diff --git a/notebooks/jupyter/data/01_Exploratory_Data_Analysis_(Do_we_know_our_data).ipynb b/notebooks/jupyter/data/01_Exploratory_Data_Analysis_(Do_we_know_our_data).ipynb
index be4bc4ab..a949dd6b 100644
--- a/notebooks/jupyter/data/01_Exploratory_Data_Analysis_(Do_we_know_our_data).ipynb
+++ b/notebooks/jupyter/data/01_Exploratory_Data_Analysis_(Do_we_know_our_data).ipynb
@@ -102,12 +102,12 @@
"id": "mFimn8EVi_rK"
},
"source": [
- "#### Load Your Data"
+ "#### Load Your Data [DEMO - WALKTHRU]"
]
},
{
"cell_type": "code",
- "execution_count": 396,
+ "execution_count": 2,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -122,7 +122,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "--2019-04-27 03:11:03-- https://raw.githubusercontent.com/jbrownlee/Datasets/master/housing.names\n",
+ "rm: cannot remove 'housing.names': No such file or directory\n",
+ "--2019-04-28 21:24:13-- https://raw.githubusercontent.com/jbrownlee/Datasets/master/housing.names\n",
"Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.16.133\n",
"Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.16.133|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
@@ -131,7 +132,7 @@
"\n",
"housing.names 100%[===================>] 2.03K --.-KB/s in 0s \n",
"\n",
- "2019-04-27 03:11:03 (10.1 MB/s) - ‘housing.names’ saved [2080/2080]\n",
+ "2019-04-28 21:24:13 (66.7 MB/s) - ‘housing.names’ saved [2080/2080]\n",
"\n",
"Names and descriptions of the fields of the Boston Housing dataset can be found at\n",
"https://github.com/jbrownlee/Datasets/blob/master/housing.names\n",
@@ -223,7 +224,7 @@
},
{
"cell_type": "code",
- "execution_count": 397,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
@@ -261,7 +262,7 @@
},
{
"cell_type": "code",
- "execution_count": 398,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
@@ -297,7 +298,7 @@
"id": "Mm5EsDitJXgQ"
},
"source": [
- "#### Get familiar with columns\n",
+ "#### Get familiar with columns [DEMO - WALKTHRU]\n",
"Go through the dataset description. Have some thoughts about which features might be related, what meaning they have, what impact they might have on target variable.\n",
">>\n",
"- Medv is our price that we will try to predict\n",
@@ -313,13 +314,13 @@
"id": "Mm5EsDitJXgQ"
},
"source": [
- "#### Dimensions of Your Data\n",
+ "#### Dimensions of Your Data [DEMO - WALKTHRU]\n",
"Have a very good handle on how much data you have, both in terms of rows and columns."
]
},
{
"cell_type": "code",
- "execution_count": 399,
+ "execution_count": 5,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -366,7 +367,7 @@
"id": "OH3OVpoBJRtl"
},
"source": [
- "#### Peek at Your Data\n",
+ "#### Peek at Your Data [DEMO - WALKTHRU]\n",
"Looking at the raw data can reveal insights that you cannot get any other way.\n",
"\n",
"Subsets of data from the head or tail of the dataset can be helpful."
@@ -374,7 +375,7 @@
},
{
"cell_type": "code",
- "execution_count": 400,
+ "execution_count": 6,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -389,17 +390,29 @@
"name": "stdout",
"output_type": "stream",
"text": [
- " crim zn indus chas nox rm age dis rad tax ptratio b lstat medv\n",
- "0 0.006 18.0 2.31 0.0 0.538 6.575 65.2 4.090 1.0 296.0 15.3 396.90 4.98 24.0\n",
- "1 0.027 0.0 7.07 0.0 0.469 6.421 78.9 4.967 2.0 242.0 17.8 396.90 9.14 21.6\n",
- "2 0.027 0.0 7.07 0.0 0.469 7.185 61.1 4.967 2.0 242.0 17.8 392.83 4.03 34.7\n",
- "3 0.032 0.0 2.18 0.0 0.458 6.998 45.8 6.062 3.0 222.0 18.7 394.63 2.94 33.4\n",
- "4 0.069 0.0 2.18 0.0 0.458 7.147 54.2 6.062 3.0 222.0 18.7 396.90 5.33 36.2\n",
- "5 0.030 0.0 2.18 0.0 0.458 6.430 58.7 6.062 3.0 222.0 18.7 394.12 5.21 28.7\n",
- "6 0.088 12.5 7.87 0.0 0.524 6.012 66.6 5.561 5.0 311.0 15.2 395.60 12.43 22.9\n",
- "7 0.145 12.5 7.87 0.0 0.524 6.172 96.1 5.950 5.0 311.0 15.2 396.90 19.15 27.1\n",
- "8 0.211 12.5 7.87 0.0 0.524 5.631 100.0 6.082 5.0 311.0 15.2 386.63 29.93 16.5\n",
- "9 0.170 12.5 7.87 0.0 0.524 6.004 85.9 6.592 5.0 311.0 15.2 386.71 17.10 18.9\n",
+ " crim zn indus chas nox rm age dis rad tax \\\n",
+ "0 0.00632 18.0 2.31 0.0 0.538 6.575 65.2 4.0900 1.0 296.0 \n",
+ "1 0.02731 0.0 7.07 0.0 0.469 6.421 78.9 4.9671 2.0 242.0 \n",
+ "2 0.02729 0.0 7.07 0.0 0.469 7.185 61.1 4.9671 2.0 242.0 \n",
+ "3 0.03237 0.0 2.18 0.0 0.458 6.998 45.8 6.0622 3.0 222.0 \n",
+ "4 0.06905 0.0 2.18 0.0 0.458 7.147 54.2 6.0622 3.0 222.0 \n",
+ "5 0.02985 0.0 2.18 0.0 0.458 6.430 58.7 6.0622 3.0 222.0 \n",
+ "6 0.08829 12.5 7.87 0.0 0.524 6.012 66.6 5.5605 5.0 311.0 \n",
+ "7 0.14455 12.5 7.87 0.0 0.524 6.172 96.1 5.9505 5.0 311.0 \n",
+ "8 0.21124 12.5 7.87 0.0 0.524 5.631 100.0 6.0821 5.0 311.0 \n",
+ "9 0.17004 12.5 7.87 0.0 0.524 6.004 85.9 6.5921 5.0 311.0 \n",
+ "\n",
+ " ptratio b lstat medv \n",
+ "0 15.3 396.90 4.98 24.0 \n",
+ "1 17.8 396.90 9.14 21.6 \n",
+ "2 17.8 392.83 4.03 34.7 \n",
+ "3 18.7 394.63 2.94 33.4 \n",
