Income Prediction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing libraries\n",
    "import pandas as pd\n",
    "import numpy as np \n",
    "from sklearn import preprocessing\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>fnlwgt</th>\n",
       "      <th>education</th>\n",
       "      <th>educational-num</th>\n",
       "      <th>marital-status</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>gender</th>\n",
       "      <th>capital-gain</th>\n",
       "      <th>capital-loss</th>\n",
       "      <th>hours-per-week</th>\n",
       "      <th>native-country</th>\n",
       "      <th>income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>77516</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>83311</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>215646</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>Private</td>\n",
       "      <td>234721</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>Private</td>\n",
       "      <td>338409</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Wife</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age          workclass  fnlwgt   education  educational-num  \\\n",
       "0   39          State-gov   77516   Bachelors               13   \n",
       "1   50   Self-emp-not-inc   83311   Bachelors               13   \n",
       "2   38            Private  215646     HS-grad                9   \n",
       "3   53            Private  234721        11th                7   \n",
       "4   28            Private  338409   Bachelors               13   \n",
       "\n",
       "        marital-status          occupation    relationship    race   gender  \\\n",
       "0        Never-married        Adm-clerical   Not-in-family   White     Male   \n",
       "1   Married-civ-spouse     Exec-managerial         Husband   White     Male   \n",
       "2             Divorced   Handlers-cleaners   Not-in-family   White     Male   \n",
       "3   Married-civ-spouse   Handlers-cleaners         Husband   Black     Male   \n",
       "4   Married-civ-spouse      Prof-specialty            Wife   Black   Female   \n",
       "\n",
       "   capital-gain  capital-loss  hours-per-week  native-country  income  \n",
       "0          2174             0              40   United-States   <=50K  \n",
       "1             0             0              13   United-States   <=50K  \n",
       "2             0             0              40   United-States   <=50K  \n",
       "3             0             0              40   United-States   <=50K  \n",
       "4             0             0              40            Cuba   <=50K  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load dataset\n",
    "data= pd.read_csv('data/adult.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# filling missing data\n",
    "column_names=data.columns \n",
    "for a in column_names:\n",
    "    data[a]=data[a].replace('?', np.NaN)\n",
    "    \n",
    "data= data.apply(lambda x: x.fillna(x.value_counts().index[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['age', 'workclass', 'fnlwgt', 'education', 'educational-num',\n",
       "       'marital-status', 'occupation', 'relationship', 'race', 'gender',\n",
       "       'capital-gain', 'capital-loss', 'hours-per-week', 'native-country',\n",
       "       'income'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([' Never-married', ' Married-civ-spouse', ' Divorced',\n",
       "       ' Married-spouse-absent', ' Separated', ' Married-AF-spouse',\n",
       "       ' Widowed'], dtype=object)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['marital-status'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>workclass</th>\n",
       "      <th>fnlwgt</th>\n",
       "      <th>education</th>\n",
       "      <th>educational-num</th>\n",
       "      <th>marital-status</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>gender</th>\n",
       "      <th>capital-gain</th>\n",
       "      <th>capital-loss</th>\n",
       "      <th>hours-per-week</th>\n",
       "      <th>native-country</th>\n",
       "      <th>income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>39</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>77516</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>not married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
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       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>50</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>83311</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>215646</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>53</td>\n",
       "      <td>Private</td>\n",
       "      <td>234721</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>married</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28</td>\n",
       "      <td>Private</td>\n",
       "      <td>338409</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>married</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Wife</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>37</td>\n",
       "      <td>Private</td>\n",
       "      <td>284582</td>\n",
       "      <td>Masters</td>\n",
       "      <td>14</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Wife</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>49</td>\n",
       "      <td>Private</td>\n",
       "      <td>160187</td>\n",
       "      <td>9th</td>\n",
       "      <td>5</td>\n",
       "      <td>married</td>\n",
       "      <td>Other-service</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>Jamaica</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>52</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>209642</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>31</td>\n",
       "      <td>Private</td>\n",
       "      <td>45781</td>\n",
       "      <td>Masters</td>\n",
       "      <td>14</td>\n",
