diff --git a/notebooks/intro_data_science/Data_Commons_For_Data_Science_Tutorial.ipynb b/notebooks/intro_data_science/Data_Commons_For_Data_Science_Tutorial.ipynb
index 5f26ac2..7b65833 100644
--- a/notebooks/intro_data_science/Data_Commons_For_Data_Science_Tutorial.ipynb
+++ b/notebooks/intro_data_science/Data_Commons_For_Data_Science_Tutorial.ipynb
@@ -3,10 +3,9 @@
   "nbformat_minor": 0,
   "metadata": {
     "colab": {
-      "name": "Data Commons For Data Science Tutorial.ipynb",
       "provenance": [],
-      "collapsed_sections": [],
       "toc_visible": true,
+      "authorship_tag": "ABX9TyNNd7nKdXr1l2/He/vsSmZZ",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -77,7 +76,7 @@
         "\n",
         "In the graph, [*entities*](https://en.wikipedia.org/wiki/Entity) like [Santa Clara County](https://browser.datacommons.org/kg?dcid=geoId/06085) are represented by nodes. Every node has a type corresponding to what the node represents. For example, [California](https://browser.datacommons.org/kg?dcid=geoId/06) is a [State](https://schema.org/State). *Relations* between entities are represented by edges between these nodes. For example, the statement \"Santa Clara County is contained in the State of California\" is represented in the graph as two nodes: \"Santa Clara County\" and \"California\" with an edge labeled \"[containedInPlace](https://schema.org/containedInPlace)\" pointing from Santa Clara to California. Data Commons closely follows the [Schema.org data model](https://schema.org/docs/datamodel.html) and leverages Schema.org schema to provide a common set of types and properties.\n",
         "\n",
-        " \n",
+        "\n",
         "\n",
         "\n",
         "\n"
@@ -127,20 +126,20 @@
           "base_uri": "https://localhost:8080/"
         },
         "id": "dThSMUJ96vK2",
-        "outputId": "d4b7109e-1c12-4c59-af45-5f03448fdc70"
+        "outputId": "66f1aedb-7e1c-440b-f557-018220f7c132"
       },
       "source": [
         "!pip install datacommons --upgrade --quiet\n",
         "!pip install datacommons_pandas --upgrade --quiet"
       ],
-      "execution_count": null,
+      "execution_count": 1,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
-            "\u001b[K     |████████████████████████████████| 46 kB 2.3 MB/s \n",
-            "\u001b[K     |████████████████████████████████| 45 kB 2.7 MB/s \n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m46.5/46.5 kB\u001b[0m \u001b[31m829.3 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m45.8/45.8 kB\u001b[0m \u001b[31m1.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
             "\u001b[?25h"
           ]
         }
@@ -180,7 +179,7 @@
         "import datacommons\n",
         "import datacommons_pandas"
       ],
-      "execution_count": null,
+      "execution_count": 2,
       "outputs": []
     },
     {
@@ -192,7 +191,7 @@
         "# Terms You Should Know\n",
         "\n",
         "### DCIDs\n",
-        "The **`dcid`** (Data Commons identifier) is a unique identifier assigned to each entity in the knowledge graph. With this identifier, you will be able to search for and query information on the given entity in ways that we will discuss later. \n",
+        "The **`dcid`** (Data Commons identifier) is a unique identifier assigned to each entity in the knowledge graph. With this identifier, you will be able to search for and query information on the given entity in ways that we will discuss later.\n",
         "\n",
         "\n",
         "### Statistical Variables (StatVars)\n",
@@ -232,7 +231,7 @@
         "         \"geoId/065300\",   # Oakland\n",
         "         \"geoId/0644000\"]  # Los Angeles"
       ],
-      "execution_count": null,
+      "execution_count": 3,
       "outputs": []
     },
     {
@@ -259,7 +258,7 @@
         "dcid_of_california = \"geoId/06\"\n",
         "dcids = datacommons.get_places_in([dcid_of_california], \"County\")[dcid_of_california]"
       ],
-      "execution_count": null,
+      "execution_count": 4,
       "outputs": []
     },
     {
@@ -287,7 +286,7 @@
         "                                             \"member\",\n",
         "                                             limit=500)[\"CDC500_City\"]"
       ],
-      "execution_count": null,
+      "execution_count": 5,
       "outputs": []
     },
     {
@@ -299,7 +298,7 @@
         "## 2) Get StatVars of Interest\n",
         "Similar to collecting a list of dcids, we also need a list of all the statistical variables we are interested in.\n",
         "\n",
-        "A complete list of Statistical Variables can be found [here](https://docs.datacommons.org/statistical_variables.html). \n",
+        "A complete list of Statistical Variables can be found [here](https://docs.datacommons.org/statistical_variables.html).\n",
         "\n",
         "However, note that data for statistical variables may not be available for all places/entities. To check if a statistical variable is available for an entity, look at the bottom of the graph browser page for that entity for a list of the statistical variables available for that entity.\n",
         "\n",
@@ -312,14 +311,14 @@
         "id": "1b-Z3IEY_DpE"
       },
       "source": [
-        "stat_vars_to_query = [\"CumulativeCount_MedicalTest_ConditionCOVID_19_Positive\",\n",
+        "stat_vars_to_query = [\"Count_MortalityEvent_COVID19\",\n",
         "                      \"Count_Person\",\n",
         "                      \"Median_Income_Person\",\n",
         "                      \"Percent_Person_Obesity\",\n",
         "                      \"Amount_Emissions_CarbonDioxide_PerCapita\"\n",
         "                      ]"
       ],
-      "execution_count": null,
+      "execution_count": 14,
       "outputs": []
     },
     {
@@ -351,22 +350,147 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 450
+          "height": 1000
         },
         "id": "Qvmu77TI_Kia",
-        "outputId": "ded73938-4e73-484c-bfba-6fa93ec2d8da"
+        "outputId": "7a306d7c-912c-4f48-8f9b-cdd125a4846d"
       },
       "source": [
         "df = datacommons_pandas.build_multivariate_dataframe(dcids,stat_vars_to_query)\n",
         "display(df)"
       ],
-      "execution_count": null,
+      "execution_count": 15,
       "outputs": [
         {
           "output_type": "display_data",
           "data": {
+            "text/plain": [
+              "             Percent_Person_Obesity  Count_MortalityEvent_COVID19  \\\n",
+              "place                                                               \n",
+              "geoId/06001                    25.1                         635.0   \n",
+              "geoId/06003                    29.1                           NaN   \n",
+              "geoId/06005                    29.7                          19.0   \n",
+              "geoId/06007                    29.7                         132.0   \n",
+              "geoId/06009                    30.6                          17.0   \n",
+              "geoId/06011                    33.1                          15.0   \n",
+              "geoId/06013                    24.6                         422.0   \n",
+              "geoId/06015                    32.8                           NaN   \n",
+              "geoId/06017                    28.4                          72.0   \n",
+              "geoId/06019                    36.6                         937.0   \n",
+              "geoId/06021                    31.5                          22.0   \n",
+              "geoId/06023                    32.5                          23.0   \n",
+              "geoId/06025                    37.5                         529.0   \n",
+              "geoId/06027                    29.3                          28.0   \n",
+              "geoId/06029                    36.4                         678.0   \n",
+              "geoId/06031                    34.8                         113.0   \n",
+              "geoId/06033                    33.7                          39.0   \n",
+              "geoId/06035                    32.0                          16.0   \n",
+              "geoId/06037                    28.5                       11176.0   \n",
+              "geoId/06039                    35.7                         170.0   \n",
+              "geoId/06041                    23.1                         114.0   \n",
+              "geoId/06043                    29.7                           NaN   \n",
+              "geoId/06045                    31.4                          35.0   \n",
+              "geoId/06047                    32.5                         260.0   \n",
+              "geoId/06049                    32.7                           NaN   \n",
+              "geoId/06051                    29.8                           NaN   \n",
+              "geoId/06053                    27.3                         256.0   \n",
+              "geoId/06055                    27.8                          38.0   \n",
+              "geoId/06057                    27.6                          63.0   \n",
+              "geoId/06059                    25.4                        2459.0   \n",
+              "geoId/06061                    26.5                         157.0   \n",
+              "geoId/06063                    29.4                           NaN   \n",
+              "geoId/06065                    36.0                        2657.0   \n",
+              "geoId/06067                    31.9                         948.0   \n",
+              "geoId/06069                    31.1                          32.0   \n",
+              "geoId/06071                    38.1                        2747.0   \n",
+              "geoId/06073                    23.7                        1748.0   \n",
+              "geoId/06075                    18.8                         222.0   \n",
+              "geoId/06077                    33.3                         793.0   \n",
+              "geoId/06079                    29.0                         116.0   \n",
+              "geoId/06081                    21.3                         248.0   \n",
+              "geoId/06083                    28.6                         177.0   \n",
+              "geoId/06085                    18.7                         852.0   \n",
+              "geoId/06087                    24.3                         122.0   \n",
+              "geoId/06089                    30.9                         102.0   \n",
+              "geoId/06091                    30.0                           NaN   \n",
+              "geoId/06093                    32.6                          14.0   \n",
+              "geoId/06095                    29.9                         171.0   \n",
+              "geoId/06097                    28.6                         196.0   \n",
+              "geoId/06099                    34.7                         634.0   \n",
+              "geoId/06101                    31.4                          62.0   \n",
+              "geoId/06103                    34.0                          44.0   \n",
+              "geoId/06105                    33.2                           NaN   \n",
+              "geoId/06107                    35.2                         451.0   \n",
+              "geoId/06109                    29.2                          33.0   \n",
+              "geoId/06111                    26.9                         376.0   \n",
+              "geoId/06113                    25.8                         110.0   \n",
+              "geoId/06115                    33.9                          29.0   \n",
+              "\n",
+              "             Count_Person  Median_Income_Person  \n",
+              "place                                            \n",
+              "geoId/06001       1663823                 54302  \n",
+              "geoId/06003          1515                 31071  \n",
+              "geoId/06005         40577                 38576  \n",
+              "geoId/06007        213605                 31677  \n",
+              "geoId/06009         45674                 34144  \n",
+              "geoId/06011         21811                 34163  \n",
+              "geoId/06013       1162648                 51100  \n",
+              "geoId/06015         27462                 28389  \n",
+              "geoId/06017        191713                 45916  \n",
+              "geoId/06019       1008280                 31853  \n",
+              "geoId/06021         28657                 30869  \n",
+              "geoId/06023        136132                 29264  \n",
+              "geoId/06025        179578                 23080  \n",
+              "geoId/06027         18829                 37827  \n",
+              "geoId/06029        906883                 29192  \n",
+              "geoId/06031        152515                 32984  \n",
+              "geoId/06033         68024                 30364  \n",
+              "geoId/06035         31873                 33358  \n",
+              "geoId/06037       9936690                 35869  \n",
+              "geoId/06039        157243                 29150  \n",
+              "geoId/06041        260485                 63765  \n",
+              "geoId/06043         17130                 33425  \n",
+              "geoId/06045         91145                 32446  \n",
+              "geoId/06047        282290                 30037  \n",
+              "geoId/06049          8651                 30115  \n",
+              "geoId/06051         13219                 45331  \n",
+              "geoId/06053        437609                 34979  \n",
+              "geoId/06055        137384                 45288  \n",
+              "geoId/06057        102322                 37964  \n",
+              "geoId/06059       3175227                 44190  \n",
+              "geoId/06061        406608                 50615  \n",
+              "geoId/06063         19650                 39176  \n",
+              "geoId/06065       2429487                 35607  \n",
+              "geoId/06067       1579211                 40179  \n",
+              "geoId/06069         64753                 41870  \n",
+              "geoId/06071       2180563                 34107  \n",
+              "geoId/06073       3289701                 42349  \n",
+              "geoId/06075        851036                 65802  \n",
+              "geoId/06077        779445                 36016  \n",
+              "geoId/06079        281712                 38724  \n",
+              "geoId/06081        754250                 59975  \n",
+              "geoId/06083        445213                 36135  \n",
+              "geoId/06085       1916831                 59207  \n",
+              "geoId/06087        268571                 41634  \n",
+              "geoId/06089        181852                 33097  \n",
+              "geoId/06091          2916                 23897  \n",
+              "geoId/06093         44049                 29476  \n",
+              "geoId/06095        450995                 43831  \n",
+              "geoId/06097        488436                 45670  \n",
+              "geoId/06099        552063                 34223  \n",
+              "geoId/06101         99101                 32987  \n",
+              "geoId/06103         65484                 30450  \n",
+              "geoId/06105         15889                 30800  \n",
+              "geoId/06107        473446                 29304  \n",
+              "geoId/06109         54993                 34956  \n",
+              "geoId/06111        842009                 40855  \n",
+              "geoId/06113        217141                 37622  \n",
+              "geoId/06115         81705                 32074  "
+            ],
             "text/html": [
-              "<div>\n",
+              "\n",
+              "  <div id=\"df-af062e9b-287c-4318-9edf-0da9f57cf075\" class=\"colab-df-container\">\n",
+              "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -384,10 +508,10 @@
               "  <thead>\n",
               "    <tr style=\"text-align: right;\">\n",
               "      <th></th>\n",
+              "      <th>Percent_Person_Obesity</th>\n",
+              "      <th>Count_MortalityEvent_COVID19</th>\n",
               "      <th>Count_Person</th>\n",
               "      <th>Median_Income_Person</th>\n",
-              "      <th>Percent_Person_Obesity</th>\n",
-              "      <th>CumulativeCount_MedicalTest_ConditionCOVID_19_Positive</th>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>place</th>\n",
@@ -399,104 +523,684 @@
               "  </thead>\n",
               "  <tbody>\n",
               "    <tr>\n",
-              "      <th>geoId/0107000</th>\n",
-              "      <td>200733</td>\n",
-              "      <td>22646</td>\n",
-              "      <td>42.0</td>\n",
-              "      <td>NaN</td>\n",
+              "      <th>geoId/06001</th>\n",
+              "      <td>25.1</td>\n",
+              "      <td>635.0</td>\n",
+              "      <td>1663823</td>\n",
+              "      <td>54302</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0135896</th>\n",
-              "      <td>92606</td>\n",
-              "      <td>44843</td>\n",
-              "      <td>28.4</td>\n",
+              "      <th>geoId/06003</th>\n",
+              "      <td>29.1</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>1515</td>\n",
+              "      <td>31071</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0137000</th>\n",
-              "      <td>215006</td>\n",
-              "      <td>30079</td>\n",
-              "      <td>36.2</td>\n",
-              "      <td>NaN</td>\n",
+              "      <th>geoId/06005</th>\n",
+              "      <td>29.7</td>\n",
+              "      <td>19.0</td>\n",
+              "      <td>40577</td>\n",
+              "      <td>38576</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06007</th>\n",
+              "      <td>29.7</td>\n",
+              "      <td>132.0</td>\n",
+              "      <td>213605</td>\n",
+              "      <td>31677</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06009</th>\n",
+              "      <td>30.6</td>\n",
+              "      <td>17.0</td>\n",
+              "      <td>45674</td>\n",
+              "      <td>34144</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0150000</th>\n",
-              "      <td>187041</td>\n",
-              "      <td>25083</td>\n",
-              "      <td>38.2</td>\n",
+              "      <th>geoId/06011</th>\n",
+              "      <td>33.1</td>\n",
+              "      <td>15.0</td>\n",
+              "      <td>21811</td>\n",
+              "      <td>34163</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06013</th>\n",
+              "      <td>24.6</td>\n",
+              "      <td>422.0</td>\n",
+              "      <td>1162648</td>\n",
+              "      <td>51100</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06015</th>\n",
+              "      <td>32.8</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>27462</td>\n",
+              "      <td>28389</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0151000</th>\n",
-              "      <td>200603</td>\n",
-              "      <td>25725</td>\n",
+              "      <th>geoId/06017</th>\n",
+              "      <td>28.4</td>\n",
+              "      <td>72.0</td>\n",
+              "      <td>191713</td>\n",
+              "      <td>45916</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06019</th>\n",
+              "      <td>36.6</td>\n",
+              "      <td>937.0</td>\n",
+              "      <td>1008280</td>\n",
+              "      <td>31853</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06021</th>\n",
+              "      <td>31.5</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>28657</td>\n",
+              "      <td>30869</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06023</th>\n",
+              "      <td>32.5</td>\n",
+              "      <td>23.0</td>\n",
+              "      <td>136132</td>\n",
+              "      <td>29264</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06025</th>\n",
+              "      <td>37.5</td>\n",
+              "      <td>529.0</td>\n",
+              "      <td>179578</td>\n",
+              "      <td>23080</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06027</th>\n",
+              "      <td>29.3</td>\n",
+              "      <td>28.0</td>\n",
+              "      <td>18829</td>\n",
+              "      <td>37827</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06029</th>\n",
+              "      <td>36.4</td>\n",
+              "      <td>678.0</td>\n",
+              "      <td>906883</td>\n",
+              "      <td>29192</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06031</th>\n",
+              "      <td>34.8</td>\n",
+              "      <td>113.0</td>\n",
+              "      <td>152515</td>\n",
+              "      <td>32984</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06033</th>\n",
+              "      <td>33.7</td>\n",
               "      <td>39.0</td>\n",
+              "      <td>68024</td>\n",
+              "      <td>30364</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06035</th>\n",
+              "      <td>32.0</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>31873</td>\n",
+              "      <td>33358</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06037</th>\n",
+              "      <td>28.5</td>\n",
+              "      <td>11176.0</td>\n",
+              "      <td>9936690</td>\n",
+              "      <td>35869</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06039</th>\n",
+              "      <td>35.7</td>\n",
+              "      <td>170.0</td>\n",
+              "      <td>157243</td>\n",
+              "      <td>29150</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06041</th>\n",
+              "      <td>23.1</td>\n",
+              "      <td>114.0</td>\n",
+              "      <td>260485</td>\n",
+              "      <td>63765</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06043</th>\n",
+              "      <td>29.7</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>17130</td>\n",
+              "      <td>33425</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
+              "      <th>geoId/06045</th>\n",
+              "      <td>31.4</td>\n",
+              "      <td>35.0</td>\n",
+              "      <td>91145</td>\n",
+              "      <td>32446</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5548000</th>\n",
-              "      <td>269840</td>\n",
-              "      <td>32949</td>\n",
-              "      <td>27.5</td>\n",
+              "      <th>geoId/06047</th>\n",
+              "      <td>32.5</td>\n",
+              "      <td>260.0</td>\n",
+              "      <td>282290</td>\n",
+              "      <td>30037</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06049</th>\n",
+              "      <td>32.7</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>8651</td>\n",
+              "      <td>30115</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5553000</th>\n",
-              "      <td>577222</td>\n",
-              "      <td>25266</td>\n",
-              "      <td>36.2</td>\n",
+              "      <th>geoId/06051</th>\n",
+              "      <td>29.8</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>13219</td>\n",
+              "      <td>45331</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06053</th>\n",
+              "      <td>27.3</td>\n",
+              "      <td>256.0</td>\n",
+              "      <td>437609</td>\n",
+              "      <td>34979</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06055</th>\n",
+              "      <td>27.8</td>\n",
+              "      <td>38.0</td>\n",
+              "      <td>137384</td>\n",
+              "      <td>45288</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06057</th>\n",
+              "      <td>27.6</td>\n",
+              "      <td>63.0</td>\n",
+              "      <td>102322</td>\n",
+              "      <td>37964</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06059</th>\n",
+              "      <td>25.4</td>\n",
+              "      <td>2459.0</td>\n",
+              "      <td>3175227</td>\n",
+              "      <td>44190</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5566000</th>\n",
-              "      <td>77816</td>\n",
-              "      <td>25366</td>\n",
-              "      <td>40.2</td>\n",
+              "      <th>geoId/06061</th>\n",
+              "      <td>26.5</td>\n",
+              "      <td>157.0</td>\n",
+              "      <td>406608</td>\n",
+              "      <td>50615</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06063</th>\n",
+              "      <td>29.4</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>19650</td>\n",
+              "      <td>39176</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5584250</th>\n",
-              "      <td>71158</td>\n",
-              "      <td>33972</td>\n",
-              "      <td>31.5</td>\n",
+              "      <th>geoId/06065</th>\n",
+              "      <td>36.0</td>\n",
+              "      <td>2657.0</td>\n",
+              "      <td>2429487</td>\n",
+              "      <td>35607</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06067</th>\n",
+              "      <td>31.9</td>\n",
+              "      <td>948.0</td>\n",
+              "      <td>1579211</td>\n",
+              "      <td>40179</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06069</th>\n",
+              "      <td>31.1</td>\n",
+              "      <td>32.0</td>\n",
+              "      <td>64753</td>\n",
+              "      <td>41870</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06071</th>\n",
+              "      <td>38.1</td>\n",
+              "      <td>2747.0</td>\n",
+              "      <td>2180563</td>\n",
+              "      <td>34107</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06073</th>\n",
+              "      <td>23.7</td>\n",
+              "      <td>1748.0</td>\n",
+              "      <td>3289701</td>\n",
+              "      <td>42349</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06075</th>\n",
+              "      <td>18.8</td>\n",
+              "      <td>222.0</td>\n",
+              "      <td>851036</td>\n",
+              "      <td>65802</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06077</th>\n",
+              "      <td>33.3</td>\n",
+              "      <td>793.0</td>\n",
+              "      <td>779445</td>\n",
+              "      <td>36016</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06079</th>\n",
+              "      <td>29.0</td>\n",
+              "      <td>116.0</td>\n",
+              "      <td>281712</td>\n",
+              "      <td>38724</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06081</th>\n",
+              "      <td>21.3</td>\n",
+              "      <td>248.0</td>\n",
+              "      <td>754250</td>\n",
+              "      <td>59975</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06083</th>\n",
+              "      <td>28.6</td>\n",
+              "      <td>177.0</td>\n",
+              "      <td>445213</td>\n",
+              "      <td>36135</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06085</th>\n",
+              "      <td>18.7</td>\n",
+              "      <td>852.0</td>\n",
+              "      <td>1916831</td>\n",
+              "      <td>59207</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06087</th>\n",
+              "      <td>24.3</td>\n",
+              "      <td>122.0</td>\n",
+              "      <td>268571</td>\n",
+              "      <td>41634</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06089</th>\n",
+              "      <td>30.9</td>\n",
+              "      <td>102.0</td>\n",
+              "      <td>181852</td>\n",
+              "      <td>33097</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06091</th>\n",
+              "      <td>30.0</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>2916</td>\n",
+              "      <td>23897</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5613900</th>\n",
-              "      <td>65132</td>\n",
-              "      <td>35481</td>\n",
-              "      <td>29.4</td>\n",
+              "      <th>geoId/06093</th>\n",
+              "      <td>32.6</td>\n",
+              "      <td>14.0</td>\n",
+              "      <td>44049</td>\n",
+              "      <td>29476</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06095</th>\n",
+              "      <td>29.9</td>\n",
+              "      <td>171.0</td>\n",
+              "      <td>450995</td>\n",
+              "      <td>43831</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06097</th>\n",
+              "      <td>28.6</td>\n",
+              "      <td>196.0</td>\n",
+              "      <td>488436</td>\n",
+              "      <td>45670</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06099</th>\n",
+              "      <td>34.7</td>\n",
+              "      <td>634.0</td>\n",
+              "      <td>552063</td>\n",
+              "      <td>34223</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06101</th>\n",
+              "      <td>31.4</td>\n",
+              "      <td>62.0</td>\n",
+              "      <td>99101</td>\n",
+              "      <td>32987</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06103</th>\n",
+              "      <td>34.0</td>\n",
+              "      <td>44.0</td>\n",
+              "      <td>65484</td>\n",
+              "      <td>30450</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06105</th>\n",
+              "      <td>33.2</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>15889</td>\n",
+              "      <td>30800</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06107</th>\n",
+              "      <td>35.2</td>\n",
+              "      <td>451.0</td>\n",
+              "      <td>473446</td>\n",
+              "      <td>29304</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06109</th>\n",
+              "      <td>29.2</td>\n",
+              "      <td>33.0</td>\n",
+              "      <td>54993</td>\n",
+              "      <td>34956</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06111</th>\n",
+              "      <td>26.9</td>\n",
+              "      <td>376.0</td>\n",
+              "      <td>842009</td>\n",
+              "      <td>40855</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06113</th>\n",
+              "      <td>25.8</td>\n",
+              "      <td>110.0</td>\n",
+              "      <td>217141</td>\n",
+              "      <td>37622</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06115</th>\n",
+              "      <td>33.9</td>\n",
+              "      <td>29.0</td>\n",
+              "      <td>81705</td>\n",
+              "      <td>32074</td>\n",
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n",
-              "<p>499 rows × 4 columns</p>\n",
-              "</div>"
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-af062e9b-287c-4318-9edf-0da9f57cf075')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-af062e9b-287c-4318-9edf-0da9f57cf075 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-af062e9b-287c-4318-9edf-0da9f57cf075');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-fc179429-d509-4235-bdb3-3b02b3354c57\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fc179429-d509-4235-bdb3-3b02b3354c57')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-fc179429-d509-4235-bdb3-3b02b3354c57 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_8c1c4cc7-a548-4a89-b5a6-618594e6b51b\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_8c1c4cc7-a548-4a89-b5a6-618594e6b51b button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
             ],
-            "text/plain": [
-              "               Count_Person  ...  CumulativeCount_MedicalTest_ConditionCOVID_19_Positive\n",
-              "place                        ...                                                        \n",
-              "geoId/0107000        200733  ...                                                NaN     \n",
-              "geoId/0135896         92606  ...                                                NaN     \n",
-              "geoId/0137000        215006  ...                                                NaN     \n",
-              "geoId/0150000        187041  ...                                                NaN     \n",
-              "geoId/0151000        200603  ...                                                NaN     \n",
-              "...                     ...  ...                                                ...     \n",
-              "geoId/5548000        269840  ...                                                NaN     \n",
-              "geoId/5553000        577222  ...                                                NaN     \n",
-              "geoId/5566000         77816  ...                                                NaN     \n",
-              "geoId/5584250         71158  ...                                                NaN     \n",
-              "geoId/5613900         65132  ...                                                NaN     \n",
-              "\n",
-              "[499 rows x 4 columns]"
-            ]
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 58,\n  \"fields\": [\n    {\n      \"column\": \"place\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 58,\n        \"samples\": [\n          \"geoId/06001\",\n          \"geoId/06011\",\n          \"geoId/06069\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Percent_Person_Obesity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4.323152333425648,\n        \"min\": 18.7,\n        \"max\": 38.1,\n        \"num_unique_values\": 53,\n        \"samples\": [\n          23.1,\n          30.9,\n          33.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Count_MortalityEvent_COVID19\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1658.130465436349,\n        \"min\": 14.0,\n        \"max\": 11176.0,\n        \"num_unique_values\": 50,\n        \"samples\": [\n          113.0,\n          14.0,\n          1748.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Count_Person\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1453959,\n        \"min\": 1515,\n        \"max\": 9936690,\n        \"num_unique_values\": 58,\n        \"samples\": [\n          1663823,\n          21811,\n          64753\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Median_Income_Person\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9335,\n        \"min\": 23080,\n        \"max\": 65802,\n        \"num_unique_values\": 58,\n        \"samples\": [\n          54302,\n          34163,\n          41870\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
           },
           "metadata": {}
         }
@@ -508,7 +1212,7 @@
         "id": "xza-1c15RZ-R"
       },
       "source": [
-        "Further data cleaning or joining is usually not necessary, but you may choose to further process your data frame for better readability or to better suit your particular data science task. \n",
+        "Further data cleaning or joining is usually not necessary, but you may choose to further process your data frame for better readability or to better suit your particular data science task.\n",
         "\n",
         "Because the Data Commons API returns a Pandas Dataframe, you are free to use any functions found in [Pandas' Documentation](https://pandas.pydata.org/docs/reference/frame.html) to edit your dataframe."
