diff --git a/dane.ipynb b/dane.ipynb
index 67eb80c..cfdb3ce 100644
--- a/dane.ipynb
+++ b/dane.ipynb
@@ -11,38 +11,27 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 97,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Collecting kaggle\n",
- " Using cached kaggle-1.6.6.tar.gz (84 kB)\n",
- "Requirement already satisfied: six>=1.10 in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (1.16.0)\n",
- "Requirement already satisfied: certifi in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (2022.6.15)\n",
- "Requirement already satisfied: python-dateutil in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (2.8.2)\n",
- "Requirement already satisfied: requests in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (2.28.1)\n",
- "Requirement already satisfied: tqdm in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (4.64.1)\n",
- "Collecting python-slugify\n",
- " Using cached python_slugify-8.0.4-py2.py3-none-any.whl (10 kB)\n",
- "Requirement already satisfied: urllib3 in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (1.26.11)\n",
+ "Requirement already satisfied: kaggle in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (1.6.6)\n",
"Requirement already satisfied: bleach in c:\\users\\adrian\\miniconda3\\lib\\site-packages (from kaggle) (4.1.0)\n",
+ "Requirement already satisfied: python-slugify in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (8.0.4)\n",
+ "Requirement already satisfied: python-dateutil in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (2.8.2)\n",
+ "Requirement already satisfied: tqdm in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (4.64.1)\n",
+ "Requirement already satisfied: requests in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (2.28.1)\n",
+ "Requirement already satisfied: certifi in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (2022.6.15)\n",
+ "Requirement already satisfied: six>=1.10 in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (1.16.0)\n",
+ "Requirement already satisfied: urllib3 in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from kaggle) (1.26.11)\n",
"Requirement already satisfied: webencodings in c:\\users\\adrian\\miniconda3\\lib\\site-packages (from bleach->kaggle) (0.5.1)\n",
"Requirement already satisfied: packaging in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from bleach->kaggle) (22.0)\n",
- "Collecting text-unidecode>=1.3\n",
- " Using cached text_unidecode-1.3-py2.py3-none-any.whl (78 kB)\n",
+ "Requirement already satisfied: text-unidecode>=1.3 in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from python-slugify->kaggle) (1.3)\n",
"Requirement already satisfied: idna<4,>=2.5 in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from requests->kaggle) (2.10)\n",
"Requirement already satisfied: charset-normalizer<3,>=2 in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from requests->kaggle) (2.1.0)\n",
- "Requirement already satisfied: colorama in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from tqdm->kaggle) (0.4.5)\n",
- "Building wheels for collected packages: kaggle\n",
- " Building wheel for kaggle (setup.py): started\n",
- " Building wheel for kaggle (setup.py): finished with status 'done'\n",
- " Created wheel for kaggle: filename=kaggle-1.6.6-py3-none-any.whl size=111961 sha256=3aa19c7655c19d77b65c2542567b6e34a57813227f1f2df6d0fd84accad6824f\n",
- " Stored in directory: c:\\users\\adrian\\appdata\\local\\pip\\cache\\wheels\\46\\aa\\c3\\b3e421522fb5acdd7c366a05c5fc80787615bdeed207e7f79b\n",
- "Successfully built kaggle\n",
- "Installing collected packages: text-unidecode, python-slugify, kaggle\n",
- "Successfully installed kaggle-1.6.6 python-slugify-8.0.4 text-unidecode-1.3\n"
+ "Requirement already satisfied: colorama in c:\\users\\adrian\\appdata\\roaming\\python\\python39\\site-packages (from tqdm->kaggle) (0.4.5)\n"
]
}
],
@@ -55,31 +44,13 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 98,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Downloading personal-key-indicators-of-heart-disease.zip to C:\\Users\\Adrian\\Desktop\\Semestr 1 (II ST)\\ML\\zadania\n",
- "\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "\n",
- " 0%| | 0.00/21.4M [00:00, ?B/s]\n",
- " 5%|4 | 1.00M/21.4M [00:00<00:11, 1.80MB/s]\n",
- " 9%|9 | 2.00M/21.4M [00:00<00:05, 3.51MB/s]\n",
- " 19%|#8 | 4.00M/21.4M [00:00<00:02, 7.25MB/s]\n",
- " 33%|###2 | 7.00M/21.4M [00:00<00:01, 12.0MB/s]\n",
- " 51%|#####1 | 11.0M/21.4M [00:01<00:00, 17.9MB/s]\n",
- " 65%|######5 | 14.0M/21.4M [00:01<00:00, 20.7MB/s]\n",
- " 79%|#######9 | 17.0M/21.4M [00:01<00:00, 20.6MB/s]\n",
- " 93%|#########3| 20.0M/21.4M [00:01<00:00, 22.7MB/s]\n",
- "100%|##########| 21.4M/21.4M [00:01<00:00, 14.9MB/s]\n"
+ "personal-key-indicators-of-heart-disease.zip: Skipping, found more recently modified local copy (use --force to force download)\n"
]
}
],
@@ -92,17 +63,8 @@
},
{
"cell_type": "code",
- "execution_count": 3,
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "'unzip' is not recognized as an internal or external command,\n",
- "operable program or batch file.\n"
- ]
- }
- ],
+ "execution_count": 99,
+ "outputs": [],
"source": [
"#!unzip -o personal-key-indicators-of-heart-disease.zip #nie działa na Windowsie więc korzystam z modułu zipfile"
],
@@ -112,7 +74,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 100,
"outputs": [],
"source": [
"import zipfile\n",
@@ -125,7 +87,7 @@
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 101,
"outputs": [],
"source": [
"import pandas as pd\n",
@@ -147,7 +109,7 @@
},
{
"cell_type": "code",
- "execution_count": 38,
+ "execution_count": 102,
"outputs": [
{
"name": "stdout",
@@ -212,14 +174,14 @@
},
{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": 103,
"outputs": [
{
"data": {
"text/plain": " State Sex GeneralHealth PhysicalHealthDays MentalHealthDays \\\n0 Alabama Female Very good 0.0 0.0 \n1 Alabama Female Excellent 0.0 0.0 \n2 Alabama Female Very good 2.0 3.0 \n3 Alabama Female Excellent 0.0 0.0 \n4 Alabama Female Fair 2.0 0.0 \n\n LastCheckupTime PhysicalActivities \\\n0 Within past year (anytime less than 12 months ... No \n1 NaN No \n2 Within past year (anytime less than 12 months ... Yes \n3 Within past year (anytime less than 12 months ... Yes \n4 Within past year (anytime less than 12 months ... Yes \n\n SleepHours RemovedTeeth HadHeartAttack ... HeightInMeters \\\n0 8.0 NaN No ... NaN \n1 6.0 NaN No ... 1.60 \n2 5.0 NaN No ... 1.57 \n3 7.0 NaN No ... 1.65 \n4 9.0 NaN No ... 1.57 \n\n WeightInKilograms BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\n0 NaN NaN No No Yes \n1 68.04 26.57 No No No \n2 63.50 25.61 No No No \n3 63.50 23.30 No No Yes \n4 53.98 21.77 Yes No No \n\n PneumoVaxEver TetanusLast10Tdap \\\n0 No Yes, received tetanus shot but not sure what type \n1 No No, did not receive any tetanus shot in the pa... \n2 No NaN \n3 Yes No, did not receive any tetanus shot in the pa... \n4 Yes No, did not receive any tetanus shot in the pa... \n\n HighRiskLastYear CovidPos \n0 No No \n1 No No \n2 No Yes \n3 No No \n4 No No \n\n[5 rows x 40 columns]",
"text/html": "
\n\n
\n \n \n \n State \n Sex \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 0 \n Alabama \n Female \n Very good \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n No \n 8.0 \n NaN \n No \n ... \n NaN \n NaN \n NaN \n No \n No \n Yes \n No \n Yes, received tetanus shot but not sure what type \n No \n No \n \n \n 1 \n Alabama \n Female \n Excellent \n 0.0 \n 0.0 \n NaN \n No \n 6.0 \n NaN \n No \n ... \n 1.60 \n 68.04 \n 26.57 \n No \n No \n No \n No \n No, did not receive any tetanus shot in the pa... \n No \n No \n \n \n 2 \n Alabama \n Female \n Very good \n 2.0 \n 3.0 \n Within past year (anytime less than 12 months ... \n Yes \n 5.0 \n NaN \n No \n ... \n 1.57 \n 63.50 \n 25.61 \n No \n No \n No \n No \n NaN \n No \n Yes \n \n \n 3 \n Alabama \n Female \n Excellent \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n Yes \n 7.0 \n NaN \n No \n ... \n 1.65 \n 63.50 \n 23.30 \n No \n No \n Yes \n Yes \n No, did not receive any tetanus shot in the pa... \n No \n No \n \n \n 4 \n Alabama \n Female \n Fair \n 2.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n Yes \n 9.0 \n NaN \n No \n ... \n 1.57 \n 53.98 \n 21.77 \n Yes \n No \n No \n Yes \n No, did not receive any tetanus shot in the pa... \n No \n No \n \n \n
\n
5 rows × 40 columns
\n
"
},
- "execution_count": 39,
+ "execution_count": 103,
"metadata": {},
"output_type": "execute_result"
}
@@ -233,14 +195,14 @@
},
{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": 104,
"outputs": [
{
"data": {
"text/plain": " PhysicalHealthDays MentalHealthDays SleepHours HeightInMeters \\\ncount 434205.000000 436065.000000 439679.000000 416480.000000 \nmean 4.347919 4.382649 7.022983 1.702691 \nstd 8.688912 8.387475 1.502425 0.107177 \nmin 0.000000 0.000000 1.000000 0.910000 \n25% 0.000000 0.000000 6.000000 1.630000 \n50% 0.000000 0.000000 7.000000 1.700000 \n75% 3.000000 5.000000 8.000000 1.780000 \nmax 30.000000 30.000000 24.000000 2.410000 \n\n WeightInKilograms BMI \ncount 403054.000000 396326.000000 \nmean 83.074470 28.529842 \nstd 21.448173 6.554889 \nmin 22.680000 12.020000 \n25% 68.040000 24.130000 \n50% 80.740000 27.440000 \n75% 95.250000 31.750000 \nmax 292.570000 99.640000 ",
"text/html": "\n\n
\n \n \n \n PhysicalHealthDays \n MentalHealthDays \n SleepHours \n HeightInMeters \n WeightInKilograms \n BMI \n \n \n \n \n count \n 434205.000000 \n 436065.000000 \n 439679.000000 \n 416480.000000 \n 403054.000000 \n 396326.000000 \n \n \n mean \n 4.347919 \n 4.382649 \n 7.022983 \n 1.702691 \n 83.074470 \n 28.529842 \n \n \n std \n 8.688912 \n 8.387475 \n 1.502425 \n 0.107177 \n 21.448173 \n 6.554889 \n \n \n min \n 0.000000 \n 0.000000 \n 1.000000 \n 0.910000 \n 22.680000 \n 12.020000 \n \n \n 25% \n 0.000000 \n 0.000000 \n 6.000000 \n 1.630000 \n 68.040000 \n 24.130000 \n \n \n 50% \n 0.000000 \n 0.000000 \n 7.000000 \n 1.700000 \n 80.740000 \n 27.440000 \n \n \n 75% \n 3.000000 \n 5.000000 \n 8.000000 \n 1.780000 \n 95.250000 \n 31.750000 \n \n \n max \n 30.000000 \n 30.000000 \n 24.000000 \n 2.410000 \n 292.570000 \n 99.640000 \n \n \n
\n
"
},
- "execution_count": 40,
+ "execution_count": 104,
"metadata": {},
"output_type": "execute_result"
}
@@ -272,13 +234,13 @@
},
{
"cell_type": "code",
- "execution_count": 41,
+ "execution_count": 105,
"outputs": [
{
"data": {
"text/plain": ""
},
- "execution_count": 41,
+ "execution_count": 105,
"metadata": {},
"output_type": "execute_result"
},
@@ -300,13 +262,13 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": 106,
"outputs": [
{
"data": {
"text/plain": "No 416959\nYes 25108\nName: HadHeartAttack, dtype: int64"
},
- "execution_count": 42,
+ "execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
@@ -329,7 +291,7 @@
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": 107,
"outputs": [],
"source": [
"from sklearn.model_selection import train_test_split\n",
@@ -344,13 +306,13 @@
},
{
"cell_type": "code",
- "execution_count": 44,
+ "execution_count": 108,
"outputs": [
{
"data": {
- "text/plain": "No 333641\nYes 20042\nName: HadHeartAttack, dtype: int64"
+ "text/plain": "No 333634\nYes 20016\nName: HadHeartAttack, dtype: int64"
},
- "execution_count": 44,
+ "execution_count": 108,
"metadata": {},
"output_type": "execute_result"
}
@@ -373,7 +335,7 @@
},
{
"cell_type": "code",
- "execution_count": 45,
+ "execution_count": 109,
"outputs": [],
"source": [
"def oversample(dataset):\n",
@@ -391,7 +353,7 @@
},
{
"cell_type": "code",
- "execution_count": 46,
+ "execution_count": 110,
"outputs": [],
"source": [
"train = oversample(train)"
@@ -402,20 +364,20 @@
},
{
"cell_type": "code",
- "execution_count": 47,
+ "execution_count": 111,
"outputs": [
{
"data": {
"text/plain": ""
},
- "execution_count": 47,
+ "execution_count": 111,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": "",
- "image/png": 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\n"
