.0,4.0,2.0,35.0,1.0
-SE,2587.0,7,6.0,7.0,6.0,7.0,10.0,7.0,,1.0,35.0,1.0
-SE,2590.0,7,2.0,7.0,8.0,5.0,8.0,7.0,3.0,1.0,35.0,1.0
-SE,2591.0,7,2.0,2.0,3.0,1.0,8.0,7.0,2.0,2.0,35.0,2.0
-SE,2593.0,7,5.0,4.0,10.0,5.0,10.0,7.0,2.0,2.0,35.0,2.0
-SE,2597.0,7,4.0,7.0,7.0,7.0,8.0,7.0,2.0,1.0,35.0,1.0
-SE,2602.0,7,2.0,8.0,9.0,8.0,8.0,2.0,4.0,1.0,35.0,1.0
-SE,2605.0,7,2.0,3.0,5.0,3.0,7.0,6.0,3.0,1.0,35.0,1.0
-SE,2622.0,7,1.0,8.0,9.0,7.0,7.0,4.0,4.0,2.0,34.0,1.0
-SE,2624.0,7,3.0,6.0,6.0,6.0,8.0,6.0,2.0,1.0,34.0,1.0
-SE,2625.0,7,1.0,4.0,5.0,4.0,7.0,6.0,2.0,1.0,34.0,2.0
-SE,2628.0,7,2.0,7.0,7.0,8.0,10.0,6.0,4.0,2.0,34.0,1.0
-SE,2632.0,7,0.0,8.0,8.0,6.0,8.0,4.0,3.0,1.0,34.0,2.0
-SE,2633.0,7,2.0,8.0,8.0,7.0,9.0,7.0,1.0,1.0,34.0,1.0
-SE,2637.0,7,4.0,8.0,6.0,8.0,7.0,6.0,4.0,1.0,34.0,1.0
-SE,2641.0,7,2.0,6.0,7.0,7.0,9.0,4.0,5.0,1.0,34.0,1.0
-SE,2644.0,7,5.0,3.0,4.0,3.0,7.0,4.0,3.0,1.0,34.0,1.0
-SE,2659.0,7,2.0,8.0,7.0,6.0,7.0,6.0,3.0,1.0,34.0,1.0
-SE,2663.0,7,3.0,8.0,8.0,7.0,8.0,7.0,3.0,1.0,34.0,1.0
-SE,2679.0,7,4.0,4.0,5.0,3.0,6.0,5.0,2.0,2.0,33.0,2.0
-SE,2683.0,7,5.0,7.0,7.0,2.0,9.0,7.0,3.0,1.0,33.0,1.0
-SE,2689.0,7,3.0,7.0,7.0,7.0,8.0,7.0,4.0,1.0,33.0,1.0
-SE,2697.0,7,7.0,8.0,8.0,8.0,8.0,6.0,4.0,2.0,33.0,2.0
-SE,2700.0,7,2.0,7.0,7.0,6.0,8.0,6.0,4.0,2.0,33.0,2.0
-SE,2714.0,7,5.0,10.0,8.0,4.0,8.0,6.0,3.0,2.0,33.0,1.0
-SE,2716.0,7,3.0,10.0,10.0,9.0,10.0,7.0,3.0,1.0,33.0,1.0
-SE,2724.0,7,1.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,33.0,1.0
-SE,2729.0,7,0.0,5.0,7.0,3.0,9.0,7.0,4.0,2.0,33.0,1.0
-SE,2732.0,7,6.0,3.0,8.0,9.0,7.0,3.0,1.0,1.0,33.0,1.0
-SE,2739.0,7,6.0,8.0,8.0,6.0,5.0,5.0,2.0,1.0,32.0,2.0
-SE,2743.0,7,2.0,8.0,6.0,9.0,8.0,6.0,2.0,1.0,32.0,1.0
-SE,2748.0,7,3.0,7.0,7.0,5.0,9.0,4.0,3.0,2.0,32.0,1.0
-SE,2749.0,7,7.0,5.0,5.0,5.0,10.0,6.0,3.0,2.0,32.0,1.0
-SE,2768.0,7,4.0,6.0,7.0,6.0,9.0,7.0,4.0,1.0,32.0,1.0
-SE,2777.0,7,3.0,7.0,6.0,4.0,8.0,7.0,3.0,2.0,32.0,1.0
-SE,2780.0,7,2.0,10.0,10.0,8.0,9.0,4.0,1.0,1.0,32.0,1.0
-SE,2788.0,7,3.0,7.0,6.0,6.0,8.0,6.0,2.0,1.0,32.0,2.0
-SE,2790.0,7,2.0,8.0,9.0,8.0,9.0,6.0,3.0,1.0,32.0,1.0
-SE,2794.0,7,3.0,7.0,5.0,6.0,9.0,7.0,3.0,2.0,32.0,2.0
-SE,2796.0,7,1.0,5.0,5.0,7.0,5.0,7.0,2.0,2.0,32.0,1.0
-SE,2799.0,7,0.0,9.0,8.0,6.0,8.0,6.0,3.0,1.0,31.0,2.0
-SE,2800.0,7,3.0,7.0,9.0,5.0,8.0,4.0,3.0,1.0,31.0,1.0
-SE,2801.0,7,1.0,7.0,8.0,8.0,9.0,6.0,3.0,2.0,31.0,1.0
-SE,2813.0,7,7.0,7.0,8.0,4.0,9.0,6.0,3.0,2.0,31.0,1.0
-SE,2816.0,7,3.0,7.0,6.0,4.0,7.0,6.0,3.0,1.0,31.0,1.0
-SE,2832.0,7,4.0,5.0,6.0,6.0,10.0,7.0,4.0,1.0,31.0,1.0
-SE,2836.0,7,,4.0,6.0,8.0,8.0,7.0,1.0,2.0,31.0,2.0
-SE,2838.0,7,5.0,8.0,8.0,8.0,7.0,5.0,2.0,1.0,31.0,1.0
-SE,2839.0,7,3.0,8.0,8.0,7.0,8.0,6.0,4.0,2.0,31.0,1.0
-SE,2840.0,7,4.0,7.0,6.0,7.0,8.0,5.0,3.0,1.0,31.0,2.0
-SE,2841.0,7,0.0,6.0,6.0,7.0,9.0,6.0,4.0,2.0,31.0,2.0
-SE,2844.0,7,1.0,8.0,3.0,7.0,9.0,7.0,3.0,1.0,31.0,1.0
-SE,2847.0,7,3.0,8.0,5.0,7.0,9.0,7.0,4.0,2.0,31.0,2.0
-SE,2851.0,7,2.0,8.0,7.0,7.0,9.0,7.0,3.0,2.0,31.0,1.0
-SE,2868.0,7,4.0,8.0,7.0,1.0,8.0,7.0,3.0,1.0,30.0,1.0
-SE,2875.0,7,0.0,8.0,10.0,10.0,10.0,7.0,,1.0,30.0,2.0
-SE,2879.0,7,4.0,8.0,7.0,8.0,7.0,4.0,2.0,1.0,30.0,2.0
-SE,2880.0,7,2.0,5.0,7.0,3.0,8.0,7.0,4.0,1.0,30.0,2.0
-SE,2893.0,7,2.0,7.0,7.0,8.0,8.0,4.0,4.0,1.0,30.0,1.0
-SE,2903.0,7,0.0,2.0,6.0,4.0,10.0,7.0,3.0,2.0,30.0,2.0
-SE,2905.0,7,2.0,7.0,7.0,7.0,7.0,5.0,3.0,2.0,30.0,1.0
-SE,2912.0,7,3.0,7.0,7.0,4.0,10.0,6.0,3.0,1.0,29.0,1.0
-SE,2929.0,7,7.0,8.0,7.0,8.0,8.0,3.0,2.0,2.0,29.0,2.0
-SE,2931.0,7,5.0,7.0,7.0,5.0,7.0,5.0,2.0,1.0,29.0,2.0
-SE,2939.0,7,2.0,6.0,6.0,5.0,7.0,6.0,3.0,1.0,29.0,1.0
-SE,2948.0,7,4.0,6.0,7.0,7.0,8.0,7.0,3.0,2.0,29.0,1.0
-SE,2951.0,7,1.0,6.0,5.0,3.0,8.0,7.0,4.0,1.0,29.0,1.0
-SE,2956.0,7,4.0,7.0,9.0,9.0,8.0,6.0,4.0,2.0,29.0,1.0
-SE,2957.0,7,3.0,6.0,9.0,7.0,3.0,6.0,2.0,2.0,29.0,2.0
-SE,2960.0,7,3.0,8.0,8.0,7.0,8.0,5.0,4.0,2.0,29.0,1.0
-SE,2968.0,7,5.0,5.0,7.0,5.0,6.0,3.0,2.0,2.0,29.0,1.0
-SE,2969.0,7,3.0,4.0,7.0,3.0,7.0,6.0,3.0,1.0,29.0,2.0
-SE,2970.0,7,3.0,7.0,7.0,7.0,6.0,7.0,4.0,2.0,29.0,2.0
-SE,2974.0,7,2.0,3.0,5.0,6.0,9.0,7.0,4.0,2.0,29.0,1.0
-SE,2992.0,7,4.0,8.0,8.0,8.0,8.0,7.0,3.0,2.0,28.0,2.0
-SE,2994.0,7,2.0,7.0,7.0,5.0,7.0,6.0,3.0,1.0,28.0,1.0
-SE,3004.0,7,1.0,10.0,10.0,5.0,9.0,6.0,2.0,1.0,28.0,2.0
-SE,3008.0,7,7.0,8.0,8.0,7.0,7.0,7.0,3.0,2.0,28.0,2.0
-SE,3012.0,7,4.0,3.0,7.0,7.0,7.0,6.0,2.0,1.0,28.0,2.0
-SE,3016.0,7,4.0,7.0,6.0,6.0,6.0,7.0,3.0,2.0,28.0,2.0
-SE,3017.0,7,3.0,5.0,7.0,6.0,8.0,7.0,3.0,1.0,28.0,1.0
-SE,3022.0,7,4.0,7.0,9.0,5.0,8.0,6.0,2.0,1.0,28.0,2.0
-SE,3031.0,7,2.0,6.0,4.0,4.0,8.0,6.0,3.0,2.0,27.0,2.0
-SE,3033.0,7,4.0,8.0,8.0,8.0,8.0,6.0,3.0,1.0,27.0,1.0
-SE,3034.0,7,0.0,7.0,7.0,6.0,9.0,7.0,3.0,1.0,27.0,1.0
-SE,3041.0,7,3.0,4.0,4.0,4.0,7.0,7.0,2.0,1.0,27.0,2.0
-SE,3046.0,7,5.0,8.0,6.0,3.0,6.0,6.0,3.0,1.0,27.0,2.0
-SE,3047.0,7,5.0,7.0,8.0,7.0,8.0,4.0,3.0,1.0,27.0,1.0
-SE,3054.0,7,6.0,7.0,6.0,6.0,8.0,7.0,4.0,2.0,27.0,2.0
-SE,3059.0,7,2.0,8.0,7.0,7.0,9.0,6.0,3.0,1.0,27.0,1.0
-SE,3080.0,7,3.0,7.0,8.0,6.0,9.0,3.0,3.0,1.0,27.0,2.0
-SE,3089.0,7,5.0,4.0,5.0,6.0,8.0,6.0,4.0,2.0,26.0,2.0
-SE,3090.0,7,3.0,8.0,7.0,5.0,7.0,5.0,3.0,2.0,26.0,1.0
-SE,3096.0,7,1.0,8.0,10.0,8.0,10.0,7.0,4.0,2.0,26.0,1.0
-SE,3098.0,7,2.0,3.0,5.0,6.0,8.0,4.0,2.0,2.0,26.0,1.0
-SE,3099.0,7,0.0,4.0,5.0,3.0,7.0,4.0,3.0,1.0,26.0,2.0
-SE,3114.0,7,0.0,6.0,8.0,8.0,9.0,6.0,3.0,2.0,26.0,2.0
-SE,3116.0,7,3.0,7.0,4.0,7.0,7.0,4.0,2.0,1.0,26.0,2.0
-SE,3120.0,7,2.0,7.0,7.0,8.0,10.0,4.0,3.0,2.0,26.0,2.0
-SE,3124.0,7,5.0,6.0,6.0,3.0,9.0,7.0,4.0,2.0,26.0,1.0
-SE,3133.0,7,2.0,7.0,7.0,8.0,9.0,7.0,4.0,1.0,26.0,2.0
-SE,3140.0,7,1.0,10.0,10.0,9.0,9.0,6.0,2.0,2.0,26.0,2.0
-SE,3143.0,7,2.0,7.0,8.0,5.0,8.0,6.0,4.0,2.0,26.0,1.0
-SE,3144.0,7,0.0,6.0,5.0,5.0,6.0,6.0,3.0,1.0,26.0,2.0
-SE,3145.0,7,3.0,6.0,7.0,7.0,4.0,4.0,2.0,2.0,26.0,1.0
-SE,3148.0,7,1.0,8.0,8.0,8.0,10.0,6.0,3.0,2.0,26.0,1.0
-SE,3151.0,7,4.0,7.0,7.0,6.0,5.0,7.0,3.0,1.0,26.0,2.0
-SE,3153.0,7,1.0,6.0,7.0,9.0,7.0,6.0,3.0,1.0,26.0,1.0
-SE,3155.0,7,3.0,7.0,7.0,8.0,9.0,6.0,2.0,1.0,26.0,1.0
-SE,3156.0,7,0.0,7.0,7.0,5.0,8.0,6.0,4.0,1.0,25.0,2.0
-SE,3157.0,7,5.0,7.0,8.0,6.0,8.0,7.0,3.0,2.0,25.0,1.0
-SE,3163.0,7,1.0,5.0,5.0,5.0,6.0,6.0,2.0,2.0,25.0,2.0
-SE,3170.0,7,2.0,7.0,6.0,6.0,7.0,6.0,3.0,1.0,25.0,1.0
-SE,3172.0,7,4.0,5.0,8.0,8.0,8.0,3.0,3.0,2.0,25.0,1.0
-SE,3176.0,7,4.0,3.0,4.0,5.0,9.0,7.0,4.0,2.0,25.0,2.0
-SE,3183.0,7,4.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,25.0,1.0
-SE,3185.0,7,4.0,9.0,8.0,8.0,10.0,6.0,3.0,1.0,25.0,1.0
-SE,3186.0,7,1.0,5.0,5.0,4.0,6.0,4.0,4.0,1.0,25.0,2.0
-SE,3189.0,7,2.0,7.0,9.0,7.0,8.0,4.0,3.0,1.0,25.0,2.0
-SE,3197.0,7,4.0,6.0,8.0,4.0,9.0,6.0,3.0,2.0,25.0,1.0
-SE,3205.0,7,3.0,8.0,7.0,3.0,8.0,4.0,3.0,1.0,25.0,2.0
-SE,3206.0,7,5.0,6.0,5.0,4.0,8.0,6.0,3.0,1.0,25.0,2.0
-SE,3214.0,7,5.0,7.0,7.0,7.0,6.0,6.0,2.0,2.0,25.0,2.0
-SE,3216.0,7,5.0,7.0,8.0,8.0,10.0,5.0,3.0,1.0,25.0,1.0
-SE,3220.0,7,7.0,5.0,5.0,6.0,10.0,2.0,3.0,2.0,25.0,1.0
-SE,3226.0,7,4.0,8.0,7.0,9.0,7.0,6.0,3.0,1.0,25.0,2.0
-SE,3235.0,7,2.0,5.0,5.0,5.0,9.0,7.0,3.0,1.0,24.0,2.0
-SE,3237.0,7,2.0,5.0,3.0,3.0,8.0,6.0,3.0,2.0,24.0,2.0
-SE,3238.0,7,3.0,6.0,7.0,7.0,7.0,7.0,3.0,1.0,24.0,1.0
-SE,3245.0,7,7.0,5.0,6.0,5.0,10.0,4.0,1.0,1.0,24.0,1.0
-SE,3246.0,7,2.0,5.0,6.0,8.0,5.0,6.0,2.0,1.0,24.0,2.0
-SE,3251.0,7,3.0,6.0,6.0,6.0,8.0,6.0,3.0,2.0,24.0,2.0
-SE,3252.0,7,3.0,3.0,7.0,5.0,5.0,6.0,3.0,1.0,24.0,2.0
-SE,3255.0,7,2.0,7.0,6.0,6.0,7.0,6.0,4.0,2.0,24.0,2.0
-SE,3256.0,7,6.0,8.0,8.0,8.0,10.0,7.0,3.0,1.0,24.0,1.0
-SE,3265.0,7,6.0,7.0,8.0,8.0,9.0,6.0,3.0,1.0,24.0,2.0
-SE,3272.0,7,3.0,6.0,8.0,8.0,9.0,7.0,5.0,1.0,24.0,2.0
-SE,3275.0,7,3.0,6.0,7.0,6.0,9.0,3.0,2.0,2.0,24.0,1.0
-SE,3277.0,7,2.0,5.0,7.0,8.0,8.0,6.0,3.0,2.0,24.0,2.0
-SE,3280.0,7,0.0,7.0,7.0,1.0,7.0,6.0,2.0,2.0,24.0,1.0
-SE,3287.0,7,4.0,6.0,4.0,5.0,8.0,5.0,2.0,1.0,24.0,2.0
-SE,3295.0,7,1.0,8.0,9.0,8.0,6.0,6.0,3.0,1.0,24.0,2.0
-SE,3296.0,7,2.0,4.0,7.0,4.0,7.0,6.0,2.0,1.0,23.0,2.0
-SE,3297.0,7,0.0,8.0,7.0,4.0,6.0,7.0,1.0,1.0,23.0,2.0
-SE,3306.0,7,1.0,3.0,5.0,2.0,7.0,4.0,4.0,1.0,23.0,2.0
-SE,3307.0,7,4.0,5.0,6.0,7.0,7.0,4.0,4.0,2.0,23.0,2.0
-SE,3309.0,7,4.0,5.0,3.0,6.0,9.0,6.0,4.0,1.0,23.0,1.0
-SE,3311.0,7,4.0,3.0,7.0,5.0,7.0,4.0,2.0,2.0,23.0,1.0
-SE,3313.0,7,2.0,2.0,7.0,7.0,10.0,5.0,2.0,1.0,23.0,1.0
-SE,3320.0,7,1.0,6.0,9.0,1.0,10.0,7.0,4.0,2.0,23.0,2.0
-SE,3322.0,7,4.0,4.0,9.0,5.0,3.0,4.0,1.0,2.0,23.0,2.0
-SE,3323.0,7,3.0,5.0,7.0,8.0,9.0,4.0,3.0,1.0,23.0,2.0
-SE,3329.0,7,3.0,3.0,5.0,3.0,8.0,7.0,3.0,2.0,23.0,1.0
-SE,3332.0,7,2.0,7.0,8.0,6.0,9.0,6.0,1.0,1.0,23.0,2.0
-SE,3333.0,7,4.0,5.0,4.0,5.0,9.0,4.0,3.0,1.0,23.0,1.0
-SE,3336.0,7,2.0,9.0,7.0,5.0,8.0,5.0,2.0,1.0,23.0,2.0
-SE,3354.0,7,2.0,4.0,5.0,6.0,8.0,4.0,2.0,2.0,22.0,1.0
-SE,3355.0,7,5.0,6.0,4.0,6.0,8.0,6.0,3.0,1.0,22.0,2.0
-SE,3359.0,7,5.0,2.0,9.0,7.0,9.0,7.0,2.0,1.0,22.0,2.0
-SE,3364.0,7,6.0,5.0,9.0,8.0,10.0,7.0,4.0,2.0,22.0,2.0
-SE,3365.0,7,4.0,8.0,10.0,5.0,6.0,5.0,2.0,2.0,22.0,1.0
-SE,3366.0,7,4.0,7.0,5.0,6.0,10.0,6.0,2.0,2.0,22.0,1.0
-SE,3367.0,7,1.0,3.0,4.0,5.0,8.0,7.0,3.0,1.0,22.0,2.0
-SE,3368.0,7,4.0,5.0,6.0,5.0,7.0,6.0,2.0,2.0,22.0,2.0
-SE,3374.0,7,5.0,6.0,8.0,8.0,9.0,2.0,1.0,1.0,61.0,2.0
-SE,3382.0,7,1.0,7.0,7.0,6.0,7.0,6.0,4.0,1.0,22.0,2.0
-SE,3390.0,7,2.0,9.0,7.0,7.0,8.0,5.0,1.0,2.0,22.0,2.0
-SE,3411.0,7,7.0,7.0,5.0,6.0,8.0,6.0,2.0,2.0,21.0,1.0
-SE,3415.0,7,7.0,5.0,7.0,5.0,7.0,7.0,2.0,1.0,21.0,2.0
-SE,3425.0,7,1.0,7.0,7.0,7.0,7.0,7.0,4.0,2.0,21.0,2.0
-SE,3426.0,7,2.0,2.0,5.0,4.0,5.0,4.0,2.0,2.0,21.0,2.0
-SE,3427.0,7,4.0,5.0,7.0,8.0,7.0,6.0,3.0,2.0,21.0,1.0
-SE,3428.0,7,2.0,7.0,7.0,6.0,6.0,7.0,3.0,1.0,21.0,2.0
-SE,3433.0,7,1.0,9.0,9.0,8.0,7.0,7.0,4.0,1.0,21.0,2.0
-SE,3447.0,7,3.0,7.0,6.0,7.0,9.0,7.0,3.0,2.0,21.0,2.0
-SE,3450.0,7,1.0,7.0,7.0,5.0,8.0,6.0,3.0,1.0,21.0,2.0
-SE,3452.0,7,5.0,5.0,6.0,5.0,8.0,7.0,3.0,1.0,21.0,2.0
-SE,3466.0,7,2.0,6.0,5.0,4.0,8.0,6.0,3.0,1.0,20.0,2.0
-SE,3478.0,7,1.0,5.0,6.0,7.0,9.0,3.0,2.0,1.0,20.0,1.0
-SE,3479.0,7,0.0,5.0,7.0,3.0,6.0,4.0,3.0,2.0,20.0,2.0
-SE,3481.0,7,3.0,6.0,9.0,7.0,8.0,4.0,3.0,2.0,20.0,1.0
-SE,3484.0,7,0.0,8.0,9.0,6.0,10.0,7.0,3.0,2.0,28.0,2.0
-SE,3488.0,7,3.0,2.0,3.0,6.0,9.0,6.0,3.0,2.0,20.0,1.0
-SE,3496.0,7,4.0,5.0,5.0,5.0,8.0,7.0,4.0,1.0,20.0,2.0
-SE,3497.0,7,4.0,5.0,7.0,7.0,10.0,4.0,3.0,1.0,23.0,1.0
-SE,3513.0,7,5.0,7.0,7.0,4.0,8.0,6.0,3.0,2.0,20.0,2.0
-SE,3514.0,7,0.0,7.0,9.0,5.0,7.0,5.0,2.0,1.0,20.0,2.0
-SE,3522.0,7,4.0,7.0,6.0,7.0,8.0,6.0,3.0,1.0,19.0,2.0
-SE,3524.0,7,1.0,6.0,7.0,6.0,9.0,7.0,3.0,1.0,19.0,2.0
-SE,3525.0,7,1.0,6.0,6.0,5.0,8.0,6.0,2.0,1.0,19.0,2.0
-SE,3526.0,7,0.0,8.0,3.0,5.0,10.0,7.0,4.0,1.0,19.0,2.0
-SE,3529.0,7,3.0,4.0,7.0,2.0,8.0,7.0,3.0,2.0,19.0,2.0
-SE,3532.0,7,1.0,6.0,9.0,7.0,6.0,6.0,3.0,2.0,19.0,2.0
-SE,3535.0,7,2.0,7.0,3.0,5.0,8.0,7.0,4.0,1.0,19.0,2.0
-SE,3550.0,7,2.0,8.0,,5.0,10.0,6.0,3.0,2.0,19.0,2.0
-SE,3551.0,7,4.0,7.0,7.0,6.0,7.0,6.0,3.0,2.0,19.0,2.0
-SE,3553.0,7,6.0,7.0,9.0,6.0,8.0,6.0,3.0,2.0,19.0,2.0
-SE,3561.0,7,4.0,5.0,6.0,6.0,8.0,7.0,3.0,1.0,19.0,2.0
-SE,3564.0,7,4.0,8.0,9.0,7.0,10.0,4.0,3.0,1.0,19.0,2.0
-SE,3569.0,7,3.0,5.0,7.0,3.0,8.0,6.0,3.0,2.0,18.0,2.0
-SE,3571.0,7,4.0,7.0,7.0,6.0,7.0,7.0,4.0,2.0,18.0,1.0
-SE,3579.0,7,4.0,7.0,8.0,7.0,10.0,7.0,4.0,1.0,18.0,2.0
-SE,3581.0,7,0.0,6.0,4.0,5.0,8.0,7.0,2.0,1.0,18.0,2.0
-SE,3584.0,7,3.0,4.0,7.0,5.0,9.0,7.0,3.0,2.0,18.0,2.0
-SE,3589.0,7,4.0,3.0,4.0,5.0,7.0,4.0,3.0,2.0,18.0,2.0
-SE,3592.0,7,4.0,7.0,7.0,3.0,9.0,4.0,2.0,2.0,18.0,2.0
-SE,3594.0,7,6.0,4.0,5.0,7.0,8.0,7.0,3.0,2.0,18.0,2.0
-SE,3599.0,7,0.0,8.0,7.0,5.0,9.0,7.0,2.0,1.0,18.0,2.0
-SE,3603.0,7,6.0,4.0,8.0,5.0,7.0,5.0,3.0,2.0,18.0,2.0
-SE,3605.0,7,0.0,4.0,7.0,5.0,6.0,3.0,2.0,1.0,18.0,2.0
-SE,3606.0,7,0.0,7.0,9.0,7.0,7.0,6.0,2.0,1.0,18.0,2.0
-SE,3608.0,7,6.0,6.0,8.0,7.0,9.0,6.0,3.0,1.0,18.0,2.0
-SE,3613.0,7,2.0,5.0,3.0,3.0,8.0,7.0,3.0,2.0,18.0,2.0
-SE,3616.0,7,4.0,5.0,6.0,8.0,7.0,6.0,3.0,1.0,17.0,2.0
-SE,3618.0,7,3.0,7.0,7.0,6.0,8.0,4.0,3.0,1.0,17.0,2.0
-SE,3620.0,7,0.0,5.0,8.0,5.0,8.0,6.0,2.0,1.0,17.0,2.0
-SE,3623.0,7,5.0,7.0,7.0,4.0,9.0,7.0,3.0,1.0,17.0,2.0
-SE,3628.0,7,0.0,8.0,8.0,7.0,9.0,5.0,4.0,1.0,17.0,2.0
-SE,3631.0,7,5.0,8.0,8.0,9.0,9.0,6.0,3.0,2.0,17.0,2.0
-SE,3633.0,7,4.0,4.0,8.0,7.0,9.0,6.0,2.0,2.0,17.0,2.0
-SE,3636.0,7,2.0,7.0,8.0,5.0,10.0,7.0,4.0,1.0,17.0,2.0
-SE,3647.0,7,5.0,8.0,7.0,7.0,9.0,7.0,3.0,1.0,17.0,2.0
-SE,3648.0,7,0.0,5.0,8.0,4.0,9.0,7.0,3.0,1.0,17.0,2.0
-SE,3649.0,7,3.0,7.0,8.0,3.0,10.0,7.0,4.0,2.0,17.0,2.0
-SE,3650.0,7,5.0,6.0,4.0,7.0,9.0,7.0,4.0,2.0,17.0,2.0
-SE,3655.0,7,5.0,2.0,2.0,6.0,9.0,4.0,3.0,1.0,17.0,2.0
-SE,3659.0,7,2.0,1.0,5.0,4.0,10.0,7.0,4.0,1.0,17.0,2.0
-SE,3661.0,7,5.0,5.0,3.0,4.0,5.0,6.0,1.0,2.0,17.0,2.0
-SE,3662.0,7,2.0,7.0,8.0,6.0,8.0,7.0,3.0,2.0,17.0,2.0
-SE,3665.0,7,2.0,4.0,8.0,7.0,9.0,7.0,4.0,2.0,17.0,2.0
-SE,3666.0,7,1.0,2.0,8.0,6.0,9.0,7.0,3.0,2.0,17.0,2.0
-SE,3668.0,7,6.0,5.0,3.0,4.0,9.0,6.0,4.0,1.0,17.0,2.0
-SE,3670.0,7,1.0,5.0,7.0,7.0,8.0,7.0,4.0,1.0,16.0,2.0
-SE,3671.0,7,3.0,4.0,9.0,7.0,8.0,6.0,3.0,1.0,16.0,2.0
-SE,3682.0,7,5.0,7.0,8.0,5.0,8.0,3.0,1.0,1.0,16.0,2.0
-SE,3684.0,7,1.0,8.0,8.0,6.0,9.0,7.0,3.0,2.0,16.0,2.0
-SE,3687.0,7,1.0,4.0,5.0,6.0,7.0,7.0,3.0,2.0,16.0,2.0
-SE,3689.0,7,3.0,8.0,7.0,7.0,8.0,7.0,3.0,1.0,16.0,2.0
-SE,3690.0,7,4.0,5.0,4.0,4.0,7.0,6.0,3.0,1.0,16.0,2.0
-SE,3692.0,7,6.0,6.0,9.0,7.0,5.0,4.0,2.0,2.0,16.0,2.0
-SE,3696.0,7,1.0,5.0,5.0,5.0,7.0,5.0,4.0,2.0,16.0,2.0
-SE,3700.0,7,2.0,8.0,9.0,7.0,9.0,7.0,3.0,2.0,16.0,2.0
-SE,3702.0,7,4.0,7.0,8.0,5.0,10.0,4.0,1.0,1.0,16.0,2.0
-SE,3703.0,7,1.0,6.0,7.0,6.0,8.0,6.0,3.0,1.0,16.0,2.0
-SE,3707.0,7,6.0,7.0,7.0,6.0,8.0,7.0,3.0,1.0,16.0,2.0
-SE,3708.0,7,2.0,6.0,8.0,5.0,10.0,6.0,5.0,1.0,16.0,2.0
-SE,3709.0,7,2.0,8.0,10.0,6.0,9.0,6.0,2.0,1.0,16.0,2.0
-SE,3712.0,7,1.0,3.0,6.0,4.0,9.0,7.0,3.0,1.0,16.0,2.0
-SE,3716.0,7,2.0,4.0,6.0,3.0,7.0,7.0,3.0,2.0,15.0,2.0
-SE,3720.0,7,4.0,4.0,6.0,7.0,9.0,7.0,3.0,1.0,15.0,2.0
-SE,3727.0,7,1.0,6.0,5.0,5.0,10.0,7.0,2.0,1.0,15.0,2.0
-SE,3729.0,7,3.0,4.0,5.0,3.0,6.0,6.0,2.0,1.0,18.0,2.0
-SE,3732.0,7,5.0,6.0,4.0,4.0,10.0,6.0,3.0,1.0,15.0,2.0
-SE,3743.0,7,4.0,5.0,7.0,6.0,8.0,6.0,3.0,1.0,44.0,2.0
-SE,3744.0,7,5.0,8.0,8.0,6.0,9.0,7.0,3.0,1.0,15.0,2.0
-SE,3746.0,7,2.0,6.0,7.0,5.0,7.0,7.0,4.0,2.0,15.0,2.0
diff --git a/Part 4/Section 3.3_3.4.ipynb b/Part 3/Section 3.3_3.4.ipynb
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/Section 3.3_3.4.ipynb
rename to Part 3/Section 3.3_3.4.ipynb
diff --git a/Part 3/Section-2.ipynb b/Part 3/Section-2.ipynb
deleted file mode 100755
index 23fb2f9..0000000
--- a/Part 3/Section-2.ipynb	
+++ /dev/null
@@ -1,2906 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Welcome back to to python data mining course! \n",
-    "# In this tutorial we will talk about basics of data mining"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Cluster analysis\n",
-    "## Classification and regression\n",
-    "### Logistic regression, k-nn classifier, and svm\n",
-    "## Association and correlation\n",
-    "### Outlier\n",
-    "## Dimensionality reduction\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Section 2.1 Cluster analysis"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import pandas as pd \n",
-    "import seaborn as sns \n",
-    "import numpy as np \n",
-    "import matplotlib.pyplot as plt  \n",
-    "from sklearn.cluster import KMeans \n",
-    "%matplotlib  inline "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "df = pd.read_csv('single_family_home_values.csv') # zillow "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>id</th>\n",
-       "      <th>address</th>\n",
-       "      <th>city</th>\n",
-       "      <th>state</th>\n",
-       "      <th>zipcode</th>\n",
-       "      <th>latitude</th>\n",
-       "      <th>longitude</th>\n",
-       "      <th>bedrooms</th>\n",
-       "      <th>bathrooms</th>\n",
-       "      <th>rooms</th>\n",
-       "      <th>squareFootage</th>\n",
-       "      <th>lotSize</th>\n",
-       "      <th>yearBuilt</th>\n",
-       "      <th>lastSaleDate</th>\n",
-       "      <th>lastSaleAmount</th>\n",
-       "      <th>priorSaleDate</th>\n",
-       "      <th>priorSaleAmount</th>\n",
-       "      <th>estimated_value</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>39525749</td>\n",
-       "      <td>8171 E 84th Ave</td>\n",
-       "      <td>Denver</td>\n",
-       "      <td>CO</td>\n",
-       "      <td>80022</td>\n",
-       "      <td>39.84916</td>\n",
-       "      <td>-104.893468</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6</td>\n",
-       "      <td>1378</td>\n",
-       "      <td>9968</td>\n",
-       "      <td>2003.0</td>\n",
-       "      <td>2009-12-17</td>\n",
-       "      <td>75000</td>\n",
-       "      <td>2004-05-13</td>\n",
-       "      <td>165700.0</td>\n",
-       "      <td>239753</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>184578398</td>\n",
-       "      <td>10556 Wheeling St</td>\n",
-       "      <td>Denver</td>\n",
-       "      <td>CO</td>\n",
-       "      <td>80022</td>\n",
-       "      <td>39.88802</td>\n",
-       "      <td>-104.830930</td>\n",
-       "      <td>2</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6</td>\n",
