exploration.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy import stats\n",
    "import seaborn as sns\n",
    "import missingno as msno\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data exploration: Part 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebooks looks at the outliers in the data using z-score as well as the missing values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "      <th>musi_wend</th>\n",
       "      <th>...</th>\n",
       "      <th>anx_band_15</th>\n",
       "      <th>exercise</th>\n",
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       "      <th>secd_diag</th>\n",
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       "      <th>panic_score</th>\n",
       "      <th>dep_thoughts</th>\n",
       "      <th>dep_score</th>\n",
       "      <th>comp_house</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>49.812426</td>\n",
       "      <td>160.224186</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
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       "<p>5 rows × 43 columns</p>\n",
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       "   Unnamed: 0  weight_16   height_16  comp_noint_bed_16  comp_int_bed_16  \\\n",
       "0           0  59.294132  181.602831                0.0              0.0   \n",
       "1           1        NaN         NaN                0.0              0.0   \n",
       "2           2        NaN         NaN                0.0              0.0   \n",
       "3           3  49.812426  160.224186                0.0              0.0   \n",
       "4           4  62.270030  191.703227                1.0              0.0   \n",
       "\n",
       "   talk_phon_wend  text_wend  talk_mob_wend  comp_wend  musi_wend  ...  \\\n",
       "0             1.0        1.0            1.0        2.0        0.0  ...   \n",
       "1             NaN        NaN            NaN        NaN        NaN  ...   \n",
       "2             NaN        NaN            NaN        NaN        NaN  ...   \n",
       "3             NaN        NaN            NaN        NaN        NaN  ...   \n",
       "4             0.0        0.0            0.0        1.0        0.0  ...   \n",
       "\n",
       "   anx_band_15  exercise  child_bull  has_dep_diag  secd_diag  prim_diag  \\\n",
       "0          0.5       4.0         0.0           0.0        0.0        0.0   \n",
       "1          NaN       NaN         NaN           NaN        NaN        NaN   \n",
       "2          NaN       NaN         NaN           NaN        NaN        NaN   \n",
       "3          NaN       NaN         NaN           NaN        NaN        NaN   \n",
       "4          3.0       3.0         0.0           NaN        NaN        NaN   \n",
       "\n",
       "   panic_score  dep_thoughts  dep_score  comp_house  \n",
       "0          0.0           NaN        0.0         1.0  \n",
       "1          NaN           NaN        NaN         0.0  \n",
       "2          NaN           NaN        NaN         0.0  \n",
       "3          NaN           NaN        NaN         0.0  \n",
       "4          NaN           NaN        NaN         0.0  \n",
       "\n",
       "[5 rows x 43 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"newdata2.csv\", engine='python')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Variable Name</th>\n",
       "      <th>Variable ALSPAC Name</th>\n",
       "      <th>Variable Description</th>\n",
       "      <th>Variable Type</th>\n",
       "      <th>Administered to</th>\n",
       "      <th>Age of child at administration</th>\n",
       "      <th>ALSPAC Measure</th>\n",
       "      <th>ALSPAC Responses</th>\n",
       "      <th>Processing Details</th>\n",
       "      <th>Reference Document</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>agg_score</td>\n",
       "      <td>f596</td>\n",
       "      <td>Aggression score of partnership</td>\n",
       "      <td>Discrete</td>\n",
       "      <td>Mother</td>\n",
       "      <td>Aged 8 months</td>\n",
       "      <td>Derived by ALSPAC. See Processing Details</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Aggression score was determined by three quest...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>alon_week</td>\n",
       "      <td>ccs1006</td>\n",
       "      <td>Average time child spent per day doing things ...</td>\n",
       "      <td>Ordinal</td>\n",
       "      <td>Child</td>\n",
       "      <td>Aged 198 months</td>\n",
       "      <td>\"How much time on average do you spend each da...</td>\n",
       "      <td>Not at all</td>\n",
       "      <td>The category \"Not at all\" was collapsed into t...</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Less than 1 hour</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>3</th>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1-2 hours</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td></td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3 or more hours</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "  Variable Name Variable ALSPAC Name  \\\n",