+ "image/png": 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8l1NoF8Gi8QFdN/DRt0dx/MdK2VGIyEu+2XYS2w4UcAqtBSwaL9N0HSUVdVj6r8OyoxCRl72+fBcaHBqn0M7DovEyVVGa//IRUXArq2rA+2sOyY7hd1g0XqRpOtZtz8POI0WyoxCRj3y+MRfFFfU8iv0sLBov0Q0D9XYNb3+yT3YUIvIhp6Zj4T8PQFG4MKAJi8ZLFCHw1if7uM0MUQhav/MUck9X8pC0RiwaL9B1A6fOVGFt1knZUYhIAsMAFny6D6rCSyzAovEKRRFY8sUhnsRHFMJ2HinCnqPcMQBg0Xhc02hm494fZUchIskWrN4PVeVllj8BD+Nohoia5JyqwPqdp0J+VMOi8SBN15FXyNEMEf2/RZ/zFF0WjQepioIlaw5yNENEzQpLa/H5xtyQXoHGovEQTddxsqAKm/byQDMiOteyrw/D6WTRUBupioL3OZohohZUVNux4pvskN0tgEXjAa7RTCU27eNohoha9sn6HFTXOWTHkIJF4wGuZzNcaUZEF1dv17D6+5yQHNWwaNpI03WcKKjEZo5miOjf+GJTLouGLp2qKHxvhohapaLajnXb8+AMsfdqWDRtoOsGThRUYst+jmaIqHU+/f4YTCG2W0BofbceJgSw6rscjmaIqNVyT1di79HikHqvhkXTBvV2Dd/vypcdg4gCzMffHQ2pnZ1D5zv1MKemY21WHhrsPKKZiC5N1sFCFJbWwgiR6RAWjZtMqoI1m3JlxyCiAGQYwBcbj4fMtLtbReNw/PRLR1lZWW6FCRS6buDIyTLknq6UHYWIAtQ32/JgIDSaxq2imTFjRotlU11djd///vf45S9/2eZg/kxRBD7feFx2DCIKYOXVDdi8tyAkjhBwq2h27NiBhx9+GHa7vflj33zzDcaPH4+PPvoI06ZN81Q+v1TX4MSGXTwKgIjaZs3m3JA4GM2t73DhwoXYv38/HnroIeTl5eGxxx7DI488guTkZKxcuRK//e1vPZ3Tbzg1Het3nkKDg4sAiKhtdmcX4UxZ8C8KEIab32FOTg6mTZuGkpISREdHY+bMmbjzzjshhPB0Rr/z7F82YP+xEtkxiCgI/HxMD0wZ1weKErzXTrfHbN26dcMHH3yAlJQUdO/eHTfffHNIlExxeR0OHGfJEJFnrNueF9QlAwCm1n7hmDFjWiyS6upq5OfnY8yYMYiIiAAACCHw9ddfey6ln9A0HV9vOxkySxKJyPtKKupxLL8Cl6XYgvZmvdVFk5mZGbQ/hNZSVQXrsvJkxyCiILNp74/okhwNNUivsW4/ozmf0+mEydTq3go4um7gWH4FZs77TnYUIgoyack2vP70aNkxvMbtZzRvvvkm7r///ubfb9++HSNHjsSSJUs8EswfrdvO0QwReV7u6UqUVNTJjuE1bhXNggULMG/ePKSlpTV/rHPnzrjhhhvwyiuvYMWKFZ7K5zcURWD7oTOyYxBRkNq453TQnlPjVtEsXboUTzzxBP7jP/6j+WPJycl47rnnMGPGDLz33nueyuc3SirqkF9ULTsGEQWpLfsLgvacGre+q8LCQgwYMKDFz11++eU4depUm0L5G6emI+tgoewYRBTE9uUUo67BKTuGV7hVNKmpqdi0aVOLn9u2bRuSkpLaFMrfmFQFOw8XyY5BREFM0w1sOxCce5+5tUzsjjvuwGuvvQaHw4HrrrsO7dq1Q2lpKdatW4d3330XTz31lKdzSmUYBnZns2iIyLs27yvAqIyOsmN4nFtFM23aNBQWFmLx4sXnPI9RVRVTp07F9OnTPZVPOsNwLWuurvvpoxGIiNpqx6FCaLoedKdvtuk9mqqqKuzcuRMVFRWw2WxIT09HXFycJ/NJp2k6PlybjSVrDsmOQkQh4I8PDUf/rglBtS1Nm96wjI6OxqhRoy74+LFjx9C1a9e2/NF+Q1UV7DzCaTMi8o1Ne0+jf7cE2TE8yq2iqaiowJ///Gds3boVdru9eYtrwzBQW1uLiooKHDx40KNBZWmwO3H4RKnsGEQUIrbsL8ADt6bLjuFRbk0EzpkzBx9++CG6dOkCVVURHR2NAQMGwOFwoLKyErNnz/Z0Tik0Xcfuo8VwatxFk4h8o6isDoWltbJjeJRbRfP999/j0Ucfxd/+9jfceeedSEpKwrx587BmzRr06tULR48e9XROKYQQ2MHdAIjIxw6fKIWmB88yZ7eKprKyEhkZGQBc59Ls27cPABAZGYl7770X3377rccCyqQIgZ2HWTRE5FtHT5VDIHgWA7hVNHFxcaiqqgIApKWloaSkBOXl5QCADh06oLAwON6iL6mow4/FNbJjEFGIOZpXEVSrztwqmiuvvBLz589Hfn4+OnfujJiYGHz88ccAgHXr1gXFEmenpmMHRzNEJEFOfrnsCB7lVtE8/vjjKCkpwTPPPAMhBB544AHMnTsXQ4cOxXvvvYfbbrvN0zl9ThECx3+slB2DiEJQbb0ThaXBM5vi1vLm1NRUfP7558jNzQUATJ8+HQkJCdixYwfS09Nx6623ejKjFIoicLKgSnYMIgpRh0+UISEmHGoQ7Ojs1newatUq1NXVoXfv3s0fmzBhAp5//nmMHDkSb731lscCynSigCMaIpIjO68cCJKjnd0qmlmzZiEvr+XTJg8ePIj//d//bVMof1BT50B5VYPsGEQUoo6eKocaJAsCWj11dv/99yMnJweAaweARx55BBaL5YKvKykpQefOnT2XUJKTHM0QkUTH8itkR/CYVhfNgw8+2HxE88cff4y+ffsiPj7+nK9RFAU2mw2TJk3ybEofc2o6jp9m0RCRPLX1ThSU1CCpXaTsKG3W6qIZNGgQBg0a1Pz7hx9+GJ06dfJKKNkUReAEFwIQkWSHT5ShfWzgLwhwK31+fj7sdnuLnzt06BAmTJjQplCyKUJw6oyIpMvOK4cIggUBrR7RZGVlNe/SvG3bNmzbtg2lpRfuarxu3bqLLhQIJFzaTESy5ZwqD4odAlpdNCtWrMAnn3zS3K4vvvjiBV/TVEQ33XSTh+LJUVVrR2VNyyM2IiJfCZZnxa0umueeew633XYbDMPA1KlT8fvf/x7du3c/52uaFgP06NHD40F9xTAMnAiSf7lEFNhq6hywOzRYzKrsKG3S6qKJjo5GZmYmAGDRokXo168fIiNbXg2xYcMGjBw50jMJfUzTjKC5iyCiwFde3YDEuAjZMdrErS1omgrnbKWlpVi5ciWWL1+OU6dOBewJm6rKrWeIyH+UlNeFZtGcbevWrVi6dCm++uorOBwOdO7cGY888ognskkhuOKMiPxIcUU9NF2HqgTuEme3iqayshIfffQRli9fjuPHjwMAbrjhBkyZMuWcd20CVUlFvewIREQAgNKKeug6EMiv0lxS0ezcuRNLly7Fl19+CbvdjmHDhuGXv/wlXnjhBUyePDkoSgYAqmu54oyI/ENpVT0CfYVzq4tm4sSJyM7ORlpaGh544AHccsstSE5ORlVVFV544QUvRvQtXTdQ2+CUHYOICIBrRBPoOwO0umiOHDmCXr16Yfr06Rg1atQF+5wFi7oGJxpfByIikq60KvCn8ltdkwsWLED37t3x/PPPY9SoUXjwwQfx9ddfw+FweDOfz9XUBdf3Q0SBrTQInhm3ekQzfPhwDB8+HFVVVfj000/x0UcfYcaMGYiJiYEQAidOnMCQIUO8mdUnqvh8hoj8SFll4BeNMAz3J4oOHz6MlStXYvXq1SgvL0dSUhJuvPFG3HjjjejXr58nc/rMjsNn8Pybm2THICJqtvKVmwJ6d4A2FU0Tp9OJtWvXYuXKldiwYQN0XQ/IFzY1XceGXT/iv97fLjsKEVGzBc9dj/YB/NJmm1/YBACTyYSxY8di7NixKCoqwrJlyzzxx/qcoQPVfEZDRH6mpKI+oIvGrTVzffr0wZ49e1r83IkTJ/DOO++0KZRMfEZDRP6muLwOuh64y2FbPaJZsGABamtrAbh2OF6xYgXWr19/wdft3LkTFovFcwl9SChAdS1HNETkX2obnNANAwoC883NVhdNQ0MD3njjDQCu/cBWrFhxwdcoioLo6Gg89NBDnkvoQ6qioLqOIxoi8i+BPJoBLqFoHnrooeYC6d27N5YvX4709HSvBZOFIxoi8jeabgT0i+RuPaMZPnw4ampqPJ3FL/AZDRH5G6emy47QJm4Vzc6dO5uPdA42ddznjIj8TKBPnblVNFdddRU+/fTToNt+BkDQFigRBS4twIvGrfdorFYrPv30U3zxxRfo1q0bIiLOXd8thMDChQs9EtDXFBYNNTIpQHiYGRFhZkSGmREeZkJEmAnhVhPCLCrCLWaEWVWEWUywWlVYzU2/FJjNKsymwN5xl/xHh/iIAF1v5uJW0RQUFCAjI6P59+dvLuCBzQakUQP94IcgYjIpiAozISLcjAirCRFNF3tr08XedcF3XeRd/2xuvNBbTCosZgVmk+uCb1YVmEwKTKoCVRUwCde/a0UBFOG6wRBCQCiu/4UQEOLSi8LQNRiaE4bmADQNgftfAvkTxawCQoebk1DSuVU0ixcv9nQOv6GwaJqFWVx38JHhJtcdfeMFvulX0918mEWFxWJCmFmFxazCYmm80JtcF/qmC7zZJFwXekXApDRe6IXrZ+66tovmXxCKW9OYrou860JvOB0wNDsMpx2GwwG9tgGGww7D2QDD6YTmtMOpOVyfdzZ+fdM/a67/1c/+XEtfe97HYAT2Q1vyT3HXTEbssJtlx3CbR7agOVttbS2ysrIwatQoT//RPuEvIxpFASIsjXfzYWZEhpkQHmZCuNWMcIuKMKsJYVYTwi0qrBYTrBYFFrPJdTdvVmExqTCbXXfy5sYLvcmkwKQoUFXA1HSRb7zQu+7o0XwnL9w4n9wwDBiaE9DOujBr9TCcdugOO4x6OwxHQ/OF2dl8gbZDb764O8+6gJ99Ebefd3E/uxQc/3+h5xiCgpBQVATy3223iiY/Px8vvPACtm7dCru95eXAgbipJgAoqqtoTKpAZHjjBd5qRkSYCRFWM8LCVIRbXXPz4U1TN2YVVovrbt7adFdvcs3Tm86+0KtNd/Su+X+l+WJ/3rQNhHsXel1vvLifdUfvdF3oDbsdRk2D64LvtEPXHNAuuFiff1E//67d2Xyn31wOZ9/N61yxR+QVSuDu3Ay4WTQvv/wyduzYgdtvvx07duxAeHg4Bg4ciB9++AFHjhzB66+/7umcPmFoDrx0/zAPTts0XYjtMOrsrmkYRwMMp+Pi0zZn3Z03fU7XWlEATjunbYiClDs3nv7ErWMChg4dikcffRT33HMPlixZgrVr12LBggXQNA333nsvUlNTMWfOHG/k9bqq3d+g/sejLUzXOC+849fOvvBz2oaIvCPhhvsRPfBaCNXjTzt8wq3UNTU16NWrFwCga9euzXugqaqKyZMnY+7cuZ5L6GN1uftQve/CzUKJiKQJ8BGNW+kTExNRXFwMAOjSpQsqKipQVFQEAIiNjUVJSYnnEvqQYRgQljDZMYiIziFMFiCA3/Fzq2iuvvpqzJs3Dzt37kRqaiqSkpKwYMECVFdXY+XKlejQoYOnc/qGoUOxhMtOQUR0DlNUXOPKs8DkVtE89thjsNls+J//+R8AwMyZM7Fw4UIMGTIEq1evxvTp0z0a0mcMAwpHNETkZ1RbO9kR2sStZzRxcXFYsWIFzpw5AwCYOHEiUlJSsGvXLqSnpyMzM9OjIX3HgDCzaIjIv6iRsbIjtEmbljAkJiaiqqoKZ86cQXp6OjIyMqCqgTu8AwQUK6fOiMiPqCaoYZGyU7SJ20sZtmzZgttvvx2ZmZmYMGECsrOz8fTTT+OVV17xZD7fUpSAv3MgouBiioyTHaHN3CqaTZs24b777kNYWBiefvrp5k00e/XqhUWLFuHdd9/1aEhfEUKBOT5ZdgwiomZqVKzsCG3mVtHMmzcP1157LRYvXoypU6c2F82DDz6IX/3qV1ixYoVHQ/qSKaa97AhERM3U6BAd0Rw8eBC33XYbgAsPChsxYgTy8/PbnkwSxWyFEh4tOwYREQDX0uZAPnoFcLNooqOjm1/QPN/p06cRHR3YF2pzbKLsCEREAAA1Kg7QNdkx2sStorn22mvx5z//GXv37m3+mBACBQUFmD9/Pq655hpP5ZPCFBugL5wSUdBRo+JlR2gzt5Y3P/XUU9i9ezfuuOMOJCQkAACefPJJFBQUIDk5GU8++aRHQ/qSoWssGiLyG6bouNA8JiAmJgYrVqzAqlWrsHnzZpSXlyM6OhpTpkzBpEmTEB4ewO+iGAanzojIb5hsCW4dW+JP3DomIJgZhoH63L04/cGLsqMQEaHLzPegRgT2c+9Wj2i2bdt2SX/wkCFDLjmMPxBCwBSfJDsGERGgqFDCo2SnaLNWF82UKVMuOnxrGhQJIVxb7QsRsEc5A4Apqh0gFJ5YSURSWRI6Bvy0GXAJRbNo0aJzfq9pGqZPn44XX3wRl112mceDySRUFWp0PLTKYtlRiCiEWZK6Nt+8B7JWF835OzJrmmtdd//+/dGvXz/PpvID5thEFg0RSWVN7uZ6hyZAj3BuEtjng3oRlzgTkWzWlO4QAV4yAIumRYbmhCWho+wYRBTKhAJrYprsFB7BommJoiKsUx/ZKYgohJkTUiFMZtkxPIJF0wIhhGtuNAiGrEQUmKxJXWVH8JhWX0nfeOONc37ftBJi2bJlSEw89016IQQeeeQRzySURKgmWJO6oSH/sOwoRBSCrEndYGjOoHhG0+qdAXr37t36PzTA36MBAEPXUbpuCSo2fyI7ChGFoJSpc2BN7RnwS5uBSxjRHDp0yJs5/FJYpz4sGiLyPaHA0iEtKEoG4DOaixKKwgUBRCSFOT4ZitkqO4bHtHpEs2rVqkv6g2+55ZZLjOJ/1PAomOOT4Sg9LTsKEYUQa3I32RE8qtVF8+yzz57z+6Yh3dmPeM4e5gVD0RiGAWvH3iwaIvIpS1LXoFkIAFxC0XzzzTfN/3zw4EH85je/wcMPP4xx48YhMTERZWVlWLt2LV5//XW8/PLLXgnrc7qGsE69Ub1nnewkRBRCwlJ6BPxhZ2dz6zyaSZMmYdy4cfj1r399wecWLlyIFStW4LPPPvNIQNkcpaeR97cZsmMQUYgQlnCkPbkQQg2eonFrMUBOTg769u3b4ue6du2KU6dOtSmUPzHHJwfFeRBEFBgiug4MqpIB3CyatLQ0rF69usXPLVu2DD179mxTKH8T1rH17xAREbVFRI8hMDSn7Bge5daTpkceeQSPP/44cnNzMXr0aMTFxaG4uBj/+te/cPToUbz11luezimNoTkR1rE3arOzZEchomAnFET0HBw0iwCauPWMBgDWrl2Lv/zlLzhw4AAMw4CiKMjIyMDMmTMxePBgT+eUxjAM2M+cQP7bT8mOQkRBztqxN1Kn/lF2DI9zu2iaNDQ0oKKiArGxsbBYLJ7K5XdO/uVhOMsLZccgoiAWP/oexAydEHQjmjbtDFBSUoLS0lI4nU4UFxfj1KlTyM7Oxj/+8Q9P5fMLhq4jss9w2TGIKMhF9h4WdCUDuPmM5tChQ3j66aeRk5PT4ueFELj77rvbFMyvCCCq30hUbPpYdhIiClKmuCSY45Nlx/AKt4rm1VdfRUVFBZ555hmsW7cOFosFo0ePxvr167F+/XosWrTI0zmlEkKBtUMaTHFJcJYVyI5DREEossdgGIYOIYJvC0q3vqPdu3fj8ccfx7Rp03DjjTeirq4OkydPxvz583Hddddh8eLFns4pnaHriOpzpewYRBSkInpmAm16Yu6/3Coau92OtLQ0AK53as4+QmDSpEnYtWuXJ7L5FwFE9rtKdgoiCkKKNQJhnXpDKME3mgHcLJqUlBTk5eUBcBVNdXV1824AFosFFRUVnkvoJ4RQYE3sAlNccM6hEpE84d0yIIJob7PzuVU0Y8eOxZ/+9Cd8+eWX6NChA7p27Yp58+bh8OHDWLBgATp16uTpnH7B0DVOnxGRx7l2A9Bkx/Aat4pmxowZGDRoED788EMAwKxZs/DVV1/hlltuwebNm/Hoo496NKTfEAJR/Tl9RkSeI0wWRPYYHHT7m52tTS9sOhwOmM1mAEBeXh727duHfv36oXPnzh4L6I/y/jaDZ9QQkUdEDbgGiROD9Oa8UauXN8+aNatVX7d+/XoIITBnzhy3Q/kzQ9cQ2Wc4yn9YKTsKEQUB2+BxMHQ9aBcCAJdQNFu2bLngY6dPn0ZCQkLzqKbJ2SdtBh2hIKrfVSwaImozS4c0hKV0lx3D61pdNGvXrj3n906nE/3798f8+fPRr18/jwfzV0IIWNp3grldKhwl+bLjEFEAsw36GQxNC+rnM0Ab9joL6lHLv2FoGmyDx8mOQUQBTFjCETXg6qAvGaCNm2qGKqGqsA28DkoYT94kIvdED7gawhS8O96fjUXjLkWFbdBY2SmIKEDZBt+IoN1z5jwsGncJgZjMm4Ag3NKbiLwrrFMfWBJSg3IDzZa0+bsM1Wc1QgiokTGI6jtCdhQiCjC2K24I6p0AztfqFzbHjBlzQank5+cjMTGxxeXNX3/9tedS+ilD1+EoycepN5+QHYWIAoQSYUOXx94OiUUATVo975OZmRmyo5eLEYoCS/tOCEsbgPrcvbLjEFEAiL78WiDErqVt2oKGXEud63L3oGDpS7KjEJHfE+j86Hyo0e1C6sY9NJ5EeZFQVUR0y4C5XarsKETk5yJ6XAGTLSGkSgZg0XiEoWmIGTpBdgwi8msCcddMhqGHziKAJiwaDxCqiuj00VAibLKjEJGfiuxzJayJXYL6gLOLYdF4ilBgG/Qz2SmIyB8pKuJH3wND12UnkYJF4yFCURAzZDyE2So7ChH5mej00TDHdQjqowB+Smh+116ihEUiZthE2TGIyI8IkwVxV98FwwjN0QzAovEooSiIHT4JanS87ChE5CdsV/wMamRsyGw305LQ/c69RCgq4q/5hewYROQHhCUcsSNvlx1DOhaNhwlFRXT6NbAmd5MdhYgkix02EYolPOTemzkfi8YLDF1Du7H3yY5BRBIpETbEDLs5ZBcAnI0/AS8Qioqwjr0Q2ftK2VGISJK44ZMgeIwIABaN1xi6jnbXT4NQzf/+i4koqKi2BNgGjwvJlzNbwqLxEqEoUKPjYcu8SXYUIvKxuKvuCLkdmn8Ki8aLhFAQN/LnUCNjZUchIh+xJndD9OWjOZo5C4vGy4TJjLir75Ydg4h8QTWh/cTHAZ6+cg4WjZcJRUX0wGthSewiOwoReVnciJ/D3C6Zo5nzsGh8Qde53JkoyFk6pCF2xKSQ3gHgYvgT8QGhqgjv0g9R6aNlRyEib1BUtJ/4mOwUfotF4yOGYSDhhl/DFNtBdhQi8rDYK2+BpX1nTpldBIvGR4QQEIoJibc8AXBoTRQ0zAmdEDfqzpDfZuan8IrnQ0JVYU3pgdjht8qOQkSeIBQkTnwM4CKzn8Si8TEhBOJG3QVrSnfZUYiojWKGToAl6TIIlVNmP4VFI4WBxFufhDCHyQ5CRG4yx6cg/prJnDJrBRaNBEJRYbK1R7vrpsqOQkTuEAraT3wUAEumNVg0kghFgW3QWET0GCw7ChFdItvgcQhL7ckps1Zi0Uhk6DraT3iUe6ERBRBLUle0GzNFdoyAwqKRSCgKFEs42k+YITsKEbWCEmFD0h2zAB5mdkn405JMqCoiumUgetDPZEchop+imJD082egRsbwxcxLxKLxA4ZhIOH66TAndJIdhYguot3Y6bB27MmScQOLxg8IIQChIPmu30GJsMmOQ0TniR54HWKuuIEbZrqJPzU/IVQValQ8ku78DwiTRXYcImpkTe2FhHH3w+AZM25j0fgRoaqwJnVzHZzE9flE0qnR8Ui6/RkA4IuZbcCi8TNCURDZeyjiR/9CdhSikCZUM5JunwUlLIrPZdqIReOHhBCIHX4rogdeJzsKUchKuPFBWDqk8aVMD2DR+CnDMJAw7gGEX5YuOwpRyLENGY/o9Gsg+L6MR/Cn6Kea5oM7/PwZmNtz2TORr4SlDUC766bJjhFUWDR+TCgKhMmM5Lt/DzUqVnYcoqBnbt8JHW77jewYQYdF4+eEokKNiEHSnb+DMFtlxyEKWqa4ZKT84kUoljBOmXkYf5oBQKgqLIldkHjLTB4DTeQFJlt7pEyZzRVmXsKrVoAQioqIHoPR7vppsqMQBRU1KhbJU1507WHGFWZewaIJIEIIxAwZzweVRB6ihEcj+RezYbIlcCTjRSyaABQzdALajb1PdgyigKaERSH5Fy/AHJ/EkvEyYXADn4BVsX0NSta8DYD/CokuhRIeheR7ZsOS0JEl4wMc0QQw26CfIWHc/eC+aEStp0TYkDLlDywZH+KIJsAZhoGq3WtR/Pl8wNBlxyHya2pkDJLv+QOny3yMRRMEDMNAzaHNOPPJPEBzyo5D5JfUqFikTHkJpphEri7zMRZNkDB0HfUn9qFgxVwYjnrZcYj8iimmPZJ/8QJMtvYsGQlYNEHE0DXYC3Nx+h+zoddVy45D5BesHXsj6Y5ZUCzhLBlJWDRBxtA1OMoKcPr9F6BVlcqOQyRVVPpotB//EADwmYxELJogZGgatJpynP7HH+AozpMdh8j3hIL40b9A7JW3wDAMno4pGYsmSBm6BkPXUPTp66g5uFF2HCKfEZYwdLj1SYR3G8SC8RMsmiBmGDqEUFC+ZTVK1y4GdE12JCKvMsW0R9Jdz8Ecn8ypMj/CogkBhqGj4dQRFK58DVpNuew4RF7heuj/LBRrBEvGz7BoQoSha9DrqlHw4Vw0nDosOw6RR0UNuMb10F8IlowfYtGEEKNx6qzkq3dRmfWF5DREHsCH/gGBRROiqvatR/Hn82E4GmRHIXKLYo1A+5sfQ0T3wSwYP8eiCVGGrsNRko+CFa/AWVYgOw7RJQm/LB3tJz4GNcLGqbIAwKIJYYamwXDaceaTeajNzpIdh+jfEuYwxF87BTFX3ABD1yEUbkAfCFg0Ia55CfSmVShbvwyG0y47ElGLrB17I/HmxxtPw2TBBBIWDQFwTaU5K4tR9M+/oj53r+w4RM2Eakbc1XcjZthEwNA5VRaAWDTUzNA1CEVF1e51KPnmPW7MSdJZkroi8ZYnYI5L5igmgLFo6AKGrkFvqEXxmrdRc2CD7DgUihQVcSNuQ+zI2wEYHMUEOBYNtajp2U1tzk4Uf/53OCuLZEeiEGFO6ITEW56AJbELly0HCRYN/SRD02DoTpSue9/1kiePiyZvUVTEZN6E+GsmAxA8OyaIsGjo32r6K2IvOI6iz96A/cwJyYko2ET2Gob4a38JU2wiRzFBiEVDrWZoGiAEyjetQvmGFVwKTW1m7dgL7a6bjrDUHs2LUSj4sGjokhm6Dq2mHGXrl6FqzzoeP0CXzByfgvgxUxDZK5MFEwJYNOQWw9ABCGiVJShdvxTVe7/j8xv6t9TIGMRedQdsGWMBw+BzmBDBoqE2aVqd5igvRNl3S1G9fwMLhy4gzGGIGToBscNvhVBNHMGEGBYNeURz4ZSeRul3/0DNwU0sHAKEguiB1yL+6ruhhEfzpcsQxaIhj2ra6NBenI+y7z5AzaEtAPhXLOQIBZG9hyHu6rthaZfSfCNCoYlFQ17RXDhFJ1H67T9Qe2Sr7EjkA0qEDbaB18E25EaYouL4oJ8AsGjIy5ouNA2FuSjf+DFqD2+BoTlkxyIPs3S4DDFDbkRU/1GAUFxHKvN9GGrEoiGfaCocrb4G1XvWoXLX13AU5cmORW2hqIjsNRQxmTchrGMvGJoTQjXJTkV+iEVDPmdoGoSqov7Ho6ja8S9UH/gBhqNedixqJSXCBlvG9bANHsfpMWoVFg1JY+g6IAQMpx3V+9ajatfXaPjxqOxYdBGWpK6IGXwjovpfxekxuiQsGvILTdMu9qI8VO74EtX7vodez/NwZDPHpyCi11BE9R0Oa1JXTo+RW1g05FeMpndvdB3VBzehes861J3cD2hOucFCiCXpMkT2GobIPsNdS5MbR54cvZC7WDTkt5runnWnHXW5e1F3dDtqc3bBWV4oO1pwEQrCOvZGZO+hiOx9JUy2djB0DRAKy4U8gkVDAcF14ROu3QfKClGbvQ21OTtRf/IAd5F2h2pCeFq6q1x6DYMaHsVpMfIaFg0FpKaLouF0oO7EPtQe3Y7anJ1wlhXIjuafhAJL+06wpvZEeJf+iOgxGIoljOVCPsGioYBn6K7nOkJR4Kg4g9ojWajPOwj7mRNwlJ4OyT3X1Oh2CEvtAWtKT1g79oQ1uRsUk8V1iJ2usVzIp1g0FHTOvks3nA7Yi0+hoSAH9sJc2M+cgP3MCej1NZJTeo6whMGa3L25WMI69oIaGQPA9bOAovJZC0nFoqGQYGhO18Ptxt2DndVlaDh9DPYzuc0F5NejH0WFKSoeqq0dTLYEmGISYI5PQVin3jDHp0AI4XqOBcEdksnvsGgoZBmGDuj6OaMfR2URtOoKaDVl0GoroddWQqupgFZb2firwvWx2ioPlpKAGhkDk60dVFuCq0iafsUmwhzT/oIt9g1dazw4jFNg5P9YNEQtMHT9/4tEUS7Y4t4wDOgNtdDrqqBVl0Orrfzp4lHNUMwWCLMVwmSBMFmgmCwQJjOUsMhzCqP5//dZIzCiQMaiIfKAlv8z+v+P8SwWCmUsGiIi8ireZhERkVexaIiIyKtYNERE5FUsGiIi8ioWDREReRWLhoiIvIpFQ+QjY8aMwZgxY1BdfeHJoc8++yymTJkiIRWR97FoiHwoPz8fr776quwYRD7FoiHyoU6dOmHZsmXYuHGj7ChEPsOiIfKhiRMn4sorr8Tvfve7FqfQAKC8vBwvvvgirr76aqSnp+Ouu+7Cli1bfJyUyHNYNEQ+JITAH//4R1RUVGDu3LkXfF7TNNx7773IysrCa6+9ho8++gg9e/bEfffdhz179khITNR2LBoiH0tNTcUzzzyD5cuXY8OGDed8bsOGDdi/fz/+9Kc/ITMzE927d8eLL76IHj164J133pGUmKhtWDREEtx5550YMWIEnnvuuXOm0I4cOYLo6Gj07Nmz+WNCCAwePBhHjhyREZWozVg0RJK89NJLqKqqwssvv9z8sYttpm4YBkwmHnJGgYlFQyRJSkoKnn32WXz44YfIysoCAPTq1QtVVVXnjF4Mw8D27dvRvXt3WVGJ2oRFQyTR7bffjpEjRyIvLw8AMHLkSPTp0wdPPfUUtm7dipycHMyePRtHjhzB1KlTJaclcg+Lhkiyl156CdHR0QAAVVWxYMEC9O3bFzNmzMBtt92G7OxsvPfeexg4cKDcoERu4gmbRETkVRzREBGRV7FoiIjIq1g0RETkVSwaIiLyKhYNERF5FYuGiIi8ikVDRERexaIhIiKvYtEQEZFXsWiIiMirWDRERORVLBoiIvIqFg0REXkVi4aIiLyKRUNERF7FoiEiIq9i0RARkVexaIiIyKtYNERE5FUsGiIi8ioWDREReRWLhoiIvIpFQ0REXsWiISIir2LREBGRV7FoiIjIq1g0RETkVf8HcjnpypR0cEwAAAAASUVORK5CYII=\n"
},
"metadata": {},
"output_type": "display_data"
@@ -430,20 +392,20 @@
},
{
"cell_type": "code",
- "execution_count": 48,
+ "execution_count": 112,
"outputs": [
{
"data": {
"text/plain": ""
},
- "execution_count": 48,
+ "execution_count": 112,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": "",
- "image/png": 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\n"
