data_exploration.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# KEN3450, Data Analysis 2020 \n",
    "\n",
    "**Kaggle Competition 2020**<br>\n",
    "\n",
    "Data Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy as sp\n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import KFold\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import roc_auc_score\n",
    "\n",
    "#import your classifiers here\n",
    "\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1: Read the data, clean and explore the data\n",
    "\n",
    "There are a large number of missing values in the data. Nearly all predictors have some degree of missingness. Not all missingness are alike: NaN in the `'pregnancy'` column is meaningful and informative, as patients with NaN's in the pregnancy column are males, where as NaN's in other predictors may appear randomly. \n",
    "\n",
    "\n",
    "**What do you do?:** We make no attempt to interpret the predictors and we make no attempt to model the missing values in the data in any meaningful way. We replace all missing values with 0.\n",
    "\n",
    "However, it would be more complete to look at the data and allow the data to inform your decision on how to address missingness. For columns where NaN values are informative, you might want to treat NaN as a distinct value; You might want to drop predictors with too many missing values and impute the ones with few missing values using a model. There are many acceptable strategies here, as long as the appropriateness of the method in the context of the task and the data is discussed."
   ]
  },
  {
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   "execution_count": 5,
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     "text": [
      "(5246, 72)\n"
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>HHIncomeMid</th>\n",
       "      <th>Poverty</th>\n",
       "      <th>HomeRooms</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Length</th>\n",
       "      <th>HeadCirc</th>\n",
       "      <th>Height</th>\n",
       "      <th>BMI</th>\n",
       "      <th>...</th>\n",
       "      <th>CompHrsDayChild</th>\n",
       "      <th>AlcoholDay</th>\n",
       "      <th>AlcoholYear</th>\n",
       "      <th>SmokeAge</th>\n",
       "      <th>AgeFirstMarij</th>\n",
       "      <th>AgeRegMarij</th>\n",
       "      <th>SexAge</th>\n",
       "      <th>SexNumPartnLife</th>\n",
       "      <th>SexNumPartYear</th>\n",
       "      <th>flu</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>count</td>\n",
       "      <td>5246.000000</td>\n",
       "      <td>5246.000000</td>\n",
       "      <td>4798.000000</td>\n",
       "      <td>4843.000000</td>\n",
       "      <td>5210.000000</td>\n",
       "      <td>5206.000000</td>\n",
       "      <td>356.000000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>5014.000000</td>\n",
       "      <td>5010.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>417.000000</td>\n",
       "      <td>2404.000000</td>\n",
       "      <td>2882.000000</td>\n",
       "      <td>1479.000000</td>\n",
       "      <td>1331.000000</td>\n",
       "      <td>629.000000</td>\n",
       "      <td>2673.000000</td>\n",
       "      <td>2773.000000</td>\n",
       "      <td>2405.000000</td>\n",
       "      <td>5246.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>mean</td>\n",
       "      <td>61707.937286</td>\n",
       "      <td>35.078155</td>\n",
       "      <td>54079.824927</td>\n",
       "      <td>2.614229</td>\n",
       "      <td>6.147025</td>\n",
       "      <td>68.701921</td>\n",
       "      <td>84.363483</td>\n",
       "      <td>41.101639</td>\n",
       "      <td>160.341424</td>\n",
       "      <td>26.371601</td>\n",
       "      <td>...</td>\n",
       "      <td>2.225420</td>\n",
       "      <td>2.959651</td>\n",
       "      <td>72.353921</td>\n",
       "      <td>17.939148</td>\n",
       "      <td>16.983471</td>\n",
       "      <td>17.545310</td>\n",
       "      <td>17.456042</td>\n",
       "      <td>14.617021</td>\n",
       "      <td>1.354678</td>\n",
       "      <td>0.059093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>std</td>\n",
       "      <td>5876.826538</td>\n",
       "      <td>23.032443</td>\n",
       "      <td>32956.594998</td>\n",
       "      <td>1.672579</td>\n",
       "      <td>2.223687</td>\n",
       "      <td>29.774856</td>\n",
       "      <td>13.827255</td>\n",
       "      <td>2.381561</td>\n",
       "      <td>21.043275</td>\n",
       "      <td>7.464134</td>\n",
       "      <td>...</td>\n",
       "      <td>2.517635</td>\n",
       "      <td>3.522538</td>\n",
       "      <td>101.779814</td>\n",
       "      <td>5.452497</td>\n",
       "      <td>3.874501</td>\n",
       "      <td>4.478533</td>\n",
       "      <td>3.740811</td>\n",
       "      <td>61.385945</td>\n",
       "      <td>2.503281</td>\n",
       "      <td>0.235820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>min</td>\n",
       "      <td>51624.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2500.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>47.100000</td>\n",
       "      <td>34.200000</td>\n",
       "      <td>83.600000</td>\n",
       "      <td>12.880000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25%</td>\n",
       "      <td>56623.250000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>22500.000000</td>\n",
       "      <td>1.110000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>73.950000</td>\n",
       "      <td>39.600000</td>\n",
       "      <td>155.400000</td>\n",
       "      <td>21.200000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50%</td>\n",
       "      <td>61669.500000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>50000.000000</td>\n",
       "      <td>2.320000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>70.600000</td>\n",
       "      <td>86.150000</td>\n",
       "      <td>41.200000</td>\n",
       "      <td>165.000000</td>\n",
       "      <td>25.700000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>75%</td>\n",
       "      <td>66841.250000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>87500.000000</td>\n",
       "      <td>4.340000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>87.300000</td>\n",
       "      <td>95.325000</td>\n",
       "      <td>42.900000</td>\n",
       "      <td>173.600000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>104.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>max</td>\n",
       "      <td>71915.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>100000.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>223.000000</td>\n",
       "      <td>112.200000</td>\n",
       "      <td>45.400000</td>\n",
       "      <td>200.400000</td>\n",
       "      <td>80.600000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>82.000000</td>\n",
       "      <td>364.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>69.000000</td>\n",
       "      <td>1.000000</td>\n",
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       "<p>8 rows × 44 columns</p>\n",
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       "                 ID          Age    HHIncomeMid      Poverty    HomeRooms  \\\n",
       "count   5246.000000  5246.000000    4798.000000  4843.000000  5210.000000   \n",
       "mean   61707.937286    35.078155   54079.824927     2.614229     6.147025   \n",
       "std     5876.826538    23.032443   32956.594998     1.672579     2.223687   \n",
       "min    51624.000000     0.000000    2500.000000     0.000000     1.000000   \n",
       "25%    56623.250000    15.000000   22500.000000     1.110000     5.000000   \n",
       "50%    61669.500000    33.000000   50000.000000     2.320000     6.000000   \n",
       "75%    66841.250000    53.000000   87500.000000     4.340000     7.000000   \n",
       "max    71915.000000    80.000000  100000.000000     5.000000    13.000000   \n",
       "\n",
       "            Weight      Length   HeadCirc       Height          BMI  ...  \\\n",
       "count  5206.000000  356.000000  61.000000  5014.000000  5010.000000  ...   \n",
       "mean     68.701921   84.363483  41.101639   160.341424    26.371601  ...   \n",
       "std      29.774856   13.827255   2.381561    21.043275     7.464134  ...   \n",
       "min       2.800000   47.100000  34.200000    83.600000    12.880000  ...   \n",
       "25%      53.000000   73.950000  39.600000   155.400000    21.200000  ...   \n",
       "50%      70.600000   86.150000  41.200000   165.000000    25.700000  ...   \n",
       "75%      87.300000   95.325000  42.900000   173.600000    30.500000  ...   \n",
       "max     223.000000  112.200000  45.400000   200.400000    80.600000  ...   \n",
       "\n",
       "       CompHrsDayChild   AlcoholDay  AlcoholYear     SmokeAge  AgeFirstMarij  \\\n",
       "count       417.000000  2404.000000  2882.000000  1479.000000    1331.000000   \n",
       "mean          2.225420     2.959651    72.353921    17.939148      16.983471   \n",
       "std           2.517635     3.522538   101.779814     5.452497       3.874501   \n",
       "min           0.000000     1.000000     0.000000     6.000000       1.000000   \n",
       "25%           0.000000     1.000000     3.000000    15.000000      15.000000   \n",
       "50%           1.000000     2.000000    24.000000    17.000000      16.000000   \n",
       "75%           6.000000     3.000000   104.000000    19.000000      18.000000   \n",
       "max           6.000000    82.000000   364.000000    72.000000      48.000000   \n",
       "\n",
       "       AgeRegMarij       SexAge  SexNumPartnLife  SexNumPartYear          flu  \n",
       "count   629.000000  2673.000000      2773.000000     2405.000000  5246.000000  \n",
       "mean     17.545310    17.456042        14.617021        1.354678     0.059093  \n",
       "std       4.478533     3.740811        61.385945        2.503281     0.235820  \n",
       "min       5.000000     9.000000         0.000000        0.000000     0.000000  \n",
       "25%      15.000000    15.000000         2.000000        1.000000     0.000000  \n",
       "50%      17.000000    17.000000         5.000000        1.000000     0.000000  \n",
       "75%      19.000000    19.000000        12.000000        1.000000     0.000000  \n",
       "max      52.000000    50.000000      2000.000000       69.000000     1.000000  \n",
       "\n",
       "[8 rows x 44 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Train\n",
    "df = pd.read_csv('data/flu_train.csv')\n",
    "df = df[~np.isnan(df['flu'])]  # Just making sure that our target attribute has no missing values\n",
    "print(df.shape)\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "      <td>No</td>\n",
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       "      <td>8</td>\n",
       "      <td>White</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 71 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID  Gender  Age  Race1     Education MaritalStatus     HHIncome  \\\n",
       "0  51625    male    4  Other           NaN           NaN  20000-24999   \n",
       "1  51678    male   60  White   High School       Married  15000-19999   \n",
       "2  51694    male   38  White  Some College       Married  20000-24999   \n",
       "3  51695    male    8  White           NaN           NaN  65000-74999   \n",
       "4  51711  female   59  Other     8th Grade       Widowed  20000-24999   \n",
       "\n",
       "   HHIncomeMid  Poverty  HomeRooms  ... RegularMarij AgeRegMarij  HardDrugs  \\\n",
       "0      22500.0     1.07        9.0  ...          NaN         NaN        NaN   \n",
       "1      17500.0     1.03        5.0  ...          NaN         NaN         No   \n",
       "2      22500.0     1.15        6.0  ...           No         NaN         No   \n",
       "3      70000.0     3.55        5.0  ...          NaN         NaN        NaN   \n",
       "4      22500.0     1.37        4.0  ...          NaN         NaN        NaN   \n",
       "\n",
       "   SexEver  SexAge  SexNumPartnLife  SexNumPartYear SameSex SexOrientation  \\\n",
       "0      NaN     NaN              NaN             NaN     NaN            NaN   \n",
       "1      Yes    20.0              1.0             NaN      No            NaN   \n",
       "2      Yes    23.0              1.0             1.0      No   Heterosexual   \n",
       "3      NaN     NaN              NaN             NaN     NaN            NaN   \n",
       "4      NaN     NaN              NaN             NaN     NaN            NaN   \n",
       "\n",
       "   PregnantNow  \n",
       "0          NaN  \n",
       "1          NaN  \n",
       "2          NaN  \n",
       "3          NaN  \n",
       "4          NaN  \n",
       "\n",
       "[5 rows x 71 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Test\n",
    "df_test = pd.read_csv('data/flu_test.csv')\n",
    "print(df_test.shape)\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x train shape: (5246, 71)\n",
      "x test shape: (1533, 70)\n",
      "train class 0: 4936, train class 1: 310\n",
      "The percentage of flu in training is 5.909%\n"
     ]
    }
   ],
   "source": [
    "#What's up in each set\n",
    "\n",
    "x = df.values[:, :-1]\n",
    "y = df.values[:, -1]\n",
    "\n",
    "x_test = df_test.values[:, :-1]\n",
    "\n",
    "print('x train shape:', x.shape)\n",
    "print('x test shape:', x_test.shape)\n",
    "print('train class 0: {}, train class 1: {}'.format(len(y[y==0]), len(y[y==1])))\n",
    "print('The percentage of flu in training is {:.3f}%'.format((100*len(y[y==1])/(len(y[y==1])+len(y[y==0])))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's check the attributes of the train dataframe ###"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ID int64\n",
      "Gender object\n",
      "Age int64\n",
      "Race1 object\n",
      "Education object\n",
      "MaritalStatus object\n",
      "HHIncome object\n",
      "HHIncomeMid float64\n",
      "Poverty float64\n",
      "HomeRooms float64\n",
      "HomeOwn object\n",
      "Work object\n",
      "Weight float64\n",
      "Length float64\n",
      "HeadCirc float64\n",
      "Height float64\n",
      "BMI float64\n",
      "BMICatUnder20yrs object\n",
      "BMI_WHO object\n",
      "Pulse float64\n",
      "BPSysAve float64\n",
      "BPDiaAve float64\n",
      "BPSys1 float64\n",
      "BPDia1 float64\n",
      "BPSys2 float64\n",
      "BPDia2 float64\n",
      "BPSys3 float64\n",
      "BPDia3 float64\n",
      "Testosterone float64\n",
      "DirectChol float64\n",
      "TotChol float64\n",
      "UrineVol1 float64\n",
      "UrineFlow1 float64\n",
      "UrineVol2 float64\n",
      "UrineFlow2 float64\n",
      "Diabetes object\n",
      "DiabetesAge float64\n",
      "HealthGen object\n",
      "DaysMentHlthBad float64\n",
      "LittleInterest object\n",
      "Depressed object\n",
      "nPregnancies float64\n",
      "nBabies float64\n",
      "Age1stBaby float64\n",
      "SleepHrsNight float64\n",
      "SleepTrouble object\n",
      "PhysActive object\n",
      "PhysActiveDays float64\n",
      "TVHrsDay object\n",
      "CompHrsDay object\n",
      "TVHrsDayChild float64\n",
      "CompHrsDayChild float64\n",
      "Alcohol12PlusYr object\n",
      "AlcoholDay float64\n",
      "AlcoholYear float64\n",
      "SmokeNow object\n",
      "Smoke100 object\n",
      "Smoke100n object\n",
      "SmokeAge float64\n",
      "Marijuana object\n",
      "AgeFirstMarij float64\n",
      "RegularMarij object\n",
      "AgeRegMarij float64\n",
      "HardDrugs object\n",