+ "4 18.7 396.90 5.33 36.2 \n",
+ "5 18.7 394.12 5.21 28.7 \n",
+ "6 15.2 395.60 12.43 22.9 \n",
+ "7 15.2 396.90 19.15 27.1 \n",
+ "8 15.2 386.63 29.93 16.5 \n",
+ "9 15.2 386.71 17.10 18.9 \n",
"\n",
"The first column lists the row number, which is handy for referencing a specific observation.\n"
]
@@ -428,7 +441,7 @@
},
{
"cell_type": "code",
- "execution_count": 401,
+ "execution_count": 7,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -488,7 +501,7 @@
},
{
"cell_type": "code",
- "execution_count": 402,
+ "execution_count": 8,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -503,8 +516,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Names of columns Index(['crim', 'zn', 'indus', 'chas', 'nox', 'rm', 'age', 'dis', 'rad', 'tax', 'ptratio', 'b',\n",
- " 'lstat', 'medv'],\n",
+ "Names of columns Index(['crim', 'zn', 'indus', 'chas', 'nox', 'rm', 'age', 'dis', 'rad', 'tax',\n",
+ " 'ptratio', 'b', 'lstat', 'medv'],\n",
" dtype='object')\n",
"\n",
"Overview of values as an array [[6.3200e-03 1.8000e+01 2.3100e+00 ... 3.9690e+02 4.9800e+00 2.4000e+01]\n",
@@ -532,7 +545,7 @@
"id": "kP4yEElUGNhi"
},
"source": [
- "### Check descriptive statistics"
+ "### Check descriptive statistics [DEMO - WALKTHRU]"
]
},
{
@@ -556,7 +569,7 @@
},
{
"cell_type": "code",
- "execution_count": 403,
+ "execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -622,10 +635,10 @@
"
555.000 | \n",
" 606.000 | \n",
" 606.000 | \n",
- " 588.000 | \n",
+ " 587.000 | \n",
" 606.000 | \n",
- " 571.000 | \n",
- " 589.000 | \n",
+ " 572.000 | \n",
+ " 588.000 | \n",
" 606.000 | \n",
" 606.000 | \n",
" 606.000 | \n",
@@ -634,36 +647,36 @@
" \n",
" mean | \n",
" 3.480 | \n",
- " 11.849 | \n",
- " 11.082 | \n",
+ " 12.059 | \n",
+ " 11.007 | \n",
" 0.070 | \n",
" 0.554 | \n",
- " 6.289 | \n",
- " 68.443 | \n",
- " 3.786 | \n",
- " 9.508 | \n",
- " 408.273 | \n",
- " 18.460 | \n",
- " 357.742 | \n",
- " 12.732 | \n",
- " 22.679 | \n",
+ " 6.303 | \n",
+ " 68.375 | \n",
+ " 3.827 | \n",
+ " 9.376 | \n",
+ " 409.168 | \n",
+ " 18.423 | \n",
+ " 355.647 | \n",
+ " 12.562 | \n",
+ " 22.652 | \n",
"
\n",
" \n",
" std | \n",
" 8.325 | \n",
- " 24.061 | \n",
- " 6.803 | \n",
+ " 24.199 | \n",
+ " 6.855 | \n",
" 0.256 | \n",
- " 0.117 | \n",
- " 0.725 | \n",
- " 28.307 | \n",
- " 2.082 | \n",
- " 8.660 | \n",
- " 168.008 | \n",
- " 2.166 | \n",
- " 89.547 | \n",
- " 7.325 | \n",
- " 9.475 | \n",
+ " 0.116 | \n",
+ " 0.717 | \n",
+ " 28.347 | \n",
+ " 2.137 | \n",
+ " 8.610 | \n",
+ " 168.146 | \n",
+ " 2.174 | \n",
+ " 91.318 | \n",
+ " 7.117 | \n",
+ " 9.429 | \n",
"
\n",
" \n",
" min | \n",
@@ -686,18 +699,18 @@
" 25% | \n",
" 0.080 | \n",
" 0.000 | \n",
- " 5.190 | \n",
+ " 5.130 | \n",
" 0.000 | \n",
" 0.448 | \n",
- " 5.887 | \n",
- " 43.250 | \n",
- " 2.100 | \n",
+ " 5.888 | \n",
+ " 42.700 | \n",
+ " 2.111 | \n",
" 4.000 | \n",
" 281.000 | \n",
- " 17.400 | \n",
- " 376.248 | \n",
- " 6.950 | \n",
- " 16.725 | \n",
+ " 17.000 | \n",
+ " 374.590 | \n",
+ " 6.877 | \n",
+ " 16.700 | \n",
"
\n",
" \n",
" 50% | \n",
@@ -705,33 +718,33 @@
" 0.000 | \n",
" 8.560 | \n",
" 0.000 | \n",
- " 0.538 | \n",
- " 6.205 | \n",
+ " 0.532 | \n",
+ " 6.229 | \n",
" 77.700 | \n",
- " 3.272 | \n",
+ " 3.216 | \n",
" 5.000 | \n",
" 330.000 | \n",
" 19.000 | \n",
- " 391.880 | \n",
- " 11.395 | \n",
+ " 391.240 | \n",
+ " 11.265 | \n",
" 21.200 | \n",
"
\n",
" \n",
" 75% | \n",
" 3.520 | \n",
- " 12.500 | \n",
+ " 18.000 | \n",
" 18.100 | \n",
" 0.000 | \n",
" 0.624 | \n",
- " 6.625 | \n",
- " 94.100 | \n",
- " 5.214 | \n",
+ " 6.630 | \n",
+ " 94.050 | \n",
+ " 5.245 | \n",
" 24.000 | \n",
" 666.000 | \n",
" 20.200 | \n",
- " 396.322 | \n",
- " 17.057 | \n",
- " 25.075 | \n",
+ " 396.060 | \n",
+ " 16.718 | \n",
+ " 25.175 | \n",
"
\n",
" \n",
" max | \n",
@@ -756,27 +769,27 @@
],
"text/plain": [
" crim zn indus chas nox rm age dis rad tax \\\n",
- "count 554.000 561.000 606.000 555.000 606.000 606.000 588.000 606.000 571.000 589.000 \n",
- "mean 3.480 11.849 11.082 0.070 0.554 6.289 68.443 3.786 9.508 408.273 \n",
- "std 8.325 24.061 6.803 0.256 0.117 0.725 28.307 2.082 8.660 168.008 \n",
+ "count 554.000 561.000 606.000 555.000 606.000 606.000 587.000 606.000 572.000 588.000 \n",
+ "mean 3.480 12.059 11.007 0.070 0.554 6.303 68.375 3.827 9.376 409.168 \n",
+ "std 8.325 24.199 6.855 0.256 0.116 0.717 28.347 2.137 8.610 168.146 \n",
"min 0.006 0.000 0.460 0.000 0.385 3.561 2.900 1.130 1.000 187.000 \n",
- "25% 0.080 0.000 5.190 0.000 0.448 5.887 43.250 2.100 4.000 281.000 \n",
- "50% 0.254 0.000 8.560 0.000 0.538 6.205 77.700 3.272 5.000 330.000 \n",
- "75% 3.520 12.500 18.100 0.000 0.624 6.625 94.100 5.214 24.000 666.000 \n",
+ "25% 0.080 0.000 5.130 0.000 0.448 5.888 42.700 2.111 4.000 281.000 \n",
+ "50% 0.254 0.000 8.560 0.000 0.532 6.229 77.700 3.216 5.000 330.000 \n",
+ "75% 3.520 18.000 18.100 0.000 0.624 6.630 94.050 5.245 24.000 666.000 \n",