       "0     agg_score                 f596   \n",
       "1     alon_week              ccs1006   \n",
       "2           NaN                  NaN   \n",
       "3                                      \n",
       "4                                      \n",
       "\n",
       "                                Variable Description Variable Type  \\\n",
       "0                    Aggression score of partnership      Discrete   \n",
       "1  Average time child spent per day doing things ...       Ordinal   \n",
       "2                                                NaN           NaN   \n",
       "3                                                NaN           NaN   \n",
       "4                                                NaN           NaN   \n",
       "\n",
       "  Administered to Age of child at administration  \\\n",
       "0          Mother                  Aged 8 months   \n",
       "1           Child                Aged 198 months   \n",
       "2             NaN                            NaN   \n",
       "3             NaN                            NaN   \n",
       "4             NaN                            NaN   \n",
       "\n",
       "                                      ALSPAC Measure  ALSPAC Responses  \\\n",
       "0          Derived by ALSPAC. See Processing Details               NaN   \n",
       "1  \"How much time on average do you spend each da...        Not at all   \n",
       "2                                                NaN  Less than 1 hour   \n",
       "3                                                NaN         1-2 hours   \n",
       "4                                                NaN   3 or more hours   \n",
       "\n",
       "                                  Processing Details Reference Document  \n",
       "0  Aggression score was determined by three quest...                NaN  \n",
       "1  The category \"Not at all\" was collapsed into t...                NaN  \n",
       "2                                                NaN                NaN  \n",
       "3                                                NaN                NaN  \n",
       "4                                                NaN                NaN  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dictionary = pd.read_csv(\"./dataset/synthetic_data_dictionary.csv\", engine='python')\n",
    "dictionary.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Height and weight distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = data.height_16\n",
    "y = data.weight_16\n",
    "\n",
    "plt.scatter(x, y, alpha=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Z-scores: any data point whose Z-score falls out of 3rd standard deviation is an outlier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def detect_outliers_zscore(xs):\n",
    "    outliers = []\n",
    "    thres = 3\n",
    "    mean = np.mean(xs)\n",
    "    std = np.std(xs)\n",
    "    # print(mean, std)\n",
    "    for i in xs:\n",
    "        z_score = (i-mean)/std\n",
    "        if (np.abs(z_score) > thres):\n",
    "            outliers.append(i)\n",
    "    return outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers from Z-scores method:  [106.912736610394, 108.647814770842, 112.24711907142598, 110.675244693617, 104.737369332756, 108.09939402285801, 99.47306111438179, 104.38093422021099, 101.68273099917299, 99.2419369092074, 104.993764250504, 103.564232306512, 105.57617218496401, 106.516786672599, 111.66027188786501, 118.770974445603, 107.804654950301, 104.150239996927, 99.99448371763441, 112.76290452972601, 111.37944130156099, 107.17580565791799, 104.73258405940001, 113.563648773647, 100.455213336368, 102.315488080777, 116.82441561596902, 105.501614226415, 100.98172721989701, 103.520171797934, 101.362847179534, 108.535012000427, 109.457015431589, 104.177905336283, 99.8247605028558, 101.471240384867, 105.79478443720501, 104.984332518791, 101.580674841762, 106.342999132539, 102.705305370059, 104.30424258178199, 101.11576469785, 100.272339147922, 100.004841144597, 106.007876150786, 97.9078574092869, 106.551411965512, 98.14630872248242, 100.928057754711, 102.767338984242, 100.89053638078899, 115.918014168421, 102.749262044485, 99.48464901564002, 119.686945257491, 126.029499101703, 111.925939605273, 99.3175096045446, 99.2122041729188, 102.61690503424299, 124.06305974527201, 104.295010628517, 120.321720927323, 97.740065033872, 97.74700034258, 108.17756838141199, 100.07579037247, 99.21581296869628, 120.498709322309, 100.065454307696, 126.029499101703, 108.787883083484, 106.514343900578, 109.246934018044, 102.81046454185899, 102.15285140481, 112.990632380385, 120.73228868515301, 115.735266856026, 107.606883640675, 99.8667955520355, 110.50810768817499, 101.498283895668, 99.08356598326851]\n"