       "      <td>not married</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>14084</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>42</td>\n",
       "      <td>Private</td>\n",
       "      <td>159449</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>5178</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>37</td>\n",
       "      <td>Private</td>\n",
       "      <td>280464</td>\n",
       "      <td>Some-college</td>\n",
       "      <td>10</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>80</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>30</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>141297</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>married</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Asian-Pac-Islander</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>India</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>23</td>\n",
       "      <td>Private</td>\n",
       "      <td>122272</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>not married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>32</td>\n",
       "      <td>Private</td>\n",
       "      <td>205019</td>\n",
       "      <td>Assoc-acdm</td>\n",
       "      <td>12</td>\n",
       "      <td>not married</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>40</td>\n",
       "      <td>Private</td>\n",
       "      <td>121772</td>\n",
       "      <td>Assoc-voc</td>\n",
       "      <td>11</td>\n",
       "      <td>married</td>\n",
       "      <td>Craft-repair</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Asian-Pac-Islander</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>?</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>34</td>\n",
       "      <td>Private</td>\n",
       "      <td>245487</td>\n",
       "      <td>7th-8th</td>\n",
       "      <td>4</td>\n",
       "      <td>married</td>\n",
       "      <td>Transport-moving</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Amer-Indian-Eskimo</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>25</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>176756</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Farming-fishing</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>32</td>\n",
       "      <td>Private</td>\n",
       "      <td>186824</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Machine-op-inspct</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>28887</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>married</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>43</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>292175</td>\n",
       "      <td>Masters</td>\n",
       "      <td>14</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>40</td>\n",
       "      <td>Private</td>\n",
       "      <td>193524</td>\n",
       "      <td>Doctorate</td>\n",
       "      <td>16</td>\n",
       "      <td>married</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>54</td>\n",
       "      <td>Private</td>\n",
       "      <td>302146</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Other-service</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>35</td>\n",
       "      <td>Federal-gov</td>\n",
       "      <td>76845</td>\n",
       "      <td>9th</td>\n",
       "      <td>5</td>\n",
       "      <td>married</td>\n",
       "      <td>Farming-fishing</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>43</td>\n",
       "      <td>Private</td>\n",
       "      <td>117037</td>\n",
       "      <td>11th</td>\n",
       "      <td>7</td>\n",
       "      <td>married</td>\n",
       "      <td>Transport-moving</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>2042</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>59</td>\n",
       "      <td>Private</td>\n",
       "      <td>109015</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Tech-support</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>56</td>\n",
       "      <td>Local-gov</td>\n",
       "      <td>216851</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>married</td>\n",
       "      <td>Tech-support</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>19</td>\n",
       "      <td>Private</td>\n",
       "      <td>168294</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Craft-repair</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>54</td>\n",
       "      <td>?</td>\n",
       "      <td>180211</td>\n",
       "      <td>Some-college</td>\n",
       "      <td>10</td>\n",
       "      <td>married</td>\n",
       "      <td>?</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Asian-Pac-Islander</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>South</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>39</td>\n",
       "      <td>Private</td>\n",
       "      <td>367260</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>80</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>49</td>\n",
       "      <td>Private</td>\n",
       "      <td>193366</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>married</td>\n",
       "      <td>Craft-repair</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32531</th>\n",
       "      <td>30</td>\n",
       "      <td>?</td>\n",
       "      <td>33811</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>not married</td>\n",
       "      <td>?</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>Asian-Pac-Islander</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32532</th>\n",
       "      <td>34</td>\n",
       "      <td>Private</td>\n",
       "      <td>204461</td>\n",
       "      <td>Doctorate</td>\n",
       "      <td>16</td>\n",
       "      <td>married</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32533</th>\n",
       "      <td>54</td>\n",
       "      <td>Private</td>\n",
