advertising.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4423bcf6-2a12-4955-9d0e-c393ab1d57b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c87b81ee-6e0a-4e41-99c0-60822197c03a",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv(r'C:\\Users\\KHJ\\Titanic\\Titanic\\netflix\\advertising.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8c2f685d-8b5e-4e8d-8b11-6628e4eae35a",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Daily Time Spent on Site</th>\n",
       "      <th>Age</th>\n",
       "      <th>Area Income</th>\n",
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       "      <th>Ad Topic Line</th>\n",
       "      <th>City</th>\n",
       "      <th>Male</th>\n",
       "      <th>Country</th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>Clicked on Ad</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>68.95</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61833.90</td>\n",
       "      <td>256.09</td>\n",
       "      <td>Cloned 5thgeneration orchestration</td>\n",
       "      <td>Wrightburgh</td>\n",
       "      <td>0</td>\n",
       "      <td>Tunisia</td>\n",
       "      <td>3/27/2016 0:53</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>80.23</td>\n",
       "      <td>31.0</td>\n",
       "      <td>68441.85</td>\n",
       "      <td>193.77</td>\n",
       "      <td>Monitored national standardization</td>\n",
       "      <td>West Jodi</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>69.47</td>\n",
       "      <td>26.0</td>\n",
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       "      <td>236.50</td>\n",
       "      <td>Organic bottom-line service-desk</td>\n",
       "      <td>Davidton</td>\n",
       "      <td>0</td>\n",
       "      <td>San Marino</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>74.15</td>\n",
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       "      <td>54806.18</td>\n",
       "      <td>245.89</td>\n",
       "      <td>Triple-buffered reciprocal time-frame</td>\n",
       "      <td>West Terrifurt</td>\n",
       "      <td>1</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1/10/2016 2:31</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>68.37</td>\n",
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       "      <td>225.58</td>\n",
       "      <td>Robust logistical utilization</td>\n",
       "      <td>South Manuel</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>72.97</td>\n",
       "      <td>30.0</td>\n",
       "      <td>71384.57</td>\n",
       "      <td>208.58</td>\n",
       "      <td>Fundamental modular algorithm</td>\n",
       "      <td>Duffystad</td>\n",
       "      <td>1</td>\n",
       "      <td>Lebanon</td>\n",
       "      <td>2/11/2016 21:49</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>51.30</td>\n",
       "      <td>45.0</td>\n",
       "      <td>67782.17</td>\n",
       "      <td>134.42</td>\n",
       "      <td>Grass-roots cohesive monitoring</td>\n",
       "      <td>New Darlene</td>\n",
       "      <td>1</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "      <td>4/22/2016 2:07</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>51.63</td>\n",
       "      <td>51.0</td>\n",
       "      <td>42415.72</td>\n",
       "      <td>120.37</td>\n",
       "      <td>Expanded intangible solution</td>\n",
       "      <td>South Jessica</td>\n",
       "      <td>1</td>\n",
       "      <td>Mongolia</td>\n",
       "      <td>2/1/2016 17:24</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>55.55</td>\n",
       "      <td>19.0</td>\n",
       "      <td>41920.79</td>\n",
       "      <td>187.95</td>\n",
       "      <td>Proactive bandwidth-monitored policy</td>\n",
       "      <td>West Steven</td>\n",
       "      <td>0</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>3/24/2016 2:35</td>\n",
       "      <td>0</td>\n",
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       "      <td>29875.80</td>\n",
       "      <td>178.35</td>\n",
       "      <td>Virtual 5thgeneration emulation</td>\n",
       "      <td>Ronniemouth</td>\n",
       "      <td>0</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>6/3/2016 21:43</td>\n",
       "      <td>1</td>\n",
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      "text/plain": [
       "     Daily Time Spent on Site   Age  Area Income  Daily Internet Usage  \\\n",
       "0                       68.95   NaN     61833.90                256.09   \n",
       "1                       80.23  31.0     68441.85                193.77   \n",
       "2                       69.47  26.0     59785.94                236.50   \n",