     ]
    }
   ],
   "source": [
    "weight_outliers = detect_outliers_zscore(data.weight_16)\n",
    "print(\"Outliers from Z-scores method: \", weight_outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers from Z-scores method:  [201.519621788055, 139.51216890513902, 196.824923377762, 194.96318435354303, 198.96069934006698, 199.15405222406602, 195.268917269699, 198.274035830561, 195.079706298698, 200.72402053858798, 194.91820679310902, 199.03111937917495, 199.057469533129, 198.306040686106, 198.46854343912497]\n"
     ]
    }
   ],
   "source": [
    "height_outliers = detect_outliers_zscore(data.height_16)\n",
    "print(\"Outliers from Z-scores method: \", height_outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers from Z-scores method:  [53.0, 51.0, 50.0, 53.0, 49.0, 48.0, 50.0, 48.0, 50.0, 48.0, 49.0, 50.0, 45.0, 50.0, 49.0, 51.0, 48.0]\n"
     ]
    }
   ],
   "source": [
    "iq_outliers = detect_outliers_zscore(data.iq)\n",
    "print(\"Outliers from Z-scores method: \", iq_outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers from Z-scores method:  [44.0, 44.0, 43.0, 43.0, 44.0, 44.0, 43.0, 44.0, 44.0, 43.0, 44.0, 44.0, 43.0, 43.0, 43.0, 43.0, 43.0, 43.0, 44.0, 43.0, 43.0, 43.0, 44.0, 43.0, 44.0, 43.0, 43.0, 43.0, 43.0, 44.0, 44.0]\n"
     ]
    }
   ],
   "source": [
    "mat_age_outliers = detect_outliers_zscore(data.mat_age)\n",
    "print(\"Outliers from Z-scores method: \", mat_age_outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers from Z-scores method:  [24.0, 23.0, 22.0, 20.0, 20.0, 26.0, 27.0, 20.0, 20.0, 21.0, 20.0, 23.0, 26.0, 21.0, 27.0, 20.0, 20.0, 21.0, 20.0, 20.0, 20.0, 24.0, 23.0, 23.0, 26.0, 21.0, 28.0, 24.0, 20.0, 23.0, 20.0, 20.0, 20.0, 22.0, 20.0, 21.0, 20.0, 20.0, 22.0, 21.0, 20.0, 22.0, 20.0, 20.0, 23.0, 21.0, 20.0, 20.0, 24.0, 22.0, 20.0, 22.0, 20.0, 20.0, 20.0, 22.0, 22.0, 27.0, 20.0, 20.0, 23.0, 26.0, 20.0, 23.0, 27.0, 22.0, 20.0, 22.0, 21.0, 28.0, 22.0, 21.0, 22.0, 28.0, 20.0, 20.0, 20.0, 24.0, 21.0, 27.0, 24.0, 26.0, 20.0, 23.0, 20.0, 20.0, 26.0, 20.0, 28.0, 20.0, 20.0, 20.0, 20.0, 23.0, 22.0, 21.0, 28.0, 22.0, 28.0, 20.0, 21.0]\n"
     ]
    }
   ],
   "source": [
    "mat_dep_outliers = detect_outliers_zscore(data.mat_dep)\n",
    "print(\"Outliers from Z-scores method: \", mat_dep_outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Outliers from Z-scores method:  [3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0]\n"
     ]
    }
   ],
   "source": [
    "agg_outliers = detect_outliers_zscore(data.agg_score)\n",
    "print(\"Outliers from Z-scores method: \", agg_outliers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 13734 entries, 0 to 13733\n",
      "Data columns (total 99 columns):\n",
      " #   Column             Non-Null Count  Dtype  \n",
      "---  ------             --------------  -----  \n",
      " 0   Unnamed: 0         13734 non-null  int64  \n",
      " 1   comp_bed_9         8174 non-null   object \n",
      " 2   mat_dep            11145 non-null  float64\n",
      " 3   mat_age            13326 non-null  float64\n",
      " 4   weight_16          5351 non-null   float64\n",
      " 5   height_16          5364 non-null   float64\n",
      " 6   iq                 7288 non-null   float64\n",
      " 7   comp_noint_bed_16  13734 non-null  bool   \n",
      " 8   comp_int_bed_16    13734 non-null  bool   \n",
      " 9   talk_phon_wend     4850 non-null   object \n",
      " 10  text_wend          4841 non-null   float64\n",
      " 11  talk_mob_wend      4834 non-null   float64\n",
      " 12  comp_wend          4839 non-null   float64\n",
      " 13  musi_wend          4831 non-null   object \n",
      " 14  read_wend          4834 non-null   float64\n",
      " 15  work_wend          4833 non-null   float64\n",
      " 16  alon_wend          4850 non-null   float64\n",
      " 17  draw_wend          4842 non-null   float64\n",
      " 18  play_wend          4850 non-null   object \n",
      " 19  tv_wend            4853 non-null   float64\n",
      " 20  out_win_wend       4849 non-null   float64\n",
      " 21  out_sum_wend       4822 non-null   object \n",
      " 22  tran_wend          4861 non-null   object \n",
      " 23  talk_phon_week     4999 non-null   object \n",
      " 24  text_week          5004 non-null   float64\n",
      " 25  talk_mob_week      5016 non-null   float64\n",
      " 26  comp_week          5011 non-null   float64\n",
      " 27  musi_week          5003 non-null   object \n",
      " 28  read_week          4993 non-null   float64\n",
      " 29  work_week          5012 non-null   float64\n",
      " 30  alon_week          5008 non-null   float64\n",
      " 31  draw_week          5012 non-null   float64\n",
      " 32  play_week          5015 non-null   object \n",
      " 33  tv_week            5020 non-null   float64\n",
      " 34  out_win_week       5007 non-null   float64\n",
      " 35  out_sum_week       5014 non-null   object \n",