       "      <td>337992</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Asian-Pac-Islander</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>Japan</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32534</th>\n",
       "      <td>37</td>\n",
       "      <td>Private</td>\n",
       "      <td>179137</td>\n",
       "      <td>Some-college</td>\n",
       "      <td>10</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>39</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32535</th>\n",
       "      <td>22</td>\n",
       "      <td>Private</td>\n",
       "      <td>325033</td>\n",
       "      <td>12th</td>\n",
       "      <td>8</td>\n",
       "      <td>not married</td>\n",
       "      <td>Protective-serv</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32536</th>\n",
       "      <td>34</td>\n",
       "      <td>Private</td>\n",
       "      <td>160216</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>not married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32537</th>\n",
       "      <td>30</td>\n",
       "      <td>Private</td>\n",
       "      <td>345898</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Craft-repair</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32538</th>\n",
       "      <td>38</td>\n",
       "      <td>Private</td>\n",
       "      <td>139180</td>\n",
       "      <td>Bachelors</td>\n",
       "      <td>13</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>15020</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32539</th>\n",
       "      <td>71</td>\n",
       "      <td>?</td>\n",
       "      <td>287372</td>\n",
       "      <td>Doctorate</td>\n",
       "      <td>16</td>\n",
       "      <td>married</td>\n",
       "      <td>?</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32540</th>\n",
       "      <td>45</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>252208</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32541</th>\n",
       "      <td>41</td>\n",
       "      <td>?</td>\n",
       "      <td>202822</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>?</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>32</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32542</th>\n",
       "      <td>72</td>\n",
       "      <td>?</td>\n",
       "      <td>129912</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>married</td>\n",
       "      <td>?</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32543</th>\n",
       "      <td>45</td>\n",
       "      <td>Local-gov</td>\n",
       "      <td>119199</td>\n",
       "      <td>Assoc-acdm</td>\n",
       "      <td>12</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>48</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32544</th>\n",
       "      <td>31</td>\n",
       "      <td>Private</td>\n",
       "      <td>199655</td>\n",
       "      <td>Masters</td>\n",
       "      <td>14</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Other-service</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>Other</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32545</th>\n",
       "      <td>39</td>\n",
       "      <td>Local-gov</td>\n",
       "      <td>111499</td>\n",
       "      <td>Assoc-acdm</td>\n",
       "      <td>12</td>\n",
       "      <td>married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Wife</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32546</th>\n",
       "      <td>37</td>\n",
       "      <td>Private</td>\n",
       "      <td>198216</td>\n",
       "      <td>Assoc-acdm</td>\n",
       "      <td>12</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Tech-support</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32547</th>\n",
       "      <td>43</td>\n",
       "      <td>Private</td>\n",
       "      <td>260761</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>married</td>\n",
       "      <td>Machine-op-inspct</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32548</th>\n",
       "      <td>65</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>99359</td>\n",
       "      <td>Prof-school</td>\n",
       "      <td>15</td>\n",
       "      <td>not married</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>1086</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32549</th>\n",
       "      <td>43</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>255835</td>\n",
       "      <td>Some-college</td>\n",
       "      <td>10</td>\n",
       "      <td>divorced</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Other-relative</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32550</th>\n",
       "      <td>43</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>27242</td>\n",
       "      <td>Some-college</td>\n",
       "      <td>10</td>\n",
       "      <td>married</td>\n",
       "      <td>Craft-repair</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32551</th>\n",
       "      <td>32</td>\n",
       "      <td>Private</td>\n",
       "      <td>34066</td>\n",
       "      <td>10th</td>\n",
       "      <td>6</td>\n",
       "      <td>married</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Husband</td>\n",
       "      <td>Amer-Indian-Eskimo</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32552</th>\n",
       "      <td>43</td>\n",
       "      <td>Private</td>\n",
       "      <td>84661</td>\n",
       "      <td>Assoc-voc</td>\n",
       "      <td>11</td>\n",
       "      <td>married</td>\n",
       "      <td>Sales</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32553</th>\n",
       "      <td>32</td>\n",
       "      <td>Private</td>\n",
       "      <td>116138</td>\n",
       "      <td>Masters</td>\n",
       "      <td>14</td>\n",
       "      <td>not married</td>\n",
       "      <td>Tech-support</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>Asian-Pac-Islander</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>Taiwan</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32554</th>\n",
