data_notebooks/feature_engineering.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "%matplotlib inline\n",
    "np.random.seed(59)\n",
    "\n",
    "# set the max columns to none\n",
    "pd.set_option('display.max_columns', None)\n",
    "\n",
    "%load_ext pycodestyle_magic\n",
    "%pycodestyle_on"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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>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>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>number_customer_service_calls</th>\n",
       "      <th>churn</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>OH</td>\n",
       "      <td>107</td>\n",
       "      <td>area_code_415</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>195.5</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>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NJ</td>\n",
       "      <td>137</td>\n",
       "      <td>area_code_415</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>121.2</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>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>OH</td>\n",
       "      <td>84</td>\n",
       "      <td>area_code_408</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>61.9</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>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>OK</td>\n",
       "      <td>75</td>\n",
       "      <td>area_code_415</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>148.3</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>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MA</td>\n",
       "      <td>121</td>\n",
       "      <td>area_code_510</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>348.5</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>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  state  account_length      area_code international_plan voice_mail_plan  \\\n",
       "0    OH             107  area_code_415                 no             yes   \n",
       "1    NJ             137  area_code_415                 no              no   \n",
       "2    OH              84  area_code_408                yes              no   \n",
       "3    OK              75  area_code_415                yes              no   \n",
       "4    MA             121  area_code_510                 no             yes   \n",
       "\n",
       "   number_vmail_messages  total_day_minutes  total_day_calls  \\\n",
       "0                     26              161.6              123   \n",
       "1                      0              243.4              114   \n",
       "2                      0              299.4               71   \n",
       "3                      0              166.7              113   \n",
       "4                     24              218.2               88   \n",
       "\n",
       "   total_day_charge  total_eve_minutes  total_eve_calls  total_eve_charge  \\\n",
       "0             27.47              195.5              103             16.62   \n",
       "1             41.38              121.2              110             10.30   \n",
       "2             50.90               61.9               88              5.26   \n",
       "3             28.34              148.3              122             12.61   \n",
       "4             37.09              348.5              108             29.62   \n",
       "\n",
       "   total_night_minutes  total_night_calls  total_night_charge  \\\n",
       "0                254.4                103               11.45   \n",
       "1                162.6                104                7.32   \n",
       "2                196.9                 89                8.86   \n",
       "3                186.9                121                8.41   \n",
       "4                212.6                118                9.57   \n",
       "\n",
       "   total_intl_minutes  total_intl_calls  total_intl_charge  \\\n",
       "0                13.7                 3               3.70   \n",
       "1                12.2                 5               3.29   \n",
       "2                 6.6                 7               1.78   \n",
       "3                10.1                 3               2.73   \n",
       "4                 7.5                 7               2.03   \n",
       "\n",
       "   number_customer_service_calls churn  \n",
       "0                              1    no  \n",
       "1                              0    no  \n",
       "2                              2    no  \n",
       "3                              3    no  \n",
       "4                              3    no  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_path = 'data\\\\train.csv'\n",
    "df = pd.read_csv(train_path)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account_length</th>\n",
       "      <th>international_plan</th>\n",
       "      <th>voice_mail_plan</th>\n",
       "      <th>number_vmail_messages</th>\n",
       "      <th>total_intl_minutes</th>\n",
       "      <th>total_intl_calls</th>\n",
       "      <th>total_intl_charge</th>\n",
       "      <th>number_customer_service_calls</th>\n",
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       "      <th>total_minutes</th>\n",
       "      <th>total_calls</th>\n",
       "      <th>total_charge</th>\n",
       "      <th>area_code_area_code_408</th>\n",
       "      <th>area_code_area_code_415</th>\n",
       "      <th>area_code_area_code_510</th>\n",
       "      <th>state_MD</th>\n",
       "      <th>state_MN</th>\n",
       "      <th>state_NJ</th>\n",
       "      <th>state_TX</th>\n",
       "      <th>state_WV</th>\n",
       "      <th>state_other</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>107</td>\n",
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       "      <td>26</td>\n",
       "      <td>13.7</td>\n",
       "      <td>3</td>\n",
       "      <td>3.70</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>611.5</td>\n",
       "      <td>329</td>\n",
       "      <td>55.54</td>\n",
       "      <td>0</td>\n",
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       "      <th>1</th>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.2</td>\n",
       "      <td>5</td>\n",
       "      <td>3.29</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>527.2</td>\n",
       "      <td>328</td>\n",
       "      <td>59.00</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>1.78</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>558.2</td>\n",
       "      <td>248</td>\n",
       "      <td>65.02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>75</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.1</td>\n",
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       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>501.9</td>\n",
       "      <td>356</td>\n",
       "      <td>49.36</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7</td>\n",
       "      <td>2.03</td>\n",
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       "      <td>779.3</td>\n",
       "      <td>314</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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      ],
      "text/plain": [
       "   account_length  international_plan  voice_mail_plan  number_vmail_messages  \\\n",
       "0             107                   0                1                     26   \n",
       "1             137                   0                0                      0   \n",
       "2              84                   1                0                      0   \n",
       "3              75                   1                0                      0   \n",
       "4             121                   0                1                     24   \n",
       "\n",
       "   total_intl_minutes  total_intl_calls  total_intl_charge  \\\n",