       ]
@@ -528,22 +1232,147 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 450
+          "height": 1000
         },
         "id": "SioY7DRTAxi6",
-        "outputId": "4cf347d4-f959-47d7-b88d-42bfb9d4be90"
+        "outputId": "85c8cc7d-ff6f-4470-d60e-64f7b43c923f"
       },
       "source": [
         "df.insert(0, 'name', df.index.map(datacommons.get_property_values(df.index, 'name')).str[0])\n",
         "display(df)"
       ],
-      "execution_count": null,
+      "execution_count": 16,
       "outputs": [
         {
           "output_type": "display_data",
           "data": {
+            "text/plain": [
+              "                               name  Percent_Person_Obesity  \\\n",
+              "place                                                         \n",
+              "geoId/06001          Alameda County                    25.1   \n",
+              "geoId/06003           Alpine County                    29.1   \n",
+              "geoId/06005           Amador County                    29.7   \n",
+              "geoId/06007            Butte County                    29.7   \n",
+              "geoId/06009        Calaveras County                    30.6   \n",
+              "geoId/06011           Colusa County                    33.1   \n",
+              "geoId/06013     Contra Costa County                    24.6   \n",
+              "geoId/06015        Del Norte County                    32.8   \n",
+              "geoId/06017        El Dorado County                    28.4   \n",
+              "geoId/06019           Fresno County                    36.6   \n",
+              "geoId/06021            Glenn County                    31.5   \n",
+              "geoId/06023         Humboldt County                    32.5   \n",
+              "geoId/06025         Imperial County                    37.5   \n",
+              "geoId/06027             Inyo County                    29.3   \n",
+              "geoId/06029             Kern County                    36.4   \n",
+              "geoId/06031            Kings County                    34.8   \n",
+              "geoId/06033             Lake County                    33.7   \n",
+              "geoId/06035           Lassen County                    32.0   \n",
+              "geoId/06037      Los Angeles County                    28.5   \n",
+              "geoId/06039           Madera County                    35.7   \n",
+              "geoId/06041            Marin County                    23.1   \n",
+              "geoId/06043         Mariposa County                    29.7   \n",
+              "geoId/06045        Mendocino County                    31.4   \n",
+              "geoId/06047           Merced County                    32.5   \n",
+              "geoId/06049            Modoc County                    32.7   \n",
+              "geoId/06051             Mono County                    29.8   \n",
+              "geoId/06053         Monterey County                    27.3   \n",
+              "geoId/06055             Napa County                    27.8   \n",
+              "geoId/06057           Nevada County                    27.6   \n",
+              "geoId/06059           Orange County                    25.4   \n",
+              "geoId/06061           Placer County                    26.5   \n",
+              "geoId/06063           Plumas County                    29.4   \n",
+              "geoId/06065        Riverside County                    36.0   \n",
+              "geoId/06067       Sacramento County                    31.9   \n",
+              "geoId/06069       San Benito County                    31.1   \n",
+              "geoId/06071   San Bernardino County                    38.1   \n",
+              "geoId/06073        San Diego County                    23.7   \n",
+              "geoId/06075    San Francisco County                    18.8   \n",
+              "geoId/06077      San Joaquin County                    33.3   \n",
+              "geoId/06079  San Luis Obispo County                    29.0   \n",
+              "geoId/06081        San Mateo County                    21.3   \n",
+              "geoId/06083    Santa Barbara County                    28.6   \n",
+              "geoId/06085      Santa Clara County                    18.7   \n",
+              "geoId/06087       Santa Cruz County                    24.3   \n",
+              "geoId/06089           Shasta County                    30.9   \n",
+              "geoId/06091           Sierra County                    30.0   \n",
+              "geoId/06093         Siskiyou County                    32.6   \n",
+              "geoId/06095           Solano County                    29.9   \n",
+              "geoId/06097           Sonoma County                    28.6   \n",
+              "geoId/06099       Stanislaus County                    34.7   \n",
+              "geoId/06101           Sutter County                    31.4   \n",
+              "geoId/06103           Tehama County                    34.0   \n",
+              "geoId/06105          Trinity County                    33.2   \n",
+              "geoId/06107           Tulare County                    35.2   \n",
+              "geoId/06109         Tuolumne County                    29.2   \n",
+              "geoId/06111          Ventura County                    26.9   \n",
+              "geoId/06113             Yolo County                    25.8   \n",
+              "geoId/06115             Yuba County                    33.9   \n",
+              "\n",
+              "             Count_MortalityEvent_COVID19  Count_Person  Median_Income_Person  \n",
+              "place                                                                          \n",
+              "geoId/06001                         635.0       1663823                 54302  \n",
+              "geoId/06003                           NaN          1515                 31071  \n",
+              "geoId/06005                          19.0         40577                 38576  \n",
+              "geoId/06007                         132.0        213605                 31677  \n",
+              "geoId/06009                          17.0         45674                 34144  \n",
+              "geoId/06011                          15.0         21811                 34163  \n",
+              "geoId/06013                         422.0       1162648                 51100  \n",
+              "geoId/06015                           NaN         27462                 28389  \n",
+              "geoId/06017                          72.0        191713                 45916  \n",
+              "geoId/06019                         937.0       1008280                 31853  \n",
+              "geoId/06021                          22.0         28657                 30869  \n",
+              "geoId/06023                          23.0        136132                 29264  \n",
+              "geoId/06025                         529.0        179578                 23080  \n",
+              "geoId/06027                          28.0         18829                 37827  \n",
+              "geoId/06029                         678.0        906883                 29192  \n",
+              "geoId/06031                         113.0        152515                 32984  \n",
+              "geoId/06033                          39.0         68024                 30364  \n",
+              "geoId/06035                          16.0         31873                 33358  \n",
+              "geoId/06037                       11176.0       9936690                 35869  \n",
+              "geoId/06039                         170.0        157243                 29150  \n",
+              "geoId/06041                         114.0        260485                 63765  \n",
+              "geoId/06043                           NaN         17130                 33425  \n",
+              "geoId/06045                          35.0         91145                 32446  \n",
+              "geoId/06047                         260.0        282290                 30037  \n",
+              "geoId/06049                           NaN          8651                 30115  \n",
+              "geoId/06051                           NaN         13219                 45331  \n",
+              "geoId/06053                         256.0        437609                 34979  \n",
+              "geoId/06055                          38.0        137384                 45288  \n",
+              "geoId/06057                          63.0        102322                 37964  \n",
+              "geoId/06059                        2459.0       3175227                 44190  \n",
+              "geoId/06061                         157.0        406608                 50615  \n",
+              "geoId/06063                           NaN         19650                 39176  \n",
+              "geoId/06065                        2657.0       2429487                 35607  \n",
+              "geoId/06067                         948.0       1579211                 40179  \n",
+              "geoId/06069                          32.0         64753                 41870  \n",
+              "geoId/06071                        2747.0       2180563                 34107  \n",
+              "geoId/06073                        1748.0       3289701                 42349  \n",
+              "geoId/06075                         222.0        851036                 65802  \n",
+              "geoId/06077                         793.0        779445                 36016  \n",
+              "geoId/06079                         116.0        281712                 38724  \n",
+              "geoId/06081                         248.0        754250                 59975  \n",
+              "geoId/06083                         177.0        445213                 36135  \n",
+              "geoId/06085                         852.0       1916831                 59207  \n",
+              "geoId/06087                         122.0        268571                 41634  \n",
+              "geoId/06089                         102.0        181852                 33097  \n",
+              "geoId/06091                           NaN          2916                 23897  \n",
+              "geoId/06093                          14.0         44049                 29476  \n",
+              "geoId/06095                         171.0        450995                 43831  \n",
+              "geoId/06097                         196.0        488436                 45670  \n",
+              "geoId/06099                         634.0        552063                 34223  \n",
+              "geoId/06101                          62.0         99101                 32987  \n",
+              "geoId/06103                          44.0         65484                 30450  \n",
+              "geoId/06105                           NaN         15889                 30800  \n",
+              "geoId/06107                         451.0        473446                 29304  \n",
+              "geoId/06109                          33.0         54993                 34956  \n",
+              "geoId/06111                         376.0        842009                 40855  \n",
+              "geoId/06113                         110.0        217141                 37622  \n",
+              "geoId/06115                          29.0         81705                 32074  "
+            ],
             "text/html": [
-              "<div>\n",
+              "\n",
+              "  <div id=\"df-3fd0190a-6597-43cc-bacb-c9172e76af18\" class=\"colab-df-container\">\n",
+              "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
               "        vertical-align: middle;\n",
@@ -562,10 +1391,10 @@
               "    <tr style=\"text-align: right;\">\n",
               "      <th></th>\n",
               "      <th>name</th>\n",
+              "      <th>Percent_Person_Obesity</th>\n",
+              "      <th>Count_MortalityEvent_COVID19</th>\n",
               "      <th>Count_Person</th>\n",
               "      <th>Median_Income_Person</th>\n",
-              "      <th>Percent_Person_Obesity</th>\n",
-              "      <th>CumulativeCount_MedicalTest_ConditionCOVID_19_Positive</th>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>place</th>\n",
@@ -578,115 +1407,742 @@
               "  </thead>\n",
               "  <tbody>\n",
               "    <tr>\n",
-              "      <th>geoId/0107000</th>\n",
-              "      <td>Birmingham</td>\n",
-              "      <td>200733</td>\n",
-              "      <td>22646</td>\n",
-              "      <td>42.0</td>\n",
-              "      <td>NaN</td>\n",
+              "      <th>geoId/06001</th>\n",
+              "      <td>Alameda County</td>\n",
+              "      <td>25.1</td>\n",
+              "      <td>635.0</td>\n",
+              "      <td>1663823</td>\n",
+              "      <td>54302</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0135896</th>\n",
