Speeddating.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory data analysis of a speeddating survey."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from scipy import stats\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While importing, due to its memory usage for different datatypes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d=pd.read_csv(\"speeddating.csv\", low_memory=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
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       "      <td>[2-3]</td>\n",
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       "      <td>European/Caucasian-American</td>\n",
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       "      <td>[3-5]</td>\n",
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       "      <td>[4-6]</td>\n",
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       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
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       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
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       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>24</td>\n",
       "      <td>24</td>\n",
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       "      <td>European/Caucasian-American</td>\n",
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       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>?</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>?</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8348</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8349</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8350</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8351</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8352</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8353</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8354</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8355</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8356</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8358</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8359</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>?</td>\n",
       "      <td>25</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>?</td>\n",
       "      <td>?</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>?</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8360</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>?</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8362</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8363</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8368</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8369</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8370</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8371</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8372</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8373</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8375</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8377</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8378 rows × 123 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      has_null  wave  gender age age_o  d_age d_d_age  \\\n",
       "0            0     1  female  21    27      6   [4-6]   \n",
       "1            0     1  female  21    22      1   [0-1]   \n",
       "2            1     1  female  21    22      1   [0-1]   \n",
       "3            0     1  female  21    23      2   [2-3]   \n",
       "4            0     1  female  21    24      3   [2-3]   \n",
       "5            0     1  female  21    25      4   [4-6]   \n",
       "6            0     1  female  21    30      9  [7-37]   \n",
       "7            1     1  female  21    27      6   [4-6]   \n",
       "8            0     1  female  21    28      7  [7-37]   \n",
       "9            0     1  female  21    24      3   [2-3]   \n",
       "10           0     1  female  24    27      3   [2-3]   \n",
       "11           0     1  female  24    22      2   [2-3]   \n",
       "12           0     1  female  24    22      2   [2-3]   \n",
       "13           0     1  female  24    23      1   [0-1]   \n",
       "14           0     1  female  24    24      0   [0-1]   \n",
       "15           0     1  female  24    25      1   [0-1]   \n",
       "16           0     1  female  24    30      6   [4-6]   \n",
       "17           0     1  female  24    27      3   [2-3]   \n",
       "18           0     1  female  24    28      4   [4-6]   \n",
       "19           0     1  female  24    24      0   [0-1]   \n",
       "20           1     1  female  25    27      2   [2-3]   \n",
       "21           1     1  female  25    22      3   [2-3]   \n",
       "22           1     1  female  25    22      3   [2-3]   \n",
       "23           1     1  female  25    23      2   [2-3]   \n",
       "24           1     1  female  25    24      1   [0-1]   \n",
       "25           1     1  female  25    25      0   [0-1]   \n",
       "26           1     1  female  25    30      5   [4-6]   \n",
       "27           1     1  female  25    27      2   [2-3]   \n",
       "28           1     1  female  25    28      3   [2-3]   \n",
       "29           1     1  female  25    24      1   [0-1]   \n",
       "...        ...   ...     ...  ..   ...    ...     ...   \n",
       "8348         1    21    male  27    27      0   [0-1]   \n",
       "8349         1    21    male  27    25      2   [2-3]   \n",
       "8350         1    21    male  27    24      3   [2-3]   \n",
       "8351         1    21    male  27    26      1   [0-1]   \n",
       "8352         1    21    male  27    24      3   [2-3]   \n",
       "8353         1    21    male  27    29      2   [2-3]   \n",
       "8354         1    21    male  27    22      5   [4-6]   \n",
       "8355         1    21    male  27    22      5   [4-6]   \n",
       "8356         1    21    male  25    28      3   [2-3]   \n",
       "8357         1    21    male  25    26      1   [0-1]   \n",
       "8358         1    21    male  25    23      2   [2-3]   \n",