       "0                13.7                 3               3.70   \n",
       "1                12.2                 5               3.29   \n",
       "2                 6.6                 7               1.78   \n",
       "3                10.1                 3               2.73   \n",
       "4                 7.5                 7               2.03   \n",
       "\n",
       "   number_customer_service_calls  churn  total_minutes  total_calls  \\\n",
       "0                              1      0          611.5          329   \n",
       "1                              0      0          527.2          328   \n",
       "2                              2      0          558.2          248   \n",
       "3                              3      0          501.9          356   \n",
       "4                              3      0          779.3          314   \n",
       "\n",
       "   total_charge  area_code_area_code_408  area_code_area_code_415  \\\n",
       "0         55.54                        0                        1   \n",
       "1         59.00                        0                        1   \n",
       "2         65.02                        1                        0   \n",
       "3         49.36                        0                        1   \n",
       "4         76.28                        0                        0   \n",
       "\n",
       "   area_code_area_code_510  state_MD  state_MN  state_NJ  state_TX  state_WV  \\\n",
       "0                        0         0         0         0         0         0   \n",
       "1                        0         0         0         1         0         0   \n",
       "2                        0         0         0         0         0         0   \n",
       "3                        0         0         0         0         0         0   \n",
       "4                        1         0         0         0         0         0   \n",
       "\n",
       "   state_other  \n",
       "0            1  \n",
       "1            0  \n",
       "2            1  \n",
       "3            1  \n",
       "4            1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from preprocessing import convert_data\n",
    "\n",
    "\n",
    "df = convert_data(df)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As every customer has different total time being by the company, we can generate features of average month charge/minutes/calls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>account_length</th>\n",
       "      <th>international_plan</th>\n",
       "      <th>voice_mail_plan</th>\n",
       "      <th>number_vmail_messages</th>\n",
       "      <th>total_intl_minutes</th>\n",
       "      <th>total_intl_calls</th>\n",
       "      <th>total_intl_charge</th>\n",
       "      <th>number_customer_service_calls</th>\n",
       "      <th>churn</th>\n",
       "      <th>total_minutes</th>\n",
       "      <th>total_calls</th>\n",
       "      <th>total_charge</th>\n",
       "      <th>area_code_area_code_408</th>\n",
       "      <th>area_code_area_code_415</th>\n",
       "      <th>area_code_area_code_510</th>\n",
       "      <th>state_MD</th>\n",
       "      <th>state_MN</th>\n",
       "      <th>state_NJ</th>\n",
       "      <th>state_TX</th>\n",
       "      <th>state_WV</th>\n",
       "      <th>state_other</th>\n",
       "      <th>avg_mt_minutes</th>\n",
       "      <th>avg_mt_calls</th>\n",
       "      <th>avg_mt_charge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>107</td>\n",
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       "      <th>1</th>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>12.2</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3.848175</td>\n",
       "      <td>2.394161</td>\n",
       "      <td>0.430657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>84</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>7</td>\n",
       "      <td>1.78</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>558.2</td>\n",
       "      <td>248</td>\n",
       "      <td>65.02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.645238</td>\n",
       "      <td>2.952381</td>\n",
       "      <td>0.774048</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>75</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10.1</td>\n",
       "      <td>3</td>\n",
       "      <td>2.73</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>501.9</td>\n",
       "      <td>356</td>\n",
       "      <td>49.36</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.692000</td>\n",
       "      <td>4.746667</td>\n",
       "      <td>0.658133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>121</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>7.5</td>\n",
       "      <td>7</td>\n",
       "      <td>2.03</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>779.3</td>\n",
       "      <td>314</td>\n",
       "      <td>76.28</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>6.440496</td>\n",
       "      <td>2.595041</td>\n",
       "      <td>0.630413</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account_length  international_plan  voice_mail_plan  number_vmail_messages  \\\n",
       "0             107                   0                1                     26   \n",
       "1             137                   0                0                      0   \n",
       "2              84                   1                0                      0   \n",
       "3              75                   1                0                      0   \n",
       "4             121                   0                1                     24   \n",
       "\n",
       "   total_intl_minutes  total_intl_calls  total_intl_charge  \\\n",
       "0                13.7                 3               3.70   \n",
       "1                12.2                 5               3.29   \n",
       "2                 6.6                 7               1.78   \n",
       "3                10.1                 3               2.73   \n",
       "4                 7.5                 7               2.03   \n",
       "\n",
       "   number_customer_service_calls  churn  total_minutes  total_calls  \\\n",
       "0                              1      0          611.5          329   \n",
       "1                              0      0          527.2          328   \n",
       "2                              2      0          558.2          248   \n",
       "3                              3      0          501.9          356   \n",
       "4                              3      0          779.3          314   \n",
       "\n",
       "   total_charge  area_code_area_code_408  area_code_area_code_415  \\\n",
       "0         55.54                        0                        1   \n",
       "1         59.00                        0                        1   \n",
       "2         65.02                        1                        0   \n",
       "3         49.36                        0                        1   \n",
       "4         76.28                        0                        0   \n",
       "\n",
       "   area_code_area_code_510  state_MD  state_MN  state_NJ  state_TX  state_WV  \\\n",
       "0                        0         0         0         0         0         0   \n",
       "1                        0         0         0         1         0         0   \n",
       "2                        0         0         0         0         0         0   \n",
       "3                        0         0         0         0         0         0   \n",
       "4                        1         0         0         0         0         0   \n",
       "\n",
       "   state_other  avg_mt_minutes  avg_mt_calls  avg_mt_charge  \n",
       "0            1        5.714953      3.074766       0.519065  \n",