      "SexEver object\n",
      "SexAge float64\n",
      "SexNumPartnLife float64\n",
      "SexNumPartYear float64\n",
      "SameSex object\n",
      "SexOrientation object\n",
      "PregnantNow object\n",
      "flu int64\n"
     ]
    }
   ],
   "source": [
    "for col in df.columns:\n",
    "    print(col, df[col].dtypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Gender ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Gender'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Very balanced for gender --> Only \"male\" or \"female\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Gender'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are no missing values. We can convert the column into one called `female` where there is a 1 if the person is a female, and a 0 if the person is a male."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['female'] = (df['Gender'] == 'female').astype(int)\n",
    "df = df.drop(columns='Gender')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Age ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5246.000000\n",
       "mean       35.078155\n",
       "std        23.032443\n",
       "min         0.000000\n",
       "25%        15.000000\n",
       "50%        33.000000\n",
       "75%        53.000000\n",
       "max        80.000000\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Age'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Age'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Race1 ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Race1'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Race1'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "dummy = pd.get_dummies(df['Race1'], prefix='race')\n",
    "dummy = dummy.drop(columns='race_Other')\n",
    "df = pd.concat([df, dummy], axis=1)\n",
    "df = df.drop(columns='Race1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Education ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Education'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1672"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Education'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAR6klEQVR4nO3dbayc5X3n8e+vOCENbWIMB+S1nZooVpqoWgw5Yp2yqlrcByBVzIugElXFQpa8L2ibbCt1na3UqtK+AKkqKdIKyQppTZUloTRZLILSWA5RtZWgPTyUkDgUh1J8ahefJEC2RX2g/e+Luc4y2GPOnCfP8ZXvRxrd9/2/rznzPzO3f759zT3jVBWSpL78wKQbkCStPMNdkjpkuEtShwx3SeqQ4S5JHVo36QYALr744tq6deuk25Ckc8pjjz327aqaGrVvTYT71q1bmZmZmXQbknROSfK3Z9rntIwkdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nq0ILhnuS9SZ4cun0vyceTbEhyKMmzbXlhG58kdyY5muSpJFeu/q8hSRq2YLhX1TNVtb2qtgMfAF4FvgDsAw5X1TbgcNsGuA7Y1m57gbtWo3FJ0pktdlpmJ/CtqvpbYBdwoNUPADe09V3APTXwCLA+ycYV6VaSNJbFfkL1JuDetn5pVZ0AqKoTSS5p9U3AsaH7zLbaieEflGQvgzN73vWudy2yjddt3ffFJd93uZ6/7UMTe2xJejNjn7kneSvwYeCPFxo6onbaf/dUVfurarqqpqemRn41giRpiRYzLXMd8HhVvdi2X5yfbmnLk60+C2wZut9m4PhyG5UkjW8x4f5RXp+SATgI7G7ru4EHhuo3t6tmdgCvzE/fSJLOjrHm3JO8HfgZ4L8MlW8D7kuyB3gBuLHVHwKuB44yuLLmlhXrVpI0lrHCvapeBS46pfYdBlfPnDq2gFtXpDtJ0pL4CVVJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjq02C8O05BJfWmZX1gmaSGeuUtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ2OFe5L1Se5P8s0kR5J8MMmGJIeSPNuWF7axSXJnkqNJnkpy5er+CpKkU4175v77wJeq6keBy4EjwD7gcFVtAw63bYDrgG3tthe4a0U7liQtaMFwT/IO4CeAuwGq6l+q6mVgF3CgDTsA3NDWdwH31MAjwPokG1e8c0nSGY1z5v5uYA74gyRPJPlUkguAS6vqBEBbXtLGbwKODd1/ttXeIMneJDNJZubm5pb1S0iS3miccF8HXAncVVVXAP/I61Mwo2RErU4rVO2vqumqmp6amhqrWUnSeMYJ91lgtqoebdv3Mwj7F+enW9ry5ND4LUP33wwcX5l2JUnjWDDcq+rvgWNJ3ttKO4FvAAeB3a22G3igrR8Ebm5XzewAXpmfvpEknR3j/h+qvwJ8JslbgeeAWxj8xXBfkj3AC8CNbexDwPXAUeDVNlaSdBaNFe5V9SQwPWLXzhFjC7h1mX1JkpbBT6hKUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdWiscE/yfJKvJXkyyUyrbUhyKMmzbXlhqyfJnUmOJnkqyZWr+QtIkk63mDP3n6qq7VU13bb3AYerahtwuG0DXAdsa7e9wF0r1awkaTzLmZbZBRxo6weAG4bq99TAI8D6JBuX8TiSpEUaN9wL+HKSx5LsbbVLq+oEQFte0uqbgGND951ttTdIsjfJTJKZubm5pXUvSRpp3Zjjrq6q40kuAQ4l+eabjM2IWp1WqNoP7AeYnp4+bb8kaenGOnOvquNteRL4AnAV8OL8dEtbnmzDZ4EtQ3ffDBxfqYYlSQtbMNyTXJDkh+fXgZ8FngYOArvbsN3AA239IHBzu2pmB/DK/PSNJOnsGGda5lLgC0nmx/+vqvpSkr8E7kuyB3gBuLGNfwi4HjgKvArcsuJdS5Le1ILhXlXPAZePqH8H2DmiXsCtK9KdJGlJ/ISqJHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6NHa4JzkvyRNJHmzblyV5NMmzST6X5K2tfn7bPtr2b12d1iVJZ7KYM/ePAUeGtm8H7qiqbcBLwJ5W3wO8VFXvAe5o4yRJZ9FY4Z5kM/Ah4FNtO8A1wP1tyAHghra+q23T9u9s4yVJZ8m4Z+6fBH4D+Pe2fRHwclW91rZngU1tfRNwDKDtf6WNf4Mke5PMJJmZm5tbYvuSpFEWDPckPw+crKrHhssjhtYY+14vVO2vqumqmp6amhqrWUnSeNaNMeZq4MNJrgfeBryDwZn8+iTr2tn5ZuB4Gz8LbAFmk6wD3gl8d8U7lySd0YJn7lX1iaraXFVbgZuAr1TVLwIPAx9pw3YDD7T1g22btv8rVXXambskafUs5zr3/wb8WpKjDObU7271u4GLWv3XgH3La1GStFjjTMv8f1X1VeCrbf054KoRY/4JuHEFepMkLZGfUJWkDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nq0LqFBiR5G/BnwPlt/P1V9dtJLgM+C2wAHgd+qar+Jcn5wD3AB4DvAL9QVc+vUv/fl7bu++LEHvv52z40sceWNL5xztz/Gbimqi4HtgPXJtkB3A7cUVXbgJeAPW38HuClqnoPcEcbJ0k6ixYM9xr4h7b5lnYr4Brg/lY/ANzQ1ne1bdr+nUmyYh1LkhY01px7kvOSPAmcBA4B3wJerqrX2pBZYFNb3wQcA2j7XwEuGvEz9yaZSTIzNze3vN9CkvQGY4V7Vf1bVW0HNgNXAe8bNawtR52l12mFqv1VNV1V01NTU+P2K0kaw6Kulqmql4GvAjuA9Unm35DdDBxv67PAFoC2/53Ad1eiWUnSeBYM9yRTSda39R8Efho4AjwMfKQN2w080NYPtm3a/q9U1Wln7pKk1bPgpZDARuBAkvMY/GVwX1U9mOQbwGeT/A/gCeDuNv5u4I+SHGVwxn7TKvQtSXoTC4Z7VT0FXDGi/hyD+fdT6/8E3Lgi3UmSlsRPqEpShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUMLhnuSLUkeTnIkydeTfKzVNyQ5lOTZtryw1ZPkziRHkzyV5MrV/iUkSW80zpn7a8CvV9X7gB3ArUneD+wDDlfVNuBw2wa4DtjWbnuBu1a8a0nSm1ow3KvqRFU93tb/L3AE2ATsAg60YQeAG9r6LuCeGngEWJ9k44p3Lkk6o0XNuSfZClwBPApcWlUnYPAXAHBJG7YJODZ0t9lWkySdJWOHe5IfAv4E+HhVfe/Nho6o1YiftzfJTJKZubm5cduQJI1hrHBP8hYGwf6Zqvp8K784P93SlidbfRbYMnT3zcDxU39mVe2vqumqmp6amlpq/5KkEca5WibA3cCRqvq9oV0Hgd1tfTfwwFD95nbVzA7glfnpG0nS2bFujDFXA78EfC3Jk63234HbgPuS7AFeAG5s+x4CrgeOAq8Ct6xox5KkBS0Y7lX1fxg9jw6wc8T4Am5dZl+SpGXwE6qS1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHVow3JN8OsnJJE8P1TYkOZTk2ba8sNWT5M4kR5M8leTK1WxekjTaOGfufwhce0ptH3C4qrYBh9s2wHXAtnbbC9y1Mm1KkhZjwXCvqj8DvntKeRdwoK0fAG4Yqt9TA48A65NsXKlmJUnjWeqc+6VVdQKgLS9p9U3AsaFxs612miR7k8wkmZmbm1tiG5KkUVb6DdWMqNWogVW1v6qmq2p6ampqhduQpO9vSw33F+enW9ryZKvPAluGxm0Gji+9PUnSUiw13A8Cu9v6buCBofrN7aqZHcAr89M3kqSzZ91CA5LcC/wkcHGSWeC3gduA+5LsAV4AbmzDHwKuB44CrwK3rELPkqQFLBjuVfXRM+zaOWJsAbcutylJ0vL4CVVJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDq1KuCe5NskzSY4m2bcajyFJOrMVD/ck5wH/E7gOeD/w0STvX+nHkSSd2bpV+JlXAUer6jmAJJ8FdgHfWIXHklbV1n1fnNhjP3/bhyb22N9venydVyPcNwHHhrZngf906qAke4G9bfMfkjyzxMe7GPj2Eu+7mrrsK7evYCdv1OXztRxjPNc+Z4uzJvvK7cvq60fOtGM1wj0janVaoWo/sH/ZD5bMVNX0cn/OSrOvxbGvxVurvdnX4qxWX6vxhuossGVoezNwfBUeR5J0BqsR7n8JbEtyWZK3AjcBB1fhcSRJZ7Di0zJV9VqSXwb+FDgP+HRVfX2lH2fIsqd2Vol9LY59Ld5a7c2+FmdV+krVadPhkqRznJ9QlaQOGe6S1KFzOtzXytccJPl0kpNJnh6qbUhyKMmzbXnhBPrakuThJEeSfD3Jx9ZCb0neluQvkvxV6+t3Wv2yJI+2vj7X3pA/65Kcl+SJJA+ulb6SPJ/ka0meTDLTamvhGFuf5P4k32zH2Qcn3VeS97bnaf72vSQfn3Rfrbf/2o75p5Pc2/4srMrxdc6G+xr7moM/BK49pbYPOFxV24DDbftsew349ap6H7ADuLU9R5Pu7Z+Ba6rqcmA7cG2SHcDtwB2tr5eAPWe5r3kfA44Mba+Vvn6qqrYPXRM96dcR4PeBL1XVjwKXM3jeJtpXVT3TnqftwAeAV4EvTLqvJJuAXwWmq+rHGFxwchOrdXxV1Tl5Az4I/OnQ9ieAT0ywn63A00PbzwAb2/pG4Jk18Jw9APzMWuoNeDvwOINPMX8bWDfq9T2L/Wxm8Af/GuBBBh/KWwt9PQ9cfEptoq8j8A7gb2gXZqyVvk7p5WeBP18LffH6p/c3MLhS8UHg51br+Dpnz9wZ/TUHmybUyyiXVtUJgLa8ZJLNJNkKXAE8yhrorU19PAmcBA4B3wJerqrX2pBJvZ6fBH4D+Pe2fdEa6auALyd5rH11B0z+dXw3MAf8QZvG+lSSC9ZAX8NuAu5t6xPtq6r+Dvhd4AXgBPAK8BirdHydy+E+1tccCJL8EPAnwMer6nuT7gegqv6tBv9s3szgy+beN2rY2ewpyc8DJ6vqseHyiKGTOM6urqorGUxD3prkJybQw6nWAVcCd1XVFcA/MpmpoZHa3PWHgT+edC8AbY5/F3AZ8B+ACxi8nqdakePrXA73tf41By8m2QjQlicn0USStzAI9s9U1efXUm8AVfUy8FUG7wmsTzL/wbpJvJ5XAx9O8jzwWQZTM59cA31RVcfb8iSD+eOrmPzrOAvMVtWjbft+BmE/6b7mXQc8XlUvtu1J9/XTwN9U1VxV/SvweeDHWaXj61wO97X+NQcHgd1tfTeD+e6zKkmAu4EjVfV7a6W3JFNJ1rf1H2Rw0B8BHgY+Mqm+quoTVbW5qrYyOJ6+UlW/OOm+klyQ5Ifn1xnMIz/NhF/Hqvp74FiS97bSTgZf7T3xY7/5KK9PycDk+3oB2JHk7e3P5vzztTrH16Te6FihNyiuB/6awXztb06wj3sZzKH9K4OzmT0M5moPA8+25YYJ9PWfGfwT7yngyXa7ftK9Af8ReKL19TTwW63+buAvgKMM/il9/gRf058EHlwLfbXH/6t2+/r8sT7p17H1sB2Yaa/l/wYuXCN9vR34DvDOodpa6Ot3gG+24/6PgPNX6/jy6wckqUPn8rSMJOkMDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUof8Hn3tFDTUaIfwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Education'].isna()]['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1672.000000\n",
       "mean        9.397727\n",
       "std         6.498378\n",
       "min         0.000000\n",
       "25%         4.000000\n",
       "50%         9.000000\n",
       "75%        14.000000\n",
       "max        80.000000\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Education'].isna()]['Age'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of the education is missing for very young people. We can probably work it out and fill the missing values as one of the categories above depending on the age. For babies we can just put no education. We could also include primary school, etc."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### MaritalStatus ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['MaritalStatus'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1666"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['MaritalStatus'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['MaritalStatus'].isna()]['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1666.000000\n",
       "mean        9.268307\n",
       "std         6.050194\n",
       "min         0.000000\n",
       "25%         4.000000\n",
       "50%         9.000000\n",
       "75%        14.000000\n",
       "max        80.000000\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['MaritalStatus'].isna()]['Age'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing the marital status for very young people. Fill value as *NeverMarried*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HHIncome ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.HHIncome.hist()\n",
    "plt.grid(False)\n",
    "plt.xticks(rotation=45);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "448"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['HHIncome'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['HHIncome'].isna()]['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['25000-34999', '35000-44999', '75000-99999', '55000-64999',\n",
       "       'more 99999', '65000-74999', nan, '15000-19999', '10000-14999',\n",
       "       ' 0-4999', '45000-54999', ' 5000-9999', '20000-24999'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.HHIncome.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's gonna be complicated to fill missing values for this. Maybe ignoring it may be best, as the poverty attribute may substitute this one."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HHIncomeMid ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.HHIncomeMid.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count      4798.000000\n",
       "mean      54079.824927\n",
       "std       32956.594998\n",
       "min        2500.000000\n",
       "25%       22500.000000\n",
       "50%       50000.000000\n",
       "75%       87500.000000\n",
       "max      100000.000000\n",
       "Name: HHIncomeMid, dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.HHIncomeMid.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "448"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['HHIncomeMid'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Same as in `HHIncome`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Complicated to fill missing values, due to polarization of richness. Maybe ignoring may be best."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Poverty ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['Poverty'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    4843.000000\n",
       "mean        2.614229\n",
       "std         1.672579\n",
       "min         0.000000\n",
       "25%         1.110000\n",
       "50%         2.320000\n",
       "75%         4.340000\n",
       "max         5.000000\n",
       "Name: Poverty, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Poverty'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "403"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Poverty'].isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Poverty'].isna()]['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can probably fill missing values with a distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAAD4CAYAAADM6gxlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAbJklEQVR4nO3df3Ac5XkH8O/js4Rlx0R2kD0gDLapxynECQYllqtOBtIQgwmJAukEj2nSXzDT8keoO85Yg2eIO/bg1h2GZso0MUnaTHEcJyCu/EiiemKYThlQIkcG4WDVQABzECwCAscoWJyf/nF74nTaV3er2913993vZ0aju+dWt+9q75577933h6gqiIgoPWbZLgAREQXDxE1ElDJM3EREKcPETUSUMkzcREQpMzuKJz3rrLN06dKlUTw1EZGTDh48+LqqttWzbSSJe+nSpRgYGIjiqYmInCQiL9a7LZtKiIhShombiChlmLiJiFKGiZuIKGWYuImIUoaJm4goZerqDigiLwA4AaAI4D1V7YiyUERptnTLw1NiL+y8OjP7j0qSjyvusgWpcV+uqhczaVMa5AcL6Np5AMu2PIyunQeQHyzEsl+/N/B0cdf2H5UkH5eNskUyAIfIpvxgAT29QxgbLwIACqNj6OkdAgB0r263WTSiUNRb41YA/y0iB0XkJr8NROQmERkQkYGRkZHwSkgU0K6+4YmkXTY2XsSuvmFLJSIKV72Ju0tVLwFwFYCbReST1Ruo6m5V7VDVjra2uobbE0XildGxQHGitKkrcavqK97v4wDuB/CJKAtF1IhzWlsCxYnSpmbiFpF5IjK/fBvAZwA8HXXBiGbq8g/7f+MzxYnSpp6Lk4sB3C8i5e2/r6o/jbRURA145Ij/NRZTnChtaiZuVX0ewMdiKAtRKGy2cS+e34zXTpzyjROFhSMnyTktTf4va1M8TP23XjElSS+e34z+W6+IfN+UHezHTc4Ze+90oHjYmKQpaqxxk3NUg8Up+UzDx5My5D1uTNzknNJ19PrjlHxrduwPFHcdEzc5p2W2oY3bEKfk87vgO13cdXwlk3PGxg1t3IY4UdowcZNzOHKSXMfETc557S3//tqmOFHaMHGTc94z9B4xxYnShombiChlmLiJiFKGiZvIIe2GC7CmOKUTEzeRQzilbTYwcRM55J4nXgoUp3Ri4ibnzDIMbTfFidKGiZvcY+r2x+6A5AhO60rOMQ1sj2vAe36wgF19w3hldAzntLZg87qV6F7dHtPeKQuYuIlClB8soKd3CGPjRQBAYXQMPb1DAMDkTaFhUwk5x2Yb966+4YmkXTY2XsSuvuHod06ZwcRNzlm7fGGgeJhsrndJ2cHETc554bf+SdIUDxNnJqQ4MHGTcwqG2q0pHqa5zf5vKVOcaCb4aiLn5AxrlJniYTp6/GSgONFMMHGTc4qGVYFNcaK0YeKmyOQHC+jaeQDLtjyMrp0HkB8sxLLfLE+0xNXQs4H9uCkSNvszZ71nB5O0+1jjpkjY7M/MEe/kOiZuikTWa71EUWLipkh8sKUpUJyI6sc2borEeNF/SidTPEyzxX9h4NkZmdZ1a34Ie/uPoaiKnAg2rFmC7d2rbBeLQlR3jVtEciIyKCIPRVkgcsPJU8VA8TA9e/vVU5L0bCnFXbc1P4R7nnhpoutjURX3PPEStuaHLJeMwhSkxv1VAM8AODOishCFJgtJ2s/e/mPGOGvd7qirxi0i5wK4GsC3oy0OETWCg4+yod6mkjsBfA3TzEUvIjeJyICIDIyMjIRSOCIKxuZwf4pPzcQtIp8FcFxVD063naruVtUOVe1oa+OK0kQ2LG+bGyhO6VRPG3cXgM+JyHoAcwCcKSL3qOoN0RaNaOay2rOCk1xlQ80at6r2qOq5qroUwPUADjBpUy2mL+ZxfGFnzwpyHQfgUCRsDjufrmcFkQsCDcBR1UcBPBpJSYhCwp4V5DrWuMk5NptpiOLAxE3OmducCxQnShsmbnLOO4Zh9aY4UdowcVMkbA4E4UrrFKcmQxY1xcPAxE2RsHmB8PIP+w8AM8WJGjFuGE9uioeBiZucs+/nLwWKE6UNEzc5x0YNiChOTNxERCnDxE1ElDJM3EREKcPETRSiFYvmBYoTzQQTN1GI9m+6bMrQevHiRGFh4iYK0Zod+6fMgKhenCgsTNxEIXrtxKlAcaKZYOImIkoZJm4iopRh4qZI2Jh4h9irJSv4NqJIcNi5HVwsOBuYuImIUoaJmyLRnPOfd9sUJ6L6MXFTJMZP+8+7bYpTONjGnQ1M3BQJ03oJXGg9Wvs3XYbF85snxRbPb+bITccwcRM5JD9YmDLY57UTp5AfLFgqkfu4dBmFLj9YQNfOA1i25WF07TzAN7DjNu07FChOjfvAnKZA8TDMjuyZybr8YAE9vUMYGy+tbl4YHUNP7xAAoHt1u82iUURMvS3ZCzM6o++MB4qHgTVuh+3qG55I2mVj40Xs6hu2VCIi95zT2hIoHgYmbocVRscCxV1h6nDIjogUhaUf8k/QpngYmLjJOaaOK+zQQlF44vk3A8XDwMRNRNSAoqGPqykeBiZuh4mhbcAUJ6LgcoY3lCkehpqJW0TmiMjPReRJETksItsiKw2FqmW2/+k1xcPEEXyUFRvWLAkUD0M97+B3AXxKVT8G4GIAV4pIZ2QlotCMGabiM8XDtH/TZVOS9IpF85wfwTfbUMkyxSn9fj3yu0DxMNRM3FpSLkGT98PrPClgo5tSpZsvX4H21hYIgPbWFtx8+YpY9mvTe4Z3hilO6ffYc28Eioehru/MIpITkUMAjgPYr6r9PtvcJCIDIjIwMjISdjlpBuY2+59eUzxM5cE/hdExKN4f/BPHyE3Wesl1db2DVbWoqhcDOBfAJ0TkIz7b7FbVDlXtaGtrC7ucNAM2J9W3OfiHtV5yXaCql6qOAngUwJWRlIacwcE/9cWJZqKeXiVtItLq3W4B8GkAR6IuGFEacfAPxaGeSabOBvA9EcmhlOh/qKoPRVssIqJ0WDC3CW/6TCi1YG50swPW06vkKVVdraofVdWPqOo/RFYaIqKUue2ai9BUtSRfU05w2zUXRbZPTutKRNSA8hTJu/qG8croGM5pbcHmdSsjnTqZQ96JiBo08OIb+M1bv4cC+M1bv8fAi9H14QZY4yYiasjW/BDueeKliftF1Yn727tXRbJP1riJiBqwt/9YoHgYmLiJiBrAaV2JiKgmJm4iogbYGC3LxE1E1AAbo2WZuImIGpDIFXCIiMjMxgo47MdNRNSAcl/tvf3HUFRFTgQb1iyJrA83wMRNRNSw7d2rIk3U1dhUQkSUMkzcREQpw8RNRJQyTNxERCnDxE1ElDJM3EREKcPugEREDcoPFmJdAYeJm4ioAfnBAjbf+yTGi6XZSQqjY9h875MAEFnyZlMJESXe4vnNgeJx2vbg4YmkXTZeVGx78HBk+2TiJqLEe/1344HicXrzHf8ymOJhYFOJZRvvfhyPPff+wqJdFyzEnhvXWiwRUfLYWGUmyVjjtqg6aQPAY8+9gY13P26pRESUBkzcFlUn7VpxIiKAiZuIUsDGYgVJxsRNRImX5DbuFYvmBYqHgYmbiBKvvbUlUDxO+zddNiVJr1g0D/s3XRbZPtmrhIgSb/O6lejpHcLYeHEi1tKUw+Z1Ky2W6n1RJmk/TNxElHjlEYhxDitPMjaVEBGlTM3ELSJLROQREXlGRA6LyFfjKBgRUVl+sICe3iEURsegKM0H0tM7hPxgwXbRrKinxv0egL9X1T8E0AngZhG5MNpiEdFM5Ay940zxtNjVNzypfRsAxsaL2NU3bKlEdtVM3Kr6qqr+0rt9AsAzALLZsESUcBvWnBconhavjI4FisctP1hA184DWLblYXTtPBD5N4FAbdwishTAagD9Po/dJCIDIjIwMjISTumIKJBHjvi/90zxtDjH0O3PFI9TeVrXymaczfc+GWnyrjtxi8gHANwH4BZVfbv6cVXdraodqtrR1tYWZhmJUmOOoU3CFA9bwVADNcXTYvO6lWhpyk2KJaU7YGKndRWRJpSS9h5V7Y2sNEQpd2THesyuytGzpRSnmete3Y7br12F9tYWCEoDb26/dlUiugPamNa1nl4lAuA7AJ5R1TsiKwmRA/KDBUjV/BkiktneD2G665Gjk5oj7nrkqO0iWVNPjbsLwJ8B+JSIHPJ+WH0g8vH1Bw5j/HTV1+bTiq8/EN3X5iy44o5HcfT4yUmxo8dP4oo7HrVToAotTf5p1BQPQ82Rk6r6vwBS3pmIKB6jY/5fj03xsM1rzuHkqaJvPM2qk3ateJzmNOUwNn7aNx4VjpwkcsiOL6xCbtbkelZulmDHF1ZZKpH7Rg1t2aZ4GJi4QxB3H04ik+7V7ehctmBSrHPZgkRcxHOVja6KTNwNstGHk8hka37Idzm8rfkhSyVyn42uikzcDbLRh5PIZG//sUDxtEjyfNw2uipyWtcGNdKH88wzcnj73akXks48I90XkrKs64KFvmuGdl2wMJb9J3mlmEZsXrcSm3/05KQeO02zJBEDcIBS8o6zOYo1bov8rv5PF6fk23Pj2ilJuuuChdhz49pY9u/02ozVh+DAIc0Ua9wWFQ2VIFOc0iGuJO2nc/kC3xp/5/IFPlunx66+Yd8myV19w5m88MoaN5FDXvit/5wkpnhaJH12wLgxcRM5xNUEl+TZAW1g4iZyiKsJLsmzA9rAxE3kEFcTXJJnB7SBFyeJQrbx7scnXSCMs1eJy6uhx93lLsmYuIlCVJ20gdLIxY13Px5r8nYxweUHC05+IM0EEzdRiPy64k0Xp/qUV3kvLxhcXuUdQCaTN9u4iSjxuMr7ZKxxE1HiJb2bY9zNOKxxE1HiJbmbY7kZp3KG0J7eoUhnCGWNG7zoQeGZBWDqWijx1pBcfD3Pbfb/D5ricZquGSeq/3vmE3d+sIBN+w5NvNkKo2PYtO8QgGxe9KDGmKaZiWv6GVcv4iV56TIbzTj2P64s6+l9akoN6bQXJwrK9ld6XsSLH1fAscBvkc/p4kTTsT1yMekX8VzEFXCIUq57dTuuu7R9Yv7rnAiuuzS+ATG2a/xRMS1EEdcCFdOxcc6ZuIlClB8s4L6DhYkVZ4qquO9gIbY1SG3X+KNie4GK6dg455m/OEkUJhs9DCq5PFdJEpK0H/YqIUq5JLQxuzpXSVKxVwlRyrnaxkxm7FVCFALTGrJxrC3rahszmW1etxJNsya/uqJegZ5NJeQcm4NgXG5jJrPyhUnT/bAxcROFjG3M2fL1Bw7jdFWePq2lOC9OElGmJXUOltGx8UDxMNRM3CLyXQCfBXBcVT8SWUmIHJHUBJNmrs7BMlP1XJz8DwBXRlwOIifYmOIzC5I8B8uCuU2B4mGombhV9X8AcN0lSo0bOs8LFA9TkhNMmiWhf7zJbddchKZcVa+SnOC2ay6KbJ+hdQcUkZtEZEBEBkZGRsJ62rrkBwvo2nkAy7Y8jK6dB1i7ybjt3auwYtG8SbEVi+Zhe/eqyPed5ASTZknuH9+9uh1f+viSSXOVfOnjS9IxV4mq7lbVDlXtaGtrC+tpa8oPFnDLvkOTvpresu8Qk3eGbc0PTZmn+ejxk9iaH4p830lOMGmW5P7x+cEC9v3i2KS5Svb94likOSj1A3A2/+hQoDi5754nXgoUD1OSE0yada9ux+3XrkJ7awsEQHtrC26/dlUiLkxue/AwxouT+wOOFxXbHjwc2T5T3x3QNG02p9MmGzgAJzpJ7R//5jv+3f5M8TDU0x1wL4DLAJwlIi8DuE1VvxNZiYhSLqkJhtxRM3Gr6oY4CkJERPVJfRs3JZPNiZ6SvFoKURiYuCkSNid6+tMO//7apjhR2jBxk3NMg104CIZcwcRNzuEgGIpTa4v/0HZTPAxM3BSJOTn/1mxTPEwcBENxEsNL2hQPAxM3ReLIjvVTkvScnODIjvWR7/vyD/uP3DXFXcMpIOI1auivbYqHIfUDcCi54kjSfu7/pX+iuv+XhVjmK7GJ05/G75zWFhR8muG45iRRACdPFQPFXcLZCeNnY5oD1riJHMILs/GzMc0BEzc5R+DfXzyOwT+22fjaTvFPc8DETZFZs2M/XjtxauL+4vnN6L/1isj3u7HzPN+ZADfGsJCCbZvXrZzUxg1wdkIXsY2bIlGdtAHgtROnsGbH/sj3vb17FW7oPG/SxPY3dJ7n/IVJINnTn1J4WOOmSFQn7VrxsG3vXpWJRO3H1dkJuQjz+5i4iSjxkt7NMe4PlcQkbn6aEpHJdN0cbecJGx8qiWjjLh945bqRPb1DHPGVYovnNweKE03Hr6fMdPE42eg7n4jEzUED7um/9YopSTquXiXknpxh4g9TPE42PlQSkbiT/GmaZjYXMwCAnvUXTurd0LP+wpj2TK4pr6BebzxONj5UEpG4KRqmfstx9Ge23fzFiZbc0m4YQGSKx8nGhwoTt8M6zl+I3KzJn/q5WYKO86Nfwstm85ftDw0Kn435QOpl40OFibtBjTRHLJjrP9G6KR7Urr5hFE9P/tQvntZYkqfN5i9eM3FPkgcW2ZhGmIm7QX+waF6geCXTN6mwvmHZnHDI5sUkTrREcXroyVcDxcPAxN2g50feCRSv9NaY/0TrpnhQNleCsXkxiSvguCfJzV+jhverKR4GJu4GNZKgPmhYk84UD8pmu6DNGneS20NpZtj8NVliRk5mUdRr1dmYJ7jMZo3b5nFTNJLc/CXi37wZZR2FiduiONaqszXhULthXui4um/ZnGiJ0zeEL8nzjEd9rcpP5ptKGv1K30hXIJfbYrPaXJHkttg0S/Lrid0BLdiwZkmgeLXN61aiqWo186ac1PWCSvKLsVHdq9tx3aXtk+bEvu7S+GrBtgbgsC02GknuDsg1J9Oq+itRnV+RXG6LzQ8WcN/BwkSbdlEV9x0soOP8hZEfn80pQJPcFpt2SZ1nnGtOWrDHZ4mrcryeifh39Q1jvGqQy7g3yKWeE5fUF2OjbE7DaXPfSW6Lpegkcs1JEbkSwL8AyAH4tqrujLRUMTJVjuu9rtBoDeujt/0Ub7/7fpI584wcntp2ZZ17r83WhTKbNU+b++aaj9m08e7H8dhzb0zc77pgIfbcuDay/dVs4xaRHIC7AFwF4EIAG0QkMdO85QzXEE3xsM1p8v8XmuKVqpM2ALz9bhEfve2noZTN5oUymxde5zbnAsXDlOS2WIpGddIGgMeeewMb7348sn3WU+P+BIBnVfV5ABCRHwD4PIBfRVaqAObPafIdoTR/TjiDWGp5973TgeKVqpN2rXhQNpsMbNY83znl//8zxcPmavMX+atO2rXiYainV0k7gGMV91/2YpOIyE0iMiAiAyMjI2GVr6aoh43XctrQpmKKx8lmk4HNmmejzV9ESVdPjduv0WHKe0BVdwPYDQAdHR2xvUcavRiUE/EdzVdvP+5G/z5Kti+U2ap5JvmcEIWhnhr3ywAqOzWfC+CVaIoTXKN9KBvtx93I3595hn+bqykelMv9xKfT6DklCqLrAv/57U3xMNSTuH8BYIWILBORZgDXA3ggzEK8sPPqQPFKjX4l3969Cjd0njdpoMgNnefV1RWw0b9/atuVU5J0mL1KsnqhrNFzShTEnhvXTknSUfcqEa1jQL2IrAdwJ0rdAb+rqjum276jo0MHBgbCKSERUQaIyEFV7ahn27r6cavqjwH8uKFSERFRKDI/VwkRUdowcRMRpQwTNxFRyjBxExGlDBM3EVHK1NUdMPCTiowAeNHw8FkAXg99p8mX1eMGsnvsWT1uILvH3shxn6+qbfVsGEninnaHIgP19lV0SVaPG8jusWf1uIHsHntcx82mEiKilGHiJiJKGRuJe7eFfSZBVo8byO6xZ/W4geweeyzHHXsbNxERNYZNJUREKcPETUSUMrElbhG5UkSGReRZEdkS137DJCJLROQREXlGRA6LyFe9+EIR2S8iR73fC7y4iMg3vGN+SkQuqXiur3jbHxWRr1TELxWRIe9vviGSrGVbRCQnIoMi8pB3f5mI9HvHsc+bsx0icoZ3/1nv8aUVz9HjxYdFZF1FPJGvERFpFZF7ReSId+7XZuWci8jfea/1p0Vkr4jMcfGci8h3ReS4iDxdEYv8HJv2UZOqRv6D0jzezwFYDqAZwJMALoxj3yEfx9kALvFuzwfwfwAuBPBPALZ48S0A/tG7vR7AT1Ba/q0TQL8XXwjgee/3Au/2Au+xnwNY6/3NTwBcZfu4q/4HmwB8H8BD3v0fArjeu/1NAH/j3f5bAN/0bl8PYJ93+0Lv/J8BYJn3usgl+TUC4HsA/tq73QygNQvnHKW1ZX8NoKXiXP+5i+ccwCcBXALg6YpY5OfYtI+a5Y3pn7IWQF/F/R4APbZfmCEc138BuALAMICzvdjZAIa9298CsKFi+2Hv8Q0AvlUR/5YXOxvAkYr4pO1s/6C0bN3PAHwKwEPei/B1ALOrzzOAPgBrvduzve2k+tyXt0vqawTAmV7ykqq48+cc7y8UvtA7hw8BWOfqOQewFJMTd+Tn2LSPWj9xNZXUtVJ8mnhfA1cD6AewWFVfBQDv9yJvM9NxTxd/2SeeFHcC+BqA0979DwEYVdX3vPuV5Z04Ru/xt7ztg/5PbFsOYATAv3tNRN8WkXnIwDlX1QKAfwbwEoBXUTqHB+H+OS+L4xyb9jGtuBJ3XSvFp4WIfADAfQBuUdW3p9vUJ6YziFsnIp8FcFxVD1aGfTbVGo+l7dhno/QV+t9UdTWAkyh9pTVx5bjhtbd+HqXmjXMAzANwlc+mrp3zWqwfZ1yJO9ErxQchIk0oJe09qtrrhV8TkbO9x88GcNyLm457uvi5PvEk6ALwORF5AcAPUGouuRNAq4iUl8CrLO/EMXqPfxDAGwj+P7HtZQAvq2q/d/9elBJ5Fs75pwH8WlVHVHUcQC+AP4L757wsjnNs2se04krcka8UHwfvSvB3ADyjqndUPPQAgPIV5K+g1PZdjn/ZuwrdCeAt7+tQH4DPiMgCr1bzGZTa+l4FcEJEOr19fbniuaxS1R5VPVdVl6J0/g6o6kYAjwD4ordZ9bGX/ydf9LZXL3691wNhGYAVKF24SeRrRFV/A+CYiKz0Qn8C4FfIwDlHqYmkU0TmemUrH7vT57xCHOfYtI/pxdjwvx6lXhjPAbjV1gWIBo/hj1H6ivMUgEPez3qU2vF+BuCo93uht70AuMs75iEAHRXP9ZcAnvV+/qIi3gHgae9v/hVVF8WS8APgMrzfq2Q5Sm/CZwH8CMAZXnyOd/9Z7/HlFX9/q3d8w6joQZHU1wiAiwEMeOc9j1KPgUyccwDbABzxyvefKPUMce6cA9iLUjv+OEo15L+K4xyb9lHrh0PeiYhShiMniYhShombiChlmLiJiFKGiZuIKGWYuImIUoaJm4goZZi4iYhS5v8BI5RIZfz9ezoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df.HHIncomeMid, df.Poverty);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HomeRooms ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['HomeRooms'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5210.000000\n",
       "mean        6.147025\n",
       "std         2.223687\n",
       "min         1.000000\n",
       "25%         5.000000\n",
       "50%         6.000000\n",
       "75%         7.000000\n",
       "max        13.000000\n",
       "Name: HomeRooms, dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['HomeRooms'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "36"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.HomeRooms.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.HomeRooms.isna()]['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This may be people who don't own a house at all. Young people leaving with their parents, living in a dorm, nursery home. Missing values for young and old people."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HomeOwn ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.HomeOwn.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "33"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.HomeOwn.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do we assume these people don't have a house?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.HomeRooms.isna()]['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This may be people who don't own a house at all. Young people leaving with their parents, living in a dorm, nursery home. Missing values for young and old people."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Work ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Work.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1357"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Work.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Work.isna()]['Age'].hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1357.000000\n",
       "mean        7.369197\n",
       "std         4.740153\n",
       "min         0.000000\n",
       "25%         3.000000\n",
       "50%         7.000000\n",
       "75%        11.000000\n",
       "max        32.000000\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Work.isna()]['Age'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing values for very young people, probably never worked. We can either put them as *NotWorking* or create a new category as *NeverWorked*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Weight ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Weight.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Weight.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Weight.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Either substitute according to distribution, or build a predictor for weight based on `age` and `gender`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df.Age, df.Weight);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Length ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Length.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4890"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Length.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most of the people's heights are missing, but we can probably work out a distribution to provide the missing values. Or build a predictor based on `age` and `gender`. Nop, ignore it because we have the `height` attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Length.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HeadCirc ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.HeadCirc.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5185"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.HeadCirc.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Almost everyone is missing this attribute. It may be better to not take it into account."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.HeadCirc.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Height ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD4CAYAAAAAczaOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAUXElEQVR4nO3df5Bd5X3f8fenKGDj1EagxcGSpqskclqSSWtVwWrSpA4k/LIH8YeZinGL6jCjqYtd/2hiizITpsl4BuxMSJi6eNSgGhIGTAkJmkKKFYzDdKb8WIj5ITBhAwStwdZ6hElaJtjE3/5xH5XL6mp3tVe6u6vzfs3s3HO+57n3PA9HfPbsc8+9J1WFJKkb/t5id0CSNDqGviR1iKEvSR1i6EtShxj6ktQhKxa7A7NZtWpVjY+PL3Y3JGlZefjhh79TVWODti3p0B8fH2diYmKxuyFJy0qSvzrUNqd3JKlDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUOW9CdyJS0t49vvXJT9Pn/V+xdlv8ciz/QlqUPmDP0kO5PsS/LEjPrHkjydZE+Sz/XVL08y2bad01c/t9Umk2w/ssOQJM3HfKZ3vgT8Z+DGA4UkvwhsBn66ql5Lcmqrnw5sAX4SeBfwp0ne3Z72BeCXgSngoSS7qurJIzUQSdLc5gz9qrovyfiM8keAq6rqtdZmX6tvBm5p9eeSTAJntG2TVfUsQJJbWltDX5JGaKFz+u8Gfj7JA0n+LMnPtPpqYG9fu6lWO1T9IEm2JZlIMjE9Pb3A7kmSBllo6K8AVgKbgF8Dbk0SIAPa1iz1g4tVO6pqY1VtHBsbeA8ASdICLfSSzSng9qoq4MEkPwBWtfravnZrgBfb8qHqkqQRWeiZ/h8DZwK0N2qPB74D7AK2JDkhyTpgPfAg8BCwPsm6JMfTe7N317CdlyQdnjnP9JPcDLwPWJVkCrgS2AnsbJdxfg/Y2s769yS5ld4btK8Dl1XV37XX+ShwN3AcsLOq9hyF8UiSZjGfq3cuPsSmf3WI9p8FPjugfhdw12H1TpJ0RPmJXEnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqkIXeREXSIhnffudid0HLmGf6ktQhhr4kdcicoZ9kZ5J97S5ZM7f9apJKsqqtJ8m1SSaTPJZkQ1/brUmeaT9bj+wwJEnzMZ8z/S8B584sJlkL/DLwQl/5PHr3xV0PbAOua21PpnebxfcCZwBXJlk5TMclSYdvztCvqvuA/QM2XQN8Gqi+2mbgxuq5HzgpyWnAOcDuqtpfVS8Duxnwi0SSdHQtaE4/yQXAN6vq0RmbVgN7+9anWu1Q9UGvvS3JRJKJ6enphXRPknQIhx36SU4ErgB+fdDmAbWapX5wsWpHVW2sqo1jY2OH2z1J0iwWcqb/Y8A64NEkzwNrgEeS/Ai9M/i1fW3XAC/OUpckjdBhh35VPV5Vp1bVeFWN0wv0DVX1LWAXcEm7imcT8EpVvQTcDZydZGV7A/fsVpMkjdB8Ltm8GfjfwE8kmUpy6SzN7wKeBSaB/wr8O4Cq2g/8JvBQ+/mNVpMkjdCcX8NQVRfPsX28b7mAyw7Rbiew8zD7J0k6gvxEriR1iKEvSR1i6EtShxj6ktQhhr4kdYihL0kdYuhLUocY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR1i6EtShxj6ktQh87lz1s4k+5I80Vf7fJJvJHksyR8lOalv2+VJJpM8neScvvq5rTaZZPuRH4okaS7zOdP/EnDujNpu4Keq6qeBvwAuB0hyOrAF+Mn2nP+S5LgkxwFfAM4DTgcubm0lSSM0Z+hX1X3A/hm1r1TV6231fmBNW94M3FJVr1XVc/TulXtG+5msqmer6nvALa2tJGmEjsSc/q8Af9KWVwN7+7ZNtdqh6pKkERoq9JNcAbwO3HSgNKBZzVIf9JrbkkwkmZienh6me5KkGRYc+km2Ah8APlRVBwJ8Cljb12wN8OIs9YNU1Y6q2lhVG8fGxhbaPUnSAAsK/STnAp8BLqiqV/s27QK2JDkhyTpgPfAg8BCwPsm6JMfTe7N313BdlyQdrhVzNUhyM/A+YFWSKeBKelfrnADsTgJwf1X926rak+RW4El60z6XVdXftdf5KHA3cByws6r2HIXxSJJmMWfoV9XFA8rXz9L+s8BnB9TvAu46rN5Jko4oP5ErSR1i6EtShxj6ktQhhr4kdYihL0kdYuhLUocY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR1i6EtShxj6ktQhhr4kdYihL0kdMmfoJ9mZZF+SJ/pqJyfZneSZ9riy1ZPk2iSTSR5LsqHvOVtb+2faTdUlSSM2nzP9LwHnzqhtB+6pqvXAPW0d4Dx6N0NfD2wDroPeLwl699Z9L3AGcOWBXxSSpNGZM/Sr6j5g/4zyZuCGtnwDcGFf/cbquR84KclpwDnA7qraX1UvA7s5+BeJJOkoW+ic/jur6iWA9nhqq68G9va1m2q1Q9UPkmRbkokkE9PT0wvsniRpkCP9Rm4G1GqW+sHFqh1VtbGqNo6NjR3RzklS1y009L/dpm1oj/tafQpY29duDfDiLHVJ0ggtNPR3AQeuwNkK3NFXv6RdxbMJeKVN/9wNnJ1kZXsD9+xWkySN0Iq5GiS5GXgfsCrJFL2rcK4Cbk1yKfACcFFrfhdwPjAJvAp8GKCq9if5TeCh1u43qmrmm8OSpKNsztCvqosPsemsAW0LuOwQr7MT2HlYvZMkHVF+IleSOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqkKFCP8knk+xJ8kSSm5O8Jcm6JA8keSbJl5Mc39qe0NYn2/bxIzEASdL8LTj0k6wG/j2wsap+CjgO2AJcDVxTVeuBl4FL21MuBV6uqh8HrmntJEkjNOz0zgrgrUlWACcCLwFnAre17TcAF7blzW2dtv2sJBly/5Kkw7Dg0K+qbwK/Re/G6C8BrwAPA9+tqtdbsylgdVteDextz329tT9l5usm2ZZkIsnE9PT0QrsnSRpgmOmdlfTO3tcB7wLeBpw3oGkdeMos294oVO2oqo1VtXFsbGyh3ZMkDTDM9M4vAc9V1XRVfR+4HfhZ4KQ23QOwBnixLU8BawHa9ncA+4fYvyTpMA0T+i8Am5Kc2ObmzwKeBO4FPtjabAXuaMu72jpt+1er6qAzfUnS0TPMnP4D9N6QfQR4vL3WDuAzwKeSTNKbs7++PeV64JRW/xSwfYh+S5IWYMXcTQ6tqq4ErpxRfhY4Y0DbvwUuGmZ/kqThDBX6kjQK49vvXLR9P3/V+xdt30eDX8MgSR1i6EtShxj6ktQhhr4kdYihL0kdYuhLUocY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR1i6EtShxj6ktQhQ4V+kpOS3JbkG0meSvLPkpycZHeSZ9rjytY2Sa5NMpnksSQbjswQJEnzNeyZ/u8C/7Oq/iHwj4Gn6N0G8Z6qWg/cwxu3RTwPWN9+tgHXDblvSdJhWnDoJ3k78Au0e+BW1feq6rvAZuCG1uwG4MK2vBm4sXruB05KctqCey5JOmzDnOn/KDAN/Lckf57k95K8DXhnVb0E0B5Pbe1XA3v7nj/Vam+SZFuSiSQT09PTQ3RPkjTTMKG/AtgAXFdV7wH+L29M5QySAbU6qFC1o6o2VtXGsbGxIbonSZppmNCfAqaq6oG2fhu9XwLfPjBt0x739bVf2/f8NcCLQ+xfknSYFhz6VfUtYG+Sn2ils4AngV3A1lbbCtzRlncBl7SreDYBrxyYBpIkjcaKIZ//MeCmJMcDzwIfpveL5NYklwIvABe1tncB5wOTwKutrSRphIYK/ar6OrBxwKazBrQt4LJh9idJGo6fyJWkDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6ZOjQT3Jckj9P8j/a+rokDyR5JsmX2121SHJCW59s28eH3bck6fAMe7tEgI8DTwFvb+tXA9dU1S1JvghcClzXHl+uqh9PsqW1+5dHYP/Sohjffudid0E6bEOd6SdZA7wf+L22HuBM4LbW5Abgwra8ua3Ttp/V2kuSRmTY6Z3fAT4N/KCtnwJ8t6peb+tTwOq2vBrYC9C2v9Lav0mSbUkmkkxMT08P2T1JUr8Fh36SDwD7qurh/vKApjWPbW8UqnZU1caq2jg2NrbQ7kmSBhhmTv/ngAuSnA+8hd6c/u8AJyVZ0c7m1wAvtvZTwFpgKskK4B3A/iH2L0k6TAs+06+qy6tqTVWNA1uAr1bVh4B7gQ+2ZluBO9ryrrZO2/7VqjroTF+SdPQcjev0PwN8KskkvTn761v9euCUVv8UsP0o7FuSNIsjcckmVfU14Gtt+VngjAFt/ha46EjsT5K0MH4iV5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeqQYW6MvjbJvUmeSrInycdb/eQku5M80x5XtnqSXJtkMsljSTYcqUFIkuZnmDP914H/UFX/CNgEXJbkdHq3QbynqtYD9/DGbRHPA9a3n23AdUPsW5K0AMPcGP2lqnqkLf8N8BSwGtgM3NCa3QBc2JY3AzdWz/3ASUlOW3DPJUmH7YjM6ScZB94DPAC8s6pegt4vBuDU1mw1sLfvaVOtJkkakaFDP8kPA38IfKKq/nq2pgNqNeD1tiWZSDIxPT09bPckSX2GCv0kP0Qv8G+qqttb+dsHpm3a475WnwLW9j19DfDizNesqh1VtbGqNo6NjQ3TPUnSDMNcvRPgeuCpqvrtvk27gK1teStwR1/9knYVzybglQPTQJKk0VgxxHN/DvjXwONJvt5q/xG4Crg1yaXAC8BFbdtdwPnAJPAq8OEh9i1JWoAFh35V/S8Gz9MDnDWgfQGXLXR/kqThDXOmL/1/49vvXOwuSJoHv4ZBkjrEM/2jYDHPep+/6v2Ltm9JS5+hf4xxmkXSbJzekaQOMfQlqUMMfUnqEENfkjrE0JekDjmmr97xShZJerNjOvQlaViLdfJ4tD5z4/SOJHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR0y8tBPcm6Sp5NMJtk+6v1LUpeNNPSTHAd8ATgPOB24OMnpo+yDJHXZqM/0zwAmq+rZqvoecAuwecR9kKTOGvUnclcDe/vWp4D39jdIsg3Y1lb/T5KnB7zOKuA7R6WHi+NYGw8ce2NyPEvbMTeeXD3UeP7BoTaMOvQzoFZvWqnaAeyY9UWSiaraeCQ7tpiOtfHAsTcmx7O0OZ75G/X0zhSwtm99DfDiiPsgSZ016tB/CFifZF2S44EtwK4R90GSOmuk0ztV9XqSjwJ3A8cBO6tqzwJeatbpn2XoWBsPHHtjcjxLm+OZp1TV3K0kSccEP5ErSR1i6EtShyyL0E/yySR7kjyR5OYkb2lvBj+Q5JkkX25vDC9JSXYm2Zfkib7ayUl2t/7vTrKy1ZPk2vY1FY8l2bB4PR/sEOP5fJJvtD7/UZKT+rZd3sbzdJJzFqfXhzZoPH3bfjVJJVnV1pfl8Wn1j7VjsCfJ5/rqS/r4wCH/zf2TJPcn+XqSiSRntPqSPkZJ1ia5N8lT7Vh8vNVHkwlVtaR/6H2g6zngrW39VuDftMctrfZF4COL3ddZxvALwAbgib7a54DtbXk7cHVbPh/4E3qfadgEPLDY/Z/neM4GVrTlq/vGczrwKHACsA74S+C4xR7DXONp9bX0Ljr4K2DVMj8+vwj8KXBCWz91uRyfWcb0FeC8vuPyteVwjIDTgA1t+e8Df9GOw0gyYVmc6dO7yuitSVYAJwIvAWcCt7XtNwAXLlLf5lRV9wH7Z5Q30+s3vLn/m4Ebq+d+4KQkp42mp/MzaDxV9ZWqer2t3k/vMxjQG88tVfVaVT0HTNL7Oo4l4xDHB+Aa4NO8+QOEy/L4AB8Brqqq11qbfa2+5I8PHHJMBby9Lb+DNz7zs6SPUVW9VFWPtOW/AZ6id3I7kkxY8qFfVd8Efgt4gV7YvwI8DHy3L2Sm6P1HW07eWVUvQe8fAXBqqw/6qorlNrZfoXdmAst0PEkuAL5ZVY/O2LQsxwO8G/j5NiX6Z0l+ptWX63gAPgF8PsleehlxeasvmzElGQfeAzzAiDJhyYd+m9faTO9Pz3cBb6P3LZ0zHSvXns75VRVLWZIrgNeBmw6UBjRb0uNJciJwBfDrgzYPqC3p8TQrgJX0pgd+Dbg1SVi+44HeXy+frKq1wCeB61t9WYwpyQ8Dfwh8oqr+eramA2oLHs+SD33gl4Dnqmq6qr4P3A78LL0/cQ58uGw5fp3Dtw/8idYeD/y5vWy/qiLJVuADwIeqTUayPMfzY/ROMh5N8jy9Pj+S5EdYnuOBXr9vb1MEDwI/oPclZct1PABb6eUBwH/njWmpJT+mJD9EL/BvqqoDYxhJJiyH0H8B2JTkxHZmchbwJHAv8MHWZitwxyL1b6F20es3vLn/u4BL2jv2m4BXDvzJt5QlORf4DHBBVb3at2kXsCXJCUnWAeuBBxejj/NVVY9X1alVNV5V4/T+p9tQVd9imR4f4I/pvQ9GkncDx9P7Vspld3z6vAj8i7Z8JvBMW17Sx6jl2PXAU1X1232bRpMJi/1O9jzf7f5PwDeAJ4Dfp3elwY/S+8c5Se+3/AmL3c9Z+n8zvfcjvk8vQC4FTgHuofcP9R7g5NY29G4085fA48DGxe7/PMczSW/e8evt54t97a9o43madrXFUvoZNJ4Z25/njat3luvxOR74g/b/0CPAmcvl+Mwypn9O7/29R+nNif/T5XCMWr8LeKzv/5fzR5UJfg2DJHXIcpjekSQdIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR3y/wDL0NGaDAGrswAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Height.