       "8359         1    21    male  25     ?     25  [7-37]   \n",
       "8360         1    21    male  25    23      2   [2-3]   \n",
       "8361         1    21    male  25    23      2   [2-3]   \n",
       "8362         1    21    male  25    23      2   [2-3]   \n",
       "8363         1    21    male  25    27      2   [2-3]   \n",
       "8364         1    21    male  25    30      5   [4-6]   \n",
       "8365         1    21    male  25    23      2   [2-3]   \n",
       "8366         1    21    male  25    26      1   [0-1]   \n",
       "8367         1    21    male  25    28      3   [2-3]   \n",
       "8368         1    21    male  25    26      1   [0-1]   \n",
       "8369         1    21    male  25    22      3   [2-3]   \n",
       "8370         1    21    male  25    27      2   [2-3]   \n",
       "8371         1    21    male  25    25      0   [0-1]   \n",
       "8372         1    21    male  25    24      1   [0-1]   \n",
       "8373         1    21    male  25    26      1   [0-1]   \n",
       "8374         1    21    male  25    24      1   [0-1]   \n",
       "8375         1    21    male  25    29      4   [4-6]   \n",
       "8376         1    21    male  25    22      3   [2-3]   \n",
       "8377         1    21    male  25    22      3   [2-3]   \n",
       "\n",
       "                                         race  \\\n",
       "0     'Asian/Pacific Islander/Asian-American'   \n",
       "1     'Asian/Pacific Islander/Asian-American'   \n",
       "2     'Asian/Pacific Islander/Asian-American'   \n",
       "3     'Asian/Pacific Islander/Asian-American'   \n",
       "4     'Asian/Pacific Islander/Asian-American'   \n",
       "5     'Asian/Pacific Islander/Asian-American'   \n",
       "6     'Asian/Pacific Islander/Asian-American'   \n",
       "7     'Asian/Pacific Islander/Asian-American'   \n",
       "8     'Asian/Pacific Islander/Asian-American'   \n",
       "9     'Asian/Pacific Islander/Asian-American'   \n",
       "10                European/Caucasian-American   \n",
       "11                European/Caucasian-American   \n",
       "12                European/Caucasian-American   \n",
       "13                European/Caucasian-American   \n",
       "14                European/Caucasian-American   \n",
       "15                European/Caucasian-American   \n",
       "16                European/Caucasian-American   \n",
       "17                European/Caucasian-American   \n",
       "18                European/Caucasian-American   \n",
       "19                European/Caucasian-American   \n",
       "20                European/Caucasian-American   \n",
       "21                European/Caucasian-American   \n",
       "22                European/Caucasian-American   \n",
       "23                European/Caucasian-American   \n",
       "24                European/Caucasian-American   \n",
       "25                European/Caucasian-American   \n",
       "26                European/Caucasian-American   \n",
       "27                European/Caucasian-American   \n",
       "28                European/Caucasian-American   \n",
       "29                European/Caucasian-American   \n",
       "...                                       ...   \n",
       "8348                 'Black/African American'   \n",
       "8349                 'Black/African American'   \n",
       "8350                 'Black/African American'   \n",
       "8351                 'Black/African American'   \n",
       "8352                 'Black/African American'   \n",
       "8353                 'Black/African American'   \n",
       "8354                 'Black/African American'   \n",
       "8355                 'Black/African American'   \n",
       "8356              European/Caucasian-American   \n",
       "8357              European/Caucasian-American   \n",
       "8358              European/Caucasian-American   \n",
       "8359              European/Caucasian-American   \n",
       "8360              European/Caucasian-American   \n",
       "8361              European/Caucasian-American   \n",
       "8362              European/Caucasian-American   \n",
       "8363              European/Caucasian-American   \n",
       "8364              European/Caucasian-American   \n",
       "8365              European/Caucasian-American   \n",
       "8366              European/Caucasian-American   \n",
       "8367              European/Caucasian-American   \n",
       "8368              European/Caucasian-American   \n",
       "8369              European/Caucasian-American   \n",
       "8370              European/Caucasian-American   \n",
       "8371              European/Caucasian-American   \n",
       "8372              European/Caucasian-American   \n",
       "8373              European/Caucasian-American   \n",
       "8374              European/Caucasian-American   \n",
       "8375              European/Caucasian-American   \n",
       "8376              European/Caucasian-American   \n",
       "8377              European/Caucasian-American   \n",
       "\n",
       "                                       race_o  samerace  ...   \\\n",
       "0                 European/Caucasian-American         0  ...    \n",
       "1                 European/Caucasian-American         0  ...    \n",
       "2     'Asian/Pacific Islander/Asian-American'         1  ...    \n",
       "3                 European/Caucasian-American         0  ...    \n",
       "4                  'Latino/Hispanic American'         0  ...    \n",
       "5                 European/Caucasian-American         0  ...    \n",
       "6                 European/Caucasian-American         0  ...    \n",
       "7                 European/Caucasian-American         0  ...    \n",
       "8                 European/Caucasian-American         0  ...    \n",
       "9                 European/Caucasian-American         0  ...    \n",
       "10                European/Caucasian-American         1  ...    \n",
       "11                European/Caucasian-American         1  ...    \n",