       "1            0        3.848175      2.394161       0.430657  \n",
       "2            1        6.645238      2.952381       0.774048  \n",
       "3            1        6.692000      4.746667       0.658133  \n",
       "4            1        6.440496      2.595041       0.630413  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features = ['minutes', 'calls', 'charge']\n",
    "\n",
    "for feature in features:\n",
    "    df['avg_mt_' + feature] = df['total_' + feature] / df['account_length']\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Same for average call, how much does it cost, how long is it (in minutes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['avg_call_charge'] = df['total_charge'] / df['total_calls']\n",
    "df['avg_intl_call_charge'] = df['total_intl_charge'] / df['total_intl_calls']\n",
    "\n",
    "df['avg_call_minutes'] = df['total_minutes'] / df['total_calls']\n",
    "df['avg_intl_call_minutes'] = df['total_intl_minutes'] / df['total_intl_calls']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Last but not least - feature as intersection of international plan and voice_mail plan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>account_length</th>\n",
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       "      <td>0</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   account_length  international_plan  voice_mail_plan  number_vmail_messages  \\\n",
       "0             107                   0                1                     26   \n",
       "1             137                   0                0                      0   \n",
       "2              84                   1                0                      0   \n",
       "3              75                   1                0                      0   \n",
       "4             121                   0                1                     24   \n",
       "\n",
       "   total_intl_minutes  total_intl_calls  total_intl_charge  \\\n",
       "0                13.7                 3               3.70   \n",
       "1                12.2                 5               3.29   \n",
       "2                 6.6                 7               1.78   \n",
       "3                10.1                 3               2.73   \n",
       "4                 7.5                 7               2.03   \n",
       "\n",
       "   number_customer_service_calls  churn  total_minutes  total_calls  \\\n",
       "0                              1      0          611.5          329   \n",
       "1                              0      0          527.2          328   \n",
       "2                              2      0          558.2          248   \n",
       "3                              3      0          501.9          356   \n",
       "4                              3      0          779.3          314   \n",
       "\n",
       "   total_charge  area_code_area_code_408  area_code_area_code_415  \\\n",
       "0         55.54                        0                        1   \n",
       "1         59.00                        0                        1   \n",
       "2         65.02                        1                        0   \n",
       "3         49.36                        0                        1   \n",
       "4         76.28                        0                        0   \n",
       "\n",
       "   area_code_area_code_510  state_MD  state_MN  state_NJ  state_TX  state_WV  \\\n",
       "0                        0         0         0         0         0         0   \n",
       "1                        0         0         0         1         0         0   \n",
       "2                        0         0         0         0         0         0   \n",
       "3                        0         0         0         0         0         0   \n",
       "4                        1         0         0         0         0         0   \n",
       "\n",
       "   state_other  avg_mt_minutes  avg_mt_calls  avg_mt_charge  avg_call_charge  \\\n",
       "0            1        5.714953      3.074766       0.519065         0.168815   \n",
       "1            0        3.848175      2.394161       0.430657         0.179878   \n",
       "2            1        6.645238      2.952381       0.774048         0.262177   \n",
       "3            1        6.692000      4.746667       0.658133         0.138652   \n",
       "4            1        6.440496      2.595041       0.630413         0.242930   \n",
       "\n",
       "   avg_intl_call_charge  avg_call_minutes  avg_intl_call_minutes  both_plans  \n",
       "0              1.233333          1.858663               4.566667           0  \n",
       "1              0.658000          1.607317               2.440000           0  \n",
       "2              0.254286          2.250806               0.942857           0  \n",
       "3              0.910000          1.409831               3.366667           0  \n",
       "4              0.290000          2.481847               1.071429           0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['both_plans'] = df['international_plan'] & df['voice_mail_plan']\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <td>4195.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "      <td>4173.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "      <td>4173.000000</td>\n",
       "      <td>4195.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>100.172825</td>\n",
       "      <td>0.093683</td>\n",
       "      <td>0.259118</td>\n",
       "      <td>7.585697</td>\n",
       "      <td>10.253206</td>\n",
       "      <td>4.425268</td>\n",
       "      <td>2.768882</td>\n",
       "      <td>1.513468</td>\n",
       "      <td>0.142551</td>\n",
       "      <td>580.432968</td>\n",
       "      <td>299.998808</td>\n",
       "      <td>56.620117</td>\n",
       "      <td>0.256257</td>\n",
       "      <td>0.496067</td>\n",
       "      <td>0.247676</td>\n",
       "      <td>0.020262</td>\n",
       "      <td>0.025507</td>\n",
       "      <td>0.022884</td>\n",
       "      <td>0.022884</td>\n",
       "      <td>0.032658</td>\n",
       "      <td>0.875805</td>\n",
       "      <td>8.924823</td>\n",
       "      <td>4.592859</td>\n",
       "      <td>0.867238</td>\n",
       "      <td>0.191281</td>\n",
       "      <td>0.861350</td>\n",
       "      <td>1.960630</td>\n",
       "      <td>3.189633</td>\n",
       "      <td>0.024315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>39.661706</td>\n",
       "      <td>0.291422</td>\n",
       "      <td>0.438203</td>\n",
       "      <td>13.409350</td>\n",
       "      <td>2.762227</td>\n",
       "      <td>2.468945</td>\n",
       "      <td>0.745774</td>\n",
       "      <td>1.246071</td>\n",
       "      <td>0.349656</td>\n",
       "      <td>88.963753</td>\n",
       "      <td>34.432531</td>\n",
       "      <td>10.350788</td>\n",
       "      <td>0.436618</td>\n",
       "      <td>0.500044</td>\n",
       "      <td>0.431714</td>\n",
       "      <td>0.140913</td>\n",
       "      <td>0.157677</td>\n",
       "      <td>0.149553</td>\n",
       "      <td>0.149553</td>\n",
       "      <td>0.177761</td>\n",
       "      <td>0.329844</td>\n",
       "      <td>26.507227</td>\n",
       "      <td>13.662220</td>\n",
       "      <td>2.559411</td>\n",
       "      <td>0.041955</td>\n",
       "      <td>0.630262</td>\n",
       "      <td>0.380115</td>\n",
       "      <td>2.334070</td>\n",
       "      <td>0.154043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</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>0.000000</td>\n",
       "      <td>275.200000</td>\n",
       "      <td>188.000000</td>\n",
       "      <td>19.980000</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>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.820725</td>\n",