"max 88.976 100.000 27.740 1.000 0.871 8.780 100.000 12.127 24.000 711.000 \n",
"\n",
" ptratio b lstat medv \n",
"count 606.000 606.000 606.000 606.000 \n",
- "mean 18.460 357.742 12.732 22.679 \n",
- "std 2.166 89.547 7.325 9.475 \n",
+ "mean 18.423 355.647 12.562 22.652 \n",
+ "std 2.174 91.318 7.117 9.429 \n",
"min 12.600 0.320 1.730 5.000 \n",
- "25% 17.400 376.248 6.950 16.725 \n",
- "50% 19.000 391.880 11.395 21.200 \n",
- "75% 20.200 396.322 17.057 25.075 \n",
+ "25% 17.000 374.590 6.877 16.700 \n",
+ "50% 19.000 391.240 11.265 21.200 \n",
+ "75% 20.200 396.060 16.718 25.175 \n",
"max 22.000 396.900 37.970 50.000 "
]
},
- "execution_count": 403,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -809,12 +822,12 @@
"id": "deGhLNUXGP4l"
},
"source": [
- "### Plot distribution of features"
+ "### Plot distribution of features [DEMO - WALKTHRU]"
]
},
{
"cell_type": "code",
- "execution_count": 404,
+ "execution_count": 10,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -829,20 +842,22 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:824: RuntimeWarning: invalid value encountered in greater_equal\n",
+ "/home/jeremie/.local/lib/python3.6/site-packages/numpy/lib/histograms.py:824: RuntimeWarning: invalid value encountered in greater_equal\n",
" keep = (tmp_a >= first_edge)\n",
- "/anaconda3/lib/python3.7/site-packages/numpy/lib/histograms.py:825: RuntimeWarning: invalid value encountered in less_equal\n",
+ "/home/jeremie/.local/lib/python3.6/site-packages/numpy/lib/histograms.py:825: RuntimeWarning: invalid value encountered in less_equal\n",
" keep &= (tmp_a <= last_edge)\n"
]
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
"
\n",
" \n",
- " 386 | \n",
+ " 333 | \n",
" NaN | \n",
" NaN | \n",
- " 18.10 | \n",
+ " 5.19 | \n",
" NaN | \n",
- " 0.700 | \n",
- " 4.652 | \n",
- " 100.0 | \n",
- " 1.467 | \n",
+ " 0.515 | \n",
+ " 6.316 | \n",
+ " 38.1 | \n",
+ " 6.458 | \n",
+ " 5.0 | \n",
" NaN | \n",
- " 666.0 | \n",
" 20.2 | \n",
- " 396.90 | \n",
- " 28.28 | \n",
- " 10.5 | \n",
+ " 389.71 | \n",
+ " 5.68 | \n",
+ " 22.2 | \n",
"
\n",
" \n",
" 27 | \n",
@@ -2532,21 +2507,21 @@
" 19.9 | \n",
"
\n",
" \n",
- " 378 | \n",
+ " 286 | \n",
" NaN | \n",
- " 0.0 | \n",
- " 18.10 | \n",
+ " 80.0 | \n",
+ " 1.76 | \n",
" NaN | \n",
- " 0.671 | \n",
- " 6.380 | \n",
- " 96.2 | \n",
- " 1.386 | \n",
+ " 0.385 | \n",
+ " 6.230 | \n",
" NaN | \n",
- " 666.0 | \n",
- " 20.2 | \n",
- " 396.90 | \n",
- " 23.69 | \n",
- " 13.1 | \n",
+ " 9.089 | \n",
+ " NaN | \n",
+ " 241.0 | \n",
+ " 18.2 | \n",
+ " 341.60 | \n",
+ " 12.93 | \n",
+ " 20.1 | \n",
"
\n",
" \n",
" 127 | \n",
@@ -2755,7 +2730,7 @@
"95 0.122 0.0 2.89 0.0 0.445 6.625 57.8 3.495 2.0 276.0 18.0 357.98 6.65 \n",
"223 0.615 0.0 6.20 0.0 0.507 6.618 80.8 3.272 8.0 307.0 17.4 396.90 7.60 \n",
"238 0.082 30.0 4.93 0.0 0.428 6.481 18.5 6.190 6.0 300.0 16.6 379.41 6.36 \n",
- "386 NaN NaN 18.10 NaN 0.700 4.652 100.0 1.467 NaN 666.0 20.2 396.90 28.28 \n",
+ "333 NaN NaN 5.19 NaN 0.515 6.316 38.1 6.458 5.0 NaN 20.2 389.71 5.68 \n",
"27 0.956 0.0 8.14 0.0 0.538 6.047 88.8 4.453 4.0 307.0 21.0 306.38 17.28 \n",
"203 0.035 95.0 2.68 0.0 0.416 7.853 33.2 5.118 4.0 224.0 14.7 392.78 3.81 \n",
"429 9.339 0.0 18.10 0.0 0.679 6.380 95.6 1.968 24.0 666.0 20.2 60.72 24.08 \n",
@@ -2779,7 +2754,7 @@
"270 0.299 20.0 6.96 0.0 0.464 5.856 42.1 4.429 3.0 223.0 18.6 388.65 13.00 \n",
"44 0.123 0.0 6.91 0.0 0.448 6.069 40.0 5.721 3.0 233.0 17.9 389.39 9.55 \n",
"470 4.349 0.0 18.10 0.0 0.580 6.167 84.0 3.033 24.0 666.0 20.2 396.90 16.29 \n",
- "378 NaN 0.0 18.10 NaN 0.671 6.380 96.2 1.386 NaN 666.0 20.2 396.90 23.69 \n",
+ "286 NaN 80.0 1.76 NaN 0.385 6.230 NaN 9.089 NaN 241.0 18.2 341.60 12.93 \n",
"127 0.259 0.0 21.89 0.0 0.624 5.693 96.0 1.788 4.0 437.0 21.2 392.11 17.19 \n",
"387 22.597 0.0 18.10 0.0 0.700 5.000 89.5 1.518 24.0 666.0 20.2 396.90 31.99 \n",
"80 0.041 25.0 4.86 0.0 0.426 6.727 33.5 5.401 4.0 281.0 19.0 396.90 5.29 \n",
@@ -2807,7 +2782,7 @@
"95 28.4 \n",
"223 30.1 \n",
"238 23.7 \n",
- "386 10.5 \n",
+ "333 22.2 \n",
"27 14.8 \n",
"203 48.5 \n",
"429 9.5 \n",
@@ -2831,7 +2806,7 @@
"270 21.1 \n",
"44 21.2 \n",
"470 19.9 \n",
- "378 13.1 \n",
+ "286 20.1 \n",
"127 16.2 \n",
"387 7.4 \n",
"80 28.0 \n",
@@ -2845,7 +2820,7 @@
"81 23.9 "
]
},
- "execution_count": 416,
+ "execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
@@ -2922,7 +2897,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.2"
+ "version": "3.6.7"
}
},
"nbformat": 4,
diff --git a/notebooks/jupyter/data/02_Data_Preparation_(Do_we_know_our_data).ipynb b/notebooks/jupyter/data/02_Data_Preparation_(Do_we_know_our_data).ipynb
index 450ec894..860e00b5 100644
--- a/notebooks/jupyter/data/02_Data_Preparation_(Do_we_know_our_data).ipynb
+++ b/notebooks/jupyter/data/02_Data_Preparation_(Do_we_know_our_data).ipynb
@@ -79,7 +79,7 @@