       "12    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "13                European/Caucasian-American         1  ...    \n",
       "14                 'Latino/Hispanic American'         0  ...    \n",
       "15                European/Caucasian-American         1  ...    \n",
       "16                European/Caucasian-American         1  ...    \n",
       "17                European/Caucasian-American         1  ...    \n",
       "18                European/Caucasian-American         1  ...    \n",
       "19                European/Caucasian-American         1  ...    \n",
       "20                European/Caucasian-American         1  ...    \n",
       "21                European/Caucasian-American         1  ...    \n",
       "22    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "23                European/Caucasian-American         1  ...    \n",
       "24                 'Latino/Hispanic American'         0  ...    \n",
       "25                European/Caucasian-American         1  ...    \n",
       "26                European/Caucasian-American         1  ...    \n",
       "27                European/Caucasian-American         1  ...    \n",
       "28                European/Caucasian-American         1  ...    \n",
       "29                European/Caucasian-American         1  ...    \n",
       "...                                       ...       ...  ...    \n",
       "8348  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8349  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8350              European/Caucasian-American         0  ...    \n",
       "8351               'Latino/Hispanic American'         0  ...    \n",
       "8352                                    Other         0  ...    \n",
       "8353               'Latino/Hispanic American'         0  ...    \n",
       "8354  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8355  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8356  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8357               'Latino/Hispanic American'         0  ...    \n",
       "8358  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8359              European/Caucasian-American         1  ...    \n",
       "8360              European/Caucasian-American         1  ...    \n",
       "8361              European/Caucasian-American         1  ...    \n",
       "8362              European/Caucasian-American         1  ...    \n",
       "8363  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8364               'Latino/Hispanic American'         0  ...    \n",
       "8365              European/Caucasian-American         1  ...    \n",
       "8366              European/Caucasian-American         1  ...    \n",
       "8367                                    Other         0  ...    \n",
       "8368              European/Caucasian-American         1  ...    \n",
       "8369              European/Caucasian-American         1  ...    \n",
       "8370  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8371  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8372              European/Caucasian-American         1  ...    \n",
       "8373               'Latino/Hispanic American'         0  ...    \n",
       "8374                                    Other         0  ...    \n",
       "8375               'Latino/Hispanic American'         0  ...    \n",
       "8376  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8377  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "\n",
       "     d_expected_num_interested_in_me d_expected_num_matches like  \\\n",
       "0                              [0-3]                  [3-5]    7   \n",
       "1                              [0-3]                  [3-5]    7   \n",
       "2                              [0-3]                  [3-5]    7   \n",
       "3                              [0-3]                  [3-5]    7   \n",
       "4                              [0-3]                  [3-5]    6   \n",
       "5                              [0-3]                  [3-5]    6   \n",
       "6                              [0-3]                  [3-5]    6   \n",
       "7                              [0-3]                  [3-5]    6   \n",
       "8                              [0-3]                  [3-5]    7   \n",
       "9                              [0-3]                  [3-5]    6   \n",
       "10                             [4-9]                  [3-5]    6   \n",
       "11                             [4-9]                  [3-5]    7   \n",
       "12                             [4-9]                  [3-5]    6   \n",
       "13                             [4-9]                  [3-5]    7   \n",
       "14                             [4-9]                  [3-5]    8   \n",
       "15                             [4-9]                  [3-5]    6   \n",
       "16                             [4-9]                  [3-5]    8   \n",
       "17                             [4-9]                  [3-5]    5   \n",
       "18                             [4-9]                  [3-5]    5   \n",
       "19                             [4-9]                  [3-5]    8   \n",
       "20                             [0-3]                  [0-2]    8   \n",
       "21                             [0-3]                  [0-2]    8   \n",
       "22                             [0-3]                  [0-2]    8   \n",
       "23                             [0-3]                  [0-2]    8   \n",
       "24                             [0-3]                  [0-2]    9   \n",
       "25                             [0-3]                  [0-2]    8   \n",
       "26                             [0-3]                  [0-2]    8   \n",
       "27                             [0-3]                  [0-2]    8   \n",
       "28                             [0-3]                  [0-2]    9   \n",
       "29                             [0-3]                  [0-2]    8   \n",
       "...                              ...                    ...  ...   \n",
       "8348                           [0-3]                  [3-5]    8   \n",