       "3                       74.15  29.0     54806.18                245.89   \n",
       "4                       68.37  35.0     73889.99                225.58   \n",
       "..                        ...   ...          ...                   ...   \n",
       "995                     72.97  30.0     71384.57                208.58   \n",
       "996                     51.30  45.0     67782.17                134.42   \n",
       "997                     51.63  51.0     42415.72                120.37   \n",
       "998                     55.55  19.0     41920.79                187.95   \n",
       "999                     45.01  26.0     29875.80                178.35   \n",
       "\n",
       "                             Ad Topic Line            City  Male  \\\n",
       "0       Cloned 5thgeneration orchestration     Wrightburgh     0   \n",
       "1       Monitored national standardization       West Jodi     1   \n",
       "2         Organic bottom-line service-desk        Davidton     0   \n",
       "3    Triple-buffered reciprocal time-frame  West Terrifurt     1   \n",
       "4            Robust logistical utilization    South Manuel     0   \n",
       "..                                     ...             ...   ...   \n",
       "995          Fundamental modular algorithm       Duffystad     1   \n",
       "996        Grass-roots cohesive monitoring     New Darlene     1   \n",
       "997           Expanded intangible solution   South Jessica     1   \n",
       "998   Proactive bandwidth-monitored policy     West Steven     0   \n",
       "999        Virtual 5thgeneration emulation     Ronniemouth     0   \n",
       "\n",
       "                    Country        Timestamp  Clicked on Ad  \n",
       "0                   Tunisia   3/27/2016 0:53              0  \n",
       "1                     Nauru    4/4/2016 1:39              0  \n",
       "2                San Marino  3/13/2016 20:35              0  \n",
       "3                     Italy   1/10/2016 2:31              0  \n",
       "4                   Iceland    6/3/2016 3:36              0  \n",
       "..                      ...              ...            ...  \n",
       "995                 Lebanon  2/11/2016 21:49              1  \n",
       "996  Bosnia and Herzegovina   4/22/2016 2:07              1  \n",
       "997                Mongolia   2/1/2016 17:24              1  \n",
       "998               Guatemala   3/24/2016 2:35              0  \n",
       "999                  Brazil   6/3/2016 21:43              1  \n",
       "\n",
       "[1000 rows x 10 columns]"
      ]
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       "      <th>3</th>\n",
       "      <td>74.15</td>\n",
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       "      <td>54806.18</td>\n",
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       "      <td>1</td>\n",
       "      <td>Italy</td>\n",
       "      <td>1/10/2016 2:31</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>68.37</td>\n",
       "      <td>35.0</td>\n",
       "      <td>73889.99</td>\n",
       "      <td>225.58</td>\n",
       "      <td>Robust logistical utilization</td>\n",
       "      <td>South Manuel</td>\n",
       "      <td>0</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>6/3/2016 3:36</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>59.99</td>\n",
       "      <td>23.0</td>\n",
       "      <td>59761.56</td>\n",
       "      <td>226.74</td>\n",
       "      <td>Sharable client-driven software</td>\n",
       "      <td>Jamieberg</td>\n",
       "      <td>1</td>\n",
       "      <td>Norway</td>\n",
       "      <td>5/19/2016 14:30</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>88.91</td>\n",
       "      <td>NaN</td>\n",
       "      <td>53852.85</td>\n",
       "      <td>208.36</td>\n",
       "      <td>Enhanced dedicated support</td>\n",
       "      <td>Brandonstad</td>\n",
       "      <td>0</td>\n",
       "      <td>Myanmar</td>\n",
       "      <td>1/28/2016 20:59</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>66.00</td>\n",
       "      <td>48.0</td>\n",
       "      <td>24593.33</td>\n",
       "      <td>131.76</td>\n",
       "      <td>Reactive local challenge</td>\n",
       "      <td>Port Jefferybury</td>\n",
       "      <td>1</td>\n",
       "      <td>Australia</td>\n",
       "      <td>3/7/2016 1:40</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>74.53</td>\n",
       "      <td>30.0</td>\n",
       "      <td>68862.00</td>\n",
       "      <td>221.51</td>\n",
       "      <td>Configurable coherent function</td>\n",