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "232"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Height.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Few missing values, fill them with distribution or predictor (based on `age` and `gender`)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0fj4GLAjc7yLgeMLXaAu9dVwWT6QTFbzZrI1KgrW8jt+xGreD1SjNRUjjEpW1StpyPw78uvfzGuCH3s9PAp/wRs2sAk5H1dvbXZ7X8BDJo4kGJvas+ZO4Gp3YIUbL3cy2AFcBF5jZMeBO4HeBPzWzWcCbeLVz4CngOuBlYBT4ZAYxt5Qky7GKSGvyizXNaKmXi0zuzrkNFW56f8h9HXBrvUG1k0TLsYpIS3KURrvkYTllzVDNmL8sq4h0jkqTlgpmDZvfolUhU1J+gWMzNI5dpMP4g2gqXQDbv4ZqI9btUXJPQflEpTxfnUVEsuNcacG1ghkXz+vhRydHp9Zr/8j7G3vZPZVlUpD1anUi0lomnOOHJ96YNnTy8d3DU0sAN4KSewo0UUlEooyNT3D7I/sa1tmq5J6CZqz4JiKtZ8K5hvXDKbmnwF/5TUQkL5TcU1DpElwiIs2i5J4C1dxFJG+U3FNwXnfjrxAjIlKNknsKalz9U0Qkc0ruKRjRkr4ikjNK7inQUEgRyRsl9xQ04+K3IlKZKqVaWyYV/noRm7cd1PK+IpILarmnpH9FH9sH1jQ7DBGhfa7kVA8ldxGRNqTknpKhPcOsHny22WFIzh0eXNfsEKRDqOaegqE9w2x8bB/jEzoZlOrycPk16QxK7gkFr7xkBpPK6xKDdhNpFCX3BIb2DLPx0X2Mexm9yRc5FxGZQTX3BO568sBUYhcRqaZZY+6V3BPQNVJFJO+U3EVEMtSsc/zI5G5mD5jZCTN7oWz7fzSzg2Z2wMz+OLB9k5m97N22Nougm21uj5b4FZF8i9Ny/xpwTXCDmV0N3Ai8zzm3FPiit/09wMeApd5j/tzM2m7RlTuvX0qxoNUrRCS/IpO7c+57wKmyzb8HDDrn3vLuc8LbfiPwTefcW865Q8DLwBUpxpsL/Sv6WP+BBRS0kLuI5FTSmvsvA//CzHaa2f81sw942/uAo4H7HfO2tZWhPcM8/P2jTGgMpIjkVNJx7rOAucAq4APAI2Z2MeGjfkIzoJndAtwCsHDhwoRhNIeGQopI3iVtuR8DnnAl3wcmgQu87QsC97sIOB72BM65+51zK51zK+fNm5cwjObQUEgRybukyX0IWANgZr8MzAZ+AjwJfMzMzjGzxcAlwPfTCFREROKLLMuY2RbgKuACMzsG3Ak8ADzgDY98G7jZOeeAA2b2CPD3wBngVufcRFbBN0uX1pIRkZyLTO7OuQ0Vbrqpwv3vBe6tJ6i8U2IX6VxGaywApxmqCfTpgtgiHetQi6zJr+SewNWXtlYHsIiko5Vmtii5J7D1+deaHYK0oYJZSyWPTuSXY1rh7F3JPYHXR1tvKGTWk2mVlOo34VxL1HIFNq5dQncx3yur6GIdMd0xtJ8tO/M/K9Ug9MpQOQ9bpCX4S470ryhNvPevxgb562RVyz2GO4b28+COI7lP7IcH1zG/tzvRaJ56W97NfGd00el8Mmi79Zc2XLkgdHseM4Na7jFs2Xk0+k45sHhga+Kd7NDgOhbp4s2SkoIZk84xe5YxNp7H1Ffdl9cv5/ZH9zERaCl1GXxn32s8tOMI53UXeePtM4xP5PdvU8s9hry32H1Jo+yqsXFlln1rOW6Lz79Xb7fW2M8Tv/9gbHyy2aEksnnbwWmJHUqlzpGxcRyl//Oc2EHJXah9UlYjjnVxD6j+ve66YSnFWo9SKfjy+uUdefEWf2RPX283N61aSF9vd1uVYYa9OnorU3KXqWFdcVu/jRwGFjU8MNjBtf6K9NfYr5TE5vYU6e0uctvDe3EOCgkPLM1MhUmTcaGrVHJxwD+efhOA7QNrODS4jskMjvztcbhoPCX3FpLVTu5PyorT+u0uFti4dkni1+qy0kHET5BRO+CkcxwaXMdNq8KXhfY7uIb2DPP47uHUS2iTzExi961fzpvjk9NO0Z1zNQ83ndtTjJztWOtnbpTe37k9xcjHHhpcx5/89mWxh/QZMGd2gYnJs0M2J5zjwR1HuGNoPwDnpVweK3QZ961fzuHBdXU1KsIO0O1Oyb2FHKpzB6/kuZdOAqXW7+aPXja185d/Gfp6u/nCh5dNDQNLotBl3HXDUg4NrqNn9iyiKrJ+srinfxk3rVo41dIsmHHTqoXc078MKNVIx8bTX6POP1YEk1jYa0262stV/v2rnTHVeqi6b/1y3jozyeuj47Ee27+ijy98eFnshPfG2+HvsT/oIO2qzMSkY/O2g0DyseX1ns0Z0FMMT5VzZhdye6DQaJkW4dd1r750Hg/uODLj9jmzC4y+PZGoU3V4ZIzFA1uZ39vNxrVL2D6wps5oKxufKH1Z+1f0TY0Prib4vbynf9lUModSa3314LMcHxmL/LvN0ukr2LLzaGqlh5GxcRYPbOXcComjVkayg1z/ir6pA/a7Nz1V8eyn2l/tP2Ykgwl+/n5SPrY87qfgxzY8Mhb63anGKDWqVnz+aUZDOodnz+riwOeviTVSrct7wkYtPKjk3gKKBePO65cCZ1vZ5Xp7ZnPg82sSD2d0lHb+TU+UTq/raZ1H8b+s83u7IzuugsliaM/w1Bc77lC03u4ie+/84NRchXpNOEdfjLjjqnVESbUVCR3EOmBWs+riuWx/pfySydH8Y3Clz7RglrhkNj9wtho8EFXb1w3oquM1fY7qQ4z92erVXsVgquEUJ/a0qCwTQ7PWkfBLIes/sIDN2w6yeGBrxaTif6nrHRI4Nj4xdRocJelr+V/WOKfZvd4Zy9CeYTY9sZ9hr8UWdyja6TdLreM0EjuUklTc8kDaa8UUzKqW5vp6u6clwmoqfXaHf5r84LB4YCtvvHWGYmH6X10sGO88t3I70j87M5s5LLe8j8c/W1sckRzT7NyNepbFA1srln76ers5NLiO7QNrMm0whVFyj6FZq0AeGlzHxrVLeHz38FRSq8T/UqcxJDBu6y/JawW/rMF6byX+9zNpTd25dGcPXjyvZ0adem5Pccb70F0s8Ce/fVmqy8P6rdCwg4v/vsY98HzosgtDtydt+Tvv38jYOBMTbqpDd25PEdz0S1MG5yYUCzb1GfujjvwO9/I+nvIDfCVzZpf+/rgHuno5wofuFruM0bfPsHhgK6sHn2Voz3BD4vGpLFNBsASQ1dDdOIv+x0lq5QnTf9zxkbGKp6Z+Qg07E4j7pailBhp2auo/R/+Kvoqnvqe9pFBvuSGOYpfxjnNnMVKlM/JHJ0eB6eUBmL6/hP2dafD7Xcrf97DXi/r8H9xxhAd3HKFgxqqL53L4p2NV71+LSUqJ+tDgOlYPPjtjoT3H2f2v/HrE4xOOn795JvR54x7gR71O341rl7DxsX0NnWzkz8z1y4b+396okmeQknsIv4Xg70hZTNqZXTD+4d7rWD34bGiC9Xf+akmtUsIMqvRFPT4yxn3rl0/7O6H2oY7BJFftb4nqpK1Uq/UPNHHq80l0F7t4c3wydk200vtZnuyzEHzpaq8XvC2qfDHh3LQae1pDSUciDsrV9utgB2gwIcY9wE9rnMT4c/yE3NtTxLlSgyLpQc4furt68NkZBy6/5Knk3kRZDasLenvi7Cl2tQRbKalVSpjlB6ZK5vd2x2oB1iLqb6nnsWG3B1va83u7ufrSeTz30slYLdCCGRuuXFBx9E21x4Wp1nKv1AFb3sqLamGeLksWcV4/rYOiP9qovKUflf6iDtpRsQUTYpy/JbjPbN52kPEYQ1PK9wOI/z0qNz+iUdaIM1CfknuIRn4AUQm21oSZpIyTVkuinoNF1GNrfe6wL2d3sVBxnH7cL3PYqoDljy1vcYYemArGnNmzOD02zpxzZvGhyy6MPDBVKpdVe/2w104iON7/B0dOT72PKz7/dOj1DfwSUtT+Gyc2//sY5wAf3Cfifo/DRqCV729xDsBxGmWN6gcAJfdQWZUAgoKjFaJOsSF+Uqu3jFOveg4WUY+t5blrfd+iDophLf1qjw22OMtj6e0p8k9vnpk6bR8eGePx3cNTCbPSgamWA7r/+v7ZXa1jw6sJ/m13Xr90Rl07OHS3f0Ufu149NXUthIIZH3n/9M8xqn/AT4i1fqZxv8eVvjNR/SrBM8XyWCrNR2nk4Awl9xCVPpi0FL1ZmnHVktSSlHGy7ghslqj3Lfi3V0p6/iSWauKcgpf3TZS3dqsdDJIe0IOTf/zHpjXev9LEovJYy5eFmHCOx3cPs/KXzp+Kq3w0TLWDWi3fhbhnLbUMIIj72pXmo1TangUl9xBZfgAFM9ZfsSCzBFpLGSeqnNDOaumbiFLrKXitB4M0X98/86j3qmKVJhaVizqrCUq7D6j8+c4tdoVOGMuiNZ2HmrvGuYfI8gPwWy5ZjXktH4NdbT2Yal+8dldr30Q11cadh6mU9JPWY2t9/Xv6l/HKF67j8OA6vrx++YzHFgtnx5r7Y9HLb3/jrXjjt2tNcv0r+qZWmExj4k/w+c6fc07ofbJozKX9GSehlnuI3p5iphfBznpIVNxWXx5aF82SZt9ErS3OekYVpfH6tT42WL4K6y+odraXh45FXyP395aouZvZA8CHgBPOufeW3fafgc3APOfcT8zMgD8FrgNGgd9xzv0g/bCz1YiLUTQygdY6TK4ZX7xGq7VvIkqWnb1pv36tj62lv6Bc2geyejRyf4+quVcaHpvmUidxyjJfA64p32hmC4DfBIKHp2uBS7x/twBfqT/ExiuffJCF3gZdvad8yrbf0hraMxx6Ol/LKXcrq7WUkba0yw+NkqTMErdMmLVGfuZR71MjYolsuTvnvmdmi0Juug/4feBbgW03An/lnHPADjPrNbMLnXOvpRFsloKt20Zo1GVZaxkmV+spdyvLovXcCZK0fhsxezeORn7mUe9TI2JJVHM3sxuAYefcPps+Y68POBr4/Zi3bUZyN7NbKLXuWbgw/Co7jZJ0Nlo9qs02TFMtw+RqPeVudXlJOq0kT2WWJBr1mcd5n7KOpebkbmY9wB8BHwy7OWRbaBvVOXc/cD/AypUrm3oZ8UYsN1CuUXXtWlpandzBKvHojCeePLxPSVru7wYWA36r/SLgB2Z2BaWWenB+9kXA8XqDzFqjk1cjWzq1tLQ6uYNV4tMZTzzNfp9qHufunNvvnHuXc26Rc24RpYR+uXPuH4EngU9YySrgdCvU29O+qG9QFtchrUUtHVrN7mQUkfTEGQq5BbgKuMDMjgF3Oue+WuHuT1EaBvkypaGQn0wpzkyNvh2+fnS9LnnXHJ757FWZPHct4rYg8nAqKSLpiDNaZkPE7YsCPzvg1vrDaqy3M1rMf/Tt+NfGzItmn0qKSDq0/ECGsl5ZUkSkko5dfqDR49pFRBqpI5N7M8a1i4g0UkeWZRo1rr3SJdlERLLWkcm9UaWYsEuyiYg0Qkcmd03KEZF215HJPWyyTha27DwafScRkQx0ZHLvX9HH5QvPy/x16rmMmYhIPToyud8xtJ/tr5zK/HXUoSoizdKRyf0bO+u/+nsc6lAVkWbpyHHukxlXSwpmbLhywdSV5kVEGq0jk3uWDg+ua3YIIiKdk9y13ICIdJKOSO6NWm6gN8N14UVEatERHaqNWG6g2GXcdcPSTF9DRCSujmi5Z1mKMdBFLUQkdzoiuVe6NmgaDqkDVURyqCPKMhvXLqHYpQlFItI5OiK5A7TeBe9ERJLriOR+97cPMJH1zCURkRzpiOT++uh4Js87Z3b2K0uKiCTREck9C4Uu497f0vICIpJPHTFaJk0a+igiraAjWu4aJyMinaYjknuaoyAdMDwyxsbH9jG0Zzi9JxYRSVFkcjezB8zshJm9ENi22cxeMrPnzeyvzaw3cNsmM3vZzA6a2dqsAo8ytGeY1YPPsnhgKxMZDJQZn3Dc/e0D6T+xiEgK4rTcvwZcU7btGeC9zrn3Af8AbAIws/cAHwOWeo/5czNr+JASf6Gw4ZExshwAmdUoHBGRekUmd+fc94BTZdueds6d8X7dAVzk/Xwj8E3n3FvOuUPAy8AVKcYbSyMWChMRybM0au7/Dvjf3s99wNHAbce8bTOY2S1mtsvMdp08eTKFMM5q1JrtWuJXRPKqruRuZn8EnAEe8jeF3C20MuKcu985t9I5t3LevHn1hDHD/N7uVJ8vjJb4FZE8S5zczexm4JF+4QgAAAnrSURBVEPAx51zfgI/BgSvCn0RcDx5eMlsXLuEYiGbAZAG9PV2s/mjl2mcu4jkVqJJTGZ2DfAHwK8750YDNz0JfMPMvgTMBy4Bvl93lAmMZzBEpq+3m+0Da1J/XhGRtEUmdzPbAlwFXGBmx4A7KY2OOQd4xswAdjjn/oNz7oCZPQL8PaVyza3OuYb3bP7hE8+n/pzdxQIb1y5J/XlFRLIQmdydcxtCNn+1yv3vBe6tJ6h6jY6nt8CvlhsQkVaktWWq6C528eJ/ubbZYYiI1Kwjlh9I6tyilvQVkdak5F7FiGagikiLUnKvohHj5UVEsqDkXoFGx4hIK1OHahmNjhGRdqDkXubQ4LpmhyAiUjeVZURE2pBa7mUWDWylYMaGKxdwT78ugC0irUkt9xATzvHgjiPcMbS/2aGIiCTSNsk9eFm9tGzZeTT6TiIiOdQWZZmhPcNsfHQf45PprgQ54bK8SJ+ISHbaouV+15MHUk/sAAXLZk14EZGstUVyHxnLZpmADVcuiL6TiEgOtUVZJm0aLSMirU7JPaBgxitfuK7ZYYiI1K0tyjJpURlGRNqFWu6oDCMi7afjk/thrSUjIm1IZRkRkTak5C4i0oaU3EVE2lDL1tyH9gyzedtBjo+MNTsUEZHcacnkPrRnmE1P7GdsfKLZoYiI5FJLlmU2bzuoxC4iUkVkcjezB8zshJm9ENh2vpk9Y2Y/9P6f6203M/szM3vZzJ43s8uzCHo4pVJMb3cxlecREcmbOC33rwHXlG0bAL7rnLsE+K73O8C1wCXev1uAr6QT5nRprNZY7DLuumFpCtGIiORPZHJ3zn0POFW2+Ubg697PXwf6A9v/ypXsAHrN7MK0gvXVs866AX293Wz+6GX0r+hLLygRkRxJ2qH6i8651wCcc6+Z2bu87X1A8PJFx7xtr5U/gZndQql1z8KFC2t68bk9RV4fTbbM7yHNSBWRDpB2h2pYvSS0me2cu985t9I5t3LevHk1vYgukCQiUl3S5P5jv9zi/X/C234MCC6teBFwPHl44bK6OIeISLtImtyfBG72fr4Z+FZg+ye8UTOrgNN++SZNuvidiEh1kTV3M9sCXAVcYGbHgDuBQeARM/sUcAT4qHf3p4DrgJeBUeCTGcQcXueJQQcFEekUkcndObehwk2/EXJfB9xab1BZUaleRDpFS85QTaqvt7vZIYiINETHJPfuYoGNa5c0OwwRkYZoyYXDamHA/N5uNq5doklLItIx2j65a9KSiHSijinLiIh0EiV3EZE2pOQuItKGlNxFRNpQWyf3WV2akyoinamtk/uZSc1JFZHO1NbJXUSkUym5i4i0obZO7qq4i0inauvk/vFVtV2+T0SkXbTl8gMFMzZcuYB7+pc1OxQRkaZou+R+WGvJiIi0d1lGRKRTKbmLiLQhJXcRkTak5C4i0oaU3EVE2pCSu4hIG1JyFxFpQy2Z3AsWvrBApe0iIp2mJZP7hisX1LRdRKTT1JXczew2MztgZi+Y2RYzO9fMFpvZTjP7oZk9bGaz0wrWd0//Mm5atXCqpV4w46ZVC7XcgIiIx5xLdkELM+sD/h/wHufcmJk9AjwFXAc84Zz7ppn9d2Cfc+4r1Z5r5cqVbteuXYniEBHpVGa22zm3Muy2essys4BuM5sF9ACvAWuAx7zbvw701/kaIiJSo8TJ3Tk3DHwROEIpqZ8GdgMjzrkz3t2OAX1hjzezW8xsl5ntOnnyZNIwREQkROLkbmZzgRuBxcB8YA5wbchdQ+s+zrn7nXMrnXMr582blzQMEREJUU9Z5l8Bh5xzJ51z48ATwK8BvV6ZBuAi4HidMYqISI3qSe5HgFVm1mNmBvwG8PfAc8C/9u5zM/Ct+kIUEZFaJR4tA2BmdwPrgTPAHuDfU6qxfxM439t2k3PurYjnOQm8WuUuFwA/SRxothRbMootGcWWTLvG9kvOudC6dl3JvVHMbFel4T7NptiSUWzJKLZkOjG2lpyhKiIi1Sm5i4i0oVZJ7vc3O4AqFFsyii0ZxZZMx8XWEjV3ERGpTau03EVEpAZK7iIibSjXyd3MrjGzg2b2spkNNDmWB8zshJm9ENh2vpk94y1v/Iy3JEMzYltgZs+Z2YveEsyfzkt83jLQ3zezfV5sd3vbM18auoYYC2a2x8y+k6fYzOywme03s71mtsvb1vTP1Iuj18weM7OXvP3uV/MQm5kt8d4v/9/PzOwzeYjNi69hy6TnNrmbWQH4b5TWq3kPsMHM3tPEkL4GXFO2bQD4rnPuEuC73u/NcAa43Tn3K8Aq4FbvvcpDfG8Ba5xzlwHLgWvMbBXwX4H7vNheBz7VhNh8nwZeDPyep9iuds4tD4yDzsNnCvCnwP9xzl0KXEbp/Wt6bM65g977tRx4PzAK/HUeYvOWSf9PwErn3HuBAvAxstrfnHO5/Af8KrAt8PsmYFOTY1oEvBD4/SBwoffzhcDBZr9vXizfAn4zb/FRWhb6B8CVlGbkzQr7rBsc00WUvuxrgO8AlqPYDgMXlG1r+mcK/DPgEN6AjDzFVhbPB4HteYmN0uz9o5Rm78/y9re1We1vuW25c/aN8FVcPriJftE59xqA9/+7mhwPZrYIWAHsJCfxeWWPvcAJ4BngFWIuDd0AXwZ+H5j0fv8F8hObA542s91mdou3LQ+f6cXASeB/euWsvzSzOTmJLehjwBbv56bH5upcJr1WeU7uYVe71rjNKszsHcDjwGeccz9rdjw+59yEK50mXwRcAfxK2N0aGxWY2YeAE8653cHNIXdt1n632jl3OaXS5K1m9i+bFEe5WcDlwFeccyuAN2heeSiUV7e+AXi02bH46l0mvVZ5Tu7HgOAVr/O4fPCPzexCAO//E80KxMyKlBL7Q865J/IWH4BzbgT4G0r9AnlYGno1cIOZHaa02N0aSi35PMSGc+649/8JSnXjK8jHZ3oMOOac2+n9/hilZJ+H2HzXAj9wzv3Y+z0PsTV0mfQ8J/e/Ay7xepJnUzrFerLJMZV7ktKyxtDE5Y3NzICvAi86574UuKnp8ZnZPDPr9X7uprSDv0gOloZ2zm1yzl3knFtEaf961jn38TzEZmZzzOyd/s+U6scvkIPP1Dn3j8BRM1vibfKX+256bAEbOFuSgXzE1thl0pvZ4RGjA+I64B8o1Wj/qMmxbKFUJxun1HL5FKX67HeBH3r/n9+k2P45pVO554G93r/r8hAf8D5KSz8/Tyk5fc7bfjHwfeBlSqfO5zT5870K+E5eYvNi2Of9O+Dv/3n4TL04lgO7vM91CJibo9h6gJ8C5wW25SW2u4GXvO/C/wLOyWp/0/IDIiJtKM9lGRERSUjJXUSkDSm5i4i0ISV3EZE2pOQuItKGlNxFRNqQkruISBv6/9RuGsMtQ2/YAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df.Age, df.Height);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BMI ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.BMI.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "236"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.BMI.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.BMI.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    236.000000\n",
       "mean       8.601695\n",
       "std       20.025363\n",
       "min        0.000000\n",
       "25%        0.000000\n",
       "50%        1.000000\n",
       "75%        1.000000\n",
       "max       80.000000\n",
       "Name: Age, dtype: float64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.BMI.isna()].Age.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BMI is missing for babies, for which the formula does not apply.\n",
    "\n",
    "BMI is calculated as $$BMI = \\frac{weight \\ (km)}{height^2 \\ (m^2)}$$\n",
    "We must be careful because height is represented in centimeters in the dataset. Once we fill the missing values for weight and height, we can fill the BMI in.\n",
    "\n",
    "It relates weight and height, so it may be very useful."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BMICatUnder20yrs ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.BMICatUnder20yrs.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4522"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.BMICatUnder20yrs.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.BMICatUnder20yrs.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Too many values missing, we might just as well ignore this attribute."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BMI_WHO ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.BMI_WHO.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "256"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.BMI_WHO.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is just a reestructuring of the BMI attribute. I wonder wether we need this or not."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Pulse ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Pulse.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "870"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Pulse.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Pulse.isna()].Age.hist(bins=40)\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Values missing for very young people (babies probably)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Age'] <= 10].Pulse.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fill missing values for young (0-10 years) according to the distribution above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df['Age'] > 10].Pulse.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the non-young (>10 yo) use the above distribution."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BPSysAve ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    4369.000000\n",
       "mean      117.683680\n",
       "std        17.390216\n",
       "min        76.000000\n",
       "25%       106.000000\n",
       "50%       115.000000\n",
       "75%       127.000000\n",
       "max       226.000000\n",
       "Name: BPSysAve, dtype: float64"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.BPSysAve.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.BPSysAve.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "877"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.BPSysAve.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    826\n",
       "1     51\n",
       "Name: flu, dtype: int64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.BPSysAve.isna()].flu.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.BPSysAve.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again for missing for babies mostly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age <= 10].BPSysAve.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age > 10].BPSysAve.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BPDiaAve ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    4369.000000\n",
       "mean       66.554131\n",
       "std        14.862799\n",
       "min         0.000000\n",
       "25%        60.000000\n",
       "50%        68.000000\n",
       "75%        76.000000\n",
       "max       116.000000\n",