-       "      <td>1653</td>\n",
-       "      <td>6970</td>\n",
-       "      <td>2004.0</td>\n",
-       "      <td>2004-09-23</td>\n",
-       "      <td>216935</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>343963</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          id            address    city state  zipcode  latitude   longitude  \\\n",
-       "0   39525749    8171 E 84th Ave  Denver    CO    80022  39.84916 -104.893468   \n",
-       "1  184578398  10556 Wheeling St  Denver    CO    80022  39.88802 -104.830930   \n",
-       "\n",
-       "   bedrooms  bathrooms  rooms  squareFootage  lotSize  yearBuilt lastSaleDate  \\\n",
-       "0         3        2.0      6           1378     9968     2003.0   2009-12-17   \n",
-       "1         2        2.0      6           1653     6970     2004.0   2004-09-23   \n",
-       "\n",
-       "   lastSaleAmount priorSaleDate  priorSaleAmount  estimated_value  \n",
-       "0           75000    2004-05-13         165700.0           239753  \n",
-       "1          216935           NaN              NaN           343963  "
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.head(2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 15000 entries, 0 to 14999\n",
-      "Data columns (total 18 columns):\n",
-      "id                 15000 non-null int64\n",
-      "address            15000 non-null object\n",
-      "city               15000 non-null object\n",
-      "state              15000 non-null object\n",
-      "zipcode            15000 non-null int64\n",
-      "latitude           14985 non-null float64\n",
-      "longitude          14985 non-null float64\n",
-      "bedrooms           15000 non-null int64\n",
-      "bathrooms          15000 non-null float64\n",
-      "rooms              15000 non-null int64\n",
-      "squareFootage      15000 non-null int64\n",
-      "lotSize            15000 non-null int64\n",
-      "yearBuilt          14999 non-null float64\n",
-      "lastSaleDate       15000 non-null object\n",
-      "lastSaleAmount     15000 non-null int64\n",
-      "priorSaleDate      11173 non-null object\n",
-      "priorSaleAmount    11287 non-null float64\n",
-      "estimated_value    15000 non-null int64\n",
-      "dtypes: float64(5), int64(8), object(5)\n",
-      "memory usage: 2.1+ MB\n"
-     ]
-    }
-   ],
-   "source": [
-    "df.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>id</th>\n",
-       "      <th>zipcode</th>\n",
-       "      <th>latitude</th>\n",
-       "      <th>longitude</th>\n",
-       "      <th>bedrooms</th>\n",
-       "      <th>bathrooms</th>\n",
-       "      <th>rooms</th>\n",
-       "      <th>squareFootage</th>\n",
-       "      <th>lotSize</th>\n",
-       "      <th>yearBuilt</th>\n",
-       "      <th>lastSaleAmount</th>\n",
-       "      <th>priorSaleAmount</th>\n",
-       "      <th>estimated_value</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>count</th>\n",
-       "      <td>1.500000e+04</td>\n",
-       "      <td>15000.000000</td>\n",
-       "      <td>14985.000000</td>\n",
-       "      <td>14985.000000</td>\n",
-       "      <td>15000.000000</td>\n",
-       "      <td>15000.000000</td>\n",
-       "      <td>15000.000000</td>\n",
-       "      <td>15000.000000</td>\n",
-       "      <td>15000.00000</td>\n",
-       "      <td>14999.000000</td>\n",
-       "      <td>1.500000e+04</td>\n",
-       "      <td>1.128700e+04</td>\n",
-       "      <td>1.500000e+04</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>mean</th>\n",
-       "      <td>5.176229e+07</td>\n",
-       "      <td>80204.919467</td>\n",
-       "      <td>39.740538</td>\n",
-       "      <td>-104.964076</td>\n",
-       "      <td>2.708400</td>\n",
-       "      <td>2.195067</td>\n",
-       "      <td>6.164133</td>\n",
-       "      <td>1514.504400</td>\n",
-       "      <td>5820.76620</td>\n",
-       "      <td>1929.517168</td>\n",
-       "      <td>4.053563e+05</td>\n",
-       "      <td>2.594350e+05</td>\n",
-       "      <td>6.371625e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>std</th>\n",
-       "      <td>6.190876e+07</td>\n",
-       "      <td>9.715263</td>\n",
-       "      <td>0.023555</td>\n",
-       "      <td>0.039788</td>\n",
-       "      <td>0.897231</td>\n",
-       "      <td>1.166279</td>\n",
-       "      <td>1.958601</td>\n",
-       "      <td>830.635999</td>\n",
-       "      <td>3013.27947</td>\n",
-       "      <td>29.937051</td>\n",
-       "      <td>7.756998e+05</td>\n",
-       "      <td>3.379387e+05</td>\n",
-       "      <td>5.044185e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>min</th>\n",
-       "      <td>1.433670e+05</td>\n",
-       "      <td>80022.000000</td>\n",
-       "      <td>39.614531</td>\n",
-       "      <td>-105.108440</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>0.000000</td>\n",
-       "      <td>350.000000</td>\n",
-       "      <td>278.00000</td>\n",
-       "      <td>1874.000000</td>\n",
-       "      <td>2.590000e+02</td>\n",
-       "      <td>0.000000e+00</td>\n",
-       "      <td>1.477670e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>25%</th>\n",
-       "      <td>1.004802e+07</td>\n",
-       "      <td>80205.000000</td>\n",
-       "      <td>39.727634</td>\n",
-       "      <td>-104.978737</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>1.000000</td>\n",
-       "      <td>5.000000</td>\n",
-       "      <td>986.000000</td>\n",
-       "      <td>4620.00000</td>\n",
-       "      <td>1907.000000</td>\n",
-       "      <td>1.940000e+05</td>\n",
-       "      <td>1.100000e+05</td>\n",
-       "      <td>3.984348e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>50%</th>\n",
-       "      <td>2.563241e+07</td>\n",
-       "      <td>80206.000000</td>\n",
-       "      <td>39.748048</td>\n",
-       "      <td>-104.957689</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>2.000000</td>\n",
-       "      <td>6.000000</td>\n",
-       "      <td>1267.500000</td>\n",
-       "      <td>5950.00000</td>\n",
-       "      <td>1925.000000</td>\n",
-       "      <td>3.200000e+05</td>\n",
-       "      <td>2.100000e+05</td>\n",
-       "      <td>5.183575e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>75%</th>\n",
-       "      <td>5.114222e+07</td>\n",
-       "      <td>80207.000000</td>\n",
-       "      <td>39.758214</td>\n",
-       "      <td>-104.937522</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>3.000000</td>\n",
-       "      <td>7.000000</td>\n",
-       "      <td>1766.250000</td>\n",
-       "      <td>6270.00000</td>\n",
-       "      <td>1949.000000</td>\n",
-       "      <td>4.632000e+05</td>\n",
-       "      <td>3.302400e+05</td>\n",
-       "      <td>6.879692e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>max</th>\n",
-       "      <td>3.209481e+08</td>\n",
-       "      <td>80209.000000</td>\n",
-       "      <td>39.888020</td>\n",
-       "      <td>-104.830930</td>\n",
-       "      <td>15.000000</td>\n",
-       "      <td>12.000000</td>\n",
-       "      <td>39.000000</td>\n",
-       "      <td>10907.000000</td>\n",
-       "      <td>122839.00000</td>\n",
-       "      <td>2016.000000</td>\n",
-       "      <td>4.560000e+07</td>\n",
-       "      <td>1.600000e+07</td>\n",
-       "      <td>1.014531e+07</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                 id       zipcode      latitude     longitude      bedrooms  \\\n",
-       "count  1.500000e+04  15000.000000  14985.000000  14985.000000  15000.000000   \n",
-       "mean   5.176229e+07  80204.919467     39.740538   -104.964076      2.708400   \n",
-       "std    6.190876e+07      9.715263      0.023555      0.039788      0.897231   \n",
-       "min    1.433670e+05  80022.000000     39.614531   -105.108440      0.000000   \n",
-       "25%    1.004802e+07  80205.000000     39.727634   -104.978737      2.000000   \n",
-       "50%    2.563241e+07  80206.000000     39.748048   -104.957689      3.000000   \n",
-       "75%    5.114222e+07  80207.000000     39.758214   -104.937522      3.000000   \n",
-       "max    3.209481e+08  80209.000000     39.888020   -104.830930     15.000000   \n",
-       "\n",
-       "          bathrooms         rooms  squareFootage       lotSize     yearBuilt  \\\n",
-       "count  15000.000000  15000.000000   15000.000000   15000.00000  14999.000000   \n",
-       "mean       2.195067      6.164133    1514.504400    5820.76620   1929.517168   \n",
-       "std        1.166279      1.958601     830.635999    3013.27947     29.937051   \n",
-       "min        0.000000      0.000000     350.000000     278.00000   1874.000000   \n",
-       "25%        1.000000      5.000000     986.000000    4620.00000   1907.000000   \n",
-       "50%        2.000000      6.000000    1267.500000    5950.00000   1925.000000   \n",
-       "75%        3.000000      7.000000    1766.250000    6270.00000   1949.000000   \n",
-       "max       12.000000     39.000000   10907.000000  122839.00000   2016.000000   \n",
-       "\n",
-       "       lastSaleAmount  priorSaleAmount  estimated_value  \n",
-       "count    1.500000e+04     1.128700e+04     1.500000e+04  \n",
-       "mean     4.053563e+05     2.594350e+05     6.371625e+05  \n",
-       "std      7.756998e+05     3.379387e+05     5.044185e+05  \n",
-       "min      2.590000e+02     0.000000e+00     1.477670e+05  \n",
-       "25%      1.940000e+05     1.100000e+05     3.984348e+05  \n",
-       "50%      3.200000e+05     2.100000e+05     5.183575e+05  \n",
-       "75%      4.632000e+05     3.302400e+05     6.879692e+05  \n",
-       "max      4.560000e+07     1.600000e+07     1.014531e+07  "
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.describe()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X = df.drop('estimated_value', axis=1) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X= X[['bedrooms', 'bathrooms',  'rooms', 'squareFootage','lotSize', 'yearBuilt', 'priorSaleAmount']]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X.fillna(0, inplace=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>bedrooms</th>\n",
-       "      <th>bathrooms</th>\n",
-       "      <th>rooms</th>\n",
-       "      <th>squareFootage</th>\n",
-       "      <th>lotSize</th>\n",
-       "      <th>yearBuilt</th>\n",
-       "      <th>priorSaleAmount</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>3</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6</td>\n",
-       "      <td>1378</td>\n",
-       "      <td>9968</td>\n",
-       "      <td>2003.0</td>\n",
-       "      <td>165700.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6</td>\n",
-       "      <td>1653</td>\n",
-       "      <td>6970</td>\n",
-       "      <td>2004.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   bedrooms  bathrooms  rooms  squareFootage  lotSize  yearBuilt  \\\n",
-       "0         3        2.0      6           1378     9968     2003.0   \n",
-       "1         2        2.0      6           1653     6970     2004.0   \n",
-       "\n",
-       "   priorSaleAmount  \n",
-       "0         165700.0  \n",
-       "1              0.0  "
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X.head(2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "kmeans = KMeans(n_clusters=5, random_state=0).fit(X)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,\n",
-       "    n_clusters=5, n_init=10, n_jobs=1, precompute_distances='auto',\n",
-       "    random_state=0, tol=0.0001, verbose=0)"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "kmeans"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "labels= kmeans.labels_"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 28,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([  3.31226296e+00,   3.83944374e+00,   8.42730721e+00,\n",
-       "         2.69720607e+03,   6.97174968e+03,   1.94200506e+03,\n",
-       "         7.43586930e+05])"
-      ]
-     },
-     "execution_count": 28,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "kmeans.cluster_centers_[0]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X['cluster'] = labels"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>bedrooms</th>\n",
-       "      <th>bathrooms</th>\n",
-       "      <th>rooms</th>\n",
-       "      <th>squareFootage</th>\n",
-       "      <th>lotSize</th>\n",
-       "      <th>yearBuilt</th>\n",
-       "      <th>priorSaleAmount</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>cluster</th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>8.0</td>\n",
-       "      <td>2582.0</td>\n",
-       "      <td>6250.0</td>\n",
-       "      <td>1927.0</td>\n",
-       "      <td>651500.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>5.0</td>\n",
-       "      <td>1133.0</td>\n",
-       "      <td>6238.0</td>\n",
-       "      <td>1929.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>4.5</td>\n",
-       "      <td>9.0</td>\n",
-       "      <td>3748.0</td>\n",
-       "      <td>8597.5</td>\n",
-       "      <td>1998.0</td>\n",
-       "      <td>13750055.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>4.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>10.0</td>\n",
-       "      <td>4424.0</td>\n",
-       "      <td>8580.0</td>\n",
-       "      <td>1989.0</td>\n",
-       "      <td>2200000.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6.0</td>\n",
-       "      <td>1327.0</td>\n",
-       "      <td>5210.0</td>\n",
-       "      <td>1923.0</td>\n",
-       "      <td>279900.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "         bedrooms  bathrooms  rooms  squareFootage  lotSize  yearBuilt  \\\n",
-       "cluster                                                                  \n",
-       "0             3.0        4.0    8.0         2582.0   6250.0     1927.0   \n",
-       "1             2.0        2.0    5.0         1133.0   6238.0     1929.0   \n",
-       "2             3.0        4.5    9.0         3748.0   8597.5     1998.0   \n",
-       "3             4.0        6.0   10.0         4424.0   8580.0     1989.0   \n",
-       "4             3.0        2.0    6.0         1327.0   5210.0     1923.0   \n",
-       "\n",
-       "         priorSaleAmount  \n",
-       "cluster                   \n",
-       "0               651500.0  \n",
-       "1                    0.0  \n",
-       "2             13750055.0  \n",
-       "3              2200000.0  \n",
-       "4               279900.0  "
-      ]
-     },
-     "execution_count": 36,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X.groupby('cluster').median()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X= X.drop('cluster', axis=1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "from  sklearn.metrics import silhouette_score"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0.614559572342\n",
-      "0.616747726506\n",
-      "0.632865622992\n",
-      "0.64350268351\n",
-      "0.657962789235\n",
-      "0.661299799128\n",
-      "0.655707743822\n"
-     ]
-    }
-   ],
-   "source": [
-    "for i in range(3, 10):\n",
-    "    kmeans=KMeans(n_clusters=i).fit(X)\n",
-    "    labels = kmeans.labels_\n",
-    "    print silhouette_score(X,  labels)\n",
-    "    #print  kmeans.cluster_centers_  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Automatically created module for IPython interactive environment\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/koyuki.nakamori/anaconda/lib/python2.7/site-packages/matplotlib/figure.py:403: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