       "8349                           [0-3]                  [3-5]    7   \n",
       "8350                           [0-3]                  [3-5]    6   \n",
       "8351                           [0-3]                  [3-5]    8   \n",
       "8352                           [0-3]                  [3-5]    6   \n",
       "8353                           [0-3]                  [3-5]    9   \n",
       "8354                           [0-3]                  [3-5]    8   \n",
       "8355                           [0-3]                  [3-5]    7   \n",
       "8356                           [0-3]                  [3-5]    8   \n",
       "8357                           [0-3]                  [3-5]    9   \n",
       "8358                           [0-3]                  [3-5]    4   \n",
       "8359                           [0-3]                  [3-5]    ?   \n",
       "8360                           [0-3]                  [3-5]    9   \n",
       "8361                           [0-3]                  [3-5]    6   \n",
       "8362                           [0-3]                  [3-5]    8   \n",
       "8363                           [0-3]                  [3-5]    8   \n",
       "8364                           [0-3]                  [3-5]    7   \n",
       "8365                           [0-3]                  [3-5]    6   \n",
       "8366                           [0-3]                  [3-5]    6   \n",
       "8367                           [0-3]                  [3-5]    5   \n",
       "8368                           [0-3]                  [3-5]    4   \n",
       "8369                           [0-3]                  [3-5]    6   \n",
       "8370                           [0-3]                  [3-5]    6   \n",
       "8371                           [0-3]                  [3-5]    7   \n",
       "8372                           [0-3]                  [3-5]    4   \n",
       "8373                           [0-3]                  [3-5]    2   \n",
       "8374                           [0-3]                  [3-5]    4   \n",
       "8375                           [0-3]                  [3-5]    6   \n",
       "8376                           [0-3]                  [3-5]    5   \n",
       "8377                           [0-3]                  [3-5]    4   \n",
       "\n",
       "     guess_prob_liked  d_like d_guess_prob_liked met decision decision_o match  \n",
       "0                   6   [6-8]              [5-6]   0        1          0     0  \n",
       "1                   5   [6-8]              [5-6]   1        1          0     0  \n",
       "2                   ?   [6-8]              [0-4]   1        1          1     1  \n",
       "3                   6   [6-8]              [5-6]   0        1          1     1  \n",
       "4                   6   [6-8]              [5-6]   0        1          1     1  \n",
       "5                   5   [6-8]              [5-6]   0        0          1     0  \n",
       "6                   5   [6-8]              [5-6]   0        1          0     0  \n",
       "7                   7   [6-8]             [7-10]   ?        0          0     0  \n",
       "8                   7   [6-8]             [7-10]   0        1          1     1  \n",
       "9                   6   [6-8]              [5-6]   0        1          0     0  \n",
       "10                  4   [6-8]              [0-4]   0        0          0     0  \n",
       "11                  3   [6-8]              [0-4]   0        0          0     0  \n",
       "12                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "13                  8   [6-8]             [7-10]   0        1          1     1  \n",
       "14                  6   [6-8]              [5-6]   1        0          1     0  \n",
       "15                  5   [6-8]              [5-6]   0        0          1     0  \n",
       "16                  7   [6-8]             [7-10]   0        1          0     0  \n",
       "17                  6   [0-5]              [5-6]   0        0          1     0  \n",
       "18                  6   [0-5]              [5-6]   0        1          1     1  \n",
       "19                  7   [6-8]             [7-10]   0        1          0     0  \n",
       "20                  7   [6-8]             [7-10]   1        0          0     0  \n",
       "21                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "22                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "23                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "24                  ?  [9-10]              [0-4]   0        0          1     0  \n",
       "25                  ?   [6-8]              [0-4]   0        0          1     0  \n",
       "26                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "27                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "28                  7  [9-10]             [7-10]   0        0          1     0  \n",
       "29                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "...               ...     ...                ...  ..      ...        ...   ...  \n",
       "8348                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8349                1   [6-8]              [0-4]   0        0          1     0  \n",
       "8350                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8351                1   [6-8]              [0-4]   1        0          1     0  \n",
       "8352                1   [6-8]              [0-4]   1        0          0     0  \n",
       "8353                1  [9-10]              [0-4]   1        0          1     0  \n",
       "8354                5   [6-8]              [5-6]   0        0          1     0  \n",
       "8355                5   [6-8]              [5-6]   0        0          0     0  \n",
       "8356                5   [6-8]              [5-6]   0        1          1     1  \n",
       "8357                8  [9-10]             [7-10]   0        1          1     1  \n",
       "8358                6   [0-5]              [5-6]   0        0          1     0  \n",
       "8359                ?   [0-5]              [0-4]   ?        0          0     0  \n",
