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Richard Zick
RichardZick/
Deviation-Founders
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  1
  
{





  
  

  2
  
 "cells": [





  
  

  3
  
  {





  
  

  4
  
   "cell_type": "code",





  
  

  5
  
   "execution_count": 10,





  
  

  6
  
   "metadata": {},





  
  

  7
  
   "outputs": [],





  
  

  8
  
   "source": [





  
  

  9
  
    "import pandas as pd\n",





  
  

  10
  
    "import numpy as np\n",





  
  

  11
  
    "import matplotlib.pyplot as plt\n",





  
  

  12
  
    "heart_data = pd.read_csv('../heart_data.csv')"





  
  

  13
  
   ]





  
  

  14
  
  },





  
  

  15
  
  {





  
  

  16
  
   "cell_type": "code",





  
  

  17
  
   "execution_count": 11,





  
  

  18
  
   "metadata": {},





  
  

  19
  
   "outputs": [],





  
  

  20
  
   "source": [





  
  

  21
  
    "heart_data['HeartDisease'] =  heart_data['HeartDisease']\n",





  
  

  22
  
    "allactive = heart_data['PhysicalActivity']\n",





  
  

  23
  
    "Active = heart_data[heart_data['PhysicalActivity']=='Yes']\n",





  
  

  24
  
    "notActive = heart_data[heart_data['PhysicalActivity']=='No']\n"





  
  

  25
  
   ]





  
  

  26
  
  },





  
  

  27
  
  {





  
  

  28
  
   "cell_type": "code",





  
  

  29
  
   "execution_count": 12,





  
  

  30
  
   "metadata": {},





  
  

  31
  
   "outputs": [





  
  

  32
  
    {





  
  

  33
  
     "data": {





  
  

  34
  
      "text/plain": [





  
  

  35
  
       "count     319795\n",





  
  

  36
  
       "unique         2\n",





  
  

  37
  
       "top          Yes\n",





  
  

  38
  
       "freq      247957\n",





  
  

  39
  
       "Name: PhysicalActivity, dtype: object"





  
  

  40
  
      ]





  
  

  41
  
     },





  
  

  42
  
     "execution_count": 12,





  
  

  43
  
     "metadata": {},





  
  

  44
  
     "output_type": "execute_result"





  
  

  45
  
    }





  
  

  46
  
   ],





  
  

  47
  
   "source": [





  
  

  48
  
    "allactive.describe()"





  
  

  49
  
   ]





  
  

  50
  
  },





  
  

  51
  
  {





  
  

  52
  
   "cell_type": "code",





  
  

  53
  
   "execution_count": 13,





  
  

  54
  
   "metadata": {},





  
  

  55
  
   "outputs": [





  
  

  56
  
    {





  
  

  57
  
     "data": {





  
  

  58
  
      "text/html": [





  
  

  59
  
       "<div>\n",





  
  

  60
  
       "<style scoped>\n",





  
  

  61
  
       "    .dataframe tbody tr th:only-of-type {\n",





  
  

  62
  
       "        vertical-align: middle;\n",





  
  

  63
  
       "    }\n",





  
  

  64
  
       "\n",





  
  

  65
  
       "    .dataframe tbody tr th {\n",





  
  

  66
  
       "        vertical-align: top;\n",





  
  

  67
  
       "    }\n",





  
  

  68
  
       "\n",





  
  

  69
  
       "    .dataframe thead th {\n",





  
  

  70
  
       "        text-align: right;\n",





  
  

  71
  
       "    }\n",





  
  

  72
  
       "</style>\n",





  
  

  73
  
       "<table border=\"1\" class=\"dataframe\">\n",





  
  

  74
  
       "  <thead>\n",





  
  

  75
  
       "    <tr style=\"text-align: right;\">\n",





  
  

  76
  
       "      <th></th>\n",





  
  

  77
  
       "      <th>BMI</th>\n",





  
  

  78
  
       "      <th>PhysicalHealth</th>\n",





  
  

  79
  
       "      <th>MentalHealth</th>\n",





  
  

  80
  
       "      <th>SleepTime</th>\n",





  
  

  81
  
       "    </tr>\n",





  
  

  82
  
       "  </thead>\n",





  
  

  83
  
       "  <tbody>\n",





  
  