-      "  \"matplotlib is currently using a non-GUI backend, \"\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAR8AAADmCAYAAADsvYEoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMp3C/wNEj4nu3MK/pgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a12f62e90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAR8AAADmCAYAAADsvYEoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsvXe4HPV59v+ZsrO9nXNUj456BdFUEKI3Y0yxCNg4ARsD\nxjYupOAkJnHMzw5vHDtvYuf1mxfbITg2xthUY1MkemiSEEIg0YR01LtO27O9zvz+mJ3Z2T67wgik\nva/Ll8We2e/M7s73mafcz/0ImqbRQQcddPBBQzzcF9BBBx0cnegYnw466OCwoGN8Ouigg8OCjvHp\noIMODgs6xqeDDjo4LOgYnw466OCwQG70x4GBWKcO30EHHRwSxozxC7Ve73g+HXTQwWFBx/h00EEH\nhwUd43ME48EH7+Wzn72Sz33uSm655WZGRoZtv3fdurV87nNXtn3uRx55mIceur/t93dw5KNjfI5Q\nbNz4Lr/5zd389Kc/51e/uo9JkyZzxx0/+cDOv2HDG6TT6Q/sfB189NAw4dzBRxdz587jt7/9HbIs\nk8lkGBg4yMSJvTWPffTR3/Pb3/4aSRIJBkN861vfKfv7P/3Td5g2bQZXXfW5qv/+3e8e4OGHH8Th\ncKAoCn/zN3/Pzp07eOmlF3j11VdwOp1cccWV/PKXd/L888+iqhoTJkzgG9+4hZ6eMXz9618iEAiy\nc+d2LrvsCsaMGcsvf3kngiAiiiJf+9pfcOKJC/7YX1cHhwEd43MEQ5ZlXnjhf/jBD27D4VC44YYb\nq47ZvHkTP/3p/+XOO+9m3Ljx3HffPdx1188577wLmq5fKBT48Y//jfvvf4Senh5WrHiMDRveYNmy\ny3nppeeZNm0GV1xxJcuXP8rWrf3853/+ElmW+f3vH+L737+Nf/3XHwPg9/u5+249RLvyymXceuv/\nYv7841izZjWvv/5ax/gcoegYnyMcZ555NmeeeTZ/+MPvuPnmm7j33t8hiqVo+7XX1nDyyUsZN248\nAFdeeRWg53yaQZIkzjnnfL7yletZuvQ0Tj75FD72sQurjlu58iXeffdtbrjhGgBUtVAWkp1wwknm\nv8877wK+9a2/ZunS01m8eAlXXXVNex+8gw89OsbnCMXu3bsYGhrihBNOBODiiz/Jv/7rPxOLRQkG\nQ+ZxkiQjWFgYmUya/fv3l60lCAJQonzlcjnz37feehtbt/azdu0afv3rX/Loo7/n+9//Ydn7VbXA\n1Vd/nj/5k08BkM1micWi5t/dbrf57y9/+WtccskyXn11NY8//ih33/0L7rzz7jKD2cGRgc4veoRi\naGiQ73zn74lEIgA8+eRypk2bUWZ4ABYsWMTatWsYHBwE4Pe/f4jbb/8/ZceEQiE2bnwXgEgkwoYN\nb5j/vvzyiwkEQlx55VV88Ytfpb9/M6B7RYVCHoCTT17KI488TCIRB+C//uun3HbbrVXXnM/n+dSn\nLiWdTnPZZZ/iG9/4Jjt2bCefz79fX0sHHyJ0PJ8jFCeccBLXXHM9N930JSRJpqenh3/+53+tOm7G\njJl89at/wTe+cRMA3d09/P3f38rOnTvMY6644jP84z9+mz/7s8uZMGEiJ52k52BCoRDXXHM9f/mX\nX0FRnEiSxDe/+Q8AnHLKqfzoR/8CwNVXf57BwQG+/OXrAIFx48ZXJbVBz1H9+Z9/g+9+91vIsowg\niNxyy60oivI+fzsdfBggNFIy7LRXdNBBB4eKTntFBx108KFCx/h00EEHhwUd49NBBx0cFnSMTwcd\ndHBY0DE+HXTQwWFBx/h00EEHhwUd49PB+wANVc2hqurhvpAOPkLoGJ8ODgmSBKIImqaiaTlUNU9n\nCm4HdtBhOHfQFkQRBIGyvjAAVc0jCAUEQSr+rya/rIMOOp5PB61BFEvejmFXJEnE6dRbIAxjo6p5\nJEktekUdT6iDanQ8nw5sQRDKDY7+moDb7cThkCgUCvh8HmKxBNlsDkEQcLkUVFUjkUgjCBKiKB2+\nD9DBhw4d49NBU0hSdXjlcik4nQqZTJZIJEU2m8XpVAgEvKiqRiyWAEB3ejQ0LU+hUOgYoQ5MdIxP\nB3Xhckk4HDKpVMZ8TVFk3G4n+XyBWCyBqpZCqkwmSyaTxe12Egr50TRIpzOWFa1GSO5o9Bzl6Bif\nDqpQSiYLiKLu8kiSiMfjAiCRSJPPF+q+P5XKkEplCIcDeDxuJEkkHk9SKBileK1YGRMBqWOEjlJ0\njE8HJmrldQC8XheyLJFKZchm7Qt75fMFMpksoijS3R0ilcqQSCRNb0nTVEDtGKGjFJ1fuwNAz+tU\n5nYURcbhkCkUVEZHEy0ZHivi8SSDgyMA9PSE8fk8ZSV4VS2YHKEOUfHoQcf4HOWoZ3SCQS+CIJDL\nFUins4d8HiMJPTQUQZJEenrCZhhnLc93iIpHDzph11GKWiRBWZZwu50AxOMps1z+fkL3ouLIsoTP\n58HrdROPJ0mlMmVGqENUPPLRMT5HGWRZwO1WyipYoqjzdSRJz+vkcvnisX+8kng+XyASieFwyPj9\nXrxeN7FYkkwmW2aE3G6ZfF5DVekYoSMMHeNzlMDwciRJKDMqbreCouh8nUTigx9vnMvlGR4eRVEc\nphGKx5MmUdHtdpJIpMjn8x2O0BGGjvE5CiAV96sg6KQ/QQBFceB2K+RyBaLRRNs5FsNAeL0u4vGk\n6TW1imw2x9BQBJdLIRDwUSgUiMWSliM6RMUjDR3jcwSjVl5HkvQZ6IoiE4+nLNyb1uF0OnC5FLLZ\nHOl0llDITy6XJx5Pks8Xqkr2dpBOZ0mns7jdLsJhP4IgVIRbHaLikYKO8TkCUcvo6HkdF7Isoqoa\n8XjK1lq1DIjDIeF2u1BVlVgsRaFQIJvNkkpl8HjchMPBYu6m/c+QSqVJpdL09IQJBn2k01ni8aSl\nFN8hKn7U0TE+RxAMg2Pdh4IALpcTRZFJp3Mkk2kCAY+t9fRQrGRBRFHE43EiigLJZG2WczKZIpVK\n4/W68XrdiKJIKpVpO6zTNJVIJImiOOjpCZFKpYnHU+Z6HaLiRxcd43MEQBQFnE65mKQtvW6ERblc\nnmg0iaZpbVWMyg1YlkwmV/H38jU1TSMeTyKKApIkM2ZMmEQiRTKZonUbJKCqKvF4kmQyhc/nqbme\nqhYQBBVVlQCxY4Q+Auj8Qh9xiKJePne5HKbhkWWJQMCDw6HndZJJq+dR7s00gyAIBAJeAKLRZJXh\naYZ0OsPQUARZlunpCeN2u1p6vxWqqhGNJorrSfT0dDUkKnbY0h9udDyfjyjK8zpasQnUCItEUqk0\nuVx1WGRUu5pBliU8HheCIBCLJdvcyPqJdGJhDFmWLOX0hC3mtFGhs6KcqOjF49HL8+l0JVFRQFU7\nRMUPKzrG5yOG2qJeeujl97trhkWtwGrAMpksiuI4RA+iZDny+QIjI9Eip8djEguz2UbXK5StYYVO\nVIyWERXj8WqiossloaoahUKHqPhhQsf4fIRQS9RLz+voLRFGXqcd1MrriKKI0+k41Muugs7pGa3g\n9CRqJrBreT6VMIiKTqditmzEYglyubzZIpLJ5Mjlsh2O0IcIHePzEYCVJGjAWu6Ox5P4/R7bhqfy\n6V8rMf1BoJzTEyCbzROPJyq4R/U9n0oYYmYul5Ng0E8+XyAeTyAIQvEzdYiKHyZ0jM+HFEYrhF6h\nKr0uSSJud+NydzMYxkXP6zhN3k9twmHzMMUQkM9k2ut+T6XSpNNpPB433d0h0ulMkdOj2fJ8KpFO\nZ0inM3g8LsLhIKBV5Jc6RMUPAzrG50MIQQCnU8LlUkwyoN7GoOBw1C53twqvV1cYtDaSVqPxrrde\nUz5fLiDfKjSNYvk8jc/npqcnTDJ5aL1myaROVOzuDhEIeIus7pKYWYeoeHjRMT4fMtTO6yi4XA6y\n2XyxD6u9tY28DkChkCeRaN+AlVor9GtKpzNVAvLt5HY1TSMWS5JIpE3RMY/H2XbTq6YZJfoYTqfD\nNGqJRIeoeLjRMT4fElTmdTRNQxR1jo3RZGkVa28VpUZSXagrk2mvAdQoweutFeXXVCkgD5DPt3ce\nVVWJRuPF0TwOxowp6f60Cr3krpYZNYOomEiU2kxKRMWOEfog0DE+hxn1mj89HheiKBKPp2zldQz2\ncmWy2BAI01nHel4nGLT3s1s5QdYSfLNckyEg390dxOv1IElSRbhjH4IglOn+GJyeVvJL1ryRYdQS\nCQm/XzdC8bjeElIqz3fY0h8EOsbnMKGW0bEO4Uun9TlYrSSUrZusnkAYlIyK3fDN7a7fWtEI+XyB\nZDJdZCNXhzt2YBxbKqc78Pm8ZeX0ZqhllAsFXcxMlmWTc2QQHztExQ8GHePzAaNW8yeUhvBls1lG\nR9MtS5ha95ZhLDKZ3CEJhCmKXJS0aJ9DpGmY4Y7f76GnJ0wikWw7mZzJ5MhkIrhczqKEh15Ob2Sk\naxkfA/l8voL4WD51Fayjnx0douL7iI7x+QDh8eiEPWs1yOHQh/AZRLvSWJnWmkA1TUNRHDidjqJA\nWCNjYfR31f67VctZ0zSSydbzLJVQ1fotEfXQyGhUltOz2ewhtIGUiI+VSXODqOhwOHC7nUQi8Q5H\n6H1Cx/h8AGg2hK9dvo4BWZaQJBGwJxBWr7+rMlTL5/MEAr62r6sWjJYIRXGUsZHbKc+DUU7P4PW6\ni5IbOkfIarQaGbFKVCbNDXG0DlHx/UfH+PwRUZnXMbwZj8eFw9H6EL7q9UvGolBQSaUybSsT6mGf\noyxUO/Toov4C2WzObImo12JhNy9lSHgkkym83tqSG63CSJobnlWhUKBQsD4gOkTFQ0XH+PwRUC+v\n43BIJklwdLR5zkP3UGo/tY0ckSH87vO527pWh0PG43HWDNXsdsCD7snVNnyNd3/J0zBaLHKW0cr2\nWyugNBvM0P3p6ekikTi0dhHDswqF/LhcOhvcOnW1Q1RsHx3j8z6jVh+Wohh5HbXFIXzVm8ZYq1L4\nvRVDoWkakiSZYV88nq54qtuHcT2gG5J28y6VLRa655Fuy3OxSm74/V4zed/u8ENN08jl8uRyOQRB\n7BAV3yd0jM/7hNp8Hb13Ctobwmfl7lSuVe1l2BMJEwSh2B+mHFLYZ81ZGTwZI+9ibMxWUd5i4aGr\nK9gyLcCKfL7A6Gic7u4gHo+7rJLVKgRBoFBQSSatnlV15a5DVLSPjvE5RLhcchWL18jFyLJEMlni\n2EiS2GIFyyr8Xr5WrWObLW20aWha+0luKxfJarxKeZe0uTFVVSXTRqFMb7FIkMnoEzF6ekpEwHau\nV9M0S37JS6Ggs51bYV9bw197U1c7RMVm6BifNmHkdNxuhWRSNT2RylyMFUYOxy5EUcDn0wXCmvN1\n6ns+hvyG0abhdrvaSibrxqvERaoFg0EsSRJdXQH8fh+QaFhSrwdVVU0VxNJU00Tb7GZrJSsc1itZ\nsVilhEe9dapzb3anrnaIirXRMT5twNr8aYRGdobwVcpj1IM1j5JIpG2xeGt5PvWnTdjXcdY5Lobx\nUsu4SI1QKBSKeZI8Ho+rzZK6nnAuV0Asn2pq5/orfwujkuX1WiU8Ug1zVY3K9c2mrkJn/nwtdIxP\nC6iVTAbMRstmHJtmxMHKPEor+SErmk2bsAtRFNE0Dbfb2XaYls8XSCQal9TroTLXU3uqafvsZiO/\nVJmrqnW8KApNjW6j6zN+92DQUwxXCwhCa2H4kYaO8bGB+kP49LxOJpMllWqvkgKYshGyXJlHaa2C\nJQhChdRF7TKznXWNFg3QWysOFUbI834wkg0FRDtrNUtW18pVGRyh8nXsExVrKzQmKRQKiKKIqqpo\nWh5NE45qomLH+DRAPbF26xA+Vc0dktRFoxxRK+GRKAo4HHIxNGocQuiova5VeiMaTRIMem2d3y7s\nMJLNK2yy4e2tZY8rZM1V6T1e4TIJj1aMjwFj6qoe3gXNplXrGKOjmajYMT51UF+svVzr2OVSWu7B\nKuVRnOTzhao8yujoKG+9tQG328XixSc3XK/kgelVN3uNpNWbqDLkO5QZ7k3PbmEk19PWeb/WatVo\nGN3ulUnkdoyPAWt4p/fNuSqM5NFJVDw6PmULcDolgsHyalCjIXytN4CCz+fG6VSIx9MkEukKwxNh\nxYrH0TSdU/LAA/fXJQC6XAp+v4dCQSWdztj2wKxhl9Hu4fO5TZJgO4annQ1TGgI4isOhTzY1lBaN\na7O738sHCuprud3OtjlCRhI5Gk3g83kQRQFZbj88Mowk6N/9mDFhvF532X2maWrRCOWOioGHHc+n\niFJ4pZkbqXwIX22OjV3jY/BjRFEgnc7VZdu+8cZ6ensnFsmAEsFggM2bNzF37jzzmHKWc9LsaG81\nd2nt52rU7tFoAxvtGaDnOnTRMGPj2Lug2t5GovjX1iyHUZo31pIkiVyufblYI4k8blw3gUBpIsah\nNAJHowkSiRQ+n9dsATkaiYpHvfGp1/xpV0DLTvLWmtfJ5wsNb1zrfaZperVIkvSfqXFo1Fp+SFGc\n5PP5pvKs9YyOMUVDEATi8TSpVOqQGc7W+VuBgLeov9yeB2CsFQj4cDoVurqCtsXHKmGEXIODI2VJ\n7lIPmj1YK2aVU1xrT109somKR9anaQFGMrkyoawosil7YWc2eSPPx+GQCQS8SJJILFYaD9zIWC1c\nuJjdu/eQz+dJJpPk8zlmzZrVNDSyYwRFUcTn0/MOuVyuKuSr8wmxGjVB0CthPp+bbDZfvJaCGVYM\nDkaQJL3/SZf5aB2ZTJbBwQi5XB5FcRAM+tpeS1VVUqk0yWSaUMhPKORHkloLn6z5nmQyzeDgCPl8\nge7uEH6/17xfmq8jFnvASjA4TKOjMTweF93dIXNQY6358x/UTLUPAkel59NsCB9gW6i8lvHRPRQn\nUD1bS7956t+sHo+HP/mTK3jrrTfxet0sWrQISRKbhkbG2i+++AIHDuxn/PiJnHbaaaYSoZX3k8+3\nxy0xKmGNpmhYRcO6uoIEAl6iUdqa6aU3cmJu9EaVsUbQNK1MfKyrK0gmUxki1kdlslnTNBIJo5/N\nWp5PN7y2Rlyh8qmrXrzecjEzOPKIikeV8anN16lmAQeDXtvVDavxKe97ytZk4NrJETmdTk455RQz\nl7JmzVqGh0eYPHkKvb29da/jkUce4cUXX0SWHbz11pvEYlGWLVtWVjo3KnStwAixrCL0zZDP6wzn\nbDZXNcK4FRjNpsZGb7UyZkyuMFBZnrejK13vXqiW8GgsESuKze8p69TVSplY477RtAJut0ImY3CF\nPppG6KgwPrWaPxsN4Wuko1MJw5hUajDXP75xeGQ1hul0lhdffIFoNIrX62PdurUkkwlmzZpd873v\nvfcesqy77A6Hws6d23A6HVUGQx/L0zyM0b0mAa/X1bCptRFyuTyJRKpMGdBuP5WVo2Pd6H6/tzh1\novkonVq/YyWx0JhgUUksNNCM3Vwp4VFPIlYQRNs5rFoysdYck9frIpMZLU51/WhyhD56V9wCrM2f\n1pyB0+kgEPCgaXrloTKv00r5XJZlBAEzr9OM6axpGqOjoxw4cKBK6tPtduL3u012cj5fYP/+fXi9\nupRpT08PW7f2113X7XYXr0lCUWQkSW67dK4nffXvKBZLtmV4rEilMgwMjJDL5c1cSbPvuFaVrVBQ\niURiRCIx3O7yHIndNQwYxMKhoVEUpVSer17D3oOoVv5GUUrXZqdFoxL1ckwGU1o3zh/NsvwR6/lY\n8zolYl9J1KtRlUf3DKCRvpa12gPYnhLxzDNPc+DAfgRBIpvNcfnlV+Dzecqmfxr3uaZpVRvH+O9N\nmzayfft2AGbPnsOMGTNYtmwZd931S4aHR/B6fVxwwYW2rskKYyig8R35fJ6W12iE1kKo+sbJmiPR\ny/NazbDOjuGoLPXrnkvpodQqwbCyalea4NoeUdHIMVlbQIqfDtAQhI+mD3FEGp/KvI6maWb+xE6D\npO7K1r7xreGakdexmyM6ePAgBw8eZMKECRQKKqqq8sYbaznnnHPrtEQITJ06hb179xMMBtm3bx8T\nJkykv38z/f39dHd3AfDWW+vp7Z3A9OnT+PM//yui0Sg+nx9Zrv3z1u6A13WDJKn5UMBDhd0Qynhw\nNEKl4LveR2UN6+xLsdYzaO0ajcpr0zRIp9sfZWToHKXTGcLhAIGAl4cf/j2nn342Ltf7+5D4ICB9\n5zvfqfvHZDJb/48fcujJZZ29qyhykRyWsuX2GkzWynDF6VTwenWvIJFImQbk4YcfYtWqVbz55npC\noRDBYKjmugcOHGB0dBiXy40oisiyzNDQEHv3HuDAgX2EQmEcjpKbLggwa9ZMCgWVLVv6OXjwIJqm\n8vTTT+H3+1BVlUDAj8/nY2QkQl9fH9ls3ly/HiRJRBQl00twuxU8HhfZbI5ksrz8ruexcg1ZwsZU\njsrvSydC5uuGfXoVKksul8fr9eDxuItC7frxOnFSsCWdkc8XSKXSRWKmH1EUyefzuFxOstn611AL\nhULBTBoHAj5kWS4Ko7VHVjSGJ7rdTpxOpUh8bL9sLkkiiiIzMDDCr399F7ff/h94PB5mz577oUw+\ne73O79Z6/Yj0fKCk2pfN5osNffbfW5nzaRSuPfHEcgAmTBiPpmk8+eSTfOELX6x5E/T19fH6668S\nDodRVY2NGzeye/cuvF4vfr+flStXctFFFzNjxszidegGaNq06axa9TLjx48jl8tRKBRIJOK43S62\nb9+Ox+Pj+ONPbJnhXMmUHhkZZuXKVUQiw6RSaURR4Nxzz2batFnU8x4MlrSqqmWzruzC0EeuNcmi\nVY+jUoZVV1PU2t7khu5POBzA5TLIne2NfQbMh5Ysy7YrbbVg5I5kWebWW/+RjRs3c99993D22ecR\nCATaurbDgSPW+AgCpqFQFAeybD8uNqpBRl7HKMNv27aNBx64j1wui6I4ufba60kkEoTDQfOGlCSR\nRCKBz1c+70pRZIJBL5df/ilefvlF0uks2WwWt9vN1KlTAchms7z66hqL8dGN4P79+9m5cwfjxo1n\ny5Z+5s+fz44dO0mnM0Uj5EVRFIJBHz5f0MZ3oze2SpJoVsIikRH+/d9/RCwWY92613C7dY7Rr361\ni89//nr6+iaXrVGpjphKpatCn0Z45ZVXePXVV1BVleOOO55zzjm3SnZD9zZa5wcZ4UkymaK7O0Qo\nFCAeT9jmblUiny+QyWRN8mT7RkMs9uEZlTZ3W021pWSz/lsee+x8vvvd77V0LR8GHLHGJ5UqeTv6\nJrZvfFRVw+mUqtorHnjgPnp7J5pr3nPPr5k2bRqZTAZFUdA0/enm9ZZkKCqF32XZwSc+cRGxWJJI\nJEIiES87dy2Pad2615g9ew6gEQqFSCZTzJw5k+7uHl5//TWmTZuKwyGzYsVyTj/9bMaPH1/zc5Xy\nVQ5UtUAsVrrhV61aRSaTYXh4mIMHD6CqGpMm9TFlSh+bNm00jY8o6qFstTpitUJgvdzZ3r17Wbny\nJRwOB6IosmHDG/T29hY/Y4mLEw4H8Hr1Cl47m90Ii2OxJF6vu0zmtBUYHpgx9tkOp6fROmBU2hLm\nGGm71AEoNz4fBrz77tsIgojP58Pr9eHxuHE6XU3fd8QaH2tSVVVV2xR4XTZDJ9RVsnitDYqCIJDL\n5fj4xz/Bo4/+nuHhA2gaXHDBBSY/xhAIs3JkRFH/2759+9i6dSuRyDDhcBiv10s6nWbatJlV1+Rw\niIwbN5l9+/bT3d3Njh07OPfc8zhw4ACFgmq62hMnTuSdd96uaXysImPJZApFKScaGpIcq1evZHh4\nGID/+Z9nufLKK+nq6gZKIVazfjejotXdHSIY9FVxaAYGBsqS4ZIkm+c0YIRjuschtT3jXRAE8nkj\nrHMU2cOtER6rjUZrY58N1Cq1WyttJTJmYwNZvs7hy/Fks1n++7/vYO/ePTgcDgqFAqqq4na7ueWW\nbzd9/xFrfKyww9uxtlckk6miASo/xul0mmsVCgU8Hj2xe+WVnwEwe7dqTf8sXQuAxlNPPcGiRQvZ\nsWMHmzdvQlGcXHrpZSxcuNA81mAih0Jhnn/+BRRFT1aecMJJyLJCIBBmxozST6gr5ZX3LRlz1/Un\nt15Rk2WpKj901lln88tf/sI0TMbmP3jwIEuWLKnqom8GVdWKo2bSuFwKHk+YeFzvb5s+fTovvfS8\nhVKgMnXqtJrr6A+BSgJfoq4qQDVKhiOTyZHJRFomPNZiJhtjnys78Rslx3VZ2trnyuXytnWq9WR6\n+536hwpjD+zbt5cnnnicf/zHfy6GyBnS6ZRtZcajxvjU83xqtVcY3kklrr32eu655+5iFcVNIBDk\nRz/6VwRBYNGixZxzzrnFxHShLo9I0zRSqZTZvT5lyhSmTJlCLBZjwYIF9Pf3oygyxx57TFFuU2Pb\ntu1MnToVVVXJZrO4XB5OPfU0AB577BEGBweLnkuOSy65DChJsxpz161P+VgsxsGDCXy+oOkBKYrC\nueeey4YN65EkyWxLmDt3Hi6X0vZgQVXVSYH6ptIrWg6HzLJll/PKK6vRNI2TTlpQ01uz6vlUish7\nPPa8l1okw9oC8vUTyfp30bwnqzSWp77kRjO7bUenujzs+uA9H2NvdHf3cMYZZzF//vFtrXOUGJ/q\n14yWiFqyGapa21gFgyG+8pWvA/Dyyy8V+TV6Dui1115l9uyZTJzYx/DwCG+99SZ9fX1ViVrQm0et\nT9tcLoeiOHn44YcIBPRE9euvv86lly4jFPKRSqWYNKnU0zU0NGT+++KLL2XPnt1kMlmOP/5YEokU\nTmd9adZ169bx9tsbigP04nz84xeZG/+qqz7Lww8/zKZN75FMJlAUhUhkhIGBYVsxfC0YHoO+qUbN\nnqX58+cxZcpkGyXw8h+vtDmt3kuyrmG0IyBfqd1cebidqlv12OdyvlGr7OZaOtVGe4VOazh83e2r\nV6/kRz/6F8aMGcuuXTtJJBKcfPJSenp66OrqZvz4CWZ1sBGOWJ5PJdHQ6XSYwuxOp6OMr5PPV2+A\nZuN1V616GbfbVTyXgMvlYng4gqrC3Xf/glQqybp1rxGJRKp6sdxuJy6Xl40b3yUajbF16xai0Qjd\n3V2EQiErp8FoAAAgAElEQVQkyYEkSUQiEfL5HGvWrKGnp8fk7qTTGY49dr65XiAQIBwOFzWIdE8m\nkUiRy1VvyCeeeJzJkyfj8+nl/c2bNzNv3jGAnve56KJPsHz5Y4TDXSxcuJB8Xuf+zJ8/v2otK2pt\nfrdb5w5Zk6MG58XKx6nnvbhcCvm8WtOLMNYRRYlQSJfc0Lkz5cf5fJ6mlaRsNkc6ncHlcuL3+9A0\nrawX0Ot1F0c322mxyNfkGwmCiMultJyzyuXypFKpsvV0gmu66NFLHzjDWVEU3G43M2bMZNq0Geze\nvZNXXlnF008/wd13/4LR0QinnXYG+XweURSPPp5P5X2il9zlIidFq8Motr5fa/jEmzNnDqtXr6Sr\nqwtN0zh48CCnn34Wy5c/xrRpev7C6XTyxhuvc+GFF5WFcZqmMW3aNKZOncr99/+W2bNnsWvXLkZH\nRykUVHp6xuBwOFizZjU7doylq6uLl156kSlTpiJJEhdf/MmyaxFFgWw2TX//Prq7x2AIT23c+A5b\ntmwFNMaNG0d/fz87d+4gHo9z/PHHmdcCJaGyVCrO1KnTkWWpKGwukMu1V6JuBKvXUb/c3JydnEzq\nye1a3kujvq5KVDaHer2usgGAh8o3akXmttl6oijidrvaEmw7VGiaxtix4/jMZ67mwIH9+P0BPJ5y\ndrVhuOsx7A0cscbHClEUEUU9zEok7LUO1DM+IyNDvPzyi2gadHX1sH//PgQBzjzzLCZPnoKu4ZPk\n9ddfx+fzEY1GWb16NUuXLrWsrW/2devW8s47bxMOh+nt7WXLlq309vbS3d3Djh07kWWZ7u5uQqEw\nkyZNYnh4mE996jNlhsztdvLGG+t4/fU30DSVjRs34vP5Aejt7cXv97Np0yZefPF5zj77HGbPnk0q\nlaK/v59QKExv7yQ8HmfxaZrB5fKiKA5efXUNqqoRDAb48pe/0vC7UhQHTqeDRKK1JlYrH8dos4jF\nSpUju8bDuo6x2fUKVJZWZVhrDSi0I4XR7LoCAV+RrOpqa+yzsV48nih63Bo33ngDH/vYJ1i27Iqq\n6uUfC4Ig8MgjD/PUUyt47713mTRpMh//+Cdwudwcc8x87rjjdk4++RSuuOIzxSpzfa/siDU+xpPP\nENFSVc2UMbX//tIm1yUukvz6178q5nE09u7dw3XX3UA4HMbncxGNJpkzZy4PPng/p5yyxPzin3nm\nSU455RSzBC8IsGbNKoaHR5g6dSpOp5OtW7cxY8YMNm3aRCaTJZvNMDAwQDqthzz6TC63eU0GOzmb\nzfPMM88SDofIZrNMmTKFffv24/N5SSYT7Nmzh9HRUd599102btzISSctYP78Y9m1axcnn3wKp522\nlI0bN/H000+zd+9eUqkkb7/9Nl6vD78/wIQJ43j33XeZO/cYhoeH8Xg8Jo9peHiQZDLBtGnT0DSh\nKPiVJh5vjZNjdKrX1nC2j5L3IhfH33jaZjdbc0vBoI9g0N8wt9TsulKpjKmlpFeyWqnYlWBUzOLx\nFN/85t/xs5/9jHvvvYef/OROxowZ2/J67eDEExfg9fr4wx8ewu8PsH796wwMDPDzn/8nU6ZM5aST\nFgHNR4MfscYHIBDwmvIUrY640ZPOoKolA7ZixeP09fUVc0l60+eqVSv5xCdKYdXZZ5/Dyy+/VGbx\nBUFPKht6wpqmsXfvfkKhEKFQmGh0FFUtMDg4yHnnnc/WrVuYNKkXRVEoFPJs27YNl8vFokUnV+k4\n5/MFotFRJk6cgKZpOJ1OkskEgUCA3bt3M3PmLJ555mlisRg+n4+XX34Zn8/L+eefzymnLOGtt97l\nX/7lB8TjUTZseBOHQyaXyyNJEtOmTSMcDjMyMsy3v/0ttm7ditvt4qqrPovP56G/fzNut5vly1dw\n0UUXM3bs2KIous7JseK1117lueeeo1BQWbRoEeedd37Vd17ZZiEIQlsbNJ/Xy9Zut5NAwEdXV5Bo\nNFGl6WQHmUwWTdPIZvPF2VuNK2P1YPS+xWIJs/JncHpaGSFtsKQBpk6dzg9+8CO2bt1CKBRu8s73\nD319k+nrm4wkScyffxzd3T01jzuqjc/oaBLD7W59xI1WnMzgMlUAJclBNpvF6dQZy5lMlnC4p2rt\nOXPmMDw8iN/vR1VVHA6Fnp6wWTZ1u11mNa27uwe/308ikeSzn/08b7/9Jl6vjz17duNyuUgmE2zY\nsJ5vfONvmT17phkeGclzPSeTJ5PRhcd1sp5AX18fmzZtwu3eTSaTQZYdxONxZNlBJBLhjDPO4ODB\nYe6//z5isSixWAxN071Dg+czOjrKmDF6aLlr166ia69x332/YfHik822kEAgyMsvv8SyZX9Sxslx\nOGQUxcHevXt5+OHfmYnR5557lvHjx5clza0wKkc9PSECAS+KIre14XO5vNlwGg7X6nhvDiP0LuWW\n3G21WFhD+FLlr/UR0taqmXHPGe04HxSMcGrfvj089ND9TJs2Hb/fTyaTZty48cycObvYa9h4v300\nhUBswnpj1Cuf14IsSzgcErJcPqfr7LPPYWhomOHhYYaGhohERjnjjDOr3n/FFZ+mq2sMIyOjZDIZ\n/vqvv1G8WY2OcY3TTjud3bt3s2XLFl544QUikRGefvpJZsyYxVtvvYnb7S6Gemni8TirVr3Etm3b\niUYTpuExcNJJCxgZiRCLxRgdHSUUCiGKMj/84f8hFOrC5XIXw4cgU6ZM4eDBAa6++mouvPBjPPbY\no7z++uvEYnHzZjnmmGMZO3YMCxcu5oYbvkR3d0+xyqJXVvR8ij6xolZOJZ8vsGvXHp555ln6+zcz\nMjJUVpERRZE9e/Y0/R1UVWN0VDeKPT3Vc66awdjwqVSmKMhlX8iscg0wcjhJhoZKIvmGF9oMtVoi\n0uksg4MjxYdY0JZQfuU6h6OL3fDq16xZzdSpU5k1azbd3d289957PPXUE/zHf/yIu+/+ZdMQVWhk\nuQcGYh9pqXxjOgVQfArLDUW/jOmfkiSZ0g6Vbr+qqrz33kYEQWDOnJKEQSw2wvbtu5g9ew4ul7NM\nsL2yFcHjcZLPq0SjMX74w//NnDmzEUWRWCzGhAm9vPnmBnNj79q1i6VLl+L3B9izZw+XXPJJpk2b\nXraepmmsWrWSQiFLd/dYjjnmWPNvkiTy7LNPsXz5cmTZwZ49exFFke3btzI4OITf70cQBKLRKFOn\nTsXtdjN79hxOPfVULrzwIrxeN6+8spp///cfkc8XiqFDFEVROO20U/H5fCiKwjHHHMtxx52IPmJm\nkNtv/w9UtUAmo+esdu3aRaFQIJvNo6oFrrnmOmbNmtXw97OOu5EkEZ/Pg6I4bPdAKYoDn8/D8PBo\n2W+si7c5bTV0Gnko6xoGDA9PkiRisUTDlohg0Ec2m6t73bpcrbtYcawvlK8bYIF4PIkgiIhifRXH\nPyby+TzXXvtn3H33/WWvf/WrN3D77f/FddddxX//9z0AjBnjr2khj+iwywrd86n/VKlsiXA6HTWf\nQqIomrwYAw899ABbt/bjdrt59NHfc/PNN+N2O+u2IhjJ8H379tLVFTavy+/3c/DgQS6++FJWrHgc\nQYDjjjsOWdY1eidP7mPt2lerjI8gCJx66ml4vS6y2Ty5XL7MkJ5//gWcddZ5ANxyy98yMHDQvK5c\nLsdJJ51EMpnkX/7l38qYxk6nA4dDYsmSJdx449dYu3YtiUScV15ZjcPh4MUXX0KWZU477XROPHGB\nqbz43HPPkkqliueXef31N7jqqs+ybt1aJElk4cLFzJ49u+Wk9OhovExtsFk7g/5dl5/DmGxqbei0\nVtgq0ajMXqsyVo913YglbVynMfbZqvJYSXo83ARDA+l0mlAozIoVj3HccSegKAp79uwuPmDs5emO\nGuOjaWpNF9WYuKknbkvGQtdLae7SxuNxNm58h+nTdYPQ1dXF3Xffwxe+8MUG16LniMaOHVfWcJlK\npenqCnPyyQvx+3384Q9/IJ1OFkvnGqpa+zOU1jUqfPV7y/r6+jh48ABjxoxhaEivXqmqyimnLDUN\njy6l6mTbtu2sW7eOmTNns2jRYhYsWMj69etZs+YVQDBZrF1duqJiqZonFENcvT1C0/S8xIIFC4uz\nwzzFcdFJs+z8zjvvsH37NkKhEEuXnmquU7nxW2lnaGQ46k1JrTRmdjg+dljXdjvRyydieE3agOEx\n6aRM4xoPX1Opx+PhqquuYfnyR9mxY3uxsrqbSy9dxsMPP8CkSdXM/kocRcanPClcXjWq7luym6BO\np9NlHAs7N6uhF+T1ejnrrHN5+eUXiuStMVx++eXEYkkmTpzEjTd+ld/85tcMDBzE5XIxODjEF77w\npbrr6mL51YbUii9+8cs4nU5GRoY4/vgTmD59Bt3dPZx//sfK+sGeeuppfvjDfyuycwUmTtTbOxTF\ngcvlKlaOBDweD2eddVbZOc4//zz6+zeRTqfJ5/Mcf/zxZue9tSvcIPP9z/+8wIoVK8xwd3BwgE9+\n8rKG32F5O0PtOVx2fot6QmaGMWuFYNhoNlirRMXSRFO5rDL2YZHTEEWRU089nbFjx/Haa2vo7Z3E\nZz97LV1d3Wze/B6XXLKs6RpHkfExWi6ss7UyVcnb0vHNjY/LpTB9+hQEQX8aORwO9u/fz9Klp9u6\nFoDFixdz1lmnFxtbM1XTLz7/+c+zZcsWBgYGmD//+JpkMkNjR5KkhnkF0KnxN9zwJcJhPyMjMfN1\nQ3JjeDjCyMgoDzzwAIlEglQqSSKRZNu2rZx66mlkMhn8fj8nnngC+bzKRRddzIQJen+bJIl4vR5C\noQA33fQXrF37Kn6/n4ULFyMIsHfvPvbu3cPs2bPx+fxmyLJ16xZ8Pq+ZM9myZQtgj2SYSqVJp2vP\n4WqF4VwpZGYYjnb0m2vNBmtncgWUaANGaCdJEqJokDAPn+czPDzEihWPc/DgfiZN6gPg5ZdfZPbs\nORxzTONWHANHjfEB3aDo3J8co6ONSWyNjE9JVrVAPJ7kppv+kkce+R2pVIYzzjibhQsX2Vrbzjx4\nTYO5c+fQ1zel6m+6KNeLSJLIWWedTW/vpLIbfO3atWze/B4A06dPZ8kSK8taP84IsVRV47777ufe\ne+8lnU6zefNmIpGRIsclWyaQ1t/fTzQaxeFwkEjEuemmv8Dv9+JyOUkmdWMQDAbLuDxPP/00Dz30\nAKqq4fV6+NrXbmLy5ClkszkymRzvvvsu27dvQ9M0pkwx5DXsib9b53D5/SWGs2BDgL4SlYYjl8u3\nNTaocjaYKLbX22XACO3Gju3C7/dw7733sGDByUyd+sGW2QuFApIk8cIL/8PLL7/ACSecxL59+4jH\nYxw4sB/QOOaY+eZxjXBEGx/jvjO0evTWh9oNl5WoVZqvJb8Bujfx2c9eY1tkXJb15sBsNtdUH6ee\nERwdHeHBB++lr68PTYNf/OIXfOlLX6anRyd87dixna1bNzNunM563b17F11dPWUVJq/XZUpujI5G\nuffee4s9cE7i8TjpdBqn01lk1eq8p1gszsjICKFQmI0bN7Jq1UpeeOF57rjjv+jpGVsnwa7xxBOP\nF5sgVXbu3Mn3v/9PfP7zX2DJkiVMnTqVn//8DnK5HLLsIJfLsHVrP2PGLLbtuUD5qGa/34ssy2UC\ncHZhNRzhcACPx9B5at1wGGGmIR7fuh5ROQRB4ODBYZxONzfd9FWWLj2Nm266Gb/f39Z67WL//n0s\nW3ZF3fFMzQwPHOHGRxAEfL6S5KfLpbR0M5fWoWHpHOyFaUaeSRCMCQmtN2wautJPPvk4vb2TzM8z\nderUItFPz5Vs376N7u5u833hcJjdu3cya9YsnE49dFNV1UxIp1IpMpmMOT3D4/HgdOpd3qIokclk\nSKXSzJw5g0wmwxtvvMHAwEHy+Tyjo6Ncd921/PCH/87MmbXL57lcgUwmw9atWxgYOIjT6WTt2q8S\nDAbx+/309U3G4VCQZRlZltm3b2/RW3DWnSRaD0YVymCUt8tw1vWTckXmuGJW2FqVYTVCrlL41B67\n2apvdOGFF3Hmmefx4IP3MTIy9IEZH+MeD4VCvPDCs4iiXjjx+wO43R56enqaNpQaOKKNj6rqtHjj\nB26H5WyVH62UVa08tl4pv3zWV4ZCQbVNTjOu2WoAU6ksouggk0njcukax+l0irFjx5qfb8qUaaxZ\ns8r0hCKRCCeccJJZIdLH1pRu/HA4zIwZM9i+fXuxEjcW0CUbtm7VG16zWX1O2ZQpk3n22WfMzayq\nKrt27eaFF56vaXwEQcDv