       "8360                6  [9-10]              [5-6]   ?        1          1     1  \n",
       "8361                9   [6-8]             [7-10]   0        0          1     0  \n",
       "8362                7   [6-8]             [7-10]   0        1          1     1  \n",
       "8363                6   [6-8]              [5-6]   0        1          1     1  \n",
       "8364                6   [6-8]              [5-6]   0        1          0     0  \n",
       "8365                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8366                4   [6-8]              [0-4]   0        0          0     0  \n",
       "8367                5   [0-5]              [5-6]   0        0          0     0  \n",
       "8368                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8369                3   [6-8]              [0-4]   0        0          1     0  \n",
       "8370                6   [6-8]              [5-6]   0        0          1     0  \n",
       "8371                6   [6-8]              [5-6]   0        1          1     1  \n",
       "8372                4   [0-5]              [0-4]   0        0          0     0  \n",
       "8373                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8374                4   [0-5]              [0-4]   0        0          0     0  \n",
       "8375                5   [6-8]              [5-6]   0        0          0     0  \n",
       "8376                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8377                5   [0-5]              [5-6]   0        0          1     0  \n",
       "\n",
       "[8378 rows x 123 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>has_null</th>\n",
       "      <th>wave</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>age_o</th>\n",
       "      <th>d_age</th>\n",
       "      <th>d_d_age</th>\n",
       "      <th>race</th>\n",
       "      <th>race_o</th>\n",
       "      <th>samerace</th>\n",
       "      <th>...</th>\n",
       "      <th>d_expected_num_interested_in_me</th>\n",
       "      <th>d_expected_num_matches</th>\n",
       "      <th>like</th>\n",
       "      <th>guess_prob_liked</th>\n",
       "      <th>d_like</th>\n",
       "      <th>d_guess_prob_liked</th>\n",
       "      <th>met</th>\n",
       "      <th>decision</th>\n",
       "      <th>decision_o</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>?</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 123 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   has_null  wave  gender age age_o  d_age d_d_age  \\\n",
       "0         0     1  female  21    27      6   [4-6]   \n",
       "1         0     1  female  21    22      1   [0-1]   \n",
       "2         1     1  female  21    22      1   [0-1]   \n",
       "3         0     1  female  21    23      2   [2-3]   \n",
       "4         0     1  female  21    24      3   [2-3]   \n",
       "\n",
       "                                      race  \\\n",
       "0  'Asian/Pacific Islander/Asian-American'   \n",
       "1  'Asian/Pacific Islander/Asian-American'   \n",
       "2  'Asian/Pacific Islander/Asian-American'   \n",
       "3  'Asian/Pacific Islander/Asian-American'   \n",
       "4  'Asian/Pacific Islander/Asian-American'   \n",
       "\n",
       "                                    race_o  samerace  ...   \\\n",
       "0              European/Caucasian-American         0  ...    \n",
       "1              European/Caucasian-American         0  ...    \n",
       "2  'Asian/Pacific Islander/Asian-American'         1  ...    \n",
       "3              European/Caucasian-American         0  ...    \n",
       "4               'Latino/Hispanic American'         0  ...    \n",
       "\n",
       "  d_expected_num_interested_in_me d_expected_num_matches like  \\\n",
       "0                           [0-3]                  [3-5]    7   \n",
       "1                           [0-3]                  [3-5]    7   \n",
       "2                           [0-3]                  [3-5]    7   \n",
       "3                           [0-3]                  [3-5]    7   \n",
       "4                           [0-3]                  [3-5]    6   \n",
       "\n",
       "  guess_prob_liked d_like d_guess_prob_liked met decision decision_o match  \n",
       "0                6  [6-8]              [5-6]   0        1          0     0  \n",
       "1                5  [6-8]              [5-6]   1        1          0     0  \n",
       "2                ?  [6-8]              [0-4]   1        1          1     1  \n",
       "3                6  [6-8]              [5-6]   0        1          1     1  \n",
       "4                6  [6-8]              [5-6]   0        1          1     1  \n",
       "\n",
       "[5 rows x 123 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
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       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>has_null</th>\n",
       "      <th>wave</th>\n",
       "      <th>d_age</th>\n",
       "      <th>samerace</th>\n",
       "      <th>decision</th>\n",
       "      <th>decision_o</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8378.00000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.87491</td>\n",
       "      <td>11.350919</td>\n",
       "      <td>4.185605</td>\n",
       "      <td>0.395799</td>\n",
       "      <td>0.419909</td>\n",
       "      <td>0.419551</td>\n",
       "      <td>0.164717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.33084</td>\n",
       "      <td>5.995903</td>\n",
       "      <td>4.596171</td>\n",
       "      <td>0.489051</td>\n",
       "      <td>0.493573</td>\n",
       "      <td>0.493515</td>\n",
       "      <td>0.370947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>7.000000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         has_null         wave        d_age     samerace     decision  \\\n",
       "count  8378.00000  8378.000000  8378.000000  8378.000000  8378.000000   \n",
       "mean      0.87491    11.350919     4.185605     0.395799     0.419909   \n",
