Customer Churn Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "df384be3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1bda8a8e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>state</th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>...</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>customer service calls</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KS</td>\n",
       "      <td>128</td>\n",
       "      <td>415</td>\n",
       "      <td>382-4657</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25</td>\n",
       "      <td>265.1</td>\n",
       "      <td>110</td>\n",
       "      <td>45.07</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>16.78</td>\n",
       "      <td>244.7</td>\n",
       "      <td>91</td>\n",
       "      <td>11.01</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OH</td>\n",
       "      <td>107</td>\n",
       "      <td>415</td>\n",
       "      <td>371-7191</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>26</td>\n",
       "      <td>161.6</td>\n",
       "      <td>123</td>\n",
       "      <td>27.47</td>\n",
       "      <td>...</td>\n",
       "      <td>103</td>\n",
       "      <td>16.62</td>\n",
       "      <td>254.4</td>\n",
       "      <td>103</td>\n",
       "      <td>11.45</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NJ</td>\n",
       "      <td>137</td>\n",
       "      <td>415</td>\n",
       "      <td>358-1921</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>243.4</td>\n",
       "      <td>114</td>\n",
       "      <td>41.38</td>\n",
       "      <td>...</td>\n",
       "      <td>110</td>\n",
       "      <td>10.30</td>\n",
       "      <td>162.6</td>\n",
       "      <td>104</td>\n",
       "      <td>7.32</td>\n",
       "      <td>12.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OH</td>\n",
       "      <td>84</td>\n",
       "      <td>408</td>\n",
       "      <td>375-9999</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>299.4</td>\n",
       "      <td>71</td>\n",
       "      <td>50.90</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>5.26</td>\n",
       "      <td>196.9</td>\n",
       "      <td>89</td>\n",
       "      <td>8.86</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OK</td>\n",
       "      <td>75</td>\n",
       "      <td>415</td>\n",
       "      <td>330-6626</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>166.7</td>\n",
       "      <td>113</td>\n",
       "      <td>28.34</td>\n",
       "      <td>...</td>\n",
       "      <td>122</td>\n",
       "      <td>12.61</td>\n",
       "      <td>186.9</td>\n",
       "      <td>121</td>\n",
       "      <td>8.41</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.73</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AL</td>\n",
       "      <td>118</td>\n",
       "      <td>510</td>\n",
       "      <td>391-8027</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>223.4</td>\n",
       "      <td>98</td>\n",
       "      <td>37.98</td>\n",
       "      <td>...</td>\n",
       "      <td>101</td>\n",
       "      <td>18.75</td>\n",
       "      <td>203.9</td>\n",
       "      <td>118</td>\n",
       "      <td>9.18</td>\n",
       "      <td>6.3</td>\n",
       "      <td>6</td>\n",
       "      <td>1.70</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>MA</td>\n",
       "      <td>121</td>\n",
       "      <td>510</td>\n",
       "      <td>355-9993</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>24</td>\n",
       "      <td>218.2</td>\n",
       "      <td>88</td>\n",
       "      <td>37.09</td>\n",
       "      <td>...</td>\n",
       "      <td>108</td>\n",
       "      <td>29.62</td>\n",
       "      <td>212.6</td>\n",
       "      <td>118</td>\n",
       "      <td>9.57</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7</td>\n",
       "      <td>2.03</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>MO</td>\n",
       "      <td>147</td>\n",
       "      <td>415</td>\n",
       "      <td>329-9001</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>79</td>\n",
       "      <td>26.69</td>\n",
       "      <td>...</td>\n",
       "      <td>94</td>\n",
       "      <td>8.76</td>\n",
       "      <td>211.8</td>\n",
       "      <td>96</td>\n",
       "      <td>9.53</td>\n",
       "      <td>7.1</td>\n",
       "      <td>6</td>\n",
       "      <td>1.92</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>LA</td>\n",
       "      <td>117</td>\n",
       "      <td>408</td>\n",
       "      <td>335-4719</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>184.5</td>\n",
       "      <td>97</td>\n",
       "      <td>31.37</td>\n",
       "      <td>...</td>\n",
       "      <td>80</td>\n",
       "      <td>29.89</td>\n",
       "      <td>215.8</td>\n",
       "      <td>90</td>\n",
       "      <td>9.71</td>\n",
       "      <td>8.7</td>\n",
       "      <td>4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>WV</td>\n",
       "      <td>141</td>\n",
       "      <td>415</td>\n",
       "      <td>330-8173</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>37</td>\n",
       "      <td>258.6</td>\n",
       "      <td>84</td>\n",
       "      <td>43.96</td>\n",
       "      <td>...</td>\n",
       "      <td>111</td>\n",
       "      <td>18.87</td>\n",
       "      <td>326.4</td>\n",
       "      <td>97</td>\n",
       "      <td>14.69</td>\n",
       "      <td>11.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.02</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  state  account length  area code phone number international plan  \\\n",
       "0    KS             128        415     382-4657                 no   \n",
       "1    OH             107        415     371-7191                 no   \n",
       "2    NJ             137        415     358-1921                 no   \n",
       "3    OH              84        408     375-9999                yes   \n",
       "4    OK              75        415     330-6626                yes   \n",
       "5    AL             118        510     391-8027                yes   \n",
       "6    MA             121        510     355-9993                 no   \n",
       "7    MO             147        415     329-9001                yes   \n",
       "8    LA             117        408     335-4719                 no   \n",
       "9    WV             141        415     330-8173                yes   \n",
       "\n",
       "  voice mail plan  number vmail messages  total day minutes  total day calls  \\\n",
       "0             yes                     25              265.1              110   \n",
       "1             yes                     26              161.6              123   \n",
       "2              no                      0              243.4              114   \n",
       "3              no                      0              299.4               71   \n",
       "4              no                      0              166.7              113   \n",
       "5              no                      0              223.4               98   \n",
       "6             yes                     24              218.2               88   \n",
       "7              no                      0              157.0               79   \n",
       "8              no                      0              184.5               97   \n",
       "9             yes                     37              258.6               84   \n",
       "\n",
       "   total day charge  ...  total eve calls  total eve charge  \\\n",
       "0             45.07  ...               99             16.78   \n",
       "1             27.47  ...              103             16.62   \n",
       "2             41.38  ...              110             10.30   \n",
       "3             50.90  ...               88              5.26   \n",
       "4             28.34  ...              122             12.61   \n",
       "5             37.98  ...              101             18.75   \n",
       "6             37.09  ...              108             29.62   \n",
       "7             26.69  ...               94              8.76   \n",
       "8             31.37  ...               80             29.89   \n",
       "9             43.96  ...              111             18.87   \n",
       "\n",
       "   total night minutes  total night calls  total night charge  \\\n",
       "0                244.7                 91               11.01   \n",