+ "image/png": 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\n"
},
"metadata": {},
"output_type": "display_data"
@@ -458,20 +420,20 @@
},
{
"cell_type": "code",
- "execution_count": 49,
+ "execution_count": 113,
"outputs": [
{
"data": {
"text/plain": ""
},
- "execution_count": 49,
+ "execution_count": 113,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"text/plain": "",
- "image/png": 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\n"
+ "image/png": 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\n"
},
"metadata": {},
"output_type": "display_data"
@@ -495,13 +457,13 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": 114,
"outputs": [
{
"data": {
"text/plain": ""
},
- "execution_count": 50,
+ "execution_count": 114,
"metadata": {},
"output_type": "execute_result"
},
@@ -523,13 +485,13 @@
},
{
"cell_type": "code",
- "execution_count": 51,
+ "execution_count": 115,
"outputs": [
{
"data": {
"text/plain": ""
},
- "execution_count": 51,
+ "execution_count": 115,
"metadata": {},
"output_type": "execute_result"
},
@@ -560,13 +522,13 @@
},
{
"cell_type": "code",
- "execution_count": 52,
+ "execution_count": 116,
"outputs": [
{
"data": {
"text/plain": ""
},
- "execution_count": 52,
+ "execution_count": 116,
"metadata": {},
"output_type": "execute_result"
},
@@ -608,13 +570,13 @@
},
{
"cell_type": "code",
- "execution_count": 53,
+ "execution_count": 117,
"outputs": [
{
"data": {
"text/plain": "array(['Female', 'Male'], dtype=object)"
},
- "execution_count": 53,
+ "execution_count": 117,
"metadata": {},
"output_type": "execute_result"
}
@@ -628,13 +590,13 @@
},
{
"cell_type": "code",
- "execution_count": 54,
+ "execution_count": 118,
"outputs": [
{
"data": {
"text/plain": "array(['Very good', 'Excellent', 'Fair', 'Poor', 'Good', nan],\n dtype=object)"
},
- "execution_count": 54,
+ "execution_count": 118,
"metadata": {},
"output_type": "execute_result"
}
@@ -648,7 +610,7 @@
},
{
"cell_type": "code",
- "execution_count": 55,
+ "execution_count": 119,
"outputs": [],
"source": [
"health_map = {\n",
@@ -665,7 +627,7 @@
},
{
"cell_type": "code",
- "execution_count": 56,
+ "execution_count": 120,
"outputs": [
{
"name": "stdout",
@@ -857,7 +819,7 @@
},
{
"cell_type": "code",
- "execution_count": 57,
+ "execution_count": 121,
"outputs": [],
"source": [
"from collections import defaultdict\n",
@@ -920,14 +882,14 @@
},
{
"cell_type": "code",
- "execution_count": 58,
+ "execution_count": 122,
"outputs": [
{
"data": {
- "text/plain": " State Sex GeneralHealth PhysicalHealthDays \\\n339824 South Dakota Female Good 3.0 \n127927 Kansas Female Good 30.0 \n362523 Utah Male Excellent 0.0 \n183687 Michigan Male Good 0.0 \n191905 Michigan Female Very good 0.0 \n\n MentalHealthDays LastCheckupTime \\\n339824 21.0 Within past year (anytime less than 12 months ... \n127927 0.0 Within past year (anytime less than 12 months ... \n362523 0.0 Within past year (anytime less than 12 months ... \n183687 7.0 Within past year (anytime less than 12 months ... \n191905 0.0 Within past year (anytime less than 12 months ... \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack \\\n339824 Yes 8.0 6 or more, but not all No \n127927 Yes 10.0 1 to 5 No \n362523 Yes 7.0 1 to 5 No \n183687 Yes 8.0 None of them No \n191905 Yes 7.0 None of them No \n\n ... HeightInMeters WeightInKilograms BMI AlcoholDrinkers \\\n339824 ... 1.60 52.16 20.37 No \n127927 ... 1.68 97.52 34.70 No \n362523 ... 1.83 113.85 34.04 No \n183687 ... 1.78 83.91 26.54 Yes \n191905 ... 1.57 68.04 27.44 Yes \n\n HIVTesting FluVaxLast12 PneumoVaxEver \\\n339824 Yes Yes Yes \n127927 No Yes Yes \n362523 No No No \n183687 No Yes Yes \n191905 Yes No Yes \n\n TetanusLast10Tdap HighRiskLastYear \\\n339824 Yes, received Tdap No \n127927 NaN No \n362523 Yes, received Tdap No \n183687 Yes, received Tdap No \n191905 Yes, received tetanus shot but not sure what type No \n\n CovidPos \n339824 No \n127927 No \n362523 Yes \n183687 No \n191905 No \n\n[5 rows x 40 columns]",
- "text/html": "\n\n
\n \n \n \n State \n Sex \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 339824 \n South Dakota \n Female \n Good \n 3.0 \n 21.0 \n Within past year (anytime less than 12 months ... \n Yes \n 8.0 \n 6 or more, but not all \n No \n ... \n 1.60 \n 52.16 \n 20.37 \n No \n Yes \n Yes \n Yes \n Yes, received Tdap \n No \n No \n \n \n 127927 \n Kansas \n Female \n Good \n 30.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n Yes \n 10.0 \n 1 to 5 \n No \n ... \n 1.68 \n 97.52 \n 34.70 \n No \n No \n Yes \n Yes \n NaN \n No \n No \n \n \n 362523 \n Utah \n Male \n Excellent \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n Yes \n 7.0 \n 1 to 5 \n No \n ... \n 1.83 \n 113.85 \n 34.04 \n No \n No \n No \n No \n Yes, received Tdap \n No \n Yes \n \n \n 183687 \n Michigan \n Male \n Good \n 0.0 \n 7.0 \n Within past year (anytime less than 12 months ... \n Yes \n 8.0 \n None of them \n No \n ... \n 1.78 \n 83.91 \n 26.54 \n Yes \n No \n Yes \n Yes \n Yes, received Tdap \n No \n No \n \n \n 191905 \n Michigan \n Female \n Very good \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n Yes \n 7.0 \n None of them \n No \n ... \n 1.57 \n 68.04 \n 27.44 \n Yes \n Yes \n No \n Yes \n Yes, received tetanus shot but not sure what type \n No \n No \n \n \n
\n
5 rows × 40 columns
\n
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+ "text/plain": " State Sex GeneralHealth PhysicalHealthDays MentalHealthDays \\\n166151 Maryland Male Good 0.0 0.0 \n359753 Texas Male Good 0.0 0.0 \n286723 Ohio Male Fair 2.0 0.0 \n305100 Oklahoma Male Very good 0.0 0.0 \n199077 Minnesota Female Excellent 0.0 0.0 \n\n LastCheckupTime PhysicalActivities \\\n166151 Within past 2 years (1 year but less than 2 ye... Yes \n359753 NaN No \n286723 Within past year (anytime less than 12 months ... No \n305100 Within past year (anytime less than 12 months ... Yes \n199077 Within past year (anytime less than 12 months ... No \n\n SleepHours RemovedTeeth HadHeartAttack ... HeightInMeters \\\n166151 7.0 None of them No ... 1.78 \n359753 8.0 None of them No ... 1.60 \n286723 8.0 All No ... 1.75 \n305100 7.0 None of them No ... 1.80 \n199077 8.0 1 to 5 No ... 1.52 \n\n WeightInKilograms BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\n166151 90.72 28.70 Yes No No \n359753 77.11 30.12 No No No \n286723 80.29 26.14 NaN NaN NaN \n305100 97.52 29.99 NaN NaN NaN \n199077 67.13 28.90 Yes Yes No \n\n PneumoVaxEver TetanusLast10Tdap \\\n166151 Yes No, did not receive any tetanus shot in the pa... \n359753 No No, did not receive any tetanus shot in the pa... \n286723 NaN NaN \n305100 NaN NaN \n199077 No NaN \n\n HighRiskLastYear CovidPos \n166151 No No \n359753 No No \n286723 NaN NaN \n305100 NaN NaN \n199077 No Yes \n\n[5 rows x 40 columns]",
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\n \n \n \n State \n Sex \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 166151 \n Maryland \n Male \n Good \n 0.0 \n 0.0 \n Within past 2 years (1 year but less than 2 ye... \n Yes \n 7.0 \n None of them \n No \n ... \n 1.78 \n 90.72 \n 28.70 \n Yes \n No \n No \n Yes \n No, did not receive any tetanus shot in the pa... \n No \n No \n \n \n 359753 \n Texas \n Male \n Good \n 0.0 \n 0.0 \n NaN \n No \n 8.0 \n None of them \n No \n ... \n 1.60 \n 77.11 \n 30.12 \n No \n No \n No \n No \n No, did not receive any tetanus shot in the pa... \n No \n No \n \n \n 286723 \n Ohio \n Male \n Fair \n 2.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n No \n 8.0 \n All \n No \n ... \n 1.75 \n 80.29 \n 26.14 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 305100 \n Oklahoma \n Male \n Very good \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n Yes \n 7.0 \n None of them \n No \n ... \n 1.80 \n 97.52 \n 29.99 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 199077 \n Minnesota \n Female \n Excellent \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n No \n 8.0 \n 1 to 5 \n No \n ... \n 1.52 \n 67.13 \n 28.90 \n Yes \n Yes \n No \n No \n NaN \n No \n Yes \n \n \n
\n
5 rows × 40 columns
\n
"
},
- "execution_count": 58,
+ "execution_count": 122,
"metadata": {},
"output_type": "execute_result"
}
@@ -950,14 +912,14 @@
},
{
"cell_type": "code",
- "execution_count": 59,
+ "execution_count": 123,
"outputs": [
{
"data": {
- "text/plain": " State Male GeneralHealth PhysicalHealthDays \\\n339824 South Dakota 0.0 3.0 3.0 \n127927 Kansas 0.0 3.0 30.0 \n362523 Utah 1.0 5.0 0.0 \n183687 Michigan 1.0 3.0 0.0 \n191905 Michigan 0.0 4.0 0.0 \n\n MentalHealthDays LastCheckupTime \\\n339824 21.0 Within past year (anytime less than 12 months ... \n127927 0.0 Within past year (anytime less than 12 months ... \n362523 0.0 Within past year (anytime less than 12 months ... \n183687 7.0 Within past year (anytime less than 12 months ... \n191905 0.0 Within past year (anytime less than 12 months ... \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack ... \\\n339824 1.0 8.0 2.0 0.0 ... \n127927 1.0 10.0 1.0 0.0 ... \n362523 1.0 7.0 1.0 0.0 ... \n183687 1.0 8.0 0.0 0.0 ... \n191905 1.0 7.0 0.0 0.0 ... \n\n HeightInMeters WeightInKilograms BMI AlcoholDrinkers HIVTesting \\\n339824 1.60 52.16 20.37 0.0 1.0 \n127927 1.68 97.52 34.70 0.0 0.0 \n362523 1.83 113.85 34.04 0.0 0.0 \n183687 1.78 83.91 26.54 1.0 0.0 \n191905 1.57 68.04 27.44 1.0 1.0 \n\n FluVaxLast12 PneumoVaxEver TetanusLast10Tdap HighRiskLastYear \\\n339824 1.0 1.0 1.0 0.0 \n127927 1.0 1.0 NaN 0.0 \n362523 0.0 0.0 1.0 0.0 \n183687 1.0 1.0 1.0 0.0 \n191905 0.0 1.0 1.0 0.0 \n\n CovidPos \n339824 0.0 \n127927 0.0 \n362523 1.0 \n183687 0.0 \n191905 0.0 \n\n[5 rows x 40 columns]",
- "text/html": "\n\n
\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 339824 \n South Dakota \n 0.0 \n 3.0 \n 3.0 \n 21.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 8.0 \n 2.0 \n 0.0 \n ... \n 1.60 \n 52.16 \n 20.37 \n 0.0 \n 1.0 \n 1.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 127927 \n Kansas \n 0.0 \n 3.0 \n 30.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 10.0 \n 1.0 \n 0.0 \n ... \n 1.68 \n 97.52 \n 34.70 \n 0.0 \n 0.0 \n 1.0 \n 1.0 \n NaN \n 0.0 \n 0.0 \n \n \n 362523 \n Utah \n 1.0 \n 5.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 7.0 \n 1.0 \n 0.0 \n ... \n 1.83 \n 113.85 \n 34.04 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 1.0 \n 0.0 \n 1.0 \n \n \n 183687 \n Michigan \n 1.0 \n 3.0 \n 0.0 \n 7.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 8.0 \n 0.0 \n 0.0 \n ... \n 1.78 \n 83.91 \n 26.54 \n 1.0 \n 0.0 \n 1.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 191905 \n Michigan \n 0.0 \n 4.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 7.0 \n 0.0 \n 0.0 \n ... \n 1.57 \n 68.04 \n 27.44 \n 1.0 \n 1.0 \n 0.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n
\n
5 rows × 40 columns
\n
"
+ "text/plain": " State Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\n166151 Maryland 1.0 3.0 0.0 0.0 \n359753 Texas 1.0 3.0 0.0 0.0 \n286723 Ohio 1.0 2.0 2.0 0.0 \n305100 Oklahoma 1.0 4.0 0.0 0.0 \n199077 Minnesota 0.0 5.0 0.0 0.0 \n\n LastCheckupTime PhysicalActivities \\\n166151 Within past 2 years (1 year but less than 2 ye... 1.0 \n359753 Unknown 0.0 \n286723 Within past year (anytime less than 12 months ... 0.0 \n305100 Within past year (anytime less than 12 months ... 1.0 \n199077 Within past year (anytime less than 12 months ... 0.0 \n\n SleepHours RemovedTeeth HadHeartAttack ... HeightInMeters \\\n166151 7.0 0.0 0.0 ... 1.78 \n359753 8.0 0.0 0.0 ... 1.60 \n286723 8.0 3.0 0.0 ... 1.75 \n305100 7.0 0.0 0.0 ... 1.80 \n199077 8.0 1.0 0.0 ... 1.52 \n\n WeightInKilograms BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\n166151 90.72 28.70 1.0 0.0 0.0 \n359753 77.11 30.12 0.0 0.0 0.0 \n286723 80.29 26.14 NaN NaN NaN \n305100 97.52 29.99 NaN NaN NaN \n199077 67.13 28.90 1.0 1.0 0.0 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \n166151 1.0 1.0 0.0 0.0 \n359753 0.0 1.0 0.0 0.0 \n286723 NaN NaN NaN NaN \n305100 NaN NaN NaN NaN \n199077 0.0 NaN 0.0 1.0 \n\n[5 rows x 40 columns]",
+ "text/html": "\n\n
\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 166151 \n Maryland \n 1.0 \n 3.0 \n 0.0 \n 0.0 \n Within past 2 years (1 year but less than 2 ye... \n 1.0 \n 7.0 \n 0.0 \n 0.0 \n ... \n 1.78 \n 90.72 \n 28.70 \n 1.0 \n 0.0 \n 0.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 359753 \n Texas \n 1.0 \n 3.0 \n 0.0 \n 0.0 \n Unknown \n 0.0 \n 8.0 \n 0.0 \n 0.0 \n ... \n 1.60 \n 77.11 \n 30.12 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 286723 \n Ohio \n 1.0 \n 2.0 \n 2.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 8.0 \n 3.0 \n 0.0 \n ... \n 1.75 \n 80.29 \n 26.14 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 305100 \n Oklahoma \n 1.0 \n 4.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 7.0 \n 0.0 \n 0.0 \n ... \n 1.80 \n 97.52 \n 29.99 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 199077 \n Minnesota \n 0.0 \n 5.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 8.0 \n 1.0 \n 0.0 \n ... \n 1.52 \n 67.13 \n 28.90 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n NaN \n 0.0 \n 1.0 \n \n \n