  84
  
       "    <tr>\n",





  
  

  85
  
       "      <th>count</th>\n",





  
  

  86
  
       "      <td>247957.00000</td>\n",





  
  

  87
  
       "      <td>247957.000000</td>\n",





  
  

  88
  
       "      <td>247957.000000</td>\n",





  
  

  89
  
       "      <td>247957.000000</td>\n",





  
  

  90
  
       "    </tr>\n",





  
  

  91
  
       "    <tr>\n",





  
  

  92
  
       "      <th>mean</th>\n",





  
  

  93
  
       "      <td>27.81011</td>\n",





  
  

  94
  
       "      <td>2.377634</td>\n",





  
  

  95
  
       "      <td>3.488121</td>\n",





  
  

  96
  
       "      <td>7.100050</td>\n",





  
  

  97
  
       "    </tr>\n",





  
  

  98
  
       "    <tr>\n",





  
  

  99
  
       "      <th>std</th>\n",





  
  

  100
  
       "      <td>5.90583</td>\n",





  
  

  101
  
       "      <td>6.479349</td>\n",





  
  

  102
  
       "      <td>7.353138</td>\n",





  
  

  103
  
       "      <td>1.320686</td>\n",





  
  

  104
  
       "    </tr>\n",





  
  

  105
  
       "    <tr>\n",





  
  

  106
  
       "      <th>min</th>\n",





  
  

  107
  
       "      <td>12.02000</td>\n",





  
  

  108
  
       "      <td>0.000000</td>\n",





  
  

  109
  
       "      <td>0.000000</td>\n",





  
  

  110
  
       "      <td>1.000000</td>\n",





  
  

  111
  
       "    </tr>\n",





  
  

  112
  
       "    <tr>\n",





  
  

  113
  
       "      <th>25%</th>\n",





  
  

  114
  
       "      <td>23.74000</td>\n",





  
  

  115
  
       "      <td>0.000000</td>\n",





  
  

  116
  
       "      <td>0.000000</td>\n",





  
  

  117
  
       "      <td>6.000000</td>\n",





  
  

  118
  
       "    </tr>\n",





  
  

  119
  
       "    <tr>\n",





  
  

  120
  
       "      <th>50%</th>\n",





  
  

  121
  
       "      <td>26.79000</td>\n",





  
  

  122
  
       "      <td>0.000000</td>\n",





  
  

  123
  
       "      <td>0.000000</td>\n",





  
  

  124
  
       "      <td>7.000000</td>\n",





  
  

  125
  
       "    </tr>\n",





  
  

  126
  
       "    <tr>\n",





  
  

  127
  
       "      <th>75%</th>\n",





  
  

  128
  
       "      <td>30.79000</td>\n",





  
  

  129
  
       "      <td>1.000000</td>\n",





  
  

  130
  
       "      <td>3.000000</td>\n",





  
  

  131
  
       "      <td>8.000000</td>\n",





  
  

  132
  
       "    </tr>\n",





  
  

  133
  
       "    <tr>\n",





  
  

  134
  
       "      <th>max</th>\n",





  
  

  135
  
       "      <td>94.85000</td>\n",





  
  

  136
  
       "      <td>30.000000</td>\n",





  
  

  137
  
       "      <td>30.000000</td>\n",





  
  

  138
  
       "      <td>24.000000</td>\n",





  
  

  139
  
       "    </tr>\n",





  
  

  140
  
       "  </tbody>\n",





  
  

  141
  
       "</table>\n",





  
  

  142
  
       "</div>"





  
  

  143
  
      ],





  
  

  144
  
      "text/plain": [





  
  

  145
  
       "                BMI  PhysicalHealth   MentalHealth      SleepTime\n",





  
  

  146
  
       "count  247957.00000   247957.000000  247957.000000  247957.000000\n",





  
  

  147
  
       "mean       27.81011        2.377634       3.488121       7.100050\n",





  
  

  148
  
       "std         5.90583        6.479349       7.353138       1.320686\n",





  
  

  149
  
       "min        12.02000        0.000000       0.000000       1.000000\n",





  
  

  150
  
       "25%        23.74000        0.000000       0.000000       6.000000\n",





  
  

  151
  
       "50%        26.79000        0.000000       0.000000       7.000000\n",





  
  