       "1                254.4                103               11.45   \n",
       "2                162.6                104                7.32   \n",
       "3                196.9                 89                8.86   \n",
       "4                186.9                121                8.41   \n",
       "5                203.9                118                9.18   \n",
       "6                212.6                118                9.57   \n",
       "7                211.8                 96                9.53   \n",
       "8                215.8                 90                9.71   \n",
       "9                326.4                 97               14.69   \n",
       "\n",
       "   total intl minutes  total intl calls  total intl charge  \\\n",
       "0                10.0                 3               2.70   \n",
       "1                13.7                 3               3.70   \n",
       "2                12.2                 5               3.29   \n",
       "3                 6.6                 7               1.78   \n",
       "4                10.1                 3               2.73   \n",
       "5                 6.3                 6               1.70   \n",
       "6                 7.5                 7               2.03   \n",
       "7                 7.1                 6               1.92   \n",
       "8                 8.7                 4               2.35   \n",
       "9                11.2                 5               3.02   \n",
       "\n",
       "   customer service calls  churn  \n",
       "0                       1  False  \n",
       "1                       1  False  \n",
       "2                       0  False  \n",
       "3                       2  False  \n",
       "4                       3  False  \n",
       "5                       0  False  \n",
       "6                       3  False  \n",
       "7                       0  False  \n",
       "8                       1  False  \n",
       "9                       0  False  \n",
       "\n",
       "[10 rows x 21 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"bigml.csv\")\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "81fed6b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3333, 21)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "89b8a0f1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['state', 'account length', 'area code', 'phone number',\n",
      "       'international plan', 'voice mail plan', 'number vmail messages',\n",
      "       'total day minutes', 'total day calls', 'total day charge',\n",
      "       'total eve minutes', 'total eve calls', 'total eve charge',\n",
      "       'total night minutes', 'total night calls', 'total night charge',\n",
      "       'total intl minutes', 'total intl calls', 'total intl charge',\n",
      "       'customer service calls', 'churn'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(data.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8bd2e3c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "        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>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>total eve minutes</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>customer service calls</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "      <td>3333.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>101.064806</td>\n",
       "      <td>437.182418</td>\n",
       "      <td>8.099010</td>\n",
       "      <td>179.775098</td>\n",
       "      <td>100.435644</td>\n",
       "      <td>30.562307</td>\n",
       "      <td>200.980348</td>\n",
       "      <td>100.114311</td>\n",
       "      <td>17.083540</td>\n",
       "      <td>200.872037</td>\n",
       "      <td>100.107711</td>\n",
       "      <td>9.039325</td>\n",
       "      <td>10.237294</td>\n",
       "      <td>4.479448</td>\n",
       "      <td>2.764581</td>\n",
       "      <td>1.562856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>39.822106</td>\n",
       "      <td>42.371290</td>\n",
       "      <td>13.688365</td>\n",
       "      <td>54.467389</td>\n",
       "      <td>20.069084</td>\n",
       "      <td>9.259435</td>\n",
       "      <td>50.713844</td>\n",
       "      <td>19.922625</td>\n",
       "      <td>4.310668</td>\n",
       "      <td>50.573847</td>\n",
       "      <td>19.568609</td>\n",
       "      <td>2.275873</td>\n",
       "      <td>2.791840</td>\n",
       "      <td>2.461214</td>\n",
       "      <td>0.753773</td>\n",
       "      <td>1.315491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>408.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>23.200000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>1.040000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>74.000000</td>\n",
       "      <td>408.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>143.700000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>24.430000</td>\n",
       "      <td>166.600000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>14.160000</td>\n",
       "      <td>167.000000</td>\n",
       "      <td>87.000000</td>\n",
       "      <td>7.520000</td>\n",
       "      <td>8.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>101.000000</td>\n",
       "      <td>415.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>179.400000</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>201.400000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>17.120000</td>\n",
       "      <td>201.200000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>9.050000</td>\n",
       "      <td>10.300000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.780000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>127.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>216.400000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>36.790000</td>\n",
       "      <td>235.300000</td>\n",
       "      <td>114.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>235.300000</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>10.590000</td>\n",
       "      <td>12.100000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.270000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>243.000000</td>\n",
       "      <td>510.000000</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>350.800000</td>\n",
       "      <td>165.000000</td>\n",
       "      <td>59.640000</td>\n",
       "      <td>363.700000</td>\n",
       "      <td>170.000000</td>\n",
       "      <td>30.910000</td>\n",
       "      <td>395.000000</td>\n",
       "      <td>175.000000</td>\n",
       "      <td>17.770000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       account length    area code  number vmail messages  total day minutes  \\\n",
       "count     3333.000000  3333.000000            3333.000000        3333.000000   \n",
       "mean       101.064806   437.182418               8.099010         179.775098   \n",
       "std         39.822106    42.371290              13.688365          54.467389   \n",
       "min          1.000000   408.000000               0.000000           0.000000   \n",
       "25%         74.000000   408.000000               0.000000         143.700000   \n",
       "50%        101.000000   415.000000               0.000000         179.400000   \n",
       "75%        127.000000   510.000000              20.000000         216.400000   \n",
       "max        243.000000   510.000000              51.000000         350.800000   \n",
       "\n",
       "       total day calls  total day charge  total eve minutes  total eve calls  \\\n",
       "count      3333.000000       3333.000000        3333.000000      3333.000000   \n",
       "mean        100.435644         30.562307         200.980348       100.114311   \n",
       "std          20.069084          9.259435          50.713844        19.922625   \n",
       "min           0.000000          0.000000           0.000000         0.000000   \n",
       "25%          87.000000         24.430000         166.600000        87.000000   \n",
       "50%         101.000000         30.500000         201.400000       100.000000   \n",
       "75%         114.000000         36.790000         235.300000       114.000000   \n",
       "max         165.000000         59.640000         363.700000       170.000000   \n",
       "\n",
       "       total eve charge  total night minutes  total night calls  \\\n",
       "count       3333.000000          3333.000000        3333.000000   \n",
       "mean          17.083540           200.872037         100.107711   \n",