       "Name: BPDiaAve, dtype: float64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.BPDiaAve.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "0 pressure, what the hell?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.BPDiaAve.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "877"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.BPDiaAve.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing the exact same entries as BPSYSAve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.BPDiaAve.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age <= 10].BPDiaAve.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age > 10].BPDiaAve.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BPSys1, 2, 3 and BPDia1, 2, 3 ####"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This are the mesuramnents which lead to the aforementioned averages, I believe we can ignore them."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Testosterone ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2008.000000\n",
       "mean      190.980538\n",
       "std       225.730181\n",
       "min         0.250000\n",
       "25%        16.905000\n",
       "50%        39.090000\n",
       "75%       351.765000\n",
       "max      1795.600000\n",
       "Name: Testosterone, dtype: float64"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Testosterone.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Testosterone.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3238"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Testosterone.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most values are missing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Cfn1jfR6B1wM/or0wY7nUtV8t7wX+aznUxYvv3j+ewSsVbwP+crGuryN25s7w2xysHlMtw5xUVU8CtO2J4ywmyTrgDOBelkFtbenjfmAfcAfwQ+DZqnqhDRnX8/kp4GPA71r7jcukrgK+lWRnu3UHjP95fDMwDXy+LWN9Nsmxy6Cu2S4Gbmz7Y62rqv4X+BfgCeBJ4DlgJ4t0fR3J4T7SbQ4ESV4LfBX4SFX9bNz1AFTVb2vw3+Y1DG42d+qwYUtZU5L3A/uqaufs7iFDx3GdnV1VZzJYhrwsyTvHUMP+VgBnAtdV1RnALxjP0tBQbe36A8C/jbsWgLbGvxE4BfgD4FgGz+f+FuT6OpLDfbnf5uCpJCcDtO2+cRSR5JUMgv1LVfW15VQbQFU9C9zN4HcCK5PMvLFuHM/n2cAHkjzO4G6m5zCYyY+7Lqpqb9vuY7B+fBbjfx6ngKmqure1b2YQ9uOua8b5wHer6qnWHndd7wF+VFXTVfUb4GvAn7FI19eRHO7L/TYH24FNbX8Tg/XuJZUkwPXArqr65HKpLcmqJCvb/qsZXPS7gLuAD46rrqq6sqrWVNU6BtfTnVX14XHXleTYJK+b2WewjvwgY34eq+rHwJ4kb21d5wI/GHdds3yIF5dkYPx1PQFsSPKa9rM58/1anOtrXL/oWKBfUFwA/DeD9dp/HGMdNzJYQ/sNg9nMZgZrtTuAR9v2+DHU9ecM/ov3AHB/e1ww7tqAPwbua3U9CPxT638z8G1gN4P/Sh8zxuf0XcBty6Gudv7vtcdDM9f6uJ/HVsPpwGR7Lv8dOG6Z1PUa4CfAG2b1LYe6Pg483K77LwLHLNb15e0HJKlDR/KyjCTpIAx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1KH/Bxl613/oS5USAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Testosterone.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I would fit testosterone values with a distribution or ignore them directly."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### DirectChol ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    4337.000000\n",
       "mean        1.357699\n",
       "std         0.387915\n",
       "min         0.390000\n",
       "25%         1.090000\n",
       "50%         1.290000\n",
       "75%         1.580000\n",
       "max         4.030000\n",
       "Name: DirectChol, dtype: float64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.DirectChol.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.DirectChol.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "909"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.DirectChol.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.DirectChol.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing mostly for very young people."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age <= 10].DirectChol.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age > 10].DirectChol.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### TotChol ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    4337.000000\n",
       "mean        4.835764\n",
       "std         1.069526\n",
       "min         1.530000\n",
       "25%         4.090000\n",
       "50%         4.730000\n",
       "75%         5.510000\n",
       "max        13.650000\n",
       "Name: TotChol, dtype: float64"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.TotChol.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.TotChol.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "909"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.TotChol.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Same instances missing as DirectChol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.TotChol.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing mostly for very young people."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age <= 10].TotChol.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age > 10].TotChol.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can either fit with distribution, or predict from `DirectChol`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df.TotChol, df.DirectChol);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`DirectChol` may not be a good predictor."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### UrineVol1 , 2; UrineFlow1, 2 ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.UrineVol1.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "609"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.UrineVol1.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.UrineVol1.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mostly missing for babies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age <= 10].UrineVol1.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.UrineFlow1.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "946"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.UrineFlow1.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing urine flows and volumes may be added using a distribution, or directly ignored."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Diabetes ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Diabetes.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "103"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Diabetes.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Diabetes.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mostly missing for babies. Based in the unbalance of the diabetes values, I believe that the best may be to ignore the attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    344\n",
       "1     58\n",
       "Name: flu, dtype: int64"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Diabetes == 'Yes'].flu.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### DiabetesAge ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    330.000000\n",
       "mean      49.339394\n",
       "std       15.788109\n",
       "min        1.000000\n",
       "25%       41.000000\n",
       "50%       50.000000\n",
       "75%       60.000000\n",
       "max       80.000000\n",
       "Name: DiabetesAge, dtype: float64"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.DiabetesAge.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.DiabetesAge.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4916"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.DiabetesAge.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.DiabetesAge.isna()].Age.hist()\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I believe that it is best to ignore this attribute."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HealthGen ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.HealthGen.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1463"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.HealthGen.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.HealthGen.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mostly missing for babies and young people. We can fill values based on probability."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### DaysMentHlthBad ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3778.000000\n",
       "mean        3.946268\n",
       "std         7.681957\n",
       "min         0.000000\n",
       "25%         0.000000\n",
       "50%         0.000000\n",
       "75%         4.000000\n",
       "max        30.000000\n",
       "Name: DaysMentHlthBad, dtype: float64"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.DaysMentHlthBad.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD4CAYAAAAAczaOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAPtElEQVR4nO3dXYxd1XnG8f8TQ9KKRMIIg6hxaxq5UkjVOsgCJKqKNg1fuTBIpQKpiRtFci5AImou6uQGSoREq3xUkVIqR1gxUhIXFVKsxCpxEVWaixAP1AEclzIlLkxs2ZM6H6BIqUjeXpw17cHMl2fGMz6z/j/p6OzznrXPXkvbfs722vtsp6qQJPXhLSvdAUnS8jH0Jakjhr4kdcTQl6SOGPqS1JFzVroDs7nwwgtr48aNK90NSRopTz/99A+rat10753Vob9x40bGxsZWuhuSNFKS/NdM7zm9I0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTmrf5G7WBt3fH1Ftnvk/vevyHYlaS4e6UtSRwx9SeqIoS9JHTH0Jakjc4Z+kg1JnkxyOMmhJHe1+j1JfpDkYHvcNLTOx5OMJ3khyfVD9RtabTzJjjMzJEnSTOZz9c7rwMeq6pkk7wCeTrK/vffZqvrUcOMklwO3Ae8Gfg345yS/1d7+PPA+YAI4kGRvVX1vKQYiSZrbnKFfVceAY2351SSHgfWzrLIV2FNVPwe+n2QcuLK9N15VLwEk2dPaGvqStExOa04/yUbgPcBTrXRnkmeT7EqyttXWA68MrTbRajPVT93G9iRjScYmJydPp3uSpDnMO/STvB14BPhoVf0UeAB4J7CZwb8EPj3VdJrVa5b6GwtVO6tqS1VtWbdu2v/iUZK0QPP6RW6ScxkE/peq6lGAqjo+9P4XgK+1lxPAhqHVLwWOtuWZ6pKkZTCfq3cCPAgcrqrPDNUvGWp2C/B8W94L3JbkbUkuAzYB3wEOAJuSXJbkrQxO9u5dmmFIkuZjPkf61wAfAJ5LcrDVPgHcnmQzgymaI8BHAKrqUJKHGZygfR24o6p+AZDkTuBxYA2wq6oOLeFYJElzmM/VO99i+vn4fbOscx9w3zT1fbOtJ0k6s/xFriR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SerInKGfZEOSJ5McTnIoyV2tfkGS/UlebM9rWz1JPpdkPMmzSa4Y+qxtrf2LSbaduWFJkqYznyP914GPVdW7gKuBO5JcDuwAnqiqTcAT7TXAjcCm9tgOPACDLwngbuAq4Erg7qkvCknS8pgz9KvqWFU905ZfBQ4D64GtwO7WbDdwc1veCjxUA98Gzk9yCXA9sL+qTlbVj4D9wA1LOhpJ0qxOa04/yUbgPcBTwMVVdQwGXwzARa3ZeuCVodUmWm2muiRpmcw79JO8HXgE+GhV/XS2ptPUapb6qdvZnmQsydjk5OR8uydJmod5hX6ScxkE/peq6tFWPt6mbWjPJ1p9AtgwtPqlwNFZ6m9QVTuraktVbVm3bt3pjEWSNIf5XL0T4EHgcFV9ZuitvcDUFTjbgMeG6h9sV/FcDfykTf88DlyXZG07gXtdq0mSlsk582hzDfAB4LkkB1vtE8D9wMNJPgy8DNza3tsH3ASMAz8DPgRQVSeTfBI40NrdW1Unl2QUkqR5mTP0q+pbTD8fD/DeadoXcMcMn7UL2HU6HZQkLR1/kStJHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkfmDP0ku5KcSPL8UO2eJD9IcrA9bhp67+NJxpO8kOT6ofoNrTaeZMfSD0WSNJf5HOl/Ebhhmvpnq2pze+wDSHI5cBvw7rbO3yZZk2QN8HngRuBy4PbWVpK0jM6Zq0FVfTPJxnl+3lZgT1X9HPh+knHgyvbeeFW9BJBkT2v7vdPusSRpwRYzp39nkmfb9M/aVlsPvDLUZqLVZqq/SZLtScaSjE1OTi6ie5KkUy009B8A3glsBo4Bn271TNO2Zqm/uVi1s6q2VNWWdevWLbB7kqTpzDm9M52qOj61nOQLwNfaywlgw1DTS4GjbXmmuiRpmSzoSD/JJUMvbwGmruzZC9yW5G1JLgM2Ad8BDgCbklyW5K0MTvbuXXi3JUkLMeeRfpKvANcCFyaZAO4Grk2ymcEUzRHgIwBVdSjJwwxO0L4O3FFVv2ifcyfwOLAG2FVVh5Z8NJKkWc3n6p3bpyk/OEv7+4D7pqnvA/adVu8kSUvKX+RKUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktSROUM/ya4kJ5I8P1S7IMn+JC+257WtniSfSzKe5NkkVwyts621fzHJtjMzHEnSbOZzpP9F4IZTajuAJ6pqE/BEew1wI7CpPbYDD8DgSwK4G7gKuBK4e+qLQpK0fOYM/ar6JnDylPJWYHdb3g3cPFR/qAa+DZyf5BLgemB/VZ2sqh8B+3nzF4kk6Qxb6Jz+xVV1DKA9X9Tq64FXhtpNtNpM9TdJsj3JWJKxycnJBXZPkjSdpT6Rm2lqNUv9zcWqnVW1paq2rFu3bkk7J0m9W2joH2/TNrTnE60+AWwYancpcHSWuiRpGS009PcCU1fgbAMeG6p/sF3FczXwkzb98zhwXZK17QTuda0mSVpG58zVIMlXgGuBC5NMMLgK537g4SQfBl4Gbm3N9wE3AePAz4APAVTVySSfBA60dvdW1aknhyVJZ9icoV9Vt8/w1nunaVvAHTN8zi5g12n1TpK0pPxFriR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHTH0Jakjhr4kdcTQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SeqIoS9JHVlU6Cc5kuS5JAeTjLXaBUn2J3mxPa9t9ST5XJLxJM8muWIpBiBJmr+lONL/g6raXFVb2usdwBNVtQl4or0GuBHY1B7bgQeWYNuSpNNwJqZ3tgK72/Ju4Oah+kM18G3g/CSXnIHtS5JmsNjQL+AbSZ5Osr3VLq6qYwDt+aJWXw+8MrTuRKu9QZLtScaSjE1OTi6ye5KkYecscv1rqupokouA/Un+fZa2maZWbypU7QR2AmzZsuVN70uSFm5RR/pVdbQ9nwC+ClwJHJ+atmnPJ1rzCWDD0OqXAkcXs31J0ulZ8JF+kvOAt1TVq235OuBeYC+wDbi/PT/WVtkL3JlkD3AV8JOpaaDVZuOOr6/Yto/c//4V27aks99ipncuBr6aZOpzvlxV/5TkAPBwkg8DLwO3tvb7gJuAceBnwIcWsW1J0gIsOPSr6iXgd6ep/zfw3mnqBdyx0O1JkhbPX+RKUkcMfUnqiKEvSR0x9CWpI4a+JHXE0Jekjhj6ktQRQ1+SOmLoS1JHDH1J6oihL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjpi6EtSRwx9SerIYv6PXEla9Tbu+PqKbPfI/e8/I5/rkb4kdcTQl6SOOL2zyqy2f4pKWloe6UtSRwx9SeqIoS9JHTH0JakjnsjVkvAEsjQaDH1pgfyi0ygy9DXSVip4V9JKjtkvnNHnnL4kdcTQl6SOLHvoJ7khyQtJxpPsWO7tS1LPljX0k6wBPg/cCFwO3J7k8uXsgyT1bLlP5F4JjFfVSwBJ9gBbge8tcz8kLUCPJ85Xm+UO/fXAK0OvJ4Crhhsk2Q5sby9fS/LCIrZ3IfDDRax/tlgt4wDHcrZaLWNZLeMgf7WosfzGTG8sd+hnmlq94UXVTmDnkmwsGauqLUvxWStptYwDHMvZarWMZbWMA87cWJb7RO4EsGHo9aXA0WXugyR1a7lD/wCwKcllSd4K3AbsXeY+SFK3lnV6p6peT3In8DiwBthVVYfO4CaXZJroLLBaxgGO5Wy1WsayWsYBZ2gsqaq5W0mSVgV/kStJHTH0JakjqzL0V9OtHpIcSfJckoNJxla6P6cjya4kJ5I8P1S7IMn+JC+257Ur2cf5mmEs9yT5Qds3B5PctJJ9nI8kG5I8meRwkkNJ7mr1kdsvs4xlFPfLryT5TpLvtrH8ZatfluSptl/+vl0As7htrbY5/Xarh/8A3sfgEtEDwO1VNZK/+k1yBNhSVSP3g5Mkvw+8BjxUVb/dan8NnKyq+9sX8tqq+ouV7Od8zDCWe4DXqupTK9m305HkEuCSqnomyTuAp4GbgT9jxPbLLGP5E0ZvvwQ4r6peS3Iu8C3gLuDPgUerak+SvwO+W1UPLGZbq/FI//9u9VBV/wNM3epBy6yqvgmcPKW8Fdjdlncz+Et61pthLCOnqo5V1TNt+VXgMINfyo/cfpllLCOnBl5rL89tjwL+EPiHVl+S/bIaQ3+6Wz2M5B+EpoBvJHm63aJi1F1cVcdg8JcWuGiF+7NYdyZ5tk3/nPVTIsOSbATeAzzFiO+XU8YCI7hfkqxJchA4AewH/hP4cVW93posSZatxtCf81YPI+aaqrqCwZ1J72jTDDo7PAC8E9gMHAM+vbLdmb8kbwceAT5aVT9d6f4sxjRjGcn9UlW/qKrNDO5UcCXwrumaLXY7qzH0V9WtHqrqaHs+AXyVwR+GUXa8zcVOzcmeWOH+LFhVHW9/UX8JfIER2TdtzvgR4EtV9Wgrj+R+mW4so7pfplTVj4F/Aa4Gzk8y9SPaJcmy1Rj6q+ZWD0nOayeoSHIecB3w/OxrnfX2Atva8jbgsRXsy6JMhWRzCyOwb9oJwweBw1X1maG3Rm6/zDSWEd0v65Kc35Z/FfgjBucongT+uDVbkv2y6q7eAWiXaP0N/3+rh/tWuEsLkuQ3GRzdw+CWGV8epbEk+QpwLYPb3R4H7gb+EXgY+HXgZeDWqjrrT5DOMJZrGUwhFHAE+MjUvPjZKsnvAf8KPAf8spU/wWAufKT2yyxjuZ3R2y+/w+BE7RoGB+MPV9W9LQP2ABcA/wb8aVX9fFHbWo2hL0ma3mqc3pEkzcDQl6SOGPqS1BFDX5I6YuhLUkcMfUnqiKEvSR35X3TQeEQF42spAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.DaysMentHlthBad.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1468"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.DaysMentHlthBad.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.DaysMentHlthBad.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing mostly for young people. We can fill values based on probability."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### LittleInterest ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.LittleInterest.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1954"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.LittleInterest.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.LittleInterest.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mostly missing in young people, we may fill based on probability."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Depressed ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Depressed.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1951"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Depressed.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Depressed.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once again young people. Fill by probabiltiy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### nPregnancies ####\n",
    "Careful, human males cannot get pregnant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1283.000000\n",
       "mean        3.060016\n",
       "std         1.738878\n",
       "min         1.000000\n",
       "25%         2.000000\n",
       "50%         3.000000\n",
       "75%         4.000000\n",
       "max        13.000000\n",