       "      <td>1.085586</td>\n",
       "      <td>0.153886</td>\n",
       "      <td>0.063581</td>\n",
       "      <td>0.015714</td>\n",
       "      <td>0.781818</td>\n",
       "      <td>0.057143</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>73.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.300000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>520.600000</td>\n",
       "      <td>277.000000</td>\n",
       "      <td>49.510000</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>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.458903</td>\n",
       "      <td>2.339421</td>\n",
       "      <td>0.426994</td>\n",
       "      <td>0.162757</td>\n",
       "      <td>0.458333</td>\n",
       "      <td>1.696857</td>\n",
       "      <td>1.700000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>99.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>10.300000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.780000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>580.700000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>56.630000</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>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.822917</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.568421</td>\n",
       "      <td>0.188060</td>\n",
       "      <td>0.682500</td>\n",
       "      <td>1.931790</td>\n",
       "      <td>2.525000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>127.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>16.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>3.240000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>640.550000</td>\n",
       "      <td>323.000000</td>\n",
       "      <td>63.430000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</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>1.000000</td>\n",
       "      <td>8.074866</td>\n",
       "      <td>4.143892</td>\n",
       "      <td>0.789408</td>\n",
       "      <td>0.217139</td>\n",
       "      <td>1.043333</td>\n",
       "      <td>2.193866</td>\n",
       "      <td>3.866667</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>243.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>876.900000</td>\n",
       "      <td>410.000000</td>\n",
       "      <td>92.560000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>704.100000</td>\n",
       "      <td>372.000000</td>\n",
       "      <td>68.060000</td>\n",
       "      <td>0.402548</td>\n",
       "      <td>4.910000</td>\n",
       "      <td>3.693644</td>\n",
       "      <td>18.200000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       account_length  international_plan  voice_mail_plan  \\\n",
       "count     4195.000000         4195.000000      4195.000000   \n",
       "mean       100.172825            0.093683         0.259118   \n",
       "std         39.661706            0.291422         0.438203   \n",
       "min          1.000000            0.000000         0.000000   \n",
       "25%         73.000000            0.000000         0.000000   \n",
       "50%         99.000000            0.000000         0.000000   \n",
       "75%        127.000000            0.000000         1.000000   \n",
       "max        243.000000            1.000000         1.000000   \n",
       "\n",
       "       number_vmail_messages  total_intl_minutes  total_intl_calls  \\\n",
       "count            4195.000000         4195.000000       4195.000000   \n",
       "mean                7.585697           10.253206          4.425268   \n",
       "std                13.409350            2.762227          2.468945   \n",
       "min                 0.000000            0.000000          0.000000   \n",
       "25%                 0.000000            8.500000          3.000000   \n",
       "50%                 0.000000           10.300000          4.000000   \n",
       "75%                16.000000           12.000000          6.000000   \n",
       "max                50.000000           20.000000         20.000000   \n",
       "\n",
       "       total_intl_charge  number_customer_service_calls        churn  \\\n",
       "count        4195.000000                    4195.000000  4195.000000   \n",
       "mean            2.768882                       1.513468     0.142551   \n",
       "std             0.745774                       1.246071     0.349656   \n",
       "min             0.000000                       0.000000     0.000000   \n",
       "25%             2.300000                       1.000000     0.000000   \n",
       "50%             2.780000                       1.000000     0.000000   \n",
       "75%             3.240000                       2.000000     0.000000   \n",
       "max             5.400000                       9.000000     1.000000   \n",
       "\n",
       "       total_minutes  total_calls  total_charge  area_code_area_code_408  \\\n",
       "count    4195.000000  4195.000000   4195.000000              4195.000000   \n",
       "mean      580.432968   299.998808     56.620117                 0.256257   \n",
       "std        88.963753    34.432531     10.350788                 0.436618   \n",
       "min       275.200000   188.000000     19.980000                 0.000000   \n",
       "25%       520.600000   277.000000     49.510000                 0.000000   \n",
       "50%       580.700000   300.000000     56.630000                 0.000000   \n",
       "75%       640.550000   323.000000     63.430000                 1.000000   \n",
       "max       876.900000   410.000000     92.560000                 1.000000   \n",
       "\n",
       "       area_code_area_code_415  area_code_area_code_510     state_MD  \\\n",
       "count              4195.000000              4195.000000  4195.000000   \n",
       "mean                  0.496067                 0.247676     0.020262   \n",
       "std                   0.500044                 0.431714     0.140913   \n",
       "min                   0.000000                 0.000000     0.000000   \n",
       "25%                   0.000000                 0.000000     0.000000   \n",
       "50%                   0.000000                 0.000000     0.000000   \n",
       "75%                   1.000000                 0.000000     0.000000   \n",
       "max                   1.000000                 1.000000     1.000000   \n",
       "\n",
       "          state_MN     state_NJ     state_TX     state_WV  state_other  \\\n",
       "count  4195.000000  4195.000000  4195.000000  4195.000000  4195.000000   \n",
       "mean      0.025507     0.022884     0.022884     0.032658     0.875805   \n",
       "std       0.157677     0.149553     0.149553     0.177761     0.329844   \n",
       "min       0.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%       0.000000     0.000000     0.000000     0.000000     1.000000   \n",
       "50%       0.000000     0.000000     0.000000     0.000000     1.000000   \n",
       "75%       0.000000     0.000000     0.000000     0.000000     1.000000   \n",
       "max       1.000000     1.000000     1.000000     1.000000     1.000000   \n",
       "\n",
       "       avg_mt_minutes  avg_mt_calls  avg_mt_charge  avg_call_charge  \\\n",
       "count     4195.000000   4195.000000    4195.000000      4195.000000   \n",
       "mean         8.924823      4.592859       0.867238         0.191281   \n",
       "std         26.507227     13.662220       2.559411         0.041955   \n",
       "min          1.820725      1.085586       0.153886         0.063581   \n",
       "25%          4.458903      2.339421       0.426994         0.162757   \n",
       "50%          5.822917      3.000000       0.568421         0.188060   \n",
       "75%          8.074866      4.143892       0.789408         0.217139   \n",