-              "      <td>Hoover</td>\n",
-              "      <td>92606</td>\n",
-              "      <td>44843</td>\n",
-              "      <td>28.4</td>\n",
+              "      <th>geoId/06003</th>\n",
+              "      <td>Alpine County</td>\n",
+              "      <td>29.1</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>1515</td>\n",
+              "      <td>31071</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0137000</th>\n",
-              "      <td>Huntsville</td>\n",
-              "      <td>215006</td>\n",
-              "      <td>30079</td>\n",
-              "      <td>36.2</td>\n",
-              "      <td>NaN</td>\n",
+              "      <th>geoId/06005</th>\n",
+              "      <td>Amador County</td>\n",
+              "      <td>29.7</td>\n",
+              "      <td>19.0</td>\n",
+              "      <td>40577</td>\n",
+              "      <td>38576</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06007</th>\n",
+              "      <td>Butte County</td>\n",
+              "      <td>29.7</td>\n",
+              "      <td>132.0</td>\n",
+              "      <td>213605</td>\n",
+              "      <td>31677</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06009</th>\n",
+              "      <td>Calaveras County</td>\n",
+              "      <td>30.6</td>\n",
+              "      <td>17.0</td>\n",
+              "      <td>45674</td>\n",
+              "      <td>34144</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0150000</th>\n",
-              "      <td>Mobile</td>\n",
-              "      <td>187041</td>\n",
-              "      <td>25083</td>\n",
-              "      <td>38.2</td>\n",
+              "      <th>geoId/06011</th>\n",
+              "      <td>Colusa County</td>\n",
+              "      <td>33.1</td>\n",
+              "      <td>15.0</td>\n",
+              "      <td>21811</td>\n",
+              "      <td>34163</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06013</th>\n",
+              "      <td>Contra Costa County</td>\n",
+              "      <td>24.6</td>\n",
+              "      <td>422.0</td>\n",
+              "      <td>1162648</td>\n",
+              "      <td>51100</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06015</th>\n",
+              "      <td>Del Norte County</td>\n",
+              "      <td>32.8</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>27462</td>\n",
+              "      <td>28389</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06017</th>\n",
+              "      <td>El Dorado County</td>\n",
+              "      <td>28.4</td>\n",
+              "      <td>72.0</td>\n",
+              "      <td>191713</td>\n",
+              "      <td>45916</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/0151000</th>\n",
-              "      <td>Montgomery</td>\n",
-              "      <td>200603</td>\n",
-              "      <td>25725</td>\n",
+              "      <th>geoId/06019</th>\n",
+              "      <td>Fresno County</td>\n",
+              "      <td>36.6</td>\n",
+              "      <td>937.0</td>\n",
+              "      <td>1008280</td>\n",
+              "      <td>31853</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06021</th>\n",
+              "      <td>Glenn County</td>\n",
+              "      <td>31.5</td>\n",
+              "      <td>22.0</td>\n",
+              "      <td>28657</td>\n",
+              "      <td>30869</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06023</th>\n",
+              "      <td>Humboldt County</td>\n",
+              "      <td>32.5</td>\n",
+              "      <td>23.0</td>\n",
+              "      <td>136132</td>\n",
+              "      <td>29264</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06025</th>\n",
+              "      <td>Imperial County</td>\n",
+              "      <td>37.5</td>\n",
+              "      <td>529.0</td>\n",
+              "      <td>179578</td>\n",
+              "      <td>23080</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06027</th>\n",
+              "      <td>Inyo County</td>\n",
+              "      <td>29.3</td>\n",
+              "      <td>28.0</td>\n",
+              "      <td>18829</td>\n",
+              "      <td>37827</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06029</th>\n",
+              "      <td>Kern County</td>\n",
+              "      <td>36.4</td>\n",
+              "      <td>678.0</td>\n",
+              "      <td>906883</td>\n",
+              "      <td>29192</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06031</th>\n",
+              "      <td>Kings County</td>\n",
+              "      <td>34.8</td>\n",
+              "      <td>113.0</td>\n",
+              "      <td>152515</td>\n",
+              "      <td>32984</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06033</th>\n",
+              "      <td>Lake County</td>\n",
+              "      <td>33.7</td>\n",
               "      <td>39.0</td>\n",
+              "      <td>68024</td>\n",
+              "      <td>30364</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06035</th>\n",
+              "      <td>Lassen County</td>\n",
+              "      <td>32.0</td>\n",
+              "      <td>16.0</td>\n",
+              "      <td>31873</td>\n",
+              "      <td>33358</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06037</th>\n",
+              "      <td>Los Angeles County</td>\n",
+              "      <td>28.5</td>\n",
+              "      <td>11176.0</td>\n",
+              "      <td>9936690</td>\n",
+              "      <td>35869</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06039</th>\n",
+              "      <td>Madera County</td>\n",
+              "      <td>35.7</td>\n",
+              "      <td>170.0</td>\n",
+              "      <td>157243</td>\n",
+              "      <td>29150</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06041</th>\n",
+              "      <td>Marin County</td>\n",
+              "      <td>23.1</td>\n",
+              "      <td>114.0</td>\n",
+              "      <td>260485</td>\n",
+              "      <td>63765</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06043</th>\n",
+              "      <td>Mariposa County</td>\n",
+              "      <td>29.7</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>17130</td>\n",
+              "      <td>33425</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06045</th>\n",
+              "      <td>Mendocino County</td>\n",
+              "      <td>31.4</td>\n",
+              "      <td>35.0</td>\n",
+              "      <td>91145</td>\n",
+              "      <td>32446</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>...</th>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
-              "      <td>...</td>\n",
+              "      <th>geoId/06047</th>\n",
+              "      <td>Merced County</td>\n",
+              "      <td>32.5</td>\n",
+              "      <td>260.0</td>\n",
+              "      <td>282290</td>\n",
+              "      <td>30037</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5548000</th>\n",
-              "      <td>Madison</td>\n",
-              "      <td>269840</td>\n",
-              "      <td>32949</td>\n",
-              "      <td>27.5</td>\n",
+              "      <th>geoId/06049</th>\n",
+              "      <td>Modoc County</td>\n",
+              "      <td>32.7</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>8651</td>\n",
+              "      <td>30115</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5553000</th>\n",
-              "      <td>Milwaukee</td>\n",
-              "      <td>577222</td>\n",
-              "      <td>25266</td>\n",
-              "      <td>36.2</td>\n",
+              "      <th>geoId/06051</th>\n",
+              "      <td>Mono County</td>\n",
+              "      <td>29.8</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>13219</td>\n",
+              "      <td>45331</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06053</th>\n",
+              "      <td>Monterey County</td>\n",
+              "      <td>27.3</td>\n",
+              "      <td>256.0</td>\n",
+              "      <td>437609</td>\n",
+              "      <td>34979</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5566000</th>\n",
-              "      <td>Racine</td>\n",
-              "      <td>77816</td>\n",
-              "      <td>25366</td>\n",
-              "      <td>40.2</td>\n",
+              "      <th>geoId/06055</th>\n",
+              "      <td>Napa County</td>\n",
+              "      <td>27.8</td>\n",
+              "      <td>38.0</td>\n",
+              "      <td>137384</td>\n",
+              "      <td>45288</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06057</th>\n",
+              "      <td>Nevada County</td>\n",
+              "      <td>27.6</td>\n",
+              "      <td>63.0</td>\n",
+              "      <td>102322</td>\n",
+              "      <td>37964</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06059</th>\n",
+              "      <td>Orange County</td>\n",
+              "      <td>25.4</td>\n",
+              "      <td>2459.0</td>\n",
+              "      <td>3175227</td>\n",
+              "      <td>44190</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06061</th>\n",
+              "      <td>Placer County</td>\n",
+              "      <td>26.5</td>\n",
+              "      <td>157.0</td>\n",
+              "      <td>406608</td>\n",
+              "      <td>50615</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06063</th>\n",
+              "      <td>Plumas County</td>\n",
+              "      <td>29.4</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>19650</td>\n",
+              "      <td>39176</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5584250</th>\n",
-              "      <td>Waukesha</td>\n",
-              "      <td>71158</td>\n",
-              "      <td>33972</td>\n",
-              "      <td>31.5</td>\n",
+              "      <th>geoId/06065</th>\n",
+              "      <td>Riverside County</td>\n",
+              "      <td>36.0</td>\n",
+              "      <td>2657.0</td>\n",
+              "      <td>2429487</td>\n",
+              "      <td>35607</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06067</th>\n",
+              "      <td>Sacramento County</td>\n",
+              "      <td>31.9</td>\n",
+              "      <td>948.0</td>\n",
+              "      <td>1579211</td>\n",
+              "      <td>40179</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06069</th>\n",
+              "      <td>San Benito County</td>\n",
+              "      <td>31.1</td>\n",
+              "      <td>32.0</td>\n",
+              "      <td>64753</td>\n",
+              "      <td>41870</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06071</th>\n",
+              "      <td>San Bernardino County</td>\n",
+              "      <td>38.1</td>\n",
+              "      <td>2747.0</td>\n",
+              "      <td>2180563</td>\n",
+              "      <td>34107</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06073</th>\n",
+              "      <td>San Diego County</td>\n",
+              "      <td>23.7</td>\n",
+              "      <td>1748.0</td>\n",
+              "      <td>3289701</td>\n",
+              "      <td>42349</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06075</th>\n",
+              "      <td>San Francisco County</td>\n",
+              "      <td>18.8</td>\n",
+              "      <td>222.0</td>\n",
+              "      <td>851036</td>\n",
+              "      <td>65802</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06077</th>\n",
+              "      <td>San Joaquin County</td>\n",
+              "      <td>33.3</td>\n",
+              "      <td>793.0</td>\n",
+              "      <td>779445</td>\n",
+              "      <td>36016</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06079</th>\n",
+              "      <td>San Luis Obispo County</td>\n",
+              "      <td>29.0</td>\n",
+              "      <td>116.0</td>\n",
+              "      <td>281712</td>\n",
+              "      <td>38724</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06081</th>\n",
+              "      <td>San Mateo County</td>\n",
+              "      <td>21.3</td>\n",
+              "      <td>248.0</td>\n",
+              "      <td>754250</td>\n",
+              "      <td>59975</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06083</th>\n",
+              "      <td>Santa Barbara County</td>\n",
+              "      <td>28.6</td>\n",
+              "      <td>177.0</td>\n",
+              "      <td>445213</td>\n",
+              "      <td>36135</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06085</th>\n",
+              "      <td>Santa Clara County</td>\n",
+              "      <td>18.7</td>\n",
+              "      <td>852.0</td>\n",
+              "      <td>1916831</td>\n",