       "Name: nPregnancies, dtype: float64"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.nPregnancies.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3963"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.nPregnancies.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.nPregnancies.isna()].female.hist()\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mostly missing for males. Let's see for females how do we carry this out."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAOjElEQVR4nO3df6ye5V3H8fdHyn6xH4VRCLaNh2XN3LI4ICdYJTFKN8OArPwxEszcmtmk/6Ayt2Tr9A9jYkwXzdiIBtMArlPcRhgLDeBcU1gWE8EdNmSwTlsR6bGVnsmPbZKpuK9/nKvz0J7T85zzPKcP5/L9Sk7u+/7e1+n9vdPTz7nO1ft5TqoKSVJffmLcDUiSRs9wl6QOGe6S1CHDXZI6ZLhLUofWjLsBgHPPPbcmJibG3YYkrSoPP/zwd6tq3XznXhbhPjExwdTU1LjbkKRVJcm/LHTOZRlJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SerQy+IVqsOY2Hnv2K795K6rxnZtSToVZ+6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwYK9yRPJvlWkkeSTLXaOUn2JTnYtme3epLclORQkkeTXLKSNyBJOtlSZu6/VFUXVdVkO94J7K+qTcD+dgzwbmBT+9gB3DyqZiVJgxlmWWYrsKft7wGumVP/bM16EFib5IIhriNJWqJBw72AryR5OMmOVju/qo4CtO15rb4eODznc6db7SWS7EgylWRqZmZmed1Lkua1ZsBxl1XVkSTnAfuSfOcUYzNPrU4qVO0GdgNMTk6edF6StHwDzdyr6kjbHgO+BFwKPH18uaVtj7Xh08DGOZ++ATgyqoYlSYtbNNyTnJXkdcf3gV8GHgP2AtvasG3A3W1/L/CB9tTMZuD548s3kqTTY5BlmfOBLyU5Pv4vq+rLSb4O3JFkO/AUcG0bfx9wJXAIeAH44Mi7liSd0qLhXlVPAO+Yp/7vwJZ56gVcP5LuJEnL4itUJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1KGBwz3JGUm+meSednxhkoeSHEzyhSSvaPVXtuND7fzEyrQuSVrIUmbuNwAH5hx/ArixqjYBzwLbW3078GxVvRm4sY2TJJ1GA4V7kg3AVcAt7TjA5cCdbcge4Jq2v7Ud085vaeMlSafJoDP3TwEfBX7Ujt8IPFdVL7bjaWB9218PHAZo559v418iyY4kU0mmZmZmltm+JGk+i4Z7kquBY1X18NzyPENrgHP/V6jaXVWTVTW5bt26gZqVJA1mzQBjLgPek+RK4FXA65mdya9NsqbNzjcAR9r4aWAjMJ1kDfAG4JmRdy5JWtCiM/eq+nhVbaiqCeA64P6qeh/wAPDeNmwbcHfb39uOaefvr6qTZu6SpJUzzHPuHwM+nOQQs2vqt7b6rcAbW/3DwM7hWpQkLdUgyzI/VlVfBb7a9p8ALp1nzA+Ba0fQmyRpmXyFqiR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA6tGXcDq9nEznvHct0nd101lutKWj0WnbkneVWSv0vy90keT/J7rX5hkoeSHEzyhSSvaPVXtuND7fzEyt6CJOlEgyzL/CdweVW9A7gIuCLJZuATwI1VtQl4Ftjexm8Hnq2qNwM3tnGSpNNo0XCvWT9oh2e2jwIuB+5s9T3ANW1/azumnd+SJCPrWJK0qIH+QzXJGUkeAY4B+4B/Ap6rqhfbkGlgfdtfDxwGaOefB944z5+5I8lUkqmZmZnh7kKS9BIDhXtV/U9VXQRsAC4F3jrfsLadb5ZeJxWqdlfVZFVNrlu3btB+JUkDWNKjkFX1HPBVYDOwNsnxp202AEfa/jSwEaCdfwPwzCialSQNZpCnZdYlWdv2Xw28EzgAPAC8tw3bBtzd9ve2Y9r5+6vqpJm7JGnlDPKc+wXAniRnMPvN4I6quifJt4HPJ/l94JvArW38rcCfJznE7Iz9uhXoW5J0CouGe1U9Clw8T/0JZtffT6z/ELh2JN1JkpbFtx+QpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShxYN9yQbkzyQ5ECSx5Pc0OrnJNmX5GDbnt3qSXJTkkNJHk1yyUrfhCTppQaZub8IfKSq3gpsBq5P8jZgJ7C/qjYB+9sxwLuBTe1jB3DzyLuWJJ3SouFeVUer6htt//vAAWA9sBXY04btAa5p+1uBz9asB4G1SS4YeeeSpAUtac09yQRwMfAQcH5VHYXZbwDAeW3YeuDwnE+bbrUT/6wdSaaSTM3MzCy9c0nSgtYMOjDJa4EvAh+qqu8lWXDoPLU6qVC1G9gNMDk5edJ5LWxi571ju/aTu64a27UlDW6gmXuSM5kN9tur6q5Wfvr4ckvbHmv1aWDjnE/fABwZTbuSpEEM8rRMgFuBA1X1yTmn9gLb2v424O459Q+0p2Y2A88fX76RJJ0egyzLXAa8H/hWkkda7beBXcAdSbYDTwHXtnP3AVcCh4AXgA+OtGNJ0qIWDfeq+hvmX0cH2DLP+AKuH7IvSdIQfIWqJHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOrRouCe5LcmxJI/NqZ2TZF+Sg217dqsnyU1JDiV5NMklK9m8JGl+g8zcPwNccUJtJ7C/qjYB+9sxwLuBTe1jB3DzaNqUJC3FouFeVV8DnjmhvBXY0/b3ANfMqX+2Zj0IrE1ywaialSQNZrlr7udX1VGAtj2v1dcDh+eMm261kyTZkWQqydTMzMwy25AkzWfNiP+8zFOr+QZW1W5gN8Dk5OS8Y/TyM7Hz3rFc98ldV43lutJqtdyZ+9PHl1va9lirTwMb54zbABxZfnuSpOVYbrjvBba1/W3A3XPqH2hPzWwGnj++fCNJOn0WXZZJ8jngF4Fzk0wDvwvsAu5Ish14Cri2Db8PuBI4BLwAfHAFepYkLWLRcK+qX1ng1JZ5xhZw/bBNSZKG4ytUJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ6N+V0hpRfhulNLSOHOXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDPucuncK4nq8Hn7HXcJy5S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SerQirz9QJIrgE8DZwC3VNWulbiOpNHzLRf6MPJwT3IG8CfAu4Bp4OtJ9lbVt0d9Laln4wxZrX4rMXO/FDhUVU8AJPk8sBUw3CWd0v/Hb2gr9dPKSoT7euDwnONp4GdPHJRkB7CjHf4gyT+sQC+jdC7w3XE3MQK93Ad4Ly9XvdzLabmPfGKoT/+phU6sRLhnnlqdVKjaDexegeuviCRTVTU57j6G1ct9gPfyctXLvaz2+1iJp2WmgY1zjjcAR1bgOpKkBaxEuH8d2JTkwiSvAK4D9q7AdSRJCxj5skxVvZjk14G/ZvZRyNuq6vFRX2cMVs0S0iJ6uQ/wXl6uermXVX0fqTppOVyStMr5ClVJ6pDhLkkdMtxPIcnGJA8kOZDk8SQ3jLunYSU5I8k3k9wz7l6GkWRtkjuTfKf9/fzcuHtajiS/1b62HkvyuSSvGndPg0pyW5JjSR6bUzsnyb4kB9v27HH2OKgF7uUP29fXo0m+lGTtOHtcKsP91F4EPlJVbwU2A9cneduYexrWDcCBcTcxAp8GvlxVPw28g1V4T0nWA78JTFbV25l9AOG68Xa1JJ8BrjihthPYX1WbgP3teDX4DCffyz7g7VX1M8A/Ah8/3U0Nw3A/hao6WlXfaPvfZzZA1o+3q+VLsgG4Crhl3L0MI8nrgV8AbgWoqv+qqufG29WyrQFenWQN8BpW0WtCquprwDMnlLcCe9r+HuCa09rUMs13L1X1lap6sR0+yOxrdlYNw31ASSaAi4GHxtvJUD4FfBT40bgbGdKbgBngz9oS0y1Jzhp3U0tVVf8K/BHwFHAUeL6qvjLeroZ2flUdhdnJEXDemPsZlV8D/mrcTSyF4T6AJK8Fvgh8qKq+N+5+liPJ1cCxqnp43L2MwBrgEuDmqroY+A9Wz4//P9bWo7cCFwI/CZyV5FfH25VOlOR3mF2ivX3cvSyF4b6IJGcyG+y3V9Vd4+5nCJcB70nyJPB54PIkfzHelpZtGpiuquM/Rd3JbNivNu8E/rmqZqrqv4G7gJ8fc0/DejrJBQBte2zM/QwlyTbgauB9tcpeFGS4n0KSMLuue6CqPjnufoZRVR+vqg1VNcHsf9rdX1WrcpZYVf8GHE7yllbawup8S+mngM1JXtO+1rawCv9j+AR7gW1tfxtw9xh7GUr7pUMfA95TVS+Mu5+lMtxP7TLg/czOch9pH1eOuykB8BvA7UkeBS4C/mDM/SxZ+8njTuAbwLeY/fe4al7ynuRzwN8Cb0kynWQ7sAt4V5KDzP7CnlXxW9gWuJc/Bl4H7Gv/9v90rE0ukW8/IEkdcuYuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KH/hfD5nGQIZhICwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.female == 1].nPregnancies.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1370"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.female==1) & (df.nPregnancies.isna())].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df.female==1) & (df.nPregnancies.isna())].Age.hist()\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could set nPregnancies as 0 if the girl is younger than 20yo, and fill by probability the rest.\n",
    "\n",
    "Is any guy pregnant?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: nPregnancies, dtype: int64)"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.female==0].nPregnancies.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "No guy is pregnant!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### nBabies ####"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's check correlation with number of pregnancies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x40376ddfd0>"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df.nPregnancies, df.nBabies)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see some abortions. I believe the number of pregnancies generates more information. We could also create a feature for the number of abortions and ignore nBabies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1471"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.female == 1) & df.nBabies.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Age1stBaby ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.female==1].Age1stBaby.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1712"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.female==1) & (df.Age1stBaby.isna())].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df.female==1) & (df.Age1stBaby.isna())].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could ignore this attribute, or fill it with probability if the woman has had a baby."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SleepHrsNight ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    3879.000000\n",
       "mean        6.913895\n",
       "std         1.356630\n",
       "min         2.000000\n",
       "25%         6.000000\n",
       "50%         7.000000\n",
       "75%         8.000000\n",
       "max        12.000000\n",
       "Name: SleepHrsNight, dtype: float64"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.SleepHrsNight.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SleepHrsNight.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1367"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SleepHrsNight.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SleepHrsNight.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mostly missing for very young people. We can fill in some values from the internet maybe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Age <= 20].SleepHrsNight.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SleepHrsNight.notna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SleepTrouble ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SleepTrouble.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1356"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SleepTrouble.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SleepTrouble.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing values for people younger than 16yo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SleepTrouble.notna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PhysActive ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.PhysActive.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1042"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.PhysActive.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.PhysActive.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Only missing for very young people. They are kids, so we may assume they ar physically active."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PhysActiveDays ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2374.000000\n",
       "mean        3.747683\n",
       "std         1.850486\n",
       "min         1.000000\n",
       "25%         2.000000\n",
       "50%         3.000000\n",
       "75%         5.000000\n",
       "max         7.000000\n",
       "Name: PhysActiveDays, dtype: float64"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.PhysActiveDays.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Po9gA7G3v/r8GuKOq1vQjhJ04G7hr4R6CdcAXquprk21pZH8FfL5NZzwOXDfhfkaW5PXAnwJ/uSLHX6uPQkqSjs9pGUnqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOvS/dlSa1v5IBEgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.PhysActiveDays.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2872"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.PhysActiveDays.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.PhysActiveDays.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing values for all age values. Filling through distribution does not seem feasible, plus there are many missing values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### TVHrsDay / TVHrsDayChild ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.TVHrsDay.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2829"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.TVHrsDay.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAOdElEQVR4nO3dbYxmZX3H8e+vLKBgy/IwELq7djBuLKQpD93QtTSNBdvyYFheSIIxdWM22Tc0xWpilzZpY9IXkDRiTRoSItbVGJSiFoKmliyQpk3E7sqD4EpZcQtTKLtWwFqiFf33xX1NGJZZZmZn7j33XH4/yZ37XNe55j7/mXPmN2euOfeZVBWSpL78wtAFSJJWnuEuSR0y3CWpQ4a7JHXIcJekDq0ZugCA0047raanp4cuQ5JWlT179nyvqqbmWzcR4T49Pc3u3buHLkOSVpUk/3G4dU7LSFKHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShybiHarLMb3jy4Nte/8NVwy2bUl6PZ65S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOLTrckxyT5MEkd7f2WUkeSPJEks8nOa71H9/a+9r66fGULkk6nKWcuV8H7J3TvhG4qao2As8D21r/NuD5qnorcFMbJ0k6ihYV7knWA1cAn2jtABcDd7QhO4Gr2vKW1qatv6SNlyQdJYs9c/8Y8GHgZ619KvBCVb3c2jPAura8DngaoK1/sY2XJB0lC4Z7kncBB6pqz9zueYbWItbNfd3tSXYn2X3w4MFFFStJWpzFnLlfBFyZZD/wOUbTMR8D1iaZ/R+s64Fn2vIMsAGgrT8J+P6hL1pVt1TVpqraNDU1taxPQpL0aguGe1VdX1Xrq2oauAa4t6reC9wHvLsN2wrc2Zbvam3a+nur6jVn7pKk8VnOde5/CnwwyT5Gc+q3tv5bgVNb/weBHcsrUZK0VGsWHvKKqrofuL8tPwlcOM+YHwFXr0BtkqQj5DtUJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDa4YuYDWb3vHlQba7/4YrBtmupNXDM3dJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHfL2A6vQULc9AG99IK0WnrlLUocWDPckb0jy9SQPJ3ksyUda/1lJHkjyRJLPJzmu9R/f2vva+unxfgqSpEMt5sz9x8DFVXUucB5waZLNwI3ATVW1EXge2NbGbwOer6q3Aje1cZKko2jBcK+RH7bmse1RwMXAHa1/J3BVW97S2rT1lyTJilUsSVrQoubckxyT5CHgAHAP8B3ghap6uQ2ZAda15XXA0wBt/YvAqStZtCTp9S3qapmq+ilwXpK1wJeAs+cb1p7nO0uvQzuSbAe2A7z5zW9eVLEanv+gRFodlnS1TFW9ANwPbAbWJpn94bAeeKYtzwAbANr6k4Dvz/Nat1TVpqraNDU1dWTVS5LmtZirZabaGTtJ3gi8E9gL3Ae8uw3bCtzZlu9qbdr6e6vqNWfukqTxWcy0zJnAziTHMPphcHtV3Z3kW8DnkvwV8CBwaxt/K/CZJPsYnbFfM4a6JUmvY8Fwr6pHgPPn6X8SuHCe/h8BV69IdZKkI+I7VCWpQ4a7JHXIG4dpVRjyZmlD8fJPLYdn7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdcjr3KUJ5e2VtRyeuUtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1aM3QBUjS0KZ3fHmwbe+/4YqxvK5n7pLUIcNdkjrktIykV+lxiuLnkWfuktQhw12SOmS4S1KHFgz3JBuS3Jdkb5LHklzX+k9Jck+SJ9rzya0/ST6eZF+SR5JcMO5PQpL0aos5c38Z+FBVnQ1sBq5Ncg6wA9hVVRuBXa0NcBmwsT22AzeveNWSpNe1YLhX1bNV9Y22/D/AXmAdsAXY2YbtBK5qy1uAT9fI14C1Sc5c8colSYe1pDn3JNPA+cADwBlV9SyMfgAAp7dh64Cn53zYTOs79LW2J9mdZPfBgweXXrkk6bAWHe5J3gR8AfhAVf3g9YbO01ev6ai6pao2VdWmqampxZYhSVqERYV7kmMZBftnq+qLrfu52emW9nyg9c8AG+Z8+HrgmZUpV5K0GIu5WibArcDeqvronFV3AVvb8lbgzjn972tXzWwGXpydvpEkHR2Luf3ARcAfAt9M8lDr+zPgBuD2JNuAp4Cr27qvAJcD+4CXgPevaMWSpAUtGO5V9S/MP48OcMk84wu4dpl1SZKWwXeoSlKHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA75b/YkTYwh/8Vfbzxzl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQwuGe5JPJjmQ5NE5fackuSfJE+355NafJB9Psi/JI0kuGGfxkqT5LebM/VPApYf07QB2VdVGYFdrA1wGbGyP7cDNK1OmJGkpFgz3qvpn4PuHdG8BdrblncBVc/o/XSNfA9YmOXOlipUkLc6RzrmfUVXPArTn01v/OuDpOeNmWt9rJNmeZHeS3QcPHjzCMiRJ81npP6hmnr6ab2BV3VJVm6pq09TU1AqXIUk/34403J+bnW5pzwda/wywYc649cAzR16eJOlIHGm43wVsbctbgTvn9L+vXTWzGXhxdvpGknT0rFloQJLbgHcApyWZAf4SuAG4Pck24Cng6jb8K8DlwD7gJeD9Y6hZkrSABcO9qt5zmFWXzDO2gGuXW5QkaXl8h6okdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6tBYwj3JpUkeT7IvyY5xbEOSdHgrHu5JjgH+FrgMOAd4T5JzVno7kqTDG8eZ+4XAvqp6sqr+D/gcsGUM25EkHcaaMbzmOuDpOe0Z4DcPHZRkO7C9NX+Y5PEj3N5pwPeO8GPHybqWxrqWblJrs64lyI3LqutXDrdiHOGeefrqNR1VtwC3LHtjye6q2rTc11lp1rU01rV0k1qbdS3NuOoax7TMDLBhTns98MwYtiNJOoxxhPu/ARuTnJXkOOAa4K4xbEeSdBgrPi1TVS8n+SPgq8AxwCer6rGV3s4cy57aGRPrWhrrWrpJrc26lmYsdaXqNdPhkqRVzneoSlKHDHdJ6tCqDvdJuc1Bkk8mOZDk0Tl9pyS5J8kT7fnkAerakOS+JHuTPJbkukmoLckbknw9ycOtro+0/rOSPNDq+nz7g/xRl+SYJA8muXtS6kqyP8k3kzyUZHfrm4RjbG2SO5J8ux1nbx+6riRva1+n2ccPknxg6LpabX/SjvlHk9zWvhfGcnyt2nCfsNscfAq49JC+HcCuqtoI7Grto+1l4ENVdTawGbi2fY2Gru3HwMVVdS5wHnBpks3AjcBNra7ngW1Hua5Z1wF757Qnpa7frarz5lwTPfR+BPgb4B+r6leBcxl93Qatq6oeb1+n84DfAF4CvjR0XUnWAX8MbKqqX2N0wck1jOv4qqpV+QDeDnx1Tvt64PoB65kGHp3Tfhw4sy2fCTw+AV+zO4Hfm6TagBOAbzB6F/P3gDXz7d+jWM96Rt/4FwN3M3pT3iTUtR847ZC+Qfcj8EvAd2kXZkxKXYfU8vvAv05CXbzy7v1TGF2peDfwB+M6vlbtmTvz3+Zg3UC1zOeMqnoWoD2fPmQxSaaB84EHmIDa2tTHQ8AB4B7gO8ALVfVyGzLU/vwY8GHgZ6196oTUVcA/JdnTbt0Bw+/HtwAHgb9r01ifSHLiBNQ11zXAbW150Lqq6j+BvwaeAp4FXgT2MKbjazWH+6JucyBI8ibgC8AHquoHQ9cDUFU/rdGvzesZ3Wzu7PmGHc2akrwLOFBVe+Z2zzN0iOPsoqq6gNE05LVJfmeAGg61BrgAuLmqzgf+l2GmhubV5q6vBP5+6FoA2hz/FuAs4JeBExntz0OtyPG1msN90m9z8FySMwHa84EhikhyLKNg/2xVfXGSagOoqheA+xn9TWBtktk31g2xPy8Crkyyn9HdTC9mdCY/dF1U1TPt+QCj+eMLGX4/zgAzVfVAa9/BKOyHrmvWZcA3quq51h66rncC362qg1X1E+CLwG8xpuNrNYf7pN/m4C5ga1veymi++6hKEuBWYG9VfXRSaksylWRtW34jo4N+L3Af8O6h6qqq66tqfVVNMzqe7q2q9w5dV5ITk/zi7DKjeeRHGXg/VtV/AU8neVvrugT41tB1zfEeXpmSgeHregrYnOSE9r05+/Uaz/E11B86VugPFJcD/85ovvbPB6zjNkZzaD9hdDazjdFc7S7gifZ8ygB1/TajX/EeAR5qj8uHrg34deDBVtejwF+0/rcAXwf2MfpV+vgB9+k7gLsnoa62/Yfb47HZY33o/dhqOA/Y3fblPwAnT0hdJwD/DZw0p28S6voI8O123H8GOH5cx5e3H5CkDq3maRlJ0mEY7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalD/w9OM/LAXOzd9QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.TVHrsDay.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.TVHrsDay.notna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    417.000000\n",
       "mean       1.966427\n",
       "std        1.400146\n",
       "min        0.000000\n",
       "25%        1.000000\n",
       "50%        2.000000\n",
       "75%        3.000000\n",
       "max        6.000000\n",
       "Name: TVHrsDayChild, dtype: float64"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.TVHrsDayChild.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.TVHrsDayChild.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan,  5.,  1.,  4.,  0.,  6.,  3.,  2.])"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.TVHrsDayChild.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could merge both columns keeping the categories in `TVHrsDay`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2412"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.TVHrsDay.isna()) & (df.TVHrsDayChild.isna())].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A lot of entries with values for both attributes missing. We should drop them out."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### CompHrsDay / CompHrsDayChild ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.CompHrsDay.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.CompHrsDayChild.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan,  0.,  6.,  3.,  1.,  2.,  5.,  4.])"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.CompHrsDayChild.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2410"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.CompHrsDay.isna()) & (df.CompHrsDayChild.isna())].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Many missing values, either merge and fill based on probability, or not take into account."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Alcohol12PlusYr ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Alcohol12PlusYr.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2014"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Alcohol12PlusYr.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Alcohol12PlusYr.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing mostly for young people. We can assume that until 16 they don't have alcohol, and if they are >= 16 then use the probabilities above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### AlcoholDay ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2404.000000\n",
