EDA-Age.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DOC constituents - EDA, pre-processing - Age"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Age vs Claim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "# sns.set()\n",
    "from palettable.colorbrewer.diverging import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(style='whitegrid', palette=\"Spectral_r\")\n",
    "# dual_colors = [ '#009fca','#00f8b9'] #'#005e79',"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cb_pal = sns.cubehelix_palette(8, start=0.5, rot=-.75)\n",
    "cpal = sns.color_palette(\"Blues\")\n",
    "# dual_colors = [cpal[3],cpal[2]]\n",
    "# sns.set_palette(cpal)\n",
    "sns.palplot(cpal)\n",
    "sns.palplot(cb_pal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x72 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = Spectral_8.hex_colors\n",
    "dual_colors = [colors[-1],colors[4]]\n",
    "sns.palplot(colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plt.style.use('seaborn-white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Agency</th>\n",
       "      <th>Agency Type</th>\n",
       "      <th>Distribution Channel</th>\n",
       "      <th>Product Name</th>\n",
       "      <th>Duration</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Net Sales</th>\n",
       "      <th>Commision (in value)</th>\n",
       "      <th>Age</th>\n",
       "      <th>Claim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>Cancellation Plan</td>\n",
       "      <td>61</td>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4245</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>Cancellation Plan</td>\n",
       "      <td>4</td>\n",
       "      <td>MALAYSIA</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9251</td>\n",
       "      <td>CWT</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>Rental Vehicle Excess Insurance</td>\n",
       "      <td>26</td>\n",
       "      <td>THAILAND</td>\n",
       "      <td>19.8</td>\n",
       "      <td>11.88</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4754</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>2 way Comprehensive Plan</td>\n",
       "      <td>15</td>\n",
       "      <td>HONG KONG</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8840</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>2 way Comprehensive Plan</td>\n",
       "      <td>15</td>\n",
       "      <td>MALAYSIA</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     ID Agency    Agency Type Distribution Channel  \\\n",
       "0  2010    EPX  Travel Agency               Online   \n",
       "1  4245    EPX  Travel Agency               Online   \n",
       "2  9251    CWT  Travel Agency               Online   \n",
       "3  4754    EPX  Travel Agency               Online   \n",
       "4  8840    EPX  Travel Agency               Online   \n",
       "\n",
       "                      Product Name  Duration  Destination  Net Sales  \\\n",
       "0                Cancellation Plan        61  PHILIPPINES       12.0   \n",
       "1                Cancellation Plan         4     MALAYSIA       17.0   \n",
       "2  Rental Vehicle Excess Insurance        26     THAILAND       19.8   \n",
       "3         2 way Comprehensive Plan        15    HONG KONG       27.0   \n",
       "4         2 way Comprehensive Plan        15     MALAYSIA       37.0   \n",
       "\n",
       "   Commision (in value)  Age  Claim  \n",
       "0                  0.00   41      0  \n",
       "1                  0.00   35      0  \n",
       "2                 11.88   47      0  \n",
       "3                  0.00   48      0  \n",
       "4                  0.00   36      0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"../data/train.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = df.columns.map(lambda x: x.lower())\n",
    "df.columns = df.columns.map(lambda x: x.replace(\" \",\"_\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>agency</th>\n",
       "      <th>agency_type</th>\n",
       "      <th>distribution_channel</th>\n",
       "      <th>product_name</th>\n",
       "      <th>duration</th>\n",
       "      <th>destination</th>\n",
       "      <th>net_sales</th>\n",
       "      <th>commision_(in_value)</th>\n",
       "      <th>age</th>\n",
       "      <th>claim</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>Cancellation Plan</td>\n",
       "      <td>61</td>\n",
       "      <td>PHILIPPINES</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>41</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4245</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>Cancellation Plan</td>\n",
       "      <td>4</td>\n",
       "      <td>MALAYSIA</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9251</td>\n",
       "      <td>CWT</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>Rental Vehicle Excess Insurance</td>\n",
       "      <td>26</td>\n",
       "      <td>THAILAND</td>\n",
       "      <td>19.8</td>\n",
       "      <td>11.88</td>\n",
       "      <td>47</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4754</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>2 way Comprehensive Plan</td>\n",
       "      <td>15</td>\n",
       "      <td>HONG KONG</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>48</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8840</td>\n",
       "      <td>EPX</td>\n",
       "      <td>Travel Agency</td>\n",
       "      <td>Online</td>\n",
       "      <td>2 way Comprehensive Plan</td>\n",
       "      <td>15</td>\n",
       "      <td>MALAYSIA</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>36</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     id agency    agency_type distribution_channel  \\\n",