       "      <td>West Colin</td>\n",
       "      <td>1</td>\n",
       "      <td>Grenada</td>\n",
       "      <td>4/18/2016 9:33</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>69.88</td>\n",
       "      <td>20.0</td>\n",
       "      <td>55642.32</td>\n",
       "      <td>183.82</td>\n",
       "      <td>Mandatory homogeneous architecture</td>\n",
       "      <td>Ramirezton</td>\n",
       "      <td>1</td>\n",
       "      <td>Ghana</td>\n",
       "      <td>7/11/2016 1:42</td>\n",
       "      <td>0</td>\n",
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       "   Daily Time Spent on Site   Age  Area Income  Daily Internet Usage  \\\n",
       "0                     68.95   NaN     61833.90                256.09   \n",
       "1                     80.23  31.0     68441.85                193.77   \n",
       "2                     69.47  26.0     59785.94                236.50   \n",
       "3                     74.15  29.0     54806.18                245.89   \n",
       "4                     68.37  35.0     73889.99                225.58   \n",
       "5                     59.99  23.0     59761.56                226.74   \n",
       "6                     88.91   NaN     53852.85                208.36   \n",
       "7                     66.00  48.0     24593.33                131.76   \n",
       "8                     74.53  30.0     68862.00                221.51   \n",
       "9                     69.88  20.0     55642.32                183.82   \n",
       "\n",
       "                           Ad Topic Line              City  Male     Country  \\\n",
       "0     Cloned 5thgeneration orchestration       Wrightburgh     0     Tunisia   \n",
       "1     Monitored national standardization         West Jodi     1       Nauru   \n",
       "2       Organic bottom-line service-desk          Davidton     0  San Marino   \n",
       "3  Triple-buffered reciprocal time-frame    West Terrifurt     1       Italy   \n",
       "4          Robust logistical utilization      South Manuel     0     Iceland   \n",
       "5        Sharable client-driven software         Jamieberg     1      Norway   \n",
       "6             Enhanced dedicated support       Brandonstad     0     Myanmar   \n",
       "7               Reactive local challenge  Port Jefferybury     1   Australia   \n",
       "8         Configurable coherent function        West Colin     1     Grenada   \n",
       "9     Mandatory homogeneous architecture        Ramirezton     1       Ghana   \n",
       "\n",
       "         Timestamp  Clicked on Ad  \n",
       "0   3/27/2016 0:53              0  \n",
       "1    4/4/2016 1:39              0  \n",
       "2  3/13/2016 20:35              0  \n",
       "3   1/10/2016 2:31              0  \n",
       "4    6/3/2016 3:36              0  \n",
       "5  5/19/2016 14:30              0  \n",
       "6  1/28/2016 20:59              0  \n",
       "7    3/7/2016 1:40              1  \n",
       "8   4/18/2016 9:33              0  \n",
       "9   7/11/2016 1:42              0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
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    }
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  {
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   "execution_count": 13,
   "id": "d7566ffd-d060-47dc-848f-840100685890",
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     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1000 entries, 0 to 999\n",
      "Data columns (total 10 columns):\n",
      " #   Column                    Non-Null Count  Dtype  \n",
      "---  ------                    --------------  -----  \n",
      " 0   Daily Time Spent on Site  1000 non-null   float64\n",
      " 1   Age                       916 non-null    float64\n",
      " 2   Area Income               1000 non-null   float64\n",
      " 3   Daily Internet Usage      1000 non-null   float64\n",
      " 4   Ad Topic Line             1000 non-null   object \n",
      " 5   City                      1000 non-null   object \n",
      " 6   Male                      1000 non-null   int64  \n",
      " 7   Country                   1000 non-null   object \n",
      " 8   Timestamp                 1000 non-null   object \n",
      " 9   Clicked on Ad             1000 non-null   int64  \n",
      "dtypes: float64(4), int64(2), object(4)\n",
      "memory usage: 78.3+ KB\n"
     ]
    }
   ],
   "source": [
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  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0ea67c01-d178-4033-a96d-dd62e66a1d17",