  152
  
       "75%        30.79000        1.000000       3.000000       8.000000\n",





  
  

  153
  
       "max        94.85000       30.000000      30.000000      24.000000"





  
  

  154
  
      ]





  
  

  155
  
     },





  
  

  156
  
     "execution_count": 13,





  
  

  157
  
     "metadata": {},





  
  

  158
  
     "output_type": "execute_result"





  
  

  159
  
    }





  
  

  160
  
   ],





  
  

  161
  
   "source": [





  
  

  162
  
    "Active.describe()"





  
  

  163
  
   ]





  
  

  164
  
  },





  
  

  165
  
  {





  
  

  166
  
   "cell_type": "code",





  
  

  167
  
   "execution_count": 14,





  
  

  168
  
   "metadata": {},





  
  

  169
  
   "outputs": [





  
  

  170
  
    {





  
  

  171
  
     "name": "stdout",





  
  

  172
  
     "output_type": "stream",





  
  

  173
  
     "text": [





  
  

  174
  
      "Percentage of active people that don't have heart disease 92.9467609303226\n",





  
  

  175
  
      "Percentage of active people that have heart disease 7.053239069677404\n"





  
  

  176
  
     ]





  
  

  177
  
    }





  
  

  178
  
   ],





  
  

  179
  
   "source": [





  
  

  180
  
    "print(\"Percentage of active people that don't have heart disease\", 100 * Active[Active[\"HeartDisease\"] == \"No\"].size / Active.size )\n",





  
  

  181
  
    "print(\"Percentage of active people that have heart disease\", 100 * Active[Active[\"HeartDisease\"] == \"Yes\"].size / Active.size )"





  
  

  182
  
   ]





  
  

  183
  
  },





  
  

  184
  
  {





  
  

  185
  
   "cell_type": "code",





  
  

  186
  
   "execution_count": 15,





  
  

  187
  
   "metadata": {},





  
  

  188
  
   "outputs": [





  
  

  189
  
    {





  
  

  190
  
     "data": {





  
  

  191
  
      "text/html": [





  
  

  192
  
       "<div>\n",





  
  

  193
  
       "<style scoped>\n",





  
  

  194
  
       "    .dataframe tbody tr th:only-of-type {\n",





  
  

  195
  
       "        vertical-align: middle;\n",





  
  

  196
  
       "    }\n",





  
  

  197
  
       "\n",





  
  

  198
  
       "    .dataframe tbody tr th {\n",





  
  

  199
  
       "        vertical-align: top;\n",





  
  

  200
  
       "    }\n",





  
  

  201
  
       "\n",





  
  

  202
  
       "    .dataframe thead th {\n",





  
  

  203
  
       "        text-align: right;\n",





  
  

  204
  
       "    }\n",





  
  

  205
  
       "</style>\n",





  
  

  206
  
       "<table border=\"1\" class=\"dataframe\">\n",





  
  

  207
  
       "  <thead>\n",





  
  

  208
  
       "    <tr style=\"text-align: right;\">\n",





  
  

  209
  
       "      <th></th>\n",





  
  

  210
  
       "      <th>BMI</th>\n",





  
  

  211
  
       "      <th>PhysicalHealth</th>\n",





  
  

  212
  
       "      <th>MentalHealth</th>\n",





  
  

  213
  
       "      <th>SleepTime</th>\n",





  
  

  214
  
       "    </tr>\n",





  
  

  215
  
       "  </thead>\n",





  
  

  216
  
       "  <tbody>\n",





  
  

  217
  
       "    <tr>\n",





  
  

  218
  
       "      <th>count</th>\n",





  
  

  219
  
       "      <td>71838.000000</td>\n",





  
  

  220
  
       "      <td>71838.000000</td>\n",





  
  

  221
  
       "      <td>71838.000000</td>\n",





  
  

  222
  
       "      <td>71838.000000</td>\n",





  
  

  223
  
       "    </tr>\n",





  
  

  224
  
       "    <tr>\n",





  
  

  225
  
       "      <th>mean</th>\n",





  
  

  226
  
       "      <td>30.103974</td>\n",





  
  

  227
  
       "      <td>6.802876</td>\n",





  
  

  228
  
       "      <td>5.314374</td>\n",





  
  

  229
  
       "      <td>7.086806</td>\n",





  
  