       "std            4.310668            50.573847          19.568609   \n",
       "min            0.000000            23.200000          33.000000   \n",
       "25%           14.160000           167.000000          87.000000   \n",
       "50%           17.120000           201.200000         100.000000   \n",
       "75%           20.000000           235.300000         113.000000   \n",
       "max           30.910000           395.000000         175.000000   \n",
       "\n",
       "       total night charge  total intl minutes  total intl calls  \\\n",
       "count         3333.000000         3333.000000       3333.000000   \n",
       "mean             9.039325           10.237294          4.479448   \n",
       "std              2.275873            2.791840          2.461214   \n",
       "min              1.040000            0.000000          0.000000   \n",
       "25%              7.520000            8.500000          3.000000   \n",
       "50%              9.050000           10.300000          4.000000   \n",
       "75%             10.590000           12.100000          6.000000   \n",
       "max             17.770000           20.000000         20.000000   \n",
       "\n",
       "       total intl charge  customer service calls  \n",
       "count        3333.000000             3333.000000  \n",
       "mean            2.764581                1.562856  \n",
       "std             0.753773                1.315491  \n",
       "min             0.000000                0.000000  \n",
       "25%             2.300000                1.000000  \n",
       "50%             2.780000                1.000000  \n",
       "75%             3.270000                2.000000  \n",
       "max             5.400000                9.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bfb43054",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 3333 entries, 0 to 3332\n",
      "Data columns (total 21 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   state                   3333 non-null   object \n",
      " 1   account length          3333 non-null   int64  \n",
      " 2   area code               3333 non-null   int64  \n",
      " 3   phone number            3333 non-null   object \n",
      " 4   international plan      3333 non-null   object \n",
      " 5   voice mail plan         3333 non-null   object \n",
      " 6   number vmail messages   3333 non-null   int64  \n",
      " 7   total day minutes       3333 non-null   float64\n",
      " 8   total day calls         3333 non-null   int64  \n",
      " 9   total day charge        3333 non-null   float64\n",
      " 10  total eve minutes       3333 non-null   float64\n",
      " 11  total eve calls         3333 non-null   int64  \n",
      " 12  total eve charge        3333 non-null   float64\n",
      " 13  total night minutes     3333 non-null   float64\n",
      " 14  total night calls       3333 non-null   int64  \n",
      " 15  total night charge      3333 non-null   float64\n",
      " 16  total intl minutes      3333 non-null   float64\n",
      " 17  total intl calls        3333 non-null   int64  \n",
      " 18  total intl charge       3333 non-null   float64\n",
      " 19  customer service calls  3333 non-null   int64  \n",
      " 20  churn                   3333 non-null   bool   \n",
      "dtypes: bool(1), float64(8), int64(8), object(4)\n",
      "memory usage: 524.2+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ab4b7f51",
   "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>state</th>\n",
       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3333</td>\n",
       "      <td>3333</td>\n",
       "      <td>3333</td>\n",
       "      <td>3333</td>\n",
       "      <td>3333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>51</td>\n",
       "      <td>3333</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>WV</td>\n",
       "      <td>382-4657</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>106</td>\n",
       "      <td>1</td>\n",
       "      <td>3010</td>\n",
       "      <td>2411</td>\n",
       "      <td>2850</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       state phone number international plan voice mail plan  churn\n",
       "count   3333         3333               3333            3333   3333\n",
       "unique    51         3333                  2               2      2\n",
       "top       WV     382-4657                 no              no  False\n",
       "freq     106            1               3010            2411   2850"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe(include=['object', 'bool'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e28502d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "churn\n",
       "False    2850\n",
       "True      483\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['churn'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "32535e33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "churn\n",
       "False    0.855086\n",
       "True     0.144914\n",
       "Name: proportion, dtype: float64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['churn'].value_counts(normalize = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3a953640",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state                     0\n",
       "account length            0\n",
       "area code                 0\n",
       "phone number              0\n",
       "international plan        0\n",
       "voice mail plan           0\n",
       "number vmail messages     0\n",
       "total day minutes         0\n",
       "total day calls           0\n",
       "total day charge          0\n",
       "total eve minutes         0\n",
       "total eve calls           0\n",
       "total eve charge          0\n",
       "total night minutes       0\n",
       "total night calls         0\n",
       "total night charge        0\n",
       "total intl minutes        0\n",
       "total intl calls          0\n",
       "total intl charge         0\n",
       "customer service calls    0\n",
       "churn                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a45d1e8b",
   "metadata": {},
   "source": [
    "## Sorting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c2ce134",
   "metadata": {},
   "source": [
    "A DataFrame can be sorted by the value of one of the variables (i.e columns). For example, we can sort by Total day charge (use ascending=False to sort in descending order):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7a74360b",
   "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>state</th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>...</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>customer service calls</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>365</th>\n",
       "      <td>CO</td>\n",
       "      <td>154</td>\n",
       "      <td>415</td>\n",
       "      <td>343-5709</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>350.8</td>\n",
       "      <td>75</td>\n",
       "      <td>59.64</td>\n",
       "      <td>...</td>\n",
       "      <td>94</td>\n",
       "      <td>18.40</td>\n",
       "      <td>253.9</td>\n",
       "      <td>100</td>\n",
       "      <td>11.43</td>\n",
       "      <td>10.1</td>\n",
       "      <td>9</td>\n",
       "      <td>2.73</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>NY</td>\n",
       "      <td>64</td>\n",
       "      <td>415</td>\n",
       "      <td>345-9140</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>346.8</td>\n",
       "      <td>55</td>\n",
       "      <td>58.96</td>\n",
       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>21.21</td>\n",
       "      <td>275.4</td>\n",
       "      <td>102</td>\n",
       "      <td>12.39</td>\n",
       "      <td>13.3</td>\n",
       "      <td>9</td>\n",
       "      <td>3.59</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2594</th>\n",
       "      <td>OH</td>\n",
       "      <td>115</td>\n",
       "      <td>510</td>\n",
       "      <td>348-1163</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>345.3</td>\n",
       "      <td>81</td>\n",
       "      <td>58.70</td>\n",
       "      <td>...</td>\n",
       "      <td>106</td>\n",
       "      <td>17.29</td>\n",
       "      <td>217.5</td>\n",
       "      <td>107</td>\n",
       "      <td>9.79</td>\n",
       "      <td>11.8</td>\n",
       "      <td>8</td>\n",
       "      <td>3.19</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>OH</td>\n",