\n
5 rows × 40 columns
\n
"
},
- "execution_count": 59,
+ "execution_count": 123,
"metadata": {},
"output_type": "execute_result"
}
@@ -972,57 +934,57 @@
},
{
"cell_type": "code",
- "execution_count": 60,
+ "execution_count": 124,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
- "Int64Index: 44513 entries, 339824 to 52161\n",
+ "Int64Index: 44513 entries, 166151 to 306609\n",
"Data columns (total 40 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 State 44513 non-null category\n",
" 1 Male 44513 non-null float64 \n",
- " 2 GeneralHealth 44393 non-null float64 \n",
- " 3 PhysicalHealthDays 43469 non-null float64 \n",
- " 4 MentalHealthDays 43622 non-null float64 \n",
+ " 2 GeneralHealth 44400 non-null float64 \n",
+ " 3 PhysicalHealthDays 43445 non-null float64 \n",
+ " 4 MentalHealthDays 43614 non-null float64 \n",
" 5 LastCheckupTime 44513 non-null category\n",
- " 6 PhysicalActivities 44408 non-null float64 \n",
- " 7 SleepHours 44008 non-null float64 \n",
- " 8 RemovedTeeth 43413 non-null float64 \n",
- " 9 HadHeartAttack 44182 non-null float64 \n",
- " 10 HadAngina 44074 non-null float64 \n",
- " 11 HadStroke 44368 non-null float64 \n",
- " 12 HadAsthma 44339 non-null float64 \n",
- " 13 HadSkinCancer 44184 non-null float64 \n",
- " 14 HadCOPD 44299 non-null float64 \n",
- " 15 HadDepressiveDisorder 44218 non-null float64 \n",
- " 16 HadKidneyDisease 44320 non-null float64 \n",
- " 17 HadArthritis 44243 non-null float64 \n",
- " 18 HadDiabetes 44411 non-null float64 \n",
- " 19 DeafOrHardOfHearing 42485 non-null float64 \n",
- " 20 BlindOrVisionDifficulty 42387 non-null float64 \n",
- " 21 DifficultyConcentrating 42169 non-null float64 \n",
- " 22 DifficultyWalking 42172 non-null float64 \n",
- " 23 DifficultyDressingBathing 42182 non-null float64 \n",
- " 24 DifficultyErrands 41999 non-null float64 \n",
- " 25 SmokerStatus 41005 non-null float64 \n",
- " 26 ECigaretteUsage 41003 non-null float64 \n",
- " 27 ChestScan 38958 non-null float64 \n",
+ " 6 PhysicalActivities 44402 non-null float64 \n",
+ " 7 SleepHours 43952 non-null float64 \n",
+ " 8 RemovedTeeth 43394 non-null float64 \n",
+ " 9 HadHeartAttack 44227 non-null float64 \n",
+ " 10 HadAngina 44101 non-null float64 \n",
+ " 11 HadStroke 44360 non-null float64 \n",
+ " 12 HadAsthma 44323 non-null float64 \n",
+ " 13 HadSkinCancer 44186 non-null float64 \n",
+ " 14 HadCOPD 44276 non-null float64 \n",
+ " 15 HadDepressiveDisorder 44239 non-null float64 \n",
+ " 16 HadKidneyDisease 44336 non-null float64 \n",
+ " 17 HadArthritis 44254 non-null float64 \n",
+ " 18 HadDiabetes 44386 non-null float64 \n",
+ " 19 DeafOrHardOfHearing 42470 non-null float64 \n",
+ " 20 BlindOrVisionDifficulty 42355 non-null float64 \n",
+ " 21 DifficultyConcentrating 42104 non-null float64 \n",
+ " 22 DifficultyWalking 42121 non-null float64 \n",
+ " 23 DifficultyDressingBathing 42141 non-null float64 \n",
+ " 24 DifficultyErrands 41986 non-null float64 \n",
+ " 25 SmokerStatus 40996 non-null float64 \n",
+ " 26 ECigaretteUsage 40955 non-null float64 \n",
+ " 27 ChestScan 38863 non-null float64 \n",
" 28 RaceEthnicityCategory 44513 non-null category\n",
" 29 AgeCategory 44513 non-null category\n",
- " 30 HeightInMeters 41714 non-null float64 \n",
- " 31 WeightInKilograms 40397 non-null float64 \n",
- " 32 BMI 39724 non-null float64 \n",
- " 33 AlcoholDrinkers 39956 non-null float64 \n",
- " 34 HIVTesting 38018 non-null float64 \n",
- " 35 FluVaxLast12 39886 non-null float64 \n",
- " 36 PneumoVaxEver 36860 non-null float64 \n",
+ " 30 HeightInMeters 41620 non-null float64 \n",
+ " 31 WeightInKilograms 40212 non-null float64 \n",
+ " 32 BMI 39520 non-null float64 \n",
+ " 33 AlcoholDrinkers 39817 non-null float64 \n",
+ " 34 HIVTesting 37853 non-null float64 \n",
+ " 35 FluVaxLast12 39779 non-null float64 \n",
+ " 36 PneumoVaxEver 36821 non-null float64 \n",
" 37 TetanusLast10Tdap 36315 non-null float64 \n",
- " 38 HighRiskLastYear 39538 non-null float64 \n",
- " 39 CovidPos 38114 non-null float64 \n",
+ " 38 HighRiskLastYear 39453 non-null float64 \n",
+ " 39 CovidPos 38048 non-null float64 \n",
"dtypes: category(4), float64(36)\n",
"memory usage: 12.7 MB\n"
]
@@ -1037,7 +999,7 @@
},
{
"cell_type": "code",
- "execution_count": 61,
+ "execution_count": 125,
"outputs": [],
"source": [
"normalize_dataset(train)\n",
@@ -1060,14 +1022,14 @@
},
{
"cell_type": "code",
- "execution_count": 62,
+ "execution_count": 126,
"outputs": [
{
"data": {
- "text/plain": " Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\ncount 676777.000000 674433.000000 655630.000000 660417.000000 \nmean 0.538139 3.055519 6.737547 4.863972 \nstd 0.498544 1.137862 10.713287 9.115863 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 2.000000 0.000000 0.000000 \n50% 1.000000 3.000000 0.000000 0.000000 \n75% 1.000000 4.000000 10.000000 5.000000 \nmax 1.000000 5.000000 30.000000 30.000000 \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack \\\ncount 674814.000000 665609.000000 654359.000000 674355.000000 \nmean 0.690146 7.032336 0.983081 0.505244 \nstd 0.462434 1.726387 1.019679 0.499973 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 6.000000 0.000000 0.000000 \n50% 1.000000 7.000000 1.000000 1.000000 \n75% 1.000000 8.000000 2.000000 1.000000 \nmax 1.000000 24.000000 3.000000 1.000000 \n\n HadAngina HadStroke ... HeightInMeters WeightInKilograms \\\ncount 657726.000000 672927.000000 ... 637313.000000 619546.000000 \nmean 0.264549 0.117193 ... 1.707193 84.657015 \nstd 0.441093 0.321650 ... 0.108002 21.753692 \nmin 0.000000 0.000000 ... 0.910000 22.680000 \n25% 0.000000 0.000000 ... 1.630000 69.400000 \n50% 0.000000 0.000000 ... 1.700000 81.650000 \n75% 1.000000 0.000000 ... 1.780000 96.160000 \nmax 1.000000 1.000000 ... 2.410000 292.570000 \n\n BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\ncount 611024.000000 606636.000000 572562.000000 605920.000000 \nmean 28.917363 0.456819 0.325787 0.569879 \nstd 6.607455 0.498132 0.468668 0.495093 \nmin 12.050000 0.000000 0.000000 0.000000 \n25% 24.410000 0.000000 0.000000 0.000000 \n50% 27.890000 0.000000 0.000000 1.000000 \n75% 32.260000 1.000000 1.000000 1.000000 \nmax 97.650000 1.000000 1.000000 1.000000 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \ncount 570114.000000 554467.0 600540.000000 585150.000000 \nmean 0.527672 1.0 0.035087 0.273055 \nstd 0.499234 0.0 0.183999 0.445529 \nmin 0.000000 1.0 0.000000 0.000000 \n25% 0.000000 1.0 0.000000 0.000000 \n50% 1.000000 1.0 0.000000 0.000000 \n75% 1.000000 1.0 0.000000 1.000000 \nmax 1.000000 1.0 1.000000 1.000000 \n\n[8 rows x 36 columns]",
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\n \n \n \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n HadAngina \n HadStroke \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n count \n 676777.000000 \n 674433.000000 \n 655630.000000 \n 660417.000000 \n 674814.000000 \n 665609.000000 \n 654359.000000 \n 674355.000000 \n 657726.000000 \n 672927.000000 \n ... \n 637313.000000 \n 619546.000000 \n 611024.000000 \n 606636.000000 \n 572562.000000 \n 605920.000000 \n 570114.000000 \n 554467.0 \n 600540.000000 \n 585150.000000 \n \n \n mean \n 0.538139 \n 3.055519 \n 6.737547 \n 4.863972 \n 0.690146 \n 7.032336 \n 0.983081 \n 0.505244 \n 0.264549 \n 0.117193 \n ... \n 1.707193 \n 84.657015 \n 28.917363 \n 0.456819 \n 0.325787 \n 0.569879 \n 0.527672 \n 1.0 \n 0.035087 \n 0.273055 \n \n \n std \n 0.498544 \n 1.137862 \n 10.713287 \n 9.115863 \n 0.462434 \n 1.726387 \n 1.019679 \n 0.499973 \n 0.441093 \n 0.321650 \n ... \n 0.108002 \n 21.753692 \n 6.607455 \n 0.498132 \n 0.468668 \n 0.495093 \n 0.499234 \n 0.0 \n 0.183999 \n 0.445529 \n \n \n min \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 0.910000 \n 22.680000 \n 12.050000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 25% \n 0.000000 \n 2.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 6.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.630000 \n 69.400000 \n 24.410000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 50% \n 1.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 7.000000 \n 1.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n ... \n 1.700000 \n 81.650000 \n 27.890000 \n 0.000000 \n 0.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 75% \n 1.000000 \n 4.000000 \n 10.000000 \n 5.000000 \n 1.000000 \n 8.000000 \n 2.000000 \n 1.000000 \n 1.000000 \n 0.000000 \n ... \n 1.780000 \n 96.160000 \n 32.260000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 1.000000 \n \n \n max \n 1.000000 \n 5.000000 \n 30.000000 \n 30.000000 \n 1.000000 \n 24.000000 \n 3.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n ... \n 2.410000 \n 292.570000 \n 97.650000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 1.000000 \n 1.000000 \n \n \n
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8 rows × 36 columns
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+ "text/plain": " Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\ncount 676361.000000 674074.000000 655378.000000 660076.000000 \nmean 0.538461 3.055939 6.729019 4.851376 \nstd 0.498519 1.138040 10.712884 9.106112 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 2.000000 0.000000 0.000000 \n50% 1.000000 3.000000 0.000000 0.000000 \n75% 1.000000 4.000000 10.000000 5.000000 \nmax 1.000000 5.000000 30.000000 30.000000 \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack \\\ncount 674264.000000 665524.000000 653726.000000 673906.000000 \nmean 0.689958 7.038852 0.978907 0.504925 \nstd 0.462511 1.729860 1.018776 0.499976 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 6.000000 0.000000 0.000000 \n50% 1.000000 7.000000 1.000000 1.000000 \n75% 1.000000 8.000000 2.000000 1.000000 \nmax 1.000000 24.000000 3.000000 1.000000 \n\n HadAngina HadStroke ... HeightInMeters WeightInKilograms \\\ncount 657289.000000 672572.000000 ... 636986.000000 619364.000000 \nmean 0.263980 0.117729 ... 1.707282 84.678030 \nstd 0.440789 0.322287 ... 0.108041 21.671753 \nmin 0.000000 0.000000 ... 0.910000 22.680000 \n25% 0.000000 0.000000 ... 1.630000 69.400000 \n50% 0.000000 0.000000 ... 1.700000 81.650000 \n75% 1.000000 0.000000 ... 1.780000 96.160000 \nmax 1.000000 1.000000 ... 2.410000 292.570000 \n\n BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\ncount 610744.000000 607296.000000 573796.000000 606661.000000 \nmean 28.935880 0.456237 0.324913 0.571250 \nstd 6.616632 0.498082 0.468343 0.494898 \nmin 12.050000 0.000000 0.000000 0.000000 \n25% 24.410000 0.000000 0.000000 0.000000 \n50% 27.890000 0.000000 0.000000 1.000000 \n75% 32.280000 1.000000 1.000000 1.000000 \nmax 99.640000 1.000000 1.000000 1.000000 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \ncount 571290.000000 554109.0 601088.000000 585564.000000 \nmean 0.528798 1.0 0.035005 0.274667 \nstd 0.499170 0.0 0.183792 0.446347 \nmin 0.000000 1.0 0.000000 0.000000 \n25% 0.000000 1.0 0.000000 0.000000 \n50% 1.000000 1.0 0.000000 0.000000 \n75% 1.000000 1.0 0.000000 1.000000 \nmax 1.000000 1.0 1.000000 1.000000 \n\n[8 rows x 36 columns]",
+ "text/html": "\n\n
\n \n \n \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n HadAngina \n HadStroke \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n count \n 676361.000000 \n 674074.000000 \n 655378.000000 \n 660076.000000 \n 674264.000000 \n 665524.000000 \n 653726.000000 \n 673906.000000 \n 657289.000000 \n 672572.000000 \n ... \n 636986.000000 \n 619364.000000 \n 610744.000000 \n 607296.000000 \n 573796.000000 \n 606661.000000 \n 571290.000000 \n 554109.0 \n 601088.000000 \n 585564.000000 \n \n \n mean \n 0.538461 \n 3.055939 \n 6.729019 \n 4.851376 \n 0.689958 \n 7.038852 \n 0.978907 \n 0.504925 \n 0.263980 \n 0.117729 \n ... \n 1.707282 \n 84.678030 \n 28.935880 \n 0.456237 \n 0.324913 \n 0.571250 \n 0.528798 \n 1.0 \n 0.035005 \n 0.274667 \n \n \n std \n 0.498519 \n 1.138040 \n 10.712884 \n 9.106112 \n 0.462511 \n 1.729860 \n 1.018776 \n 0.499976 \n 0.440789 \n 0.322287 \n ... \n 0.108041 \n 21.671753 \n 6.616632 \n 0.498082 \n 0.468343 \n 0.494898 \n 0.499170 \n 0.0 \n 0.183792 \n 0.446347 \n \n \n min \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 0.910000 \n 22.680000 \n 12.050000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 25% \n 0.000000 \n 2.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 6.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.630000 \n 69.400000 \n 24.410000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 50% \n 1.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 7.000000 \n 1.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n ... \n 1.700000 \n 81.650000 \n 27.890000 \n 0.000000 \n 0.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 75% \n 1.000000 \n 4.000000 \n 10.000000 \n 5.000000 \n 1.000000 \n 8.000000 \n 2.000000 \n 1.000000 \n 1.000000 \n 0.000000 \n ... \n 1.780000 \n 96.160000 \n 32.280000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 1.000000 \n \n \n max \n 1.000000 \n 5.000000 \n 30.000000 \n 30.000000 \n 1.000000 \n 24.000000 \n 3.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n ... \n 2.410000 \n 292.570000 \n 99.640000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 1.000000 \n 1.000000 \n \n \n