       "      <td>53</td>\n",
       "      <td>Private</td>\n",
       "      <td>321865</td>\n",
       "      <td>Masters</td>\n",
       "      <td>14</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32555</th>\n",
       "      <td>22</td>\n",
       "      <td>Private</td>\n",
       "      <td>310152</td>\n",
       "      <td>Some-college</td>\n",
       "      <td>10</td>\n",
       "      <td>not married</td>\n",
       "      <td>Protective-serv</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32556</th>\n",
       "      <td>27</td>\n",
       "      <td>Private</td>\n",
       "      <td>257302</td>\n",
       "      <td>Assoc-acdm</td>\n",
       "      <td>12</td>\n",
       "      <td>married</td>\n",
       "      <td>Tech-support</td>\n",
       "      <td>Wife</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>38</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32557</th>\n",
       "      <td>40</td>\n",
       "      <td>Private</td>\n",
       "      <td>154374</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>married</td>\n",
       "      <td>Machine-op-inspct</td>\n",
       "      <td>Husband</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32558</th>\n",
       "      <td>58</td>\n",
       "      <td>Private</td>\n",
       "      <td>151910</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Unmarried</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32559</th>\n",
       "      <td>22</td>\n",
       "      <td>Private</td>\n",
       "      <td>201490</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>not married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Own-child</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&lt;=50K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32560</th>\n",
       "      <td>52</td>\n",
       "      <td>Self-emp-inc</td>\n",
       "      <td>287927</td>\n",
       "      <td>HS-grad</td>\n",
       "      <td>9</td>\n",
       "      <td>married</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Wife</td>\n",
       "      <td>White</td>\n",
       "      <td>Female</td>\n",
       "      <td>15024</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "      <td>United-States</td>\n",
       "      <td>&gt;50K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32561 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       age          workclass  fnlwgt      education  educational-num  \\\n",
       "0       39          State-gov   77516      Bachelors               13   \n",
       "1       50   Self-emp-not-inc   83311      Bachelors               13   \n",
       "2       38            Private  215646        HS-grad                9   \n",
       "3       53            Private  234721           11th                7   \n",
       "4       28            Private  338409      Bachelors               13   \n",
       "5       37            Private  284582        Masters               14   \n",
       "6       49            Private  160187            9th                5   \n",
       "7       52   Self-emp-not-inc  209642        HS-grad                9   \n",
       "8       31            Private   45781        Masters               14   \n",
       "9       42            Private  159449      Bachelors               13   \n",
       "10      37            Private  280464   Some-college               10   \n",
       "11      30          State-gov  141297      Bachelors               13   \n",
       "12      23            Private  122272      Bachelors               13   \n",
       "13      32            Private  205019     Assoc-acdm               12   \n",
       "14      40            Private  121772      Assoc-voc               11   \n",
       "15      34            Private  245487        7th-8th                4   \n",
       "16      25   Self-emp-not-inc  176756        HS-grad                9   \n",
       "17      32            Private  186824        HS-grad                9   \n",
       "18      38            Private   28887           11th                7   \n",
       "19      43   Self-emp-not-inc  292175        Masters               14   \n",
       "20      40            Private  193524      Doctorate               16   \n",
       "21      54            Private  302146        HS-grad                9   \n",
       "22      35        Federal-gov   76845            9th                5   \n",
       "23      43            Private  117037           11th                7   \n",
       "24      59            Private  109015        HS-grad                9   \n",
       "25      56          Local-gov  216851      Bachelors               13   \n",
       "26      19            Private  168294        HS-grad                9   \n",
       "27      54                  ?  180211   Some-college               10   \n",
       "28      39            Private  367260        HS-grad                9   \n",
       "29      49            Private  193366        HS-grad                9   \n",
       "...    ...                ...     ...            ...              ...   \n",
       "32531   30                  ?   33811      Bachelors               13   \n",
       "32532   34            Private  204461      Doctorate               16   \n",
       "32533   54            Private  337992      Bachelors               13   \n",
       "32534   37            Private  179137   Some-college               10   \n",
       "32535   22            Private  325033           12th                8   \n",
       "32536   34            Private  160216      Bachelors               13   \n",
       "32537   30            Private  345898        HS-grad                9   \n",
       "32538   38            Private  139180      Bachelors               13   \n",
       "32539   71                  ?  287372      Doctorate               16   \n",