       "      <td>83</td>\n",
       "      <td>415</td>\n",
       "      <td>370-9116</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>337.4</td>\n",
       "      <td>120</td>\n",
       "      <td>57.36</td>\n",
       "      <td>...</td>\n",
       "      <td>116</td>\n",
       "      <td>19.33</td>\n",
       "      <td>153.9</td>\n",
       "      <td>114</td>\n",
       "      <td>6.93</td>\n",
       "      <td>15.8</td>\n",
       "      <td>7</td>\n",
       "      <td>4.27</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>605</th>\n",
       "      <td>MO</td>\n",
       "      <td>112</td>\n",
       "      <td>415</td>\n",
       "      <td>373-2053</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>335.5</td>\n",
       "      <td>77</td>\n",
       "      <td>57.04</td>\n",
       "      <td>...</td>\n",
       "      <td>109</td>\n",
       "      <td>18.06</td>\n",
       "      <td>265.0</td>\n",
       "      <td>132</td>\n",
       "      <td>11.93</td>\n",
       "      <td>12.7</td>\n",
       "      <td>8</td>\n",
       "      <td>3.43</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     state  account length  area code phone number international plan  \\\n",
       "365     CO             154        415     343-5709                 no   \n",
       "985     NY              64        415     345-9140                yes   \n",
       "2594    OH             115        510     348-1163                yes   \n",
       "156     OH              83        415     370-9116                 no   \n",
       "605     MO             112        415     373-2053                 no   \n",
       "\n",
       "     voice mail plan  number vmail messages  total day minutes  \\\n",
       "365               no                      0              350.8   \n",
       "985               no                      0              346.8   \n",
       "2594              no                      0              345.3   \n",
       "156               no                      0              337.4   \n",
       "605               no                      0              335.5   \n",
       "\n",
       "      total day calls  total day charge  ...  total eve calls  \\\n",
       "365                75             59.64  ...               94   \n",
       "985                55             58.96  ...               79   \n",
       "2594               81             58.70  ...              106   \n",
       "156               120             57.36  ...              116   \n",
       "605                77             57.04  ...              109   \n",
       "\n",
       "      total eve charge  total night minutes  total night calls  \\\n",
       "365              18.40                253.9                100   \n",
       "985              21.21                275.4                102   \n",
       "2594             17.29                217.5                107   \n",
       "156              19.33                153.9                114   \n",
       "605              18.06                265.0                132   \n",
       "\n",
       "      total night charge  total intl minutes  total intl calls  \\\n",
       "365                11.43                10.1                 9   \n",
       "985                12.39                13.3                 9   \n",
       "2594                9.79                11.8                 8   \n",
       "156                 6.93                15.8                 7   \n",
       "605                11.93                12.7                 8   \n",
       "\n",
       "      total intl charge  customer service calls  churn  \n",
       "365                2.73                       1   True  \n",
       "985                3.59                       1   True  \n",
       "2594               3.19                       1   True  \n",
       "156                4.27                       0   True  \n",
       "605                3.43                       2   True  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sort_values(by='total day charge', ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c06773a8",
   "metadata": {},
   "source": [
    "We can also sort by multiple columns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b66e73b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
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       "      <th>area code</th>\n",
       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>...</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>customer service calls</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>365</th>\n",
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       "      <td>343-5709</td>\n",
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       "      <td>no</td>\n",
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       "      <td>75</td>\n",
       "      <td>59.64</td>\n",
       "      <td>...</td>\n",
       "      <td>94</td>\n",
       "      <td>18.40</td>\n",
       "      <td>253.9</td>\n",
       "      <td>100</td>\n",
       "      <td>11.43</td>\n",
       "      <td>10.1</td>\n",
       "      <td>9</td>\n",
       "      <td>2.73</td>\n",
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       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
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       "      <td>415</td>\n",
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       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>346.8</td>\n",
       "      <td>55</td>\n",
       "      <td>58.96</td>\n",
       "      <td>...</td>\n",
       "      <td>79</td>\n",
       "      <td>21.21</td>\n",
       "      <td>275.4</td>\n",
       "      <td>102</td>\n",
       "      <td>12.39</td>\n",
       "      <td>13.3</td>\n",
       "      <td>9</td>\n",
       "      <td>3.59</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>2594</th>\n",
       "      <td>OH</td>\n",
       "      <td>115</td>\n",
       "      <td>510</td>\n",
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       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>345.3</td>\n",
       "      <td>81</td>\n",
       "      <td>58.70</td>\n",
       "      <td>...</td>\n",
       "      <td>106</td>\n",
       "      <td>17.29</td>\n",
       "      <td>217.5</td>\n",
       "      <td>107</td>\n",
       "      <td>9.79</td>\n",
       "      <td>11.8</td>\n",
       "      <td>8</td>\n",
       "      <td>3.19</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>OH</td>\n",
       "      <td>83</td>\n",
       "      <td>415</td>\n",
       "      <td>370-9116</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>337.4</td>\n",
       "      <td>120</td>\n",
       "      <td>57.36</td>\n",
       "      <td>...</td>\n",
       "      <td>116</td>\n",
       "      <td>19.33</td>\n",
       "      <td>153.9</td>\n",
       "      <td>114</td>\n",
       "      <td>6.93</td>\n",
       "      <td>15.8</td>\n",
       "      <td>7</td>\n",
       "      <td>4.27</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>605</th>\n",
       "      <td>MO</td>\n",
       "      <td>112</td>\n",
       "      <td>415</td>\n",
       "      <td>373-2053</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>335.5</td>\n",
       "      <td>77</td>\n",
       "      <td>57.04</td>\n",
       "      <td>...</td>\n",
       "      <td>109</td>\n",
       "      <td>18.06</td>\n",
       "      <td>265.0</td>\n",
       "      <td>132</td>\n",
       "      <td>11.93</td>\n",
       "      <td>12.7</td>\n",
       "      <td>8</td>\n",
       "      <td>3.43</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     state  account length  area code phone number international plan  \\\n",
       "365     CO             154        415     343-5709                 no   \n",
       "985     NY              64        415     345-9140                yes   \n",
       "2594    OH             115        510     348-1163                yes   \n",
       "156     OH              83        415     370-9116                 no   \n",
       "605     MO             112        415     373-2053                 no   \n",
       "\n",
       "     voice mail plan  number vmail messages  total day minutes  \\\n",
       "365               no                      0              350.8   \n",
       "985               no                      0              346.8   \n",
       "2594              no                      0              345.3   \n",