},
{
"cell_type": "code",
- "execution_count": 131,
+ "execution_count": 14,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -94,61 +94,11 @@
"name": "stdout",
"output_type": "stream",
"text": [
+ "rm: cannot remove 'housing.names': No such file or directory\n",
"Names and descriptions of the fields of the Boston Housing dataset can be found at\n",
"https://github.com/jbrownlee/Datasets/blob/master/housing.names\n",
"\n",
- "1. Title: Boston Housing Data\n",
- "\n",
- "2. Sources:\n",
- " (a) Origin: This dataset was taken from the StatLib library which is\n",
- " maintained at Carnegie Mellon University.\n",
- " (b) Creator: Harrison, D. and Rubinfeld, D.L. 'Hedonic prices and the \n",
- " demand for clean air', J. Environ. Economics & Management,\n",
- " vol.5, 81-102, 1978.\n",
- " (c) Date: July 7, 1993\n",
- "\n",
- "3. Past Usage:\n",
- " - Used in Belsley, Kuh & Welsch, 'Regression diagnostics ...', Wiley, \n",
- " 1980. N.B. Various transformations are used in the table on\n",
- " pages 244-261.\n",
- " - Quinlan,R. (1993). Combining Instance-Based and Model-Based Learning.\n",
- " In Proceedings on the Tenth International Conference of Machine \n",
- " Learning, 236-243, University of Massachusetts, Amherst. Morgan\n",
- " Kaufmann.\n",
- "\n",
- "4. Relevant Information:\n",
- "\n",
- " Concerns housing values in suburbs of Boston.\n",
- "\n",
- "5. Number of Instances: 506\n",
- "\n",
- "6. Number of Attributes: 13 continuous attributes (including \"class\"\n",
- " attribute \"MEDV\"), 1 binary-valued attribute.\n",
- "\n",
- "7. Attribute Information:\n",
- "\n",
- " 1. CRIM per capita crime rate by town\n",
- " 2. ZN proportion of residential land zoned for lots over \n",
- " 25,000 sq.ft.\n",
- " 3. INDUS proportion of non-retail business acres per town\n",
- " 4. CHAS Charles River dummy variable (= 1 if tract bounds \n",
- " river; 0 otherwise)\n",
- " 5. NOX nitric oxides concentration (parts per 10 million)\n",
- " 6. RM average number of rooms per dwelling\n",
- " 7. AGE proportion of owner-occupied units built prior to 1940\n",
- " 8. DIS weighted distances to five Boston employment centres\n",
- " 9. RAD index of accessibility to radial highways\n",
- " 10. TAX full-value property-tax rate per $10,000\n",
- " 11. PTRATIO pupil-teacher ratio by town\n",
- " 12. B 1000(Bk - 0.63)^2 where Bk is the proportion of blacks \n",
- " by town\n",
- " 13. LSTAT % lower status of the population\n",
- " 14. MEDV Median value of owner-occupied homes in $1000's\n",
- "\n",
- "8. Missing Attribute Values: None.\n",
- "\n",
- "\n",
- "\n"
+ "cat: housing.names: No such file or directory\n"
]
}
],
@@ -163,7 +113,7 @@
"\n",
"url = \"https://raw.githubusercontent.com/jbrownlee/Datasets/master/housing.csv\"\n",
"names = [\"crim\",\"zn\",\"indus\",\"chas\",\"nox\",\"rm\",\"age\",\"dis\",\"rad\",\"tax\",\"ptratio\",\"b\",\"lstat\",\"medv\"]\n",
- "data = pandas.read_csv(url, names=names)\n",
+ "data = pd.read_csv(url, names=names)\n",
"\n",
"!rm housing.names || true\n",
"!wget https://raw.githubusercontent.com/jbrownlee/Datasets/master/housing.names &> /dev/null\n",
@@ -184,7 +134,7 @@
},
{
"cell_type": "code",
- "execution_count": 132,
+ "execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
@@ -222,7 +172,7 @@
},
{
"cell_type": "code",
- "execution_count": 133,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -318,7 +268,7 @@
},
{
"cell_type": "code",
- "execution_count": 134,
+ "execution_count": 17,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -336,7 +286,23 @@
"Dataset rows count before dropping duplicates: 606\n",
"Duplicated rows count: 50\n",
"% of duplicated rows to total rows in the dataset: 8.25082508250825\n",
- "\n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
"50 rows deleted\n",
"Dataset rows count after dropping duplicates: 556\n"
]
@@ -351,6 +317,13 @@
"print(\"% of duplicated rows to total rows in the dataset:\", duplicated_rows_count / total_rows_count * 100)\n",
"print()\n",
"\n",
+ "\n",
+ "labels = (\"Total rows:\", \"Duplicate rows\", \"Unique rows\")\n",
+ "values = (total_rows_count, duplicated_rows_count, total_rows_count - duplicated_rows_count)\n",
+ "plt.title(\"Dataset with duplicated rows\")\n",
+ "plt.bar(labels, values)\n",
+ "plt.show()\n",
+ "\n",
"# Delete duplicates\n",
"if duplicated_rows_count > 0:\n",
" data = data.drop_duplicates()\n",
@@ -370,9 +343,16 @@
"#### Deal with outliers [DEMO - WALKTHRU]"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "![Normal distribution](https://www.mathsisfun.com/data/images/normal-distrubution-large.svg)"
+ ]
+ },
{
"cell_type": "code",
- "execution_count": 135,
+ "execution_count": 58,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -387,32 +367,80 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "count 512.000000\n",
- "mean 11.435547\n",
- "std 23.412362\n",