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8 rows × 36 columns
\n
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},
- "execution_count": 62,
+ "execution_count": 126,
"metadata": {},
"output_type": "execute_result"
}
@@ -1081,14 +1043,14 @@
},
{
"cell_type": "code",
- "execution_count": 63,
+ "execution_count": 127,
"outputs": [
{
"data": {
- "text/plain": " Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\ncount 44513.000000 44393.000000 43469.000000 43622.000000 \nmean 0.471593 3.441511 4.275001 4.298221 \nstd 0.499198 1.050924 8.588663 8.299250 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 3.000000 0.000000 0.000000 \n50% 0.000000 3.000000 0.000000 0.000000 \n75% 1.000000 4.000000 3.000000 4.000000 \nmax 1.000000 5.000000 30.000000 30.000000 \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack \\\ncount 44408.000000 44008.000000 43413.000000 44182.000000 \nmean 0.760021 7.036584 0.685302 0.057241 \nstd 0.427075 1.512667 0.884912 0.232304 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 1.000000 6.000000 0.000000 0.000000 \n50% 1.000000 7.000000 0.000000 0.000000 \n75% 1.000000 8.000000 1.000000 0.000000 \nmax 1.000000 24.000000 3.000000 1.000000 \n\n HadAngina HadStroke ... HeightInMeters WeightInKilograms \\\ncount 44074.000000 44368.000000 ... 41714.000000 40397.000000 \nmean 0.061056 0.042869 ... 1.703194 83.021746 \nstd 0.239436 0.202563 ... 0.107438 21.551394 \nmin 0.000000 0.000000 ... 0.910000 22.680000 \n25% 0.000000 0.000000 ... 1.630000 68.040000 \n50% 0.000000 0.000000 ... 1.700000 80.740000 \n75% 0.000000 0.000000 ... 1.780000 95.250000 \nmax 1.000000 1.000000 ... 2.340000 290.300000 \n\n BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\ncount 39724.000000 39956.000000 38018.000000 39886.000000 \nmean 28.512326 0.529532 0.342233 0.527002 \nstd 6.596149 0.499133 0.474463 0.499277 \nmin 12.020000 0.000000 0.000000 0.000000 \n25% 24.030000 0.000000 0.000000 0.000000 \n50% 27.410000 1.000000 0.000000 1.000000 \n75% 31.650000 1.000000 1.000000 1.000000 \nmax 97.650000 1.000000 1.000000 1.000000 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \ncount 36860.000000 36315.0 39538.000000 38114.000000 \nmean 0.413592 1.0 0.043427 0.289500 \nstd 0.492484 0.0 0.203818 0.453536 \nmin 0.000000 1.0 0.000000 0.000000 \n25% 0.000000 1.0 0.000000 0.000000 \n50% 0.000000 1.0 0.000000 0.000000 \n75% 1.000000 1.0 0.000000 1.000000 \nmax 1.000000 1.0 1.000000 1.000000 \n\n[8 rows x 36 columns]",
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\n \n \n \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n HadAngina \n HadStroke \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n count \n 44513.000000 \n 44393.000000 \n 43469.000000 \n 43622.000000 \n 44408.000000 \n 44008.000000 \n 43413.000000 \n 44182.000000 \n 44074.000000 \n 44368.000000 \n ... \n 41714.000000 \n 40397.000000 \n 39724.000000 \n 39956.000000 \n 38018.000000 \n 39886.000000 \n 36860.000000 \n 36315.0 \n 39538.000000 \n 38114.000000 \n \n \n mean \n 0.471593 \n 3.441511 \n 4.275001 \n 4.298221 \n 0.760021 \n 7.036584 \n 0.685302 \n 0.057241 \n 0.061056 \n 0.042869 \n ... \n 1.703194 \n 83.021746 \n 28.512326 \n 0.529532 \n 0.342233 \n 0.527002 \n 0.413592 \n 1.0 \n 0.043427 \n 0.289500 \n \n \n std \n 0.499198 \n 1.050924 \n 8.588663 \n 8.299250 \n 0.427075 \n 1.512667 \n 0.884912 \n 0.232304 \n 0.239436 \n 0.202563 \n ... \n 0.107438 \n 21.551394 \n 6.596149 \n 0.499133 \n 0.474463 \n 0.499277 \n 0.492484 \n 0.0 \n 0.203818 \n 0.453536 \n \n \n min \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 0.910000 \n 22.680000 \n 12.020000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 25% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 6.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.630000 \n 68.040000 \n 24.030000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 50% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 7.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.700000 \n 80.740000 \n 27.410000 \n 1.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 75% \n 1.000000 \n 4.000000 \n 3.000000 \n 4.000000 \n 1.000000 \n 8.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.780000 \n 95.250000 \n 31.650000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 1.000000 \n \n \n max \n 1.000000 \n 5.000000 \n 30.000000 \n 30.000000 \n 1.000000 \n 24.000000 \n 3.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n ... \n 2.340000 \n 290.300000 \n 97.650000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 1.000000 \n 1.000000 \n \n \n
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8 rows × 36 columns
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+ "text/plain": " Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\ncount 44513.000000 44400.000000 43445.000000 43614.000000 \nmean 0.468402 3.437815 4.266222 4.363989 \nstd 0.499006 1.047836 8.570562 8.340355 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 3.000000 0.000000 0.000000 \n50% 0.000000 3.000000 0.000000 0.000000 \n75% 1.000000 4.000000 3.000000 5.000000 \nmax 1.000000 5.000000 30.000000 30.000000 \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack \\\ncount 44402.000000 43952.000000 43394.000000 44227.000000 \nmean 0.761092 7.016746 0.683505 0.056775 \nstd 0.426421 1.490779 0.884697 0.231415 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 1.000000 6.000000 0.000000 0.000000 \n50% 1.000000 7.000000 0.000000 0.000000 \n75% 1.000000 8.000000 1.000000 0.000000 \nmax 1.000000 24.000000 3.000000 1.000000 \n\n HadAngina HadStroke ... HeightInMeters WeightInKilograms \\\ncount 44101.000000 44360.000000 ... 41620.000000 40212.000000 \nmean 0.059817 0.042178 ... 1.702194 83.020179 \nstd 0.237151 0.200997 ... 0.107023 21.645999 \nmin 0.000000 0.000000 ... 0.910000 22.680000 \n25% 0.000000 0.000000 ... 1.630000 68.040000 \n50% 0.000000 0.000000 ... 1.700000 80.740000 \n75% 0.000000 0.000000 ... 1.780000 95.250000 \nmax 1.000000 1.000000 ... 2.240000 290.300000 \n\n BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\ncount 39520.000000 39817.000000 37853.000000 39779.000000 \nmean 28.509078 0.531281 0.343539 0.529123 \nstd 6.571327 0.499027 0.474896 0.499157 \nmin 12.340000 0.000000 0.000000 0.000000 \n25% 24.030000 0.000000 0.000000 0.000000 \n50% 27.410000 1.000000 0.000000 1.000000 \n75% 31.660000 1.000000 1.000000 1.000000 \nmax 94.660000 1.000000 1.000000 1.000000 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \ncount 36821.000000 36315.0 39453.000000 38048.000000 \nmean 0.417615 1.0 0.043774 0.290896 \nstd 0.493173 0.0 0.204594 0.454181 \nmin 0.000000 1.0 0.000000 0.000000 \n25% 0.000000 1.0 0.000000 0.000000 \n50% 0.000000 1.0 0.000000 0.000000 \n75% 1.000000 1.0 0.000000 1.000000 \nmax 1.000000 1.0 1.000000 1.000000 \n\n[8 rows x 36 columns]",
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\n \n \n \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n HadAngina \n HadStroke \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n count \n 44513.000000 \n 44400.000000 \n 43445.000000 \n 43614.000000 \n 44402.000000 \n 43952.000000 \n 43394.000000 \n 44227.000000 \n 44101.000000 \n 44360.000000 \n ... \n 41620.000000 \n 40212.000000 \n 39520.000000 \n 39817.000000 \n 37853.000000 \n 39779.000000 \n 36821.000000 \n 36315.0 \n 39453.000000 \n 38048.000000 \n \n \n mean \n 0.468402 \n 3.437815 \n 4.266222 \n 4.363989 \n 0.761092 \n 7.016746 \n 0.683505 \n 0.056775 \n 0.059817 \n 0.042178 \n ... \n 1.702194 \n 83.020179 \n 28.509078 \n 0.531281 \n 0.343539 \n 0.529123 \n 0.417615 \n 1.0 \n 0.043774 \n 0.290896 \n \n \n std \n 0.499006 \n 1.047836 \n 8.570562 \n 8.340355 \n 0.426421 \n 1.490779 \n 0.884697 \n 0.231415 \n 0.237151 \n 0.200997 \n ... \n 0.107023 \n 21.645999 \n 6.571327 \n 0.499027 \n 0.474896 \n 0.499157 \n 0.493173 \n 0.0 \n 0.204594 \n 0.454181 \n \n \n min \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 0.910000 \n 22.680000 \n 12.340000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 25% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 6.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.630000 \n 68.040000 \n 24.030000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 50% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 7.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.700000 \n 80.740000 \n 27.410000 \n 1.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 75% \n 1.000000 \n 4.000000 \n 3.000000 \n 5.000000 \n 1.000000 \n 8.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.780000 \n 95.250000 \n 31.660000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 1.000000 \n \n \n max \n 1.000000 \n 5.000000 \n 30.000000 \n 30.000000 \n 1.000000 \n 24.000000 \n 3.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n ... \n 2.240000 \n 290.300000 \n 94.660000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 1.000000 \n 1.000000 \n \n \n
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8 rows × 36 columns
\n
"
},
- "execution_count": 63,
+ "execution_count": 127,
"metadata": {},
"output_type": "execute_result"
}
@@ -1102,14 +1064,14 @@
},
{
"cell_type": "code",
- "execution_count": 64,
+ "execution_count": 128,
"outputs": [
{
"data": {
- "text/plain": " Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\ncount 44514.000000 44388.000000 43458.000000 43578.000000 \nmean 0.469043 3.434554 4.355470 4.379022 \nstd 0.499046 1.051996 8.718506 8.383576 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 3.000000 0.000000 0.000000 \n50% 0.000000 3.000000 0.000000 0.000000 \n75% 1.000000 4.000000 3.000000 5.000000 \nmax 1.000000 5.000000 30.000000 30.000000 \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack \\\ncount 44401.000000 43966.000000 43360.000000 44202.000000 \nmean 0.758361 7.013010 0.684732 0.057396 \nstd 0.428081 1.491967 0.882396 0.232600 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 1.000000 6.000000 0.000000 0.000000 \n50% 1.000000 7.000000 0.000000 0.000000 \n75% 1.000000 8.000000 1.000000 0.000000 \nmax 1.000000 24.000000 3.000000 1.000000 \n\n HadAngina HadStroke ... HeightInMeters WeightInKilograms \\\ncount 44031.000000 44344.000000 ... 41677.000000 40327.000000 \nmean 0.058936 0.042463 ... 1.702146 82.981070 \nstd 0.235507 0.201646 ... 0.106978 21.512676 \nmin 0.000000 0.000000 ... 0.910000 22.680000 \n25% 0.000000 0.000000 ... 1.630000 68.040000 \n50% 0.000000 0.000000 ... 1.700000 79.830000 \n75% 0.000000 0.000000 ... 1.780000 95.250000 \nmax 1.000000 1.000000 ... 2.360000 263.080000 \n\n BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\ncount 39626.000000 39950.000000 38041.000000 39885.000000 \nmean 28.521370 0.527910 0.342525 0.525285 \nstd 6.622255 0.499227 0.474560 0.499367 \nmin 12.160000 0.000000 0.000000 0.000000 \n25% 24.030000 0.000000 0.000000 0.000000 \n50% 27.400000 1.000000 0.000000 1.000000 \n75% 31.750000 1.000000 1.000000 1.000000 \nmax 99.640000 1.000000 1.000000 1.000000 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \ncount 36926.000000 36250.0 39535.000000 38212.000000 \nmean 0.412771 1.0 0.044846 0.291872 \nstd 0.492339 0.0 0.206969 0.454630 \nmin 0.000000 1.0 0.000000 0.000000 \n25% 0.000000 1.0 0.000000 0.000000 \n50% 0.000000 1.0 0.000000 0.000000 \n75% 1.000000 1.0 0.000000 1.000000 \nmax 1.000000 1.0 1.000000 1.000000 \n\n[8 rows x 36 columns]",
- "text/html": "\n\n
\n \n \n \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n HadAngina \n HadStroke \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n count \n 44514.000000 \n 44388.000000 \n 43458.000000 \n 43578.000000 \n 44401.000000 \n 43966.000000 \n 43360.000000 \n 44202.000000 \n 44031.000000 \n 44344.000000 \n ... \n 41677.000000 \n 40327.000000 \n 39626.000000 \n 39950.000000 \n 38041.000000 \n 39885.000000 \n 36926.000000 \n 36250.0 \n 39535.000000 \n 38212.000000 \n \n \n mean \n 0.469043 \n 3.434554 \n 4.355470 \n 4.379022 \n 0.758361 \n 7.013010 \n 0.684732 \n 0.057396 \n 0.058936 \n 0.042463 \n ... \n 1.702146 \n 82.981070 \n 28.521370 \n 0.527910 \n 0.342525 \n 0.525285 \n 0.412771 \n 1.0 \n 0.044846 \n 0.291872 \n \n \n std \n 0.499046 \n 1.051996 \n 8.718506 \n 8.383576 \n 0.428081 \n 1.491967 \n 0.882396 \n 0.232600 \n 0.235507 \n 0.201646 \n ... \n 0.106978 \n 21.512676 \n 6.622255 \n 0.499227 \n 0.474560 \n 0.499367 \n 0.492339 \n 0.0 \n 0.206969 \n 0.454630 \n \n \n min \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 0.910000 \n 22.680000 \n 12.160000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 25% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 6.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.630000 \n 68.040000 \n 24.030000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 50% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 7.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.700000 \n 79.830000 \n 27.400000 \n 1.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 75% \n 1.000000 \n 4.000000 \n 3.000000 \n 5.000000 \n 1.000000 \n 8.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.780000 \n 95.250000 \n 31.750000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 1.000000 \n \n \n max \n 1.000000 \n 5.000000 \n 30.000000 \n 30.000000 \n 1.000000 \n 24.000000 \n 3.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n ... \n 2.360000 \n 263.080000 \n 99.640000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 1.000000 \n 1.000000 \n \n \n