       "32540   45          State-gov  252208        HS-grad                9   \n",
       "32541   41                  ?  202822        HS-grad                9   \n",
       "32542   72                  ?  129912        HS-grad                9   \n",
       "32543   45          Local-gov  119199     Assoc-acdm               12   \n",
       "32544   31            Private  199655        Masters               14   \n",
       "32545   39          Local-gov  111499     Assoc-acdm               12   \n",
       "32546   37            Private  198216     Assoc-acdm               12   \n",
       "32547   43            Private  260761        HS-grad                9   \n",
       "32548   65   Self-emp-not-inc   99359    Prof-school               15   \n",
       "32549   43          State-gov  255835   Some-college               10   \n",
       "32550   43   Self-emp-not-inc   27242   Some-college               10   \n",
       "32551   32            Private   34066           10th                6   \n",
       "32552   43            Private   84661      Assoc-voc               11   \n",
       "32553   32            Private  116138        Masters               14   \n",
       "32554   53            Private  321865        Masters               14   \n",
       "32555   22            Private  310152   Some-college               10   \n",
       "32556   27            Private  257302     Assoc-acdm               12   \n",
       "32557   40            Private  154374        HS-grad                9   \n",
       "32558   58            Private  151910        HS-grad                9   \n",
       "32559   22            Private  201490        HS-grad                9   \n",
       "32560   52       Self-emp-inc  287927        HS-grad                9   \n",
       "\n",
       "      marital-status          occupation     relationship  \\\n",
       "0        not married        Adm-clerical    Not-in-family   \n",
       "1            married     Exec-managerial          Husband   \n",
       "2           divorced   Handlers-cleaners    Not-in-family   \n",
       "3            married   Handlers-cleaners          Husband   \n",
       "4            married      Prof-specialty             Wife   \n",
       "5            married     Exec-managerial             Wife   \n",
       "6            married       Other-service    Not-in-family   \n",
       "7            married     Exec-managerial          Husband   \n",
       "8        not married      Prof-specialty    Not-in-family   \n",
       "9            married     Exec-managerial          Husband   \n",
       "10           married     Exec-managerial          Husband   \n",
       "11           married      Prof-specialty          Husband   \n",
       "12       not married        Adm-clerical        Own-child   \n",
       "13       not married               Sales    Not-in-family   \n",
       "14           married        Craft-repair          Husband   \n",
       "15           married    Transport-moving          Husband   \n",
       "16       not married     Farming-fishing        Own-child   \n",
       "17       not married   Machine-op-inspct        Unmarried   \n",
       "18           married               Sales          Husband   \n",
       "19          divorced     Exec-managerial        Unmarried   \n",
       "20           married      Prof-specialty          Husband   \n",
       "21       not married       Other-service        Unmarried   \n",
       "22           married     Farming-fishing          Husband   \n",
       "23           married    Transport-moving          Husband   \n",
       "24          divorced        Tech-support        Unmarried   \n",
       "25           married        Tech-support          Husband   \n",
       "26       not married        Craft-repair        Own-child   \n",
       "27           married                   ?          Husband   \n",
       "28          divorced     Exec-managerial    Not-in-family   \n",
       "29           married        Craft-repair          Husband   \n",
       "...              ...                 ...              ...   \n",
       "32531    not married                   ?    Not-in-family   \n",
       "32532        married      Prof-specialty          Husband   \n",
       "32533        married     Exec-managerial          Husband   \n",
       "32534       divorced        Adm-clerical        Unmarried   \n",
       "32535    not married     Protective-serv        Own-child   \n",
       "32536    not married     Exec-managerial    Not-in-family   \n",
       "32537    not married        Craft-repair    Not-in-family   \n",
       "32538       divorced      Prof-specialty        Unmarried   \n",
       "32539        married                   ?          Husband   \n",
       "32540    not married        Adm-clerical        Own-child   \n",
       "32541    not married                   ?    Not-in-family   \n",
       "32542        married                   ?          Husband   \n",
       "32543       divorced      Prof-specialty        Unmarried   \n",
       "32544       divorced       Other-service    Not-in-family   \n",
       "32545        married        Adm-clerical             Wife   \n",
       "32546       divorced        Tech-support    Not-in-family   \n",
       "32547        married   Machine-op-inspct          Husband   \n",
       "32548    not married      Prof-specialty    Not-in-family   \n",
       "32549       divorced        Adm-clerical   Other-relative   \n",
       "32550        married        Craft-repair          Husband   \n",
       "32551        married   Handlers-cleaners          Husband   \n",
       "32552        married               Sales          Husband   \n",
       "32553    not married        Tech-support    Not-in-family   \n",
       "32554        married     Exec-managerial          Husband   \n",
       "32555    not married     Protective-serv    Not-in-family   \n",