       "max        704.100000    372.000000      68.060000         0.402548   \n",
       "\n",
       "       avg_intl_call_charge  avg_call_minutes  avg_intl_call_minutes  \\\n",
       "count           4173.000000       4195.000000            4173.000000   \n",
       "mean               0.861350          1.960630               3.189633   \n",
       "std                0.630262          0.380115               2.334070   \n",
       "min                0.015714          0.781818               0.057143   \n",
       "25%                0.458333          1.696857               1.700000   \n",
       "50%                0.682500          1.931790               2.525000   \n",
       "75%                1.043333          2.193866               3.866667   \n",
       "max                4.910000          3.693644              18.200000   \n",
       "\n",
       "        both_plans  \n",
       "count  4195.000000  \n",
       "mean      0.024315  \n",
       "std       0.154043  \n",
       "min       0.000000  \n",
       "25%       0.000000  \n",
       "50%       0.000000  \n",
       "75%       0.000000  \n",
       "max       1.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "account_length                    0\n",
       "international_plan                0\n",
       "voice_mail_plan                   0\n",
       "number_vmail_messages             0\n",
       "total_intl_minutes                0\n",
       "total_intl_calls                  0\n",
       "total_intl_charge                 0\n",
       "number_customer_service_calls     0\n",
       "churn                             0\n",
       "total_minutes                     0\n",
       "total_calls                       0\n",
       "total_charge                      0\n",
       "area_code_area_code_408           0\n",
       "area_code_area_code_415           0\n",
       "area_code_area_code_510           0\n",
       "state_MD                          0\n",
       "state_MN                          0\n",
       "state_NJ                          0\n",
       "state_TX                          0\n",
       "state_WV                          0\n",
       "state_other                       0\n",
       "avg_mt_minutes                    0\n",
       "avg_mt_calls                      0\n",
       "avg_mt_charge                     0\n",
       "avg_call_charge                   0\n",
       "avg_intl_call_charge             22\n",
       "avg_call_minutes                  0\n",
       "avg_intl_call_minutes            22\n",
       "both_plans                        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like we have some missing values. Probably because of zerodivisionerror. Let's look at them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>account_length</th>\n",
       "      <th>international_plan</th>\n",
       "      <th>voice_mail_plan</th>\n",
       "      <th>number_vmail_messages</th>\n",
       "      <th>total_intl_minutes</th>\n",
       "      <th>total_intl_calls</th>\n",
       "      <th>total_intl_charge</th>\n",
       "      <th>number_customer_service_calls</th>\n",
       "      <th>churn</th>\n",
       "      <th>total_minutes</th>\n",
       "      <th>total_calls</th>\n",
       "      <th>total_charge</th>\n",
       "      <th>area_code_area_code_408</th>\n",
       "      <th>area_code_area_code_415</th>\n",
       "      <th>area_code_area_code_510</th>\n",
       "      <th>state_MD</th>\n",
       "      <th>state_MN</th>\n",
       "      <th>state_NJ</th>\n",
       "      <th>state_TX</th>\n",
       "      <th>state_WV</th>\n",
       "      <th>state_other</th>\n",
       "      <th>avg_mt_minutes</th>\n",
       "      <th>avg_mt_calls</th>\n",
       "      <th>avg_mt_charge</th>\n",
       "      <th>avg_call_charge</th>\n",
       "      <th>avg_intl_call_charge</th>\n",
       "      <th>avg_call_minutes</th>\n",
       "      <th>avg_intl_call_minutes</th>\n",
       "      <th>both_plans</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>725.6</td>\n",
       "      <td>346</td>\n",
       "      <td>73.36</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10.365714</td>\n",
       "      <td>4.942857</td>\n",
       "      <td>1.048000</td>\n",
       "      <td>0.212023</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.097110</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285</th>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>485.5</td>\n",
       "      <td>268</td>\n",
       "      <td>36.97</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.954082</td>\n",
       "      <td>2.734694</td>\n",
       "      <td>0.377245</td>\n",
       "      <td>0.137948</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.811567</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>405</th>\n",
       "      <td>165</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>681.1</td>\n",
       "      <td>317</td>\n",
       "      <td>69.40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.127879</td>\n",
       "      <td>1.921212</td>\n",
       "      <td>0.420606</td>\n",
       "      <td>0.218927</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.148580</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>593</th>\n",
       "      <td>106</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>425.4</td>\n",
       "      <td>283</td>\n",
       "      <td>36.58</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.013208</td>\n",
       "      <td>2.669811</td>\n",
       "      <td>0.345094</td>\n",
       "      <td>0.129258</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.503180</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>735</th>\n",
       "      <td>62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>519.5</td>\n",
       "      <td>248</td>\n",
       "      <td>64.93</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>8.379032</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.047258</td>\n",
       "      <td>0.261815</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.094758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>70</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>662.2</td>\n",
       "      <td>349</td>\n",
       "      <td>66.29</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>9.460000</td>\n",
       "      <td>4.985714</td>\n",
       "      <td>0.947000</td>\n",
       "      <td>0.189943</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.897421</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>903</th>\n",
       "      <td>114</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>587.0</td>\n",
       "      <td>284</td>\n",
       "      <td>57.36</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.149123</td>\n",
       "      <td>2.491228</td>\n",
       "      <td>0.503158</td>\n",
       "      <td>0.201972</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.066901</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>115</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>505.3</td>\n",
       "      <td>279</td>\n",
       "      <td>47.14</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.393913</td>\n",
       "      <td>2.426087</td>\n",
       "      <td>0.409913</td>\n",
       "      <td>0.168961</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.811111</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>137</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>582.1</td>\n",
       "      <td>255</td>\n",
       "      <td>46.22</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.248905</td>\n",
       "      <td>1.861314</td>\n",
       "      <td>0.337372</td>\n",
       "      <td>0.181255</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.282745</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>632.5</td>\n",
       "      <td>282</td>\n",