  230
  
       "    </tr>\n",





  
  

  231
  
       "    <tr>\n",





  
  

  232
  
       "      <th>std</th>\n",





  
  

  233
  
       "      <td>7.441630</td>\n",





  
  

  234
  
       "      <td>11.014781</td>\n",





  
  

  235
  
       "      <td>9.618466</td>\n",





  
  

  236
  
       "      <td>1.777442</td>\n",





  
  

  237
  
       "    </tr>\n",





  
  

  238
  
       "    <tr>\n",





  
  

  239
  
       "      <th>min</th>\n",





  
  

  240
  
       "      <td>12.020000</td>\n",





  
  

  241
  
       "      <td>0.000000</td>\n",





  
  

  242
  
       "      <td>0.000000</td>\n",





  
  

  243
  
       "      <td>1.000000</td>\n",





  
  

  244
  
       "    </tr>\n",





  
  

  245
  
       "    <tr>\n",





  
  

  246
  
       "      <th>25%</th>\n",





  
  

  247
  
       "      <td>25.020000</td>\n",





  
  

  248
  
       "      <td>0.000000</td>\n",





  
  

  249
  
       "      <td>0.000000</td>\n",





  
  

  250
  
       "      <td>6.000000</td>\n",





  
  

  251
  
       "    </tr>\n",





  
  

  252
  
       "    <tr>\n",





  
  

  253
  
       "      <th>50%</th>\n",





  
  

  254
  
       "      <td>29.050000</td>\n",





  
  

  255
  
       "      <td>0.000000</td>\n",





  
  

  256
  
       "      <td>0.000000</td>\n",





  
  

  257
  
       "      <td>7.000000</td>\n",





  
  

  258
  
       "    </tr>\n",





  
  

  259
  
       "    <tr>\n",





  
  

  260
  
       "      <th>75%</th>\n",





  
  

  261
  
       "      <td>33.910000</td>\n",





  
  

  262
  
       "      <td>10.000000</td>\n",





  
  

  263
  
       "      <td>5.000000</td>\n",





  
  

  264
  
       "      <td>8.000000</td>\n",





  
  

  265
  
       "    </tr>\n",





  
  

  266
  
       "    <tr>\n",





  
  

  267
  
       "      <th>max</th>\n",





  
  

  268
  
       "      <td>94.660000</td>\n",





  
  

  269
  
       "      <td>30.000000</td>\n",





  
  

  270
  
       "      <td>30.000000</td>\n",





  
  

  271
  
       "      <td>24.000000</td>\n",





  
  

  272
  
       "    </tr>\n",





  
  

  273
  
       "  </tbody>\n",





  
  

  274
  
       "</table>\n",





  
  

  275
  
       "</div>"





  
  

  276
  
      ],





  
  

  277
  
      "text/plain": [





  
  

  278
  
       "                BMI  PhysicalHealth  MentalHealth     SleepTime\n",





  
  

  279
  
       "count  71838.000000    71838.000000  71838.000000  71838.000000\n",





  
  

  280
  
       "mean      30.103974        6.802876      5.314374      7.086806\n",





  
  

  281
  
       "std        7.441630       11.014781      9.618466      1.777442\n",





  
  

  282
  
       "min       12.020000        0.000000      0.000000      1.000000\n",





  
  

  283
  
       "25%       25.020000        0.000000      0.000000      6.000000\n",





  
  

  284
  
       "50%       29.050000        0.000000      0.000000      7.000000\n",





  
  

  285
  
       "75%       33.910000       10.000000      5.000000      8.000000\n",





  
  

  286
  
       "max       94.660000       30.000000     30.000000     24.000000"





  
  

  287
  
      ]





  
  

  288
  
     },





  
  

  289
  
     "execution_count": 15,





  
  

  290
  
     "metadata": {},





  
  

  291
  
     "output_type": "execute_result"





  
  

  292
  
    }





  
  

  293
  
   ],





  
  

  294
  
   "source": [





  
  

  295
  
    "notActive.describe()"





  
  

  296
  
   ]





  
  

  297
  
  },





  
  

  298
  
  {





  
  

  299
  
   "cell_type": "code",





  
  

  300
  
   "execution_count": 16,





  
  

  301
  
   "metadata": {},





  
  

  302
  
   "outputs": [





  
  