       "32556        married        Tech-support             Wife   \n",
       "32557        married   Machine-op-inspct          Husband   \n",
       "32558    not married        Adm-clerical        Unmarried   \n",
       "32559    not married        Adm-clerical        Own-child   \n",
       "32560        married     Exec-managerial             Wife   \n",
       "\n",
       "                      race   gender  capital-gain  capital-loss  \\\n",
       "0                    White     Male          2174             0   \n",
       "1                    White     Male             0             0   \n",
       "2                    White     Male             0             0   \n",
       "3                    Black     Male             0             0   \n",
       "4                    Black   Female             0             0   \n",
       "5                    White   Female             0             0   \n",
       "6                    Black   Female             0             0   \n",
       "7                    White     Male             0             0   \n",
       "8                    White   Female         14084             0   \n",
       "9                    White     Male          5178             0   \n",
       "10                   Black     Male             0             0   \n",
       "11      Asian-Pac-Islander     Male             0             0   \n",
       "12                   White   Female             0             0   \n",
       "13                   Black     Male             0             0   \n",
       "14      Asian-Pac-Islander     Male             0             0   \n",
       "15      Amer-Indian-Eskimo     Male             0             0   \n",
       "16                   White     Male             0             0   \n",
       "17                   White     Male             0             0   \n",
       "18                   White     Male             0             0   \n",
       "19                   White   Female             0             0   \n",
       "20                   White     Male             0             0   \n",
       "21                   Black   Female             0             0   \n",
       "22                   Black     Male             0             0   \n",
       "23                   White     Male             0          2042   \n",
       "24                   White   Female             0             0   \n",
       "25                   White     Male             0             0   \n",
       "26                   White     Male             0             0   \n",
       "27      Asian-Pac-Islander     Male             0             0   \n",
       "28                   White     Male             0             0   \n",
       "29                   White     Male             0             0   \n",
       "...                    ...      ...           ...           ...   \n",
       "32531   Asian-Pac-Islander   Female             0             0   \n",
       "32532                White     Male             0             0   \n",
       "32533   Asian-Pac-Islander     Male             0             0   \n",
       "32534                White   Female             0             0   \n",
       "32535                Black     Male             0             0   \n",
       "32536                White   Female             0             0   \n",
       "32537                Black     Male             0             0   \n",
       "32538                Black   Female         15020             0   \n",
       "32539                White     Male             0             0   \n",
       "32540                White   Female             0             0   \n",
       "32541                Black   Female             0             0   \n",
       "32542                White     Male             0             0   \n",
       "32543                White   Female             0             0   \n",
       "32544                Other   Female             0             0   \n",
       "32545                White   Female             0             0   \n",
       "32546                White   Female             0             0   \n",
       "32547                White     Male             0             0   \n",
       "32548                White     Male          1086             0   \n",
       "32549                White   Female             0             0   \n",
       "32550                White     Male             0             0   \n",
       "32551   Amer-Indian-Eskimo     Male             0             0   \n",
       "32552                White     Male             0             0   \n",
       "32553   Asian-Pac-Islander     Male             0             0   \n",
       "32554                White     Male             0             0   \n",
       "32555                White     Male             0             0   \n",
       "32556                White   Female             0             0   \n",
       "32557                White     Male             0             0   \n",
       "32558                White   Female             0             0   \n",
       "32559                White     Male             0             0   \n",
       "32560                White   Female         15024             0   \n",
       "\n",
       "       hours-per-week  native-country  income  \n",
       "0                  40   United-States   <=50K  \n",
       "1                  13   United-States   <=50K  \n",
       "2                  40   United-States   <=50K  \n",
       "3                  40   United-States   <=50K  \n",
       "4                  40            Cuba   <=50K  \n",
       "5                  40   United-States   <=50K  \n",
       "6                  16         Jamaica   <=50K  \n",
       "7                  45   United-States    >50K  \n",
       "8                  50   United-States    >50K  \n",
       "9                  40   United-States    >50K  \n",