       "mean        2.959651\n",
       "std         3.522538\n",
       "min         1.000000\n",
       "25%         1.000000\n",
       "50%         2.000000\n",
       "75%         3.000000\n",
       "max        82.000000\n",
       "Name: AlcoholDay, dtype: float64"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.AlcoholDay.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan,  2.,  3.,  1.,  6., 12.,  4.,  5.,  7., 20.,  8., 10., 16.,\n",
       "       15., 13., 36., 24.,  9., 82., 64., 30., 18., 11., 21., 14.])"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.AlcoholDay.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Y83NYVf8JPJnk5a10DYOfSR9rX83N/HBqB8bf0xPA5iQvbn+Tc4/V6PetcXzAcg4+JLkB+DcGc8J/PMY+7mIwX/d9Bu+CbmEwJ7wPONSWF4+4p19l8C/jo8Aj7XTDBPT1S8AXW18HgD9p9ZcBnwcOM/jX/EVjei6vBu6bhJ7a9r/UTo/N7ePjfg5bDxuB6fY8/iOwctx9MTgw4FvATw3VJuGxegfw1ba//y3wonHsW/4MgyR15HyY3pEkLZKhL0kdMfQlqSOGviR1xNCXpI4Y+pLUEUNfkjryf86XT+ySWUdlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.AlcoholDay.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2842"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.AlcoholDay.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.AlcoholDay.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing for all ages. Below 16, put a 0. Otherwise, if they are doing alcohol (`Alcohol12PlusYr`) put somethong according to probabilities above, and if not just put 0."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### AlcoholYear ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2882.000000\n",
       "mean       72.353921\n",
       "std       101.779814\n",
       "min         0.000000\n",
       "25%         3.000000\n",
       "50%        24.000000\n",
       "75%       104.000000\n",
       "max       364.000000\n",
       "Name: AlcoholYear, dtype: float64"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.AlcoholYear.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.,  20.,  nan,  52., 100., 104., 364.,  12., 312., 156.,   5.,\n",
       "         1., 183.,   3., 200.,   2., 260.,  24., 208.,  14.,   9.,  36.,\n",
       "        60.,   6.,   4.,  96.,  30.,  48.,  72., 300., 180.,   8.,   7.,\n",
       "        65., 240.,  25.,  10.,  90.,  13., 270.,  84.,  28., 168.,  15.,\n",
       "        56., 108., 288., 144., 120.,  35., 360., 182.,  40., 220., 138.,\n",
       "        45.])"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.AlcoholYear.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD4CAYAAAAAczaOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAULElEQVR4nO3dfZBd9X3f8fenksGxnViAFpdImkokygPxuLZGwbRuPa6JeXLGIjMwIyYtGpcZTROcOnXTGOqZkCbDDE7b0DJxyShBQbQeMCVO0DSkRAVcpjPlYbF5xpgtULRGQevhIUk9wcH+9o/7k7ms7u5q967uXem8XzM795zv+d093z3Sfu7Z3304qSokSd3wt8bdgCRpdAx9SeoQQ1+SOsTQl6QOMfQlqUNWj7uB+axdu7Y2btw47jYk6Zjy0EMPfauqJgZtW9Ghv3HjRiYnJ8fdhiQdU5L837m2Ob0jSR1i6EtShxj6ktQhhr4kdYihL0kdYuhLUocY+pLUIYa+JHWIoS9JHbKi35E7rI1X/MlY9vv8NR8fy34laSGe6UtShxj6ktQhhr4kdYihL0kdsmDoJ9md5GCSx2fVfynJ00meSPJbffUrk0y1bef21c9rtakkVyzvjyFJOhJH8uqdG4HfAW46VEjyj4BtwPuq6vUkp7b6GcB24KeAHwb+R5Ifa3f7AvAxYBp4MMneqnpyuX4QSdLCFgz9qro3ycZZ5V8Arqmq19uYg62+Dbil1Z9LMgWc2bZNVdWzAEluaWMNfUkaoaXO6f8Y8A+T3J/kfyb56VZfB+zvGzfdanPVD5NkZ5LJJJMzMzNLbE+SNMhSQ381cBJwFvCvgFuTBMiAsTVP/fBi1a6q2lpVWycmBl7iUZK0REt9R+408OWqKuCBJN8D1rb6hr5x64EX2/JcdUnSiCz1TP+PgY8CtCdqTwC+BewFtic5MckmYDPwAPAgsDnJpiQn0Huyd++wzUuSFmfBM/0kNwMfAdYmmQauAnYDu9vLOL8D7Ghn/U8kuZXeE7RvAJdX1Xfb9/kUcCewCthdVU8chZ9HkjSPI3n1ziVzbPrHc4y/Grh6QP0O4I5FdSdJWla+I1eSOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqkAVDP8nuJAfbVbJmb/uVJJVkbVtPkuuSTCV5NMmWvrE7kjzTvnYs748hSToSR3KmfyNw3uxikg3Ax4AX+srn07su7mZgJ3B9G3syvcssfhA4E7gqyUnDNC5JWrwFQ7+q7gVeHrDpWuBXgeqrbQNuqp77gDVJTgPOBfZV1ctV9QqwjwEPJJKko2tJc/pJPgF8s6oembVpHbC/b3261eaqD/reO5NMJpmcmZlZSnuSpDksOvSTvAP4HPBrgzYPqNU89cOLVbuqamtVbZ2YmFhse5KkeSzlTP9HgE3AI0meB9YDX03yt+mdwW/oG7seeHGeuiRphBYd+lX1WFWdWlUbq2ojvUDfUlV/DuwFLm2v4jkLeK2qDgB3AuckOak9gXtOq0mSRuhIXrJ5M/C/gR9PMp3ksnmG3wE8C0wBvwf8IkBVvQz8JvBg+/qNVpMkjdDqhQZU1SULbN/Yt1zA5XOM2w3sXmR/kqRl5DtyJalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I65EguorI7ycEkj/fV/m2Sryd5NMkfJVnTt+3KJFNJnk5ybl/9vFabSnLF8v8okqSFHMmZ/o3AebNq+4D3VtX7gG8AVwIkOQPYDvxUu89/SrIqySrgC8D5wBnAJW2sJGmEFgz9qroXeHlW7c+q6o22eh+9C50DbANuqarXq+o5epdNPLN9TVXVs1X1HeCWNlaSNELLMaf/T4E/bcvrgP1926Zbba66JGmEhgr9JJ8D3gC+eKg0YFjNUx/0PXcmmUwyOTMzM0x7kqRZlhz6SXYAPwv8fLsgOvTO4Df0DVsPvDhP/TBVtauqtlbV1omJiaW2J0kaYEmhn+Q84LPAJ6rq232b9gLbk5yYZBOwGXgAeBDYnGRTkhPoPdm7d7jWJUmLtXqhAUluBj4CrE0yDVxF79U6JwL7kgDcV1X/rKqeSHIr8CS9aZ/Lq+q77ft8CrgTWAXsrqonjsLPI0max4KhX1WXDCjfMM/4q4GrB9TvAO5YVHeSpGXlO3IlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDlkw9JPsTnIwyeN9tZOT7EvyTLs9qdWT5LokU0keTbKl7z472vhn2vV1JUkjdiRn+jcC582qXQHcVVWbgbvaOsD59K6LuxnYCVwPvQcJepdZ/CBwJnDVoQcKSdLoLBj6VXUv8PKs8jZgT1veA1zYV7+peu4D1iQ5DTgX2FdVL1fVK8A+Dn8gkSQdZUud039PVR0AaLentvo6YH/fuOlWm6t+mCQ7k0wmmZyZmVlie5KkQZb7idwMqNU89cOLVbuqamtVbZ2YmFjW5iSp65Ya+i+1aRva7cFWnwY29I1bD7w4T12SNEJLDf29wKFX4OwAbu+rX9pexXMW8Fqb/rkTOCfJSe0J3HNaTZI0QqsXGpDkZuAjwNok0/RehXMNcGuSy4AXgIvb8DuAC4Ap4NvAJwGq6uUkvwk82Mb9RlXNfnJYknSULRj6VXXJHJvOHjC2gMvn+D67gd2L6k6StKx8R64kdYihL0kdYuhLUocY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR1i6EtShxj6ktQhhr4kdYihL0kdYuhLUocY+pLUIUOFfpJ/keSJJI8nuTnJ25NsSnJ/kmeSfCnJCW3siW19qm3fuBw/gCTpyC059JOsA/45sLWq3gusArYDnweurarNwCvAZe0ulwGvVNWPAte2cZKkERp2emc18ANJVgPvAA4AHwVua9v3ABe25W1tnbb97CQZcv+SpEVYcuhX1TeBf0fvwugHgNeAh4BXq+qNNmwaWNeW1wH7233faONPmf19k+xMMplkcmZmZqntSZIGGGZ65yR6Z++bgB8G3gmcP2BoHbrLPNveLFTtqqqtVbV1YmJiqe1JkgYYZnrnZ4Dnqmqmqv4G+DLw94E1bboHYD3wYlueBjYAtO3vBl4eYv+SpEUaJvRfAM5K8o42N3828CRwD3BRG7MDuL0t723rtO13V9VhZ/qSpKNnmDn9++k9IftV4LH2vXYBnwU+k2SK3pz9De0uNwCntPpngCuG6FuStASrFx4yt6q6CrhqVvlZ4MwBY/8auHiY/UmShuM7ciWpQwx9SeoQQ1+SOsTQl6QOMfQlqUMMfUnqEENfkjrE0JekDjH0JalDDH1J6hBDX5I6xNCXpA4x9CWpQwx9SeoQQ1+SOsTQl6QOGSr0k6xJcluSryd5KsnfS3Jykn1Jnmm3J7WxSXJdkqkkjybZsjw/giTpSA17pv8fgf9eVT8B/F3gKXqXQbyrqjYDd/HmZRHPBza3r53A9UPuW5K0SEsO/SQ/BHyYdg3cqvpOVb0KbAP2tGF7gAvb8jbgpuq5D1iT5LQldy5JWrRhzvRPB2aAP0jytSS/n+SdwHuq6gBAuz21jV8H7O+7/3SrvUWSnUkmk0zOzMwM0Z4kabZhQn81sAW4vqo+APw/3pzKGSQDanVYoWpXVW2tqq0TExNDtCdJmm2Y0J8Gpqvq/rZ+G70HgZcOTdu024N94zf03X898OIQ+5ckLdKSQ7+q/hzYn+THW+ls4ElgL7Cj1XYAt7flvcCl7VU8ZwGvHZoGkiSNxuoh7/9LwBeTnAA8C3yS3gPJrUkuA14ALm5j7wAuAKaAb7exkqQRGir0q+phYOuATWcPGFvA5cPsT5I0HN+RK0kdYuhLUocY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR1i6EtShxj6ktQhhr4kdYihL0kdYuhLUocY+pLUIYa+JHXI0KGfZFWSryX5b219U5L7kzyT5EvtqlokObGtT7XtG4fdtyRpcZbjTP/TwFN9658Hrq2qzcArwGWtfhnwSlX9KHBtGydJGqGhQj/JeuDjwO+39QAfBW5rQ/YAF7blbW2dtv3sNl6SNCLDnun/B+BXge+19VOAV6vqjbY+Daxry+uA/QBt+2tt/Fsk2ZlkMsnkzMzMkO1JkvotOfST/CxwsKoe6i8PGFpHsO3NQtWuqtpaVVsnJiaW2p4kaYDVQ9z3Q8AnklwAvB34IXpn/muSrG5n8+uBF9v4aWADMJ1kNfBu4OUh9i9JWqQln+lX1ZVVtb6qNgLbgbur6ueBe4CL2rAdwO1teW9bp22/u6oOO9OXJB09R+N1+p8FPpNkit6c/Q2tfgNwSqt/BrjiKOxbkjSPYaZ3vq+qvgJ8pS0/C5w5YMxfAxcvx/4kSUuzLKGvt9p4xZ+Mbd/PX/Pxse1b0srnxzBIUocY+pLUIYa+JHWIoS9JHWLoS1KHGPqS1CGGviR1iKEvSR1i6EtSh/iO3OPMuN4N7DuBpWODZ/qS1CGGviR1iKEvSR1i6EtShxj6ktQhw1wYfUOSe5I8leSJJJ9u9ZOT7EvyTLs9qdWT5LokU0keTbJluX4ISdKRGeZM/w3gX1bVTwJnAZcnOYPeZRDvqqrNwF28eVnE84HN7WsncP0Q+5YkLcEwF0Y/UFVfbct/CTwFrAO2AXvasD3AhW15G3BT9dwHrEly2pI7lyQt2rLM6SfZCHwAuB94T1UdgN4DA3BqG7YO2N93t+lWm/29diaZTDI5MzOzHO1JkpqhQz/Ju4A/BH65qv5ivqEDanVYoWpXVW2tqq0TExPDtidJ6jNU6Cd5G73A/2JVfbmVXzo0bdNuD7b6NLCh7+7rgReH2b8kaXGGefVOgBuAp6rqt/s27QV2tOUdwO199Uvbq3jOAl47NA0kSRqNYT5w7UPAPwEeS/Jwq/1r4Brg1iSXAS8AF7dtdwAXAFPAt4FPDrFvCRjfB8yBHzKnY9OSQ7+q/heD5+kBzh4wvoDLl7o/SdLw/GhlSZrH8fZx5X4MgyR1iKEvSR1i6EtShxj6ktQhPpErLdHx9gSfusEzfUnqEM/0JR0x/7o59nmmL0kdYuhLUocY+pLUIYa+JHWIoS9JHWLoS1KH+JJNSSveOK+bcLzxTF+SOmTkoZ/kvCRPJ5lKcsWo9y9JXTbS6Z0kq4AvAB+jd6H0B5PsraonR9mHlp9/fkvHhlHP6Z8JTFXVswBJbgG2AYa+dIR8gNUwRh3664D9fevTwAf7ByTZCexsq3+V5Okh9rcW+NYQ9x+FY6FHsM/lZp/L61joc1E95vND7evvzLVh1KE/6ELq9ZaVql3ArmXZWTJZVVuX43sdLcdCj2Cfy80+l9ex0OdK6XHUT+ROAxv61tcDL464B0nqrFGH/oPA5iSbkpwAbAf2jrgHSeqskU7vVNUbST4F3AmsAnZX1RNHcZfLMk10lB0LPYJ9Ljf7XF7HQp8rosdU1cKjJEnHBd+RK0kdYuhLUoccl6G/kj/qIcnzSR5L8nCSyVY7Ocm+JM+025PG0NfuJAeTPN5XG9hXeq5rx/fRJFvG3OevJ/lmO6YPJ7mgb9uVrc+nk5w7oh43JLknyVNJnkjy6VZfUcdznj5X2vF8e5IHkjzS+vw3rb4pyf3teH6pvTiEJCe29am2feOY+7wxyXN9x/P9rT6e36OqOq6+6D1B/H+A04ETgEeAM8bdV19/zwNrZ9V+C7iiLV8BfH4MfX0Y2AI8vlBfwAXAn9J738VZwP1j7vPXgV8ZMPaM9u9/IrCp/b9YNYIeTwO2tOUfBL7RellRx3OePlfa8Qzwrrb8NuD+dpxuBba3+u8Cv9CWfxH43ba8HfjSiI7nXH3eCFw0YPxY/t2PxzP973/UQ1V9Bzj0UQ8r2TZgT1veA1w46gaq6l7g5VnlufraBtxUPfcBa5KcNsY+57INuKWqXq+q54Apev8/jqqqOlBVX23Lfwk8Re/d6CvqeM7T51zGdTyrqv6qrb6tfRXwUeC2Vp99PA8d59uAs5MMemPoqPqcy1j+3Y/H0B/0UQ/z/UcetQL+LMlD7SMnAN5TVQeg94sInDq27t5qrr5W4jH+VPsTeXff9NjY+2xTCx+gd9a3Yo/nrD5hhR3PJKuSPAwcBPbR+yvj1ap6Y0Av3++zbX8NOGUcfVbVoeN5dTue1yY5cXafzUiO5/EY+gt+1MOYfaiqtgDnA5cn+fC4G1qClXaMrwd+BHg/cAD4960+1j6TvAv4Q+CXq+ov5hs6oDbOPlfc8ayq71bV++m9i/9M4Cfn6WXF9JnkvcCVwE8APw2cDHx2nH0ej6G/oj/qoapebLcHgT+i9x/4pUN/1rXbg+Pr8C3m6mtFHeOqeqn9sn0P+D3enHIYW59J3kYvSL9YVV9u5RV3PAf1uRKP5yFV9SrwFXpz4GuSHHqDaX8v3++zbX83Rz4luNx9ntem0aqqXgf+gDEfz+Mx9FfsRz0keWeSHzy0DJwDPE6vvx1t2A7g9vF0eJi5+toLXNpefXAW8NqhaYtxmDUP+nP0jin0+tzeXs2xCdgMPDCCfgLcADxVVb/dt2lFHc+5+lyBx3MiyZq2/APAz9B7/uEe4KI2bPbxPHScLwLurvbM6Rj6/HrfA33oPe/QfzxH/3s0imeLR/1F71nxb9Cb9/vcuPvp6+t0eq9+eAR44lBv9OYb7wKeabcnj6G3m+n9Kf839M5ALpurL3p/ln6hHd/HgK1j7vM/tz4epfeLdFrf+M+1Pp8Gzh9Rj/+A3p/pjwIPt68LVtrxnKfPlXY83wd8rfXzOPBrrX46vQedKeC/Aie2+tvb+lTbfvqY+7y7Hc/Hgf/Cm6/wGcu/ux/DIEkdcjxO70iS5mDoS1KHGPqS1CGGviR1iKEvSR1i6EtShxj6ktQh/x/dtAPhmMliQQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.AlcoholYear.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2364"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.AlcoholYear.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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odkmSI0mOt+XFY+hre5JHkxxL8lyST2yE3pK8K8nXknyj9fXpVr8yyROtry+0N+TXXZILkjyV5OGN0leSF5N8M8nTSaZbbSO8xjYneTDJt9vr7MPj7ivJB9rPaf72/SSfHHdfrbdfbq/5Z5Pc3/4trMnr67wN9w12mYPfAW44o3YAOFpVO4CjbXu9vQH8alV9ENgF3NF+RuPu7e+A66vqKmAncEOSXcBngLtaX68A+9a5r3mfAI4NbW+Uvn6qqnYOnRM97ucR4LeAr1TVjwFXMfi5jbWvqnq+/Zx2Aj8OvA58adx9JdkK/BIwVVX/msEJJ7eyVq+vqjovb8CHgT8c2v4U8Kkx9jMJPDu0/Tywpa1vAZ7fAD+zh4Cf2Ui9Ae8Gvs7gU8zfBTYt9PyuYz/bGPzDvx54mMGH8jZCXy8Cl51RG+vzCLwH+DPaiRkbpa8zevlZ4E82Ql+8+en9Sxicqfgw8HNr9fo6b4/cWfgyB1vH1MtCrqiqUwBtefk4m0kyCVwNPMEG6K1NfTwNnAaOAN8BXq2qN9qQcT2fvwn8GvBPbfvSDdJXAX+U5Ml26Q4Y//P4fmAO+O02jfXZJBdtgL6G3Qrc39bH2ldV/QXwP4CXgFPAa8CTrNHr63wO95EucyBI8sPAHwCfrKrvj7sfgKr6xxr8t3kbg4vNfXChYevZU5KfB05X1ZPD5QWGjuN1dl1VXcNgGvKOJD8xhh7OtAm4Brinqq4G/obxTA0tqM1dfxT4/XH3AtDm+PcAVwL/EriIwfN5plV5fZ3P4b7RL3PwcpItAG15ehxNJHkHg2D/fFV9cSP1BlBVrwKPMXhPYHOS+Q/WjeP5vA74aJIXGVzN9HoGR/Lj7ouqOtmWpxnMH1/L+J/HWWC2qp5o2w8yCPtx9zXvRuDrVfVy2x53Xz8N/FlVzVXVPwBfBP4da/T6Op/DfaNf5uAwsLet72Uw372ukgS4FzhWVb+xUXpLMpFkc1v/IQYv+mPAo8DHxtVXVX2qqrZV1SSD19NXq+oXxt1XkouS/Mj8OoN55GcZ8/NYVX8JnEjygVbaDXxr3H0N+ThvTsnA+Pt6CdiV5N3t3+b8z2ttXl/jeqNjld6guAn4vwzma//LGPu4n8Ec2j8wOJrZx2Cu9ihwvC0vGUNf/57Bf/GeAZ5ut5vG3Rvwb4CnWl/PAv+11d8PfA2YYfBf6XeO8Tn9SeDhjdBXe/xvtNtz86/1cT+PrYedwHR7Lv83cPEG6evdwPeA9w7VNkJfnwa+3V73vwu8c61eX15+QJI6dD5Py0iSzsFwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR36/yL8TCI9V7SYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.AlcoholYear.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing for young people mainly. We could fill it as well as the last alcohol variables. However, using all of them for the predictor may not be benefitial, because too many filled NaNs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SmokeNow ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SmokeNow.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3707"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SmokeNow.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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kzwzVLkpyIMmRtrxwAn1tTvJoksNJnk3yybXQW5J3Jflmkm+1vj7b6lckebz19aX2C/mzLsl5SZ5M8vBa6SvJC0m+neSpJDOtthaOsfVJHkzy3XacfWTSfSX5YPs5zT9+mORTk+6r9fYf2zH/TJL725+FVTm+ztlwX2O3Ofg94IZTanuAg1W1FTjYts+2N4Bfr6oPAduAO9rPaNK9/T1wfVVdCVwF3JBkG/A54K7W1yvArrPc17xPAoeHttdKXz9TVVcNXRM96fcR4LeBr1XVjwNXMvi5TbSvqnqu/ZyuAn4SeB34yqT7SrIR+FVguqr+FYMLTm5ltY6vqjonH8BHgD8e2v4M8JkJ9rMFeGZo+zlgQ1vfADy3Bn5mDwE/t5Z6A94NPMHgU8wvA+tGvb9nsZ9NDP7gXw88zOBDeWuhrxeAS06pTfR9BN4L/AXtwoy10tcpvfw88GdroS/e/PT+RQyuVHwY+IXVOr7O2TN3Rt/mYOOEehnlsqo6AdCWl06ymSRbgKuBx1kDvbWpj6eAk8AB4HvAq1X1Rhsyqffzt4DfAP65bV+8Rvoq4E+SHGq37oDJv4/vB+aA323TWJ9PcsEa6GvYrcD9bX2ifVXVXwH/HXgROAG8BhxilY6vczncx7rNgSDJjwF/BHyqqn446X4AquqfavDP5k0Mbjb3oVHDzmZPSX4ROFlVh4bLI4ZO4ji7rqquYTANeUeSn5pAD6daB1wD3FNVVwN/y2SmhkZqc9cfA/5w0r0AtDn+HcAVwL8ALmDwfp5qRY6vcznc1/ptDl5KsgGgLU9Oookk72AQ7F+sqi+vpd4AqupV4BsMfiewPsn8B+sm8X5eB3wsyQsM7mZ6PYMz+Un3RVUdb8uTDOaPr2Xy7+MsMFtVj7ftBxmE/aT7mncj8ERVvdS2J93XzwJ/UVVzVfWPwJeBf8MqHV/ncriv9dsc7Ad2tvWdDOa7z6okAe4FDlfVb66V3pJMJVnf1n+UwUF/GHgU+Pik+qqqz1TVpqrawuB4+npV/dKk+0pyQZL3zK8zmEd+hgm/j1X118CxJB9spe3Adybd15BP8OaUDEy+rxeBbUne3f5szv+8Vuf4mtQvOlboFxQ3Af+bwXztf55gH/czmEP7RwZnM7sYzNUeBI605UUT6OvfMvgn3tPAU+1x06R7A/418GTr6xngv7T6+4FvAkcZ/FP6nRN8T38aeHgt9NVe/1vt8ez8sT7p97H1cBUw097L/wlcuEb6ejfwfeB9Q7W10Ndnge+24/73gXeu1vHl7QckqUPn8rSMJOkMDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUof8LnBtIAJv7/qIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SmokeNow.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Too many missing values, we may as well just ignore this variable."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Smoke100 ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Smoke100.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1665"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Smoke100.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Smoke100.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing for very young people, we can fill it as *No*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Smoke100n ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Smoke100n.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1665"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Smoke100n.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Smoke100n.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1665"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.Smoke100n.isna()) | (df.Smoke100.isna())].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Same entries are missing as `Smoke100`, we can just classify every missing as *Non-smoker*. I don't know if we should use both `Smoke100` and `Smoke100n`, or would be enough with `Smoke100`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SmokeAge ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1479.000000\n",
       "mean       17.939148\n",
       "std         5.452497\n",
       "min         6.000000\n",
       "25%        15.000000\n",
       "50%        17.000000\n",
       "75%        19.000000\n",
       "max        72.000000\n",
       "Name: SmokeAge, dtype: float64"