- "min 0.000000\n",
- "25% 0.000000\n",
- "50% 0.000000\n",
- "75% 12.500000\n",
- "max 100.000000\n",
- "Name: zn, dtype: float64\n",
- "Number of outliers in the Zone column (> std dev): 89\n",
- "Number of outliers in the Zone column (< 0): 0\n",
- "Number of outliers in the Zone column (= 0): 376\n"
+ "\n",
+ "count 506.000000\n",
+ "mean 6.284634\n",
+ "std 0.702617\n",
+ "min 3.561000\n",
+ "25% 5.885500\n",
+ "50% 6.208500\n",
+ "75% 6.623500\n",
+ "max 8.780000\n",
+ "Name: rm, dtype: float64\n",
+ "Number of outliers in the Room column (< mean - 2 std dev OR > mean + 2 std dev): 31\n"
]
}
],
"source": [
- "print(data.describe()[\"zn\"])\n",
- "zone_column = data[\"zn\"]\n",
- "num_of_outliers_zone_col = zone_column[zone_column > 23.32].count()\n",
- "print(\"Number of outliers in the Zone column (> std dev):\", num_of_outliers_zone_col)\n",
+ "print(\"\")\n",
+ "print(data.describe()[\"rm\"])\n",
+ "rm_column = data[\"rm\"]\n",
"\n",
- "num_of_outliers_zone_col = zone_column[zone_column < 0].count()\n",
- "print(\"Number of outliers in the Zone column (< 0):\", num_of_outliers_zone_col)\n",
+ "num_of_outliers_rm_col = rm_column[(rm_column > (6.3 + 2 * 0.7))|(rm_column < (6.3 - 2 * 0.7))].count()\n",
+ "print(\"Number of outliers in the Room column (< mean - 2 std dev OR > mean + 2 std dev):\", num_of_outliers_rm_col)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Distribution with all values\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\n",
+ "Distribution without outliers\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
"\n",
- "num_of_outliers_zone_col = zone_column[zone_column == 0].count()\n",
- "print(\"Number of outliers in the Zone column (= 0):\", num_of_outliers_zone_col)"
+ "print(\"Distribution with all values\")\n",
+ "plt.hist(data[\"rm\"],bins=40)\n",
+ "plt.show()\n",
+ "print();\n",
+ "print(\"Distribution without outliers\")\n",
+ "data_without_outliers=data[(data[\"rm\"] < (6.3 + 2 * 0.7))&(data[\"rm\"] > (6.3 - 2 * 0.7))]\n",
+ "plt.hist(data_without_outliers[\"rm\"],bins=20)\n",
+ "plt.show()"
]
},
{
@@ -440,7 +468,7 @@
},
{
"cell_type": "code",
- "execution_count": 136,
+ "execution_count": 19,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -453,7 +481,7 @@
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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CLFq0CAqFAh9++CGysrIwbtw4AMDgwYOhVCoxbNgwyOVy9O3bV7/Bi1tPcZRKJW7duoU33ngDLVu21L/+spj+KiAgAC1bttTH0rNnT/00c3NzrFq1CklJSejSpQs6duyIr776Cjk5OQCA48ePo1evXpDL5ZgzZw6WLFmiHyYprG3btvj666/1e16hoaFISUkB8Od/Yvfv34eXlxfCwsIwatQovP/++6XGVprmzZujV69e6Nq1Kzw8PEo8O6t3795YsWIFFAoFfvvtNyxcuBAAYGdnh7Vr1yI+Ph5eXl748MMPERUVhYKCgmKXExwcDH9/f4SGhqJLly6wtLTE1KlTS4zPxcUFK1euLHK21Nq1a1/5mqXStk1ZvWw7ACV/18qib9+++OCDD+Dv74/AwEB4e3vDwsLita7tKI5Op8O6devg5eUFT09PnD17FjNmzADw57GDkJAQyOVyfPrpp5gyZUqZrw1xcnLCsmXLsHDhQigUCty4cQNt2rRBjRo1SpynuvxWpTATgjelIqLKd/ToUcyYMaPIcaHqSKfToVOnToiKikLHjh0NHU6lM7k9ESIyDJVKhaNHj+qvcVmxYgW6du1q6LAkOX78OLKzs1FQUIBVq1YBQLme8VSdmPyBdSKqHEIILF++HGPGjIG1tTU6d+6ML774wtBhSXLhwgVERESgoKAAb7/9NlasWFFuw0PVDYeziIhIMg5nERGRZCwiREQkGYsIERFJZtQH1h89yoVOZ3qHfOrUsUNmprTrBYwB82f+zF9a/jKZGWrXti3TPEZdRHQ6YZJFBIDJ5v0c82f+pqwy8+dwFhERScYiQkREkrGIEBGRZCwiREQkGYsIERFJxiJCRESSsYgQEZFkLCJERCQZiwgREUlWpYrIjh07MHr0aEOHQUREr6hKFREiIqpeJBcRV1dX/POf/0RwcDC6dOmCU6dOYdGiRQgMDETv3r2RnJysf+/OnTsREhKCjz76CIMHD8bNmzcBAAUFBZg2bRq6deuGfv364eLFi/p5unXrhqSkJP3zDRs2YPLkyVLDJSKiiiAkatGihdiwYYMQQoj4+Hjh7u4uDh06JIQQYvXq1SI8PFwIIcTZs2fF8OHDRX5+vhBCiCNHjoh+/foJIYRYv369GDp0qCgoKBB5eXkiKChIjBo1SgghxIoVK8TcuXP16wsKChJnzpyRGi4REVWA1+ri26NHDwBA69atAQA+Pj4AgDZt2uDnn38GABw6dAhJSUkICQl5XrSQnZ0NAEhISEBgYCBq1KiBGjVqwN/fH+fPnwcABAYGom/fvhg/fjySk5ORnZ0NDw+PMsWXmZljkt08nZ3t8eDBU0OHYTDMn/kzf2n5y2RmqFPHrkzzvFYRsbKy+v8Vy2BpaVkoEBk0Gg2AP4tGcHAwvvjiizItu0GDBnj77bdx7NgxnDlzBkFBQTAzM3udcImIqJxV+IF1pVKJ2NhYpKWlAQC0Wi0uX74MAOjYsSNiY2Oh0WigUqmwe/fuIvMGBQVh69at2L17N4KCgio6VCIiKqMKvylVhw4dMGbMGHz66afQarVQq9Xo3r072rRpg759++Lq1avo2bMnateujXfeeQeZmZn6ebt164bIyEi88847aNCgQUWHSkREZWQmhDDagwY8JmKamD/zZ/6Vd0yE14kQEZFkLCJERCQZiwgREUnGIkJERJKxiBARkWQVUkRcXV2Rm5tb4vTs7Gx8++23r7y86OhoFBQUlEdoRERUjgyyJ5KdnY01a9a88vu/+eYbqNXqCoyIiIikqNCLDXU6HSIjI3H69GlYWlrCxsYGMTExiIyMxNOnTxEQEICaNWsiJiYG3333Hfbs2QOtVgsrKyvMmDEDbm5umDlzJgCgf//+kMlk+OGHH1CrVq2KDJuIiF5RhVxs6OrqivPnz+P27dsIDw/Hnj17IJPJ8OTJEzg4OODevXsIDg5GQkKCfp6srCw4OTkBAE6ePImlS5diy5YtRZZna2tbpjh4saFpYv7Mn/lXkwaMpWncuDE0Gg2mTJkChUKh7/JbnMuXL+Nf//oXnjx5AjMzM9y6deu111/WD8OYODvbGzoEg2L+zN+UVWb+FVpE7O3tsWfPHiQkJODkyZOIiorCzp07X3hfQUEBvvjiC2zYsAGtW7dGeno6OnXq9Nrr556IaWL+zJ/5G0nbk6ysLDx79gxeXl6IiIiAvb097t69Czs7O6hUKn27+IKCAmg0Gri4uAAANm3aVGQ5tra2yMnJqchQiYhIggrdE0lNTcXUqVOh0Wig1WrRqVMnuLu7QyaTwc/PD35+fnBwcEBMTAxGjx6NPn36wNHREb6+vkWWM2zYMAwePBjW1tY8sE5EVIWwi68R4u4882f+zF+KKjecRURExo1FhIiIJGMRISIiyVhEiIhIMhYRIiKSrMoWkdI6ARMRkeFV2SJCRERVX5UuImvXrkVAQAB8fX2xf/9+Q4dDRER/UaFXrL8umUyG2NhY3Lx5EwMGDICHhwfq1Klj6LCIiOj/Vdkr1l1dXXHs2DHUq1cPADB06FCEhoaiS5cuBo6MiIieq9J7Iq+LbU9ME/Nn/syfbU8AANu3bwcA3Lp1C1euXIG7u7uBIyIiosKq9J6IVqtFYGAgnj17hsjISB4PISKqYqpsEbl69SoAYNSoUQaOhIiISlKlh7OIiKhqYxEhIiLJWESIiEgyFhEiIpKMRYSIiCRjESEiIsleq4hER0ejoKBA0rz37t3Djz/+WOS14cOH486dO68TEhERVaLXKiLffPMN1Gp1sdM0Gs1L571///4LReTbb79FkyZNXickIiKqRKVebOjq6orPP/8c//M//wOVSoVx48bB19cXM2fOBAD0798fMpkMP/zwA+bOnQtzc3P88ccfyM3NRWxsLMLDw/HHH39ArVajSZMmmDt3LhwcHBAZGYl79+4hICAAb775JpYvXw6lUolVq1ahRYsWuH37NqZNm4asrCxYWFhg7Nix6NSpU4V/IEREVAaiFC1atBDR0dFCCCGSk5OFp6enePjwoX5aTk6O/r0TJ04UQUFBIjc3V/9aZmam/vHixYvFwoULhRBCnD59WgQFBRVZl4+Pj7h69aoQQog+ffqILVu2CCGEuH79uvD09CyyLCIiMrxXansSEhICAGjWrBlatWqFCxculNiSvXv37rCxsdE/j42NRVxcHNRqNfLy8vDWW2+Vur6cnBz8/vvvCA4OBgC8/fbbcHNzw4ULF6BUKl8lZADs4muqmD/zZ/6V18W33HtnFS4g586dw+bNmxETEwMnJyfExcVhy5Yt5b1KIiIykFc6sF5SS3ZbW1vk5OSUOF92djbs7Ozg6OiIgoIC/XIAwM7OrsR57ezs4Obmhp07dwIAkpOTkZSUxFbwRERVzCvtiZTUkn3YsGEYPHgwrK2t8cMPP7wwn5eXF3bt2gVfX1/Url0bHh4euHTpEoA/D9g3bdoUvXv3RrNmzbB8+fIi80ZFRWHatGlYt24dLCwssGDBAjg5Ob1uvkREVI5KvT2uq6srzp8/D1tb28qKqdzwmIhpYv7Mn/nzzoZERFQNlDqc9fzmUERERH/FPREiIpKsyt4etzyUdWzPmDg72xs6hDJR5WvwNPuZocMgojIy6iLyyewDyHjEP0zVQdyiAJjuoVCi6qvSh7Nep/MvERFVLZVeRF7W+ZeIiKqXSi0ihTv/BgQEIC4uDiEhIQgMDERgYCBOnToFAMjMzIRSqdRfmLhz504MGDCg1PbyRERUuSr1mMj06dOxadMmxMTEwNbWFo8ePULv3r1hZmaGmzdvYsiQITh27Bjq1KmDr7/+GhEREZg/fz6WL1+OTZs2wcLCqA/hEBFVOwb9q3z37l2Eh4cjPT0dFhYWePjwIR48eABnZ2coFAr07t0bAwcOxDfffAMXFxdDhkqVoDzPKKtuZ6eVN+bP/CuLQYvIuHHjMGnSJHTt2hU6nQ7vvvsu8vPz9dOvXLkCJycnpKWlGTBKqizl1aqCbS+YP/M34rYnhTv/Pn36FI0aNQLwZ6fgwmdtrVu3DhqNBjt27MCaNWvw+++/V3aoRERUikrfEync+Xfy5Mn47LPP4ODgAC8vLzg6OgIALl68iPXr12Pbtm1wcnLCrFmzMHbsWGzbtg12dqZ7ASERUVVTahff6owXG1YfcYsCOJxVTpg/86/WdzasStZ+1c3QIdArUuXz9G2i6sioiwjvJ0JEVLHYxZeIiCQz6j0RdvE1Xcy/fPJnd2UqjVEXER5YJ3o97K5Mpak2w1mTJk3Chg0bDB0GEREVYrAiwmaKRETVX6UOZ7m6uiIsLAxHjhyBl5cXevTogZkzZ+LZs2fIz89H3759MWTIEABAeno6JkyYgAcPHqBhw4aQyarNThMRkcmo9GMiVlZW2L59OwAgJycH69atg6WlJXJzcxESEgIvLy80b94cs2fPRocOHRAWFoa7d+/C398fXl5elR0uERG9RKUXkaCgIP1jlUqFGTNm4OrVqzAzM0NGRgaSkpLQvHlzJCQk4KuvvgIANG7cGO+9915lh0pEqJ5nulXHmMuTUXfxtbGx0T9evHgxnJ2dMW/ePFhYWGDYsGFFuvgSkeFVtwtXTf1iW6Pv4lvY06dPUb9+fVhYWODatWs4d+6cflrHjh31w153797V3/WQiIiqDoNeJ/Lpp59iwoQJ2LZtG5o2bYoOHTrop02ZMgUTJkzA7t270ahRIygUCgNGSkRExanUInL16tUiz1u1aoXdu3cX+9569erh+++/r4ywiIhIIp43S0REkhl12xO2gid6PWzRT6Ux6iLCVvCmifmbdv5UuTicRUREkrGIEBGRZCwiREQkWZUpIq6ursjNzUVAQABUKpWhwyEioldQ5Q6sx8bGGjoEIiJ6RQYrIgcOHMDixYthZWWFbt3+cyquq6srzp8/j5o1ayIyMhKnT5+GpaUlbGxsEBMTY6hwiYioGAYpIg8fPsTUqVOxefNmNGvWDN9+++0L70lKSkJCQgLi4+Mhk8nw5MmTMq+H91g3Xcyf+Zsyo+7iCwC//vorWrVqhWbNmgEA+vXrh6ioqCLvady4MTQaDaZMmQKFQgEfH58yr4fXiZgm5s/8mb+JdPF9GXt7e+zZswc9e/bE1atX0atXLzx48MDQYRERUSEGKSLu7u64cuUKbt26BQDYunXrC+/JysrCs2fP4OXlhYiICNjb2+Pu3buVHCkREb2MQYaz6tSpg1mzZmHkyJGwtrYucmD9udTUVEydOhUajQZarRadOnWCu7u7AaIlIqKSmAkhjPagAY+JmCbmz/yZP4+JEBFRNcAiQkREkrGIEBGRZFWu7Ul54sWG1Z8qX4On2c8MHQYRlcCoi8gnsw8g4xH/AFVncYsCYLqHSImqPg5nERGRZCwiREQkWaUMZ4WHh+OPP/6AWq1GkyZNMHfuXDg4OGDJkiWIj4+Ho6MjPD09cerUKezYsQMAsHPnTmzatAlarRZ2dnaYMWOGvtcWERFVDZVSRKZMmQInJycAwJIlS/Dtt9+iXbt2OHz4MGJjY2FtbY3Ro0fr33/u3Dns3bsXGzduhKWlJY4ePYovv/ySreCJiKqYSikisbGxiIuLg1qtRl5eHt566y2o1Wr06NEDNjY2AIDAwECsXLkSAHDo0CEkJSUhJCQEACCEQHZ2dmWESlWQlDPNjOXsNKmYP/OvLBVeRM6dO4fNmzcjJiYGTk5OiIuLw5YtW146jxACwcHB+OKLLyo6PKoGytrCgW0vmD/zN6K2J9nZ2bCzs4OjoyMKCgqwfft2AICnpyf279+PZ8+eQafTYdeuXfp5lEolYmNjkZaWBgDQarW4fPlyRYdKRERlVOF7Il5eXti1axd8fX1Ru3ZteHh44NKlS+jSpQsSExPh7+8PBwcHuLu76+9e2KFDB4wZMwaffvoptFot1Go1unfvjjZt2lR0uEREVAYVXkRq1KiBpUuXFjtt5MiRiIiIgE6nw5QpU4q0evf394e/v39Fh0dERK/BoFesT5w4Effv34dKpULr1q0xfPjwcl3+2q9evE8JVS+qfI2hQyCilzBoEVmxYkWFLp/3EyEiqli8Yp2IiCRjESEiIslYRIiISDIWESIikqxKFBGNhmfgEBFwzG3TAAAOM0lEQVRVRwY7O8vV1RVhYWE4cuQIvLy80KRJE+zevRv29va4evUq6tWrh6lTp2L+/Pm4c+cO2rRpg6ioKJiZmRkqZCIi+guDnuJrZWWlb4OyY8cOXLp0CXFxcahfvz7++7//G+Hh4fjhhx9gY2ODoKAgnDp1Cu+//74hQyYiokIMWkSCgoKKPG/Xrh3q168PAHBzc0PDhg1Rq1YtAEDLli1x+/btMhUR3mPddDF/5m/KjKqL78s8bwP/nJWVlf6xubn5C8+1Wm2Zls+LDU0T82f+zN+IuvgSEZHxYhEhIiLJzIQQRjvew+Es08T8mT/z53AWERFVAywiREQkGYsIERFJxiJCRESSsYgQEZFkLCJERCQZiwgREUnGIkJERJJVShFxdXXFqlWrEBwcjC5dumD//v36aceOHUNgYCD8/Pzw8ccf4/bt2wCA2NhYhISEQK1WQ6fTYciQIdi8eXNlhEtERK+oUq5Yd3V1xdSpUxEaGor//d//xZgxY3D8+HFkZmaiV69e2LBhA95++21s3boVW7ZswdatWwEAX375JWrVqgU7Oztcv34dy5Ytq+hQiYioDCqtiJw6dQpOTk7QarVo1aoVLl68iF9++QXr16/HunXrAAA6nQ5t27bF6dOnYWdnB5VKhY8++ggajQY7duyAnV3ZLsdn2xPTxPyZP/M3wrYnz9u6m5ubA3i1W+I+ePAAeXl5UKvVyMnJqdD4iIio7Ax6YN3d3R1JSUlITk4GAOzcuROtWrWCnZ0dCgoKMHbsWIwfPx5hYWEYO3Ys78VORFTFGPSmVE5OTliwYAEiIiKg0Wjg5OSEhQsXAgAWLlwINzc39OrVCwBw+vRpLF26FBEREYYMmYiICmEreCPEMWHmz/yZvxRV+pgIEREZHxYRIiKSjEWEiIgkM+pjIkRExkiVr8HT7GfFTqvsYyIGPTuron0y+wAyHhX/QRMRVVdxiwJQVU4dqJThLKVSiWvXrlXGqoiIqBLxmAgREUlW7sNZiYmJWLBgAXJzcwEAEyZMAADs3bsXU6dOxYMHDzBs2DCEhoYCAObPn48zZ85ArVajdu3amDt3Lho2bIjMzEyEh4cjMzMTAPDee+/hyy+/LO9wiYjoNZRrEXn8+DHCwsIQHR2Ndu3aQavV6nteqVQq/Pjjj7h37x78/PwQFBQEW1tbDB8+HBMnTgQAbN26FVFRUViyZAni4uLQpEkTfXPGJ0+elGeoRERUDsq1iFy4cAHNmzdHu3btAPzZbNHBwQEA0LNnTwBAo0aNUKtWLaSlpaF58+Y4duwYNm3ahLy8vCK9sd59912sW7cO8+fPh6enJz788MPyDJWIqFpzdraXNK28VdrZWc+7+AJ/FhetVov79+/j66+/xrZt29C4cWOcP39e3xtLLpdj586dOHnyJGJjY7F69WrelIqI6P+VdBpvtW574u7ujuTkZCQmJgIAtFrtS4ehcnJyUKNGDTg7O0On0yEmJkY/7e7du7Czs0OvXr0wefJk/Pbbb9DpdOUZLhERvaZy3RNxdHREdHQ05s2bh7y8PMhkMv3xjuK4urqie/fu6NmzJ2rXrg1vb2+cO3cOAHDmzBmsW7cOMpkMOp0OM2fOhEzGk8mIiKoSo75inRcbEpExilsUUGWGs4y6iBARGSO2PakkvJ+IaWL+zN+U869sPMhARESSsYgQEZFkLCJERCTZaxWRgIAAqFSqMs/Hrr5ERMbhtQ6sx8bGllccRERUDb1WEXF1dcX58+dha2sLpVKJgIAAnDx58oVOvefOncPMmTMBAB06dEDhs4oLL6Pw8+cXKt64cQMWFhZo2rQpli1b9jrhEhFROSvXU3yL69Rbo0YNjB07FlFRUVAoFIiPj8fGjRtLXdaJEyeQm5uL+Ph4AOziS0RUFZVrESmuU69arUbNmjWhUCj075k2bVqpy2rZsiWSk5Mxc+ZMeHp6onPnzmWOp6wXzRiTyuziWRUxf+ZvyqptF9/iOvUWx8zMrMj7ng9v5efn619v3Lgxdu/ejdOnT+PYsWP6e4wUXkdpeLGhaWL+zJ/5V9MuvsVp1qwZVCqVvrHivn37kJ2drZ/epEkTXLp0CQAQFxenfz0tLQ3m5ubo2rUrJk+ejKysLDx+/LiiwyUiojKo8LYnlpaWWLx4cZED6w0aNNBPnzx5MqZNmwZ7e3t0795d//rVq1exaNEiAIBOp8OIESNQr169ig6XiIjKwKgbMHI4yzQxf+bP/I1oOIuIiIwXiwgREUnGIkJERJKxiBARkWRGfWCdiKgivOzOgobGOxuWI95jnYgqQtyiAJju+V9FcTiLiIgkYxEhIiLJDD6cdfToUSxevFj/PDk5GUuXLkV0dDTeffddJCYmwszMDEuWLEHz5s0NGCkREf2VwYuIt7c3vL29AQBbtmzBjh07YGlpiRs3buDrr79GZGQk/vnPf2LlypX6NihERIZWlTsFV9suvq/j+PHj+Pe//42NGzfi+vXraNq0KVq1agUAcHd3x+HDhw0cIRHRf1TV1iomeXZWUlISpk+fjrVr18LJyQnAn40bn5PJZNBoNIYKj4iISmDwA+vp6ekYNWoUFi5ciKZNmxo6HCIiKgOD74ls3boVWVlZiIyM1L82efJkA0ZERESvyqivWOfFhkRUEeIWBfCYyP8z6iJCRFQR2PbkPww+nFWReFMq08T8mb8p51/ZDH5gnYiIqi8OZxERGZECtRZPHudJmpfDWX/BA+tEZGriFgVU6voMNpx16dIlhIeHG2r1RERUDgxSRDQaDd555x32wiIiquYqZDgrMTERCxYsQG5uLgBgwoQJmDZtGnr27InTp0+jRYsWCAgIwPz587Fjxw7cu3cPwcHB6Nu3L44fPw6VSoWoqCjExMTg119/hbW1NVauXAlnZ+eKCJeIiCQq9z2Rx48fIywsDOPHj8euXbuwc+dOvPPOOwCAnJwcbNu2DXPnzi12vvbt2+Onn35Cnz59MGTIEPzXf/0X4uLi0Lp1a2zYsKG8QyUiotdU7nsiFy5cQPPmzdGuXTsAgLm5ORwcHAAAgYGBJc5nY2ODzp07AwBat26N+vXrw83NTf/85MmT5R0qEZFRMtpW8DY2NiVO+2vX3sLPzc3NodVqKzQ2IiJjUZlXrJf7cJa7uzuSk5ORmJgIANBqtXjy5El5r4aIiKqAct8TcXR0RHR0NObNm4e8vDzIZDJMnDixvFdDRERVgFFfsc6LDYnI1LxOh2F28SUiMnFse1KO2MXXNDF/5m/q+VcmdvElIiLJWESIiEgyFhEiIpKMRYSIiCRjESEiIslYRIiISDIWESIiksyorxORycwMHYLBmHLuAPNn/sy/subjFetERCQZh7OIiEgyFhEiIpKMRYSIiCRjESEiIslYRIiISDIWESIikoxFhIiIJGMRISIiyVhEiIhIMqMrIn/88Qf69esHX19f9OvXD7du3TJ0SBVq/vz5UCqVcHV1xbVr1/Svm8Ln8OjRIwwfPhy+vr7w8/NDWFgYsrKyAAAXLlyAv78/fH19MWzYMGRmZho42orx2Wefwd/fH4GBgRg4cCB+//13AKax/Z/75ptvinz/TWXbK5VKdO/eHQEBAQgICMDx48cBGCB/YWQGDRokfvrpJyGEED/99JMYNGiQgSOqWGfPnhUpKSnCx8dHXL16Vf+6KXwOjx49EqdPn9Y/nzdvnpg8ebLQarWia9eu4uzZs0IIIVasWCEmTZpkqDArVHZ2tv7xzz//LAIDA4UQprH9hRDi8uXL4pNPPtF//01p2//1Ny+EMEj+RrUnkpmZiStXrqB3794AgN69e+PKlSv6/06NkYeHB1xcXIq8Ziqfg6OjIxQKhf65u7s7UlJScPnyZVhZWcHDwwMA0L9/f+zbt89QYVYoe3t7/eOcnByYmZmZzPYvKChAZGQkZsyYoX/NlLZ9cQyRv1F18U1NTUW9evVgbm4OADA3N0fdunWRmpoKJycnA0dXeUzxc9DpdNi8eTOUSiVSU1PRoEED/TQnJyfodDo8fvwYjo6OBoyyYkyZMgW//PILhBBYs2aNyWz/ZcuWwd/fH40aNdK/ZmrbPiIiAkIItG/fHuPGjTNI/ka1J0Kma9asWbCxsUFoaKihQ6l0c+bMwZEjRzB27FgsWLDA0OFUisTERFy+fBkDBw40dCgGs3HjRuzatQvbt2+HEAKRkZEGicOoioiLiwvS09Oh1WoBAFqtFhkZGS8M9xg7U/sc5s+fj9u3b2Pp0qWQyWRwcXFBSkqKfnpWVhZkMplR/idaWGBgIBISElC/fn2j3/5nz55FcnIyunTpAqVSibS0NHzyySe4ffu2yWz759vT0tISAwcOxPnz5w3y3TeqIlKnTh24ublh9+7dAIDdu3fDzc3NqHbhX4UpfQ6LFy/G5cuXsWLFClhaWgIA2rRpA5VKhXPnzgEAYmJi0L17d0OGWSFyc3ORmpqqf37o0CE4ODiYxPYfMWIETpw4gUOHDuHQoUOoX78+1q5di3/84x8mse3z8vLw9OlTAIAQAvHx8XBzczPId9/obkqVnJyMSZMmITs7G7Vq1cL8+fPRrFkzQ4dVYWbPno0DBw7g4cOHqF27NhwdHbFnzx6T+ByuX7+O3r1746233oK1tTUAoFGjRlixYgXOnz+P6dOnIz8/Hw0bNsTChQvxxhtvGDji8vXw4UN89tlnePbsGWQyGRwcHDBx4kS0bt3aJLZ/YUqlEqtWrUKLFi1MYtvfvXsXo0aNglarhU6nQ/PmzfHVV1+hbt26lZ6/0RURIiKqPEY1nEVERJWLRYSIiCRjESEiIslYRIiISDIWESIikoxFhIiIJGMRISIiyVhEiIhIsv8DeL3JxihHb0EAAAAASUVORK5CYII=\n",
"text/plain": [
""
]
@@ -470,7 +498,7 @@
},
{
"data": {
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\n",
+ "image/png": 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\n",
"text/plain": [
""
]
@@ -589,7 +617,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.2"
+ "version": "3.6.7"
}
},
"nbformat": 4,
diff --git a/notebooks/jupyter/data/03_Feature_Engineering_(Do_we_know_our_data).ipynb b/notebooks/jupyter/data/03_Feature_Engineering_(Do_we_know_our_data).ipynb
index 79294214..ad04a3ac 100644
--- a/notebooks/jupyter/data/03_Feature_Engineering_(Do_we_know_our_data).ipynb
+++ b/notebooks/jupyter/data/03_Feature_Engineering_(Do_we_know_our_data).ipynb
@@ -75,7 +75,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 2,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -90,17 +90,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "rm: cannot remove 'housing.names': No such file or directory\n",
- "--2019-04-25 14:10:57-- https://raw.githubusercontent.com/jbrownlee/Datasets/master/housing.names\n",
- "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.120.133\n",
- "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.120.133|:443... connected.\n",