\n
8 rows × 36 columns
\n
"
+ "text/plain": " Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\ncount 44514.000000 44388.000000 43430.000000 43655.000000 \nmean 0.470571 3.429733 4.332006 4.394823 \nstd 0.499139 1.052177 8.681714 8.423078 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 0.000000 3.000000 0.000000 0.000000 \n50% 0.000000 3.000000 0.000000 0.000000 \n75% 1.000000 4.000000 3.000000 4.500000 \nmax 1.000000 5.000000 30.000000 30.000000 \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack \\\ncount 44413.000000 44011.000000 43420.000000 44190.000000 \nmean 0.759215 7.014360 0.684938 0.058407 \nstd 0.427565 1.510916 0.880082 0.234514 \nmin 0.000000 1.000000 0.000000 0.000000 \n25% 1.000000 6.000000 0.000000 0.000000 \n50% 1.000000 7.000000 0.000000 0.000000 \n75% 1.000000 8.000000 1.000000 0.000000 \nmax 1.000000 24.000000 3.000000 1.000000 \n\n HadAngina HadStroke ... HeightInMeters WeightInKilograms \\\ncount 44057.000000 44339.000000 ... 41618.000000 40342.000000 \nmean 0.059605 0.041747 ... 1.702956 83.157638 \nstd 0.236755 0.200012 ... 0.107780 21.489722 \nmin 0.000000 0.000000 ... 0.910000 24.950000 \n25% 0.000000 0.000000 ... 1.630000 68.040000 \n50% 0.000000 0.000000 ... 1.700000 80.740000 \n75% 0.000000 0.000000 ... 1.780000 95.250000 \nmax 1.000000 1.000000 ... 2.290000 285.000000 \n\n BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\ncount 39646.000000 39861.000000 37852.000000 39827.000000 \nmean 28.558016 0.530493 0.341118 0.524795 \nstd 6.623124 0.499076 0.474091 0.499391 \nmin 12.020000 0.000000 0.000000 0.000000 \n25% 24.130000 0.000000 0.000000 0.000000 \n50% 27.415000 1.000000 0.000000 1.000000 \n75% 31.750000 1.000000 1.000000 1.000000 \nmax 99.340000 1.000000 1.000000 1.000000 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \ncount 36781.000000 36224.0 39424.000000 38088.000000 \nmean 0.410810 1.0 0.042639 0.288542 \nstd 0.491988 0.0 0.202044 0.453091 \nmin 0.000000 1.0 0.000000 0.000000 \n25% 0.000000 1.0 0.000000 0.000000 \n50% 0.000000 1.0 0.000000 0.000000 \n75% 1.000000 1.0 0.000000 1.000000 \nmax 1.000000 1.0 1.000000 1.000000 \n\n[8 rows x 36 columns]",
+ "text/html": "\n\n
\n \n \n \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n HadAngina \n HadStroke \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n count \n 44514.000000 \n 44388.000000 \n 43430.000000 \n 43655.000000 \n 44413.000000 \n 44011.000000 \n 43420.000000 \n 44190.000000 \n 44057.000000 \n 44339.000000 \n ... \n 41618.000000 \n 40342.000000 \n 39646.000000 \n 39861.000000 \n 37852.000000 \n 39827.000000 \n 36781.000000 \n 36224.0 \n 39424.000000 \n 38088.000000 \n \n \n mean \n 0.470571 \n 3.429733 \n 4.332006 \n 4.394823 \n 0.759215 \n 7.014360 \n 0.684938 \n 0.058407 \n 0.059605 \n 0.041747 \n ... \n 1.702956 \n 83.157638 \n 28.558016 \n 0.530493 \n 0.341118 \n 0.524795 \n 0.410810 \n 1.0 \n 0.042639 \n 0.288542 \n \n \n std \n 0.499139 \n 1.052177 \n 8.681714 \n 8.423078 \n 0.427565 \n 1.510916 \n 0.880082 \n 0.234514 \n 0.236755 \n 0.200012 \n ... \n 0.107780 \n 21.489722 \n 6.623124 \n 0.499076 \n 0.474091 \n 0.499391 \n 0.491988 \n 0.0 \n 0.202044 \n 0.453091 \n \n \n min \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 0.910000 \n 24.950000 \n 12.020000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 25% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 6.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.630000 \n 68.040000 \n 24.130000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 50% \n 0.000000 \n 3.000000 \n 0.000000 \n 0.000000 \n 1.000000 \n 7.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.700000 \n 80.740000 \n 27.415000 \n 1.000000 \n 0.000000 \n 1.000000 \n 0.000000 \n 1.0 \n 0.000000 \n 0.000000 \n \n \n 75% \n 1.000000 \n 4.000000 \n 3.000000 \n 4.500000 \n 1.000000 \n 8.000000 \n 1.000000 \n 0.000000 \n 0.000000 \n 0.000000 \n ... \n 1.780000 \n 95.250000 \n 31.750000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 0.000000 \n 1.000000 \n \n \n max \n 1.000000 \n 5.000000 \n 30.000000 \n 30.000000 \n 1.000000 \n 24.000000 \n 3.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n ... \n 2.290000 \n 285.000000 \n 99.340000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.000000 \n 1.0 \n 1.000000 \n 1.000000 \n \n \n
\n
8 rows × 36 columns
\n
"
},
- "execution_count": 64,
+ "execution_count": 128,
"metadata": {},
"output_type": "execute_result"
}
@@ -1132,12 +1094,12 @@
},
{
"cell_type": "code",
- "execution_count": 65,
+ "execution_count": 129,
"outputs": [
{
"data": {
"text/plain": "",
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\n"
+ "image/png": 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\n"
},
"metadata": {},
"output_type": "display_data"
@@ -1170,14 +1132,14 @@
},
{
"cell_type": "code",
- "execution_count": 66,
+ "execution_count": 130,
"outputs": [
{
"data": {
- "text/plain": " SmokerStatus HadHeartAttack\n0 0.0 0.037883\n1 1.0 0.072598\n2 2.0 0.088887\n3 3.0 0.090192",
- "text/html": "\n\n
\n \n \n \n SmokerStatus \n HadHeartAttack \n \n \n \n \n 0 \n 0.0 \n 0.037883 \n \n \n 1 \n 1.0 \n 0.072598 \n \n \n 2 \n 2.0 \n 0.088887 \n \n \n 3 \n 3.0 \n 0.090192 \n \n \n
\n
"
+ "text/plain": " SmokerStatus HadHeartAttack\n0 0.0 0.036784\n1 1.0 0.072586\n2 2.0 0.092351\n3 3.0 0.090198",
+ "text/html": "\n\n
\n \n \n \n SmokerStatus \n HadHeartAttack \n \n \n \n \n 0 \n 0.0 \n 0.036784 \n \n \n 1 \n 1.0 \n 0.072586 \n \n \n 2 \n 2.0 \n 0.092351 \n \n \n 3 \n 3.0 \n 0.090198 \n \n \n
\n
"
},
- "execution_count": 66,
+ "execution_count": 130,
"metadata": {},
"output_type": "execute_result"
}
@@ -1200,14 +1162,14 @@
},
{
"cell_type": "code",
- "execution_count": 67,
+ "execution_count": 131,
"outputs": [
{
"data": {
- "text/plain": " GeneralHealth HadHeartAttack\n0 1.0 0.228411\n1 2.0 0.129270\n2 3.0 0.056693\n3 4.0 0.027336\n4 5.0 0.014743",
- "text/html": "\n\n
\n \n \n \n GeneralHealth \n HadHeartAttack \n \n \n \n \n 0 \n 1.0 \n 0.228411 \n \n \n 1 \n 2.0 \n 0.129270 \n \n \n 2 \n 3.0 \n 0.056693 \n \n \n 3 \n 4.0 \n 0.027336 \n \n \n 4 \n 5.0 \n 0.014743 \n \n \n
\n
"
+ "text/plain": " GeneralHealth HadHeartAttack\n0 1.0 0.228482\n1 2.0 0.125921\n2 3.0 0.058758\n3 4.0 0.028679\n4 5.0 0.014917",
+ "text/html": "\n\n
\n \n \n \n GeneralHealth \n HadHeartAttack \n \n \n \n \n 0 \n 1.0 \n 0.228482 \n \n \n 1 \n 2.0 \n 0.125921 \n \n \n 2 \n 3.0 \n 0.058758 \n \n \n 3 \n 4.0 \n 0.028679 \n \n \n 4 \n 5.0 \n 0.014917 \n \n \n
\n
"
},
- "execution_count": 67,
+ "execution_count": 131,
"metadata": {},
"output_type": "execute_result"
}
@@ -1221,14 +1183,14 @@
},
{
"cell_type": "code",
- "execution_count": 68,
+ "execution_count": 132,
"outputs": [
{
"data": {
- "text/plain": "SmokerStatus 0.0 1.0 2.0 3.0\nGeneralHealth \n1.0 0.194640 0.310680 0.257100 0.222222\n2.0 0.090772 0.146429 0.184443 0.155059\n3.0 0.039989 0.031068 0.091645 0.060469\n4.0 0.021611 0.032070 0.035265 0.048292\n5.0 0.011078 0.012579 0.026298 0.018315",
- "text/html": "\n\n
\n \n \n SmokerStatus \n 0.0 \n 1.0 \n 2.0 \n 3.0 \n \n \n GeneralHealth \n \n \n \n \n \n \n \n \n 1.0 \n 0.194640 \n 0.310680 \n 0.257100 \n 0.222222 \n \n \n 2.0 \n 0.090772 \n 0.146429 \n 0.184443 \n 0.155059 \n \n \n 3.0 \n 0.039989 \n 0.031068 \n 0.091645 \n 0.060469 \n \n \n 4.0 \n 0.021611 \n 0.032070 \n 0.035265 \n 0.048292 \n \n \n 5.0 \n 0.011078 \n 0.012579 \n 0.026298 \n 0.018315 \n \n \n
\n
"
+ "text/plain": "SmokerStatus 0.0 1.0 2.0 3.0\nGeneralHealth \n1.0 0.176024 0.258065 0.257364 0.245614\n2.0 0.085981 0.123404 0.178412 0.146520\n3.0 0.041363 0.055769 0.090743 0.063766\n4.0 0.019886 0.021918 0.048122 0.034739\n5.0 0.012267 0.028736 0.020260 0.021978",
+ "text/html": "\n\n
\n \n \n SmokerStatus \n 0.0 \n 1.0 \n 2.0 \n 3.0 \n \n \n GeneralHealth \n \n \n \n \n \n \n \n \n 1.0 \n 0.176024 \n 0.258065 \n 0.257364 \n 0.245614 \n \n \n 2.0 \n 0.085981 \n 0.123404 \n 0.178412 \n 0.146520 \n \n \n 3.0 \n 0.041363 \n 0.055769 \n 0.090743 \n 0.063766 \n \n \n 4.0 \n 0.019886 \n 0.021918 \n 0.048122 \n 0.034739 \n \n \n 5.0 \n 0.012267 \n 0.028736 \n 0.020260 \n 0.021978 \n \n \n
\n
"
},
- "execution_count": 68,
+ "execution_count": 132,
"metadata": {},
"output_type": "execute_result"
}
@@ -1251,7 +1213,7 @@
},
{
"cell_type": "code",
- "execution_count": 69,
+ "execution_count": 133,
"outputs": [],
"source": [
"from sklearn.preprocessing import MinMaxScaler\n",
@@ -1266,14 +1228,14 @@
},
{
"cell_type": "code",
- "execution_count": 70,
+ "execution_count": 134,
"outputs": [
{
"data": {
- "text/plain": " State Male GeneralHealth PhysicalHealthDays \\\n339824 South Dakota 0.0 3.0 3.0 \n127927 Kansas 0.0 3.0 30.0 \n362523 Utah 1.0 5.0 0.0 \n183687 Michigan 1.0 3.0 0.0 \n191905 Michigan 0.0 4.0 0.0 \n\n MentalHealthDays LastCheckupTime \\\n339824 21.0 Within past year (anytime less than 12 months ... \n127927 0.0 Within past year (anytime less than 12 months ... \n362523 0.0 Within past year (anytime less than 12 months ... \n183687 7.0 Within past year (anytime less than 12 months ... \n191905 0.0 Within past year (anytime less than 12 months ... \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack ... \\\n339824 1.0 8.0 2.0 0.0 ... \n127927 1.0 10.0 1.0 0.0 ... \n362523 1.0 7.0 1.0 0.0 ... \n183687 1.0 8.0 0.0 0.0 ... \n191905 1.0 7.0 0.0 0.0 ... \n\n HeightInMeters WeightInKilograms BMI AlcoholDrinkers HIVTesting \\\n339824 1.60 52.16 20.37 0.0 1.0 \n127927 1.68 97.52 34.70 0.0 0.0 \n362523 1.83 113.85 34.04 0.0 0.0 \n183687 1.78 83.91 26.54 1.0 0.0 \n191905 1.57 68.04 27.44 1.0 1.0 \n\n FluVaxLast12 PneumoVaxEver TetanusLast10Tdap HighRiskLastYear \\\n339824 1.0 1.0 1.0 0.0 \n127927 1.0 1.0 NaN 0.0 \n362523 0.0 0.0 1.0 0.0 \n183687 1.0 1.0 1.0 0.0 \n191905 0.0 1.0 1.0 0.0 \n\n CovidPos \n339824 0.0 \n127927 0.0 \n362523 1.0 \n183687 0.0 \n191905 0.0 \n\n[5 rows x 40 columns]",
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\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 339824 \n South Dakota \n 0.0 \n 3.0 \n 3.0 \n 21.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 8.0 \n 2.0 \n 0.0 \n ... \n 1.60 \n 52.16 \n 20.37 \n 0.0 \n 1.0 \n 1.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 127927 \n Kansas \n 0.0 \n 3.0 \n 30.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 10.0 \n 1.0 \n 0.0 \n ... \n 1.68 \n 97.52 \n 34.70 \n 0.0 \n 0.0 \n 1.0 \n 1.0 \n NaN \n 0.0 \n 0.0 \n \n \n 362523 \n Utah \n 1.0 \n 5.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 7.0 \n 1.0 \n 0.0 \n ... \n 1.83 \n 113.85 \n 34.04 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 1.0 \n 0.0 \n 1.0 \n \n \n 183687 \n Michigan \n 1.0 \n 3.0 \n 0.0 \n 7.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 8.0 \n 0.0 \n 0.0 \n ... \n 1.78 \n 83.91 \n 26.54 \n 1.0 \n 0.0 \n 1.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 191905 \n Michigan \n 0.0 \n 4.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 7.0 \n 0.0 \n 0.0 \n ... \n 1.57 \n 68.04 \n 27.44 \n 1.0 \n 1.0 \n 0.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n
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5 rows × 40 columns
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+ "text/plain": " State Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\n166151 Maryland 1.0 3.0 0.0 0.0 \n359753 Texas 1.0 3.0 0.0 0.0 \n286723 Ohio 1.0 2.0 2.0 0.0 \n305100 Oklahoma 1.0 4.0 0.0 0.0 \n199077 Minnesota 0.0 5.0 0.0 0.0 \n\n LastCheckupTime PhysicalActivities \\\n166151 Within past 2 years (1 year but less than 2 ye... 1.0 \n359753 Unknown 0.0 \n286723 Within past year (anytime less than 12 months ... 0.0 \n305100 Within past year (anytime less than 12 months ... 1.0 \n199077 Within past year (anytime less than 12 months ... 0.0 \n\n SleepHours RemovedTeeth HadHeartAttack ... HeightInMeters \\\n166151 7.0 0.0 0.0 ... 1.78 \n359753 8.0 0.0 0.0 ... 1.60 \n286723 8.0 3.0 0.0 ... 1.75 \n305100 7.0 0.0 0.0 ... 1.80 \n199077 8.0 1.0 0.0 ... 1.52 \n\n WeightInKilograms BMI AlcoholDrinkers HIVTesting FluVaxLast12 \\\n166151 90.72 28.70 1.0 0.0 0.0 \n359753 77.11 30.12 0.0 0.0 0.0 \n286723 80.29 26.14 NaN NaN NaN \n305100 97.52 29.99 NaN NaN NaN \n199077 67.13 28.90 1.0 1.0 0.0 \n\n PneumoVaxEver TetanusLast10Tdap HighRiskLastYear CovidPos \n166151 1.0 1.0 0.0 0.0 \n359753 0.0 1.0 0.0 0.0 \n286723 NaN NaN NaN NaN \n305100 NaN NaN NaN NaN \n199077 0.0 NaN 0.0 1.0 \n\n[5 rows x 40 columns]",