       "std       0.33084     5.995903     4.596171     0.489051     0.493573   \n",
       "min       0.00000     1.000000     0.000000     0.000000     0.000000   \n",
       "25%       1.00000     7.000000     1.000000     0.000000     0.000000   \n",
       "50%       1.00000    11.000000     3.000000     0.000000     0.000000   \n",
       "75%       1.00000    15.000000     5.000000     1.000000     1.000000   \n",
       "max       1.00000    21.000000    37.000000     1.000000     1.000000   \n",
       "\n",
       "        decision_o        match  \n",
       "count  8378.000000  8378.000000  \n",
       "mean      0.419551     0.164717  \n",
       "std       0.493515     0.370947  \n",
       "min       0.000000     0.000000  \n",
       "25%       0.000000     0.000000  \n",
       "50%       0.000000     0.000000  \n",
       "75%       1.000000     0.000000  \n",
       "max       1.000000     1.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8378 entries, 0 to 8377\n",
      "Columns: 123 entries, has_null to match\n",
      "dtypes: int64(7), object(116)\n",
      "memory usage: 7.9+ MB\n"
     ]
    }
   ],
   "source": [
    "d.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8378, 123)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                      Law\n",
       "1                      Law\n",
       "2                      Law\n",
       "3                      Law\n",
       "4                      Law\n",
       "5                      Law\n",
       "6                      Law\n",
       "7                      Law\n",
       "8                      Law\n",
       "9                      Law\n",
       "10                     law\n",
       "11                     law\n",
       "12                     law\n",
       "13                     law\n",
       "14                     law\n",
       "15                     law\n",
       "16                     law\n",
       "17                     law\n",
       "18                     law\n",
       "19                     law\n",
       "20               Economics\n",
       "21               Economics\n",
       "22               Economics\n",
       "23               Economics\n",
       "24               Economics\n",
       "25               Economics\n",
       "26               Economics\n",
       "27               Economics\n",
       "28               Economics\n",
       "29               Economics\n",
       "               ...        \n",
       "8348              Business\n",
       "8349              Business\n",
       "8350              Business\n",
       "8351              Business\n",
       "8352              Business\n",
       "8353              Business\n",
       "8354              Business\n",
       "8355              Business\n",
       "8356    'Climate Dynamics'\n",
       "8357    'Climate Dynamics'\n",
       "8358    'Climate Dynamics'\n",
       "8359    'Climate Dynamics'\n",
       "8360    'Climate Dynamics'\n",
       "8361    'Climate Dynamics'\n",
       "8362    'Climate Dynamics'\n",
       "8363    'Climate Dynamics'\n",
       "8364    'Climate Dynamics'\n",
       "8365    'Climate Dynamics'\n",
       "8366    'Climate Dynamics'\n",
       "8367    'Climate Dynamics'\n",
       "8368    'Climate Dynamics'\n",
       "8369    'Climate Dynamics'\n",
       "8370    'Climate Dynamics'\n",
       "8371    'Climate Dynamics'\n",
       "8372    'Climate Dynamics'\n",
       "8373    'Climate Dynamics'\n",
       "8374    'Climate Dynamics'\n",
       "8375    'Climate Dynamics'\n",
       "8376    'Climate Dynamics'\n",
       "8377    'Climate Dynamics'\n",
       "Name: field, Length: 8378, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d.field\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another way of calling a specific column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                      Law\n",
       "1                      Law\n",
       "2                      Law\n",
       "3                      Law\n",
       "4                      Law\n",
       "5                      Law\n",
       "6                      Law\n",
       "7                      Law\n",
       "8                      Law\n",
       "9                      Law\n",
       "10                     law\n",
       "11                     law\n",
       "12                     law\n",
       "13                     law\n",
       "14                     law\n",
       "15                     law\n",
       "16                     law\n",
       "17                     law\n",
       "18                     law\n",
       "19                     law\n",
       "20               Economics\n",
       "21               Economics\n",
       "22               Economics\n",
       "23               Economics\n",
       "24               Economics\n",
       "25               Economics\n",
       "26               Economics\n",
       "27               Economics\n",
       "28               Economics\n",
       "29               Economics\n",
       "               ...        \n",
       "8348              Business\n",
       "8349              Business\n",
       "8350              Business\n",
       "8351              Business\n",
       "8352              Business\n",
       "8353              Business\n",
       "8354              Business\n",
       "8355              Business\n",
       "8356    'Climate Dynamics'\n",
       "8357    'Climate Dynamics'\n",
       "8358    'Climate Dynamics'\n",
       "8359    'Climate Dynamics'\n",
       "8360    'Climate Dynamics'\n",
       "8361    'Climate Dynamics'\n",
       "8362    'Climate Dynamics'\n",
       "8363    'Climate Dynamics'\n",
       "8364    'Climate Dynamics'\n",
       "8365    'Climate Dynamics'\n",
       "8366    'Climate Dynamics'\n",
       "8367    'Climate Dynamics'\n",
       "8368    'Climate Dynamics'\n",
       "8369    'Climate Dynamics'\n",
       "8370    'Climate Dynamics'\n",
       "8371    'Climate Dynamics'\n",
       "8372    'Climate Dynamics'\n",
       "8373    'Climate Dynamics'\n",
       "8374    'Climate Dynamics'\n",