       "156               no                      0              337.4   \n",
       "605               no                      0              335.5   \n",
       "\n",
       "      total day calls  total day charge  ...  total eve calls  \\\n",
       "365                75             59.64  ...               94   \n",
       "985                55             58.96  ...               79   \n",
       "2594               81             58.70  ...              106   \n",
       "156               120             57.36  ...              116   \n",
       "605                77             57.04  ...              109   \n",
       "\n",
       "      total eve charge  total night minutes  total night calls  \\\n",
       "365              18.40                253.9                100   \n",
       "985              21.21                275.4                102   \n",
       "2594             17.29                217.5                107   \n",
       "156              19.33                153.9                114   \n",
       "605              18.06                265.0                132   \n",
       "\n",
       "      total night charge  total intl minutes  total intl calls  \\\n",
       "365                11.43                10.1                 9   \n",
       "985                12.39                13.3                 9   \n",
       "2594                9.79                11.8                 8   \n",
       "156                 6.93                15.8                 7   \n",
       "605                11.93                12.7                 8   \n",
       "\n",
       "      total intl charge  customer service calls  churn  \n",
       "365                2.73                       1   True  \n",
       "985                3.59                       1   True  \n",
       "2594               3.19                       1   True  \n",
       "156                4.27                       0   True  \n",
       "605                3.43                       2   True  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.sort_values(by=['total day charge','churn'], ascending=False).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70c0f7d5",
   "metadata": {},
   "source": [
    "## Indexing and retrieving data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4639d6ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.14491449144914492"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['churn'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9b3ff12b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "212.41014492753624"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['churn'] == 1]['total eve minutes'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1fd702fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100.56107660455487"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['churn'] == 1]['total eve calls'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fc7a6546",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100.39958592132506"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['churn'] == 1]['total night calls'].mean() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ed82bde4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['churn'] == 0) & (data['international plan'] == 'no')]['total intl minutes'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "224f16eb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.3"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['churn'] == 0) & (data['international plan'] == 'yes')]['total intl minutes'].min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "bd1bd6ee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18.9"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['churn'] == 0) & (data['international plan'] == 'no')]['total intl minutes'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5b7ae1e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13.0"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['churn'] == 0) & (data['international plan'] == 'yes')]['total intl minutes'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "75452d60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.777956989247311"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['churn'] == 0) & (data['international plan'] == 'yes')]['total intl minutes'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a4b543c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.185472972972972"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[(data['churn'] == 0) & (data['international plan'] == 'no')]['total intl minutes'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45a981de",
   "metadata": {},
   "source": [
    "DataFrames can be indexed by column name (label) or row name (index) or by the serial number of a row. The loc method is used for indexing by name, while iloc() is used for indexing by number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "45affa88",
   "metadata": {},
   "outputs": [
    {
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      ],
      "text/plain": [
       "  state  account length  area code\n",
       "0    KS             128        415\n",
       "1    OH             107        415\n",
       "2    NJ             137        415\n",
       "3    OH              84        408\n",
       "4    OK              75        415\n",
       "5    AL             118        510"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[0:5, 'state':'area code']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ef7b5928",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>yes</td>\n",
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      ],
      "text/plain": [
       "   account length  area code phone number international plan\n",
       "0             128        415     382-4657                 no\n",
       "1             107        415     371-7191                 no\n",
       "2             137        415     358-1921                 no\n",
       "3              84        408     375-9999                yes\n",
       "4              75        415     330-6626                yes\n",
       "5             118        510     391-8027                yes\n",
       "6             121        510     355-9993                 no\n",
       "7             147        415     329-9001                yes"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.iloc[0:8, 1:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "de7bf9f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3332</th>\n",
       "      <td>TN</td>\n",
       "      <td>74</td>\n",
       "      <td>415</td>\n",
       "      <td>400-4344</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>25</td>\n",
       "      <td>234.4</td>\n",
       "      <td>113</td>\n",
       "      <td>39.85</td>\n",
       "      <td>...</td>\n",
       "      <td>82</td>\n",
       "      <td>22.6</td>\n",
       "      <td>241.4</td>\n",
       "      <td>77</td>\n",
       "      <td>10.86</td>\n",
       "      <td>13.7</td>\n",
       "      <td>4</td>\n",
       "      <td>3.7</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     state  account length  area code phone number international plan  \\\n",
       "3332    TN              74        415     400-4344                 no   \n",
       "\n",
       "     voice mail plan  number vmail messages  total day minutes  \\\n",
       "3332             yes                     25              234.4   \n",
       "\n",
       "      total day calls  total day charge  ...  total eve calls  \\\n",
       "3332              113             39.85  ...               82   \n",
       "\n",
       "      total eve charge  total night minutes  total night calls  \\\n",
       "3332              22.6                241.4                 77   \n",
       "\n",
       "      total night charge  total intl minutes  total intl calls  \\\n",
       "3332               10.86                13.7                 4   \n",
       "\n",
       "      total intl charge  customer service calls  churn  \n",
       "3332                3.7                       0  False  \n",
       "\n",
       "[1 rows x 21 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[-1:]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f66cd31",
   "metadata": {},
   "source": [
    "## Applying Functions to Cells, Columns and Rows"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "564d6202",
   "metadata": {},
   "source": [