       "10                 80   United-States    >50K  \n",
       "11                 40           India    >50K  \n",
       "12                 30   United-States   <=50K  \n",
       "13                 50   United-States   <=50K  \n",
       "14                 40               ?    >50K  \n",
       "15                 45          Mexico   <=50K  \n",
       "16                 35   United-States   <=50K  \n",
       "17                 40   United-States   <=50K  \n",
       "18                 50   United-States   <=50K  \n",
       "19                 45   United-States    >50K  \n",
       "20                 60   United-States    >50K  \n",
       "21                 20   United-States   <=50K  \n",
       "22                 40   United-States   <=50K  \n",
       "23                 40   United-States   <=50K  \n",
       "24                 40   United-States   <=50K  \n",
       "25                 40   United-States    >50K  \n",
       "26                 40   United-States   <=50K  \n",
       "27                 60           South    >50K  \n",
       "28                 80   United-States   <=50K  \n",
       "29                 40   United-States   <=50K  \n",
       "...               ...             ...     ...  \n",
       "32531              99   United-States   <=50K  \n",
       "32532              60   United-States    >50K  \n",
       "32533              50           Japan    >50K  \n",
       "32534              39   United-States   <=50K  \n",
       "32535              35   United-States   <=50K  \n",
       "32536              55   United-States    >50K  \n",
       "32537              46   United-States   <=50K  \n",
       "32538              45   United-States    >50K  \n",
       "32539              10   United-States    >50K  \n",
       "32540              40   United-States   <=50K  \n",
       "32541              32   United-States   <=50K  \n",
       "32542              25   United-States   <=50K  \n",
       "32543              48   United-States   <=50K  \n",
       "32544              30   United-States   <=50K  \n",
       "32545              20   United-States    >50K  \n",
       "32546              40   United-States   <=50K  \n",
       "32547              40          Mexico   <=50K  \n",
       "32548              60   United-States   <=50K  \n",
       "32549              40   United-States   <=50K  \n",
       "32550              50   United-States   <=50K  \n",
       "32551              40   United-States   <=50K  \n",
       "32552              45   United-States   <=50K  \n",
       "32553              11          Taiwan   <=50K  \n",
       "32554              40   United-States    >50K  \n",
       "32555              40   United-States   <=50K  \n",
       "32556              38   United-States   <=50K  \n",
       "32557              40   United-States    >50K  \n",
       "32558              40   United-States   <=50K  \n",
       "32559              20   United-States   <=50K  \n",
       "32560              40   United-States    >50K  \n",
       "\n",
       "[32561 rows x 15 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.replace([' Never-married', ' Married-civ-spouse', ' Divorced',\n",
    "       ' Married-spouse-absent', ' Separated', ' Married-AF-spouse',\n",
    "       ' Widowed'], [' not married', ' married', ' divorced',\n",
    "       ' married', ' not married', ' married',\n",
    "       ' not married'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'workclass': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8}, 'race': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4}, 'education': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9, 10: 10, 11: 11, 12: 12, 13: 13, 14: 14, 15: 15}, 'marital-status': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6}, 'occupation': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9, 10: 10, 11: 11, 12: 12, 13: 13, 14: 14}, 'relationship': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5}, 'gender': {0: 0, 1: 1}, 'native-country': {0: 0, 1: 1, 2: 2, 3: 3, 4: 4, 5: 5, 6: 6, 7: 7, 8: 8, 9: 9, 10: 10, 11: 11, 12: 12, 13: 13, 14: 14, 15: 15, 16: 16, 17: 17, 18: 18, 19: 19, 20: 20, 21: 21, 22: 22, 23: 23, 24: 24, 25: 25, 26: 26, 27: 27, 28: 28, 29: 29, 30: 30, 31: 31, 32: 32, 33: 33, 34: 34, 35: 35, 36: 36, 37: 37, 38: 38, 39: 39, 40: 40, 41: 41}, 'income': {0: 0, 1: 1}}\n"
     ]
    }
   ],
   "source": [
    "#  Label Encoder\n",
    "category_column= ['workclass', 'race', 'education','marital-status', 'occupation','relationship', 'gender', 'native-country', 'income'] \n",
    "labelEncoder= preprocessing.LabelEncoder()\n",
    "\n",
    "# creating a map of all the numerical values of each categorical labels.\n",
    "\n",
    "mapping_dict={}\n",
    "for col in category_column:\n",
    "    data[col]=labelEncoder.fit_transform(data[col])\n",
    "    le_name_mapping=dict(zip(labelEncoder.classes_, labelEncoder.transform(labelEncoder.classes_)))\n",
    "    mapping_dict[col]=le_name_mapping\n",
    "print(mapping_dict)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Desicion Tree using Gini Index\n",
      "Accuracy is  83.13031016480704\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "X= data.values[:,0:12]\n",
    "Y=data.values[:,12]\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split( X, Y,test_size =0.3, random_state = 100)\n",
    "data_clf=DecisionTreeClassifier(criterion='gini',random_state=100, max_depth=5, min_samples_leaf=5)\n",
    "data_clf.fit(X_train,y_train)\n",
    "\n",
    "y_pred=data_clf.predict(X_test)\n",
    "\n",
    "print(\"Desicion Tree using Gini Index\\nAccuracy is \", accuracy_score(y_test,y_pred)*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating and training a model\n",
    "import pickle\n",
    "pickle.dump(data_clf, open(\"model.pkl\",\"wb\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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