9/H8889x8ODBoka2Qj6fJxaLMn78eHbt2sWZZ+qETVEU6eubYvZCud1O\nW2X1ShiqlKqqFhnOubKRw3ZgyLDG40lbJfXaa5QUDA+d3Vy6dp/Pz7XX3mD7s7wfMO6vYDBEIpHg\n+eefw+12F6uHEb72tT9n+vSZtvbaEW18QJfONL6DVlnOgiAUSW2ppjdsvS/baryMPFM9pcTa6+rH\nBwLeYpuHbgDPPfc87rjjZ0QiETQNZNnBueeeZ75v6tSpDAwcpL9/E6Axd+5cTjrpBDNcDAa95nXr\noZLKN795Cw888ACpVIpFixYhiiL/+Z8/Q5ZlxowZgyiK7NixnX/4h29z7733kcvlTNVD/f9LxjcS\niZDL5Uzjp+dzStT8dDqNKIpkMhmcTheaBtOmTUfTNM466+yiQgCmt2BHJbAShhpjKmVUoXTlwlZa\nI6rbIuwLmRmolWyuFAurVa2rXufwV7qM+/bUU09nyZKl7Nmz23wtEokwbtz4suMa4Yg3PlbYscbW\ncrNx49p5UlaubU3kVmoHWatdjVAK04SqmeuiKPKlL93Ijh26p2LIeVjXXbz4ZM4443ST8xONlifZ\nNU1F0/R5W6lUkvvu+y0DAwPs3LmTd999h0mTJrF48cmsWrUSh0NGEAQymQKhUJhLLrmEp556klgs\nhqIozJkzm4997AIA7rzzTp54YjmqqrJgwUJuvvkbbNu2HZ/PRyLhK0pvFExvcWRkmFmzZvOXf/lX\nxflfFD0FPeFcrxLVbCNaq12GJo7en+W1LUhf23BkzApbd3eQVCpDIlG/96yRJEetylg9w6gbn1Jf\n1+GsduXzeR5++EGi0VG+/vW/4pVXVrJ48ZKWFC+PKuOjEwebsZxL8qMGld0ODINiZRZXaieXjm1s\nBMvDtCxut1LTAAqCQLnwuoZBPCvNXK/Wk9Y0zQx9dAatyj/9021s376dzZs3kUwmmTlzFkNDQyxa\ntIjJk/vYunUrIHDJJZfi9we45Za/Z+LEXnbu3EE4HOZv/uZv6e2dwOuvr2fFiseLJWGRN954nSef\nfIKuri6GhgYJhUJFb0fvWtenHqh8+9v/H6BvMEHQkCQHglA+urpyo1YygGOxGM899yy5XI5jjz2W\nJUsWU1kt0xnO5YL0jfI4748Ma2OPpbIyVs8wVoZdhxM//vG/0dc3hWeeeYrrrvsS//3f/8XmzZu4\n9tobbO+ZI974WL2MepveWjqPxRLmRjW4IvbOoz/F/X5PTWaxXdQK04y5X82vQf+sXq+7aub6hg0b\nOHhwP/PmHcv48WO57bZ/ZP369Xi9Xi655FI2b96MoihkMhk0DUZGRhg7dgyxWJRbbvl7tm/fTjAY\nMsOo7u5u/uqvbi47/8hIlMHBAdNL0vWGRRKJJFdccQUrVqwoTl0Q8HjcTJ48he7ubjRNM6twRo+T\nojgYGdEbOI2po4YhMJjRVuGweDzJPff8imQyxfDwMA8+eD8nnngiJ520gPPPv6Dqd7fbGtGM51Mu\nZFbNSAb7+s3NxvIcbuF4A8lkkh07dvDd7/4zq1evJBQKceedv+Izn7mM666rz+yvxBFvfKyonGJh\nlM4FoXoAnnG8HStutGiAUMzJ2JVZKIUFtUbctApFkXE49IqctWFy+fLHiMWiBIMBnnxyOdFonOee\new5RFBkdHeWuu+4qjg3ScLlcJBK65kwul6enZyySJFfJNqxdu5bdu3exd+9e0ukU48eP58or/5R5\n846lu7uH4eHhYjOvk9NOO41JkyYRCoW5/fb/R6GQZ2BgoMihyXHZZZehKIpJXOvv38KePXvo6upi\n8uQpXHvt9TidStkGruz1isWi7Nu3j71799Lfvxm/P8Dg4CD9/f0EAkGWLDml5ndWmceplN2wSzI0\nGMm1es9aJSrWG8tj1fI5nEgmk+bASodDNyHr179OOKy32djdN0eV8dFdeNFW6Ryaf4mVvB+v1237\nJtOP03M09Ubc2IXhuamqLrZu5ZAUCgV27drJlClTEATo7Z3IypX3I4oikUiEwcFBCoUCV199Nf39\n/UydOpVEIsm8efOYNm0a1157XdX57rnn1yxf/ji7du1ieHiY2bNn4/f7iUZj3HjjV/jud2/jd797\nEE3TWLZsGTNmzCCRSLJx40b27NlNLpczk8Fz5szlqquuxul08LOf/YRIZJQ1a9ZQKOSZN+8YRFFk\n+fLHuPzyKwDNkiDXYbRHZLN5+vv7yedzpFIpUqkU06dPQ5IkRkcjTb/D8jxOyOwsb9Vw1Oo9U1W1\nrd+1WlwNSyh2eDyfQqGA1+vl4x+/iPvuu4eRkQh33fVzNmx4g3PPrRaIa4SjyvgYzaUlhcP6pXOo\nnyOya7waX4tmju5pFqZpWu0ncOXoYigNGjQ2qaYVgPLwceLEXrZv38GOHTuKQwRl1q9fz49//H/Z\ns2cPsViUY4+dTzye4IEH7iMYDHPRRRcVQ6kCzzzzNKIoEo/H0TSNffv2MTAwwKZN77F37x7+7M+u\nLmuszWZzBIN+Xn11jVkZ0nV2ksydO5dQKMB7721mx46d5HI5s4oWiYwwZswYIpEIQ0NDeL3e4uBG\niEaj7Nmzh7FjxxEOh9m//wATJkxk9+5dOBwOnE4nbrebfD7PxImTbP8uRlLa6Cxv1o1eD9bes0BA\nb4vIZLJteS7GWt3dIbxeN2vWrGbs2F7Gj+9t/ub3GZIk4Xa7ueCCC5k8eTIbN77D8PAwN9xwI3Pn\nHtMSneWoMT5GWCMIEIs1L51Dbc9HURy43Yqpbmg1CEbOpdmDUpb1ZKwkaXWHC1ZcSdUrtUYXS5Jo\nehR6F7zu6U2Y0Es0GiUQCLBv334+/enPEI3G2L17F5IkMXbsWCKRUW6//XY2bdqEpqkUCjopUJIk\n8vkCGzasZ8GChTzwwL2sXfsqXq8PWZbJZDJEo6M4HA58Pj+RSIS77voF3/ve983vLp3OkMlk8Xo9\npqi+Ifl64YUfZ2QkysqVq1i37rUi8TFJKBTC6XSTSCRYt+413nrrTVwuN5/61KcZM2YMjz/+GJqm\nUSgUOO20M+jt7WXChAlMnjyZeDzOrl07mTRpEuecczbz5tnrNTJQ6ixP09MTKuZx2mMlp1K6PIum\naW1rXFsxMjLK9u07+Lu/+zsuuuiTXHvtF/B6fW2t1SqWL3+U//2//7koHtbD1KnT6O2dxHHHnUA6\nnWZwcNDMCdrBETu3y4AuHuXC6dTncDkcUhm5rtl79TYIQ8zKjSxLJBLpmg2pTqej5uwo63oej8vM\nX6TT9p6E+roFs8XB59OJhfF4dZ7K5VJM3WHDbs6aNZt0OkMymWT+/OOZPXs2oVCAN9/cQCAQIB6P\ns2fPbt5++x0SiQThcJidO3cyMDBAT08PkqQTDd999x00DbPzPBAIIIoiiuLE4VCYPXsWiuIkk8lw\n3nnnVzFdE4kE+/btw+/3M2bMGK655vMsXXoahUKB//f//i+y7CCZTCDLEqFQiEsuuZRUKonD4TDX\nMkIrgyckiiIHD+5nyZKlyLLMrl27kCSZU045hZtuuom+vj78fg+qqtnmB1nh8biIRGL4fB48Hhf5\nfKHlfJzH4y4KlyXNEApoORTz+dwkEmlmzZrNxz9+MevWrcXj8dLba9+zOxSMHTuW448/galTp+N0\nOhkYOMhbb23gpZde4Le/vRun08mCBYvMeV0Gjrq5XVbowwH1sETTFNuCTIbn4/G4mnbBW49v5KkY\nIZbX62qpjC9JQnE2fHVy3EoUTCZThEJ+MpksyWRp0F13dzc//ent7N27h97eXv7hH77NsmWX8cQT\nT7B161bGjRvP8PAwkUiEffv2mWvn84ViyKd7Qw6Hg97eXnw+HzNmzORv//abrFu3jsceewRJktA0\njQkTJtacWHn99dczbtwYtm/fQU9PD5/73GeRJJmRkQi5XJ7u7m6z+nXCCSdy/fVf4I47fsa2bdvM\nNbLZbBmpzwiLRFFkyZIlLFy4yAwldQ7RaLEKaW+euhVGqGvkXlwuhWDQX2Rm259kYaxjCJlJUro4\nOjpcVs1qBmu1q6dnDDff/E1b73u/EAyGmio2QPN5XQaOeM9HZ9WWbhKHQy4mAZsbH6fTgaLI5PMF\nWyxnRaleu56n4nDIxQ3d/Cmqc34cZLM5ksny4XPWEAswE876eT1omv7aD37wfTZt2oimaYyMjPDe\ne5v41re+zZlnnsXq1asJhUKoaqFY6XLS1zeZQMCPquoiZhdffCmqWiCbzSAI4HS6uPHGG5k5cxYz\nZ840S+uTJvVx/fVfKDM+DodMIOArqjFOY8GChQSDQX7zm9+ybt1rzJ07h6GhQXbv3m2S5z75ycuY\nOHEi2WyWd999x9x4c+bMZcGChWzbttWcBnrcccczeXKf+V5R1JsavV4PyaSu1ZRKZVBVlUDAV6zk\nFZqGPpWd6JVTUo3zN4ugfD532YNAb23JksvlTY+qUGh8LxgPQaOKKQjSB04yNMJcVVXN/1dVtWhY\n68/oOqo9HztcHyus7GTAll5w6Tz62vU64C1HN72OUgmfqm583dtRi3mdcsa0pmkkEqli9cZT1AVO\nmDcJQCSiaxL39PTQ19fHgQMHGD9+Am63hzPOOJ1Pf/pPmThxIq++uoaxY8dy7LHzOXDgAA88cB+q\nqnLOOWezaNFi0ml9oudFF13MRRddXHb9oijg9XqKoWrK9DiGhob4wQ9+QDKp85hee20t3/ve95kz\nZ2vU9H8AACAASURBVA779x8gkUiwY8d2nE4nS5eeitPpYvPmTYTDYc4773wkScLv97Nnz266u7vL\n+smMDnxJkqtIeSWmdImZXE8r2bj+Wg+pWlNSG2lBG7O2KmH1qAIBX/EhV7t9pPpaPvhqlyAItr0a\nOzgqjI8Vjfq7ytnJaXK5AqGQ/WSekWexq9NT7way8o/i8TQul8M81hpi2aECSJJIoVDguOOO4513\n3gEEVLXAvHlzAd1F/ta3vs2vfnUXqVSKxYsXc+GFnzDXOOecc81/jxs3jq997SZAr3o4nYopxF6Z\nv3C5nHg8LtLpTNUAwNWrV5NIlKZlRKMxXnrpRS644OP85jf3sHXrFlRVY82aV7jiik+zePFiFixY\nULbGpEmTmDSpOtdhkBSdTqXIjRHMdo0SU7pkPOqPam7M8bGSC2tNW60+vubLgL0+L2vIdbjaKlas\neIxCoYDP58fjceN2e/B4PHg8XhRFoauru/kiFhx1xqfehq2ne2xl1jaD3hbhqlkJq30d1a/XMlya\nZrQaWKtY0Mh4eb16cjweT5LL5bn22i/gdLrYuXMH48dP4JprrjWPHzduHH/913/T9PNZUSgUGB2N\nmxMi8vkCiUTKnA5hjL2pFUqEQkFUVTU1XzRNIxTqIp8vsH79hmJDr4wsS7z11gYWL15s65oUxYHX\n6yGbzTEyEjVZ53oOTizzHOwYDzu/e71pq4aX14qCYaM+L2tfl3FtHzS2b99GMpko8sny5nVJkgxo\n3HTTX3V6uyphDbsquTvW1opaBsOO8dEbQHXRrWYyptZ1rTGyMf44l6u+DsNQ6VrAjZtS3W4XbreT\nVKrc4xBFkauv/lxZ+0IymWpb1MpANpsjm80VtZQDxQbOREPu06mnnsb69W+wZs2rgMbpp5/OwoUL\nAYoTU3NkMlkkSW8zCASMZtTaORFDlF4UBWKxeFXYYojZ1yIpVhoPj8dltlm0QjCspwWtaUaTrD3U\nU2U0BgjoODyez1VXXUM6nTL7AmOxKIlEokhWHWjJ8MARPrfLQK35XalU1gxtUqlM3TKsz+cmna49\n491KNkylssXGUtH2TClZFslkckX+kVBMjlq737Vi/kLA7/ea3kWtUq+RYG50jBX6xtYbZ2uFTa3A\n6dTnj2cyWVOGxJBTrQcj8S0IAuFwadTvmjWreeihh8hms3R3d/PFL36ZyZP78HhcVRU8sBrbtO3c\nnNE5X68q6fd7TflUSRKr1ADswONx4fV6yOVyiKJYc+6XHVinv2YyOUZHYxzOeV0A69e/wTPPPEFf\n3xR8Ph/jxo1HlmWOP/7EmsfXm9t11Bkfo9tbELDFTrbOwrLCIBtms3nSab0Z0zAodhQKdY9LKRq/\nbFX5tzrEKm00nbOTLn62UlI3Hk+1LBuqhypu20bLCt2AeQCKIl2F4uu6kLzRVNqqYYvH4wwPDzN+\n/HhTMN+o9jidCqmUnsD3ej0UCq1fN5QMu7Vp1Qqv143X6zEF3NshBQqCQDCoqykaPJ82uYWEQn4c\nDgerVq1CVWHevOPbW+gQsWfPbm677VYmTuxl5coX6eubwsaN7zB//nH85Cc/r1n1OuqHBkLJYABN\nWysMWEM2KGns6O5xqspTsROL6yGWC9CqQqxKo2NdLpVKk8nooljhcJBcLoeiOKpCrFZgDZtCIT/p\ndJZUqloWwgq9H81tSnJUhm6Fgt6dbeSDdJ6VfQVBn8+Hz1ee6C9V8LIEAt6ih5luW5DdKMsLgoqm\nCVVGKJFImV7cmDHh4tjs1uRcjZI6aOZ4ZbvTVmutFYsliMcTfO97/4t5847l61+/uWzI4x8Txndz\n8OABuru7ufXW2/j5z/+T66//Ek8+uYItWza3vOYRPavdgCTpUhelccmC7SdQScZUf/L6fO5iNaKa\n99PM+BjXoT+9MyZHwniv/t9qsTJTew1V1UwGs6LoWjjtiKRXIpVKE4lEEUWBcDho6jxXQlEchEJB\nBEFgZCTaMGdkJH6N3q5W9JFqwelUzLHDhnELBn3IcnOx8nrQQxjRrAyW/00gnc4wNDSKosj09ITN\n3jm7MAito6NxRkZiuN0uurtDKEprYZNR7TrxxAX8+tf3MWfOMbzzzlstrXEoMO7TWCyGLDsYGRkm\nl8uxefMmxo8fz86dO8qOs4OjxvMxSF1gT0XQgKZpyLJcpbFT79ham6syN5TN5oo3un4D2q9iVfNm\njARnNpuzLQ1aD6qqJztlWcLr9eB2O4nHUyZd3hgBo0uZ2g+ljN4uvZQcaJoPqoTe2qLLvo6Oxs3w\nLhKJ4XQq+P0+crlcUa+5vc9fKyltJJyN6aaG9o8hl2EnnLQmrfN5+9NWq6+vVGp3Ol187nPXtvU5\n24URSs2bdwxvv/1mUemyj9/85lcEAkFzdlcrOCqMTz6vllUc7JbPZVnC6dQNhB2NnUaNqJVd9Max\nqlqoGWJVwu124nZX82YymSzZbBa32004HGgp8VoP+XyB0VFjs3nMytyhrF1JfCzxgxp7bR6Pu8gy\nrl2ZK31+F6FQoCwf1g5KY55VZFmf2mGgmfZP7fXEqjaMymmr2Wy22GDcaB1ryf7wCYm53R7OOed8\nJk7spVDI89prr5LNZvjTP726eJ32g6mjwvhUopnxseo4ZzK5opqenS74kgEpH8dcnRvK53VvR28W\nrP/EdjhkvF59nnokEqt5HZpGcXNm8PncuFxOk99zKKj8ft4PbomRDyp9LmfNfJBRvcvlCk0Tvvrn\nT5cR9ZLJVMsjbgxY+ULGd2h9sNTT/ql1jaIokM/XvvZG01ar1zm84vEbN75LLpfliSeWM3/+cYwZ\nM4ZCocCtt97G888/SyQywvjxE1q6R44K41P5Wxos51q/ZSXZUJYl2zmFUiOq0xyTU9mIag2xRkai\neDz6EzuV0udiGajXmtAIugxnosxgtZLorXVuw4jpHfnuQ97YBnK5PJFIFJfLSTDoJ5PRwyZBoOrc\ndqGqalXY2AqNwPjckiQRjyeKn1tsmJQub7Oo1l1upgdk5fVYZWGt90L1g/KD93yGh4d45ZWVrFjx\nKP39m3jrrQ1omobP52f16pf5+tf/EihNJ7GDo6LUDiBJJa+kVvncKriuJ4O14vvEIvEs2fQciuLA\n43GSyeTM8ruBWqVzA1ZGciKRKg4GdB1yCGG0ONTixzR7T71zGxsbIJFItiVTUQkjme9yOYsVokP7\n3AZaoRE0+9xA8Z7QahoTvd/MiyxLZYL0XV3BlmZ8GbweSRKJxZJFsqVIOBxkcHAEAFFUPnCGcyaj\nS7I88cRjzJt3LG63m+3bt5HJZJg4sZf584/H6aytNX5U83yg3PgYkqOZTK7Yz+WqElw3oCsfehom\nmq3ld52UVnLBS4qCuvFp9NRyuZymFGs7EzZrwcpoTiTqeyy6aLneFmHHWzImeB5qorfy3KB/n3a9\nPTsw8mW1jHCJq6TZHihoeEC19o6RlDZK44GAj9HRWMtG2rpOKpXG7XYxPDxarLw6Dlt/Vz6f5/HH\nHyGXy3LFFZ9h69Z+pk9vPC++nvE5KkrtlTBcZ53NqrOC9c1efYM0Kp8bIZa1/G493iidN6PF6/1Q\nXnMyZzKZJhDwHnJp2rj+eDzJ6Ggcl0shFPKXdSYLgt6L5ff7SCbTRKNxWxswk8kyMjKKqqqEQoEi\nb6k1CMVJG4GAj1QqQzQaJxqNE48n8Xj01+3M/G6GVCrDyEgUEAiHA7hc+hPa43ETDPpIpzPFKpq9\n8FQUBfN/UJ4bM5LSqVSaUMhfrGq2/hta1zE8IYMKcDjndd1xx0/YvXsXP/vZ7QwODvLjH/+Q5557\nuq21jhrjY31IiaJueAwvpZ38hdPpIBDQ9XJGRxNmbkc/j1asYhmd5/XX0SsnAVS1YHJi0ml9s+it\nB4G6nJtWYDSC6j1DXvx+Ly6Xs9iPpRGJjLblaSSTaSKRGLIsEQ4HbPNXKvlC1t/AyAdls1mCQR8+\nn+d9McKJRJLRUb08390dQpalqnPbha4bJJYZBasRSqUyxTBJoKsr0PZnMAikhYLKO++8yZ133kE0\nGm15nfcD2WyWV199hWuuuZ4pU6bS0/P/t3fe8VHV6f5/T01mMjNpkEIooQYEVECKLjZs1y6CDRRd\nsaAra9tVf666eFV23dVddVddr3ItrF1UbLgKwsUCCEqHkADSQtqQ6SVTf3+cOdOSmcxMBkLIeb9e\n/AEkJ9+ZyXnOUz9PL2bPvpXXXnslo+v1GOMD4gCiBqVSGcoDpJYHifZmhNhei0qlxGZzxZSexUZB\ntVqVtFEQBCmLggLhZjWbbW3yDLEei5CU7UwznYjYoKdUKsPzWEKFJfNrBgJCv4rN5kSrzU16Vrlc\njsGgC/XK2JPq6bjdHkwmK4FAkMJCAxpNavvLEiF4qqIapCuscNgZ70o0Qu01KYrVT6PRhFwudDiL\nFdB0EAeW+/Tph8ViZsaMaSxd+p+Mz5wpVquFnJwcdDodKpXwkOnXb0A4wZxuj1mPyfloNCq0WnVY\nNzk3V43dnlq7vMGgxeFoJSdHhUqlwOlsu+JGTCiDEEqoVCocDmcbb0LMwST6/0RE51gybSaMHosQ\nq0DRie5s5VjEQdP4xsdMhkBF4pPy6Z5VPJPb7YkZk/B6W/F6PSGBe314lixTopPScrmM4uJCmptb\ngPaTyamg1+fh9wsqijKZgj179nLokJHx4yd26qzp4nDYWbToPX7+eR179+7httvmsmHDzyiVSu65\n5/6Ela4en3BWKoUdWWLDnE6Xi9XacQULBOMjk7Uvl5GoiqVUCvKpogcjGLyOKyrJEITKhKpQujew\n2LvSnvGKPasrZW3ijs+qCQnae1GplAQCghxtZ/pVhDaC1M8a3R0dPfwKgvSH2+2iT59y1Gp1SBmx\nd6f7o4CwXlF+vg6jMXZvWHQy2WptKwEST36+LlxBlckUyOVd2yGzaNF77NpVi8Vipk+fvtxyy+1h\nT6g9erzxiZ5sT6WCBRE51fYmz1OtYokGBwiFeun33bR9LUL4KPSjJO+Fida6sduTl8Yj0hje0M7x\nzn38QjJbg1qtDhvhw+FdJaq2ieX7ROMcDQ319O/fHxBmltxuNxCkpKSEvXv3IZcLa4VSwWQyYTQa\n8fm8FBYWodHkUFpaQjAow2y20tzcTE6OGp/PS35+Ibm5gheo0wnNjMk6nAsLDWFvTy5XIpN1PvxO\nl40b1/PBB+9SWlrG5ZdfQZ8+qe8Mk6pdUXQ0ACqERrnk5eXicnnaDbFSqWIJmrcKgiERd6FhsfNP\nLbGZ0G53kpenDU95xyM0MOrxeLyYzR2Xe4UKlhUIxlSFMiEnR01hoYFAIEhLixmbzRGuLmWjgpWs\n2qZSKSksNIQWD1qTzpH5/X5aWg6h1WrQ6fKord3Jrl27GD58GGVlvamr29/hWZqbm3E4bAwZMihU\nPPBSVlZGTc1OGhoa2Lv3FxwOG263E6vVEr6mkJQ24/cH6NWrIGFSuqu7m5ct+5qFC1+loqIvJlML\nr732CvX1BwE65SX3GOMT/xBPZIDEKpawe9sR3sMlLuNLp4ol3nwmkwWr1Z715LFYFfJ6fRQUCLq6\nMll6N1884gyWONtVUGAI7+NOBYVCTn6+jtzcHCwWeziZLZ61tTWbFaz4als+BoNwbYfDhc3mSNp/\nVFJSSk1NTahXyUlLi4mKigp69+6NyyUMw/p8XpqaGpLOoJnNJiorK3G5nOTn56NSqVi3bh1qtZr6\n+oMYjU1MmHASI0eOZPz48THrm0WP0Gg0h5PS8W0LXT3XtXnzRk48cSxz5tzBvffej9Pp5Kef1gqn\n6cRnKBmfEEqlAoNBrGI5Y4YYhUQaHcpdiNcpKNCjVquwWGwxyU2h3G3D7W5Fr8/ODQiRPhaFQk5R\nUQF6fR52u7PDmy8Z4gyWw+FCp0vsXUUjVrpExb32nopiBSsYzE4FC4TPx+PxIpMJ77+47qcj5HI5\n5eV9cLlcKJUq+vbtG/48rFYzBoMBnU5PZWUldrslbNwBnE4n9fUHqa8/iM1mY+/ePWzYsCEcrg4Y\n0J9evYopKCiktdUbrnwJuTBtSLnSgdHYhNHYHJLxtWMyCdssevUqCA81d7XnY7NZ6d+/EgCtNg+N\nRhPO8XTmXD3G+ECsARKrEWKIJayX8YQSorHiXh6PJ6zxK+6EiiedZr3WVg9msyV8A3YmvBHJzVWj\nUilxu1vx+wNotZoseVeCJk+8dxVNtKclaPwk97SivSuVSpVWf1A8YuleoxE8rZYWS4xxT7SpRESr\n1eL1+sI3k91uZ8+ePbhcbqxWKy6XO6SZ5A9rHclkQWw2K5WVlVRVDcXjEVo2JkyYiM/nZffu3RQW\nFmE2mxgyZDAKhQyLRQg9zWYzgUAwtMooQEVFX8rKymhsbACE8NxksmKzOdDr88J9WBGOvOfjcNgZ\nMKAy/Hefz0dV1Qgg9QWB7dFjEs7Qdr4rGASVShGqJMSWPZPJmMYPgUaqWB2rALY9U+ckR4VKlTY8\nVBnRfGm/3N0ZotsEhD1i3oyHQKPJdBBW/DwSJZTFhHNH1cVgMEhDQz2BQACXy0VhYSEHDuyjtLSM\n/Px8CgoK2b17FxUV/UKhbAsDBgiJap/Pz549e/D7/Xg8Hvr0KWf16tWMHTsOr9dLQUEBGzZsAORo\ntRqcThfDhg3DYrFQUdEnXLgwmUyAHI1GE3O2vDwNOp0Wm82B0diCTldwxDucp0+/GJlMTr9+/Sgq\nKmbFimVceOEljB59Amp1DpMmnZK0RaHHV7sgYnyE4UgNwWCgjafTURUrut/E5WolN1ed8jxUMmKH\nIJ0dhkup9AvFyp2mJ+CVDLFfRS6Xh3dMZYNUB2GFWbC8lEr3wjS+EE7HT+MfPFiHz+dHp9NRVFQE\nCBWwAQMG4PV6qaur49AhY0hQTsXAgYPQaDTU1x8gLy8PrTYPq9WC0XiIkpIS8vPz8Xo9rFy5kr59\n+6JUqsjNzUWlymlTNWtqaozZO2Y0GsnJyUWhUMakBESPe9u27dxyy01MnXoFM2bMQqvVZvw+p8uu\nXTsxGpsxm020tLRgs1kxGpux2aw0NNTz7LP/wmAwJPx+yfgg9Prk5Qk6PT6fkDiOz+0kmjyPRiaT\nhbqcVfh8/lBuJTsxufi0jveuosnNFRoOU/W0OutdRRM9BOr1esnNzc3KcKlItFB8vMEUO5SFIdn0\nyvbx0/i1tTsZMKA/Wq2WpqZGXC43paVlHDxYx8CBAwFwu11s3ryZoUOHUldXh8vlRC6XYzQa0Wg0\nDBgwAKVSyebNmykqKkYmg5qaGg4dauGCC87HbLaQk5NLeXk5Op0+5jytra1YrRZKS0txuVxYLFZK\nSkraTM7n5KjRaHIwm200NTXyyisv09zczHPP/auT7/SRQzI+gMGQGzY4OTmq8JqbVI0ORG584ens\nCvdrZEsGAuKX/kXU/mK3RSRX0GuPzmyqiO+OjvYgUjGY6RJvMAVPT4vH4wkldTO7rtgpXlNTAwh5\nQK1Wi9lspm/ffhw6dIhgMECvXr3YunULpaUlqFRqKir68NNPP1FZOYhfftkV+l5hLbPL5SQvT0dD\nQz2nn346Ho+HNWvW8Ktf/QqLxYrL1UppaWmbs/h8PiwWQVY13jiJk/NCLk+F1WpHXJmT6qKCowWp\nzwew291hT0cwNLKURNshUsXKyVFjsdjCJWRReF2hSG+wMhnirJTQx6MJl48jE9jtbwLtCFHQ3efz\nh5LHqc0ZJRsChcyHS5MhVttcLnfo9efhcDg7PYcm9gft37+fIUMGM2zYEJRKOYcOGQEoLi5Gp9PT\n1NSM3W6jsrIyNIBqQtykajAYGDVqFCUlJYwbN5YDBw5QX3+Qc845h0AggE6nY9CgwVgsNvLydLhc\n7Y/xKJXK8M+LRy6XkZMTeVhEOwndyfAko0coGbaH3+9Hq81BqVTg9QZI1igYnWRtbx4nEBC0W8TE\nqShj2tlQzOv14XK5Q9IaynDvSWeJrODRUliYnzCEiRWNTz4GIBrM6Pegs3kwUYdH8CiD6HTatITR\nEuHxeNDpdOzbtx+dTpib0usjBkBIPDvQ6XSsXbsWs9lCSUnv8OCwMESqwGazUVtbS35+Pna7A7lc\naCIVROeFhYM7d+6kf/8BaZ9R0GBS43BEBMWyUTQ4muhRng+I2yr9oZZ2B3l5mnDyNJ7cXHWM5ERH\nN36k6c+blmfRHgpFpIQs9n+Ipd7seFdB7HZHqPM4t03nsbjHy+v1YjZbUxbDishhZL4uR/QyVSph\n4l+cY4vV5Ml8AFQmk+Hz+SgpEUIqrVaY/Soo0BMMBjl0qJkxY06kvLwcs9kCBDEajbS0tLBt2zb2\n799PY2MjarUatVqN2WylX79+rFy5ktzcXBoaGlizZi11dXUMHFhJ797FHZb8RcS2BZlMFn4fQY5M\npuzSLaWHgx6V85HJAkDbKlZ8CT2SnMx80DJSZUl/CjvZTJI4BJqNCls0Yi5LWBGsyMoQaLLkcftf\nnzivFI1CIVQrU0mgOxwOjMZmQAipWlpM2O1W7HY7w4ePQK/XUV/fgMvlZPTo0ZhMLSiVynAflkaj\nCSV9taxfv55AwI/P58Pv91NQUIjH00pRUS/Ky/vQ2NjIxo3r0Wp1TJ48OXyGVEr+EQ9bGdO2EAzK\nEHyE7htqSQlnQDA6QSCATBZrgETxcKHZLJj0lz8d0ulhSafcnok+czIicqtqIJhwVU0mpFJtSzZ1\nn4iOEuhut5umpgaqqqoAWL78G8aMGYtOp6elxUh9fSN9+pSTn19AU1MDQ4YMoaZmJ36/l/z8fIqL\ne2GxmHE4nPTr148dO6ppaTERCPg54YQT0Gp1bN26lcLCIvLz85OeVRTgby98j2zLiCTTBaMT/af7\nIq1LBqI/TLGPR4wIVCoVKpUSr9eLUqlArVbh9fqykreJ3tIQrycDkepWKlPqIpFFfJrw1HOmxjIy\nze7BZDIjlwuehZC7cnVaSzp+fXK0sYjeGJHuMsKOVj03NjZSVTUs/PVil65SqUSrzcPr9SCTyWls\nrKeioh/19U3s3LkLpVKO3x+gqamJsrIyPB4Pu3btwu8P4nK5GDNmDE1NRuTyFhwOB5WVAzs8a+xC\nRk1os4Y7pKipiMmpHQveTir0uJyPgAxQAHK2b69m7tzfsGHDeiwWOzabI6YilIk2cXuI0qjxeRvx\nxvH5/OEh0VSJSINmNrCaaAhUnDMSJFe1oZxY52+E+GqbwaCjoMAQ2ghqzdjIuVzumPdWlJ0VGkEj\nYU5raysymfArr9cbyM/Pp6iogLKyPpjNFnbv3klpaQklJSVYrdZQ+bwJs9mE3W5DqVRSUdEXs9lC\n3759UauVFBYWpnVWYSGjHa/Xh8GQF2N4gkEZwaAc4Xfz2DY80OPCrljeemsh77yzkNtvn8u5556H\nQhHr4kZ7JJ1tzotG7BCWyeT4fL6sVMYgPbXDjrRu2vvabPXxiP1KouxotkLc6GvLZMKyxurqakpL\nS5DJZGzduo2Kij5UVJTT0tKCSqXGYCgAYOvWLZSU9GLQoMHYbDY2bdqI3x/EYMhn8ODBMSFeQ0MT\nhw4dwmAwUFBQkNb5xAqiTCboK6lUCq6++irGjBnH9dfPJj8/PWPWHZByPu2wd+8eCguLQq3hQi4o\nOhQTUalU6HSpjz4kIzqx6PH4QgsKO9c4F3v95CMV4ibQdF9LZ2VMRcT1x6LBORx7wCA2H1Rf34Df\nH6CoqAilUo7JZEKlyolR31u7dg1TppyJ+PAxGo3U1u5k1KjRMddNtoanI8Q8XbQKpSA2ZmHBgpdZ\nvvxr3njjXYqKijv/BhxFSMYnZcRqWFsjFPEAMttZHj2AKuZ9UukjyoT4JK/f7+/SIdDI+mNfu15Z\nNjSq20OsZPr9gfA+sPbe4127aiktLaWsrBS/P8COHTXodPrwzFc00bvQUvEcI1KuwRjFQiHEinjb\nJlMLBQWFx0wToYhkfNIiWVUs0niXaigmzkNF6zln8jWZICZ5ZTIZbncrDkdqovkdkWq1TZQaScXo\nRes+Z2rg4xGNXugnJDTwra2t7N27h9LSUnw+LyaThSFDki/DS6XkH5m8j1QPe0pCWUQyPhmR2AtK\npSwuDkLm5CTfFhpN7OxY50ro0ds4fT4/OTnqrM5fdfT6Ihsj0pt7y0aI117fjBjiHTx4kJYWYZ1N\nRUVkstzn89HY2IBKpU5Zuxkivwt+f8QbjJ28d4ZmtY6d8nk6SManU6QfikWXr9M1IqmuOE78/e03\n68UOrGYvgR498OpwCHu4Ihsj0h+AFck0xBO9vfZyafv376esrITS0hKsVhu7du2OEcrqDKI3KI5g\nRAvm9zRvJxqpz6dTyBGNjzCAGgnFhJjfg06nJScnB5fLFVImlKW0FqU9xNBLfFKLs2KpdFpHN+uJ\ncqUi8fNX2ehihog8bE6OGoNBj0wGTqer02FTfI9UR4ZcXDstl8uTvPcBDAYDLpcbrVZoI9BocrPi\nDfr94gCoDI/Hw9KlSzn55MkolSp6mreTCj20zycTxCeXnGBQHifJGgjJpvpDT/zMDU80Qk+IoPmc\nn69LOicVuwnUkXQTaFvh+c73MqlUSrRaQdvH7W4N5zqygdgjlWyuS1w7Lb62RO99tKH1er1hI9+Z\nmTkxr6XTabHbnZjNVkwmC59++gmzZs1g1apVSIanLVLYlTFCKBYMBti2bQvjx58U6gdyodHkpNxD\nkyrRc1LxoZhY/s1sE2ik7T9dgS7xXGJuJTo/c3hDPE2oT8ZFMBgIV5JSSdQ3Nzfj9Qpyp83Nzfj9\nAcrKyqMWJ6ZX8k82GhEMwurVP/DZZ4t57LEnOxTgP1aRcj6Hgbq6/TzzzFM0NtbzwgsvotdH5nsi\npe6Ol/WlQ3R+RfQw4vWbMyGTgdXovFaiKlq2QzyR6Cqew+FKy8i7XC7MZhN6vQGdThfzf6mW/EVv\nRxyJEbuze3JuJxGS8TkMPPzwAwwbNpyrr74mtNsqUVUsvYHJjhA2ruahVCrxen3YbI6s9cWkGVGW\nMwAAF/dJREFUUkKP3oJqs6WWixK9s0xE9uNRKpXo9UKjpN/vT0kkPh1iS/5tq4PtVfF6aiUrFSTj\nc0QQO6TbipOJnb2dDcWivQ2Xy41GI0pWZG8KPVkJvaONER1dtzMNlYlE86NF4jMJHRMRX/IXxObb\nGl3J20mOZHyOGIkbFDsTigldslpA1qbyJeZBQJbVEYXYEM+NRqOJ6VvJlExGKtrLrbR3XaFRk5Sr\ng6kgNCoKw7VutxuHI97b6Zm5nFSRjM8Rp6MGxdRDsVSHQA/HiIKwqSMvJDeS3RAvld1i0ZIbdrsj\nJUOVzZ1l0aMRHo+PTZs28MUXS7j22uspKuqN5O10jCQgf8QRpRHkoSdk5AbweLxxG0vblwRNd+d6\ntjehirva/X4/JpMZv9+ftQ2r4nlNpsTnFcvnotxIqh5d/HUzLflrNOL651YsFkHMvk+fAahUaq67\n7hqWLPk8o+tKCEiezxEhOhSL/Z/ocEoMQdKZh0qEeF1RuiGdUCx6fi3e28jmDrD484rXFRo1hd6j\nznRIZ3re6N1kdntk3330IOi+fXuprz/IxIknZ3y2noIUdh0VJA7FxJApEBCmr7NVvUk3xEu1Zyjd\nDaupotdrUavVIUGz7C1jTHVUI17yA6SEcmeRjM9RhSBkH52QFpO7crks3LuSLXmN6NJxorxR7NM+\n9Z6hbAmNiYOYfr9gzHJycrK+jBESl/yjdY7E7nCpfJ4dJONz1CF4QA6HjUWL3mXq1Kn07l0a2tEU\nO6iZvepVJAQRG+NS3RiRjM50M4s/X9xRFV0mP1wl9Fg9HhcKhbLNCmbJ28keUsL5qEPGqlWruO66\na2hsbEKpzA3f+OKgptvdisGgIy9PmxWBKVHI3el0odfnkZ+vS7qJNFViN6xqMRja34MWT/Qm1MiO\nqujrJt8tlini4K7T6SYvT0tOjgq73Y7H443SUZYMz+FG8ny6kPfff4ehQ4dx4oljaS8Ug+QzXZkS\nWRMkiBpkS7hLJBLatB8yxZbPI6MJHZEtraP4hL5MJuPBBx9AJpNz6613UFpantF1JdpHCru6Bcmq\nYpFQrDMNdBEdYSFHk4kyYyokGljNVGBMJHYRYfpd3ZGfH5GyDQZluFxu3nzzDT766AP++tdnOe64\nUWmfTaJ9JOPTrUheFctEpCxa1bC96e/DVb2KnhYXN8V2tnwO8d3iHe8Wi2j9xLYexOd2WloOkZeX\nR05OdlYmSUjGp5uSLBRLXZ61vfJx4q/tnEh+e0S0fWS0trZmZcOqSCpGM97bA2kQ9EgiGZ9uS+KV\nPtEzUu2FYh1tjEiEEIppkMs7t68somMcwG53EAySltFMh/ZK/rHzcBFvS6pkHVkk49PtSRyKxSZi\nXUDnO6Qhfl9Z6lo80eX7aB1jkcPVShBd8vd6fW1W23S3QVCfz4dS2f2VjiXjc0yQeGI+uncFyGpz\nnhg2pdJIKBqsVLytwzEIq1AoMBiEbbBut4v9+w9QXNy7zY6soxmr1YLBEBGms9ls6PX6LjxR55D6\nfI4JxKe2oo2OtFwuQ6FQEAgECASCqFTK8DrizuJyuTGbbSGtY0O4RB9zstD0u06nwW53JtWQFsn2\nIKzYC+R0umlpMbN79x6uv34Wzz77LDabg+5geABmzryCL774FIDHHnuYBx64h0WL3sVms3XxybKL\n5PlEYTab09693bUEaG118dZbC+nbt4JLLrk0XHqOVSTMzipmiF+3LIRi7ZWv0yXd6lU0QkVNi9/v\njzF6waAck8nMyy+/yP79+/jHP17K6GxHArPZTE1NNRMmTGLZsq+YP/9RLr74MgoKCunfv5LVq79n\nwIBKZs68vquPmjaJPB/FvHnzEn6T0+lJ/J/HGA0N9cyadTV1dQcYN25Ct4i1d+7cyW9/extKpZLL\nL78itHtc+Jx9Pj9utyc8WBoIBLKyBTUQCOB2t6JQKNDrhbU+CoUCm82Bx5N5AjkYDNLa6iEQCKLT\nCQ2QPp8vqdGUySAvT4NWqwmt6omuZAlyJhqNhl/96jQuuODijM92JKivP8g999zBpEm/Yty48Vgs\nZpYu/Yr58//K4MFD8Pl8rF//MwUFBZSVda8myLy8nEfb+3cp7Arx73+/xtixJ1FSUsodd9zCZ58t\n7uojdUgwGODuu+/j0Uf/TGFhrzahmDhGYLPZ0WpzMRh0WQvFRH2iYDAYCvmyc12PR9g35vf7KSgw\noNG032+jUinbjGZ0x9EIMYk/cOAgjj/+BG68cSbffvt/3H77nbjdbr7/fiUAI0aMZNCgwXz66Uc4\nnc6uPHLWOPof70eAtWvXsHbtGl55ZSF6vZ4zzzybxx9/BK/Xy9Sp07v6eAkZOrQq6m/izR8IhR2R\nqpggxmULL9/rTHgUPf1uNtsIBAJhuQpxuWE2ZDDEZYx5eRoKCw3hql3sGmRHuJLX3crnfr8fhUKB\nXC7HZrNRU1PNqFHHs2NHNU6nA6VSyT333Mf8+Y9y2mlnUlZWznHHjcJms2G1WtBqtR3/kKOcHp/z\naW1t5d5751JVNYK5c+8O//tbby3EarUwZ84dBIPBrAx2Hjk6roplsqcrLy/59HtHM12ZIuaZAoFg\nSOsodjSiOzcLfvzxB3z77Up0Oh1/+MM8du/eyZw5N/LRR0soLCzkzjtvQ6VS8dRTz3Xb0rtU7UrA\nxx9/wP79e9m4cT2vvvoyALW1O9ixYxtWqwUQbthgMJg1YavDT+LtqpFQzIFWq0kpFBPlXDuafne5\nWjGbrcjlQlUs0w2g8fj9wooccVJ+w4afQ1o8kdfZHQxPJBEepLW1lSeffJzVq3/gggsuoqGhno8/\n/oDhw4/j7LPP44kn/gjA44//hebmZmw2W/j1Z6s7vKvp0canru4Aixd/yDPPvMgrr7zBgQP7ufHG\nmbz00vP4/X7mzLkDgP379yGTyZDL5d3IAEG8jnT076zP5wvnSvLz21+ZHL8GOJXyuSiDYbc7UzZu\nycjNVYfWIPsxmSyYzVb+85+vmDnzGpYtW5q1Kt7hRHxwid6zTCbD6/Vy8GAdv//9g5x11rncdNMc\nGhsb2LDhZx566FEaGho477zTqas7wOuvv41erw8bn+7lhSemR4ddb7/9bzZtWs+f/vR0+N9qa2vI\nycmhvLwPK1cuZ82aVTQ01FNR0Zfbb78z3OzV/Rq/EodikQn0yMrjVLaRpoJY8k83zySXy9HrE49G\nbNiwnhdf/Af33fcHBg8ekvH5DjeBQCBsNKqrt7F69Q+cfPJkysv78M9//p3Jk0/ntNPOAODRRx8i\nEAjw+98/iMfTisvloqKib5vrdDekDucEiHG01+sNlaoFNm/eyMMPP8BJJ03goYceZeHCV3E4HGFv\n6J13/k1+fgFnnHEWGo2mq46fAYnHNMTEsVwuC69gzsboQ7p5JjF31P5oRHfN7Szis88WU1k5kOrq\nbTzwwCN8881XGAz5TJx4MiNGjOSFF56jpqaayy+/MmyQurPREZGMTwLik8nih/3HPz6IXm8AhJ3s\np556Blu3bubXv76Z119fQFNTE3Pm/IYRI0Z21dE7SdvtquJN7/X6UKmUWU8cR1fK2hNxF3uH4nWk\nu2slC8Dj8fD555/wyScf8uSTf6ekpJSnnvozBoOBMWPGsXnzRn7+eR1yuZx+/fqj1xvwej3MnXtP\nF7+K7CElnBMQHz+Lq1vq6w9y7bU38LvfPcDMmdfz6acfoVQqqajoy4ED+9izZxeHDhljvjdbGzKP\nDGJCWkFNTS0PPng/LpcLs9mGzebAbLaiUGQ3cSyW/MU8U16eJux9iaMRLlcrVqudQCAQ1bejoDsY\nHtFYKhQK/H4/jY0NqFQqBg4chFKpYsWKbwCYPfsWtm/fisnUwsyZ13Pnnfdy/vkX8fvfP4jT6aCs\nrM8xk1ROhtTh3A4qlYq6ugN8//1KqqqGo1KpuOiiyzjvvPP54IN30en03HvvA2g0WpqaGti0aSMD\nBw5CLpfHVGWOfmS8+uorPPPM01xxxVUMHjyMSPOg0PDn9/vJy9OiVivxev1ZuSmiu691Om14R5fV\nao8S+RKrWEf/e2m321Gr1WGvedWq73jwwfuorz/IypXLGTduPIWFRWzbtoX+/SspL+8DCDK6Eyee\njN8fYMOGn/nHP/5O//6V3HDDTcdMUhkSdzj3+LArEV6vl5deep4ff1xFSUkp06ZdSUFBIe+88yan\nnXYGZ511LsuWfcUvv+ympmYHTqeDO++8N9z4t2bNKkaMOC5mOvloZPHiDzn11NMpKiqmvVBMJNs9\nPNFbKyDI9u3bcbs9DBgwiO4UYjmdTi64YAovvriAESNGsmNHNQsWvMQ999yP02nnxhuvZf78pygv\n78OXX35OMBjg9tvvBGDLlk2MGnU8IFRe/X4//fsP6MqXc1iQcj4ZYjQa6dWrFwAvv/wiubm5XHfd\nrzl4sA4Ah8PO0KFVLFnyGevX/8SDD/6R7du38sEH7zJixHFMn351Vx4/A5JXxfLysqET1FbkbN26\ntcyb9whnnXUus2fP6RaVRDG38/LLL7J8+VLeemsR27dv5dtv/49AIMBPP/3INdfMYsiQIeTmati9\nexeLFy9ixoxZjB59Qvg63a+JNT2knE+GiIantbUVk6mFuroDGI1Gbr55Fi+99Dxff/0f/ud/XmDZ\nsq/CBunHH1dTXFzMySdPBrpbU1jiBsVAIBhekaPTadHrU1uRE75ygr6hYFDGuHGTWLjwfTweD199\n9UXWX1U2MRqbY/5+8823AfDGG/9LUVExX3/9JTablWeffZEpU87m+eefZcWKbxg79iTuuOPuGMMD\nx07fTrpInk8auN1u1q1bg9PpYsWKZcyf/1fcbjfbt2/lt7+dw5tvvo/VauWzzxYzadIpnHHGWTHf\n3z3Lpu3rSEN6ImNifie6b6i7lc99Ph8ffvgejY0NXH/9TRgMhnCLxu7dO7nhhhksXvwlCxe+Smtr\nK+eddwF+v5/nnnua++9/mOHDR4Svdax7O9FIkhpZQKlU0r9/JcXFvfjss49Zteo71Go1//rXPznl\nlFM5//yLeffdNyku7sV5510Y7hvat28ver2hGxoeiDUOsb1BPp+P1lYvublCQ6Lf72/TAS5ujcjJ\nUWOzOdrZf9498juBQACFQoHRaGT//v14PK0MGTIUhUKBz+ejuLgXFouFRYveZd68+VRXb2flyuWs\nXbuGa6/9NWPHnhRzvZ5ieEBKOB8Wli37mq+/XsJPP63j88+Xsnz5UjZt2sD551/MqFGjQyFFkAUL\nXkKv1zN9+tXhwcDu+eRL3qAYERkTtki0t6Oru3k74mcoPjgCgQDvv/82Bw4c4KKLLqWqanjMwOe0\naRcxdep0rr32BqxWKwaDIeZa3e8z7zxSzucwcNZZ5/DII4/z9NNCZ+qaNasYOrSKUaNGA4TL7h6P\nh9zcXBQKBatX/0B9/cHwL2E6in1dT/SsGIhleQCv14fJZMXnE3R4CgoEWVSLxRZneLqPtwOEZ/pq\na2tYuPBVtm7dzKWXTkOhEErqLpcr3CEP8Ic/zOOrr5bg8/nIy8sDIv1fPdHwJEMyPp1Eq9Vy/PEn\nUlJSSlXVcMaPnwgIv3BKpRKTqYXly5dy7rkX8OmnH/PQQ/fx9tsLw98vPjGXLPmsS86fGaKOtKKd\nwc7IPzQ3N7Np06ZuKfIVzcKFr/HEE/Pwer3cccctHDpkZMqUc6ivP8gPP3wHCL1hfr+fsWNP4o03\n3kWpVIa7nLOxX/5YRDI+WaKkpJSrrpoZHgQUf+FWr/6B008/ky1bNrFw4WuMHHl8WIf30UcfYu/e\nPXi9Xn75ZVeXnT0zoqtiMnbv3s2rry5ApVJhNtswm600NTUzb94fefjhP9DU1Ex3MDzxXeoNDfXU\n1u7g6aef44ILLqGwsIh58x7k+ONPZNCgwaxfv46ammog1sh0r273rkEyPocZh8PO1q1bWLlyOVOn\nTuPCCy+hpqaahQtfw+VyUlHRl7/97UluueU3gJAX6E6hWDAoY8GCV5g793b69u2L1WoLj0ZUVAxg\n4cJ3qawcyGuvvdLVR02KmPsUDciBA/txuVzYbDaGDq2ivv4gn3zyIX//+/OYTCbee+8tJk8+HaVS\n2e7nJXk7HdP9ZNG6GT/9tI6cnFxmz76Vffv28f77b2O32zj11DN4/PG/8M9/PkN19TaUSmW4aU0M\nxTZv3timJ+Row+FwYDabefXVt+jduzfBoFjtEkIs8bUf7Yj5mOrqbTz22CP06VPBoUNG5s9/muuu\nu4HXX19ASUkJAwcOYvz4SbzwwnNMmHAyt956RzdTNTh6kKpdRwCPx4Narea222ZTW7uDX//6ZmbO\nvJ6dO2u56abrWLJkOatWfc/atWvYubOGuXPvpry8D1dfPZVXXlnIwIGDuvolHJOIfVei0Nfbb/+b\n3bt3csYZU5g8+XSeeupPuFxOrrjiGu6//25eeGEBq1d/z5Ytmzn99DPDfVw9tYqVKomqXZLncwRQ\nKpV4PB5OPHEsp512Jtdccy0AjzzyAHfd9Ts2b97I+++/xfTpVzNlytksXvwh1dXbmDFjFgMHDuK7\n71bicjk555z/6uJXcuwQLXshltHr6w9SXb2dq66aAcDdd9/H7NnXEQwGmTr1Cp566k8Eg0Eefvi/\nKS4WOt8lw5M5kvE5AsjlctRqNbfe+ptwSfb11xfgdDq57LLpzJlzI7Nm3cikSacgl8tZuXIFMpmc\nCy+8lBdeeJaamh3cfPPtAFRXb4/plJXIDGHXmI3nn3+G3r1LqKjoy113/Y57752L2WwKe6unnDKZ\nLVs2c8MNN8UslRS9JsnwZI6UcD7CiF3PKpWK//f/HsHn81FYWES/fv3DT+Cff17LzJmzUKtVfPXV\nl9TXH6SgoIB1637kiSf+yK5dO7vyJXRL4ndd7du3l7lzb2Xo0GGcdNJEnnhiHjU11Vx00aW8/fab\nLF36H37+eR0//PBdWKZVNDzdSzbl6EXyfLqIGTNmAUI+yOv1UFNTTb9+/fnb355k2LDhTJlyDhs3\nrqeyciDTpl2J0djMjz+uYuLEU8I3Q3ToIJGYBQteorZ2Bzqdnssvv4LjjhtFY2MD06dfyZgxJ/GX\nv8zniiuuprS0jBEjRlJbW8P7779N//4DmD37ljajEdJ7nh0k893FqNVqrrxyBp9//in33Xc3H38s\nSC6YTCYWL17E5MmnceqpZ7BzZy1ffPEpv/yym/feewuQboKOaGxs4LbbZrNv317uuuv39O3bL1xJ\ndLlcPPXUn3n88UeYMeM6fvvbe1m48DU+//wTpk+/CoMhn9NOO5NTTz0DoJttLekeSJ7PUcCECZOY\nMGESixa9y/HHn8DQocN4551/I5PJmTbtKvbt28uKFcu4+uprufLKGdx992+w2WzdooTdlWzfvpWT\nTpoQfp8uuWQqOTk5mM1mTjxxLFOmnEPv3iVMnHgyFouZ2todXHzxZfTuXcJpp53Bxx8vYuTI0ZSV\nlUth1mFAMj5HEdOmXUUwGMTv9/PNN0uZMuVsZDIZS5Z8Ru/eJVx77Q2A0E0tSo9K1ZbEmM0mli37\niksvncaiRe9SX3+Q3bt3olKpmTBhErNm3cg999yBydTC9u1bOeWUU8NtDdOmXUVV1XGUlZV38as4\ndpH6fI5SfvjhO7Zt28LIkaN5440F3HXXfVRVDee77/6P5cuX8l//dSHjx0/q6mMe1VitVv761/ls\n27aF4uJenHnm2RQXF5OXp+Ojj97ngQcexufzYTQ2o1KpqaoaDki5tGwj9fl0M045ZTKnnDKZVau+\nY/ToE6mqGo7NZuP7779l8OBhDB06vKuPeNRjMBh47LE/h6VwRS/RarWwYsUydDo9ubm5Ye8mfsRC\n4vAiBbJHOSefPJnbbpsLCHvlPR4PY8aMDZd9JTrG6XTw7bcrkMlk1NUd4L//+2GUShUymSxG4lYm\nk0kh7BFE8ny6AeINMW7ceCoq+jF48NAuPlH3wmw28cYb/8uXX35ObW0Nl102nRkzruvqY/V4pJyP\nRI/AaDRiNDZRVFRMSUkpIOV2jhTS6hwJiRDiIKkUYh0ZpISzhEQIqWfn6ED6FCQkJLoEyfhISEh0\nCZLxkZCQ6BIk4yMhIdElSMZHQkKiS5CMj4SERJcgGR8JCYkuQTI+EhISXULSDmcJCQmJw4Xk+UhI\nSHQJkvGRkJDoEiTjIyEh0SVIxkdCQqJLkIyPhIRElyAZHwkJiS7h/wP5ibcmERXiywAAAABJRU5E\nrkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a12f97410>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAR8AAADmCAYAAADsvYEoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nyMFHhgwZg4L/D0wNdbzREoHMAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a13035b90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAR8AAADmCAYAAADsvYEoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a131331d0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "print(__doc__)\n",
-    "\n",
-    "\n",
-    "# Code source: Gaël Varoquaux\n",
-    "# Modified for documentation by Jaques Grobler\n",
-    "# License: BSD 3 clause\n",
-    "\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "# Though the following import is not directly being used, it is required\n",
-    "# for 3D projection to work\n",
-    "from mpl_toolkits.mplot3d import Axes3D\n",
-    "\n",
-    "from sklearn.cluster import KMeans\n",
-    "from sklearn import datasets\n",
-    "\n",
-    "np.random.seed(5)\n",
-    "\n",
-    "iris = datasets.load_iris()\n",
-    "X = iris.data\n",
-    "y = iris.target\n",
-    "\n",
-    "estimators = [('k_means_iris_8', KMeans(n_clusters=8)),\n",
-    "              ('k_means_iris_3', KMeans(n_clusters=3)),\n",
-    "              ('k_means_iris_bad_init', KMeans(n_clusters=3, n_init=1,\n",
-    "                                               init='random'))]\n",
-    "\n",
-    "fignum = 1\n",
-    "titles = ['8 clusters', '3 clusters', '3 clusters, bad initialization']\n",
-    "for name, est in estimators:\n",
-    "    fig = plt.figure(fignum, figsize=(4, 3))\n",
-    "    ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n",
-    "    est.fit(X)\n",
-    "    labels = est.labels_\n",
-    "\n",
-    "    ax.scatter(X[:, 3], X[:, 0], X[:, 2],\n",
-    "               c=labels.astype(np.float), edgecolor='k')\n",
-    "\n",
-    "    ax.w_xaxis.set_ticklabels([])\n",
-    "    ax.w_yaxis.set_ticklabels([])\n",
-    "    ax.w_zaxis.set_ticklabels([])\n",
-    "    ax.set_xlabel('Petal width')\n",
-    "    ax.set_ylabel('Sepal length')\n",
-    "    ax.set_zlabel('Petal length')\n",
-    "    ax.set_title(titles[fignum - 1])\n",
-    "    ax.dist = 12\n",
-    "    fignum = fignum + 1\n",
-    "\n",
-    "# Plot the ground truth\n",
-    "fig = plt.figure(fignum, figsize=(4, 3))\n",
-    "ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)\n",
-    "\n",
-    "for name, label in [('Setosa', 0),\n",
-    "                    ('Versicolour', 1),\n",
-    "                    ('Virginica', 2)]:\n",
-    "    ax.text3D(X[y == label, 3].mean(),\n",
-    "              X[y == label, 0].mean(),\n",
-    "              X[y == label, 2].mean() + 2, name,\n",
-    "              horizontalalignment='center',\n",
-    "              bbox=dict(alpha=.2, edgecolor='w', facecolor='w'))\n",
-    "# Reorder the labels to have colors matching the cluster results\n",
-    "y = np.choose(y, [1, 2, 0]).astype(np.float)\n",
-    "ax.scatter(X[:, 3], X[:, 0], X[:, 2], c=y, edgecolor='k')\n",
-    "\n",
-    "ax.w_xaxis.set_ticklabels([])\n",
-    "ax.w_yaxis.set_ticklabels([])\n",
-    "ax.w_zaxis.set_ticklabels([])\n",
-    "ax.set_xlabel('Petal width')\n",
-    "ax.set_ylabel('Sepal length')\n",
-    "ax.set_zlabel('Petal length')\n",
-    "ax.set_title('Ground Truth')\n",
-    "ax.dist = 12\n",
-    "\n",
-    "fig.show()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Section 2.2 Classification and regression"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 104,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "from sklearn.linear_model import LinearRegression, LogisticRegression \n",
-    "\n",
-    "from sklearn.svm import SVC, SVR\n",
-    "\n",
-    "from sklearn.neighbors import KNeighborsClassifier , KNeighborsRegressor\n",
-    "from sklearn.cross_validation import train_test_split\n",
-    "from sklearn.metrics import confusion_matrix"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>bedrooms</th>\n",
-       "      <th>bathrooms</th>\n",
-       "      <th>rooms</th>\n",
-       "      <th>squareFootage</th>\n",
-       "      <th>lotSize</th>\n",
-       "      <th>yearBuilt</th>\n",
-       "      <th>priorSaleAmount</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>3</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6</td>\n",
-       "      <td>1378</td>\n",
-       "      <td>9968</td>\n",
-       "      <td>2003.0</td>\n",
-       "      <td>165700.0</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>6</td>\n",
-       "      <td>1653</td>\n",
-       "      <td>6970</td>\n",
-       "      <td>2004.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   bedrooms  bathrooms  rooms  squareFootage  lotSize  yearBuilt  \\\n",
-       "0         3        2.0      6           1378     9968     2003.0   \n",
-       "1         2        2.0      6           1653     6970     2004.0   \n",
-       "\n",
-       "   priorSaleAmount  \n",
-       "0         165700.0  \n",
-       "1              0.0  "
-      ]
-     },
-     "execution_count": 41,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X.head(2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 42,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "y=df.estimated_value "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 45,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.7648477834199694"
-      ]
-     },
-     "execution_count": 45,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "lg = LinearRegression()\n",
-    "lg.fit(X,y) #training \n",
-    "lg.score(X,y) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X_train, X_test,  y_train, y_test= train_test_split(X,y)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "((11250, 7), (11250,))"
-      ]
-     },
-     "execution_count": 48,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_train.shape, y_train.shape "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.80307010330903539"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "lg = LinearRegression()\n",
-    "lg.fit(X_train,y_train) # training , fit \n",
-    "lg.score(X_test,y_test) # evaluate , score, R2 "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 70,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "df['estimated_value_bins']=df.estimated_value.apply(lambda x: 'high' if x> 500000 else 'low')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 71,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "high    7963\n",
-       "low     7037\n",
-       "Name: estimated_value_bins, dtype: int64"
-      ]
-     },
-     "execution_count": 71,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.estimated_value_bins.value_counts()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 75,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "y2= df.estimated_value_bins"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 76,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "log = LogisticRegression() "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 77,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X_train, X_test,  y2_train, y2_test= train_test_split(X,y2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 78,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
-       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
-       "          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
-       "          verbose=0, warm_start=False)"
-      ]
-     },
-     "execution_count": 78,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "log.fit(X_train, y2_train)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 79,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.81679999999999997"
-      ]
-     },
-     "execution_count": 79,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "log.score(X_test, y2_test)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 87,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "y_pred = log.predict(X_test) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 85,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['low', 'low', 'high', ..., 'high', 'low', 'high'], dtype=object)"
-      ]
-     },
-     "execution_count": 85,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.array(y2_test)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 88,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1568,  377],\n",
-       "       [ 310, 1495]])"
-      ]
-     },
-     "execution_count": 88,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "confusion_matrix(y2_test,y_pred )"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 92,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "## Section 2.2 Continued\n",
-    "from IPython.display import Image"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 113,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Support Vector Machine\n"
-     ]
-    }
-   ],
-   "source": [
-    "Image('svm.png')\n",
-    "print 'Support Vector Machine'"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 100,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-0.056414465159077887"
-      ]
-     },
-     "execution_count": 100,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "svr= SVR() \n",