       "8375    'Climate Dynamics'\n",
       "8376    'Climate Dynamics'\n",
       "8377    'Climate Dynamics'\n",
       "Name: field, Length: 8378, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['field']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Counts of the elements of a specific column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Business                                521\n",
       "MBA                                     468\n",
       "Law                                     462\n",
       "'Social Work'                           378\n",
       "'International Affairs'                 252\n",
       "'Electrical Engineering'                164\n",
       "Psychology                              139\n",
       "law                                     123\n",
       "Finance                                 113\n",
       "business                                110\n",
       "Mathematics                              95\n",
       "Film                                     92\n",
       "Sociology                                88\n",
       "Biology                                  85\n",
       "Engineering                              81\n",
       "'Business [MBA]'                         77\n",
       "'Clinical Psychology'                    76\n",
       "Biochemistry                             70\n",
       "'Political Science'                      69\n",
       "Economics                                67\n",
       "?                                        63\n",
       "chemistry                                57\n",
       "Physics                                  56\n",
       "'Operations Research'                    56\n",
       "'School Psychology'                      56\n",
       "Education                                55\n",
       "sociology                                52\n",
       "medicine                                 52\n",
       "'Mechanical Engineering'                 51\n",
       "'Urban Planning'                         50\n",
       "                                       ... \n",
       "'Business & International Affairs'       10\n",
       "Anthropology                              9\n",
       "'American Studies'                        9\n",
       "'Philosophy [Ph.D.]'                      9\n",
       "'elementary education'                    9\n",
       "'English Education'                       9\n",
       "'Japanese Literature'                     9\n",
       "'Instructional Tech & Media'              9\n",
       "'MA in Quantitative Methods'              9\n",
       "'art education'                           9\n",
       "'Instructional Media and Technology'      9\n",
       "'SIPA / MIA'                              9\n",
       "'Arts Administration'                     9\n",
       "'Early Childhood Education'               9\n",
       "'Sociology and Education'                 9\n",
       "'Earth and Environmental Science'         9\n",
       "'Conservation biology'                    9\n",
       "biochemistry/genetics                     7\n",
       "'Biology PhD'                             7\n",
       "epidemiology                              7\n",
       "'SOA -- writing'                          6\n",
       "'Business [Finance & Marketing]'          6\n",
       "'Fundraising Management'                  6\n",
       "'biomedical informatics'                  6\n",
       "Stats                                     6\n",
       "'art history'                             6\n",
       "'math of finance'                         6\n",
       "'MFA  Poetry'                             6\n",
       "theory                                    5\n",
       "'marine geophysics'                       5\n",
       "Name: field, Length: 260, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['field'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>11</th>\n",
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       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>law</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Economics</td>\n",
       "      <td>female</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8348</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8349</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8350</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8351</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8352</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8353</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8354</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8355</th>\n",
       "      <td>Business</td>\n",
       "      <td>male</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8356</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8358</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8359</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8360</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8362</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8363</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8368</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8369</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8370</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8371</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8372</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8373</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8375</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8377</th>\n",
       "      <td>'Climate Dynamics'</td>\n",
       "      <td>male</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8378 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   field  gender                                     race  \\\n",
       "0                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "1                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "2                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "3                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "4                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "5                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "6                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "7                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "8                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "9                    Law  female  'Asian/Pacific Islander/Asian-American'   \n",