       "      <td>69.99</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.454082</td>\n",
       "      <td>2.877551</td>\n",
       "      <td>0.714184</td>\n",
       "      <td>0.248191</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.242908</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>101</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>634.7</td>\n",
       "      <td>374</td>\n",
       "      <td>65.04</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.284158</td>\n",
       "      <td>3.702970</td>\n",
       "      <td>0.643960</td>\n",
       "      <td>0.173904</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.697059</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2136</th>\n",
       "      <td>86</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>456.3</td>\n",
       "      <td>345</td>\n",
       "      <td>37.82</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>5.305814</td>\n",
       "      <td>4.011628</td>\n",
       "      <td>0.439767</td>\n",
       "      <td>0.109623</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.322609</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2316</th>\n",
       "      <td>158</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>664.3</td>\n",
       "      <td>287</td>\n",
       "      <td>61.71</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.204430</td>\n",
       "      <td>1.816456</td>\n",
       "      <td>0.390570</td>\n",
       "      <td>0.215017</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.314634</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2461</th>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>602.4</td>\n",
       "      <td>289</td>\n",
       "      <td>55.32</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.924138</td>\n",
       "      <td>3.321839</td>\n",
       "      <td>0.635862</td>\n",
       "      <td>0.191419</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.084429</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2470</th>\n",
       "      <td>58</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>622.6</td>\n",
       "      <td>321</td>\n",
       "      <td>60.45</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>10.734483</td>\n",
       "      <td>5.534483</td>\n",
       "      <td>1.042241</td>\n",
       "      <td>0.188318</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.939564</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2780</th>\n",
       "      <td>120</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>535.1</td>\n",
       "      <td>327</td>\n",
       "      <td>46.69</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.459167</td>\n",
       "      <td>2.725000</td>\n",
       "      <td>0.389083</td>\n",
       "      <td>0.142783</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.636391</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2792</th>\n",
       "      <td>127</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>513.4</td>\n",
       "      <td>300</td>\n",
       "      <td>44.07</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.042520</td>\n",
       "      <td>2.362205</td>\n",
       "      <td>0.347008</td>\n",
       "      <td>0.146900</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.711333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2886</th>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>533.6</td>\n",
       "      <td>372</td>\n",
       "      <td>56.10</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>6.352381</td>\n",
       "      <td>4.428571</td>\n",
       "      <td>0.667857</td>\n",
       "      <td>0.150806</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.434409</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3090</th>\n",
       "      <td>78</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>612.5</td>\n",
       "      <td>331</td>\n",
       "      <td>55.62</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>7.852564</td>\n",
       "      <td>4.243590</td>\n",
       "      <td>0.713077</td>\n",
       "      <td>0.168036</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.850453</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3703</th>\n",
       "      <td>138</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>503.1</td>\n",
       "      <td>305</td>\n",
       "      <td>62.12</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.645652</td>\n",
       "      <td>2.210145</td>\n",
       "      <td>0.450145</td>\n",
       "      <td>0.203672</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.649508</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3768</th>\n",
       "      <td>44</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>567.8</td>\n",
       "      <td>240</td>\n",
       "      <td>58.59</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12.904545</td>\n",
       "      <td>5.454545</td>\n",
       "      <td>1.331591</td>\n",
       "      <td>0.244125</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.365833</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4192</th>\n",
       "      <td>149</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>595.4</td>\n",
       "      <td>291</td>\n",
       "      <td>59.79</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.995973</td>\n",
       "      <td>1.953020</td>\n",
       "      <td>0.401275</td>\n",
       "      <td>0.205464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.046048</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      account_length  international_plan  voice_mail_plan  \\\n",
       "146               70                   0                0   \n",
       "285               98                   0                1   \n",
       "405              165                   0                0   \n",
       "593              106                   0                0   \n",
       "735               62                   0                0   \n",
       "863               70                   0                0   \n",
       "903              114                   0                0   \n",
       "1186             115                   0                0   \n",
       "1317             137                   0                0   \n",
       "1993              98                   0                0   \n",
       "2007             101                   0                0   \n",
       "2136              86                   0                0   \n",
       "2316             158                   0                0   \n",
       "2461              87                   0                1   \n",
       "2470              58                   0                0   \n",
       "2780             120                   0                1   \n",
       "2792             127                   0                0   \n",
       "2886              84                   0                0   \n",
       "3090              78                   0                0   \n",
       "3703             138                   1                0   \n",
       "3768              44                   0                0   \n",
       "4192             149                   0                1   \n",
       "\n",
       "      number_vmail_messages  total_intl_minutes  total_intl_calls  \\\n",
       "146                       0                 0.0                 0   \n",
       "285                      21                 0.0                 0   \n",
       "405                       0                 0.0                 0   \n",
       "593                       0                 0.0                 0   \n",
       "735                       0                 0.0                 0   \n",
       "863                       0                 0.0                 0   \n",
       "903                       0                 0.0                 0   \n",