  303
  
    {





  
  

  304
  
     "name": "stdout",





  
  

  305
  
     "output_type": "stream",





  
  

  306
  
     "text": [





  
  

  307
  
      "Percentage of non active people that don't have heart disease 86.24126506862663\n",





  
  

  308
  
      "Percentage of non active people  that have heart disease 13.758734931373368\n"





  
  

  309
  
     ]





  
  

  310
  
    }





  
  

  311
  
   ],





  
  

  312
  
   "source": [





  
  

  313
  
    "print(\"Percentage of non active people that don't have heart disease\", 100 * notActive[notActive[\"HeartDisease\"] == \"No\"].size / notActive.size )\n",





  
  

  314
  
    "print(\"Percentage of non active people  that have heart disease\", 100 * notActive[notActive[\"HeartDisease\"] == \"Yes\"].size / notActive.size )"





  
  

  315
  
   ]





  
  

  316
  
  },





  
  

  317
  
  {





  
  

  318
  
   "cell_type": "code",





  
  

  319
  
   "execution_count": 17,





  
  

  320
  
   "metadata": {},





  
  

  321
  
   "outputs": [





  
  

  322
  
    {





  
  

  323
  
     "data": {





  
  

  324
  
      "text/plain": [





  
  

  325
  
       "<AxesSubplot: >"





  
  

  326
  
      ]





  
  

  327
  
     },





  
  

  328
  
     "execution_count": 17,





  
  

  329
  
     "metadata": {},





  
  

  330
  
     "output_type": "execute_result"





  
  

  331
  
    },





  
  

  332
  
    {





  
  

  333
  
     "data": {





  
  