       "0  2010    EPX  Travel Agency               Online   \n",
       "1  4245    EPX  Travel Agency               Online   \n",
       "2  9251    CWT  Travel Agency               Online   \n",
       "3  4754    EPX  Travel Agency               Online   \n",
       "4  8840    EPX  Travel Agency               Online   \n",
       "\n",
       "                      product_name  duration  destination  net_sales  \\\n",
       "0                Cancellation Plan        61  PHILIPPINES       12.0   \n",
       "1                Cancellation Plan         4     MALAYSIA       17.0   \n",
       "2  Rental Vehicle Excess Insurance        26     THAILAND       19.8   \n",
       "3         2 way Comprehensive Plan        15    HONG KONG       27.0   \n",
       "4         2 way Comprehensive Plan        15     MALAYSIA       37.0   \n",
       "\n",
       "   commision_(in_value)  age  claim  \n",
       "0                  0.00   41      0  \n",
       "1                  0.00   35      0  \n",
       "2                 11.88   47      0  \n",
       "3                  0.00   48      0  \n",
       "4                  0.00   36      0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a245e4ac8>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df.age)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Converting age to categorical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"age_cut\"] = pd.cut(df.age, [0,20,40,60,80,100,120])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 40]      37131\n",
       "(40, 60]      11849\n",
       "(60, 80]       2147\n",
       "(100, 120]      737\n",
       "(0, 20]         356\n",
       "(80, 100]        88\n",
       "Name: age_cut, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.age_cut.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Interval(20, 40, closed='right')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "da = df.age_cut.value_counts().index\n",
    "da[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "age_dict = {da[0]:\"20-40\",da[1]:\"40-60\",da[2]:\"60-80\",da[3]:\"100-120\",da[4]:\"0-20\",da[5]:\"80-1000\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{Interval(20, 40, closed='right'): '20-40',\n",
       " Interval(40, 60, closed='right'): '40-60',\n",
       " Interval(60, 80, closed='right'): '60-80',\n",
       " Interval(100, 120, closed='right'): '100-120',\n",
       " Interval(0, 20, closed='right'): '0-20',\n",
       " Interval(80, 100, closed='right'): '80-1000'}"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df.age_cut = df.age_cut.map(age_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(20, 40]      37131\n",
       "(40, 60]      11849\n",
       "(60, 80]       2147\n",
       "(100, 120]      737\n",
       "(0, 20]         356\n",
       "(80, 100]        88\n",
       "Name: age_cut, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.age_cut.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.age_cut.value_counts().plot.bar()\n",
    "for num, counts in enumerate(df.age_cut.value_counts()):\n",
    "    plt.text(x=num, y=counts, s = counts)\n",
    "plt.xlabel(\"Age group\")\n",
    "plt.ylabel(\"Counts\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Majority travellers are in the age group 20-60."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>claim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age_cut</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>(0, 20]</th>\n",
       "      <td>0.680558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(20, 40]</th>\n",
       "      <td>70.982604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(40, 60]</th>\n",
       "      <td>22.651501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(60, 80]</th>\n",
       "      <td>4.104378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(80, 100]</th>\n",
       "      <td>0.168228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>(100, 120]</th>\n",
       "      <td>1.408908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                claim\n",
       "age_cut              \n",
       "(0, 20]      0.680558\n",
       "(20, 40]    70.982604\n",
       "(40, 60]    22.651501\n",
       "(60, 80]     4.104378\n",
       "(80, 100]    0.168228\n",
       "(100, 120]   1.408908"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age_claims = (df.groupby([\"age_cut\"])[[\"claim\"]].count()/len(df)*100)\n",
    "ax = (df.groupby([\"age_cut\"])[[\"claim\"]].count()/len(df)*100).plot(kind=\"bar\",figsize=(10,8))\n",
    "for p in ax.patches:\n",
    "    w,h = p.get_width(), p.get_height()\n",
    "    x,y = p.get_xy()\n",
    "    ax.annotate(str(np.round(h,2))+\"%\", (x,y+h+0.5))\n",
    "plt.xlabel(\"Age group\")\n",
    "plt.ylabel(\"Claims\")\n",
    "plt.title(\"Age group has most Claims\",fontdict={'fontsize':14})\n",
    "plt.show()\n",
    "age_claims"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# df.groupby([\"age_cut\"])[\"claim\"].value_counts().plot(kind='pie')\n",
    "age_claims.reset_index().claim.plot(kind='pie',figsize=(8,8),autopct='%1.1f%%')\n",
    "plt.legend(age_claims.index,bbox_to_anchor=(1,1))\n",
    "plt.title(\"Age group has most claims\",fontdict={'fontsize':14})\n",
    "plt.ylabel('Claims')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Majority Claims were made by people in age group 20-60, mainly 20-40."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>claim</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age_cut</th>\n",
       "      <th>claim</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(0, 20]</th>\n",
       "      <th>0</th>\n",