-    "svr.fit(X_train, y_train)\n",
-    "svr.score(X_test, y_test) \n",
-    "# not so great "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 101,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.55386666666666662"
-      ]
-     },
-     "execution_count": 101,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "svc= SVC() \n",
-    "svc.fit(X_train, y2_train)\n",
-    "svc.score(X_test, y2_test) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 102,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "y2_pred=svc.predict(X_test)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 103,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1937,    8],\n",
-       "       [1665,  140]])"
-      ]
-     },
-     "execution_count": 103,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "confusion_matrix(y2_test, y2_pred)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "## KNN: \n",
-    "xxxxxx\n",
-    "unknown=x\n",
-    "xxxxx    \n",
-    "\n",
-    "     ooooooo\n",
-    "        unknown= o \n",
-    "    ooooooo"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 105,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "knn= KNeighborsRegressor() "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 106,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\n",
-       "          metric_params=None, n_jobs=1, n_neighbors=5, p=2,\n",
-       "          weights='uniform')"
-      ]
-     },
-     "execution_count": 106,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "knn.fit(X_train, y_train)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 107,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "-0.2227615288381741"
-      ]
-     },
-     "execution_count": 107,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "knn.score(X_test, y_test)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 108,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "knn= KNeighborsClassifier()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 109,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
-       "           metric_params=None, n_jobs=1, n_neighbors=5, p=2,\n",
-       "           weights='uniform')"
-      ]
-     },
-     "execution_count": 109,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "knn.fit(X_train, y2_train)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 110,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.81999999999999995"
-      ]
-     },
-     "execution_count": 110,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "knn.score(X_test,y2_test) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 111,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "y2_pred=knn.predict(X_test)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 112,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[1564,  381],\n",
-       "       [ 294, 1511]])"
-      ]
-     },
-     "execution_count": 112,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "confusion_matrix(y2_test, y2_pred)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Section 2.3 Association and correlation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 148,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1599c9d0>"
-      ]
-     },
-     "execution_count": 148,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaIAAAE5CAYAAADSqiTvAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a14ce2ad0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sns.heatmap(df.corr())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 149,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style>\n",
-       "    .dataframe thead tr:only-child th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: left;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>id</th>\n",
-       "      <th>zipcode</th>\n",
-       "      <th>latitude</th>\n",
-       "      <th>longitude</th>\n",
-       "      <th>bedrooms</th>\n",
-       "      <th>bathrooms</th>\n",
-       "      <th>rooms</th>\n",
-       "      <th>squareFootage</th>\n",
-       "      <th>lotSize</th>\n",
-       "      <th>yearBuilt</th>\n",
-       "      <th>lastSaleAmount</th>\n",
-       "      <th>priorSaleAmount</th>\n",
-       "      <th>estimated_value</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>id</th>\n",
-       "      <td>3.832695e+15</td>\n",
-       "      <td>-4.794798e+06</td>\n",
-       "      <td>-134755.796294</td>\n",
-       "      <td>97277.793395</td>\n",
-       "      <td>4.241855e+06</td>\n",
-       "      <td>9.277448e+06</td>\n",
-       "      <td>1.140562e+07</td>\n",
-       "      <td>7.357116e+09</td>\n",
-       "      <td>8.457335e+09</td>\n",
-       "      <td>7.661356e+07</td>\n",
-       "      <td>3.326786e+12</td>\n",
-       "      <td>2.403030e+11</td>\n",
-       "      <td>3.940756e+12</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>zipcode</th>\n",
-       "      <td>-4.794798e+06</td>\n",
-       "      <td>9.438634e+01</td>\n",
-       "      <td>0.105769</td>\n",
-       "      <td>0.152571</td>\n",
-       "      <td>-1.605609e-01</td>\n",
-       "      <td>-8.546300e-02</td>\n",
-       "      <td>5.964580e-01</td>\n",
-       "      <td>6.549458e+00</td>\n",
-       "      <td>-1.103540e+03</td>\n",
-       "      <td>-5.065034e+01</td>\n",
-       "      <td>2.479246e+05</td>\n",
-       "      <td>1.030079e+05</td>\n",
-       "      <td>4.366604e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>latitude</th>\n",
-       "      <td>-1.347558e+05</td>\n",
-       "      <td>1.057691e-01</td>\n",
-       "      <td>0.000555</td>\n",
-       "      <td>0.000468</td>\n",
-       "      <td>-1.754563e-03</td>\n",
-       "      <td>-6.524595e-03</td>\n",
-       "      <td>-9.848155e-03</td>\n",
-       "      <td>-5.015548e+00</td>\n",
-       "      <td>-6.593470e+00</td>\n",
-       "      <td>-7.428908e-02</td>\n",
-       "      <td>-2.317704e+03</td>\n",
-       "      <td>-1.773170e+03</td>\n",
-       "      <td>-3.163364e+03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>longitude</th>\n",
-       "      <td>9.727779e+04</td>\n",
-       "      <td>1.525709e-01</td>\n",
-       "      <td>0.000468</td>\n",
-       "      <td>0.001583</td>\n",
-       "      <td>7.981594e-04</td>\n",
-       "      <td>4.991539e-03</td>\n",
-       "      <td>2.032934e-03</td>\n",
-       "      <td>2.241057e+00</td>\n",
-       "      <td>7.941290e+00</td>\n",
-       "      <td>7.233661e-02</td>\n",
-       "      <td>1.134553e+03</td>\n",
-       "      <td>1.306180e+03</td>\n",
-       "      <td>2.449320e+03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>bedrooms</th>\n",
-       "      <td>4.241855e+06</td>\n",
-       "      <td>-1.605609e-01</td>\n",
-       "      <td>-0.001755</td>\n",
-       "      <td>0.000798</td>\n",
-       "      <td>8.050231e-01</td>\n",
-       "      <td>5.294167e-01</td>\n",
-       "      <td>1.251811e+00</td>\n",
-       "      <td>4.627877e+02</td>\n",
-       "      <td>4.285138e+02</td>\n",
-       "      <td>-1.656479e+00</td>\n",
-       "      <td>9.398271e+04</td>\n",
-       "      <td>6.326439e+04</td>\n",
-       "      <td>1.670586e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>bathrooms</th>\n",
-       "      <td>9.277448e+06</td>\n",
-       "      <td>-8.546300e-02</td>\n",
-       "      <td>-0.006525</td>\n",
-       "      <td>0.004992</td>\n",
-       "      <td>5.294167e-01</td>\n",
-       "      <td>1.360206e+00</td>\n",
-       "      <td>1.567688e+00</td>\n",
-       "      <td>7.790507e+02</td>\n",
-       "      <td>9.104679e+02</td>\n",
-       "      <td>6.793260e+00</td>\n",
-       "      <td>2.683082e+05</td>\n",
-       "      <td>1.783968e+05</td>\n",
-       "      <td>4.211742e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>rooms</th>\n",
-       "      <td>1.140562e+07</td>\n",
-       "      <td>5.964580e-01</td>\n",
-       "      <td>-0.009848</td>\n",
-       "      <td>0.002033</td>\n",
-       "      <td>1.251811e+00</td>\n",
-       "      <td>1.567688e+00</td>\n",
-       "      <td>3.836116e+00</td>\n",
-       "      <td>1.254643e+03</td>\n",
-       "      <td>1.038417e+03</td>\n",
-       "      <td>-2.797016e+00</td>\n",
-       "      <td>3.502513e+05</td>\n",
-       "      <td>2.430849e+05</td>\n",
-       "      <td>5.740237e+05</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>squareFootage</th>\n",
-       "      <td>7.357116e+09</td>\n",
-       "      <td>6.549458e+00</td>\n",
-       "      <td>-5.015548</td>\n",
-       "      <td>2.241057</td>\n",
-       "      <td>4.627877e+02</td>\n",
-       "      <td>7.790507e+02</td>\n",
-       "      <td>1.254643e+03</td>\n",
-       "      <td>6.899562e+05</td>\n",
-       "      <td>9.241945e+05</td>\n",
-       "      <td>2.866840e+03</td>\n",
-       "      <td>2.154884e+08</td>\n",
-       "      <td>1.377630e+08</td>\n",
-       "      <td>3.454582e+08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>lotSize</th>\n",
-       "      <td>8.457335e+09</td>\n",
-       "      <td>-1.103540e+03</td>\n",
-       "      <td>-6.593470</td>\n",
-       "      <td>7.941290</td>\n",
-       "      <td>4.285138e+02</td>\n",
-       "      <td>9.104679e+02</td>\n",
-       "      <td>1.038417e+03</td>\n",
-       "      <td>9.241945e+05</td>\n",
-       "      <td>9.079853e+06</td>\n",
-       "      <td>2.575406e+04</td>\n",
-       "      <td>4.521032e+08</td>\n",
-       "      <td>1.919438e+08</td>\n",
-       "      <td>6.939180e+08</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>yearBuilt</th>\n",
-       "      <td>7.661356e+07</td>\n",
-       "      <td>-5.065034e+01</td>\n",
-       "      <td>-0.074289</td>\n",
-       "      <td>0.072337</td>\n",
-       "      <td>-1.656479e+00</td>\n",
-       "      <td>6.793260e+00</td>\n",
-       "      <td>-2.797016e+00</td>\n",
-       "      <td>2.866840e+03</td>\n",
-       "      <td>2.575406e+04</td>\n",
-       "      <td>8.962271e+02</td>\n",
-       "      <td>1.801012e+06</td>\n",
-       "      <td>1.141169e+06</td>\n",
-       "      <td>2.634072e+06</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>lastSaleAmount</th>\n",
-       "      <td>3.326786e+12</td>\n",
-       "      <td>2.479246e+05</td>\n",
-       "      <td>-2317.703724</td>\n",
-       "      <td>1134.552961</td>\n",
-       "      <td>9.398271e+04</td>\n",
-       "      <td>2.683082e+05</td>\n",
-       "      <td>3.502513e+05</td>\n",
-       "      <td>2.154884e+08</td>\n",
-       "      <td>4.521032e+08</td>\n",
-       "      <td>1.801012e+06</td>\n",
-       "      <td>6.017103e+11</td>\n",
-       "      <td>7.543743e+10</td>\n",
-       "      <td>1.637338e+11</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>priorSaleAmount</th>\n",
-       "      <td>2.403030e+11</td>\n",
-       "      <td>1.030079e+05</td>\n",
-       "      <td>-1773.169570</td>\n",
-       "      <td>1306.179672</td>\n",
-       "      <td>6.326439e+04</td>\n",
-       "      <td>1.783968e+05</td>\n",
-       "      <td>2.430849e+05</td>\n",
-       "      <td>1.377630e+08</td>\n",
-       "      <td>1.919438e+08</td>\n",
-       "      <td>1.141169e+06</td>\n",
-       "      <td>7.543743e+10</td>\n",
-       "      <td>1.142026e+11</td>\n",
-       "      <td>9.951301e+10</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>estimated_value</th>\n",
-       "      <td>3.940756e+12</td>\n",
-       "      <td>4.366604e+05</td>\n",
-       "      <td>-3163.363716</td>\n",
-       "      <td>2449.320289</td>\n",
-       "      <td>1.670586e+05</td>\n",
-       "      <td>4.211742e+05</td>\n",
-       "      <td>5.740237e+05</td>\n",
-       "      <td>3.454582e+08</td>\n",
-       "      <td>6.939180e+08</td>\n",
-       "      <td>2.634072e+06</td>\n",
-       "      <td>1.637338e+11</td>\n",
-       "      <td>9.951301e+10</td>\n",
-       "      <td>2.544380e+11</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                           id       zipcode       latitude     longitude  \\\n",
-       "id               3.832695e+15 -4.794798e+06 -134755.796294  97277.793395   \n",
-       "zipcode         -4.794798e+06  9.438634e+01       0.105769      0.152571   \n",
-       "latitude        -1.347558e+05  1.057691e-01       0.000555      0.000468   \n",
-       "longitude        9.727779e+04  1.525709e-01       0.000468      0.001583   \n",
-       "bedrooms         4.241855e+06 -1.605609e-01      -0.001755      0.000798   \n",
-       "bathrooms        9.277448e+06 -8.546300e-02      -0.006525      0.004992   \n",
-       "rooms            1.140562e+07  5.964580e-01      -0.009848      0.002033   \n",
-       "squareFootage    7.357116e+09  6.549458e+00      -5.015548      2.241057   \n",
-       "lotSize          8.457335e+09 -1.103540e+03      -6.593470      7.941290   \n",
-       "yearBuilt        7.661356e+07 -5.065034e+01      -0.074289      0.072337   \n",
-       "lastSaleAmount   3.326786e+12  2.479246e+05   -2317.703724   1134.552961   \n",
-       "priorSaleAmount  2.403030e+11  1.030079e+05   -1773.169570   1306.179672   \n",
-       "estimated_value  3.940756e+12  4.366604e+05   -3163.363716   2449.320289   \n",
-       "\n",
-       "                     bedrooms     bathrooms         rooms  squareFootage  \\\n",
-       "id               4.241855e+06  9.277448e+06  1.140562e+07   7.357116e+09   \n",
-       "zipcode         -1.605609e-01 -8.546300e-02  5.964580e-01   6.549458e+00   \n",
-       "latitude        -1.754563e-03 -6.524595e-03 -9.848155e-03  -5.015548e+00   \n",
-       "longitude        7.981594e-04  4.991539e-03  2.032934e-03   2.241057e+00   \n",
-       "bedrooms         8.050231e-01  5.294167e-01  1.251811e+00   4.627877e+02   \n",
-       "bathrooms        5.294167e-01  1.360206e+00  1.567688e+00   7.790507e+02   \n",
-       "rooms            1.251811e+00  1.567688e+00  3.836116e+00   1.254643e+03   \n",
-       "squareFootage    4.627877e+02  7.790507e+02  1.254643e+03   6.899562e+05   \n",
-       "lotSize          4.285138e+02  9.104679e+02  1.038417e+03   9.241945e+05   \n",
-       "yearBuilt       -1.656479e+00  6.793260e+00 -2.797016e+00   2.866840e+03   \n",
-       "lastSaleAmount   9.398271e+04  2.683082e+05  3.502513e+05   2.154884e+08   \n",
-       "priorSaleAmount  6.326439e+04  1.783968e+05  2.430849e+05   1.377630e+08   \n",
-       "estimated_value  1.670586e+05  4.211742e+05  5.740237e+05   3.454582e+08   \n",
-       "\n",
-       "                      lotSize     yearBuilt  lastSaleAmount  priorSaleAmount  \\\n",
-       "id               8.457335e+09  7.661356e+07    3.326786e+12     2.403030e+11   \n",
-       "zipcode         -1.103540e+03 -5.065034e+01    2.479246e+05     1.030079e+05   \n",
-       "latitude        -6.593470e+00 -7.428908e-02   -2.317704e+03    -1.773170e+03   \n",
-       "longitude        7.941290e+00  7.233661e-02    1.134553e+03     1.306180e+03   \n",
-       "bedrooms         4.285138e+02 -1.656479e+00    9.398271e+04     6.326439e+04   \n",
-       "bathrooms        9.104679e+02  6.793260e+00    2.683082e+05     1.783968e+05   \n",
-       "rooms            1.038417e+03 -2.797016e+00    3.502513e+05     2.430849e+05   \n",
-       "squareFootage    9.241945e+05  2.866840e+03    2.154884e+08     1.377630e+08   \n",
-       "lotSize          9.079853e+06  2.575406e+04    4.521032e+08     1.919438e+08   \n",
-       "yearBuilt        2.575406e+04  8.962271e+02    1.801012e+06     1.141169e+06   \n",
-       "lastSaleAmount   4.521032e+08  1.801012e+06    6.017103e+11     7.543743e+10   \n",
-       "priorSaleAmount  1.919438e+08  1.141169e+06    7.543743e+10     1.142026e+11   \n",
-       "estimated_value  6.939180e+08  2.634072e+06    1.637338e+11     9.951301e+10   \n",
-       "\n",
-       "                 estimated_value  \n",
-       "id                  3.940756e+12  \n",
-       "zipcode             4.366604e+05  \n",
-       "latitude           -3.163364e+03  \n",
-       "longitude           2.449320e+03  \n",
-       "bedrooms            1.670586e+05  \n",
-       "bathrooms           4.211742e+05  \n",
-       "rooms               5.740237e+05  \n",
-       "squareFootage       3.454582e+08  \n",
-       "lotSize             6.939180e+08  \n",
-       "yearBuilt           2.634072e+06  \n",
-       "lastSaleAmount      1.637338e+11  \n",
-       "priorSaleAmount     9.951301e+10  \n",
-       "estimated_value     2.544380e+11  "
-      ]
-     },
-     "execution_count": 149,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.cov()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 152,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "y=df.estimated_value"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 141,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Index([u'bedrooms', u'bathrooms', u'rooms', u'squareFootage', u'lotSize',\n",