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       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>916.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>65.000200</td>\n",
       "      <td>36.128821</td>\n",
       "      <td>55000.000080</td>\n",
       "      <td>180.000100</td>\n",
       "      <td>0.481000</td>\n",
       "      <td>0.50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>15.853615</td>\n",
       "      <td>9.018548</td>\n",
       "      <td>13414.634022</td>\n",
       "      <td>43.902339</td>\n",
       "      <td>0.499889</td>\n",
       "      <td>0.50025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>32.600000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>13996.500000</td>\n",
       "      <td>104.780000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>51.360000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>47031.802500</td>\n",
       "      <td>138.830000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>68.215000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>57012.300000</td>\n",
       "      <td>183.130000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.50000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>78.547500</td>\n",
       "      <td>42.000000</td>\n",
       "      <td>65470.635000</td>\n",
       "      <td>218.792500</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>91.430000</td>\n",
       "      <td>61.000000</td>\n",
       "      <td>79484.800000</td>\n",
       "      <td>269.960000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Daily Time Spent on Site         Age   Area Income  \\\n",
       "count               1000.000000  916.000000   1000.000000   \n",
       "mean                  65.000200   36.128821  55000.000080   \n",
       "std                   15.853615    9.018548  13414.634022   \n",
       "min                   32.600000   19.000000  13996.500000   \n",
       "25%                   51.360000   29.000000  47031.802500   \n",
       "50%                   68.215000   35.000000  57012.300000   \n",
       "75%                   78.547500   42.000000  65470.635000   \n",
       "max                   91.430000   61.000000  79484.800000   \n",
       "\n",
       "       Daily Internet Usage         Male  Clicked on Ad  \n",
       "count           1000.000000  1000.000000     1000.00000  \n",
       "mean             180.000100     0.481000        0.50000  \n",
       "std               43.902339     0.499889        0.50025  \n",
       "min              104.780000     0.000000        0.00000  \n",
       "25%              138.830000     0.000000        0.00000  \n",
       "50%              183.130000     0.000000        0.50000  \n",
       "75%              218.792500     1.000000        1.00000  \n",
       "max              269.960000     1.000000        1.00000  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8f7c412b-a45c-4ca7-8858-44e19d77f065",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\KHJ\\AppData\\Local\\Temp\\ipykernel_7344\\814957152.py:1: UserWarning: \n",
      "\n",
      "`distplot` is a deprecated function and will be removed in seaborn v0.14.0.\n",
      "\n",
      "Please adapt your code to use either `displot` (a figure-level function with\n",
      "similar flexibility) or `histplot` (an axes-level function for histograms).\n",
      "\n",
      "For a guide to updating your code to use the new functions, please see\n",
      "https://gist.github.com/mwaskom/de44147ed2974457ad6372750bbe5751\n",
      "\n",
      "  sns.distplot(data['Area Income'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Area Income', ylabel='Density'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(data['Area Income'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "9489245c-071e-4100-8659-67cbd3ce6cf5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "237"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Country'].nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "079c46ab-a07a-491e-8d19-3d67a5675b73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Daily Time Spent on Site     0\n",
       "Age                         84\n",
       "Area Income                  0\n",
       "Daily Internet Usage         0\n",
       "Ad Topic Line                0\n",
       "City                         0\n",
       "Male                         0\n",
       "Country                      0\n",
       "Timestamp                    0\n",
       "Clicked on Ad                0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dabf3db7-ee29-440d-bb0c-5140df8cee42",
   "metadata": {},
   "outputs": [],
   "source": [
    "impute"
   ]
  }
 ],
 "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}