    "To apply functions to each column, use apply():"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "dea436ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state                           WY\n",
       "account length                 243\n",
       "area code                      510\n",
       "phone number              422-9964\n",
       "international plan             yes\n",
       "voice mail plan                yes\n",
       "number vmail messages           51\n",
       "total day minutes            350.8\n",
       "total day calls                165\n",
       "total day charge             59.64\n",
       "total eve minutes            363.7\n",
       "total eve calls                170\n",
       "total eve charge             30.91\n",
       "total night minutes          395.0\n",
       "total night calls              175\n",
       "total night charge           17.77\n",
       "total intl minutes            20.0\n",
       "total intl calls                20\n",
       "total intl charge              5.4\n",
       "customer service calls           9\n",
       "churn                         True\n",
       "dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.apply(np.max)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "030ab925",
   "metadata": {},
   "source": [
    "The apply method can also be used to apply a function to each row. To do this, specify axis=1. Lambda functions are very convenient in such scenarios. For example, if we need to select all states starting with W"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "58cee284",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>...</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>customer service calls</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>WV</td>\n",
       "      <td>141</td>\n",
       "      <td>415</td>\n",
       "      <td>330-8173</td>\n",
       "      <td>yes</td>\n",
       "      <td>yes</td>\n",
       "      <td>37</td>\n",
       "      <td>258.6</td>\n",
       "      <td>84</td>\n",
       "      <td>43.96</td>\n",
       "      <td>...</td>\n",
       "      <td>111</td>\n",
       "      <td>18.87</td>\n",
       "      <td>326.4</td>\n",
       "      <td>97</td>\n",
       "      <td>14.69</td>\n",
       "      <td>11.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.02</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>WY</td>\n",
       "      <td>57</td>\n",
       "      <td>408</td>\n",
       "      <td>357-3817</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>39</td>\n",
       "      <td>213.0</td>\n",
       "      <td>115</td>\n",
       "      <td>36.21</td>\n",
       "      <td>...</td>\n",
       "      <td>112</td>\n",
       "      <td>16.24</td>\n",
       "      <td>182.7</td>\n",
       "      <td>115</td>\n",
       "      <td>8.22</td>\n",
       "      <td>9.5</td>\n",
       "      <td>3</td>\n",
       "      <td>2.57</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>WI</td>\n",
       "      <td>64</td>\n",
       "      <td>510</td>\n",
       "      <td>352-1237</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>67</td>\n",
       "      <td>26.18</td>\n",
       "      <td>...</td>\n",
       "      <td>118</td>\n",
       "      <td>19.19</td>\n",
       "      <td>265.3</td>\n",
       "      <td>86</td>\n",
       "      <td>11.94</td>\n",
       "      <td>3.5</td>\n",
       "      <td>3</td>\n",
       "      <td>0.95</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>WY</td>\n",
       "      <td>97</td>\n",
       "      <td>415</td>\n",
       "      <td>405-7146</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>24</td>\n",
       "      <td>133.2</td>\n",
       "      <td>135</td>\n",
       "      <td>22.64</td>\n",
       "      <td>...</td>\n",
       "      <td>58</td>\n",
       "      <td>18.46</td>\n",
       "      <td>70.6</td>\n",
       "      <td>79</td>\n",
       "      <td>3.18</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.97</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>WY</td>\n",
       "      <td>87</td>\n",
       "      <td>415</td>\n",
       "      <td>353-3759</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>83</td>\n",
       "      <td>25.67</td>\n",
       "      <td>...</td>\n",
       "      <td>116</td>\n",
       "      <td>18.67</td>\n",
       "      <td>203.9</td>\n",
       "      <td>127</td>\n",
       "      <td>9.18</td>\n",
       "      <td>9.7</td>\n",
       "      <td>3</td>\n",
       "      <td>2.62</td>\n",
       "      <td>5</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   state  account length  area code phone number international plan  \\\n",
       "9     WV             141        415     330-8173                yes   \n",
       "26    WY              57        408     357-3817                 no   \n",
       "44    WI              64        510     352-1237                 no   \n",
       "49    WY              97        415     405-7146                 no   \n",
       "54    WY              87        415     353-3759                 no   \n",
       "\n",
       "   voice mail plan  number vmail messages  total day minutes  total day calls  \\\n",
       "9              yes                     37              258.6               84   \n",
       "26             yes                     39              213.0              115   \n",
       "44              no                      0              154.0               67   \n",
       "49             yes                     24              133.2              135   \n",
       "54              no                      0              151.0               83   \n",
       "\n",
       "    total day charge  ...  total eve calls  total eve charge  \\\n",
       "9              43.96  ...              111             18.87   \n",
       "26             36.21  ...              112             16.24   \n",
       "44             26.18  ...              118             19.19   \n",
       "49             22.64  ...               58             18.46   \n",
       "54             25.67  ...              116             18.67   \n",
       "\n",
       "    total night minutes  total night calls  total night charge  \\\n",
       "9                 326.4                 97               14.69   \n",
       "26                182.7                115                8.22   \n",
       "44                265.3                 86               11.94   \n",
       "49                 70.6                 79                3.18   \n",
       "54                203.9                127                9.18   \n",
       "\n",
       "    total intl minutes  total intl calls  total intl charge  \\\n",
       "9                 11.2                 5               3.02   \n",
       "26                 9.5                 3               2.57   \n",
       "44                 3.5                 3               0.95   \n",
       "49                11.0                 3               2.97   \n",
       "54                 9.7                 3               2.62   \n",
       "\n",
       "    customer service calls  churn  \n",
       "9                        0  False  \n",
       "26                       0  False  \n",
       "44                       1  False  \n",
       "49                       1  False  \n",
       "54                       5   True  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data['state'].apply(lambda state: state[0] == 'W')].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1075c833",
   "metadata": {},
   "source": [
    "The map method can be used to replace values in a column by passing a dictionary of the form {old_value: new_value} as its argument:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "36b801da",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>account length</th>\n",
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       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
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       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>...</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
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       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
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       "      <th>total intl charge</th>\n",
       "      <th>customer service calls</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KS</td>\n",
       "      <td>128</td>\n",
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       "      <td>False</td>\n",