+ "--2019-04-28 21:59:07-- https://raw.githubusercontent.com/jbrownlee/Datasets/master/housing.names\n",
+ "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.16.133\n",
+ "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.16.133|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 2080 (2.0K) [text/plain]\n",
"Saving to: ‘housing.names’\n",
"\n",
"housing.names 100%[===================>] 2.03K --.-KB/s in 0s \n",
"\n",
- "2019-04-25 14:10:57 (9.82 MB/s) - ‘housing.names’ saved [2080/2080]\n",
+ "2019-04-28 21:59:07 (51.8 MB/s) - ‘housing.names’ saved [2080/2080]\n",
"\n",
"Names and descriptions of the fields of the Boston Housing dataset can be found at\n",
"https://github.com/jbrownlee/Datasets/blob/master/housing.names\n",
@@ -188,7 +187,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -197,7 +196,7 @@
"0.7261570836552489"
]
},
- "execution_count": 2,
+ "execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
@@ -282,7 +281,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 14,
"metadata": {
"colab": {},
"colab_type": "code",
@@ -332,7 +331,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 5,
"metadata": {},
"outputs": [
{
@@ -357,7 +356,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
@@ -411,7 +410,7 @@
},
{
"cell_type": "code",
- "execution_count": 60,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
@@ -426,7 +425,7 @@
},
{
"cell_type": "code",
- "execution_count": 61,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
@@ -452,173 +451,6 @@
">We can gain 1% in accuracy with normalization"
]
},
- {
- "cell_type": "code",
- "execution_count": 64,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": 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\n",
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\n",
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\n",
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\n",
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\n",
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\n",
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\n",
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\n",
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\n",
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- "data": {
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\n",
- "text/plain": [
- ""
- ]
- },
- "metadata": {
- "needs_background": "light"
- },
- "output_type": "display_data"
- }
- ],
- "source": [
- "# we loop through all the columns\n",
- "for index,col in enumerate(data.columns): \n",
- " if(col not in ['medv','chas']):\n",
- " # and for each column we create space for one row with 2 charts \n",
- " f, axes = plt.subplots(1, 2, figsize=(12, 2))\n",
- "\n",
- " axes[0].hist(X_train[:, index],bins = 30)\n",
- " axes[0].set_title('Distribution of '+ col)\n",
- "\n",
- " axes[1].hist(X_train_normalized[:, index],bins = 30)\n",
- " axes[1].set_title('Distribution of '+ col + ' normalized')\n",
- "\n",
- " # we then use this to command to display the charts\n",
- " plt.show()"
- ]
- },
{
"cell_type": "markdown",
"metadata": {
@@ -701,7 +533,7 @@
},
{
"cell_type": "code",
- "execution_count": 65,
+ "execution_count": 9,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
@@ -755,10 +587,10 @@
{
"data": {
"text/plain": [
- ""
+ ""
]
},
- "execution_count": 65,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
@@ -818,7 +650,7 @@
},
{
"cell_type": "code",
- "execution_count": 69,
+ "execution_count": 10,
"metadata": {
"colab": {},
"colab_type": "code",
@@ -860,7 +692,7 @@
},
{
"cell_type": "code",
- "execution_count": 73,
+ "execution_count": 11,
"metadata": {},
"outputs": [
{
@@ -869,7 +701,7 @@
"0.7336244309845095"
]
},
- "execution_count": 73,
+ "execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
@@ -902,34 +734,34 @@
},
{
"cell_type": "code",
- "execution_count": 22,
+ "execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "accuracy of randomForest on full dataset: 0.977969\n"
+ "accuracy of randomForest on full dataset: 0.974383\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
- "/usr/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 216, got 192\n",
- " return f(*args, **kwds)\n",
"/home/jeremie/.local/lib/python3.6/site-packages/sklearn/ensemble/forest.py:246: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
" \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n"
]
},
{
"data": {
- "image/png": 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\n",
+ "image/png": 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\n",
"text/plain": [
""
]
},
- "metadata": {},
+ "metadata": {
+ "needs_background": "light"
+ },
"output_type": "display_data"
}
],
@@ -956,7 +788,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 13,
"metadata": {},
"outputs": [
{
@@ -1059,7 +891,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.7.2"
+ "version": "3.6.7"
}
},
"nbformat": 4,