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\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 166151 \n Maryland \n 1.0 \n 3.0 \n 0.0 \n 0.0 \n Within past 2 years (1 year but less than 2 ye... \n 1.0 \n 7.0 \n 0.0 \n 0.0 \n ... \n 1.78 \n 90.72 \n 28.70 \n 1.0 \n 0.0 \n 0.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 359753 \n Texas \n 1.0 \n 3.0 \n 0.0 \n 0.0 \n Unknown \n 0.0 \n 8.0 \n 0.0 \n 0.0 \n ... \n 1.60 \n 77.11 \n 30.12 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 1.0 \n 0.0 \n 0.0 \n \n \n 286723 \n Ohio \n 1.0 \n 2.0 \n 2.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 8.0 \n 3.0 \n 0.0 \n ... \n 1.75 \n 80.29 \n 26.14 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 305100 \n Oklahoma \n 1.0 \n 4.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 7.0 \n 0.0 \n 0.0 \n ... \n 1.80 \n 97.52 \n 29.99 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 199077 \n Minnesota \n 0.0 \n 5.0 \n 0.0 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 8.0 \n 1.0 \n 0.0 \n ... \n 1.52 \n 67.13 \n 28.90 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n NaN \n 0.0 \n 1.0 \n \n \n
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5 rows × 40 columns
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},
- "execution_count": 70,
+ "execution_count": 134,
"metadata": {},
"output_type": "execute_result"
}
@@ -1287,14 +1249,14 @@
},
{
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+ "execution_count": 135,
"outputs": [
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- "text/plain": " State Male GeneralHealth PhysicalHealthDays \\\n339824 South Dakota 0.0 0.50 0.1 \n127927 Kansas 0.0 0.50 1.0 \n362523 Utah 1.0 1.00 0.0 \n183687 Michigan 1.0 0.50 0.0 \n191905 Michigan 0.0 0.75 0.0 \n\n MentalHealthDays LastCheckupTime \\\n339824 0.700000 Within past year (anytime less than 12 months ... \n127927 0.000000 Within past year (anytime less than 12 months ... \n362523 0.000000 Within past year (anytime less than 12 months ... \n183687 0.233333 Within past year (anytime less than 12 months ... \n191905 0.000000 Within past year (anytime less than 12 months ... \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack ... \\\n339824 1.0 0.304348 0.666667 0.0 ... \n127927 1.0 0.391304 0.333333 0.0 ... \n362523 1.0 0.260870 0.333333 0.0 ... \n183687 1.0 0.304348 0.000000 0.0 ... \n191905 1.0 0.260870 0.000000 0.0 ... \n\n HeightInMeters WeightInKilograms BMI AlcoholDrinkers \\\n339824 0.482517 0.110156 0.097513 0.0 \n127927 0.538462 0.279650 0.264860 0.0 \n362523 0.643357 0.340670 0.257153 0.0 \n183687 0.608392 0.228795 0.169567 1.0 \n191905 0.461538 0.169494 0.180077 1.0 \n\n HIVTesting FluVaxLast12 PneumoVaxEver TetanusLast10Tdap \\\n339824 1.0 1.0 1.0 0.0 \n127927 0.0 1.0 1.0 NaN \n362523 0.0 0.0 0.0 0.0 \n183687 0.0 1.0 1.0 0.0 \n191905 1.0 0.0 1.0 0.0 \n\n HighRiskLastYear CovidPos \n339824 0.0 0.0 \n127927 0.0 0.0 \n362523 0.0 1.0 \n183687 0.0 0.0 \n191905 0.0 0.0 \n\n[5 rows x 40 columns]",
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\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 339824 \n South Dakota \n 0.0 \n 0.50 \n 0.1 \n 0.700000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.304348 \n 0.666667 \n 0.0 \n ... \n 0.482517 \n 0.110156 \n 0.097513 \n 0.0 \n 1.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 127927 \n Kansas \n 0.0 \n 0.50 \n 1.0 \n 0.000000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.391304 \n 0.333333 \n 0.0 \n ... \n 0.538462 \n 0.279650 \n 0.264860 \n 0.0 \n 0.0 \n 1.0 \n 1.0 \n NaN \n 0.0 \n 0.0 \n \n \n 362523 \n Utah \n 1.0 \n 1.00 \n 0.0 \n 0.000000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.260870 \n 0.333333 \n 0.0 \n ... \n 0.643357 \n 0.340670 \n 0.257153 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 1.0 \n \n \n 183687 \n Michigan \n 1.0 \n 0.50 \n 0.0 \n 0.233333 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.304348 \n 0.000000 \n 0.0 \n ... \n 0.608392 \n 0.228795 \n 0.169567 \n 1.0 \n 0.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 191905 \n Michigan \n 0.0 \n 0.75 \n 0.0 \n 0.000000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.461538 \n 0.169494 \n 0.180077 \n 1.0 \n 1.0 \n 0.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n
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5 rows × 40 columns
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+ "text/plain": " State Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\n166151 Maryland 1.0 0.50 0.000000 0.0 \n359753 Texas 1.0 0.50 0.000000 0.0 \n286723 Ohio 1.0 0.25 0.066667 0.0 \n305100 Oklahoma 1.0 0.75 0.000000 0.0 \n199077 Minnesota 0.0 1.00 0.000000 0.0 \n\n LastCheckupTime PhysicalActivities \\\n166151 Within past 2 years (1 year but less than 2 ye... 1.0 \n359753 Unknown 0.0 \n286723 Within past year (anytime less than 12 months ... 0.0 \n305100 Within past year (anytime less than 12 months ... 1.0 \n199077 Within past year (anytime less than 12 months ... 0.0 \n\n SleepHours RemovedTeeth HadHeartAttack ... HeightInMeters \\\n166151 0.260870 0.000000 0.0 ... 0.654135 \n359753 0.304348 0.000000 0.0 ... 0.518797 \n286723 0.304348 1.000000 0.0 ... 0.631579 \n305100 0.260870 0.000000 0.0 ... 0.669173 \n199077 0.304348 0.333333 0.0 ... 0.458647 \n\n WeightInKilograms BMI AlcoholDrinkers HIVTesting \\\n166151 0.254241 0.198737 1.0 0.0 \n359753 0.203385 0.215986 0.0 0.0 \n286723 0.215268 0.167638 NaN NaN \n305100 0.279650 0.214407 NaN NaN \n199077 0.166094 0.201166 1.0 1.0 \n\n FluVaxLast12 PneumoVaxEver TetanusLast10Tdap HighRiskLastYear \\\n166151 0.0 1.0 0.0 0.0 \n359753 0.0 0.0 0.0 0.0 \n286723 NaN NaN NaN NaN \n305100 NaN NaN NaN NaN \n199077 0.0 0.0 NaN 0.0 \n\n CovidPos \n166151 0.0 \n359753 0.0 \n286723 NaN \n305100 NaN \n199077 1.0 \n\n[5 rows x 40 columns]",
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\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 166151 \n Maryland \n 1.0 \n 0.50 \n 0.000000 \n 0.0 \n Within past 2 years (1 year but less than 2 ye... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.654135 \n 0.254241 \n 0.198737 \n 1.0 \n 0.0 \n 0.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 359753 \n Texas \n 1.0 \n 0.50 \n 0.000000 \n 0.0 \n Unknown \n 0.0 \n 0.304348 \n 0.000000 \n 0.0 \n ... \n 0.518797 \n 0.203385 \n 0.215986 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 286723 \n Ohio \n 1.0 \n 0.25 \n 0.066667 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 0.304348 \n 1.000000 \n 0.0 \n ... \n 0.631579 \n 0.215268 \n 0.167638 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 305100 \n Oklahoma \n 1.0 \n 0.75 \n 0.000000 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.669173 \n 0.279650 \n 0.214407 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 199077 \n Minnesota \n 0.0 \n 1.00 \n 0.000000 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 0.304348 \n 0.333333 \n 0.0 \n ... \n 0.458647 \n 0.166094 \n 0.201166 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n NaN \n 0.0 \n 1.0 \n \n \n
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5 rows × 40 columns
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+ "execution_count": 135,
"metadata": {},
"output_type": "execute_result"
}
@@ -1322,7 +1284,7 @@
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+ "execution_count": 136,
"outputs": [
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"name": "stdout",
@@ -1343,14 +1305,14 @@
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{
"cell_type": "code",
- "execution_count": 73,
+ "execution_count": 137,
"outputs": [
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"data": {
- "text/plain": " State Male GeneralHealth PhysicalHealthDays \\\n339824 South Dakota 0.0 0.50 0.1 \n127927 Kansas 0.0 0.50 1.0 \n362523 Utah 1.0 1.00 0.0 \n183687 Michigan 1.0 0.50 0.0 \n191905 Michigan 0.0 0.75 0.0 \n\n MentalHealthDays LastCheckupTime \\\n339824 0.700000 Within past year (anytime less than 12 months ... \n127927 0.000000 Within past year (anytime less than 12 months ... \n362523 0.000000 Within past year (anytime less than 12 months ... \n183687 0.233333 Within past year (anytime less than 12 months ... \n191905 0.000000 Within past year (anytime less than 12 months ... \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack ... \\\n339824 1.0 0.304348 0.666667 0.0 ... \n127927 1.0 0.391304 0.333333 0.0 ... \n362523 1.0 0.260870 0.333333 0.0 ... \n183687 1.0 0.304348 0.000000 0.0 ... \n191905 1.0 0.260870 0.000000 0.0 ... \n\n HeightInMeters WeightInKilograms BMI AlcoholDrinkers \\\n339824 0.482517 0.110156 0.097513 0.0 \n127927 0.538462 0.279650 0.264860 0.0 \n362523 0.643357 0.340670 0.257153 0.0 \n183687 0.608392 0.228795 0.169567 1.0 \n191905 0.461538 0.169494 0.180077 1.0 \n\n HIVTesting FluVaxLast12 PneumoVaxEver TetanusLast10Tdap \\\n339824 1.0 1.0 1.0 0.0 \n127927 0.0 1.0 1.0 NaN \n362523 0.0 0.0 0.0 0.0 \n183687 0.0 1.0 1.0 0.0 \n191905 1.0 0.0 1.0 0.0 \n\n HighRiskLastYear CovidPos \n339824 0.0 0.0 \n127927 0.0 0.0 \n362523 0.0 1.0 \n183687 0.0 0.0 \n191905 0.0 0.0 \n\n[5 rows x 40 columns]",
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\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 339824 \n South Dakota \n 0.0 \n 0.50 \n 0.1 \n 0.700000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.304348 \n 0.666667 \n 0.0 \n ... \n 0.482517 \n 0.110156 \n 0.097513 \n 0.0 \n 1.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 127927 \n Kansas \n 0.0 \n 0.50 \n 1.0 \n 0.000000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.391304 \n 0.333333 \n 0.0 \n ... \n 0.538462 \n 0.279650 \n 0.264860 \n 0.0 \n 0.0 \n 1.0 \n 1.0 \n NaN \n 0.0 \n 0.0 \n \n \n 362523 \n Utah \n 1.0 \n 1.00 \n 0.0 \n 0.000000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.260870 \n 0.333333 \n 0.0 \n ... \n 0.643357 \n 0.340670 \n 0.257153 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 1.0 \n \n \n 183687 \n Michigan \n 1.0 \n 0.50 \n 0.0 \n 0.233333 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.304348 \n 0.000000 \n 0.0 \n ... \n 0.608392 \n 0.228795 \n 0.169567 \n 1.0 \n 0.0 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 191905 \n Michigan \n 0.0 \n 0.75 \n 0.0 \n 0.000000 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.461538 \n 0.169494 \n 0.180077 \n 1.0 \n 1.0 \n 0.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n
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5 rows × 40 columns
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+ "text/plain": " State Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\n166151 Maryland 1.0 0.50 0.000000 0.0 \n359753 Texas 1.0 0.50 0.000000 0.0 \n286723 Ohio 1.0 0.25 0.066667 0.0 \n305100 Oklahoma 1.0 0.75 0.000000 0.0 \n199077 Minnesota 0.0 1.00 0.000000 0.0 \n\n LastCheckupTime PhysicalActivities \\\n166151 Within past 2 years (1 year but less than 2 ye... 1.0 \n359753 Unknown 0.0 \n286723 Within past year (anytime less than 12 months ... 0.0 \n305100 Within past year (anytime less than 12 months ... 1.0 \n199077 Within past year (anytime less than 12 months ... 0.0 \n\n SleepHours RemovedTeeth HadHeartAttack ... HeightInMeters \\\n166151 0.260870 0.000000 0.0 ... 0.654135 \n359753 0.304348 0.000000 0.0 ... 0.518797 \n286723 0.304348 1.000000 0.0 ... 0.631579 \n305100 0.260870 0.000000 0.0 ... 0.669173 \n199077 0.304348 0.333333 0.0 ... 0.458647 \n\n WeightInKilograms BMI AlcoholDrinkers HIVTesting \\\n166151 0.254241 0.198737 1.0 0.0 \n359753 0.203385 0.215986 0.0 0.0 \n286723 0.215268 0.167638 NaN NaN \n305100 0.279650 0.214407 NaN NaN \n199077 0.166094 0.201166 1.0 1.0 \n\n FluVaxLast12 PneumoVaxEver TetanusLast10Tdap HighRiskLastYear \\\n166151 0.0 1.0 0.0 0.0 \n359753 0.0 0.0 0.0 0.0 \n286723 NaN NaN NaN NaN \n305100 NaN NaN NaN NaN \n199077 0.0 0.0 NaN 0.0 \n\n CovidPos \n166151 0.0 \n359753 0.0 \n286723 NaN \n305100 NaN \n199077 1.0 \n\n[5 rows x 40 columns]",
+ "text/html": "\n\n
\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 166151 \n Maryland \n 1.0 \n 0.50 \n 0.000000 \n 0.0 \n Within past 2 years (1 year but less than 2 ye... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.654135 \n 0.254241 \n 0.198737 \n 1.0 \n 0.0 \n 0.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 359753 \n Texas \n 1.0 \n 0.50 \n 0.000000 \n 0.0 \n Unknown \n 0.0 \n 0.304348 \n 0.000000 \n 0.0 \n ... \n 0.518797 \n 0.203385 \n 0.215986 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 286723 \n Ohio \n 1.0 \n 0.25 \n 0.066667 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 0.304348 \n 1.000000 \n 0.0 \n ... \n 0.631579 \n 0.215268 \n 0.167638 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 305100 \n Oklahoma \n 1.0 \n 0.75 \n 0.000000 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.669173 \n 0.279650 \n 0.214407 \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n NaN \n \n \n 199077 \n Minnesota \n 0.0 \n 1.00 \n 0.000000 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 0.304348 \n 0.333333 \n 0.0 \n ... \n 0.458647 \n 0.166094 \n 0.201166 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n NaN \n 0.0 \n 1.0 \n \n \n