       "1186                      0                 0.0                 0   \n",
       "1317                      0                 0.0                 0   \n",
       "1993                      0                 0.0                 0   \n",
       "2007                      0                 0.0                 0   \n",
       "2136                      0                 0.0                 0   \n",
       "2316                      0                 0.0                 0   \n",
       "2461                     19                 0.0                 0   \n",
       "2470                      0                 0.0                 0   \n",
       "2780                     27                 0.0                 0   \n",
       "2792                      0                 0.0                 0   \n",
       "2886                      0                 0.0                 0   \n",
       "3090                      0                 0.0                 0   \n",
       "3703                      0                 0.0                 0   \n",
       "3768                      0                 0.0                 0   \n",
       "4192                     28                 0.0                 0   \n",
       "\n",
       "      total_intl_charge  number_customer_service_calls  churn  total_minutes  \\\n",
       "146                 0.0                              3      0          725.6   \n",
       "285                 0.0                              2      0          485.5   \n",
       "405                 0.0                              1      0          681.1   \n",
       "593                 0.0                              2      0          425.4   \n",
       "735                 0.0                              1      0          519.5   \n",
       "863                 0.0                              1      0          662.2   \n",
       "903                 0.0                              0      0          587.0   \n",
       "1186                0.0                              3      0          505.3   \n",
       "1317                0.0                              1      0          582.1   \n",
       "1993                0.0                              0      0          632.5   \n",
       "2007                0.0                              3      0          634.7   \n",
       "2136                0.0                              2      0          456.3   \n",
       "2316                0.0                              2      0          664.3   \n",
       "2461                0.0                              1      0          602.4   \n",
       "2470                0.0                              4      0          622.6   \n",
       "2780                0.0                              1      0          535.1   \n",
       "2792                0.0                              0      0          513.4   \n",
       "2886                0.0                              1      0          533.6   \n",
       "3090                0.0                              3      0          612.5   \n",
       "3703                0.0                              3      1          503.1   \n",
       "3768                0.0                              0      0          567.8   \n",
       "4192                0.0                              1      0          595.4   \n",
       "\n",
       "      total_calls  total_charge  area_code_area_code_408  \\\n",
       "146           346         73.36                        1   \n",
       "285           268         36.97                        1   \n",
       "405           317         69.40                        0   \n",
       "593           283         36.58                        0   \n",
       "735           248         64.93                        0   \n",
       "863           349         66.29                        0   \n",
       "903           284         57.36                        0   \n",
       "1186          279         47.14                        0   \n",
       "1317          255         46.22                        0   \n",
       "1993          282         69.99                        1   \n",
       "2007          374         65.04                        0   \n",
       "2136          345         37.82                        0   \n",
       "2316          287         61.71                        1   \n",
       "2461          289         55.32                        0   \n",
       "2470          321         60.45                        1   \n",
       "2780          327         46.69                        0   \n",
       "2792          300         44.07                        0   \n",
       "2886          372         56.10                        0   \n",
       "3090          331         55.62                        0   \n",
       "3703          305         62.12                        0   \n",
       "3768          240         58.59                        1   \n",
       "4192          291         59.79                        1   \n",
       "\n",
       "      area_code_area_code_415  area_code_area_code_510  state_MD  state_MN  \\\n",
       "146                         0                        0         0         0   \n",
       "285                         0                        0         0         0   \n",
       "405                         0                        1         0         0   \n",
       "593                         1                        0         0         0   \n",
       "735                         1                        0         0         0   \n",
       "863                         1                        0         0         0   \n",
       "903                         1                        0         0         0   \n",
       "1186                        1                        0         0         0   \n",
       "1317                        0                        1         0         0   \n",
       "1993                        0                        0         0         0   \n",
       "2007                        1                        0         0         0   \n",
       "2136                        0                        1         0         0   \n",
       "2316                        0                        0         0         0   \n",
       "2461                        1                        0         0         0   \n",
       "2470                        0                        0         0         0   \n",
       "2780                        0                        1         0         0   \n",
       "2792                        0                        1         0         0   \n",
       "2886                        1                        0         0         0   \n",
       "3090                        0                        1         0         0   \n",
       "3703                        1                        0         0         0   \n",
       "3768                        0                        0         0         1   \n",
       "4192                        0                        0         0         0   \n",
       "\n",
       "      state_NJ  state_TX  state_WV  state_other  avg_mt_minutes  avg_mt_calls  \\\n",
       "146          0         0         0            1       10.365714      4.942857   \n",
       "285          0         0         0            1        4.954082      2.734694   \n",
       "405          0         0         0            1        4.127879      1.921212   \n",
       "593          0         0         0            1        4.013208      2.669811   \n",
       "735          0         0         0            1        8.379032      4.000000   \n",
       "863          0         0         0            1        9.460000      4.985714   \n",
       "903          0         0         0            1        5.149123      2.491228   \n",