+              "      <td>59207</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06087</th>\n",
+              "      <td>Santa Cruz County</td>\n",
+              "      <td>24.3</td>\n",
+              "      <td>122.0</td>\n",
+              "      <td>268571</td>\n",
+              "      <td>41634</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06089</th>\n",
+              "      <td>Shasta County</td>\n",
+              "      <td>30.9</td>\n",
+              "      <td>102.0</td>\n",
+              "      <td>181852</td>\n",
+              "      <td>33097</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06091</th>\n",
+              "      <td>Sierra County</td>\n",
+              "      <td>30.0</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>2916</td>\n",
+              "      <td>23897</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th>geoId/5613900</th>\n",
-              "      <td>Cheyenne</td>\n",
-              "      <td>65132</td>\n",
-              "      <td>35481</td>\n",
-              "      <td>29.4</td>\n",
+              "      <th>geoId/06093</th>\n",
+              "      <td>Siskiyou County</td>\n",
+              "      <td>32.6</td>\n",
+              "      <td>14.0</td>\n",
+              "      <td>44049</td>\n",
+              "      <td>29476</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06095</th>\n",
+              "      <td>Solano County</td>\n",
+              "      <td>29.9</td>\n",
+              "      <td>171.0</td>\n",
+              "      <td>450995</td>\n",
+              "      <td>43831</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06097</th>\n",
+              "      <td>Sonoma County</td>\n",
+              "      <td>28.6</td>\n",
+              "      <td>196.0</td>\n",
+              "      <td>488436</td>\n",
+              "      <td>45670</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06099</th>\n",
+              "      <td>Stanislaus County</td>\n",
+              "      <td>34.7</td>\n",
+              "      <td>634.0</td>\n",
+              "      <td>552063</td>\n",
+              "      <td>34223</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06101</th>\n",
+              "      <td>Sutter County</td>\n",
+              "      <td>31.4</td>\n",
+              "      <td>62.0</td>\n",
+              "      <td>99101</td>\n",
+              "      <td>32987</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06103</th>\n",
+              "      <td>Tehama County</td>\n",
+              "      <td>34.0</td>\n",
+              "      <td>44.0</td>\n",
+              "      <td>65484</td>\n",
+              "      <td>30450</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06105</th>\n",
+              "      <td>Trinity County</td>\n",
+              "      <td>33.2</td>\n",
               "      <td>NaN</td>\n",
+              "      <td>15889</td>\n",
+              "      <td>30800</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06107</th>\n",
+              "      <td>Tulare County</td>\n",
+              "      <td>35.2</td>\n",
+              "      <td>451.0</td>\n",
+              "      <td>473446</td>\n",
+              "      <td>29304</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06109</th>\n",
+              "      <td>Tuolumne County</td>\n",
+              "      <td>29.2</td>\n",
+              "      <td>33.0</td>\n",
+              "      <td>54993</td>\n",
+              "      <td>34956</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06111</th>\n",
+              "      <td>Ventura County</td>\n",
+              "      <td>26.9</td>\n",
+              "      <td>376.0</td>\n",
+              "      <td>842009</td>\n",
+              "      <td>40855</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06113</th>\n",
+              "      <td>Yolo County</td>\n",
+              "      <td>25.8</td>\n",
+              "      <td>110.0</td>\n",
+              "      <td>217141</td>\n",
+              "      <td>37622</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>geoId/06115</th>\n",
+              "      <td>Yuba County</td>\n",
+              "      <td>33.9</td>\n",
+              "      <td>29.0</td>\n",
+              "      <td>81705</td>\n",
+              "      <td>32074</td>\n",
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n",
-              "<p>499 rows × 5 columns</p>\n",
-              "</div>"
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3fd0190a-6597-43cc-bacb-c9172e76af18')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-3fd0190a-6597-43cc-bacb-c9172e76af18 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-3fd0190a-6597-43cc-bacb-c9172e76af18');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-d51c3de8-4308-4375-b928-a2555b1f526e\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d51c3de8-4308-4375-b928-a2555b1f526e')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-d51c3de8-4308-4375-b928-a2555b1f526e button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_52e137ad-7e4c-42e4-8d81-20adabea7c6e\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_52e137ad-7e4c-42e4-8d81-20adabea7c6e button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
             ],
-            "text/plain": [
-              "                     name  ...  CumulativeCount_MedicalTest_ConditionCOVID_19_Positive\n",
-              "place                      ...                                                        \n",
-              "geoId/0107000  Birmingham  ...                                                NaN     \n",
-              "geoId/0135896      Hoover  ...                                                NaN     \n",
-              "geoId/0137000  Huntsville  ...                                                NaN     \n",
-              "geoId/0150000      Mobile  ...                                                NaN     \n",
-              "geoId/0151000  Montgomery  ...                                                NaN     \n",
-              "...                   ...  ...                                                ...     \n",
-              "geoId/5548000     Madison  ...                                                NaN     \n",
-              "geoId/5553000   Milwaukee  ...                                                NaN     \n",
-              "geoId/5566000      Racine  ...                                                NaN     \n",
-              "geoId/5584250    Waukesha  ...                                                NaN     \n",
-              "geoId/5613900    Cheyenne  ...                                                NaN     \n",
-              "\n",
-              "[499 rows x 5 columns]"
-            ]
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "dataframe",
+              "variable_name": "df",
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 58,\n  \"fields\": [\n    {\n      \"column\": \"place\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 58,\n        \"samples\": [\n          \"geoId/06001\",\n          \"geoId/06011\",\n          \"geoId/06069\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 58,\n        \"samples\": [\n          \"Alameda County\",\n          \"Colusa County\",\n          \"San Benito County\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Percent_Person_Obesity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4.323152333425648,\n        \"min\": 18.7,\n        \"max\": 38.1,\n        \"num_unique_values\": 53,\n        \"samples\": [\n          23.1,\n          30.9,\n          33.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Count_MortalityEvent_COVID19\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1658.130465436349,\n        \"min\": 14.0,\n        \"max\": 11176.0,\n        \"num_unique_values\": 50,\n        \"samples\": [\n          113.0,\n          14.0,\n          1748.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Count_Person\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1453959,\n        \"min\": 1515,\n        \"max\": 9936690,\n        \"num_unique_values\": 58,\n        \"samples\": [\n          1663823,\n          21811,\n          64753\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Median_Income_Person\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9335,\n        \"min\": 23080,\n        \"max\": 65802,\n        \"num_unique_values\": 58,\n        \"samples\": [\n          54302,\n          34163,\n          41870\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+            }
           },
           "metadata": {}
         }
@@ -759,10 +2215,10 @@
         "# libraries we'll use for the visualizations\n",
         "import matplotlib.pyplot as plt\n",
         "\n",
-        "!pip install heatmapz\n",
+        "!pip install heatmapz --upgrade --quiet\n",
         "from heatmap import heatmap, corrplot"
       ],
-      "execution_count": null,
+      "execution_count": 17,
       "outputs": []
     },
     {
@@ -770,10 +2226,10 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 632
+          "height": 883
         },
         "id": "U0u-9rvdCFe_",
-        "outputId": "b9eeb94c-bf1f-4869-bc64-7765c331dbc8"
+        "outputId": "12d986ac-906c-437c-b815-7e7ba81b900f"
       },
       "source": [
         "# List of DCIDs\n",
@@ -789,7 +2245,7 @@
         "                      \"Percent_Person_WithMentalHealthNotGood\",\n",
         "                      \"Percent_Person_WithHighCholesterol\",\n",
         "                      \"Percent_Person_Obesity\"\n",
-        "                      \n",
+        "\n",
         "]\n",
         "\n",
         "# Build Data Frame\n",
@@ -800,19 +2256,17 @@
         "plt.figure(figsize=(8, 8))\n",
         "corrplot(df.corr(), size_scale=300);"
       ],
-      "execution_count": null,
+      "execution_count": 18,
       "outputs": [
         {
           "output_type": "display_data",
           "data": {
-            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAr8AAAJnCAYAAACedDusAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzde5hcVZX38e8v3Z0QiAISZTAicURE5JKEBoZ7ENRBCIKAXJXoyEWdoDDwIIJjUFEYURQcUUQIvFwFMS8Xx8gQAnkJDDQQEi7CjILjbUQCIsRMruv94+yG09VVXdXd1VVddX4fn366atfZZ6996hhWr9rnlCICMzMzM7MiGNPsAMzMzMzMGsXJr5mZmZkVhpNfMzMzMysMJ79mZmZmVhhOfs3MzMysMJz8mpmZmVlhdDY7ADMDSTOAGeuvv/7xb3nLW5odTsOsW7eOMWOK8Td4keYKxZpvkeYKxZpvkeYK8PTTTz8fEW8EmDhxYkyePLkh4z700EOvjtsI8n1+zUaPqVOnxt13393sMBqmp6eH7u7uZofREEWaKxRrvkWaKxRrvkWaK8CGG274UER0A3R3d0dPT09DxpX06riNUJw/Z8zMzMys8Jz8mpmZmVlhOPk1MzMzs8Jw8mtmZmZmheHk18zMzMwKw8mvmZmZmRWGk18zMzMzKwwnv2ZmZmZWGE5+zczMzKwwnPyamZmZWWE4+TUzMzOzwnDya2ZmZmaF4eTXzMzMzArDya+ZmZmZFYaTXzMzMzMrDCe/ZmZmZjZqSbpc0nOSHqvH/pz8mpmZmdloNgf4+3rtzMmvmZmZmY1aEXEP8EK99tdZrx2ZmZmZWXt46vfPMX32dxo13ERJPbnnl0bEpSM1mJNfMzMzM+tHUqOGej4iuhs1mJNfszZ3xMXXsmL1mmHvZ3xXJzfMOroOEZmZmTWPk1+zNlePxLee+zGz2vzX+f9ErFo55P4aO44tz/hGHSOyIpHEmMZVfhvKya+ZtZ1ff/crxOpVQ+qrrrFs8amz6xyR1dNvr/z2oN9fdY3lLcd9ZoQiGhnDSXzr0b8Z/ucnVxJrVg+qjzq7+JtDjhuhiEbOr7//tSH9O6WusWxx4pkjEFGZsUZJ7ivpOmA62drg3wJfjIgfDnV/Tn7NrO0MNfEdbt9m+uPcqwaVNKizi00P/ugIRjRyhvIeter7WjSDTXyH2mc0GOo5WcRzOSKOquf+nPyambWBwSYArZowmFnjeNmDmZmZmRWCaOjdHhrKX3LRIiSFpKtzzzsl/UnSbYPczwJJ3enxTyVtVMcYZ0s6rV77GymS1kpaLOkxSTdKWr/ZMZmZmVljOPltHcuBbSWNT8/fC/xuODuMiA9ExJ+HHVnrWRERUyJiW2AVcFItnST5kxIzMysMSQ35aTQnv63lp8AB6fFRwHW9L0jaQNLlkh6Q9IikD6b28ZKul/SkpJ8A43N9npU0MT2eK+khSY9LOiG3zSuSzpX0qKT7JW1aS6Cpwnx+iudpSXum9g5JF6Sq6xJJs1L7vinupWke43Ixfi1VanskTZM0T9IvJZ2UG+90SQ+mfZ4ziGO6ENhygOM3U9ItkuYDd0raTNI9ucpx77yOSrE/Jun84R4/MzOzphKMadBPozn5bS3XA0dKWg/YHviP3GtnAfMjYmdgH+DrkjYAPgn8NSLeBXwR2LHCvj8eETsC3cDJkjZJ7RsA90fEDsA9wPGDiLczxfPZNDbACcBkYEpEbA9ck+YzBzgiIrYjW4v+ydx+/jsippAlqnOAw4C/A84BkPQ+4B3AzsAUYEdJe1ULLlVy9weWUvn4AUwDDouIvYGjgXkpnh2AxZLeDJwPvCeNv5Okg1PfqsdP0gkpse9ZtmxZtbDNzMxsGJz8tpCIWEKWOB5FVgXOex/wOUmLgQXAesBbgb2Aq3P9l1TY/cmSHgXuBzYnSyYhWxbQu674oTR+rW4u028/4PsRsSbF9ALwTuCZiHg6bXNlirvXLen3UuA/IuLliPgTsDKtWX5f+nkEeBjYOhd/OePTceoB/hv4IZWPH8AdKU6AB4GPSZoNbBcRLwM7AQsi4k9pXtfk4q96/CLi0ojojojuTTbZpPRlMzOzplCD/tdoXsPYem4BLiC72XM+UxJwaEQ8ld+4lrU0kqaTJaW7RsRfJS0gS/4AVkdEpMdrGdw503uH9cH2q7SfdbnHvc87yeb+tYj4fo37W5Eqt69SdqDKHb9dyNZbAxAR96Sq8gHAHEnfBF4aYKzhHD8zM7OmEM1Zj9sIrvy2nsuBcyJiaUn7PGBWSuKQNDW130P2UT2StiVbLlFqQ+DFlPhuTbakYKTcAZyYlhwg6Q3AU8BkSVumbT4C3D2Ifc4DPi5pQtrnJElvGmRclY5fH5K2AP4YET8ALiNbEvEAsLekiZI6yCrzg4nfzMzMGsRVqBYTEb8FLirz0peBbwFLJI0BngEOBC4BrpD0JPAk2UfvpX4GnJS2eYps6cNIuQzYKsW5GvhBRHxH0seAG1NS/CDwvVp3GBE/l/Qu4L6Uu74CHAs8N4i4Kh2/UtOB01PsrwAfjYg/SPoccBdZFfr2iPi/gxjbzMxs1PGXXFhTRcSEMm0LyNanEhErgBPLbLMCOLLCPifnnu5fbdyIuAm4aYAYZ+ceT889fp601jWtiT01/eT73gn0q7bmY4yIOWQXvJV77dvAtyvFVrLPcsey0vErHfNKsjXJpdtdR+7uG+XGqnb8zMzMbOQ5+TUzawPq7BrUVxars2sEozEbmsGex719bGS0aeHXya8NnqSzgMNLmm+MiHObEU856VZtd5Z5ad+I8P3E2py6xhKrVw25byva9OCPNjuEhhnK+9uq72vR/M0hxzU7hIYZ6r9TjTqXhZc9mL0qJbmjJtEtJyW4U6puaG1pi0+d3ewQbAS95bjPNDuEhtDYccSqldU3HKC/jV5bnHhms0MoLCe/Zm1ufFcnK1avqct+zKxxtjzjG80OwYpMtd0utRX5v2Zmbe6GWUc3OwQzM2tB7Zr8+j6/ZmZmZlYYrvyamZmZWR/ZBW/NjmJkOPk1MzMzsxL+emMzMzMzs5bnyq+ZmZmZ9eP7/JqZmZlZYYj2TH697MHMzMzMCsOVXzMzMzPrQ8p+2pGTXzMzMzPrp13X/HrZg5mZmZkVhiu/ZmZmZlbC9/k1MzMzM2t5rvyamZmZWT/tWvl18mtmZmZmfQgY0565r5c9mJmZmVlxuPJrZmZmZn3Jyx7MzMzMrEB8n18zMzMzsxbnyq+ZmZmZ9SG87MHMzMzMCqQ9U18nv2ajgqQZwIxJkybR