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       "      <td>110</td>\n",
       "      <td>45.07</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
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       "      <td>244.7</td>\n",
       "      <td>91</td>\n",
       "      <td>11.01</td>\n",
       "      <td>10.0</td>\n",
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       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OH</td>\n",
       "      <td>107</td>\n",
       "      <td>415</td>\n",
       "      <td>371-7191</td>\n",
       "      <td>False</td>\n",
       "      <td>yes</td>\n",
       "      <td>26</td>\n",
       "      <td>161.6</td>\n",
       "      <td>123</td>\n",
       "      <td>27.47</td>\n",
       "      <td>...</td>\n",
       "      <td>103</td>\n",
       "      <td>16.62</td>\n",
       "      <td>254.4</td>\n",
       "      <td>103</td>\n",
       "      <td>11.45</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NJ</td>\n",
       "      <td>137</td>\n",
       "      <td>415</td>\n",
       "      <td>358-1921</td>\n",
       "      <td>False</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>243.4</td>\n",
       "      <td>114</td>\n",
       "      <td>41.38</td>\n",
       "      <td>...</td>\n",
       "      <td>110</td>\n",
       "      <td>10.30</td>\n",
       "      <td>162.6</td>\n",
       "      <td>104</td>\n",
       "      <td>7.32</td>\n",
       "      <td>12.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OH</td>\n",
       "      <td>84</td>\n",
       "      <td>408</td>\n",
       "      <td>375-9999</td>\n",
       "      <td>True</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>299.4</td>\n",
       "      <td>71</td>\n",
       "      <td>50.90</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>5.26</td>\n",
       "      <td>196.9</td>\n",
       "      <td>89</td>\n",
       "      <td>8.86</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OK</td>\n",
       "      <td>75</td>\n",
       "      <td>415</td>\n",
       "      <td>330-6626</td>\n",
       "      <td>True</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>166.7</td>\n",
       "      <td>113</td>\n",
       "      <td>28.34</td>\n",
       "      <td>...</td>\n",
       "      <td>122</td>\n",
       "      <td>12.61</td>\n",
       "      <td>186.9</td>\n",
       "      <td>121</td>\n",
       "      <td>8.41</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.73</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  state  account length  area code phone number  international plan  \\\n",
       "0    KS             128        415     382-4657               False   \n",
       "1    OH             107        415     371-7191               False   \n",
       "2    NJ             137        415     358-1921               False   \n",
       "3    OH              84        408     375-9999                True   \n",
       "4    OK              75        415     330-6626                True   \n",
       "\n",
       "  voice mail plan  number vmail messages  total day minutes  total day calls  \\\n",
       "0             yes                     25              265.1              110   \n",
       "1             yes                     26              161.6              123   \n",
       "2              no                      0              243.4              114   \n",
       "3              no                      0              299.4               71   \n",
       "4              no                      0              166.7              113   \n",
       "\n",
       "   total day charge  ...  total eve calls  total eve charge  \\\n",
       "0             45.07  ...               99             16.78   \n",
       "1             27.47  ...              103             16.62   \n",
       "2             41.38  ...              110             10.30   \n",
       "3             50.90  ...               88              5.26   \n",
       "4             28.34  ...              122             12.61   \n",
       "\n",
       "   total night minutes  total night calls  total night charge  \\\n",
       "0                244.7                 91               11.01   \n",
       "1                254.4                103               11.45   \n",
       "2                162.6                104                7.32   \n",
       "3                196.9                 89                8.86   \n",
       "4                186.9                121                8.41   \n",
       "\n",
       "   total intl minutes  total intl calls  total intl charge  \\\n",
       "0                10.0                 3               2.70   \n",
       "1                13.7                 3               3.70   \n",
       "2                12.2                 5               3.29   \n",
       "3                 6.6                 7               1.78   \n",
       "4                10.1                 3               2.73   \n",
       "\n",
       "   customer service calls  churn  \n",
       "0                       1  False  \n",
       "1                       1  False  \n",
       "2                       0  False  \n",
       "3                       2  False  \n",
       "4                       3  False  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {'no' : False, 'yes' : True}\n",
    "data['international plan'] = data['international plan'].map(d)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7de5c5a0",
   "metadata": {},
   "source": [
    "The same thing can be done with the replace method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d535d854",
   "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>state</th>\n",
       "      <th>account length</th>\n",
       "      <th>area code</th>\n",
       "      <th>phone number</th>\n",
       "      <th>international plan</th>\n",
       "      <th>voice mail plan</th>\n",
       "      <th>number vmail messages</th>\n",
       "      <th>total day minutes</th>\n",
       "      <th>total day calls</th>\n",
       "      <th>total day charge</th>\n",
       "      <th>...</th>\n",
       "      <th>total eve calls</th>\n",
       "      <th>total eve charge</th>\n",
       "      <th>total night minutes</th>\n",
       "      <th>total night calls</th>\n",
       "      <th>total night charge</th>\n",
       "      <th>total intl minutes</th>\n",
       "      <th>total intl calls</th>\n",
       "      <th>total intl charge</th>\n",
       "      <th>customer service calls</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>KS</td>\n",
       "      <td>128</td>\n",
       "      <td>415</td>\n",
       "      <td>382-4657</td>\n",
       "      <td>False</td>\n",
       "      <td>yes</td>\n",
       "      <td>25</td>\n",
       "      <td>265.1</td>\n",
       "      <td>110</td>\n",
       "      <td>45.07</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>16.78</td>\n",
       "      <td>244.7</td>\n",
       "      <td>91</td>\n",
       "      <td>11.01</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>OH</td>\n",
       "      <td>107</td>\n",
       "      <td>415</td>\n",
       "      <td>371-7191</td>\n",
       "      <td>False</td>\n",
       "      <td>yes</td>\n",
       "      <td>26</td>\n",
       "      <td>161.6</td>\n",
       "      <td>123</td>\n",
       "      <td>27.47</td>\n",
       "      <td>...</td>\n",
       "      <td>103</td>\n",
       "      <td>16.62</td>\n",
       "      <td>254.4</td>\n",
       "      <td>103</td>\n",
       "      <td>11.45</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NJ</td>\n",
       "      <td>137</td>\n",
       "      <td>415</td>\n",
       "      <td>358-1921</td>\n",
       "      <td>False</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>243.4</td>\n",
       "      <td>114</td>\n",
       "      <td>41.38</td>\n",
       "      <td>...</td>\n",
       "      <td>110</td>\n",
       "      <td>10.30</td>\n",
       "      <td>162.6</td>\n",
       "      <td>104</td>\n",
       "      <td>7.32</td>\n",
       "      <td>12.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OH</td>\n",
       "      <td>84</td>\n",
       "      <td>408</td>\n",
       "      <td>375-9999</td>\n",
       "      <td>True</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>299.4</td>\n",
       "      <td>71</td>\n",
       "      <td>50.90</td>\n",
       "      <td>...</td>\n",
       "      <td>88</td>\n",
       "      <td>5.26</td>\n",
       "      <td>196.9</td>\n",
       "      <td>89</td>\n",