-       "       u'yearBuilt', u'priorSaleAmount'],\n",
-       "      dtype='object')"
-      ]
-     },
-     "execution_count": 141,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X.columns"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 146,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "====\n",
-      "bedrooms\n",
-      "mean: 2.7084\n",
-      "std: 0.897230799854\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD3CAYAAAAT+Z8iAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAEuZJREFUeJzt3X9sXWd9x/G3EzdJg5zMGg4dUkU3wb7qKpVORYU1SWOh\nlpBs0A2t21QxUrqloQorbNWAtummTmGFrgSWoRbm0qWlQ2gEukGklEoUsiRji8aKlGjlW4Ux8Qfr\n5BU3MZikS+L9cY+H41773jqxz/Gj90tCOve5z+n5nGv0uU/O/dUzPj6OJKlci+oOIEmaWxa9JBXO\nopekwln0klQ4i16SCtdbd4B2hodHZ/1WoP7+5YyMjJ3POOdd0zM2PR80P2PT80HzMzY9HzQv48BA\nX0+78eJW9L29i+uO0FHTMzY9HzQ/Y9PzQfMzNj0fLIyMUGDRS5LOZtFLUuEsekkqnEUvSYWz6CWp\ncBa9JBXOopekwln0klQ4i16SCtfIr0DQy3PzR56q5bgPf+jNtRxX0svjil6SCmfRS1LhLHpJKpxF\nL0mFs+glqXAWvSQVzqKXpMJZ9JJUOItekgpn0UtS4Tp+BUJE3ATcVN1cBlwBrAE+AYwDR4CtmXkm\nIjYDW4BTwPbM3BMRFwKPAauAUWBTZg6f5/OQJE2j44o+M3dl5mBmDgLfAm4D/gTYlplrgR7g+oi4\nqLpvNbAeuDcilgK3AoeruY8C2+bkTCRJbXV96SYi3gBclpl/DVwJ7Kvu2gtcC1wFHMzMk5l5DDgK\nXE5r9f/ElLmSpHnycr698k7gnmq7JzPHq+1RYCWwAjg2aX678YmxGfX3L6e3d/HLiHa2gYG+We87\nXxZCxk7qPoe6j99J0/NB8zM2PR8sjIxdFX1E/AwQmfn1aujMpLv7gBeA49X2TOMTYzMaGRnrJlZb\nAwN9DA+Pznr/+bAQMnajznNo+mPY9HzQ/IxNzwfNyzjdk063l26uAb426fbTETFYbW8A9gOHgLUR\nsSwiVgKX0nqh9iCwccpcSdI86bboA/iPSbdvB+6JiG8CS4DdmfkcsJNWkT8F3JWZJ4AHgcsi4gBw\nCz+9/CNJmgddXbrJzL+YcvtZYF2beUPA0JSxMeCGc8goSToHfmBKkgpn0UtS4Sx6SSqcRS9JhbPo\nJalwL+eTsZrBzR95qu4IktSWK3pJKpxFL0mFs+glqXAWvSQVzqKXpMJZ9JJUOItekgpn0UtS4Sx6\nSSqcRS9JhbPoJalwFr0kFc6il6TCWfSSVLiuvqY4Iu4A3g4sAR4A9gG7gHHgCLA1M89ExGZgC3AK\n2J6ZeyLiQuAxYBUwCmzKzOHzfSKSpPY6rugjYhC4GlgNrAMuBnYA2zJzLdADXB8RFwG3VfPWA/dG\nxFLgVuBwNfdRYNscnIckaRrdrOjXA4eBx4EVwB8Dm2mt6gH2Am8BTgMHM/MkcDIijgKXA2uA+ybN\nvbvTAfv7l9Pbu/hlnMbZBgb6Zr2vulf341z38Ttpej5ofsam54OFkbGbon8l8Brg14CfB74MLMrM\n8er+UWAlrSeBY5P2azc+MTajkZGxbrK3NTDQx/Dw6Kz3V/fqfJyb/nduej5ofsam54PmZZzuSaeb\non8e+E5mvghkRJygdflmQh/wAnC82p5pfGJMkjRPunnXzQHgrRHRExGvBl4BfK26dg+wAdgPHALW\nRsSyiFgJXErrhdqDwMYpcyVJ86Tjir5658w1tIp8EbAV+B4wFBFLgGeA3Zl5OiJ20iryRcBdmXki\nIh4EHomIA8CLwI1zdC6SpDa6entlZn6gzfC6NvOGgKEpY2PADbNKJ0k6Z35gSpIKZ9FLUuEsekkq\nnEUvSYWz6CWpcBa9JBXOopekwln0klQ4i16SCmfRS1LhLHpJKpxFL0mFs+glqXAWvSQVzqKXpMJZ\n9JJUOItekgpn0UtS4Sx6SSpcV78ZGxH/Bhyvbn4P+DCwCxgHjgBbM/NMRGwGtgCngO3VD4tfCDwG\nrAJGgU2ZOXxez0KSNK2OK/qIWAb0ZOZg9b93AzuAbZm5FugBro+Ii4DbgNXAeuDeiFgK3AocruY+\nCmybo3ORJLXRzYr+9cDyiHiymn8ncCWwr7p/L/AW4DRwMDNPAicj4ihwObAGuG/S3LvPX3xJUifd\nFP0YcD/wEPA6WmXdk5nj1f2jwEpgBXBs0n7txifGZtTfv5ze3sXd5G9rYKBv1vuqe3U/znUfv5Om\n54PmZ2x6PlgYGbsp+meBo1WxPxsRz9Na0U/oA16gdQ2/r8P4xNiMRkbGuojV3sBAH8PDo7PeX92r\n83Fu+t+56fmg+Rmbng+al3G6J51u3nVzM/AxgIh4Na0V+pMRMVjdvwHYDxwC1kbEsohYCVxK64Xa\ng8DGKXMlSfOkmxX9Z4BdEXGA1rtsbgb+BxiKiCXAM8DuzDwdETtpFfki4K7MPBERDwKPVPu/CNw4\nFyciSWqvY9Fn5nTlvK7N3CFgaMrYGHDDbANKks6NH5iSpMJZ9JJUOItekgpn0UtS4Sx6SSqcRS9J\nhbPoJalwFr0kFc6il6TCWfSSVDiLXpIKZ9FLUuEsekkqnEUvSYWz6CWpcBa9JBXOopekwln0klQ4\ni16SCmfRS1LhOv44OEBErAK+BVwHnAJ2AePAEWBrZp6JiM3Alur+7Zm5JyIuBB4DVgGjwKbMHD7v\nZyFJmlbHFX1EXAB8GvhJNbQD2JaZa4Ee4PqIuAi4DVgNrAfujYilwK3A4Wruo8C2838KkqSZdHPp\n5n7gU8APqttXAvuq7b3AtcBVwMHMPJmZx4CjwOXAGuCJKXMlSfNoxks3EXETMJyZX42IO6rhnswc\nr7ZHgZXACuDYpF3bjU+MddTfv5ze3sVdnUA7AwN9s95X3av7ca77+J00PR80P2PT88HCyNjpGv3N\nwHhEXAtcQevyy6pJ9/cBLwDHq+2ZxifGOhoZGetmWlsDA30MD4/Oen91r87Huel/56bng+ZnbHo+\naF7G6Z50Zrx0k5nXZOa6zBwEvg28C9gbEYPVlA3AfuAQsDYilkXESuBSWi/UHgQ2TpkrSZpHs3l7\n5e3APRHxTWAJsDsznwN20iryp4C7MvME8CBwWUQcAG4B7jk/sSVJ3erq7ZUA1ap+wro29w8BQ1PG\nxoAbZhtOknTu/MCUJBXOopekwln0klQ4i16SCmfRS1LhLHpJKpxFL0mFs+glqXAWvSQVzqKXpMJZ\n9JJUOItekgpn0UtS4Sx6SSqcRS9JhbPoJalwFr0kFc6il6TCWfSSVLiOvxkbEYtp/RZsAOPAe4AT\nwK7q9hFga2aeiYjNwBbgFLA9M/dExIXAY8AqYBTYlJnDc3AukqQ2ulnRvw0gM1cD24APAzuAbZm5\nFugBro+Ii4DbgNXAeuDeiFgK3AocruY+Wv03JEnzpGPRZ+bfA7dUN18DvABcCeyrxvYC1wJXAQcz\n82RmHgOOApcDa4AnpsyVJM2TjpduADLzVEQ8AvwG8JvAdZk5Xt09CqwEVgDHJu3WbnxibEb9/cvp\n7V3c1Qm0MzDQN+t91b26H+e6j99J0/NB8zM2PR8sjIxdFT1AZm6KiA8C/wJcOOmuPlqr/OPV9kzj\nE2MzGhkZ6zbWSwwM9DE8PDrr/dW9Oh/npv+dm54Pmp+x6fmgeRmne9LpeOkmIn43Iu6obo4BZ4B/\njYjBamwDsB84BKyNiGURsRK4lNYLtQeBjVPmSpLmSTcr+i8BfxMR/whcALwfeAYYiogl1fbuzDwd\nETtpFfki4K7MPBERDwKPRMQB4EXgxrk4EUlSex2LPjN/DPxWm7vWtZk7ROutmJPHxoAbZhtQknRu\n/MCUJBXOopekwln0klQ4i16SCmfRS1LhLHpJKpxFL0mFs+glqXAWvSQVzqKXpMJZ9JJUOItekgpn\n0UtS4Sx6SSqcRS9JhbPoJalwFr0kFc6il6TCWfSSVDiLXpIKN+OPg0fEBcDDwCXAUmA78O/ALmAc\nOAJszcwzEbEZ2AKcArZn5p6IuBB4DFgFjAKbMnN4bk5FktROpxX9O4HnM3Mt8Fbgk8AOYFs11gNc\nHxEXAbcBq4H1wL0RsRS4FThczX0U2DY3pyFJmk6nov8CcHe13UNrtX4lsK8a2wtcC1wFHMzMk5l5\nDDgKXA6sAZ6YMleSNI9mvHSTmT8CiIg+YDetFfn9mTleTRkFVgIrgGOTdm03PjHWUX//cnp7F3d5\nCi81MNA3633Vvbof57qP30nT80HzMzY9HyyMjDMWPUBEXAw8DjyQmZ+LiPsm3d0HvAAcr7ZnGp8Y\n62hkZKybaW0NDPQxPDw66/3VvTof56b/nZueD5qfsen5oHkZp3vSmfHSTUS8CngS+GBmPlwNPx0R\ng9X2BmA/cAhYGxHLImIlcCmtF2oPAhunzJUkzaNOK/o7gX7g7oiYuFb/PmBnRCwBngF2Z+bpiNhJ\nq8gXAXdl5omIeBB4JCIOAC8CN87JWUiSptXpGv37aBX7VOvazB0ChqaMjQE3nEtASdK58QNTklQ4\ni16SCmfRS1LhLHpJKpxFL0mFs+glqXAWvSQVzqKXpMJZ9JJUOItekgpn0UtS4Sx6SSqcRS9JhbPo\nJalwFr0kFc6il6TCWfSSVDiLXpIKZ9FLUuEsekkq3Iw/Dj4hIt4IfDQzByPitcAuYBw4AmzNzDMR\nsRnYApwCtmfmnoi4EHgMWAWMApsyc3gOzkOSNI2OK/qI+ADwELCsGtoBbMvMtUAPcH1EXATcBqwG\n1gP3RsRS4FbgcDX3UWDb+T8FSdJMulnRfxd4B/DZ6vaVwL5qey/wFuA0cDAzTwInI+IocDmwBrhv\n0ty7uwnV37+c3t7FXZ1AOwMDfbPeV92r+3Gu+/idND0fND9j0/PBwsjYsegz84sRccmkoZ7MHK+2\nR4GVwArg2KQ57cYnxjoaGRnrZlpbAwN9DA+Pznp/da/Ox7npf+em54PmZ2x6PmhexumedGbzYuyZ\nSdt9wAvA8Wp7pvGJMUnSPJpN0T8dEYPV9gZgP3AIWBsRyyJiJXAprRdqDwIbp8yVJM2j2RT97cA9\nEfFNYAmwOzOfA3bSKvKngLsy8wTwIHBZRBwAbgHuOT+xJUnd6urtlZn5n8Cbqu1ngXVt5gwBQ1PG\nxoAbzjmlJGnW/MCUJBXOopekwln0klQ4i16SCmfRS1LhLHpJKpxFL0mFs+glqXAWvSQVzqKXpMJZ\n9JJUuK6+62Yhedvt/1B3BElqlOKKXvPn5o88Vduxv/Kx62s7trTQeOlGkgpn0UtS4Sx6SSqcRS9J\nhbPoJalwFr0kFW7O314ZEYuAB4DXAyeB38/Mo3N9XJWtrs9LPPyhN9dyXOlczMeK/teBZZn5K8CH\ngI/NwzElSZX5KPo1wBMAmfnPwBvm4ZiSpErP+Pj4nB4gIh4CvpiZe6vb3wd+ITNPzemBJUnA/Kzo\njwN9k49pyUvS/JmPoj8IbASIiDcBh+fhmJKkynx8qdnjwHUR8U9AD/DueTimJKky59foJUn18gNT\nklQ4i16SCmfRS1LhiviFqYXwNQsRcQHwMHAJsBTYnplfrjVUGxGxCvgWcF1mfqfuPFNFxB3A24El\nwAOZ+ZmaI52l+js/QuvvfBrY3JTHMSLeCHw0Mwcj4rXALmAcOAJszcwzdeaDl2S8AvgrWo/jSeBd\nmfnfTck3aexG4A+qT/83Uikr+oXwNQvvBJ7PzLXAW4FP1pznJaqS+jTwk7qztBMRg8DVwGpgHXBx\nrYHa2wj0ZubVwJ8BH645DwAR8QHgIWBZNbQD2Fb9/7EHqP23Gdtk/EtaBToIfAn4YE3RgLb5iIhf\nBn6P1mPYWKUU/UL4moUvAHdX2z1AEz80dj/wKeAHdQeZxnpan8N4HPgKsKfeOG09C/RW/8pcAfxv\nzXkmfBd4x6TbVwL7qu29wLXznuilpmb8ncz8drXdC5yY/0hnOStfRPws8OfA+2tL1KVSin4FcGzS\n7dMR0ajLUpn5o8wcjYg+YDewre5Mk0XETcBwZn617iwzeCWtJ/EbgPcAfxsRTVtJ/YjWZZvvAEPA\nzlrTVDLzi5z9pNOTmRPvrR4FVs5/qrNNzZiZ/wUQEVcD7wU+XlO0iTz/ny8iFgOfAf6I1uPXaKUU\n/YL4moWIuBj4OvDZzPxc3XmmuJnWB9u+AVwBPBoRF9Ub6SWeB76amS9mZtJa4Q3UnGmqP6SV8Rdp\nvWb0SEQs67BPHSZfj+8DXqgryEwi4rdp/SvzVzNzuO48k1wJvA54EPg88EsR8Yl6I02vUavec3AQ\neBvwd039moWIeBXwJPDezPxa3XmmysxrJrarsn9PZj5XX6K2DgDvi4gdwM8Br6BV/k0ywk9XpT8E\nLgAW1xdnWk9HxGBmfgPYQGsB0igR8U5gCzCYmT+sO89kmXkIuAwgIi4BPp+Zjb2EU0rRL4SvWbgT\n6AfujoiJa/UbMrORL3w2UWbuiYhrgEO0/jW6NTNP1xxrqo8DD0fEflrvDLozM39cc6Z2bgeGImIJ\n8Ayty4mNUV0a2Ql8H/hSRADsy8w/rTXYAuVXIEhS4Uq5Ri9JmoZFL0mFs+glqXAWvSQVzqKXpMJZ\n9JJUOItekgr3f3HvUDQES/vyAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15f6ec50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "====\n",
-      "bathrooms\n",
-      "mean: 2.19506666667\n",
-      "std: 1.16627884429\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD3CAYAAAAT+Z8iAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a1578ab50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "====\n",
-      "rooms\n",
-      "mean: 6.16413333333\n",
-      "std: 1.95860051822\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD3CAYAAAAUl4NyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nVb8sOvw1RwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15a51d10>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "====\n",
-      "squareFootage\n",
-      "mean: 1514.5044\n",
-      "std: 830.635998733\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD3CAYAAAAT+Z8iAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nv9UHO4hScAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a1604be10>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "====\n",
-      "lotSize\n",
-      "mean: 5820.7662\n",
-      "std: 3013.27947037\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD3CAYAAAAUl4NyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nygCQpEL9H9MaDj8jYgCcAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15b2ba50>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "====\n",
-      "yearBuilt\n",
-      "mean: 1929.38853333\n",
-      "std: 33.8285343041\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD3CAYAAAAUl4NyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQJIKZQFIUqEsAEkqlAUgSYX6XxI7714SMbWrAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15cd7290>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "====\n",
-      "priorSaleAmount\n",
-      "mean: 195216.200667\n",
-      "std: 313797.906645\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEDCAYAAAA849PJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noSwASSrU/wHIJ++ChH46ewAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15b20850>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "for i in X.columns:\n",
-    "    print  ('====')\n",
-    "    print i\n",
-    "    X.loc[:, i].hist()\n",
-    "    print 'mean:' ,  X.loc[:, i].mean()\n",
-    "    print 'std:' ,  X.loc[:, i].std()\n",
-    "    plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 156,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X2=X[(X.bedrooms<7) & (X.bathrooms< 7)   ] #drop  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 157,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x1a15c86d10>"
-      ]
-     },
-     "execution_count": 157,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAD3CAYAAAAT+Z8iAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15c93050>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "X2.bathrooms.hist()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 134,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "# Outliers \n",
-    "\n",
-    "# 1. Three Sigma Rule:   \n",
-    "# 2. Boxplot Rule:\n",
-    "    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 162,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x1a15b54c90>"
-      ]
-     },
-     "execution_count": 162,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW8AAAD3CAYAAADSftWOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15bd1110>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sns.boxplot(X[['bedrooms', 'bathrooms', 'rooms']])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 165,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x1a15eab3d0>"
-      ]
-     },
-     "execution_count": 165,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAD3CAYAAADyvkg2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWwAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x1a15c09dd0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sns.boxplot(X[['lotSize']])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 124,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "#Mahalanobis Rule  "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 131,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "def MahalanobisDist(x, y):\n",
-    "    covariance_xy = np.cov(x,y, rowvar=0)\n",
-    "    inv_covariance_xy = np.linalg.inv(covariance_xy)\n",
-    "    xy_mean = np.mean(x),np.mean(y)\n",
-    "    x_diff = np.array([x_i - xy_mean[0] for x_i in x])\n",
-    "    y_diff = np.array([y_i - xy_mean[1] for y_i in y])\n",
-    "    diff_xy = np.transpose([x_diff, y_diff])\n",
-    "    \n",
-    "    md = []\n",
-    "    for i in range(len(diff_xy)):\n",
-    "        md.append(np.sqrt(np.dot(np.dot(np.transpose(diff_xy[i]),inv_covariance_xy),diff_xy[i])))\n",
-    "    return md"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 133,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[0.29907509139050276,\n",
-       " 0.46486017984700306,\n",
-       " 1.4436650807702445,\n",
-       " 1.1015699997639492,\n",
-       " 2.0068484330525269,\n",
-       " 1.6628011461732402,\n",
-       " 2.0775848572441347,\n",
-       " 0.46486017984700306,\n",
-       " 1.2045428522263557,\n",
-       " 1.2732274657026237]"
-      ]
-     },
-     "execution_count": 133,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# as column vectors\n",
-    "x = np.random.poisson(5,10)\n",
-    "y = np.random.poisson(5,10)\n",
-    "MahalanobisDist(x,y)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Section 2.4 Dimensionality reduction"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Curse of dimensionality: \"As the number of features or dimensions grows, the amount of data we need to generalize accurately grows exponentially\" "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 116,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "from sklearn.decomposition import PCA "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 117,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "pca = PCA(4) "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 167,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(15000, 7)"
-      ]
-     },
-     "execution_count": 167,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X.shape "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 168,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X_transformed = pca.fit_transform(X)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 169,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(15000, 4)"
-      ]
-     },
-     "execution_count": 169,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "X_transformed.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 171,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([  4.34835866e-07,   1.39033126e-06,   1.76645671e-06,\n",
-       "         9.91884229e-04,   1.22556479e-03,   8.13159056e-06,\n",
-       "         9.99998757e-01])"
-      ]
-     },
-     "execution_count": 171,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "pca.components_[0] "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 174,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "lg=LinearRegression()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 175,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "X_train, X_test, y_train, y_test= train_test_split(X_transformed, y)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 176,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
-      ]
-     },
-     "execution_count": 176,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "lg.fit(X_train, y_train)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 177,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0.70664730600167636"
-      ]
-     },
-     "execution_count": 177,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "lg.score(X_test, y_test) "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Seciton 2.5 Dimensionality reduction Continued : PCA"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## What is Principal Components Analysis (PCA)?\n",
-    "\n",
-    "PCA is a complexity-reduction technique that tries to reduce a set of variables down to a smaller set of components that represent most of the information in the variables.  At a conceptual level, PCA works by identifying sets of variables that share variance, and creating a component to represent that variance.  For example, the two images below represent the two different ways of sharing variance across three variables.  In each, overlapping areas represent shared variance.  \n",
-    "\n",
-    "![PCA example](pca_pic.png)\n",
-    "\n",
-    "A PCA of set A would probably result in one component representing the variance shared by all three, discarding the rest of the information in the circles.  A PCA of set B, on the other hand, would probably result in two components, one representing the overlapping area shared by magenta and cyan, and one representing the variance in yellow not already included in the magenta/cyan component.  In both cases, some variance is lost.\n",
-    "\n",
-    "## Why PCA?\n",
-    "Losing variance in exchange for a smaller set of features can be worthwhile. Some model types (such as regression) assume that features will be uncorrelated with each other, and high levels of inter-feature correlation create unstable solutions. Solutions with fewer features are easier to understand and are more computationally efficient. Solutions with fewer features are also less vulnerable to overfitting.\n",
-    "\n",
-    "Curse of dimensionality: \n",
-    "Working with data becomes more demanding as the number of dimensions increases. \n",