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},
- "execution_count": 73,
+ "execution_count": 137,
"metadata": {},
"output_type": "execute_result"
}
@@ -1373,28 +1335,13 @@
},
{
"cell_type": "code",
- "execution_count": 74,
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\Adrian\\AppData\\Local\\Temp\\ipykernel_18732\\896322512.py:4: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n",
- " test.fillna(test.median(),inplace=True)\n",
- "C:\\Users\\Adrian\\AppData\\Local\\Temp\\ipykernel_18732\\896322512.py:5: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n",
- " train.fillna(train.median(),inplace=True)\n",
- "C:\\Users\\Adrian\\AppData\\Local\\Temp\\ipykernel_18732\\896322512.py:6: FutureWarning: Dropping of nuisance columns in DataFrame reductions (with 'numeric_only=None') is deprecated; in a future version this will raise TypeError. Select only valid columns before calling the reduction.\n",
- " valid.fillna(valid.median(),inplace=True)\n"
- ]
- }
- ],
+ "execution_count": 138,
+ "outputs": [],
"source": [
- "#test.dropna(inplace=True)\n",
- "#train.dropna(inplace=True)\n",
- "#valid.dropna(inplace=True)\n",
- "test.fillna(test.median(),inplace=True)\n",
- "train.fillna(train.median(),inplace=True)\n",
- "valid.fillna(valid.median(),inplace=True)"
+ "numeric_columns = train.select_dtypes(include=['number']).columns\n",
+ "test[numeric_columns] = test[numeric_columns].fillna(test[numeric_columns].median().iloc[0])\n",
+ "train[numeric_columns] = train[numeric_columns].fillna(train[numeric_columns].median().iloc[0])\n",
+ "valid[numeric_columns] = valid[numeric_columns].fillna(valid[numeric_columns].iloc[0])"
],
"metadata": {
"collapsed": false
@@ -1402,14 +1349,14 @@
},
{
"cell_type": "code",
- "execution_count": 75,
+ "execution_count": 139,
"outputs": [
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- "text/plain": " State Male GeneralHealth PhysicalHealthDays \\\n339824 South Dakota 0.0 0.50 0.1 \n127927 Kansas 0.0 0.50 1.0 \n362523 Utah 1.0 1.00 0.0 \n183687 Michigan 1.0 0.50 0.0 \n191905 Michigan 0.0 0.75 0.0 \n\n MentalHealthDays LastCheckupTime \\\n339824 0.700000 Within past year (anytime less than 12 months ... \n127927 0.000000 Within past year (anytime less than 12 months ... \n362523 0.000000 Within past year (anytime less than 12 months ... \n183687 0.233333 Within past year (anytime less than 12 months ... \n191905 0.000000 Within past year (anytime less than 12 months ... \n\n PhysicalActivities SleepHours RemovedTeeth HadHeartAttack ... \\\n339824 1.0 0.304348 0.666667 0.0 ... \n127927 1.0 0.391304 0.333333 0.0 ... \n362523 1.0 0.260870 0.333333 0.0 ... \n183687 1.0 0.304348 0.000000 0.0 ... \n191905 1.0 0.260870 0.000000 0.0 ... \n\n HeightInMeters WeightInKilograms BMI AlcoholDrinkers \\\n339824 0.482517 0.110156 0.097513 0.0 \n127927 0.538462 0.279650 0.264860 0.0 \n362523 0.643357 0.340670 0.257153 0.0 \n183687 0.608392 0.228795 0.169567 1.0 \n191905 0.461538 0.169494 0.180077 1.0 \n\n HIVTesting FluVaxLast12 PneumoVaxEver TetanusLast10Tdap \\\n339824 1.0 1.0 1.0 0.0 \n127927 0.0 1.0 1.0 0.0 \n362523 0.0 0.0 0.0 0.0 \n183687 0.0 1.0 1.0 0.0 \n191905 1.0 0.0 1.0 0.0 \n\n HighRiskLastYear CovidPos \n339824 0.0 0.0 \n127927 0.0 0.0 \n362523 0.0 1.0 \n183687 0.0 0.0 \n191905 0.0 0.0 \n\n[5 rows x 40 columns]",
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5 rows × 40 columns
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+ "text/plain": " State Male GeneralHealth PhysicalHealthDays MentalHealthDays \\\n166151 Maryland 1.0 0.50 0.000000 0.0 \n359753 Texas 1.0 0.50 0.000000 0.0 \n286723 Ohio 1.0 0.25 0.066667 0.0 \n305100 Oklahoma 1.0 0.75 0.000000 0.0 \n199077 Minnesota 0.0 1.00 0.000000 0.0 \n\n LastCheckupTime PhysicalActivities \\\n166151 Within past 2 years (1 year but less than 2 ye... 1.0 \n359753 Unknown 0.0 \n286723 Within past year (anytime less than 12 months ... 0.0 \n305100 Within past year (anytime less than 12 months ... 1.0 \n199077 Within past year (anytime less than 12 months ... 0.0 \n\n SleepHours RemovedTeeth HadHeartAttack ... HeightInMeters \\\n166151 0.260870 0.000000 0.0 ... 0.654135 \n359753 0.304348 0.000000 0.0 ... 0.518797 \n286723 0.304348 1.000000 0.0 ... 0.631579 \n305100 0.260870 0.000000 0.0 ... 0.669173 \n199077 0.304348 0.333333 0.0 ... 0.458647 \n\n WeightInKilograms BMI AlcoholDrinkers HIVTesting \\\n166151 0.254241 0.198737 1.0 0.0 \n359753 0.203385 0.215986 0.0 0.0 \n286723 0.215268 0.167638 0.0 0.0 \n305100 0.279650 0.214407 0.0 0.0 \n199077 0.166094 0.201166 1.0 1.0 \n\n FluVaxLast12 PneumoVaxEver TetanusLast10Tdap HighRiskLastYear \\\n166151 0.0 1.0 0.0 0.0 \n359753 0.0 0.0 0.0 0.0 \n286723 0.0 0.0 0.0 0.0 \n305100 0.0 0.0 0.0 0.0 \n199077 0.0 0.0 0.0 0.0 \n\n CovidPos \n166151 0.0 \n359753 0.0 \n286723 0.0 \n305100 0.0 \n199077 1.0 \n\n[5 rows x 40 columns]",
+ "text/html": "\n\n
\n \n \n \n State \n Male \n GeneralHealth \n PhysicalHealthDays \n MentalHealthDays \n LastCheckupTime \n PhysicalActivities \n SleepHours \n RemovedTeeth \n HadHeartAttack \n ... \n HeightInMeters \n WeightInKilograms \n BMI \n AlcoholDrinkers \n HIVTesting \n FluVaxLast12 \n PneumoVaxEver \n TetanusLast10Tdap \n HighRiskLastYear \n CovidPos \n \n \n \n \n 166151 \n Maryland \n 1.0 \n 0.50 \n 0.000000 \n 0.0 \n Within past 2 years (1 year but less than 2 ye... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.654135 \n 0.254241 \n 0.198737 \n 1.0 \n 0.0 \n 0.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 359753 \n Texas \n 1.0 \n 0.50 \n 0.000000 \n 0.0 \n Unknown \n 0.0 \n 0.304348 \n 0.000000 \n 0.0 \n ... \n 0.518797 \n 0.203385 \n 0.215986 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 286723 \n Ohio \n 1.0 \n 0.25 \n 0.066667 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 0.304348 \n 1.000000 \n 0.0 \n ... \n 0.631579 \n 0.215268 \n 0.167638 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 305100 \n Oklahoma \n 1.0 \n 0.75 \n 0.000000 \n 0.0 \n Within past year (anytime less than 12 months ... \n 1.0 \n 0.260870 \n 0.000000 \n 0.0 \n ... \n 0.669173 \n 0.279650 \n 0.214407 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n \n \n 199077 \n Minnesota \n 0.0 \n 1.00 \n 0.000000 \n 0.0 \n Within past year (anytime less than 12 months ... \n 0.0 \n 0.304348 \n 0.333333 \n 0.0 \n ... \n 0.458647 \n 0.166094 \n 0.201166 \n 1.0 \n 1.0 \n 0.0 \n 0.0 \n 0.0 \n 0.0 \n 1.0 \n \n \n
\n
5 rows × 40 columns
\n
"
},
- "execution_count": 75,
+ "execution_count": 139,
"metadata": {},
"output_type": "execute_result"
}
@@ -1433,13 +1380,13 @@
},
{
"cell_type": "code",
- "execution_count": 76,
+ "execution_count": 140,
"outputs": [
{
"data": {
- "text/plain": "0.0 42796\n1.0 1717\nName: HighRiskLastYear, dtype: int64"
+ "text/plain": "0.0 42786\n1.0 1727\nName: HighRiskLastYear, dtype: int64"
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- "execution_count": 76,
+ "execution_count": 140,
"metadata": {},
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}
@@ -1453,13 +1400,13 @@
},
{
"cell_type": "code",
- "execution_count": 77,
+ "execution_count": 141,
"outputs": [
{
"data": {
"text/plain": "0"
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- "execution_count": 77,
+ "execution_count": 141,
"metadata": {},
"output_type": "execute_result"
}
@@ -1482,14 +1429,14 @@
},
{
"cell_type": "code",
- "execution_count": 78,
+ "execution_count": 142,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
- "Int64Index: 44513 entries, 339824 to 52161\n",
+ "Int64Index: 44513 entries, 166151 to 306609\n",
"Data columns (total 40 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
@@ -1547,59 +1494,59 @@
},
{
"cell_type": "code",
- "execution_count": 79,
+ "execution_count": 143,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
- "RangeIndex: 676777 entries, 0 to 676776\n",
+ "RangeIndex: 676361 entries, 0 to 676360\n",
"Data columns (total 40 columns):\n",
" # Column Non-Null Count Dtype \n",
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- " 2 GeneralHealth 676777 non-null float64 \n",
- " 3 PhysicalHealthDays 676777 non-null float64 \n",
- " 4 MentalHealthDays 676777 non-null float64 \n",
- " 5 LastCheckupTime 676777 non-null category\n",
- " 6 PhysicalActivities 676777 non-null float64 \n",
- " 7 SleepHours 676777 non-null float64 \n",
- " 8 RemovedTeeth 676777 non-null float64 \n",
- " 9 HadHeartAttack 676777 non-null float64 \n",
- " 10 HadAngina 676777 non-null float64 \n",
- " 11 HadStroke 676777 non-null float64 \n",
- " 12 HadAsthma 676777 non-null float64 \n",
- " 13 HadSkinCancer 676777 non-null float64 \n",
- " 14 HadCOPD 676777 non-null float64 \n",
- " 15 HadDepressiveDisorder 676777 non-null float64 \n",
- " 16 HadKidneyDisease 676777 non-null float64 \n",
- " 17 HadArthritis 676777 non-null float64 \n",
- " 18 HadDiabetes 676777 non-null float64 \n",
- " 19 DeafOrHardOfHearing 676777 non-null float64 \n",
- " 20 BlindOrVisionDifficulty 676777 non-null float64 \n",
- " 21 DifficultyConcentrating 676777 non-null float64 \n",
- " 22 DifficultyWalking 676777 non-null float64 \n",
- " 23 DifficultyDressingBathing 676777 non-null float64 \n",
- " 24 DifficultyErrands 676777 non-null float64 \n",
- " 25 SmokerStatus 676777 non-null float64 \n",
- " 26 ECigaretteUsage 676777 non-null float64 \n",
- " 27 ChestScan 676777 non-null float64 \n",
- " 28 RaceEthnicityCategory 676777 non-null category\n",
- " 29 AgeCategory 676777 non-null category\n",
- " 30 HeightInMeters 676777 non-null float64 \n",
- " 31 WeightInKilograms 676777 non-null float64 \n",
- " 32 BMI 676777 non-null float64 \n",
- " 33 AlcoholDrinkers 676777 non-null float64 \n",
- " 34 HIVTesting 676777 non-null float64 \n",
- " 35 FluVaxLast12 676777 non-null float64 \n",
- " 36 PneumoVaxEver 676777 non-null float64 \n",
- " 37 TetanusLast10Tdap 676777 non-null float64 \n",
- " 38 HighRiskLastYear 676777 non-null float64 \n",
- " 39 CovidPos 676777 non-null float64 \n",
+ " 0 State 676361 non-null category\n",
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+ " 2 GeneralHealth 676361 non-null float64 \n",
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+ " 5 LastCheckupTime 676361 non-null category\n",
+ " 6 PhysicalActivities 676361 non-null float64 \n",
+ " 7 SleepHours 676361 non-null float64 \n",
+ " 8 RemovedTeeth 676361 non-null float64 \n",
+ " 9 HadHeartAttack 676361 non-null float64 \n",
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+ " 13 HadSkinCancer 676361 non-null float64 \n",
+ " 14 HadCOPD 676361 non-null float64 \n",
+ " 15 HadDepressiveDisorder 676361 non-null float64 \n",
+ " 16 HadKidneyDisease 676361 non-null float64 \n",
+ " 17 HadArthritis 676361 non-null float64 \n",
+ " 18 HadDiabetes 676361 non-null float64 \n",
+ " 19 DeafOrHardOfHearing 676361 non-null float64 \n",
+ " 20 BlindOrVisionDifficulty 676361 non-null float64 \n",
+ " 21 DifficultyConcentrating 676361 non-null float64 \n",
+ " 22 DifficultyWalking 676361 non-null float64 \n",
+ " 23 DifficultyDressingBathing 676361 non-null float64 \n",
+ " 24 DifficultyErrands 676361 non-null float64 \n",
+ " 25 SmokerStatus 676361 non-null float64 \n",
+ " 26 ECigaretteUsage 676361 non-null float64 \n",
+ " 27 ChestScan 676361 non-null float64 \n",
+ " 28 RaceEthnicityCategory 676361 non-null category\n",
+ " 29 AgeCategory 676361 non-null category\n",
+ " 30 HeightInMeters 676361 non-null float64 \n",
+ " 31 WeightInKilograms 676361 non-null float64 \n",
+ " 32 BMI 676361 non-null float64 \n",
+ " 33 AlcoholDrinkers 676361 non-null float64 \n",
+ " 34 HIVTesting 676361 non-null float64 \n",
+ " 35 FluVaxLast12 676361 non-null float64 \n",
+ " 36 PneumoVaxEver 676361 non-null float64 \n",
+ " 37 TetanusLast10Tdap 676361 non-null float64 \n",
+ " 38 HighRiskLastYear 676361 non-null float64 \n",
+ " 39 CovidPos 676361 non-null float64 \n",
"dtypes: category(4), float64(36)\n",
- "memory usage: 188.5 MB\n"
+ "memory usage: 188.4 MB\n"
]
}
],
@@ -1612,14 +1559,14 @@
},
{
"cell_type": "code",
- "execution_count": 80,
+ "execution_count": 144,
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
- "Int64Index: 44514 entries, 66965 to 224311\n",
+ "Int64Index: 44514 entries, 399706 to 77011\n",
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@@ -1659,7 +1606,7 @@
" 33 AlcoholDrinkers 44514 non-null float64 \n",
" 34 HIVTesting 44514 non-null float64 \n",
" 35 FluVaxLast12 44514 non-null float64 \n",
- " 36 PneumoVaxEver 44514 non-null float64 \n",
+ " 36 PneumoVaxEver 36781 non-null float64 \n",
" 37 TetanusLast10Tdap 44514 non-null float64 \n",
" 38 HighRiskLastYear 44514 non-null float64 \n",
" 39 CovidPos 44514 non-null float64 \n",
@@ -1677,7 +1624,7 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 144,
"outputs": [],
"source": [],
"metadata": {