       "      <td>8.86</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>OK</td>\n",
       "      <td>75</td>\n",
       "      <td>415</td>\n",
       "      <td>330-6626</td>\n",
       "      <td>True</td>\n",
       "      <td>no</td>\n",
       "      <td>0</td>\n",
       "      <td>166.7</td>\n",
       "      <td>113</td>\n",
       "      <td>28.34</td>\n",
       "      <td>...</td>\n",
       "      <td>122</td>\n",
       "      <td>12.61</td>\n",
       "      <td>186.9</td>\n",
       "      <td>121</td>\n",
       "      <td>8.41</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.73</td>\n",
       "      <td>3</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  state  account length  area code phone number  international plan  \\\n",
       "0    KS             128        415     382-4657               False   \n",
       "1    OH             107        415     371-7191               False   \n",
       "2    NJ             137        415     358-1921               False   \n",
       "3    OH              84        408     375-9999                True   \n",
       "4    OK              75        415     330-6626                True   \n",
       "\n",
       "  voice mail plan  number vmail messages  total day minutes  total day calls  \\\n",
       "0             yes                     25              265.1              110   \n",
       "1             yes                     26              161.6              123   \n",
       "2              no                      0              243.4              114   \n",
       "3              no                      0              299.4               71   \n",
       "4              no                      0              166.7              113   \n",
       "\n",
       "   total day charge  ...  total eve calls  total eve charge  \\\n",
       "0             45.07  ...               99             16.78   \n",
       "1             27.47  ...              103             16.62   \n",
       "2             41.38  ...              110             10.30   \n",
       "3             50.90  ...               88              5.26   \n",
       "4             28.34  ...              122             12.61   \n",
       "\n",
       "   total night minutes  total night calls  total night charge  \\\n",
       "0                244.7                 91               11.01   \n",
       "1                254.4                103               11.45   \n",
       "2                162.6                104                7.32   \n",
       "3                196.9                 89                8.86   \n",
       "4                186.9                121                8.41   \n",
       "\n",
       "   total intl minutes  total intl calls  total intl charge  \\\n",
       "0                10.0                 3               2.70   \n",
       "1                13.7                 3               3.70   \n",
       "2                12.2                 5               3.29   \n",
       "3                 6.6                 7               1.78   \n",
       "4                10.1                 3               2.73   \n",
       "\n",
       "   customer service calls  churn  \n",
       "0                       1  False  \n",
       "1                       1  False  \n",
       "2                       0  False  \n",
       "3                       2  False  \n",
       "4                       3  False  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = {'no' : False, 'yes' : True}\n",
    "data = data.replace({'voice mail plan': 'd'})\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e04e6f8f",
   "metadata": {},
   "source": [
    "## Ploting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "cb3c58dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "54c82ca8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 432,
       "width": 580
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='international plan', hue='churn', data=data);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cbbdf7ab",
   "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>customer service calls</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>churn</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>False</th>\n",
       "      <td>605</td>\n",
       "      <td>1059</td>\n",
       "      <td>672</td>\n",
       "      <td>385</td>\n",
       "      <td>90</td>\n",
       "      <td>26</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>True</th>\n",
       "      <td>92</td>\n",
       "      <td>122</td>\n",
       "      <td>87</td>\n",
       "      <td>44</td>\n",
       "      <td>76</td>\n",
       "      <td>40</td>\n",
       "      <td>14</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>697</td>\n",
       "      <td>1181</td>\n",
       "      <td>759</td>\n",
       "      <td>429</td>\n",
       "      <td>166</td>\n",
       "      <td>66</td>\n",
       "      <td>22</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "customer service calls    0     1    2    3    4   5   6  7  8  9   All\n",
       "churn                                                                  \n",
       "False                   605  1059  672  385   90  26   8  4  1  0  2850\n",
       "True                     92   122   87   44   76  40  14  5  1  2   483\n",
       "All                     697  1181  759  429  166  66  22  9  2  2  3333"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['churn'], data['customer service calls'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c9b26060",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 432,
       "width": 580
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='customer service calls', hue='churn', data=data);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8029c69",
   "metadata": {},
   "source": [
    "Although it's not so obvious from the summary table, it's easy to see from the above plot that the churn rate increases sharply from 4 customer service calls and above.\n",
    "\n",
    "Now let's add a binary feature to our DataFrame – Customer service calls > 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "3305940a",
   "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>churn</th>\n",
       "      <th>False</th>\n",
       "      <th>True</th>\n",
       "      <th>All</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>many_service_calls</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2721</td>\n",
       "      <td>345</td>\n",
       "      <td>3066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>129</td>\n",
       "      <td>138</td>\n",
       "      <td>267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>2850</td>\n",
       "      <td>483</td>\n",
       "      <td>3333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "churn               False  True   All\n",
       "many_service_calls                   \n",
       "0                    2721   345  3066\n",
       "1                     129   138   267\n",
       "All                  2850   483  3333"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['many_service_calls'] = (data['customer service calls'] > 3).astype('int')\n",
    "pd.crosstab(data['many_service_calls'], data['churn'], margins=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "e447d95f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 433,
       "width": 580
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='many_service_calls', hue='churn', data=data);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee31652b",
   "metadata": {},
   "source": [
    "Let's construct another contingency table that relates Churn with both International plan and freshly created Many_service_calls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d6f6e506",
   "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>churn</th>\n",
       "      <th>False</th>\n",
       "      <th>True</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>row_0</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>False</th>\n",
       "      <td>2841</td>\n",
       "      <td>464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>True</th>\n",
       "      <td>9</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "churn  False  True \n",
       "row_0              \n",
       "False   2841    464\n",
       "True       9     19"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(data['many_service_calls'] & data['international plan'] , data['churn'])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}