  334
  
      "image/png": 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LlZ2drdTUVHXt2lUFBQUB3zV01VVX6fXXX9ecOXP04IMP6pJLLlFRUZH69+9vjZk9e7bq6uo0Y8YM1dTU6Oqrr1ZJSYmioqJa+2sDAIB2yOb3+8+tz2//gjwej2JiYlRbWxuSm6WLi4s1e0v4OXWP0N7Hx7b1EgAA7UTTuXDMmDFBv1m6pedv/tYYAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADBWq0Now4YNuu6665SQkCCbzaaioqKA/X6/XwUFBerevbs6duyojIwM7d69O2DM4cOHNXnyZDkcDsXGxiorK0vHjh0LGPP555/rmmuuUVRUlBITE7VgwYJma3nzzTfVp08fRUVFKSUlRcXFxa1eCwAAMFerQ6iurk4DBgzQ0qVLT7t/wYIFWrx4sZYvX67NmzfrvPPOk9Pp1Pfff2+NmTx5srZv3y6Xy6XVq1drw4YNmjFjhrXf4/EoMzNTPXv2VEVFhZ588knNnTtXL7zwgjVm06ZNmjRpkrKysvTpp59q3LhxGjdunKqqqlq1FgAAYC6b3+/3n/WTbTa9/fbbGjdunKQfrsAkJCTonnvu0b333itJqq2tVVxcnFasWKGJEydqx44dSk5O1scff6whQ4ZIkkpKSjRmzBjt379fCQkJeu655/THP/5RbrdbkZGRkqQHHnhARUVF2rlzpyRpwoQJqqur0+rVq631XHnllRo4cKCWL1/eorWcicfjUUxMjGpra+VwOM72MJ2Wz+dTcXGxZm8Jl7fBFtS5Q2nv42PbegkAgHai6Vw4ZswYRUREBG3e1py/g3qP0J49e+R2u5WRkWFti4mJUVpamsrLyyVJ5eXlio2NtSJIkjIyMhQWFqbNmzdbY4YNG2ZFkCQ5nU7t2rVLR44cscac/DpNY5pepyVrAQAAZusQzMncbrckKS4uLmB7XFyctc/tdqtbt26Bi+jQQZ07dw4Yk5SU1GyOpn2dOnWS2+0+4+ucaS2n8nq98nq91mOPxyPph2L1+Xw/9au3WtN89rCzviDXJoJ9HAAA5mo6p4TqHNsSQQ2hc11hYaHmzZvXbHtpaamio6ND8przhzSGZN5QOfWGdAAAfi6XyxXU+Y4fP97isUENofj4eElSdXW1unfvbm2vrq7WwIEDrTEHDx4MeN6JEyd0+PBh6/nx8fGqrq4OGNP0+ExjTt5/prWcKj8/X3l5edZjj8ejxMREZWZmhuQeIZfLpYe2hsnbeO7cI1Q119nWSwAAtBNN58KRI0cG/R6hlgpqCCUlJSk+Pl5lZWVWbHg8Hm3evFkzZ86UJKWnp6umpkYVFRVKTU2VJL3//vtqbGxUWlqaNeaPf/yjfD6fdWBcLpd69+6tTp06WWPKysqUm5trvb7L5VJ6enqL13Iqu90uu93ebHtERERQ/4NO5m20nVM3S4fqOAAAzBXs82xr5mr1zdLHjh1TZWWlKisrJf1wU3JlZaX27dsnm82m3NxcPfroo3rnnXe0bds23XbbbUpISLA+Wda3b1+NGjVK06dP15YtW7Rx40bl5ORo4sSJSkhIkCTdcsstioyMVFZWlrZv365Vq1Zp0aJFAVdr7r77bpWUlGjhwoXauXOn5s6dq61btyonJ0eSWrQWAABgtlZfEdq6dauGDx9uPW6KkylTpmjFihWaPXu26urqNGPGDNXU1Ojqq69WSUmJoqKirOe89tprysnJ0YgRIxQWFqbx48dr8eLF1v6YmBiVlpYqOztbqamp6tq1qwoKCgK+a+iqq67S66+/rjlz5ujBBx/UJZdcoqKiIvXv398a05K1AAAAc/2s7xFq7/geoeb4HiEAQLC0u+8RAgAAOJcQQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWEEPoblz58pmswX89OnTx9r//fffKzs7W126dNH555+v8ePHq7q6OmCOffv2aezYsYqOjla3bt1033336cSJEwFj1q1bp8GDB8tut+viiy/WihUrmq1l6dKl6tWrl6KiopSWlqYtW7YE+9cFAADnsJBcEerXr5++/vpr6+fDDz+09s2aNUvvvvuu3nzzTa1fv14HDhzQjTfeaO1vaGjQ2LFjVV9fr02bNmnlypVasWKFCgoKrDF79uzR2LFjNXz4cFVWVio3N1d33HGH1q5da41ZtWqV8vLy9PDDD+uTTz7RgAED5HQ6dfDgwVD8ygAA4BwUkhDq0KGD4uPjrZ+uXbtKkmpra/Xyyy/rqaee0rXXXqvU1FS9+uqr2rRpkz766CNJUmlpqf7973/rL3/5iwYOHKjRo0dr/vz5Wrp0qerr6yVJy5cvV1JSkhYuXKi+ffsqJydHN910k55++mlrDU899ZSmT5+uadOmKTk5WcuXL1d0dLReeeWVUPzKAADgHNQhFJPu3r1bCQkJioqKUnp6ugoLC3XRRRepoqJCPp9PGRkZ1tg+ffrooosuUnl5ua688kqVl5crJSVFcXFx1hin06mZM2dq+/btGjRokMrLywPmaBqTm5srSaqvr1dFRYXy8/Ot/WFhYcrIyFB5efmPrtvr9crr9VqPPR6PJMnn88nn8/2sY3KqpvnsYf6gzhtqwT4OAABzNZ1TQnWObYmgh1BaWppWrFih3r176+uvv9a8efN0zTXXqKqqSm63W5GRkYqNjQ14TlxcnNxutyTJ7XYHRFDT/qZ9PzXG4/Hou+++05EjR9TQ0HDaMTt37vzRtRcWFmrevHnNtpeWlio6OrplB6CV5g9pDMm8oVJcXNzWSwAAtDMulyuo8x0/frzFY4MeQqNHj7b+fdlllyktLU09e/bUG2+8oY4dOwb75YIqPz9feXl51mOPx6PExERlZmbK4XAE9bV8Pp9cLpce2homb6MtqHOHUtVcZ1svAQDQTjSdC0eOHKmIiIigzdv0jk5LhOStsZPFxsbq0ksv1RdffKGRI0eqvr5eNTU1AVeFqqurFR8fL0mKj49v9umupk+VnTzm1E+aVVdXy+FwqGPHjgoPD1d4ePhpxzTNcTp2u112u73Z9oiIiKD+B53M22iTt+HcCaFQHQcAgLmCfZ5tzVwh/x6hY8eO6csvv1T37t2VmpqqiIgIlZWVWft37dqlffv2KT09XZKUnp6ubdu2BXy6y+VyyeFwKDk52Rpz8hxNY5rmiIyMVGpqasCYxsZGlZWVWWMAAACCHkL33nuv1q9fr71792rTpk264YYbFB4erkmTJikmJkZZWVnKy8vTBx98oIqKCk2bNk3p6em68sorJUmZmZlKTk7Wrbfeqs8++0xr167VnDlzlJ2dbV2tufPOO/Xf//5Xs2fP1s6dO7Vs2TK98cYbmjVrlrWOvLw8vfjii1q5cqV27NihmTNnqq6uTtOmTQv2rwwAAM5RQX9rbP/+/Zo0aZK+/fZbXXjhhbr66qv10Ucf6cILL5QkPf300woLC9P48ePl9XrldDq1bNky6/nh4eFavXq1Zs6cqfT0dJ133nmaMmWKHnnkEWtMUlKS1qxZo1mzZmnRokXq0aOHXnrpJTmd/7t/ZcKECTp06JAKCgrkdrs1cOBAlZSUNLuBGgAAmMvm9/vPrc9v/4I8Ho9iYmJUW1sbkpuli4uLNXtL+Dl1j9Dex8e29RIAAO1E07lwzJgxQb9ZuqXnb/7WGAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjdWjrBQAAgODo9cCatl5Cq9jD/VpwRduugStCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjEUIAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFhGhNDSpUvVq1cvRUVFKS0tTVu2bGnrJQEAgF+Bdh9Cq1atUl5enh5++GF98sknGjBggJxOpw4ePNjWSwMAAG2s3YfQU089penTp2vatGlKTk7W8uXLFR0drVdeeaWtlwYAANpYh7ZeQCjV19eroqJC+fn51rawsDBlZGSovLy82Xiv1yuv12s9rq2tlSQdPnxYPp8vqGvz+Xw6fvy4OvjC1NBoC+rcofTtt9+29RIAAD+iw4m6tl5Cq3Ro9Ov48UZ9++23ioiICNq8R48elST5/f4zryFor/or9M0336ihoUFxcXEB2+Pi4rRz585m4wsLCzVv3rxm25OSkkK2xnNN14VtvQIAQHtySwjnPnr0qGJiYn5yTLsOodbKz89XXl6e9bixsVGHDx9Wly5dZLMF96qNx+NRYmKivvrqKzkcjqDODQDAuSBU50K/36+jR48qISHhjGPbdQh17dpV4eHhqq6uDtheXV2t+Pj4ZuPtdrvsdnvAttjY2FAuUQ6HgxACABgtFOfCM10JatKub5aOjIxUamqqysrKrG2NjY0qKytTenp6G64MAAD8GrTrK0KSlJeXpylTpmjIkCG64oor9Mwzz6iurk7Tpk1r66UBAIA21u5DaMKECTp06JAKCgrkdrs1cOBAlZSUNLuB+pdmt9v18MMPN3srDgAAU/wazoU2f0s+WwYAANAOtet7hAAAAH4KIQQAAIxFCAEAAGMRQgAAwFiEUAhNnTpVNptNjz/+eMD2oqKioH9TNQAAvxZ+v18ZGRlyOp3N9i1btkyxsbHav39/G6ysOUIoxKKiovTEE0/oyJEjbb0UAAB+ETabTa+++qo2b96s559/3tq+Z88ezZ49W88++6x69OjRhiv8H0IoxDIyMhQfH6/CwsIfHfPWW2+pX79+stvt6tWrlxYu5C+bAgDObYmJiVq0aJHuvfde7dmzR36/X1lZWcrMzNSgQYM0evRonX/++YqLi9Ott96qb775xnru3//+d6WkpKhjx47q0qWLMjIyVFdXF5J1EkIhFh4erscee0zPPvvsaS8DVlRU6Oabb9bEiRO1bds2zZ07Vw899JBWrFjxyy8WAIAgmjJlikaMGKHbb79dS5YsUVVVlZ5//nlde+21GjRokLZu3aqSkhJVV1fr5ptvliR9/fXXmjRpkm6//Xbt2LFD69at04033qhQfe0hX6gYQlOnTlVNTY2KioqUnp6u5ORkvfzyyyoqKtINN9wgv9+vyZMn69ChQyotLbWeN3v2bK1Zs0bbt29vw9UDAPDzHTx4UP369dPhw4f11ltvqaqqSv/617+0du1aa8z+/fuVmJioXbt26dixY0pNTdXevXvVs2fPkK+PK0K/kCeeeEIrV67Ujh07Arbv2LFDQ4cODdg2dOhQ7d69Ww0NDb/kEgEACLpu3brpD3/4g/r27atx48bps88+0wcffKDzzz/f+unTp48k6csvv9SAAQM0YsQIpaSk6Pe//71efPHFkN5nSwj9QoYNGyan06n8/Py2XgoAAL+oDh06qEOHH/686bFjx3TdddepsrIy4Gf37t0aNmyYwsPD5XK59N577yk5OVnPPvusevfurT179oRmbSGZFaf1+OOPa+DAgerdu7e1rW/fvtq4cWPAuI0bN+rSSy9VeHj4L71EAABCavDgwXrrrbfUq1cvK45OZbPZNHToUA0dOlQFBQXq2bOn3n77beXl5QV9PVwR+gWlpKRo8uTJWrx4sbXtnnvuUVlZmebPn6///Oc/WrlypZYsWaJ77723DVcKAEBoZGdn6/Dhw5o0aZI+/vhjffnll1q7dq2mTZumhoYGbd68WY899pi2bt2qffv26R//+IcOHTqkvn37hmQ9hNAv7JFHHlFjY6P1ePDgwXrjjTf0t7/9Tf3791dBQYEeeeQRTZ06te0WCQBAiCQkJGjjxo1qaGhQZmamUlJSlJubq9jYWIWFhcnhcGjDhg0aM2aMLr30Us2ZM0cLFy7U6NGjQ7IePjUGAACMxRUhAABgLEIIAAAYixACAADGIoQAAICxCCEAAGAsQggAABiLEAIAAMYihAAAgLEIIQAAYCxCCAAAGIsQAgAAxiKEAACAsf4fQ/O4yZMaYUwAAAAASUVORK5CYII=",