09PT7HAaZvny5YWZb5HmCsWab5HmCsWab5HmWiROfs1GgYi4Fbh16tSpx3d3dzc7nIbp6emhKPMt0lyhWPMt0lyhWPMt0lz7U9te8Obk18zMzMz6adc1v77bg5mZmZkVhiu/ZmZmZtaH/CUXZmZmZlYkY9oz9/WyBzMzMzMrDld+zczMzKyfdl324MqvmZmZmRWGK79mZmZm1ofA9/k1MzMzs6KQlz2YmZmZmbU6V37NzMzMrC9l9/ptR05+zczMzKyfdl3z62UPZmZmZlYYrvyamZmZWR8CRHtWfp38mpmZmVk/XvZgZmZmZtbiXPk1MzMzs37atPDr5NfMzMzMSgh/yYWZmZmZWatz5dfMzMzM+hBq2wvenPyaWVs54uJrWbF6zbD2Mb6rkxtmHV2niMzMWlO7Lntw8mtmbWW4iW+99mEj4+T/cxsrh/H+jOvq5KKPHFjHiEbO5380j5Vr1g65/7jODr764ffXMSKrl1Ouvp2Va4ZxHnd2cuGxB9QxomJx8mtWEL/+7leI1asG3U9dY9niU2ePQERWL9/8t3tZtXbwSdLYjg5O3X/3EYho5Awn8a1H/0YaTuJbj/6Ndv5t97BqiDGP7ezgjAP3qnNEI2c4iW89+teqTQu/vuDNrCiGkvgOp581zlAS3+H0MxsJQ018h9vXiseVXzMzMzPrQ7TvN7w5+TUzMzOzvnyf39Yjaa2kxZIek3SjpPWbEMN0SbtV2Wa2pN/lYj2oUfFVU+4YSpos6bE67PskSR8dYt9X0u+6xFKy7ymSPpB7fpCkz1Xp8yVJ+6XHn23GuWZmZma1advkF1gREVMiYltgFXBSLZ0k1bMaPh0YMPlNLoyIKcDhwOWSanpfJHUMI7ZaDOkY1iIivhcRV9Vrf3U0BXg1+Y2IWyLivIE6RMQ/R8S/p6efBZz8mplZyxuDGvLT+HkVw0JgS0kbSLpc0gOSHpH0QQBJMyXdImk+cKekCZKukLRU0hJJh6bt3ifpPkkPp0rohNT+rKRzUvtSSVtLmkyWLJ6Sqqd7VgsyIp4E1gATq4x1vqSHgcMlnSzpiRTn9WmbN0iam9rul7R9ap+d5r9A0q8knTzYY5ged0j6gaTHJf1c0nhJb08xkcZ6R+9zSeflYrwgF8tp6fGWkv5d0qNpvm9P78GduWP6wYGCS+/hzZJ+Juk/Jf1L7rVLJPWkeM/Jte8kaVEa9wFJGwJfAo5I79kRab/fkbShpF/3/mGSzqXfSOqSNEfSYel4vhm4S9Jdkj4u6Vu58Y6XdOEgjrmZmVnTSI35abS2X/ObKrn7Az8DzgLmR8THJW0EPCCpt2I3Ddg+Il6QdD7wUkRsl/axsaSJwNnAfhGxXNIZwKlkyRLA8xExTdKngNMi4hOSvge8EhEX1BjrLsA6IKqMtSwipqU+vwfeFhEr05wAzgEeiYiDJb0HuIqsogmwNbAP8DrgKUmXRMTqQRxDgHcAR0XE8ZJ+BBwaEVdLeknSlIhYDHwMuELSJsAhwNYREbkY864BzouIn0haj+yPslXAIRHxl3Ts75d0S0TEAKFOAaYCK9PcLo6I3wBnpfe1g+yPm+2BXwA3AEdExIOSXg/8FfhnoDsi/jHNfSZARLwkaTGwN3AXcCAwLyJWK/0/NyIuknQqsE9EPJ/+YDlL0unpGH8MOLHM8T0BOAFg8803H2B6ZmZmNlztnPyOT8kKZFXLHwKLgIN6K47AesBb0+M7IuKF9Hg/4MjeHUXEi5IOBLYB7k3Jzljgvtx4N6ffDwEfGmSsp0g6FngZOALYpcpYN+QeLwGukTQXmJva9gAOTbHPl7RJSu4Abo+IlcBKSc8BmwK/rRBXuWP4ZuCZlOD2zndyenwZ8LGUAB4B7Ay8BPwv8ENJtwG35QeQ9DpgUkT8JMX7v6m9C/iqpL3I/iCYlGL9nwqxAtwZES+l/k8AWwC/AT6cEsxOYDOyYxvAHyLiwTTuX1K/AXafJctkye+RwHcH2jgiXlH2acKBkp4EuiJiaZntLgUuBZg6depAyb2ZmVlDCLXtBW/tnPyuSOtoX6XsXTw0Ip4qad8FWF5lfyJLkI+q8PrK9Hstgz+uF+arw5JmVBkrH+sBwF7ADLIq43ZVxlqZe1wt1nLHsNw+xqfHPwa+CMwHHoqIZanPzsC+wGHAPwLvqRIjwDHAG4EdU3X1WbI/VgbSb26S3gacBuyU/oiZU8N+KrmFLCF/A7Aj2TyruQz4PFml+YohjmtmZtZw7Xqrs6Ks+e01D5iVkmAkTa2w3R3Ap3ufSNoYuB/YXdKWqW0DSVtVGe9lsuUFg1XTWGn96eYRcRdwBrAhMIGsSntM2mY62ZKMvwwhjkFJVdt5wCWkRC999L9hRPwUOAXYoaTPy8BvJR2cth+n7G4JGwLPpcR3H7Iq7lC8nuyPhZckbUq2fAPgKWAzSTulcV+XlndUfM8i4hXgQeDbwG0RUe6u6n36R8R/AJsDRwPXDXEOZmZmVidFS36/DHQBSyQ9np6X8xVgY2W3+HqUbA3nn4CZwHWSlpAtQ9i6yni3Aoeoxgveeg1irA7gaklLgUeAiyLiz8BsYMfU9zzguFrHroNryJYp/Dw9fx1wW4rl/5GtXS71EeDktM0i4G/SfrrT3D5KVjkdtIh4lOzY/AK4Frg3ta8iW8JwcXqP7yCrCN8FbNN7wVuZXd4AHEvfpSd5lwI/k3RXru1HwL0R8eJQ5mBmZtYMvuCtxUTEhDJtKyhzwVFEzAHm5J6/QpmEMSLmAzuVaZ+ce9xDdoszIuJpYPsqcc6u0F7LWKvJ1veWbvMCcHC1sdItzAaKrdwxfBbYNve89GK+PYArequiEfEHsrW/FWOJiP+k/FKIXQeKKx9LmffwwNzjmRX28yDwd2VeKj3u+f3eBH3vy5Lff0RcDFxc0n8PwHd5MDOz1tHGX3LRtsmvNZ6knwBvp7Y1vW2v944iwKMRcWez4zEzMzMnvw0j6SyyL7HIuzEizm1GPL3SrcjKJWb79l6wVquIOKQ+UbWHtASl2rrwhlHXWGL1qiH1s9FtbEcHq9aWW4JevZ/ZaDG2s4NVawZ/Hvf2tfoS7XvBm5PfBklJblMT3XJSgjul6obW8rb41NnNDsFGyKn7797sEBpmXFcnK1evGVb/VjGus4OVQ0wGe/u3kjMO3KvZITTMuM5OVq4Zxnnc2Zjz2MsezMxawPiuTlYMIznq3YeNThd95MDqG7WJr374/c0OwUbIhcce0OwQCs3/wptZW7lh1tHNDsHMrC2Mac/Cb+FudWZmZmZmBebKr5mZmZn14a83NjMzM7NCEe2Z/HrZg5mZmZkVhiu/ZmZmZtaXfJ9fMzMzMyuQNs19vezBzMzMzIrDlV8zMzMz68Nfb2xmZmZmhdKutzrzsgczMzMzKwxXfs3MzMyshL/kwszMzMwKQoIx7Zn7etmDmZmZmRWHK79mZmZm1o+XPZiZmZlZYbTrrc687MHMzMzMCsOVXzMzMzPrw19yYWZmZmaF0q5rfr3swczMzMwKw5VfMzMzM+tL/pILMxtBkmYAMyZNmkRPT0+zw2mY5cuXF2a+RZorFGu+RZorFGu+RZprkTj5NRsFIuJW4NapU6ce393d3exwGqanp4eizLdIc4VizbdIc4VizbdIcy2nXb/hzcmvmZmZmfUhfMGbmZmZmVnLc+XXzMzMzPoR7Vn5dfJrZmZmZv2065dceNmDmZmZmRWGK79mZmZm1kd2wVuzoxgZTn7NzMzMrC952YOZmZmZWctz5dfMzMzMSvjrjc3MzMysQNo1+fWyBzMzMzMrDFd+zczMzKwPAWPas/Dr5NfMzMzM+vOyBzMzMzOzFufKr5mZmZn1JVd+zczMzMxaniu/ZmZmZtaHgDG0Z+XXya+ZmZmZ9dOmqx687MHMzMzMisOVXzMzMzMrIca0aenXya+ZWYs64uJrWbF6zbD3M76rkxtmHV2HiMysnfhuD2ZmNqrUI/Gt537MzFqBK79m1na++W/3smrt2iH1HdvRwan7717niKxevnbr3axaM8T3trODM2fsXeeIRtbXf7pwSPMd29nB6R/YcwQisqIQ7Vv5dfJrViB/nHsVsWZ1zdurs4tND/7oCEY0Moaa+A63r428oSa+w+3bLEONuRXnCnBzzxOsWbduUH06x4zhQ93bjFBEI2vOwodZvXZw8+3qGMPMPaeNUEQ5gjHtmft62YNZkQwm8R3K9mZmwzHYxHeofUaLwSa+Q+1jfbnya2ZmZmb9tOuyh6ZWfiWtlbRY0mOSbpS0fhNimC5ptyrbzJb0u1ysBzUqvmoknSXpcUlLUny7pPYFkrrrPNZMSd+p8z4/luJeLGmVpKXp8XnpuJ9Wp3EuzI3ztKQ/p/bJkh4r2bZu45qZmbUiAWOkhvw0WrMrvysiYgqApGuAk4BvVuskqTMi6nV58nTgFWBRle0ujIgLJL0LWCjpTRFR9bMHSR0RMSKLryTtChwITIuIlZImAmNHYqyREhFXAFcASHoW2Ccink/PZ9dxnFN6H0uaBUyt174rqfN5amZmZnUwmtb8LgS2lLSBpMslPSDpEUkfhFerjrdImg/cKWmCpCtSpXCJpEPTdu+TdJ+kh1M1eUJqf1bSOal9qaStJU0mS7hPSRXBqpfGRsSTwBpgYpWxzpf0MHC4pJMlPZHivD5t8wZJc1Pb/ZK2T+2z0/wXSPqVpJMHCGcz4PmIWJliez4ifl+60QBx7ijpbkkPSZonabPUvkDSt3OV7p0HOiaSjk3v12JJ35fUkX7mpP5LJZ2Stu13LKrYptyxSMfuoVT1PiHX/oqkcyU9mo7rpmX2eRRwXQ1jI2lK2s8SST+RtHHuGHWnxxNT4l7uPN1M0j25Y+nLr83MrAUIqTE/jTYqkl9JncD+wFLgLGB+ROwM7AN8XdIGadNpwGERsTfwBeCliNguIrYH5iurfJ4N7BcR04Ae4NTcUM+n9kuA0yLiWeB7ZFXdKRGxsIZYdwHWAVFlrGURMS0irgc+B0xNcZ6UXj8HeCS1fR64Ktd3a+D9wM7AFyV1VQjn58Dmyj7G/66kfvfwqXRM0j4vJjueOwKXA+fmuq6fqvKfSq9VOh7vAo4Adk/brwWOAaYAkyJi24jYjlTdrXAsBlLpWHw8xd0NnCxpk9S+AXB/ROwA3AMcXxLvFsDbgPm55rfrtSURi0viugo4I8W7FPhiDTHnz9OjgXnp2OwALC7dWNIJknok9SxbtqyG3ZuZmY08qTE/jdbsZQ/jU7IBWeX3h2TLDw7Sa2su1wPemh7fEREvpMf7AUf27igiXpR0ILANcG/6S2IscF9uvJvT74eADw0y1lMkHQu8TJbs7VJlrBtyj5cA10iaC8xNbXsAh6bY50vaRNLr02u3p2ruSknPAZsCvy0NKCJekbQjsCfZHwo3SPpcRMzJbfZ3FeJ8J7AtcEdq7wD+kOt3XRrjHkmvl7RRheOyL7Aj8GDaz3jgOeBW4G8lXQzcTpaoVzoWA6l0LE6WdEjaZnPgHcAyYBVwW2p/CHhvyf6OBG4qWYryy97lN/DacgtJGwIbRcTd6aUrgRtriDl/nj4IXJ6S9rkR0S/5jYhLgUsBpk6dGjXs38zMzIao2cnvinzSAaAsgzo0Ip4qad8FWF5lfyJLPI6q8PrK9Hstg5/7hRFxQS6eGVXGysd6ALAXMAM4S9J2VcZamXs8YKwpiVsALJC0FDgOmJPbpOwxSTE8HhG7Vtp1lef5/V8ZEWf2e0HagaxqexLwYeDjlDkWVdbF9jsWkqaT/fGza0T8VdICsj+SAFZHROS3L9nfkcCnBxivVmt47ZOT9Upee/W9T3887EU27zmSvhkRV2FmZjbKjcF3e2iUecCslAQjqdKFSXeQS2LSWsz7gd0lbZnaNpC0VZXxXgZeN4Q4axpL0hhg84i4CzgD2BCYQFbpPiZtM51sScZfBhOApHdKekeuaQrw6xrjfAp4o7KL5pDUJenduX5HpPY9yJaXvFQhjDuBwyS9KW3/BklbpOUWYyLix2TLLqYNcCwGa0PgxZT4bk1W3a4qbbsxfSv0FaU5v5hbp/sRoLcK/CxZxRvgsAHG3AL4Y0T8ALiMbEmEmZmZNUmzK7/lfBn4FrAkJUvPkN3RoNRXgH9VdpuqtcA5EXGzpJnAdZLGpe3OBp4eYLxbgZuUXVg3q5Z1vwAR8acax+oArk4foQu4KCL+nD5av1zSEuCvZBXbwZoAXJyWJKwB/gs4Ib9BpTgj4mlJhwEXpdg6yY7742mb/5X0CNBFVrHtNVPSwbnnf5fm/fP0fq0m+6NkBXBFagM4s9KxGMK8fwacJOlJsiT+/hr7HQlcn6sM1+I44HvKbsP3K+Bjqf0C4EfKLra7fYD+04HTJa0mu6tI631dmpmZFU62Hrc9K79NTX4jol/VLyJWACeWaZ9D7uP8iHiFMgljRMwHdirTPjn3uIcsKSEinga2rxLn7ArttYy1mmx9b+k2LwAHl2mfXfJ82wHieggoe4/iiJheQ5yLyZYglHN1RHy2ZPs59F1S0esG+q5x7lWuytnvWOT2P7nk+eyS5/ljsX+FfUzIPb4JuKnS/lLbs2Rrn8uOm45Rv8pyRPyCvufN2al9Dn3P0yvJ1gqbmZm1lHZNfkfjsgczGyHqrHTjkPpsb2Y2HJ1jBp+WDKWPFdtoXPbQNJLOAg4vab4xIs4tt32jpNt43VnmpX0jou73xspXja29bHpwMVZdjO3oYNXaoX23zNiOjjpHY/U0trODVWuG+N52tt57O9T5tuJcAT7UvU2zQ2ioro4xrF5b9fuy+vVplDHtWfh18puXktymJrrlpAR3StUNzQyAU/ffvdkh2Ag5c0a/25m3tdM/4O/FaWcz9xzd10B72YOZmY0q47vqU7+o137MzFqB/8UzM2tRN8w6utkhmFmbEmJMm1Z+nfyamZmZWV9tfKszL3swMzMzs8Jw5dfMzMzM+mnTwq+TXzMzMzPrS9C2a3697MHMzMzMCsOVXzMzMzPrp10veHPya2ZmZmb9iPZMfr3swczMzMwKw5VfMzMzM+tnTHsWfl35NTMzM7PicOXXzMzMzPqQ5AvezMzMzKw4fJ9fMzMzM7MW58qvmZmZmfXjZQ9mZmZmVhhtmvt62YOZmZmZFYcrv2ZmZmbWh2jfC96c/JqZmZlZX2rfNb9e9mBmZmZmheHKr5mZmZmVkJc9mNnIkTQDmDFp0iR6enqaHU7DLF++vDDzLdJcoVjzLdJcoVjzLdJcSyn9tCMnv2ajQETcCtw6derU47u7u5sdTsP09PRQlPkWaa5QrPkWaa5QrPkWaa5F4uTXzMzMzPpp1wvenPyamZmZWT/tuubXd3swMzMzs8Jw5dfMzMzM+mnXZQ+u/JqZmZlZYbjya2ZmZmZ9SNlPO3Lya2ZmZmb9+II3MzMzM7MW58qvmZmZmZVQ217w5uTXzMzMzPoQXvZgZmZmZtbyXPk1MzMzs37atPDr5NfMzMzMSshfcmFmZmZm1vJc+TUzMzOzfsbQnpVfJ79mZmZm1ofwsgczMzMzs5bnyq+ZmZmZ9TOmPQu/Tn7NzMzMrFT7fsOblz2YmZmZWWG48mtmZmZm/bRr5dfJr5m1nZP/z22sXL1myP3HdXVy0UcOrGNEVg9HXHwtK4bxvgKM7+rkhllH1ykis6H5zNXD/zfq28f636ihcvJrVhC/vfLbxOpVg+6nrrG85bjPjEBEI2c4/1GpR/9G+9qtd7NqzdpB9xvb2cGZM/YegYhGxnAT33rto1G+cNMdrBzC+9prXGcHXz7svXWMaGQN9TyG1juXW2igVw8AACAASURBVOHfKAnGuPJrZq1sKInvcPpZ4ww1YRhqP2uM4SS+9ejfaMM5H30uj4w2zX19wZuZmZmZFYcrv2ZmZmbWT7te8ObKr5mZmZn1IcQYNeanaizS30t6StJ/SfrccOfWkORX0lpJiyU9JulGSes3YtySGKZL2q3KNrMl/S4X60GNim8gki6U9Nnc83mSLss9/4akUyUd1HtSSDpY0ja5bRZI6i6z7+mSbitpmyPpsPT4svx+KsT36vYl7ZMlrUjH81FJiyS9s9K4QyXpWUkT0+Omn2tmZmZWH5I6gH8F9ge2AY6qlpdU06jK74qImBIR2wKrgJNq6SSpnssypgMDJr/JhRExBTgcuFxSTccovTkj5V5S7CmeicC7c6/vBiyKiFsi4rzUdjDZSTIsEfGJiHhiGLv4ZXrvdwCuBD4/3JiqGPBcq/M5NaBGjmVmZlZXyr7euBE/VewM/FdE/CoiVgHXAx8cztSasexhIbClpA0kXS7pAUmPSPoggKSZkm6RNB+4U9IESVdIWippiaRD03bvk3SfpIdThW9Can9W0jmpfamkrSVNJkuCTklVwT2rBRkRTwJrgIlVxjpf0sPA4ZJOlvREivP6tM0bJM1NbfdL2j61z07zXyDpV5JOHiCcRcCu6fG7gceAlyVtLGkc8C7g4XTsvpMq3AcBX0/zfXvqe3g63k/XcgxSnK9WjCX9Q+r7gKQfSPpObtO9UmX3V+WqwMnrgRfLjFHpGFVq30TSzyU9nirglf6v03uuTZe0UNItwBOSOiR9XdKDad8npv1uJumeXOV4z7TtnPR8qaRTyhyXiZKeTY9Lz9+y53nJ/E+Q1COpZ9myZVXeETMzs5GnCMY06Ics1+rJ/ZyQC2US8Jvc89+mtiFraGUqVcL2B34GnAXMj4iPS9oIeEDSv6dNpwHbR8QLks4HXoqI7dI+Nlb2EffZwH4RsVzSGcCpwJdS/+cjYpqkTwGnRcQnJH0PeCUiLqgx1l2AdUBUGWtZRExLfX4PvC0iVqY5AZwDPBIRB0t6D3AVMCW9tjWwD/A64ClJl0TE6tJYIuL3ktZIeitZlfc+sjd+V+AlYGlErFJaNxMRi1Kid1tE3JRiA+iMiJ0lfQD4IrBfGmJPSYtzQ74VKF0K8WbgC2TvzcvAfODR3CabAXukOd0C3JTa3572/TpgfWCXMoe70jGq1P5F4P9FxJckHQD8Q+kOS841UtzbRsQz6f9UL0XETumPh3sl/Rz4EDAvIs5VVslfP403KVWSyb2vA8mfv1+lzHkeEct7N46IS4FLAaZOnRo17N/MzKydPB8R/ZZmjpRGJb/jc8nVQuCHZNXMgySdltrXI0u6AO6IiBfS4/2AI3t3FBEvSjqQ7CP9e1NSN5YsIex1c/r9EFlCMxinSDqWLME7gixZG2isG3KPlwDXSJoLzE1tewCHptjnp6rl69Nrt0fESmClpOeATcn+oilnEVniuxvwTbLkdzey5PfeGueWPy6Tc+0LI+LVr4qRNKdM352Bu3vfF0k3AlvlXp8bEevIKqub5tp/mZaRIOkIsiTv70v2XekYVWrfi/S+RsTtkvLV5HLn2m7AAxHxTGp/H7B9rkK9IfAO4EGypS5daT6LJf0K+FtJFwO3Az8vc2xK5c/f91H+PH+yhv2YmZk1T6xrdgQAvwM2zz1/S2obskYlvyt6E6BeyjLJQyPiqZL2XYDlDExkCcZRFV5fmX6vZfBzvDBfHZY0o8pY+VgPIEvMZgBnSdquylgrc4+rxdq77nc7smUPvwH+CfgLcEWVcUrHG8pxqXXfUHkZwi3UHutQlTvXoO/7JGBWRMwr7SxpL7L3cY6kb0bEVZJ2AN5PtnTmw8DHyZbE9C4bWq9kN6Vj9TvPzczMRr11o+LDyAeBd0h6G1nSeyQwrO8ob+atzuYBs1ISjKSpFba7A/h07xNJGwP3A7tL2jK1bSBpqwr9e71M9tH7YNU0lrIL0TaPiLuAM8iqiRPIqo/HpG2mk5X2/zKEOBYBBwIvRMTaVFnciGzpw6Iy2w91vpU8COydlp10kiqyg7QH8Msy7ZWOUaX2e0gnvqT9gY0HGcc84JOpwoukrdL7ugXwx4j4AXAZMC0tsRkTET8mW/4yLe3jWWDH9LjSGufesWo5z83MzKxERKwB/pHsv6dPAj+KiMeHs89mXo3+ZeBbwJKUOD5DltyV+grwr5IeI6tYnhMRN0uaCVyX1mxClpg8PcB4twI3pQuOZkXEwlqCjIg/1ThWB3C1pA3Jqn0XRcSfJc0m+yh9CfBX4Lhaxi1jKdldHq4taZsQEc+X2f564AfKLqQbKDmrSUT8Lq1ffQB4AfgF2ZKLanrX/Irs7gufKLPNbMofo0rt55C9H4+TJf7/PcjpXEa27OPhlJT+iezuGNOB0yWtBl4BPkq2vOQKvXbXjzPT7wuAH6X1w7cPMFat57mZmdmoERHE6Fj2QET8FPhpvfbXkOQ3IiaUaVsBnFimfQ4wJ/f8FcokjBExH9ipTPvk3OMesoSGiHga2L5KnLMrtNcy1mqyymbpNi+QJVYDjtV7QdUAsa0lu1tCvm1myfM5pGMXEffS91Zn03PbPU9a8xsRC4AFlfYbEdNzL10bEZemyu9PSOuay8QxIf1+FhhfYT6vjjvAMarUvoxsLW25/ZY7114dKz1fR3bLtdLbrl2ZfkpNK22IiF/Q93w6O7XPoe/5W/Y8NzMzG/ViVCx7qDt/w5sNxuxUxX2MrII5t8r2Noqoa2xD+5mZmY1GhbwJv6SzyL7EIu/GiDi3GfH0krQJcGeZl/ZN1c6miojTqm9lo9VbjvtMs0NomHFdnaxcvWZY/VvJ2M4OVq1ZO6R+NnqN6+xg5RDe13z/VjLU87i3bytpmX+jRsmyh3prrX/h6yQluU1NdMtJCe6Uqhua2YAu+kixllWfOWPvZofQEOO7OlkxjIShdx+t4suHvbfZITRUUc5jgG8fW6x/o0ab1vlXwMzMCu2GWcO6u5GZDUoQo+NWZ3Xn5NfMzMzM+gp8wZuZmZmZWatz5dfMzMzM+hkt9/mtNye/ZmZmZtaflz2YmZmZmbU2V37NzMzMrET4Pr9mZmZmVhBB297qzMsezMzMzKwwXPk1MzMzs/687MHMzMzMiiF8twczMzMzs1bnyq+ZmZmZ9ZF9u3F7Vn6d/JqZmZlZXwGsa881v172YGZmZmaF4cqvmZmZmfXjZQ9mZmZmVhDt+w1vXvZgZmZmZoXhyq+ZmZmZ9demyx5c+TUzMzOzwnDl18zMzMz6iTZd8+vk12wUkDQDmDFp0iR6enqaHU7DLF++vDDzLdJcoVjzLdJcoVjzLdJc+4mAde257MHJr9koEBG3ArdOnTr1+O7u7maH0zA9PT0UZb5FmisUa75FmisUa75FmmuROPk1MzMzs/687MHMzMzMiqJdv+TCd3swMzMzs8Jw5dfMzMzM+mvTyq+TXzMzMzPrK6Jtb3XmZQ9mZmZmVhiu/JqZmZlZf77Pr5mZmZkVhpc9mJmZmZm1Nld+zczMzKyPINr2Pr9Ofs3MzMysr8DLHszMzMzMWp0rv2ZmZmbWX5ve7cGVXzMzMzMrDFd+zczMzKwfX/BmZmZmZgURvuDNzMzMzKzVufJrZmZmZn2Flz2YmZmZWZF42YOZmZmZWWtz5dfMzMzMSkTb3ufXya+Zmdkoc8TF17Ji9Zph72d8Vyc3zDq6DhFZEUWbLntw8mtWAP91/j8Rq1YOub/GjmPLM75Rx4hG1ud/NI+Va9YOqe+4zg6++uH31zmikfX1ny5k1RDmO7azg9M/sOcIRDRyvnDTHcN6b7982HvrHNHIqEfiW8/9WH0N5zyG1jqXRyMnv2YFMJzEtx79G204/1EZTt9mGUriO5x+zVS097Zovn/XA6xeO7hqY1fHGE7cZ+cRimhkDPdcbMi5HIDv9mBmZmY2cgab+A61j9XCX3JhZmZmZtbyXPk1MzMzs36iTe/2ULXyK2mtpMWSHpN0o6T1GxFYSQzTJe1WZZvZkn6Xi/WgRsU3EEkXSvps7vk8SZflnn9D0qmSDpL0udR2sKRtctsskNRdZt/TJYWkT+TapqS204YY72RJVS8NTts9lovjtpLX50g6bIgxzO6NX9JMSW/OvfaspIll+syUtE7S9rm2xyRNrjLW50uebyrpWkm/kvSQpPskHTKUeZQZq+z7aGZmNipFNOanwWpZ9rAiIqZExLbAKuCkWnYsqZ5V5enAgMlvcmFETAEOBy6XVNOyDkkdw4itmntJsad4JgLvzr2+G7AoIm6JiPNS28HANtTmMeDDuedHAY8OI97JwGi6L85M4M3VNkp+C5w1yP2/mvxKEjAXuCci/jYidgSOBN4yyH2amZnZKDXYNb8LgS0lbSDpckkPSHpE0gfh1erbLZLmA3dKmiDpCklLJS2RdGja7n2povZwqiZPSO3PSjontS+VtHWq3J0EnJKqulXvyxMRTwJrgIlVxjpf0sPA4ZJOlvREivP6tM0bJM1Nbff3VhVTZfLyVMn7laSTBwhnEbBrevxusmT1ZUkbSxoHvAt4OB2776QK90HA19N83576Hp6O99Mlx+DXwHqpYing74F/631R0tsl/SxVMRdK2jq1z5F0kaRFaQ69VdrzgD3T2KekCu/CdPweVpUKfDmSdpR0d4phnqTNUvvxkh6U9KikH6vkU4UUUzdwTYpnfHppVv4cyXW5DXi3pHeWieGotP1jks5PbecB49O+rwHeA6yKiO/19ouIX0fExWn79XLn8yOS9qnSPl7S9ZKelPQTYHxpXGm7EyT1SOpZtmzZYA+vmZlZ3WVF2XUN+Wm0mpPfVMndH1hKVl2bHxE7A/uQJWobpE2nAYdFxN7AF4CXImK7iNgemK/sI+uzgf0iYhrQA5yaG+r51H4JcFpEPAt8j1TVjYiFNcS6C7CO7EYdA421LCKmRcT1wOeAqSnO3ur2OcAjqe3zwFW5vlsD7wd2Br4oqatcLBHxe2CNpLeSVXnvA/6DLCHuBpZGxKrc9ouAW4DT03x/mV7qTMf7s8AXS4a5iazavRvwMJC/L9WlwKxUxTwN+G7utc2APYADyZJe0nFYmMa+EHgOeG86fkcAF5WbJ68lzIslLSZL4EnH5WKyc2JH4HLg3NTn5ojYKSJ2AJ4E/qHk2N1E9p4dk+JZkV7qc47kuqwD/oVcNTfF8GbgfLLkdgqwk6SDI+JzvPbJxjFkf5w8XGF+AJ/OwortyCrsV0pab4D2TwJ/jYh3kb1nO5bbaURcGhHdEdG9ySabDDC8mZmZDVctSxPGp2QGssrvD8mqmQfptXWl6wFvTY/viIgX0uP9yD42BiAiXpR0INlH+vdmhUrGkiWEvW5Ovx8CPjS46XCKpGOBl8kStV2qjHVD7vESsgrjXLKPviFLDA9