       "      <td>88.483146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.516854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(20, 40]</th>\n",
       "      <th>0</th>\n",
       "      <td>82.922625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>17.077375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(40, 60]</th>\n",
       "      <th>0</th>\n",
       "      <td>83.475399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16.524601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(60, 80]</th>\n",
       "      <th>0</th>\n",
       "      <td>85.933861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>14.066139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(80, 100]</th>\n",
       "      <th>0</th>\n",
       "      <td>89.772727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.227273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(100, 120]</th>\n",
       "      <th>0</th>\n",
       "      <td>90.637720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.362280</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      claim\n",
       "age_cut    claim           \n",
       "(0, 20]    0      88.483146\n",
       "           1      11.516854\n",
       "(20, 40]   0      82.922625\n",
       "           1      17.077375\n",
       "(40, 60]   0      83.475399\n",
       "           1      16.524601\n",
       "(60, 80]   0      85.933861\n",
       "           1      14.066139\n",
       "(80, 100]  0      89.772727\n",
       "           1      10.227273\n",
       "(100, 120] 0      90.637720\n",
       "           1       9.362280"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "age_claim_rate = df.groupby([\"age_cut\",\"claim\"])[[\"claim\"]].count()/df.groupby([\"age_cut\"])[[\"claim\"]].count()*100\n",
    "age_claim_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = age_claim_rate.unstack().plot(kind=\"bar\", figsize=(8,6))\n",
    "for p in ax.patches:\n",
    "    w,h = p.get_width(), p.get_height()\n",
    "    x,y = p.get_xy()\n",
    "    ax.annotate(str(np.round(h,2))+\"%\", (x,y+h+0.5))\n",
    "plt.xlabel(\"Age group\")\n",
    "plt.ylabel(\"Claim Rate\")\n",
    "plt.title(\"Age group with the most Claims approval rate\",fontdict={'fontsize':14})\n",
    "plt.legend(['Claim: Denied','Claim: Approved'],loc='upper left')\n",
    "plt.ylim((0,110))\n",
    "plt.xticks(rotation='horizontal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "age_claim_rate.columns = ['Claim Rate']\n",
    "age_claim_rate_ri = age_claim_rate.reset_index().set_index('age_cut')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = age_claim_rate.unstack().plot(kind=\"barh\", figsize=(8,8),stacked=True)\n",
    "for p in ax.patches:\n",
    "    w,h = p.get_width(), p.get_height()\n",
    "    x,y = p.get_xy()\n",
    "    ax.annotate(str(np.round(w,2))+\"%\", (x,y+h-0.25), color='white')\n",
    "plt.ylabel(\"Age group\")\n",
    "plt.xlabel(\"Claim Rate\")\n",
    "plt.title(\"Age group with the most Claims approval rate\",fontdict={'fontsize':14})\n",
    "plt.legend(['Claim: Denied','Claim: Approved'],bbox_to_anchor=(1,1))\n",
    "# plt.xlim((0,115))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>agency_type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age_cut</th>\n",
       "      <th>agency_type</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(0, 20]</th>\n",
       "      <th>Airlines</th>\n",
       "      <td>51.123596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel Agency</th>\n",
       "      <td>48.876404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(20, 40]</th>\n",
       "      <th>Airlines</th>\n",
       "      <td>25.410035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel Agency</th>\n",
       "      <td>74.589965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(40, 60]</th>\n",
       "      <th>Airlines</th>\n",
       "      <td>49.978901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel Agency</th>\n",
       "      <td>50.021099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(60, 80]</th>\n",
       "      <th>Airlines</th>\n",
       "      <td>50.489054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel Agency</th>\n",
       "      <td>49.510946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(80, 100]</th>\n",
       "      <th>Airlines</th>\n",
       "      <td>52.272727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel Agency</th>\n",
       "      <td>47.727273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">(100, 120]</th>\n",
       "      <th>Airlines</th>\n",
       "      <td>87.516961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel Agency</th>\n",
       "      <td>12.483039</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          agency_type\n",
       "age_cut    agency_type               \n",
       "(0, 20]    Airlines         51.123596\n",
       "           Travel Agency    48.876404\n",
       "(20, 40]   Airlines         25.410035\n",
       "           Travel Agency    74.589965\n",
       "(40, 60]   Airlines         49.978901\n",
       "           Travel Agency    50.021099\n",
       "(60, 80]   Airlines         50.489054\n",
       "           Travel Agency    49.510946\n",
       "(80, 100]  Airlines         52.272727\n",
       "           Travel Agency    47.727273\n",
       "(100, 120] Airlines         87.516961\n",
       "           Travel Agency    12.483039"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby([\"age_cut\",\"agency_type\"])[[\"agency_type\"]].count()/df.groupby([\"age_cut\"])[[\"agency_type\"]].count()*100"
   ]
  },
  {
   "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": "3.7.3"
  }
 },
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 "nbformat_minor": 4
}