-    "![CurseofDimensionality](curse_of_dimensionality.png)\n",
-    "\n",
-    "With n = 1, there are only 5 boxes to search. With n = 2, there are now 25 boxes; and with n = 3, there are 125 boxes to search. As n gets bigger, it becomes difficult to sample all the boxes. This makes the treasure harder to find — especially as many of the boxes are likely to be empty!\n",
-    "In general, with n dimensions each allowing for m states, we will have m^n possible combinations. Try plugging in a few different values and you will be convinced that this presents a workload-versus-sampling challenge to machines tasked with repeatedly sampling different combinations of variables.\n",
-    "With high-dimensional data, we simply cannot comprehensively sample all the possible combinations, leaving vast regions of feature space in the dark."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "import seaborn as sns\n",
-    "import math\n",
-    "from matplotlib.mlab import PCA as mlabPCA\n",
-    "from sklearn.preprocessing import StandardScaler\n",
-    "from sklearn.decomposition import PCA "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "  cntry  idno  year  tvtot  ppltrst  pplfair  pplhlp  happy  sclmeet  sclact  \\\n",
-      "0    CH   5.0     6    3.0      3.0     10.0     5.0    8.0      5.0     4.0   \n",
-      "1    CH  25.0     6    6.0      5.0      7.0     5.0    9.0      3.0     2.0   \n",
-      "\n",
-      "   gndr  agea  partner  \n",
-      "0   2.0  60.0      1.0  \n",
-      "1   2.0  59.0      1.0  \n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAETCAYAAADah9Z7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n4Ggi/H/ntXseTnJxJgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x11ccd0250>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAETCAYAAADah9Z7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkGghSKMvISEh0UL4/0hovGGPhukpAAAAAElFTkSuQmCC\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x110aa6610>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Make the scatterplot matrix.\n",
-    "\n",
-    "# Setting the default plot aesthetics to be prettier.\n",
-    "sns.set_style(\"white\")\n",
-    "\n",
-    "df = pd.read_csv('ESSdata.csv')\n",
-    "\n",
-    "print df.head(2)\n",
-    "\n",
-    "# Take a subset of the data for PCA. This limits to Swiss and Czech data from 2012\n",
-    "# and keeps only specific columns.\n",
-    "df_pca = df.loc[\n",
-    "    ((df['cntry'] == 'CZ') | (df['cntry'] == 'CH')) & (df['year'] == 6),\n",
-    "    ['tvtot','ppltrst','pplfair','pplhlp']\n",
-    "].dropna()\n",
-    "\n",
-    "t = sns.regplot(\n",
-    "    'ppltrst',\n",
-    "    'pplfair',\n",
-    "    df_pca,\n",
-    "    x_jitter=.49,\n",
-    "    y_jitter=.49,\n",
-    "    fit_reg=False\n",
-    ")\n",
-    "t.set(xlim=(-1, 11), ylim=(-1, 11))\n",
-    "t.axhline(0, color='k', linestyle='-', linewidth=2)\n",
-    "t.axvline(0, color='k', linestyle='-', linewidth=2)\n",
-    "t.axes.set_title('Raw data')\n",
-    "plt.show()\n",
-    "\n",
-    "# Standardizing variables by subtracting the mean and dividing by the standard\n",
-    "# deviation. Now both variables are on the same scale.\n",
-    "df_pca['ppltrst_z'] = (df_pca['ppltrst'] - df_pca['ppltrst'].mean()) / df_pca['ppltrst'].std()\n",
-    "df_pca['pplfair_z'] = (df_pca['pplfair'] - df_pca['pplfair'].mean()) / df_pca['pplfair'].std()\n",
-    "\n",
-    "t = sns.regplot(\n",
-    "    'ppltrst_z',\n",
-    "    'pplfair_z',\n",
-    "    df_pca,\n",
-    "    x_jitter=.49,\n",
-    "    y_jitter=.49,\n",
-    "    fit_reg=False\n",
-    ")\n",
-    "t.axhline(0, color='k', linestyle='-', linewidth=2)\n",
-    "t.axvline(0, color='k', linestyle='-', linewidth=2)\n",
-    "t.axes.set_title('Standardized data')\n",
-    "plt.show()\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "In the plot above, both axes describe equal variance- they both run from about -3 to 2.5.  If we were to drop one of the axes and describe the data using only the information from the other axis, we would lose roughly 50% of our information. \n",
-    "\n",
-    "However, if we fit a line through the origin that minimizes the distance between the line and each point and then rotate the data, our axes and their information value will change.\n",
-    "\n",
-    "<IMG SRC='pca_vector.png'>\n",
-    "\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## The Math Behind PCA\n",
-    "The \"rotation\" pictured above is based on calculating the covariance matrix of the data and applying a linear transformation (rotation) and deriving from that the eigenvalues and eigenvectors that express the amount of variance in the data explained by the new axes.  To explore this further, let's delve into some linear algebra.\n",
-    "\n",
-    "## Covariance matrix\n",
-    "A correlation matrix, which we have discussed before, is a covariance matrix where the covariances have been divided by the variances.  This standardizes the covariances so that they are all on the same scale (-1 to 1) and can be compared.  Covariance matrices, like correlation matrices, contain information about the amount of variance shared between pairs of variables.\n",
-    "\n",
-    "The variance of x is the sum of the squared differences between each value in x ($x_i$) and the mean of x ($\\bar{x}$), divided by the sample size (*n*).\n",
-    "\n",
-    "$$var(x)=\\frac{\\sum(x_i-\\bar{x})^2}n$$\n",
-    "\n",
-    "(Note that the standard deviation is $\\sqrt{var(x)}$)\n",
-    "\n",
-    "The covariance between two variables x and y is the product of the differences of each variable value and its mean, divided by the sample size.\n",
-    "\n",
-    "$$cov(A)=\\sum\\frac{(x_i-\\bar{x})(y_i-\\bar{y})}n$$\n",
-    "\n",
-    "Here is the covariance matrix for the ESS data:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Covariance Matrix:\n",
-      "[[ 1.00071174 -0.24535312 -0.23531159 -0.17820482]\n",
-      " [-0.24535312  1.00071174  0.60528939  0.49609931]\n",
-      " [-0.23531159  0.60528939  1.00071174  0.53193085]\n",
-      " [-0.17820482  0.49609931  0.53193085  1.00071174]]\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Take a subset of the data for PCA and drop missing values because PCA cannot\n",
-    "# handle them. We could also impute, but missingness is quite low so dropping\n",
-    "# missing rows is unlikely to create bias.\n",
-    "df_pca = df.loc[\n",
-    "    ((df['cntry'] == 'CZ') | (df['cntry'] == 'CH')) & (df['year']==6),\n",
-    "    ['tvtot','ppltrst','pplfair','pplhlp']\n",
-    "].dropna()\n",
-    "\n",
-    "# Normalize the data so that all variables have a mean of 0 and standard deviation\n",
-    "# of 1.\n",
-    "X = StandardScaler().fit_transform(df_pca)\n",
-    "\n",
-    "# The NumPy covariance function assumes that variables are represented by rows,\n",
-    "# not columns, so we transpose X.\n",
-    "Xt = X.T\n",
-    "Cx = np.cov(Xt)\n",
-    "print 'Covariance Matrix:\\n', Cx"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Eigenvectors\n",
-    "An Eigenvector is the directional aspect of a component – it is the red line in the graph earlier.  During PCA, the eigenvectors are chosen to be orthogonal, that is, to have a correlation of 0 with one another.  In fact, this is done sequentially.  First, a vector is found that minimizes the distance between that vector and the datapoints. This vector is the first component. Next, a second vector is found that also minimizes the distance between that vector and the datapoints, the catch being that this second vector must be perpendicular to the first in one of the n dimensions of the space. This procedure continues until there are n vectors.\n",
-    "\n",
-    "## Eigenvalues\n",
-    "Eigenvalues represent the length of the Eigenvectors – each eigenvector has an eigenvalue.  The length of the eigenvector encodes the proportion of total variance explained by a component.  The total variance is equal to the number of variables in the PCA.  Thus, an Eigenvalue of 1 means that the component explains the same amount of variance as one variable.  An eigenvalue greater than 1 is desirable, since a component with an eigenvalue of 1 adds no value beyond the information contained in any individual variable, and an eigenvalue of less than 1 is actually less efficient at conveying information than a variable by itself.  An eigenvalue of 2 means that the component contains an amount of information equal to that of two variables.  Of course, it doesn’t mean that only two variables load on that component.\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Eigenvector 1: \n",
-      "[[-0.30084526]\n",
-      " [ 0.55945823]\n",
-      " [ 0.5681188 ]\n",
-      " [ 0.52320135]]\n",
-      "Eigenvalue 1: 2.2112568632\n",
-      "----------------------------------------\n",
-      "Eigenvector 2: \n",
-      "[[ 0.94786152]\n",
-      " [ 0.11600843]\n",
-      " [ 0.15403897]\n",
-      " [ 0.25371751]]\n",
-      "Eigenvalue 2: 0.884741357071\n",
-      "----------------------------------------\n",
-      "Eigenvector 3: \n",
-      "[[ 0.10491426]\n",
-      " [ 0.51597659]\n",
-      " [ 0.28505945]\n",
-      " [-0.80093836]]\n",
-      "Eigenvalue 3: 0.515142138924\n",
-      "----------------------------------------\n",
-      "Eigenvector 4: \n",
-      "[[ 0.00660771]\n",
-      " [ 0.63821367]\n",
-      " [-0.75647481]\n",
-      " [ 0.14277786]]\n",
-      "Eigenvalue 4: 0.391706615894\n",
-      "----------------------------------------\n",
-      "The percentage of total variance in the dataset explained by each component calculated by hand \n",
-      "[ 0.55242103  0.22102802  0.12869394  0.097857  ]\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Calculating eigenvalues and eigenvectors.\n",
-    "eig_val_cov, eig_vec_cov = np.linalg.eig(Cx)\n",
-    "\n",
-    "# Inspecting the eigenvalues and eigenvectors.\n",
-    "for i in range(len(eig_val_cov)):\n",
-    "    eigvec_cov = eig_vec_cov[:, i].reshape(1, 4).T\n",
-    "    print('Eigenvector {}: \\n{}'.format(i + 1, eigvec_cov))\n",
-    "    print('Eigenvalue {}: {}'.format(i + 1, eig_val_cov[i]))\n",
-    "    print(40 * '-')\n",
-    "\n",
-    "print 'The percentage of total variance in the dataset explained by each component calculated by hand \\n',  eig_val_cov / sum(eig_val_cov)\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## How many components?\n",
-    "The biggest decision to make when running a PCA is how many components to keep.  PCA will actually give us back as many components as there are variables in the correlation matrix.  If we have n variables and choose to keep n components, we will be able to reproduce 100% of the information in the original data.  On the other hand, we won’t have simplified our situation at all – we’ll still be dealing with the same number of separate pieces of information, just expressed as components instead of as variables.\n",
-    "\n",
-    "There are a number of rules to guide us in choosing the number of components to keep.  The most straightforward is to keep components with eigenvalues greater than 1, as they add value (because they contain more information than a single variable).  This rule tends to keep more components than is ideal.\n",
-    "\n",
-    "Another rule is to visualize the eigenvalues in order from highest to lowest, connecting them with a line. This is called a \"scree\" plot because it supposedly resembles the loose rock that accumulates at the foot of a mountain.  Upon visual inspection, the analyst will keep all the components whose eigenvalue falls above the point where the slope of the line changes the most drastically, also called the \"elbow\".  \n",
-    "\n",
-    "Many other rules also exist, including variance cutoffs where we only keep components that explain at least x% of the variance in the data, and programmatic ones involving simulating the PCA solution on equivalent randomized data.  Ultimately, the choice of how many components to keep comes down to your reasons for doing PCA.\n",
-    "\n",
-    "Let's see how many "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD3CAYAAADmBxSSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nXJDKXUTEBf1/Nc53EflTJaQAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x117bc1a90>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "plt.plot(eig_val_cov)\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The scree plot and the eigenvalues >1 rule agree that we should keep only the first component. "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Summary\n",
-    "\n",
-    "PCA is a series of linear transformations applied to a data frame to yield a smaller number of columns that explain a large proportion of the total variance contained in the data frame."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "collapsed": true
-   },
-   "source": [
-    "# Python Installations"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 1) Install Anaconda \n",
-    "https://www.anaconda.com/download/"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 2) Install Jupyter Notebook \n",
-    "https://jupyter.org/install"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 3) To launch Notebook \n",
-    "### In your terminal, enter\n",
-    "### jupyter notebook "
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 4) Install Python Libraries\n",
-    "### Conda install pandas \n",
-    "### Conda install numpy "
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 2",
-   "language": "python",
-   "name": "python2"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 2
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/Part 4/Section_3.1_3.2.ipynb b/Part 3/Section_3.1_3.2.ipynb
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/Section_3.1_3.2.ipynb
rename to Part 3/Section_3.1_3.2.ipynb
diff --git a/Part 4/assets/spark_ecosystem.png b/Part 3/assets/spark_ecosystem.png
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/assets/spark_ecosystem.png
rename to Part 3/assets/spark_ecosystem.png
diff --git a/Part 4/assets/spark_execution.png b/Part 3/assets/spark_execution.png
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/assets/spark_execution.png
rename to Part 3/assets/spark_execution.png
diff --git a/Part 3/curse_of_dimensionality.png b/Part 3/curse_of_dimensionality.png
deleted file mode 100755
index 3e15858..0000000
Binary files a/Part 3/curse_of_dimensionality.png and /dev/null differ
diff --git a/Part 4/data/AAPL.csv b/Part 3/data/AAPL.csv
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/data/AAPL.csv
rename to Part 3/data/AAPL.csv
diff --git a/Part 3/pca_pic.png b/Part 3/pca_pic.png
deleted file mode 100755
index 7f2a631..0000000
Binary files a/Part 3/pca_pic.png and /dev/null differ
diff --git a/Part 3/pca_vector.png b/Part 3/pca_vector.png
deleted file mode 100755
index be4265c..0000000
Binary files a/Part 3/pca_vector.png and /dev/null differ
diff --git a/Part 4/spark-install/README.md b/Part 3/spark-install/README.md
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/spark-install/README.md
rename to Part 3/spark-install/README.md
diff --git a/Part 4/spark-install/images/spark-install-21.png b/Part 3/spark-install/images/spark-install-21.png
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/spark-install/images/spark-install-21.png
rename to Part 3/spark-install/images/spark-install-21.png
diff --git a/Part 4/spark-install/setup_aws.md b/Part 3/spark-install/setup_aws.md
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/spark-install/setup_aws.md
rename to Part 3/spark-install/setup_aws.md
diff --git a/Part 4/spark-install/spark-install.sh b/Part 3/spark-install/spark-install.sh
old mode 100755
new mode 100644
similarity index 100%
rename from Part 4/spark-install/spark-install.sh
rename to Part 3/spark-install/spark-install.sh
diff --git a/Part 3/svm.png b/Part 3/svm.png
deleted file mode 100755
index da91276..0000000
Binary files a/Part 3/svm.png and /dev/null differ
diff --git a/Part 5/Section-4.ipynb b/Part 4/Section-4.ipynb
old mode 100755
new mode 100644
similarity index 100%
rename from Part 5/Section-4.ipynb
rename to Part 4/Section-4.ipynb
diff --git a/Part 5/test.db b/Part 4/test.db
old mode 100755
new mode 100644
similarity index 100%
rename from Part 5/test.db
rename to Part 4/test.db
diff --git a/Part 6/Section-5 .ipynb b/Part 5/Section-5 .ipynb
old mode 100755
new mode 100644
similarity index 100%
rename from Part 6/Section-5 .ipynb
rename to Part 5/Section-5 .ipynb
diff --git a/Part 6/data/SMSSpamCollection b/Part 5/data/SMSSpamCollection
old mode 100755
new mode 100644
similarity index 100%
rename from Part 6/data/SMSSpamCollection
rename to Part 5/data/SMSSpamCollection