Nsc+XtImk16fXbo+IlcBKSc8Bm5J97F7OIrLEdDfgm8Ck9PglsmURtcgfl8klr/0ozWVr4DpeW2YxIT2+Mc0fYFyu39zI/uR6QtKmFcbtAr4jaQqwFtiqwnYLI+LA3ieS5qSH7wS2Be5IMXQAf0ivbSvpK8BGwARgXoV9lxroHLkWOEvS23JtOwELIuJPKbZrgL147X0uS9K/kp0DqyJip/T4YoCI+IWkX5Mdj0rte5H+WIiIJZKW1Dg/MzOzJmvOetxGqCX5XZHW0b4qfbx+aEQ8VdK+C7C8yv5EliAfVeH13qrl2hrjy7swIi7IxTOjylj5WA8gS1ZmkCVP21UZK19drRZr77rf7ciWPfwG+CfgL8AVVcYpHa/fWBHxP5JWA+8FPsNr66PHAH8uff8qzEEVtjkF+COwQ9rf/9YYb36/j0fErmVemwMcHBGPSppJtra7FgMdizWSvgGcMcg4AR4n/bGT9vXp9ElFzxD2ZWZm1tp8n98+5pGtuxSApKkVtruD7CNh0nYbA/cDu0vaMrVtIKlSNbHXy8DrhhBnTWMpuxBt84i4iyxp2pCsErkQOCZtM53s4/a/DCGORWRLC16IiLWpMr4R2dKHRWW2H8p8/xk4IyJe/dqXFOszkg6H7I8WSTtU2U/p2BsCf0gV4o+QVW4H4yngjZJ2TTF0Seq94O91wB/S0ohjaoynFnPIPnV4Y3r+ALC3pInKLm48Crg7vbY6t2RlPtn66U/m9pVfh5w/H7Yi+7TjqQHa7yFdPChpW2B7zMzMrKmGmvx+mezj8CWSHk/Py/kKsHG6yOhRYJ/00fNM4Lr0MfB9ZB/XD+RW4BDVeMFbr0GM1QFcLWkp8AhwUUT8GZgN7Jj6ngccV+vYJZaS3eXh/pK2lyLi+TLbXw+cni6eenuZ1/uJiEURUe5j/GOAf0jH/3Hgg1V2tQRYmy5CO4VsjfBxqf/WVK/sl8a1CjgMOD/tYzGvVaa/QLb++V7gFxV2MQf4XskFb7WMeRHwpvT8D2Rrme8iuxPGQxHxf9Pml5Kdx9dERJDdaWNvSc9IegC4kteqyN8FxqTz5AZgZlr6Uqn9EmCCpCeBL5Et0zAzM2sJsS4a8tNoVZcVRMSEMm0rgBPLtM8hS1Z6n79CmYQxIuaTrcMsbZ+ce9xD+hg8Ip6mStUsImZXaK9lrNVk6zZLt3mBLBkacKx0G7iBYlsLvL6kbWbJ8zmkYxcR99L3VmfTc9s9T1rzGxELgAUDxRcRz5DdAaJ0m9LxJ6Tfq8kuDMvLH/sz0nbPkq3lLRtHfv8RsZhsSUlpDJeQJYgDxf9j4Me5lyfnXsufI3Poe+5dRO7ivIi4jmw9dOlYZ5BbIpES5SNLt0uv/S/wsUG0r6i0LzMzs1Et/PXGZmZmZiOqq2PwaclQ+lixtdzXG0s6i+y2Xnk3RsS55bZvFEmbAHeWeWnfiPDNW62pNHYcsWpl9Q0H6N9KxnV2sHLN2uobVujbasZ2drBqCPMd24JzLdp7WzQn7rNzs0NoiOGcx739G6LAd3sYVVKS29REt5yU4Fa6q4JZU215xjeaHUJDffXD7292CA11+gdqvhSi5X35sPc2O4SGGN/VyYrVa+qyHxt9WuU8Die/ZmZm1gg3zBpN3zJv1l6c/JqZmZlZf+va84I3J79mZmZm1ldE2y578CWSZmZmZlYYrvyamZmZWX9tep9fJ79mZmZm1p+XPZiZmZmZtTZXfs3MzMysRBBtuuzBlV8zMzMzKwxXfs3MzMysrwDWteeaXye/ZmZmZtafL3gzMzMzM2ttrvyamZmZWR8BbXvBm5NfMzMzMysRXvZgZmZmZtbqXPk1MzMzs3687MHMzMzMiqGNb3XmZQ9mZmZmVhiu/JqZmZlZiQAvezAzMzOzogjf7cHMzMzMrLW58ms2CkiaAcyYNGkSPT09zQ6nYZYvX16Y+RZprlCs+RZprlCs+RZprmV52YOZjZSIuBW4derUqcd3d3c3O5yG6enpoSjzLdJcoVjzLdJcoVjzLdJc+4nw3R7MzMzMzFqdK79mZmZm1o8veDMzMzMza3Gu/JqZmZlZf77gzczMzMwKIYJY157Jr5c9mJmZmVlhuPJrZmZmZv216QVvTn7NzMzMrL82XfPrZQ9mZmZmVhiu/JqZmZlZH0H73ufXya+ZmZmZ9RUBvtuDmZmZmVlrc+XXzMzMzPrxsgczMzMzKw7f7cHMzMzMrLW58mtmZmZmJcJfcmFmZmZmBREQ69oz+fWyBzMzMzMrDFd+zczMzKw/X/BmZmZmZtbaXPk1MzMzs/58wZuZmZlZ/R1x8bWsWL1mWPsY39XJDbOOrlNEBkG06bIHJ79m1nbOv+0eVq1ZO6S+Yzs7OOPAveockdXL1269e1jv7Zkz9q5zRFYPw01867UPKwYnv2YF8j8/uZJYs7rm7dXZxd8cctwIRjQyhpocDbdvM93c8wRr1tVepekcM4YPdW8zghGNjKK9t9+/6wFWrx189a2rYwwn7rPzCERk9XLJnf8x5Pf2k/vuMgIRlQi87MHMWt9gEt+hbG/NM5jEdyjbW3MMJTkaTj9rnFZ4b6NN/53w3R7MzMzMrDBc+TUzMzOzEu379cajuvIraa2kxZIek3SjpPWbEMN0SbtV2Wa2pN/lYj2oUfENRNKFkj6bez5P0mW559+QdKqkgyR9LrUdLGmb3DYLJHWX2fd0SbeVtM2RdFh6fFl+PxXie3X7Mq9tJemnkv5T0sOSfiRpU0kzJX2n1mOQ9vWspImD6ZP6zZT05sH2G2B/ZY+lmZnZqBTrGvPTYKM6+QVWRMSUiNgWWAWcVEsnSfWsaE8HBkx+kwsjYgpwOHC5pJqOraSOYcRWzb2k2FM8E4F3517fDVgUEbdExHmp7WBg2FfBRMQnIuKJofSVtB5wO3BJRLwjIqYB3wXeONy4BmkmMKjkt87nnpmZmdXZaE9+8xYCW0raQNLlkh6Q9IikD8KrVbpbJM0H7pQ0QdIVkpZKWiLp0LTd+yTdl6qJN0qakNqflXROal8qaWtJk8kS7lNSVXfPakFGxJPAGmBilbHOl/QwcLikkyU9keK8Pm3zBklzU9v9krZP7bPT/BdI+pWkkwcIZxGwa3r8buAx4GVJG0saB7wLeLi3mpoq3AcBX0/zfXvqe3g63k/XcgxSnK9WOSX9Q+r7gKQflFRu95K0KM2ltwp8NHBfRNyaO64LIuKx9PTNkn6WqsL/khvzqPTePSbp/ApxHZviWCzp+5I60s+c1G+ppFNSLN3ANWnb8ZJ2lHS3pIeUVdE3y831W5J6gM9I2jedm0vTezWuyrE6QVKPpJ5ly5bVcnjNzMxGVAREREN+Gq0lqlSpmrY/8DPgLGB+RHxc0kbAA5L+PW06Ddg+Il5Iyc9LEbFd2sfG6aPvs4H9ImK5pDOAU4Evpf7PR8Q0SZ8CTouIT0j6HvBKRFxQY6y7AOvIbhIy0FjLUkUTSb8H3hYRK9OcAM4BHomIgyW9B7gKmJJe2xrYB3gd8JSkSyKi32X5EfF7SWskvZWsynsfMIksIX4JWBoRqyT1br9I0i3AbRFxU4oNoDMidpb0AeCLwH5piD0lLc4N+VagdCnEm4EvkL03LwPzgUdzm2wG7JHmdAtwE7At8FDFg5wdh6nAyjT/i4G1wPnAjsCLwM8lHRwRc3OxvAs4Atg9IlZL+i5wDPA4MCl9woCkjSLiz5L+kew86JHUBVwMfDAi/iTpCOBc4ONp92MjoltZ1fo/gX0j4mlJVwGfBL5VaTIRcSlwKcDUqVPbc4GVmZm1nnXt+Z+k0Z78js8lVwuBH5JVMw+SdFpqX48s6QK4IyJeSI/3A47s3VFEvCjpQLKP9O9NSd1YsoSw183p90PAhwYZ6ymSjiVL8I4Adqky1g25x0vIKoxzgd5kbQ/g0BT7fEmbSHp9eu32iFgJrJT0HLAp8NsKcS0iS3x3A75JlvzuRpb83lvj3PLHZXKufWFEHNj7RNKcMn13Bu7ufV8k3QhslXt9bmRfIfOEpE1rjOfOiHgp7e8JYAtgE2BBRPwptV8D7MVrxxNgX7Lk+MH0nowHngNuBf42JdG3Az8vM+Y7yZLyO1LfDuAPuddvyG33TEQ8nZ5fCXyaAZJfMzMza5zRnvyuSOtoX6Us8zg0Ip4qad8FWF5lfyJLkI+q8PrK9Hstgz82F+arw5JmVBkrH+sBZInaDOAsSdtVGWtl7nG1WHvX/W5HtuzhN8A/AX8BrqgyTul4Qzkute4bsvcHskrsQF/DNJj55wm4MiLO7PeCtAPwfrJlLh/mtYpuvu/jEbFrad+k2rlnZmbWQqIpF6M1Qiut+e01D5iVkmAkTa2w3R1kFTfSdhsD9wO7S9oytW0gaasK/Xu9TLa8YLBqGkvZhWibR8RdwBnAhsAEskr3MWmb6WRLMv4yhDgWAQcCL0TE2lSB3Yhs6cOiMtsPdb6VPAjsnZaddJKq2VVcC+wm6YDeBkl7Sdp2gD4PpHEmKruI8Cjg7pJt7gQOk/SmtM83SNoiLYcZExE/JluqMi1tnz8WTwFvlLRr6tsl6d309xQwufd9Bz5SJg4zM7NRr13X/LZi8vtloAtYIunx9LycrwAbp4uYHgX2SR+JzwSuk7SEbBnC1lXGuxU4RDVe8NZrEGN1AFdLWgo8AlwUEX8GZgM7pr7nAUP9jtmlZHd5uL+k7aWIeL7M9tf/f/bOMtyu8mjD90MSggTX4l4ohWKFIkWKO8GtEKBFChR3istXnFK0SHAJDikUCVZocXcobsUpAULk+X7Mu8PmEAjJOTkr6+y5rytX9ll7rb3n3ctmzfvMDLBXSdiafQTvjxK23wKOIpzTe4FXCcnFD23zJeGw76xIansG+APw/g9s8w6wL3AHoSl+2PZ1bdZ5hnBubym/662E5nh64M4isbkIaESG+wJnlOXdgPWBP5fj6TFGUAXE9lfAVkC/sk+HAWf80HiTJEmSJOk8xmrZg+1eI1j2JbDdCJb3JZyVxt+fMwKH0fYA4JcjWD5L0+uHiBJnFO3m/COx85DvWf5jvmswoe9tu85HRNmxH/yuRpLWD9g2FJi4zbI+bf7uS/ntbN/Lt0udLdu03gcUza/tO4E7v+9zbS/b9NYlts8qkd9rKDrcEdjRq+n1c8AqIxjScFvLems0vb4UuLTtBm1+78v5tt66wUJtF5RI8FVNix4j5Clt11u2zd+3Ewl5P7hekiRJkoy1mJQ9JEk7OKRET58CXuHbSWhJJ6LuPcbo+kl1dB9n1C7no7p+Ug09uo3efhrd7ZLOI/dtdYzVkd+xDUkHEE0smuln+8gq7GkgaQpCz9qW5W1XXjjW9p4jXyvpDKbtPbrqmXoxbvdufD1k6GhvW0fWXaTdvWlqQavt2+2WW7RqE5IxxA7LL1a1CSOhGj1uZ5DO7yhQnNxKHd0RURzcBUa6YpK0CPus8R11StJF2G/NHyoEk9SV8Xt058vBQ9r9GUkHM6xryh7ySEmSJEmSpFIu33nTqk1IWoh0fpMkSw5a/QAAIABJREFUSZIkSZLvkrKHJEmSJEmSpCUwXVbzmymDSZIkSZIkScuQkd8kSZIkSZKkDV23vXE6v0mSJEmSJMl3GZayhyRJkiRJkiSpNRn5TZIkSZIkSb6DU/aQJEmSJEmStAR2ly11lrKHJEmSJEmSpGXIyG+SJEmSJEnyLUzKHpIkSZIkSZJWImUPSZIkSZIkSVJvMvKbJEmSJEmSfJcuWuc3nd8kSZIkSZLk29hdVvObsockSZIkSZKkZcjIb5IkSZIkSfJdMuEtSZIkSZIkSepNRn6TJEmSJEmS79JFNb/p/CZJkiRJkiRtME7ZQ5IkSZIkSZLUm4z8JkmSJEmSJN/GwLCUPSRJMoaQtCaw5vTTT89DDz1UtTmdxsCBA1tmvK00Vmit8bbSWKG1xttKYx0RXVX2kM5vkowF2L4BuGHBBRf8/SKLLFK1OZ3GQw89RKuMt5XGCq013lYaK7TWeFtprK1EOr9JkiRJkiRJG5zVHpIkSZIkSZIWoovKHrLaQ5IkSZIkSdIyZOQ3SZIkSZIk+TYGD+uakd90fpMkSZIkSZLv0kU1vyl7SJIkSZIkSVqGjPwmSZIkSZIkbXCXTXhL5zdJkiRJkiT5FgacsockSZIkSZIkqTcZ+U2SJEmSJEm+SxeVPWTkN0mSJEmSJGkZMvKbJEmSJEmSfBsbD+uamt90fpMkSZIkSZLvkrKHJEmSJEmSJKk3GflNkiRJkiRJvksXjfym85skSZIkSZK0wVnnN0mSJEmSJEnqTkZ+kyRJkiRJkm9jYFjKHpIkSZIkSZJWIWUPSZIkSZIkSVJvMvKbJEmSJEnSSWx0yiV8OXhIuz9n/B7duXznTTvAou/HWe0hSZI689qZR+PBX4/yduoxLjNvt98YsGjMsdtF/Rk0ZPRvLj27d+fEzVfvQIuSjmKXi25kUDsch549unPy5mt0oEVjjj9deSuDhgwd7e17du/G4euv2IEWJR1BRzi+Hfk534+7rOwhnd8kaRFGx/Ftz3ZV0h7HtyO2r4K+9zzC4KGjdqPq0W0c+vx6oTFk0ZihPY5vR2zfmbTH8e2I7avg9NvvH63jeIflFxtDFiVdkXR+kyRJugCj6jCM7jZJMibJ43gswil7SJIkSZIkSVqJLlrqLKs9JEmSJEmSJC1DOr9jMZKGSnpM0lOS+kmaoAIblpW0xEjWOUTSW022rtVZ9o0MSTNIuk7Si5JelnSypHHLe30k/bUDvuMwSSuU17tWsZ+SJEmSpGMpCW+d8a+TSed37OZL2wvY/jnwNbD9j9lIUkfKWZYFftD5LZxoewFgA+BcST/q2JLUrR22jeyzBVwNXGt7TmAuoBdwZEd+j+2DbN9W/twVSOc3SZIkScZS0vmtD/cAc0iaUNK5kh6Q9KiktWF4FPN6SQOA2yX1knSepCclPSFpvbLeSpL+JemREk3uVZa/KunQsvxJSXNLmoVwuHcrUd1fj8xI288CQ4ApR/Jdf5b0CLCBpD9KeqbYeVlZZ3JJ15Zl/5Y0f1l+SBn/nZL+I+mPP2DOb4CvbJ9XbBsK7AZs3RSdnbF81ouSDm5sKGnz8hs/JulMSd3Kv74luv2kpN3Kun0lrV9smQ64Q9IdkraWdFLTZ/5e0okj+w2TJEmSpGpMJLx1xr/OJhPeakCJ5K4K3AwcAAywvbWkSYEHJDWijgsB89v+SNKfgU9tz1c+YzJJUwIHAivYHihpH2B34LCy/Qe2F5L0B2BP27+TdAbwue3jfqStiwHDiPPmh77rQ9sLlW3eBma1PaiMCeBQ4FHb60j6DXABsEB5b25gOWAi4HlJp9sePAJz5gUebl5g+zNJrwNzlEWLAj8HvgAelNQfGAhsBCxpe7Ck04DNgKeB6UskniZbG5/9F0m7A8vZ/qA4+wdI2qvYtxWw3Qh+s22BbQFmnHHG7/tpkyRJkqTzMFnnN6mE8SU9Vl7fA5wD3AesJWnPsnw8YKby+lbbH5XXKwAbNz7I9seS1gB+BtwbigDGBf7V9H1Xl/8fBtYdRVt3k7Q58D/CcVxsJN91edPrJ4CLJV0LXFuWLQWsV2wfIGkKSROX9/rbHgQMkvRfYBrgzVG0t8Gttj8EkHR1+d4hwMKEMwwwPvBf4AZgNkmnAP2BW37og21/XiLxa0h6Fuhh+8kRrHcWcBbAggsu2DVTa5MkSZJkLCGd37GbL4uOdjhFx7qe7efbLF+MiFj+ECKcvU2+5/1B5f+hjPqxcWJzdFjSmiP5rmZbVweWBtYkIqXzjeS7BjW9/iFbnwHWb15QHOiZgJeISHlbZ9PE73S+7e+0NZP0C2BlQg6yIbD1SGw9G9gfeA44byTrJkmSJMnYQ5Y6S8YS/gHsXJxgJC34PevdCuzY+EPSZMC/gSUlzVGWTShprpF83/8IecGo8qO+S5EYN6PtO4B9gEmIpLR7CKkBkpYlJBmfjaINtwMTSNqifE434Higr+0vyjorFn3x+MA6wL1lu/UlTV22m1zSzEU2Mo7tqwhJx4haY33r97J9PzAjsClw6SjanyRJkiQVYexhnfKvs0nnt34cDvQAnpD0dPl7RBwBTFaSsx4ndKjvA32ASyU9QcgQ5h7J990A9P6xCW8NRuG7ugEXSXoSeBT4i+1PgEOAhcu2/wds+WO/u8kGA72JpLoXgReAr4hIbIMHgKsI6cVVth+y/Qzh3N5Svv9W4CfA9MCdRYpyEfCdyDAhX7hZ0h1Ny64A7rX98aiOIUmSJEmSjiVlD2MxtnuNYNmXjCBpynZfoG/T358zAofR9gDglyNYPkvT64eIEmfYfgGYfyR2HvI9y3/Mdw0mdLZt1/mIiMT+4Hc1ks9+wLY3CDnFiN7rS9Nv1ua9y/m2LrnBd6K9tvs0vT4FOKXNKksBWeUhSZIkqRfZ3jhJklGhUY0DeNz27VXbk3RtenQbh8FDR236sEe3nPxLxi7yOB6LMJVIEjqDdH6TH42kA4gmFs30s92hTSNGFUlTEDrdtizfqORQBUW+MTJNdaehHuPiwV+P1nbJ2E+fX49Igp7UmZ7duzFoyNB2bV83dlh+sapNSGqGpA0IqeQ8wKJl9voHSec3+dEUJ7dSR3dEFAd3gZGu2OLMvN2IJMpdk57duzNoyJB2bZ+MnfTs0Z1Bg9uxb3vUZ98evv6KVZuQjAHG79GdL9txDDd/zpjFdZE9PEWUZz3zx25Qn6tAkiTJj+TEzVev2oRkDHHy5mtUbUKStIvLd960ahN+PDUodVY6y1KKYP0o0vlNkiRJkiRJqmRKSc1yhbNKA6gxQjq/SZIkSZIkybfoNdvcLHXFvZ3zZdIHthf5/rd1GzDtCN46wPZ1o/p16fwmSZIkSZIkYy22V+jIz8v6IEmSJEmSJEnLkM5vkiRJkiRJUksk9Zb0JrA40F/SP0a2TcoekiRJkiRJklpi+xrgmlHZJiO/SZIkSZIkScuQzm+SJEmSJEnSMqTzmyRJkiRJkrQM6fwmSZIkSZIkLUM6v0mSJEmSJEnLkM5vkiRJkiRJ0jKk85skSZIkSZK0DOn8JkmSJEmSJC1DOr9JkiRJkiRJy5DOb5IkSZIkSdIypPObJEmSJEmStAzp/CZJkiRJkiQtQzq/SZIkSZIkScuQzm+SJEmSJEnSMqTzmyRJkiRJkrQMsl21DUmSFCS9D7xWwVdPCXxQwfdOAnxawfdWMd5WGiu01nhbaazQWuNtpbECzGl7Euj0+9HMtqfqpO+ie2d9UZIkI6czT/5mJD1ke5EKvvcs29tW8L2dPt5WGmv53pYZbyuNtXxvy4y3lcZavvesxuuq7kedQcoekiSpkhuqNqATaaWxQmuNt5XGCq013lYaK7TIeNP5TZKkMmy3xIUWWmus0FrjbaWxQmuNt5XGCq0z3nR+kyQBOGvkq3QpWmm8rTRWaK3xttJYobXG20pj7XQy4S1JkiRJkiRpGTLymyRJkiRJkrQM6fwmSZIkSZIkLUM6v0mSJEkyFiJJVdvQWUhKfyTpNPJgS5IkSZKxDEkzADtJmrRqW8Y0kqYDDin/J8kYJ53fJOnitFL0qBlJM1Vtw5imsW8lTS6pR9X2dDZd/NieENgc2FLS5FUbM4b5Algc2EXStFUb01lIml/S4lXb0Yqk85skXRzblrSKpBMlbSppxqptGtNImhLYX9KcVdsyppCksm/XAs4GurTT0OTozyJpLohju1qrxgySutt+HjgW+C2wh6QJKjZrjCCpm+1PgA2BOYC9W8EBltQTWB2Yu/yd/lgnkj92knRRmpyFeYBDga+BRYEDJM1WpW2dgICpgYWrNmRMURzf5Yl9e6TtNySN21WdpDLeNYBrgAMl3V2kAV0O20MkrQ7sANwM/A7YVdLE1VrWsZQHuKGSxrf9MbAV8BNg367uANseBLwB7CBpMtvDqraplUjnN0m6KMVZWAq4ADjI9j7A+cA7wF6S5qjUwDGApJkkTWn7feBU4sbSpcbZ9FAzHjAFcDXwlaStgH7AoV0xul+ivXsDKwPXA1MBnze93yUkEAomBP4AnG77QGA5YBXCKZywUgM7iKaZi+WB0yUdTEgftiT27Z6SflKpkR1I03k7m6QdAWxfRDzcbFzeS5+sk8gfOkm6Ni8AsxKRI2w/SkTOPgH2kzR+hba1mzJ12Hg9N7AZcLOkXwPvAn8HJinvd4nrXXEYViX2o4mp4ssIjej1RNS7S+l/Jc1OPLRdBmwA7AmsbvsTSb+BriOBcDAQeBaYrERFnwH+BOwL/L4r6LubHs7PBgYAXwJbE87vNoQcYG9J41ZnZfuR1EvS9GW8SwLLAitJulrSxsAwYBqAjP52Ht2rNiBJko6jKZoyK9DD9gsl8vmopBNs7277iRKF+ML2lxWbPNqUMWwgaRDwHnAQsAnwPrA+0AtYG/iVpPVtD63M2A5E0s+B3YHdbD8l6Z/AMNvvSZoP2I2I8HcJJC0LnEJEfdcGpgTWsP1Oecg5QdIGtl+s0Mx20XTezgKMC7wMPA38Cvg38CTxMHcT8C/bgysytd00jXUywuk7yfYFJaI9L3H89gO2AGa1/XWF5nYE0wEnS7qTuC71sX2upD5EhHtjYEZJL9u+sDozW4t0fpOkC1FuKusA+wBfS3oWuBL4BfCApJ62d7T9eKWGtpOS/T6EmDJ8hpjFWrXIHc4u708GDCW0v8sAAxo33orMHm2aHIbuQG9gfiLB7aniBI5XIqCnAXvafrJKezsKST8F9gf2sH2LouzX3kDv4ixtCexXZ8cXhp+3qwPHAS8CExNO4HyE1GHc8npn2/dXZ2n7KWNdCViV0LxuK+kS2+9LehwYD5jd9sPAR1Xa2h4UZdt+Zvs2SQ8CRwK72n4awHbfst6/iMS32crftbxG1Y0uMQ2YJEkgaWrC8d2ayJ4eAGxERFiWJpyGuessASha112BKW1/QEybfkpJbpM0ju2PbL9MREifAhaC+k6NN02Zzkg4SOcBG0laqKzSiI5tafvGKmzsKNpod+cijt0NAGxfSiT4jUfIWXa2fUPd9b4lcW8f4Le21wJuA/Ygqj0cCJxZ3ru1Ois7BknzEjM0l9k+gZDvnK4oTTgnMAMwqEITO4pFgPdKkuLDxP7dSdIyjRXKteohYqZmeUnT1vUaVTdqewNMkmSEdCNmdN6z/R5wBzAYWM32f4FZbD9XZ22Z7a+AE4HBknYiEtsaNUL3tT1M0iKS5rP9OaFv/o2knjV3kpYB7iIivkcDrwFbS1rU9jDbA+oeFYThjv7iko6wfQOwFzCOpF3L+9faPsH2gbbvaGxTpc0dwMfAf4mZCmwfQTzQHGr7Fdu32X6wSgPbi6RuikokxxMzUeOU8/EE4D+EnvtU4GjbT1Vnacdg+3rgdeAvwIS2jweOAs6RtECR7JxSAhFTEbkZSSeRsockqTFN0+FLAENt31+m0faV9OcylfgYMLekbpSbaxdgXCKp6zfA+MQNZg2gf5luXI+YEn+ScH73LaWFaoekHrYH2z5K0lCgP7Aa8Fci8et3kp4D/tcFnMAGbwMbShpi+5Ay7b+6pL1sH1u1ce2l6bydAOhu+zNJHwALSnqzyHf6AUtVa2n7aZrG72H7i6J1PQ1YCXi6jHVvSVMAQ2x/Wuep/6Z9O4PtNyXdC6wsaXDRNovQsI9POPrDitxjKdvvVmp8C6GaHl9JkhQUmf+nAlvY/qekXwJrEo7huUSW+O9s316hmR1CuXFMTEgZ1gG+IjLgHwdOJiIoKwIv2r6vKjs7iiJrWA84uUTukbQfkTjTmyj1Nbntl6qzsuMomt6BtgdLmpko49bf9kGSehMPOIfZfq1SQzsARXOSHYnEzPOBt4DtgFcJGc96wN51lrE0OYKrANsCzwEPAfcRYx4AnFPkS7WnabxrAb8nklJfkrQ1sAJwle2rFCXcujtqc3dzF0nGrRPp/CZJjZE0FSFt6GP7oaKnm4mInC1EJH09XnfHt0SthzWiQZJ2ACayfYyiXNI2RKLQOUXuMVw7WtcIEgzXgp4H3E849x8S+/QmYAJgkSIDqT1lrH2JxKB/Fgd4FiKp8WLbh0uauvEQUGckzU/s122J0nSHE5HeO4FfArMTv8HddY6CApREzOOJusV9gNlsr6ioQnMucCsRAR1SnZUdh6Jd8VnAprafbDi3JaHx98AlwJV1lp51BVL2kCQ1RVEC6h0iOrZVmU78KaEffKg4hnW/cU5m++Ny8/g5EfEFeAw4WNI5Jdo9DhE1G97drI7jboocLUAkdb1NRHjPJ5L8TiG0gQOAK+ru+DaNdybbr0u6iUhSHCzpQduvSrqRbyoCvFyxyaNFSUSdGnimOD29gFccFQ2QtDPhBL5t+/Lmbet2HI/gmjMtcW72AhYgEnEhju3fAlN3Bce3JK8NA34O/Av4XNIuwAqKeuprEGX6nk/Ht3oy4S1JakiJLhxPdPh6EBhIZE2vDNwIzAz1u3E2I6kXsJ2ia1t34FhJ/SStT2RP30UkjHS3fTewo+1XqrS5PTQ5gqsTUcEdiEoWvyead8wI/Jl42Lnb9iOVGdtBNE0RnynppyUpaABwAKGTXAeYHli+xo7vT4HrCKnKimXx54SD/wtFE4uXiIoOdW86MwHh/CFpmSJdGRe4gkj2WtX2a4pSZ/sDb3WBRL5GEm2j9fRtwEREw5khwGFEOcZ5bZ/vmpeZ7Cpk5DdJakaZCt4PuNH2fWVa7Yby3uLALoTOt+4MIZy/HoSsYQ2iIPxixPhPBZYknKPXbH9SkZ3tQtIkACXRZ2IiiW3nEtGehYj6vkt06ZsSOMr28xWZ26FIWgw4AtjE9vOSxrV9oqRXiTqwixDjfaFKO0cXRdfBfsCxti9oLHc0mnmU2Nf3SnqPeMjZshpLO4xJiaorXxNJmevY7itpOUKm9JGinfFJRD3q2kd8mzXNkh4iZuO2BHqV8S5EPPScU6WdybdJ5zdJ6kdPIjlmVUnX2n60RB/mJaKFh9n+e10lD4o6vuM5WtdORtQnXpKoZnE2cLGkLYkEkpWI6HctE6BKdHsf4ANJ59n+WNIXRMc6yrT/qcDCjhq3b1do7phgVuARYKik3Ygp4kmAtW1fI2mSumb/FynOHsB5zY6vpB0Jp35rYF1gUSI5dUfb/6zC1o6g7KO3Jd1KPLSeYfux8vYBwFGSbidmnPey/feqbO1ImmbhNib06l8AlwIDFbW5zyeaW2TEdywiE96SZCynaTp8QUI39xJgIhI4LXBmSazoDkzmKG9WO2cBhjsMvyKcg4HAgkSh/wWAVYAXbJ9Y1p2ccJJr7RCWTPC5CQ3o6ZIOI6Key9n+XNKGhE5yM+DrOu7XBk3H8iJECbqviP07LxHJf4BogHBjkbLUGkl/Ay5sjEXSesTMzAfEufvromcf3zVvNV7268+Idr4TEAlu1wIXOeptN9adtDzY1vIa1aBpzBsTJSRfI47h9Yu0Yw4imXESRyOLZCwiNb9JMhZTkiga02qXAMsCzxIVHa4jIsC7SVrQ9hBHzczaan1LIsi7RET3KOA+R1mr24FbgNkk7VvW/ajh+Dbp7mqBonoFALbPBR4FNpO0DdHA4h/AI5L2ITSDZ9seVNf92qAcy6sClxMPam/a3gRYwvaZxD1pLUITW1v0TQfFr4mHlgZvE87RukQDhCXL8lonLpb9ug5R5eAzR4OHI4nukhtI2kTS38tMx2eNbaqzePRpnLtN9r9FVOs4j2gm9JqkNYGtgDfT8R07Sec3ScZCSuIIRBekiYlM/9WAu4kb6Mu2nwSuBN7gm/a2taXJYXiFqOowAPiZpDlL5Oh64J/A9JK+1Q2pTjdSSVMSzTjmbFq8EfAlkSy0he0DCT3oi8C2tm/ufEs7njLmY4Heth+UNE/R/Y5fZjYuI7SgtUzmkzSRpOkdjQvmJc5PSdoKwPa/bP9X0ZRmBr6Rt9Tm+B0RitJtBxHttR+QNC3wPFHKbRlC4tHX9ueuaaUDRQ1qSqT+15L+qOjS9jER4b4JmFLSrwgd+7/rHM3v6qTsIUnGMkqSzHFEsfvngQuIqeCpiaSvTWy/XKbDbwa+sl1r57dpCnFtokHHDsCcRNRsAuDA8v+iwCO236nM2A5A0omElGNrItL7uu29Ja1LRPdfIKbLP63Oyo6n6HkPAgYRU8JLEg7gncANwFQu5b/qSJn2v4BIcluF0HP/gjhuPy3vzQL8H7B7F3qoWYxIsr2AKLe4OFGreGtC0z1e0bPXUupQItYHA28SDXXOJK698xKzUp8RreU3JdpUn2P7urqOtxXIyG+SjEWUm+fZRJTzaeBnhLZ3cSKDeL3i+C4EHArMVXfHF4ZPmy5PjOlKRzvfZ4iIykCiVNIjwAd1dXwl/UzShQC2dyOi+M8AX9jeuyy/mtC9zgNMUpWtHUVDjiJpFknzEFr1J4FpiPGvTUT4J7P9ep0dX4ByzN5CSHausf0AcBVwITHmw4HNgX3q7Pg27deZFDVsXwP+TnRbfJ6o63sCMIvtL21/DLWOcJsorzg7McY/2t6FKNfWAxhs+y9EqclN0/Ed+8nIb5KMJUgal4j4PWR7/ZLAth9R8utvRGTs30SVlqWBPxVtXZdA0q7AR7YvkDSeSwMHSdMRXa8+tX1nlTaOLoparxcRlSn2tX1FkXn8iahasb5LZ7qy/k/q6uS3pUTzDyAcpM+BY4DnygPPL4EzgAPq7Aw2Ux7iFiWivuvaHtDm/fFsf1V356joWncnGs4MIqLZX9oeVKb+zwX+UNdzFoYn1Ta6S35Yxrw/kXi7ZVlnNeL4XtX2Z9VZm4wKGflNkrGEEsH9LbCMpK0dNTAHAnPY/oDQhd5LNLXY3vb1dUv0GgnTE5FAmhzfxYAhtq+r601U0lxEsuKZhMRhMRie3Hc4MW16laKmL+W9ruL4zkXo1VcgIoMLEXVQKRrfPwGH2765rsdyUxR0sZKwOMT20UTC0zWS5i3/jpLUAxgMtY6CNmaoDiWqkHQn9uswoJuk+YjEt33qes4CKDpKXk/MxF0t6WSic9vRwCBJe5RV/0OMvdYNSlqNjPwmyViCvukBvyTQn2h3OgWwVal40GVo0vj+FBjf9mOKmr6nE8l8B5SkoPOJJJr7KjV4NJHUk0jwesD2RZJmI5L2drHdr6wjYpp8BeDXQO2rOgBImoEo6bUH8D9Ct76Z7f9IWpiQ9UzuqA1b9yjoakTjhn8APyF0nwcRzQ2OIsq6HVzXmZryYNbb35QZXAJYnpDoHMI3+3V+4uFmovJ3LfdrOU+vJx5ObyLyDS4FniDO5wWJhNTxiADFX2xfW421yeiQzm+SjEWo9IcvEc/biKjYMSViNKSON5LvQ9HW9mCiusOHxDTpF0TB+MGEE/En2/0rM7IDkDS5o9NT4+FmK6Kqw8HAwPIQICLC/2K11raPpuN3GULmsSmwIzAH4SA9X2QBJwJr1vWhTtIUtj8sr7sT+tZrbQ8oUdHVgB62jy5a56+LVr+uzuCswH3Aybb/T9LURDv1aYClywPMqkR1h981fpu6Imlz4Be291J0Hfy6JL1dDbxoe0dFabfViTrrD9V137Yq2eEtScYiiuMwju37Ja0MXCfpf7ZPr9q2jkTR5GAvop7vesQU6hdEOaSVJE1BZIi/VaGZ7aLhCNr+qCxqlHh6gciCn8H2c431iLJmtaThIJTjdzYi2rmF7XtKdL8n0FvRvW47Ykq8ro5vd+ASSY/Z3sf2kKINXRsYYPsZSTMDO5Xf5dnGtnV0jspD2yuKsl7XS+pu+whJ/YjKDutJeg74M3Bg3R3fwtTAVBBytDLmzyWtD9wuaXYiOPFv2++W9Wq3b1uZ1PwmyVhGkwN8H+EYHidpBn1TB7cr8AWwG6EV3JaIoMwGHCtpWdsf1tzxVdmPPy8Z8dM0bo627wXuAU5RdPaqZd3TBsW5vVDSYZL6EA1YpiQ06jhaUp9P7POpgZ1s31hXjW/R4u8ILCXp0LL4WKJW8e/L328QwaXJKjCxwyjH8dDi/L1ElFrcuOhdzyMa7fyaKE+4fxfKQ7gBmFnSShD7XFF7fSBR7gxHzeJ3K7QxaQcZ+U2SsZDiOHWzfbeiaP4nVdvUHpo0vlMD/3OUhELSQcBZth+RdAOwLuXmUleaxvobYur/HuBDSefZfrCsdiEh65iMaG5RS8qU/jnEFHhPojX1V0R0d3dJe9k+dkR6yLpFyiTNRJS8Gmj7JUmbAJdKMqH3vQnYRVERYC6iqsd73/+JYzdNx/HSwEqSXiE0zSsQ+QiyfRxwc3GOh3SFqf/ivL8N3AisJmmY7dtsf6FI5puZqFGd1JjU/CZJJ9N0U1mCaHTwGJHk9Z0bZeOm0ulGjgEkrUHUyIQobXWXpI2I7OkTCCnArrbvrsrGjkLSUkSy03VEstPaxL7+q6OzWQ9gRtv/qdDM0aY4CBMSDyrn2t5d0QHrYKKl6/GSliOc4CdsH9XYro7OkaQJCc3rbES96dOIGs2nOFi2AAAgAElEQVRvEVUsLiSqefQk9NyfFH1zLcfboOizzwZOJRo6DCEivq8Rv8e5tg/9/k+oL4pmQ2sRzv6L5d/2xLXrqiptS9pPOr9JUgElOeR4orrBH4CTiQjosKZ1GglSkxH1Qs+pxtr2o2jKcTSRIb0ckSl+DtHoYA0iQegi23+vzMgOoOnB5m6iQcnMtgcqSn6tBiwBnOSaVq9o0BTp2x44jKgEcK+kg4lM/z0ljQcsRUgEdrf9SpU2twdFDe51iX04BeEAL0q04e4BbAD8zfZBlRnZwZQHnH2I7oOXKOptLw8sYnuXckxP2xUeVr+P8kA3M7AF4fA/VZIaa/1Qk6TsIUk6HUkTAb2BVYHpiALx1xapQyOzuOH4TkJ0OatVdKUk/Kxs+6widfgjMdP9JPCkpIFAH6C7owTY5bYH1/Wm0mT3OMBQ20tLeoCQPfS2/UJxJroTusHaImkq4HJJ29g+Q9JQ4EZJFxCtfPtA1GqWdA/Rjvqj7//EsZuyb78ushwTOvW3ifbFGwIzENPgB0q6tDnBrW7om+TLRtfFcYE+kq51VHS4D9ha0ky2XwBeqOs5+2MocrNPiHJ9zcu75HhbiXR+k6STsf0/SW8SSTIzA2vbfldR+uttSQ8Xx3dSoB8xzfbPKm0eDaYG9i0RwtMk3QJsL2k722faPqfcWH8n6d6G5KOON5WmaO8KwCKSPrB9tu1FJd0v6Urb65dp8Ddsf1G1ze3B9vuSngAukLSp7b9JGkyUqlvf9quSetoeZHsQ8XBXS5oeQie2/ZmiwsFgIsHrS9t9y3rXEl3AahndljSB7S/KA/iCxHXpeqL73oTEuXwI8XDXg6Zk+Tqes/Ct83YKYt99/H2OfOM4aN6u0w1OOpSulD2eJGMlJeKHIut/nrL4ReIGc5Tt1yQtSskYLxfk8YEBwGF1cnwlzSlp5ZLYtRnw++LwXkLoBheW9DsAR/m2beucFATDI2SrAH8BHgWOlnSipF62FwPmlnR9WbfWjq+izBfAKUAv4DZJMxcncFvgdEW1jto6vDD8XJ22OL5rA7dI+guwoe2riWoAv5K0O4DtlxuOb+N8rwvlIfsISYtLWhy4nJAnXUNco24GpiU0vpcCJ9p+tSJzO4xy3q5FOPl3SVrjhxxfSRNI6pGOb9cgI79JMoZpusj+H9EW8xbgSGB+YCNFeag5gD1t31M2GwxsYvv5KmxuB3MA/SWtabu/pB2BU0uw5CxJw4B1SkT4DCJhqLYUR2dSYCdiCnwaYkp8HuBkSTva/rkiubH2FJ3vqoTO90hgS8IxXMn22YqOdv0lTQ985vqWcdueOE77EJ3pTgCGEg9zE5aZi+7AykUC8Hpjwzo5R2X2ZUKiI91mhLO7lqP+9PHA74AzbG9bpExDbL/VFaKfkuYFdiaSMn8KHFVmLK5qWqfh+E4K3EEcC89VYnDSoaTzmyRjiKZpNRE6wY2JiO+9RM3Tw4iIyqzAe7afLuvKUeGhVo5vGe9Nis5Hl0razPYNTQ7wsOIgdScShWrlKDSjbxpYGPhY0jaEE3wk0fp0KuBVQsZyqGue4NaG5YFrbF8JXCnpRGCApOVtnyrpete0NF/jnLW9fzkXLwMusX2FIoHvI2DvEgE8Q9JddZ25UCSs7UNUc7iFSE5cgTh+n7O9h6RjgP0lHW37kca2dT1vG0iaEdgVGGz7KeApSUOAg8u+vUzfzrvoB/zRdjq+XYSUPSTJGKI4vmsQpYF+CUxo+0uiq9lqwHG2X7E9wPbTjW3qGi1rOPq2rwe2Ai4uEeD7iIoWe0va3valjsS32qEoedWow7ywpHWLHvQ9YFyiZu94RP3e24Dr3UVK1TXxKjB+4w/buxHd6y4ukd+3oZbT/xMA85XXvyJmai4E1pc0ne2vgH8SUeCNJM1QY8d3HkLe8CjwdnFs+xHXqt8o9OvY3pto2DG0Kls7ijbH43tEEGKYpN+WiO91xMPrwU2Sl8kIicuhTbNySRcgS50lyRhC0fnqTKA/Ufvzc6Ic0mOSpiSco01dGj7UlaYI9/zAxETU6ANJvYnOXpsUCcSSxDWnNhrmZhSJMb8H/kVk9/clnIf5iDq+rwBHEPVQZwd2tP2PSoztIJr27aLABIQc5zWitu2ficYOsxF63/Md3etqR5mN6AUcR4xxDWAN249LOhlYjCg3+LaiRvNErmkFC0m9CIfuEtt/a/PeLMA6RJOOG2zf1OkGjgGajuNlieN1nDIL1YeYlbsfuNL2IElT2/5v2a4P8JrtOyoyPRlDpPObJGMASQsTju85tk+XtADRwncawkl4uEyvDa7U0A5C0mrAicDVhHZwHUfXtrWIUm29S2SllhSnYBNgEsLxnRE4wfZDiiz4FQjH+D3iQedr2/+uxNgORtHi9a/AlUS90/0J2cqRwIdEV7c/uqY1mhWl27Ykpv+XIcrTnWl7z6Z1TiL28Uq2367E0A6iROfPB7Z2dC3rTpTnc3l/fqJBy8+AvYGP6i5zgOENO04BziJab79I6H3XA5Ylao5fSPhFtZx9S348KXtIkjHDY4RjsAGA7ceIaMtnRHmviYip4toj6edEA4tViBvIhMBFkpYoEoj1iJa3tUTR6elq4EFiKvx/hE57EQDbhxCayUuAGWzf3RUcXwUTArsAe9neH1gaOJBwjNYkdJOr1dXxLcwKzElIcwYD6wM/l7SDpMkBbO9KdOubtTIrO44hRGLq6hBJjAzf3ZqSkLRcBRxu+8O6O76SukkaB9iUeGA9yfbiRLOSU21fRDQteajOsrNk1MiEtyTpANpM/U8BPG97ZUnXS7rY9ma2nyi6s4G2/1exye2iTbb3s0Slg5mIG+YUkv4M3CxpBdvXjGCbWlCkK/2JknO3lWXnEM0OZldUObjF9mFNU+ddgrKvBkr6D1GlRLb/I2lrIiLYz/YHwAeVGtpObD9QpAxrAwsT0of3iQ6MXyhqGG8IbFD3mZqSqDlUUl9gUUnP236i4fApSp1tDGxn+/MqbW0vTdebCRy11V8jahQ32Ai4pJy3Z6TT21pk5DdJOoDi+K5FJIzsDJwoaR/bawETSrqqrPe47ZeqtLW9NDn6q0vaFxjXUZJtPuCustoASkWHBjV0fOchpkHHo0R5AWy/A1wAfEokBzUiaAe55lUdGklBijq3P5HUDXgB2IFI4gPoRhe4dzQnQBWt8hXEg+vehH57D6IV99bApXV1fNskek2sKG/WD5gI2Kxx/Epahqg1fnFXcXwlrUzUnu5BVM/ZRtKixeGdl6i2MynxMJu0EKn5TZIOoGSKXw3sX7Su8xE3z5uIG82dwM62H6/Oyo6jZIOfAOzeFBFdldCEvkGUw/qD7furs3L0UZQ3+hsR3ewnaQDwhu0tm9aZgdAMTgAcXaKgtaVEBYeV/Xgc8fAyA7AWofOdG3id0PgeXCQttaRNAtQvgScJyc5sRG3bDwgN8H+BSfwD3b/GZiRNA8xt+67i5B5IdNw7lqh2sB0hzXoD+AnRdKe2+7WZ4vieAmxve0BZtiEx5jeIOuuHdJXxJqNGOr9JMpo03UDHA74myiDtbvvfZdmWwJzNiTN1pWgBJ7H9cvn7r8C/bV+kaFgxpNxolwQWB+603b9Ck9tF0br+pBGlL9Gym4HXbfdpWm9GoGedo/mKTnSfl9ezESWwdrF9X5GvLAmsTDQCmBL41Pb9dXQGm1GUITycmK1ZlZDvHEm05v4jkbx4jGvclU/RgW4hIt9gK6K2eC/igXwr21eXB/dJIGY16rxfm67JkwG7A7cTlRzWJCL4RwAvE1VpxrX9ZJ3Hm4w+tZ+6SpIqaLrILkeUtBpGTJseJGluR03Qd4GZJU1Ypo9rSXHkNyNqYo5XFo9PTBfCN9eRXkB/23s5SpvVqs5rgxIBHQiMVxwDbH9NZMDPWDS/lOVv1N3xBc6StFlZ9CExPfwfANv7EFnxB9l+pOib7y/v1dZhkDQdoflslKibgciBORh4h6hucXmdHV8A2ycATwDrAv+1fZ/tW4hyZmdJ2tb2F7bfKXKeWu/Xck1eiZiBGkIkofYjZi3+SbQgt+3nXWqN13m8yeiTzm+SjAblIrsCMTX6cFl8LqF1vUnSAYQs4BzbA23Xtkh8ceT7EhUb9i/T/ecSTStWsf11SZT5O1HftrFdLW8qZep/DWKM88M3iUJEg5J5JV1UpY0diIF/ABuWKeHPiIeaVZrWuRUYWIFtY5L3gT8ROuZDiMhgf+IB58/AC7afrcy6DkLSFLaPIVrzTiNpJUV75juIxLaTJE2nqIZQe4rcbAPgPtuHAtsAO9k+DDiHqNRSy4fypGPJag9JMoqUiGYPInK0r+07i3P0GXCcpCcIHegWrmnR/wYNHSjRjnl6IiFoG6JW5jbAOZL+DiwB7OGaN+wAkDQvoYlc1/azkqYmdJKflkz5JWlKgKsjRaIyDlGP+HxJgwiZznuEVv1yRfvbj4HfAvtWZmwH0DRTsyQxQzHU9m2KTm5P2H5V0vREA5OT6prcBt8a69xEt7J/OFoxT0CUcRsm6b4y/hlc02YdzZSZtV7ANUTk/g0AlyYdkjYhdOsHNyLcSWvTJZ72kqQzcfA18BEwQ8kcbhSIXwB41Pa1XcDxVYmCLk8khjxDVDnoRWT/P0zoe48nurjdWFepQxsmJab+eygaWFwBPC1pJgDbQ+uayAfDy7fdQuhb/1acvhuJyhb7Ebre1YG3CC3obrb/Xud9W5zBNYhp71mA4yVtSlSyWFvSxYTW+cq6R3zLWNcGTiOa6mwsaZsigXgG6AMsVaK9n0D9WlE3aLbb9qeEnGMyorZ4M+MC+xSNcy3HmnQs6fwmyY+gccGUNKukmcviR4huXnOVG84viC5nk1dkZodSxrQqcRO9rSy7n4j6TgDsA0xq+0XbTze2qcre0aVp3y4uabXy0NKdiP6+QkgArgR+U52VHYOknxHTv8cRmf9vEfrtr21fRjzc7AcsYvtU2wfavh3qt2+L1n6C8npiogXzqkSb8c+Bu0vUczZCF7qua9qsQ9L4TcfxlESkfkciUfE84FeSNrd9EqEBftf2sDKrU7t9C9+KcK8InCHpj0QZvo2A3ST9rrGu7fMbD3B1HGvS8aTsIUlGQtNFdjXgDOBfkgbb3lzSnMTUYk+iycMRjpq3taVpvOMAmxNtUO8tkbPehDP8VyIj/usKTe0QyljXBI4hunxhe43G+5IWJLS+l1ZjYcegqFhxFjHkC8uydQgpy2yS9rN9SZlC3kHSgxQnqTqrRw9JkxKVDe6S9A9Cs/whIe1Yg6h08GYZ//O2r63O2vZRxnokMa3/aVnck6jmNLiMf3FgW0lfFQ1w7WlKbjuWGPt2wEK2+xSZww2KFvKnN29TkbnJWEaWOkuS70GlhFd5PTfRyvVC4FEimjKO7Q2KfnJO4GPbT3eF6IKkpQjd3JrAXkS5oDeJDOoViU5YvYrOudaUBL5LCSf/RUmLEIluFwPzEFHf3WzfUKGZHUKR5ZxI1LSdh4j8HkE4hKcQWuY3iLJ271ZlZ0cgaX9gRuDvtm+QdBAxW7Gk7ceK/vdMYDPXtP62pPFtf1l06b2AGR01ffclNPon235JUm+i4sPnwAF11fmWa+2UwFu2P5G0K5GQOTmRYLyu7TfKugsDE9m+syp7k7GXjPwmyQiQNBXR/ehmouzTOUT06HXbX0jamGiNeYft5YhEIaDLRBeWAqayvYekz4EHbD9TdK/z00Uc38I7RDmvIyW9SxT7n4iIIu0kaV3bT1RqYQdRnL4/EiWghtresLx1fkn+mtT2C8CXlRnZDpofWG0fVZyjvSQNIyqWdAf6SrqCqHawX40d38mJ0oq3EhU7NgA2l7QXUZN6deCyMtbtieYduxLHd+2c36JVv5rQ4y+hqLbzAfFw+imwpu13ywzdzI2Ib1cIRiQdT2p+k2TEzEVExtYmphB3JSo8LC9pgnIx3RT4QNKi1ZnZMYwgCeTfROtPbPctju86RLH8s+rs+DZpIxeQ9GtC83kcUf7qKkLqcSTQ0EPW1vFt3q+SJpU0qaO+6WbAlyU62oiSrQDUucrBFETt2rmaFi9NJDutDfyCaGpxOPA40fnrhromQJXo7UBCx7y07VMJzfb+wISENOnPxGxNb6LM1wzU0/GdFbie6KS4LiE/ux54iHCG7ymO75JEBPjlxrbp+CYjIp3fJBkBJenpYsIB/CPwHHFT6QNsoKiVadsb2H6gOks7hqKf+5WkHcvfdxK+01HEi56Ek3hA3TOmy1jXIfSvvQnN4DS2d7R9F/BroirAbRWa2W7KFPHS5fXqRB3ma0ri0xOERnIVSZcRkoddbD9amcHt5ysiAniApNklXQ68aPtXwGOEA7w6IYPob/s+qJ9zpKaavLYPAN4G9pO0bIl29ieSFhe23c9R5WFSQu6ylWtW6qtca1YjZuBeArB9CPAAMUPxF6KZ0J3EGPdyNPJIku8lZQ9J0obGNJntu8uNZm3CAT6ZyKI+BegmqW8dk4EajGA6sAfwW0lzEFKA04gyUOPaHiTpxOI41noasegjfw8sR2SGLwk8WRz8aYg2sIfYvr7mY90MWEjStMSY9iQigv3KuC6UtAtwGVEGqq6VDqYlkhX7EI0r9iVmLm50dKjD9mmS9iQedu6jvrKOKYHDJR1u++2yeFHCud1UUZf7VEk9gAMlPWr7Y+J83tT26xWZPtqUa04/4tjdoDjD8xNR7PdtvwYMUJTsG2L7vZqft0knkAlvSTICmi+ekpYlHOD3gFOB+YBhtv9dnYXtQ1I3l65zZcpbwJPAUGABwpFYkmgL+lvbV1ZkaofQZn9OBRxFTI2uAWxp++UigXgF+Mz2Z13hBippbyI5cZDtLcqyZQmd5D62z5HUy/bndR2vpAmJ6f5hxMNMT6LSw3TAns2RTkkzF2eplijKLO5FSDn+RDyI/8f2vpL2AH4K9LN9q6SZ6ujstqVxXJaH1q0JZ/8XhNTjrfJwXvuqM0nnks5vknwPbRympYFNiCnGI2se8Z2KaN27LlGn+GrCEXwauM72gLLegsS0+RLEFPmndXOOSqRMtt9vsz+PJrpdbWr7QUm/IaZP13PNS9U1ULS2/VDS9kTE83jgXtsDS7LQ9USVknfqfDzDcAf4NKIpx7p8U4d6LqIL4ysVmtehFP3rDoQjeJXt7cpyAQcBswK7u6YVHUZEkwM8JfFgPhtwvmvcbCaplnR+k+QHaOMwLUfUPa11BygASX8lIrwvEVHQD4mbygzArY0pcEVG+V+Bnep2M5U0HrA3MDVwmO3/Nt1ElwHWIpy/u4lM+D1t31idxe2naXxzAwcD/7DdV9LuRBT/CuA+R8WSyeu2T5tpG6lW1DE+l5geX49o3nEIMDvxkPNVFXZ2BCMY69TE2HoCu9r+X9N7s9n+T+dbOWZpOranImQ8swD9bfev1rKkjqTzm7Q0TRfUmYF3AYq+dZxGNKyu08FtKRGjFYBngdeJaODhwC9tP1/e7004hDfa7i9pCaK28TK236zI9NGmTPGvRHR+Ot72f5vem4JIpOkBvFQ03rXf14rWtruUP78mpsHPUZT9WoSQCDQ69g2r45ibztsVieYyPWyfoWg1fj4hC9iIiABP5yjfVjskTQQMtv2VpFWIKf+PbZ9SoqD7AVMBe9h+v0pbO4KiVZbtrxVJxQPbvN/Y79MA2wBX236uEmOTWpPOb9LylJvKGcAAosD/SbY/buMAd7c9RNEudQ7XrPyVokbmJYSm9Svgv0QZpEOI5JG1bX8gaTZCDnCD7WcVbWEnrZt2sM2+W4KIBA4BTnRp3lCkDtPavqQ6S9uPpPGBr5qmhW8gpsRfIiQAKwB32b6oaIBvrtvxOyIUHQePIhL5zgOutL2LokNdP6C77bWqtLE9FCnHJURC4n8Ip/5sQor0le0NywPcYUSThy1s17lUXQ8iz6AbkcA3L3Cc7S/arNdwgHvaHlSWDT/fk+THkKXOkpamJHstS7Q9vQgYj2hXPFmJio1TksOGKNqIXkskhdWGEtG9j0hwWp9o2DEz8BPbOwD/Aq6QNHWZLj2lOL7dbH9WQ8dXZd/NImkqR0mrc4mb6u5lnYUICUBtnQUY3tr2OGDipsXDW9sSzQ8GEq1t17d9TBdxfCclGjdsRJyzrwJrSbrIkci5AZEQVltK1PNiIsK5BdE6/ThibONKutz2h4TO97A6O74Axf5xiWodJxKNdb4oWubm9VyCEYMkjVtep+ObjBLp/CYtSXFqexHOwWKO+q53EclfXwFHF03kMNtDy822H5Hs9nR1lo8WnxFT+78CsH0Hce7PWN7fj0h2u6ZEXwaV9Wrl5DcoN8fViUj+2Yr6n+8Q8o2hkq4lOmD9zna/tjfXuqBobfsJcCgwhaRlbH9AOPU7SJqjvH8X8BrRoGXyCk0ebSSNr+hAh6R5CL3n1kS5zkOJaOhyRLmvs2wPdX07t40nabry5zVEicWFgAWKFGAQsCEwuaRrbX9Y9zyEpnPwX4CJuswTSJq4rSSnTTDiLKI8YZKMEun8Ji1JcWo/B1YhaqHuVJy9B4hp4y8oHc6K7u4GIrpyV1U2jw7lRvEhkfW+raSDJa1H3DAeguERl92AbWwPrnsUpThHGwCb2V6baFByVfn/cmLfbmv72ho7vpMTD2irEx27VgX+T9JShGP/LtHadm+iysN5wPREa9s6MimwuqJVb1/gk6Lf7gE8VM7d6YjuXldUZmXHsBCwjqJN8cPAjYQ2f2HiNxjfUdpr9bK81jTJGKYnHrzXBk4n5DoblHV+Immmcj0bKmkSIlBxnu23KjM+qS3Z5CJpGZousosDcwDP2n6oJEXdLgnbf5V0H/CU7U+Lc9SbSCipXSe3cqPo5mj9uRhwL+H4TlaSSnraHmR7COEc1hZFQ5JGNKgH8AmA7e0lXQn8yfaBknZo7Nu6JXo1sP2RpEZr2y8djQ2GEV0IjyQqdLxARPd7E9PJtWxtC2D7HUnvEA9p/Wy/Wt4SMJGk0whd9/q276njvi1JXPMS1Uf2JBI19yrj+LuimsVOQE9JVxUt7MOVGdxBlGvyGsBJxCzFq7YPL5rn5SQtAqxIlCF8vUR8ryO6Tf6zOsuTOpOR36QlaHJ8VyUiR5MB/SVt42jpuixwoqRdHXwKw1ufXlxHx7dBkwP8DrAY8AFF+9pIGKkzTdFbO0p37UREd5cuCUEQ0bOhZaXmfVsr1JqtbRvcBPyhLD4UwPbDhIb9UmAD2/eU5bXat8Wh+yXwFhGUOo2IYP9E0pKSeti+lkjM3ZaoZ9wlUJTlWwXYETgTmFvSMY7GOn0Jyc7Oth8vsqyDgAPT8U3aQ1Z7SLo0kqZzaQMqaRYiqa0PUR7pHKLk15WO0kG/AKa2fWs11o5Z9E3FimmJcmdn296rarvaQ9NDzcpE8tNrhAM4hIgkvQg8QrSn3ss1ruOr0toWOLzpmL6WkDM8Clxme4CipNlaRKTsY0lzEdUBapW42EDRkGN+4DXbVxXt727AE8S+3oSQJA38gY8Za5E0GbArkX/wDJHAeKvtyyUdQ8xinAVMSQSsnrP9XlX2dhSKqhxTAw8S1Ug2U5Sqm51IVvzU9o4j2K7W9amTsYOM/CZdnQMkzQtQpkq3JCJhxxAX2VOA4yRtbftxR1vQWupAR0ZxfLs5Sn39jIik1Zri+K5ElLy6CJiHmA59DDiAaOzwK0LPXFvHtzAhEb0+RNI0Rf/6nO1fAs8DG0ta0fZJQB/bHwPYfqHGju/ihOPXHfiLpIMdbcWPARYkEsLuqqvjW+hGyB2WKwmKDwIrSVoNOJB4kNuNqDQzUd0d38b1tSQlvgPsDCxejt0hxAPrkUQS57xN241TtkvHN2k3GflNuiRluvuTMuU/M3Cs7Q3Le2sRU8C9JS0AHAvsXeQPtaUpCjoFMKxE/b6jfWxEgNtu1+kGdxCS/gDcQehbDwc2tP1auVkuBPwfMS1+qdvUDK0baqHWtpLmI6b4/1mioDMQCamn2z68rFPbbmYlkj+u7bfL1P/dwI6OCiR9iAoWl9v+h6Q5gJ62n67z+dp0jfoNoeN9nojeL0kkZv6+zF6MA4xX9/M1GXvJhLeky1F0YacBb0g6ojhCM0q6wPYWxDR4nxI5m4+44dTa8YXhUdC1gH2IJKD9vyfa2WjXPD4wxDWvD0p08eoHfEw063i3aLvnsX2CpOMIPeFVhBa4VjQ7O7ZfKePpRSQ+TWT7f+X9Q4szWHvHt/BLoiPd55IG2H6zJG0+Xca9d40d38mJB7Khkna3/YykrYAtJT0BXAkMA7ZQ1By/rLFtXR1fGH6NWg04ggg6bA0sYHvXkuB2maTNivSsdudqUh9S9pB0KYqjMBjYjpgC/wOA7cWBaSRdCLwH7E3Ugf2D7QFV2duRlCnCnYmxHwocpShr1rxOo1TQpETji9k739LRpzFlKmkJSb2L/vNc4GXgmeL4LkvofZ8GsH0zsFGZUq4NkiaSNF5xGFaRdJCknR0lvg4iqlmcKmmqxjZ1dQbhW/t29qKDPR84mIjoL1m0nm8QEoF/VGdp+ykPKE8BPydK1q1FyB+eBpZwlGG8Bbi9LOtKLA6sA7xPSNCOB7B9MaF9HvL9myZJx5Cyh6RL0TSttghx41wGuMT29uX9m4CBjk5nXQZJMxIO0fS2VyvL1iZ+g2NsX6Zv18i8kkgSuqc6q0eP4ij8iajZuybRBeufREWDoUSr18Nt91dpe1q3qWK1Xmvbxn5aFTiamApfCViC0On/f3vnHm5XWZ373xvC5SQ1JYiIRcHGCyiHinirKAgqKokIcj1cPFguQlXA2gQrVIIFJLRC8SiCHCgQKUpFMFzlIo1ARSgqVBERQQQRucstGAh5+8f4FntmkVDIXsna35zj9zx5kr3XmvsZX+bca445vvGO9+1EMniZY251le06peL7sl77AjGZYxIhvF0DeDfwGLCvY6zXSo6ZvgPBSCwAABviSURBVNXS+EyeZPsRSUcQbQ7jgZ1t36kYdbaKY8JDlec2qYus/CatonzIvpEQP32WGJT+WkmzyutbAquW91RNr1JWuIeY4btQ0kcU83vnEMKRmZLWLInvZMKw4/O1JL6SJiiU4b2kcFfivN5FWNueY/vntt9fXtu6JL5yMeyo7UbqjljbKtT9lMT39cSOxXbEjOKJRJ/rSYTz14dotOrVdk4lrULMYf6MpL1K/DcSaz2HGOt1OzH269Tyf1N1FbSR+E4DDik7Tt8gzuN5JfF9J2FO8kDvuNrObVIfWflNWkf5MJ1ue5vy9TqEmORSoqJS9Q0FFrmpbAZMAcbZPqkIZTYCriFGuM2XtEbZKqe8/huHxfGYR9IkIik4mXAuW5GYBfp7ohq4h+1flZvrnbb/a1ixDoKSIK1WRFArEonQQcSDzUzbjyvMDi4gdjC2GWK4o0Ih8voYcHKphK5FuHvdTTy47mz7Vkmb2r5CjbGFtVIS/FcR/a5nERMcpgOn2z5f0srA3xIivyuGF+ngkLQp8Tu7t+2rJE0gruv9gEcJq+ol6ROSZJmQgrekehqJ4Hhi2/t2YF6p7t5cBG8nAP+HcLm6fWjBDoiy3vcQo9pOBHYqN5l9iGrR5sAKpcf5/sZxpw4h3KWibPk+Iul7xI3yKduXSPohkRztWRLfdxF9gzsPM94BsRGwYalwfwR4A3FNzyCsbc+z/URJ9jcYYpyDYCfgAELQdh7R3vFpouL7Z+Ua3xj4nMKMpspxbU1s/xz4uaQfE20sTwGPA4dLutf2tZKOLGuvduu/L/a3Ecn9VYpJM/MU86m/S9htL3QIOatdb1Ifmfwm1VNuFFsRPYL/i5j5eishnrha0kPEWJ19PWKLWi2lBcDALsAxZVv4WEkXAMfZ3qNUTK8rN5PqbiiSXgdML4nAcZKeAg6UZOAywuHqqFL53pao9Fc7sUPdtLa9iHhIe5qoBJ4G7Ei05Xxc0pPElI6ZbUh8e5Te+7sk7URcuysRJh67SboBeBLq3vpvfCZvQExhWau81GvVehMwz/aNzWOWb5RJl8nkN6meUvk7BNieGGf19yUB3JNoCdgSONr21UMMc9Q0KiMTbD8q6TdEG0CPnYAzSgX8hF6/a22UreHZRM/rrwFsn1hanA8kBFH/j5j5uiIwp1TMqqwcacTa9hZGrG3/QLG2Ba61/Z1yXg8gkv8qx0CVtY63fX85Z7cR1e2fES0QJwFTy78fI+ZvX1LruV0cpfd+XNnVmA2sXP5c5hbYjQOUXbcDyp8VgVMk/QD4iaSXEQ86uwwxxKTjZM9vUh2S1gZeYfs/ytfTCVvQhcR0g11t36YRBfnE0itZ7Q200drxfmI7/K+IqtEMYpzbj4lqypeJ5OGBGtda+gFPA861/XWVYfcUZytJ2xOJ0ZdsXzDMWAeBOmRtK+nPCBvmHwP/4jBzeBXwfqLlYXOiDeBU278aXqTDo+bPqB4K845/ADaxvUH53vaErfyjwDrAUQ5BbpIMhaz8JtWgKP29iBBzPSzpANsXE/MiP0aMfNqtJL7/l+idnA78EereVmskvl8m2jeeAs4sbQBHAncSW6eH2r7/OX7UWGc+0bP8aPl6BtEHu66knwL7E9fAdEk/dBl7VTE9a9snbf9AUs/a9lHC2vYIwtp2O2D3WhPfwkKiz3MDYuLB6sC6wEuIKv6XiMr+HpKOAh6p9Xe28bD6nG6L5b0r2H56CGEOjL61PUiYzqwjaSYwy/ZZkq4hdiwmZY9vMmyy8ptUh6QjCeenp4CvANcR/YNnENum65W/D7R90bDiHASNm+hkQgz0PSL534pwRzqc6G+eRFil/rTWm0pjrbsR4rV1gV8Qkw1uIirdP7d9gqS1a+4DVQetbSEMLIjzuBlwHGHHfASx1n0kvYGYY3zz8KIcDGq4LbKEaQYamb09gXgAqm4STeP3dkti9+lponVnY6KX+25Cm1D1vOKkXWTlN6kCSSt6ZJbpXMIZ6CJGegN3ISqgbyO2iA+yfVHtyUK5qbyPcKtbQCT4PyYqZVcRva9Tm8lCrettxH0R0QP6FmK9fywJwmZElRDgt8s/wsGgjlnbNn8HHaPLziB+R3cE9iV+n1cor98wrDgHiRZ1W1yXcFtc2fa3G+9pui3+O/HA94uhBLyUNBLfLYBZhCHJpcTEjiOI63gHYIakL9R4/SbtJJPfZMxTKmMHSTrFMZ/2EuJD9i+J/tC/A75ge1stOie16sQXQNIGxM3jRNv/Kela4CbbtxfhyBaMKKhbQWlleAC4vvc9hWPfNkQLALWK+SCsbSX9jDivR0o6ubzUs7Y9RdIlxOdztda2kl5EjKf7o6QPAG8FHrT9FUn/RLj0HQd8pvJWnUVQuC1+ilj7z4CfSVpAmM2s6Ge7LX4L2N92NYmvpDWBCURL2e+A9xAtSX9K7ESdaPsJ4GJJTwN31/5ZnLSLbHtIxjyK+bVzCbHMCUQ14TKiUnIasYW6DzHm61vDiXKwKMaZ/QkxzupuYAfbv2+8vjNhfjDT9tnDiXLZU3om301Ukf7W9nlDDmmpUYesbfXc9szzbe9Qzu1hwGTCxW5BrQlS80FbMZZuF2L6zJnAvznMZrYj2pQ2t/370so0h9ilumpYsb9QSjFiNvAwsQNzNrEjswnwGqI3/VZJexP9zicv8YclyZDI5DepAoVr28XEVunGRKKwFiEE+kn5/i9tXze0IAdAYxuxVxn630QCcbzt4xrv2x24z/aFbahwL4lSPXwzUUW7qta1lh2Jw4kk9wqHG9/WwIuJNo+VCYX8bsSD3vuIxKHaCrekHYm2pJuBq22frnAwO5NIgHcqCfAatm8aZqyjofE7uxktdluEZ8YQ/iuhP7iFcOR7DfEZfChRwT5P0obA14n52xcPKdwkWSKZ/CbVUKYdHEtMNXgjIab4D9vfUzgHVScWadLXP7cj8FPg+0Sv7xxCNX3S4o5Z/tGOjqVVw6uMr1vuAQ8AdcDaVh2yZ26iPrdFIjHch3g434wQNH6duOdWef3CM0WIK2yPK1+/jnBX/CCwd/l7PlGYONL2ucOKNUmei0x+k6pQ2Lp+EfhL2w/3CeGqp4jb/olIGPYheiQ/KukthPPV520fP8wYB8VSqOGfasO5lrQW0QLwQ2BtQiH/MTeMOip+qNkY2JAQPPXsmbckRtYdD/TsmVcCNrBdtUudRtwW/z9R3T6pfP8C4B6H2c7HgbkOa+PqKf3bX7U9RdKHCefBrW0/JmkKkfyuUlofqryOk/aTgrekKmxfUAQUv5S0nu2Hhh3TaFDY2q4O3GX7D8DriX7B1Qjf+08AFLHbNCJRrJ6uqOH7UUutbdUxe+ZGUtdqt8XFYfu7kj4p6THi93FT2/PK/8ltfe+t6jpOukMmv0l1lA/fPYiq0twhh7PUSFqXEIvcDGws6b3A/cSW+MPAVkUYMxVYp1fxrb2a0gU1/JJwC61t1SF7Zni226JiTN3NxDivHxGjCNcH1iRGMtZuxPIsitbgQ8Ds8iADMa6u6tazpDuMG3YASbI02L7A9tyimq8OSX8OnEv0xW1LTLE4lzDsuBm4siS+7wCOIcYHAXVWU/rO0z1ED+hCSR8pFd85xESHmZLWLEniZEZaPa4cQtjLhF4V0PZC20/Ynl4e6Kq7lss5+hvC1esewnTmxbb3IGyptwdeLWkTwolxe9t3DyveQdBIfL9M2DQ/ZftM4B+JWeMnES0eh9u+v8bf1+eD7cuBvSTdq5hHnYlvUg1Z+U2qpsYbS0lyphIjoH4FYPtQxQihJwjjin0lzSVmac6wfcmQwh01z6GGh6gYLpR0lu1vS7qyp4YnlOQzXdEYKOictW1n7Jkb53Uy8E5iksU1iqkWPbfF3WiB2+LzpTy0fZTKd+GS7pGCtyQZApLWAD4KvJRoc/gLQiD0vt42YhFGLbB9T+030a6o4XsshZivKmtbddeeuee2uCpx/fbcFhcSPdxT3ZjH3SVqP7dJt8jKb5IsZ8pN4l5JpxIVoxlE5aQnHFnJ9pO27+odU+tNpaGG3wU4pqjhjy1q+OOKGn4ScF1ZY5XrbNJ2MZ86Zs/cQx10W3wh1Hxuk+6RyW+SLGfK1mkvAT6JEIn8Hng5MfWhSlevJl1Vw3dBzOeO2DP30Ijb4jmE2+KdALYvKq833Rar7mdOkq6QgrckGQKNBPh+wvr1dqJyNm24kY2ePjX88Qqzg5uBPSW9tSS8TTV81RWjroj5JK1WqtoQDl9fBW4iHto2At4D7CBp7bL1f7rtnw4n2tHTPK+2Hwa2IayYt+t760rAZ2yfXaNoMUm6SFZ+k2QZUhI/2X5S0kTbj/deayTA90k6DdiTxlSHWulTw+/rMKY4U5IJNfydRI/zoSX5r5auiPkUzm0HAWtI6tkz38ii9sxTCMHXqaU3tpoe5n4a53ULYEdJPbfFnYA5kuaXFh5sn9Y8ZnhRJ0nyfEnBW5IsI0ri+w5CEb8qUe38okfmYvbe17vRruwy61UV2vj2qeE/DXwPuAbYihE1/K20TA3fFTGfOmDP3EQdcltMkq6RyW+SLEPKDXQGIXz6WBkN9KyET9J42wsUTlgLa1L+N+mSGl4dtLaF9tozq89tUdKngEsJt8VjgG1t31ne+ybgRbbnDiveJEmWnmx7SJJlQOPmfzWRIF0PTJA0yfYjfe9doSS+qwLHAgcDdz3rh45xuqKG76qYD1ptz9xJt8Uk6SopeEuSAdOofq0FzCf6O48H3kskh0h6maS1+5T/ZwOnNEec1YCkFUr85wDr0VDDl8R3Z+AS4Eu1q+G7Jubrxw17ZmA20cpyDHCh7fk1JoLqmNtikiRZ+U2SgVOSow8SVdzvA7fbPkzSRGBzSW8mqqDb2b6jVHznAAfXIoCCRateth+WtA3wTaLX9bjGW3tq+Atrr5R1Scy3JNywZyYcCadDnVXQMp2hM26LSZIE2fObJAOm3Dg/SYhiHgIOIPoIDyximfcAN9i+qFQOjwLOqWXkFTxbDQ/01PALiER+Vq8Htv+Y5R/t6OmSmK+x1hdkz1zxejvltpgkSSa/STIwigBqDeA/ge/b3rVsg78K+BzwsO1PLOa41Ww/uHyjHT1dU8N3TMzXanvmHo1Efw3iIeatjLgt3qXitjjcKJMkGTTZ9pAko6R3Ay0VsLsl7QccLWkL25dKuoURk4P1bd9Yjhtne2EtiW+/Gh54PWFbvBrwMuATAEXsNo1InFpBV8R80H575iaNyRStdVtMkuTZZPKbJKOgUTl6N5EA3QxcQGyNnyBpb9uXS7oZ2MONGb81TQHoqhpeHbO2VQfsmftpJMD3K8xm/opwW1zd9gXDji9JksGT0x6SZBSUG+dU4IvAfwG7EsK17wCHAN8sFeCF7jO3qIUuquGLEApov7VtX9xttmdeUTFHmyI+fYZGAnwfYTf+W1rgtpgkyeLJym+SjJ63E8nRa4l+0KMBbP9rmQJQXS9kjy6q4fvFfGqxtW1jrZvRbnvmZ9wWS6vG+pIWcVtsJMD3SDraFbstJkny3GTymyQvkEbC0DOsGEfMPB1PcYFSjDpbxfYZzWOGGPZSUdb5LWAisENJhv+C6Im8z/ZvgMvbpIYva+4X821UxHw7A+eVFoDjm8cMKdxRUda6iD2zpE2JNS8ANicSxq8TbS69404dQrhLje2nStW36bY4r/9aLf8f423PV+Vui0mSLJlse0iSF0Aj8Z0GHFKqSN8gEt/zSuL7TmL7/4HecbUmRz0xEHAqcB+RPBwI7FSSh5UAbN9l+57y7+rWKumlktYv5xNGxHyPEGK+z0GI+YBpwE1DCXSAKMxJxhHrPMb2sbbfDrwYOM726cREi+uKoLPK6mejrWNxbov9NuNNt8UTifFnSZK0jKz8JskLoCS+mxI9vnvb/oOkJ4lkd7/S9/pK4NO2/32IoQ6ELqjhuybma8TdenvmxsPqWsTD29bAZsR85snAyYppHSsS13PTbfHzrsxtMUmS50dWfpPkedAnCnobcLrtq8oW6TzgO0RF8G+ArW2fX6sAqp+mGp4QA91OqOGnDTey0dM1MV8jGeyEPXNZ6weJnu3jgemOSR2XAxtJOh64EpjskdFt5wKH2P7+0AJPkmSZkpXfJHkelJvoVsAGhGvbWuWlXoL7JmCeywzf3jHLN8rRURIh2X5S0kTbj/dea6rhFeOg9qRyNXwXxXyNxLcT9szlXH6AmEH9EHCApH90uC3+hnBb3M/2DeX6PwT4+1qEfEmSLB3p8JYkzwNJbyQEUAcQW6SnAAcDPyF6Qk8HdrF9/dCCHAVNNTxR8VsfWEQNX97Xqxyu3AY1vDpibds4b623Z4buuS0mSfLCyOQ3Sf4HJK0O/AOwie0Nyve2J5KmR4F1gKMc81CrpUw4aKrhv7u4BKi0eiyoXQ3fSAg7YW2rDtgz91+vkj5MjB7cx+G2OI64vmcCh7nPbXEoQSdJstzJtockWQx9N9EHCSerdSTNBGbZPkvSNcA8YJLtX9daKWvEvTg1/CN9722q4Y8lqt9VioK6IObroQ7YMzceZlrttpgkyejJym+S9NG4iW5J9PI+DXwV2JjoH7ybGA1VfXK0GDX8Coyo4X9ke0lq+HMINXz1oqDG/8FLCGvbVwIXuAXWthqxZ/4Rcd3u0KzualF75rOHE+XgKBM5DidalPYAbrT9KUm7Av8M7Gr70mHGmCTJ8MlpD0nSoJEIbQHMAs4nKkczgLnAhcCrgRltmObQFTW8OmZt27w23XJ75j56bov30ee2CHyKit0WkyQZHFn5TRJA0pqEov+Ptn8naRZwUXn5KGBH23eU974XuLs52aFWihr+k8B5FDU8UeE9UNJbCDX8DbYvKqK4o4BzbF85tKBfIF0T8/U9wO0I9OyZFwBziLadkxZ3zPKPdnQ01jrJ9iOSjiDO9XhgZy/qtnhW85hhxp0kyXDJ5DfpPCUBnE0YGvyWGHD/EmAT4DXA7rZvlbQ3IfA6eWjBDoiuqeE7KObrt2d+0GHP/BbiQefzbtgz10gj8Z1G2DAfTvRrn0C4LR6lcFv8F0LwVr3pTJIkgyHbHpJOI+n1hD3xZ4h+z+uIaufTRO/rUSXx3RDYn0iOq6W3tW37adt3A/sBb5e0RUn0bgGOAF4saf3GcePKcVUlvo2t/FZb26qD9swl8e25LX7H9h+Imc3HAB+QdC7Rq98Kt8UkSQZHVn6TTlMqQ1fYHle+fh3RJ/hBYO/y93zC1OJI2+cOK9bR8hxq+HcQa+6p4ccR28TznuPHjXm6IuZTnz0z8F5gQ2ISx8PANm6nPTOSZhBziY9oVO3HAasQSf/CmiexJEmybMhRZ0mncVgUT5V0m+0pwHrAysAE21+TdCmR/K5SKsDV3kRLItivht+wqOEnAt+U1FPDV534wiJivmOJntfbbR9W1rq5pDcTDwHb2b6jVE3nAAe7EocvjdgzH2b7dEmHlq+nEsnwLV7Unnn/3rGVX8etdltMkmTZkslv0nlK/+cnJT0G/IIwOZhXEt3b+t5b+020p4Z/LX1qeIXFbZU9rotDLbe2LS0dnbJnhmfcFg+g4bYo6QfAT0ol/zSi5SNJkmSxZNtDkhRKO8Bs2y8vX4+vVfDUo4tq+C6J+dQRe+Ye6ojbYpIky5YUvCVJwfblwF6S7pU0uUWJ7zTgkLKt/w0i8T2vJL7vJLbDH+gdV2ty1EUxn+17gVOJnuYZwIHATmXnYiUA23fZvqf8u7pz2xAtwojb4h2SZirG0p0F/DUxsm9X23P6jkmSJFmErPwmSR+lL3ae7bnDjmW0FDX81wgx21WSJhCtAPsRlbJXAgfZPn94UY6eron5ejTWvTpR/ZwCnGb7muFGNhga62u922KSJMuPTH6TZAnUukXcVTX8YsR8nbC2bSSIrbJnbqxrC2Kc2e7ApcTD3BHApsAOwK+BL9R+/SZJsvxIwVuSLIFab6YdVsO3VsxXBHmy/aSkibYf771Wzrds3yfpNGBPKrZnVsNtEfgdIUzcH/hTYl0n2n4CuFjS04TbYhuu3yRJlhOZ/CZJy+iKGr5fzEdoGGYTn2vb9on5zmgeM8SwXzBq2DOXvu31JS1iz9xIgO+RdLQrtWdWn9uipLOBXxItHa8hqvd3qEVui0mSLH9S8JYkLaL0fu4NvNT2jbavJ7aIP04I274CfLZ8v1q6JOaz/RSwEvB3RPvGtb1RfH3vc2ltmS9ppfLvmhLfTrktJkkyPLLnN0kqp6/HdxzwLmA6cC0wqyRDryCMKya1qMe39WK+RpL/IuDbRCvAqcBlpdrdfO8KDpe6VQljj4Nt37Xcg15K1CG3xSRJhksmv0lSMV1Tw3dJzNc4t622Z24i6QPAV21PkfRhYnzZ1rYfkzSFlrgtJkkyXLLnN0kqpU8NP4sRNfxEotVhIaGGnyGpFWr4Lon5ylpbbc/cj7vltpgkyZDI5DdJKqPLaviuiPmg/fbMS8L2hZI+RLgt9kR9K1DxtI4kScYW2faQJBXRr4YHzgZeAmxCqOF3L1vCrVPDqyPWtuqQPfNzUVogZgPr2n5o2PEkSdIectpDklRCF9XwfRMNWm1t24vbHbFn/p+w/V3iweYNQw4lSZKWkZXfJKmErqnhuyTma6y1U/bMz5cUtyVJMkiy5zdJKqGM85oq6TbbU4D1gJWBCba/JulSWqKG75qYr6y13555Q4c980Tgm5J69sydSnwhxW1JkgyWTH6TpCLarobvspiPFtszJ0mSjCWy7SFJKqRsj8+2/fLy9fjSF1otXRPzNarbk2w/IukIos1hPLCzF7VnPqt5zDDjTpIkqZ0UvCVJhdi+HNhL0r2SJrcg8e2UmK+R+LbenjlJkmSskZXfJKmY0ic6z/bcYccyGrom5oNu2DMnSZKMRTL5TZIW0Ibt8C5Y23bJnjlJkmSskoK3JGkBbUiO2i7mg27ZMydJkoxVsuc3SZIxg+0LgQ8Ba/ZZ27aChj3zHOBqYFppXVld0kaEPfOKQwwxSZKk9WTlN0mSMUUxc9hL0r20yNq22DPvDby0V9ktEx4+zog982dtXz+8KJMkSdpP9vwmSTImaYOYr6/HdxzwLmA6cC0wy/Z8Sa8gjCsmZY9vkiTJsieT3yRJxjS1JoNdsmdOkiSpiez5TZJkTFN54tuzZz4f+DQwA5gLXAi8mrBn1hJ/UJIkSTJwsuc3SZJkQHTcnjlJkqQKsu0hSZJkAHTNnjlJkqRWsu0hSZJklHTNnjlJkqRmsvKbJEkySrpoz5wkSVIr2fObJEkySmxfJWmqpNtsTwHWA1YGJtj+mqRLaYE9c5IkSRvIym+SJMmAKLOJ/41n2zPnB22SJMkYIXt+kyRJBkTb7ZmTJEnaQCa/SZIkA8T25cBeku6VNNn2gmHHlCRJkoyQbQ9JkiTLgDbYMydJkrSRTH6TJEmWIdnzmyRJMrbI5DdJkiRJkiTpDNnzmyRJkiRJknSGTH6TJEmSJEmSzpDJb5IkSZIkSdIZMvlNkiRJkiRJOkMmv0mSJEmSJElnyOQ3SZIkSZIk6Qz/DUfMbw2ggBfJAAAAAElFTkSuQmCC\n",
             "text/plain": [
-              "<Figure size 576x576 with 2 Axes>"
-            ]
+              "<Figure size 800x800 with 2 Axes>"
+            ],
+            "image/png": "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\n"
           },
-          "metadata": {
-            "needs_background": "light"
-          }
+          "metadata": {}
         }
       ]
     },
@@ -837,7 +2291,7 @@
         "import matplotlib.pyplot as plt\n",
         "import seaborn as sns"
       ],
-      "execution_count": null,
+      "execution_count": 19,
       "outputs": []
     },
     {
@@ -845,10 +2299,10 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 386
+          "height": 523
         },
         "id": "rTD7eN7zCIl_",
-        "outputId": "7e91290a-dd2a-48b7-d57b-a7d16ab09f52"
+        "outputId": "1b54bb85-d6bf-43d6-c5c6-9b109de02630"
       },
       "source": [
         "# List of DCIDs\n",
@@ -857,41 +2311,39 @@
         "\n",
         "# List of StatVars\n",
         "stat_vars_to_query = [\n",
-        "                      \"CumulativeCount_MedicalTest_ConditionCOVID_19_Positive\",\n",
+        "                      \"Count_MortalityEvent_COVID19\",\n",
         "                      \"Count_Person\",\n",
-        "                      \n",
+        "\n",
         "]\n",
         "\n",
         "# Build Data Frame\n",
         "df = datacommons_pandas.build_multivariate_dataframe(dcids, stat_vars_to_query)\n",
         "\n",
         "sns.lmplot(x=\"Count_Person\",\n",
-        "            y=\"CumulativeCount_MedicalTest_ConditionCOVID_19_Positive\",\n",
+        "            y=\"Count_MortalityEvent_COVID19\",\n",
         "            data=df)"
       ],
-      "execution_count": null,
+      "execution_count": 20,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "<seaborn.axisgrid.FacetGrid at 0x7f6a10f55590>"
+              "<seaborn.axisgrid.FacetGrid at 0x7e4142e37f10>"
             ]
           },
           "metadata": {},
-          "execution_count": 24
+          "execution_count": 20
         },
         {
           "output_type": "display_data",
           "data": {
-            "image/png": "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\n",
             "text/plain": [
-              "<Figure size 360x360 with 1 Axes>"
-            ]
+              "<Figure size 500x500 with 1 Axes>"
+            ],
+            "image/png": "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\n"
           },
-          "metadata": {
-            "needs_background": "light"
-          }
+          "metadata": {}
         }
       ]
     },
@@ -905,4 +2357,4 @@
       ]
     }
   ]
-}
\ No newline at end of file
+}