      " 36  tran_week          5024 non-null   object \n",
      " 37  pat_pres_10        8057 non-null   object \n",
      " 38  pat_pres_8         7729 non-null   object \n",
      " 39  pat_pres           9579 non-null   object \n",
      " 40  num_home           9583 non-null   float64\n",
      " 41  mat_anx_1          9700 non-null   object \n",
      " 42  mat_anx_18m        9884 non-null   object \n",
      " 43  mat_anx_8m         10488 non-null  object \n",
      " 44  agg_score          10714 non-null  float64\n",
      " 45  emot_cruel         11301 non-null  object \n",
      " 46  phys_cruel         11301 non-null  object \n",
      " 47  mat_anx_0m         11265 non-null  object \n",
      " 48  pat_ses            11021 non-null  object \n",
      " 49  mat_ses            10110 non-null  object \n",
      " 50  pat_edu            10750 non-null  float64\n",
      " 51  mat_edu            12375 non-null  float64\n",
      " 52  parity             12544 non-null  float64\n",
      " 53  dep_band_15        5299 non-null   float64\n",
      " 54  dep_band_13        7003 non-null   float64\n",
      " 55  dep_band_10        7679 non-null   float64\n",
      " 56  dep_band_07        8089 non-null   float64\n",
      " 57  anx_band_15        5303 non-null   float64\n",
      " 58  anx_band_13        7158 non-null   float64\n",
      " 59  anx_band_10        7852 non-null   float64\n",
      " 60  anx_band_07        8280 non-null   float64\n",
      " 61  exercise           4971 non-null   float64\n",
      " 62  child_bull         4989 non-null   object \n",
      " 63  phone_14_wend      5962 non-null   float64\n",
      " 64  phone_14_week      6131 non-null   float64\n",
      " 65  musi_13            6880 non-null   object \n",
      " 66  tv_bed_9           8348 non-null   object \n",
      " 67  own_mob            4386 non-null   object \n",
      " 68  has_dep_diag       4513 non-null   object \n",
      " 69  secd_diag          4513 non-null   float64\n",
      " 70  prim_diag          4513 non-null   float64\n",
      " 71  panic_score        4513 non-null   float64\n",
      " 72  dep_thoughts       1805 non-null   float64\n",
      " 73  dep_score          4513 non-null   float64\n",
      " 74  comp_house         13734 non-null  bool   \n",
      " 75  tv_bed_16          13734 non-null  bool   \n",
      " 76  creat_14           7093 non-null   object \n",
      " 77  comp_games         9660 non-null   object \n",
      " 78  fam_tv_eve         11174 non-null  float64\n",
      " 79  fam_tv_aft         11038 non-null  float64\n",
      " 80  fam_tv_mor         11096 non-null  float64\n",
      " 81  sex                13734 non-null  object \n",
      " 82  birth_order        13734 non-null  object \n",
      " 83  alon               4837 non-null   float64\n",
      " 84  draw               4827 non-null   float64\n",
      " 85  musi               4816 non-null   float64\n",
      " 86  out_sum            4812 non-null   float64\n",
      " 87  phone_14           5949 non-null   float64\n",
      " 88  play               4834 non-null   float64\n",
      " 89  read               4825 non-null   float64\n",
      " 90  text               4824 non-null   float64\n",
      " 91  tran               4854 non-null   float64\n",
      " 92  work               4828 non-null   float64\n",
      " 93  comp               13734 non-null  bool   \n",
      " 94  comp_bed_16        13734 non-null  bool   \n",
      " 95  tv                 4849 non-null   float64\n",
      " 96  talk_mob           4830 non-null   float64\n",
      " 97  talk_phon          4834 non-null   float64\n",
      " 98  fam_tv             10895 non-null  float64\n",
      "dtypes: bool(6), float64(61), int64(1), object(31)\n",
      "memory usage: 9.8+ MB\n"
     ]
    }
   ],
   "source": [
    "df = pd.DataFrame(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1800x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "msno.matrix(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "transposed_data = data.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "missing_data = pd.DataFrame(data[data.columns[data.isnull().any()]].isnull().sum()/len(data)*100)\n",
    "\n",
    "names = []\n",
    "for i in range(len(missing_data)):\n",
    "        names.append(missing_data.iloc[i].name)\n",
    "values = []\n",
    "for i in range(len(missing_data)):\n",
    "        values.append(missing_data.iloc[i][0])\n",
    "\n",
    "data_1 = {'Features': names,'% Missing Data': values}\n",
    "missing_df = pd.DataFrame(data_1)\n",
    "missing_df.sort_values(by = ['% Missing Data'], ascending = False)\n",
    "\n",
    "\n",
    "missing_df_bar_plot = missing_df.plot.bar(x= \"Features\", y= \"% Missing Data\", title= \"Features with Missing Data\",figsize=(10,6))\n",
    "missing_df_bar_plot.axhline(40, color = 'red')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}