       "1186         0         0         0            1        4.393913      2.426087   \n",
       "1317         0         0         0            1        4.248905      1.861314   \n",
       "1993         0         0         0            1        6.454082      2.877551   \n",
       "2007         0         0         0            1        6.284158      3.702970   \n",
       "2136         0         0         0            1        5.305814      4.011628   \n",
       "2316         0         0         0            1        4.204430      1.816456   \n",
       "2461         0         0         0            1        6.924138      3.321839   \n",
       "2470         0         0         0            1       10.734483      5.534483   \n",
       "2780         0         0         0            1        4.459167      2.725000   \n",
       "2792         0         0         0            1        4.042520      2.362205   \n",
       "2886         0         0         0            1        6.352381      4.428571   \n",
       "3090         0         0         0            1        7.852564      4.243590   \n",
       "3703         0         0         0            1        3.645652      2.210145   \n",
       "3768         0         0         0            0       12.904545      5.454545   \n",
       "4192         0         0         0            1        3.995973      1.953020   \n",
       "\n",
       "      avg_mt_charge  avg_call_charge  avg_intl_call_charge  avg_call_minutes  \\\n",
       "146        1.048000         0.212023                   NaN          2.097110   \n",
       "285        0.377245         0.137948                   NaN          1.811567   \n",
       "405        0.420606         0.218927                   NaN          2.148580   \n",
       "593        0.345094         0.129258                   NaN          1.503180   \n",
       "735        1.047258         0.261815                   NaN          2.094758   \n",
       "863        0.947000         0.189943                   NaN          1.897421   \n",
       "903        0.503158         0.201972                   NaN          2.066901   \n",
       "1186       0.409913         0.168961                   NaN          1.811111   \n",
       "1317       0.337372         0.181255                   NaN          2.282745   \n",
       "1993       0.714184         0.248191                   NaN          2.242908   \n",
       "2007       0.643960         0.173904                   NaN          1.697059   \n",
       "2136       0.439767         0.109623                   NaN          1.322609   \n",
       "2316       0.390570         0.215017                   NaN          2.314634   \n",
       "2461       0.635862         0.191419                   NaN          2.084429   \n",
       "2470       1.042241         0.188318                   NaN          1.939564   \n",
       "2780       0.389083         0.142783                   NaN          1.636391   \n",
       "2792       0.347008         0.146900                   NaN          1.711333   \n",
       "2886       0.667857         0.150806                   NaN          1.434409   \n",
       "3090       0.713077         0.168036                   NaN          1.850453   \n",
       "3703       0.450145         0.203672                   NaN          1.649508   \n",
       "3768       1.331591         0.244125                   NaN          2.365833   \n",
       "4192       0.401275         0.205464                   NaN          2.046048   \n",
       "\n",
       "      avg_intl_call_minutes  both_plans  \n",
       "146                     NaN           0  \n",
       "285                     NaN           0  \n",
       "405                     NaN           0  \n",
       "593                     NaN           0  \n",
       "735                     NaN           0  \n",
       "863                     NaN           0  \n",
       "903                     NaN           0  \n",
       "1186                    NaN           0  \n",
       "1317                    NaN           0  \n",
       "1993                    NaN           0  \n",
       "2007                    NaN           0  \n",
       "2136                    NaN           0  \n",
       "2316                    NaN           0  \n",
       "2461                    NaN           0  \n",
       "2470                    NaN           0  \n",
       "2780                    NaN           0  \n",
       "2792                    NaN           0  \n",
       "2886                    NaN           0  \n",
       "3090                    NaN           0  \n",
       "3703                    NaN           0  \n",
       "3768                    NaN           0  \n",
       "4192                    NaN           0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['avg_intl_call_charge'].isna()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is ok to just replace NaNs with zeros"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.fillna(0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 4195 entries, 0 to 4249\n",
      "Data columns (total 29 columns):\n",
      " #   Column                         Non-Null Count  Dtype  \n",
      "---  ------                         --------------  -----  \n",
      " 0   account_length                 4195 non-null   int64  \n",
      " 1   international_plan             4195 non-null   int64  \n",
      " 2   voice_mail_plan                4195 non-null   int64  \n",
      " 3   number_vmail_messages          4195 non-null   int64  \n",
      " 4   total_intl_minutes             4195 non-null   float64\n",
      " 5   total_intl_calls               4195 non-null   int64  \n",
      " 6   total_intl_charge              4195 non-null   float64\n",
      " 7   number_customer_service_calls  4195 non-null   int64  \n",
      " 8   churn                          4195 non-null   int64  \n",
      " 9   total_minutes                  4195 non-null   float64\n",
      " 10  total_calls                    4195 non-null   int64  \n",
      " 11  total_charge                   4195 non-null   float64\n",
      " 12  area_code_area_code_408        4195 non-null   uint8  \n",
      " 13  area_code_area_code_415        4195 non-null   uint8  \n",
      " 14  area_code_area_code_510        4195 non-null   uint8  \n",
      " 15  state_MD                       4195 non-null   uint8  \n",
      " 16  state_MN                       4195 non-null   uint8  \n",
      " 17  state_NJ                       4195 non-null   uint8  \n",
      " 18  state_TX                       4195 non-null   uint8  \n",
      " 19  state_WV                       4195 non-null   uint8  \n",
      " 20  state_other                    4195 non-null   uint8  \n",
      " 21  avg_mt_minutes                 4195 non-null   float64\n",
      " 22  avg_mt_calls                   4195 non-null   float64\n",
      " 23  avg_mt_charge                  4195 non-null   float64\n",
      " 24  avg_call_charge                4195 non-null   float64\n",
      " 25  avg_intl_call_charge           4195 non-null   float64\n",
      " 26  avg_call_minutes               4195 non-null   float64\n",
      " 27  avg_intl_call_minutes          4195 non-null   float64\n",
      " 28  both_plans                     4195 non-null   int64  \n",
      "dtypes: float64(11), int64(9), uint8(9)\n",
      "memory usage: 725.1 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save the train data for now, for test we will write scripts, as it is in production.\n",
    "Besides, it's pointless now, since some features will be unnecessary.\n",
    "We will check in sharp, feature_importance_, etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = 'featured_data//'\n",
    "file_name = 'train.csv'\n",
    "df.to_csv(path + file_name, index=False)"
   ]
  }
 ],
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