  
  

  335
  
      "text/plain": [





  
  

  336
  
       "<Figure size 640x480 with 1 Axes>"





  
  

  337
  
      ]





  
  

  338
  
     },





  
  

  339
  
     "metadata": {},





  
  

  340
  
     "output_type": "display_data"





  
  

  341
  
    }





  
  

  342
  
   ],





  
  

  343
  
   "source": [





  
  

  344
  
    "Active['HeartDisease'].hist()"





  
  

  345
  
   ]





  
  

  346
  
  },





  
  

  347
  
  {





  
  

  348
  
   "cell_type": "code",





  
  

  349
  
   "execution_count": 18,





  
  

  350
  
   "metadata": {},





  
  

  351
  
   "outputs": [





  
  

  352
  
    {





  
  

  353
  
     "data": {





  
  

  354
  
      "text/plain": [





  
  

  355
  
       "<AxesSubplot: >"





  
  

  356
  
      ]





  
  

  357
  
     },





  
  

  358
  
     "execution_count": 18,





  
  

  359
  
     "metadata": {},





  
  

  360
  
     "output_type": "execute_result"





  
  

  361
  
    },





  
  

  362
  
    {





  
  

  363
  
     "data": {





  
  

  364
  
      "image/png": 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       "<Figure size 640x480 with 1 Axes>"





  
  

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     },





  
  

  369
  
     "metadata": {},





  
  

  370
  
     "output_type": "display_data"





  
  

  371
  
    }





  
  

  372
  
   ],





  
  

  373
  
   "source": [





  
  

  374
  
    "Active['HeartDisease'].hist()"





  
  

  375
  
   ]





  
  

  376
  
  }





  
  

  377
  
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   "name": "python3"





  
  

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   "codemirror_mode": {





  
  

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    "name": "ipython",





  
  

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    "version": 3





  
  

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   },





  
  

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   "file_extension": ".py",





  
  

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   "mimetype": "text/x-python",





  
  

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   "name": "python",





  
  

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}