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.SmokeAge.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SmokeAge.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3767"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SmokeAge.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SmokeAge.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A lot of values missing, we might as well just discard this attribute."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Marijuana ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.Marijuana.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2835"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Marijuana.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.Marijuana.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could do the same thing as with alcohol. Assume no if the person is <= 16 yo. Otherwise follow the probabilities above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### AgeFirstMarij ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    1331.000000\n",
       "mean       16.983471\n",
       "std         3.874501\n",
       "min         1.000000\n",
       "25%        15.000000\n",
       "50%        16.000000\n",
       "75%        18.000000\n",
       "max        48.000000\n",
       "Name: AgeFirstMarij, dtype: float64"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.AgeFirstMarij.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.AgeFirstMarij.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3915"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.AgeFirstMarij.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.AgeFirstMarij.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Many many values missing, I would ignore this attribute."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### RegularMarij ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.RegularMarij.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2835"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.RegularMarij.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+Xi5zkOQzSU4meWaodnGSg0mOtOVFE+hrS5JHkxxO8mySj62H3pK8I8lXk3y99fXJVr8iyeOtr8+3N+TPuiTnJXkyyUPrpa8kLyT5RpKnksy22np4jW1I8kCSb7XX2Qcn3VeS97Wf08Lt+0k+Pum+Wm+/1l7zzyS5r/0urMnr65wN93V2mYM/AK4/pbYXOFRVW4FDbftsex34jap6P7AduL39jCbd2z8C11XVlcA24Pok24FPAXe2vl4Gdp/lvhZ8DDg8tL1e+vqZqto2dE70pJ9HgN8DvlRVPwZcyeDnNtG+quq59nPaBvwE8BrwxUn3lWQT8KvATFX9RwYnnNzKWr2+quqcvAEfBP5kaPsTwCcm2M808MzQ9nPAxra+EXhuHfzMHgR+bj31BrwT+BqDTzF/Bzh/1PN7FvvZzOAX/zrgIQYfylsPfb0AXHpKbaLPI/Au4C9pJ2asl75O6eXngf+3HvrijU/vX8zgTMWHgP+yVq+vc/bIndGXOdg0oV5GubyqTgC05WWTbCbJNHAV8DjroLc29fEUcBI4CHwbeKWqXm9DJvV8/i7wm8C/tu1L1klfBfxpkifapTtg8s/je4F54PfbNNank1y4DvoaditwX1ufaF9V9dfA/wJeBE4ArwJPsEavr3M53Me6zIEgyQ8Dfwx8vKq+P+l+AKrqX2rw3+bNDC429/5Rw85mT0l+AThZVU8Ml0cMncTr7NqquprBNOTtSX5qAj2c6nzgauDuqroK+HsmMzU0Upu7/hDwR5PuBaDN8e8ErgD+PXAhg+fzVKvy+jqXw329X+bgpSQbAdry5CSaSPI2BsH+2ar6wnrqDaCqXgG+wuA9gQ1JFj5YN4nn81rgQ0leYHA10+sYHMlPui+q6nhbnmQwf3wNk38e54C5qnq8bT/AIOwn3deCG4CvVdVLbXvSff0s8JdVNV9V/wx8AfhPrNHr61wO9/V+mYMDwK62vovBfPdZlSTAPcDhqvqd9dJbkqkkG9r6DzF40R8GHgU+PKm+quoTVbW5qqYZvJ6+XFW/OOm+klyY5EcW1hnMIz/DhJ/Hqvob4FiS97XSDuCbk+5ryEd4Y0oGJt/Xi8D2JO9sv5sLP6+1eX1N6o2OVXqD4kbg/zOYr/3vE+zjPgZzaP/M4GhmN4O52kPAkba8eAJ9/WcG/8V7Gniq3W6cdG/AjwNPtr6eAf5Hq78X+CpwlMF/pd8+wef0p4GH1kNf7fG/3m7PLrzWJ/08th62AbPtufy/wEXrpK93At8F3j1UWw99fRL4Vnvd/yHw9rV6fXn5AUnq0Lk8LSNJOgPDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXo3wB95Ec6SB3dUwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.RegularMarij.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, if the person is <= 16 yo, say no, otherwise use probabilities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### AgeRegMarij ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    629.000000\n",
       "mean      17.545310\n",
       "std        4.478533\n",
       "min        5.000000\n",
       "25%       15.000000\n",
       "50%       17.000000\n",
       "75%       19.000000\n",
       "max       52.000000\n",
       "Name: AgeRegMarij, dtype: float64"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.AgeRegMarij.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.AgeRegMarij.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4617"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.AgeRegMarij.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing for almost everyone, just discard the attribute."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### HardDrugs ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.HardDrugs.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2448"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.HardDrugs.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.HardDrugs.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Missing mainly for youngsters and old adults. Assume no for <= 16 yo and use probabilities for rest."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SexEver ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SexEver.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2450"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SexEver.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SexEver.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Assume no for <= 16yo and otherwise use probability."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SexAge ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2673.000000\n",
       "mean       17.456042\n",
       "std         3.740811\n",
       "min         9.000000\n",
       "25%        15.000000\n",
       "50%        17.000000\n",
       "75%        19.000000\n",
       "max        50.000000\n",
       "Name: SexAge, dtype: float64"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.SexAge.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SexAge.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2573"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SexAge.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAASAElEQVR4nO3dbYyd5X3n8e9vcUga2sQ8GOS1nR2iWmmi1WLoiDrLqmpx2+WhinkRJKJqsZAl7wt2m7SVWmcrtYrUF0RalRapQrJCWlOlNJQmi0VQWsshWu1KkA6BEIjDekIpntrFkwTItqgPtP++ONeIg33MnHnyGV/6fqSj+77/93Xm/GfO7Z/vuc4596SqkCT15d9MugFJ0uoz3CWpQ4a7JHXIcJekDhnuktShDZNuAOCyyy6rqampSbchSeeVJ5988rtVtWnUvnUR7lNTU8zMzEy6DUk6ryT5q7Ptc1pGkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdWjRcE/ygSRPD91+kOQTSS5JcjjJsba8uI1PknuSzCZ5Jsk1a/9tSJKGLRruVfV8Ve2oqh3AjwOvA18E9gNHqmo7cKRtA9wIbG+3fcC9a9G4JOnsljotswv4TlX9FbAbONjqB4Fb2vpu4P4aeBzYmGTzqnQrSRrLUj+hehvwQFu/oqpOAlTVySSXt/oW4PjQfeZa7eTwF0qyj8GZPe973/uW2MabpvZ/adn3XakX77p5Yo8tSW9n7DP3JBcCHwH+ZLGhI2pn/LmnqjpQVdNVNb1p08hLI0iSlmkp0zI3Al+vqpfb9ssL0y1tearV54BtQ/fbCpxYaaOSpPEtJdw/xptTMgCHgD1tfQ/w8FD99vaumZ3AawvTN5Kkc2OsOfck7wZ+FvivQ+W7gAeT7AVeAm5t9UeBm4BZBu+suWPVupUkjWWscK+q14FLT6t9j8G7Z04fW8Cdq9KdJGlZ/ISqJHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdWuqFwzRkUhct84Jlkhbjmbskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOjRWuCfZmOShJN9OcjTJh5NckuRwkmNteXEbmyT3JJlN8kySa9b2W5AknW7cM/ffBb5cVT8GXAUcBfYDR6pqO3CkbQPcCGxvt33AvavasSRpUYuGe5L3AD8J3AdQVf9YVa8Cu4GDbdhB4Ja2vhu4vwYeBzYm2bzqnUuSzmqcM/f3A/PA7yd5KslnklwEXFFVJwHa8vI2fgtwfOj+c632Fkn2JZlJMjM/P7+ib0KS9FbjhPsG4Brg3qq6Gvg73pyCGSUjanVGoepAVU1X1fSmTZvGalaSNJ5xwn0OmKuqJ9r2QwzC/uWF6Za2PDU0ftvQ/bcCJ1anXUnSOBYN96r6G+B4kg+00i7gW8AhYE+r7QEebuuHgNvbu2Z2Aq8tTN9Iks6Ncf+G6n8HPpfkQuAF4A4G/zE8mGQv8BJwaxv7KHATMAu83sZKks6hscK9qp4Gpkfs2jVibAF3rrAvSdIK+AlVSeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA6NFe5JXkzyzSRPJ5lptUuSHE5yrC0vbvUkuSfJbJJnklyzlt+AJOlMSzlz/+mq2lFV0217P3CkqrYDR9o2wI3A9nbbB9y7Ws1KksazkmmZ3cDBtn4QuGWofn8NPA5sTLJ5BY8jSVqiccO9gD9P8mSSfa12RVWdBGjLy1t9C3B86L5zrfYWSfYlmUkyMz8/v7zuJUkjbRhz3HVVdSLJ5cDhJN9+m7EZUaszClUHgAMA09PTZ+yXJC3fWGfuVXWiLU8BXwSuBV5emG5py1Nt+BywbejuW4ETq9WwJGlxi4Z7kouS/MjCOvBzwLPAIWBPG7YHeLitHwJub++a2Qm8tjB9I0k6N8aZlrkC+GKShfF/VFVfTvIXwINJ9gIvAbe28Y8CNwGzwOvAHavetSTpbS0a7lX1AnDViPr3gF0j6gXcuSrdSZKWxU+oSlKHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6NO4fyJakbk3t/9LEHvvFu25ek6/rmbskdchwl6QOGe6S1KGxwz3JBUmeSvJI274yyRNJjiX5fJILW/2dbXu27Z9am9YlSWezlDP3jwNHh7Y/DdxdVduBV4C9rb4XeKWqfhS4u42TJJ1DY4V7kq3AzcBn2naA64GH2pCDwC1tfXfbpu3f1cZLks6Rcc/cfwf4VeBf2valwKtV9UbbngO2tPUtwHGAtv+1Nv4tkuxLMpNkZn5+fpntS5JGWTTck/w8cKqqnhwujxhaY+x7s1B1oKqmq2p606ZNYzUrSRrPOB9iug74SJKbgHcB72FwJr8xyYZ2dr4VONHGzwHbgLkkG4D3At9f9c4lSWe16Jl7VX2yqrZW1RRwG/CVqvoF4DHgo23YHuDhtn6obdP2f6WqzjhzlyStnZW8z/3XgF9OMstgTv2+Vr8PuLTVfxnYv7IWJUlLtaRry1TVV4GvtvUXgGtHjPl74NZV6E2StEx+QlWSOmS4S1KHDHdJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4uGe5J3Jflakm8keS7Jp1r9yiRPJDmW5PNJLmz1d7bt2bZ/am2/BUnS6cY5c/8H4PqqugrYAdyQZCfwaeDuqtoOvALsbeP3Aq9U1Y8Cd7dxkqRzaNFwr4G/bZvvaLcCrgceavWDwC1tfXfbpu3flSSr1rEkaVFjzbknuSDJ08Ap4DDwHeDVqnqjDZkDtrT1LcBxgLb/NeDSEV9zX5KZJDPz8/Mr+y4kSW8xVrhX1T9X1Q5gK3At8MFRw9py1Fl6nVGoOlBV01U1vWnTpnH7lSSNYUnvlqmqV4GvAjuBjUk2tF1bgRNtfQ7YBtD2vxf4/mo0K0kazzjvltmUZGNb/yHgZ4CjwGPAR9uwPcDDbf1Q26bt/0pVnXHmLklaOxsWH8Jm4GCSCxj8Z/BgVT2S5FvAHyf5LeAp4L42/j7gD5PMMjhjv20N+pYkvY1Fw72qngGuHlF/gcH8++n1vwduXZXuJEnL4idUJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0a5xOqWmem9n9pYo/94l03T+yxJY3PM3dJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDi4Z7km1JHktyNMlzST7e6pckOZzkWFte3OpJck+S2STPJLlmrb8JSdJbjXPm/gbwK1X1QWAncGeSDwH7gSNVtR040rYBbgS2t9s+4N5V71qS9LYWDfeqOllVX2/r/x84CmwBdgMH27CDwC1tfTdwfw08DmxMsnnVO5ckndWS5tyTTAFXA08AV1TVSRj8BwBc3oZtAY4P3W2u1SRJ58jY4Z7kh4E/BT5RVT94u6EjajXi6+1LMpNkZn5+ftw2JEljGCvck7yDQbB/rqq+0MovL0y3tOWpVp8Dtg3dfStw4vSvWVUHqmq6qqY3bdq03P4lSSOM826ZAPcBR6vqt4d2HQL2tPU9wMND9dvbu2Z2Aq8tTN9Iks6Ncf7M3nXAfwG+meTpVvsfwF3Ag0n2Ai8Bt7Z9jwI3AbPA68Adq9qxJGlRi4Z7Vf0fRs+jA+waMb6AO1fYlyRpBfyEqiR1yHCXpA4Z7pLUIcNdkjpkuEtShwx3SeqQ4S5JHTLcJalDhrskdchwl6QOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHVonD+zJ0nnxNT+L026hW545i5JHTLcJalDTstoSSb1a/OLd908kceVzleLnrkn+WySU0meHapdkuRwkmNteXGrJ8k9SWaTPJPkmrVsXpI02jjTMn8A3HBabT9wpKq2A0faNsCNwPZ22wfcuzptSpKWYtFwr6r/DXz/tPJu4GBbPwjcMlS/vwYeBzYm2bxazUqSxrPcF1SvqKqTAG15eatvAY4PjZtrtTMk2ZdkJsnM/Pz8MtuQJI2y2i+oZkStRg2sqgPAAYDp6emRY6QFvpArLc1yz9xfXphuactTrT4HbBsatxU4sfz2JEnLsdxwPwTsaet7gIeH6re3d83sBF5bmL6RJJ07i07LJHkA+CngsiRzwG8CdwEPJtkLvATc2oY/CtwEzAKvA3esQc+SpEUsGu5V9bGz7No1YmwBd660KWm9mOS1Tpzv10p4+QFJ6pDhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIa/nLq1TXnJBK2G4S3oL/45pH5yWkaQOGe6S1CHDXZI6ZLhLUocMd0nqkOEuSR0y3CWpQ4a7JHXIcJekDhnuktQhw12SOmS4S1KHDHdJ6tCahHuSG5I8n2Q2yf61eAxJ0tmtergnuQD4PeBG4EPAx5J8aLUfR5J0dmtx5n4tMFtVL1TVPwJ/DOxeg8eRJJ3FWvyxji3A8aHtOeAnTh+UZB+wr23+bZLnl/l4lwHfXeZ915J9LY19Ld167c2+liCfXlFf/+5sO9Yi3DOiVmcUqg4AB1b8YMlMVU2v9OusNvtaGvtauvXam30tzVr1tRbTMnPAtqHtrcCJNXgcSdJZrEW4/wWwPcmVSS4EbgMOrcHjSJLOYtWnZarqjST/Dfgz4ALgs1X13Go/zpAVT+2sEftaGvtauvXam30tzZr0laozpsMlSec5P6EqSR0y3CWpQ+d1uK+Xyxwk+WySU0meHapdkuRwkmNtefEE+tqW5LEkR5M8l+Tj66G3JO9K8rUk32h9farVr0zyROvr8+0F+XMuyQVJnkryyHrpK8mLSb6Z5OkkM622Ho6xjUkeSvLtdpx9eNJ9JflA+zkt3H6Q5BOT7qv19kvtmH82yQPt38KaHF/nbbivs8sc/AFww2m1/cCRqtoOHGnb59obwK9U1QeBncCd7Wc06d7+Abi+qq4CdgA3JNkJfBq4u/X1CrD3HPe14OPA0aHt9dLXT1fVjqH3RE/6eQT4XeDLVfVjwFUMfm4T7auqnm8/px3AjwOvA1+cdF9JtgC/CExX1b9n8IaT21ir46uqzssb8GHgz4a2Pwl8coL9TAHPDm0/D2xu65uB59fBz+xh4GfXU2/Au4GvM/gU83eBDaOe33PYz1YG//CvBx5h8KG89dDXi8Blp9Um+jwC7wH+kvbGjPXS12m9/Bzwf9dDX7z56f1LGLxT8RHgP6/V8XXenrkz+jIHWybUyyhXVNVJgLa8fJLNJJkCrgaeYB301qY+ngZOAYeB7wCvVtUbbcikns/fAX4V+Je2fek66auAP0/yZLt0B0z+eXw/MA/8fpvG+kySi9ZBX8NuAx5o6xPtq6r+GvifwEvASeA14EnW6Pg6n8N9rMscCJL8MPCnwCeq6geT7gegqv65Br82b2VwsbkPjhp2LntK8vPAqap6crg8YugkjrPrquoaBtOQdyb5yQn0cLoNwDXAvVV1NfB3TGZqaKQ2d/0R4E8m3QtAm+PfDVwJ/FvgIgbP5+lW5fg6n8N9vV/m4OUkmwHa8tQkmkjyDgbB/rmq+sJ66g2gql4FvsrgNYGNSRY+WDeJ5/M64CNJXmRwNdPrGZzJT7ovqupEW55iMH98LZN/HueAuap6om0/xCDsJ93XghuBr1fVy2170n39DPCXVTVfVf8EfAH4j6zR8XU+h/t6v8zBIWBPW9/DYL77nEoS4D7gaFX99nrpLcmmJBvb+g8xOOiPAo8BH51UX1X1yaraWlVTDI6nr1TVL0y6ryQXJfmRhXUG88jPMuHnsar+Bjie5AOttAv41qT7GvIx3pySgcn39RKwM8m727/NhZ/X2hxfk3qhY5VeoLgJ+H8M5mt/fYJ9PMBgDu2fGJzN7GUwV3sEONaWl0ygr//E4Fe8Z4Cn2+2mSfcG/AfgqdbXs8BvtPr7ga8Bswx+lX7nBJ/TnwIeWQ99tcf/Rrs9t3CsT/p5bD3sAGbac/m/gIvXSV/vBr4HvHeoth76+hTw7Xbc/yHwzrU6vrz8gCR16HyelpEknYXhLkkdMtwlqUOGuyR1yHCXpA4Z7pLUIcNdkjr0r8ZoRV5QZ1weAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SexAge.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "May not be a good idea to use this attribute. What value do we give if `SexEver` is no? Anyway, we can give that value if <= 16yo, otherwise use probability."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SexNumPartnLife ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2773.000000\n",
       "mean       14.617021\n",
       "std        61.385945\n",
       "min         0.000000\n",
       "25%         2.000000\n",
       "50%         5.000000\n",
       "75%        12.000000\n",
       "max      2000.000000\n",
       "Name: SexNumPartnLife, dtype: float64"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.SexNumPartnLife.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SexNumPartnLife.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2473"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SexNumPartnLife.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SexNumPartnLife.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How do we fill this in? DO we build a predictor based on age or something if `SexEver` is true? We could also ignore this."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SexNumPartYear ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    2405.000000\n",
       "mean        1.354678\n",
       "std         2.503281\n",
       "min         0.000000\n",
       "25%         1.000000\n",
       "50%         1.000000\n",
       "75%         1.000000\n",
       "max        69.000000\n",
       "Name: SexNumPartYear, dtype: float64"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.SexNumPartYear.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SexNumPartYear.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2841"
      ]
     },
     "execution_count": 227,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SexNumPartYear.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SexNumPartYear.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, how do we fill this in? Based on probs taking into account the total number of partners or something."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SameSex ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SameSex.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2448"
      ]
     },
     "execution_count": 230,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SameSex.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SameSex.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fill based on probabilities, taking into account `SexEver` and <= 16 yo things."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### SexOrientation ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.SexOrientation.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2889"
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.SexOrientation.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[df.SexOrientation.isna()].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can include a *DontKnow* category for <= 16 yo. And the rest fill by probabilities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PregnantNow ####"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.PregnantNow.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4363"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.PregnantNow.isna()].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1770"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[(df.PregnantNow.isna()) & (df.female == 1)].shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df[(df.PregnantNow.isna()) & (df.female == 1)].Age.hist()\n",
    "plt.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fill in all men as not pregnant. If a woman is <= 20 or >= 50 fill her as no. Otherwise, use the probabilities above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Done with attribute analysis! #"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}