       "10                   law  female              European/Caucasian-American   \n",
       "11                   law  female              European/Caucasian-American   \n",
       "12                   law  female              European/Caucasian-American   \n",
       "13                   law  female              European/Caucasian-American   \n",
       "14                   law  female              European/Caucasian-American   \n",
       "15                   law  female              European/Caucasian-American   \n",
       "16                   law  female              European/Caucasian-American   \n",
       "17                   law  female              European/Caucasian-American   \n",
       "18                   law  female              European/Caucasian-American   \n",
       "19                   law  female              European/Caucasian-American   \n",
       "20             Economics  female              European/Caucasian-American   \n",
       "21             Economics  female              European/Caucasian-American   \n",
       "22             Economics  female              European/Caucasian-American   \n",
       "23             Economics  female              European/Caucasian-American   \n",
       "24             Economics  female              European/Caucasian-American   \n",
       "25             Economics  female              European/Caucasian-American   \n",
       "26             Economics  female              European/Caucasian-American   \n",
       "27             Economics  female              European/Caucasian-American   \n",
       "28             Economics  female              European/Caucasian-American   \n",
       "29             Economics  female              European/Caucasian-American   \n",
       "...                  ...     ...                                      ...   \n",
       "8348            Business    male                 'Black/African American'   \n",
       "8349            Business    male                 'Black/African American'   \n",
       "8350            Business    male                 'Black/African American'   \n",
       "8351            Business    male                 'Black/African American'   \n",
       "8352            Business    male                 'Black/African American'   \n",
       "8353            Business    male                 'Black/African American'   \n",
       "8354            Business    male                 'Black/African American'   \n",
       "8355            Business    male                 'Black/African American'   \n",
       "8356  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8357  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8358  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8359  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8360  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8361  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8362  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8363  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8364  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8365  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8366  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8367  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8368  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8369  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8370  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8371  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8372  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8373  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8374  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8375  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8376  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "8377  'Climate Dynamics'    male              European/Caucasian-American   \n",
       "\n",
       "                                       race_o  \n",
       "0                 European/Caucasian-American  \n",
       "1                 European/Caucasian-American  \n",
       "2     'Asian/Pacific Islander/Asian-American'  \n",
       "3                 European/Caucasian-American  \n",
       "4                  'Latino/Hispanic American'  \n",
       "5                 European/Caucasian-American  \n",
       "6                 European/Caucasian-American  \n",
       "7                 European/Caucasian-American  \n",
       "8                 European/Caucasian-American  \n",
       "9                 European/Caucasian-American  \n",
       "10                European/Caucasian-American  \n",
       "11                European/Caucasian-American  \n",
       "12    'Asian/Pacific Islander/Asian-American'  \n",
       "13                European/Caucasian-American  \n",
       "14                 'Latino/Hispanic American'  \n",
       "15                European/Caucasian-American  \n",
       "16                European/Caucasian-American  \n",
       "17                European/Caucasian-American  \n",
       "18                European/Caucasian-American  \n",
       "19                European/Caucasian-American  \n",
       "20                European/Caucasian-American  \n",
       "21                European/Caucasian-American  \n",
       "22    'Asian/Pacific Islander/Asian-American'  \n",
       "23                European/Caucasian-American  \n",
       "24                 'Latino/Hispanic American'  \n",
       "25                European/Caucasian-American  \n",
       "26                European/Caucasian-American  \n",
       "27                European/Caucasian-American  \n",
       "28                European/Caucasian-American  \n",
       "29                European/Caucasian-American  \n",
       "...                                       ...  \n",
       "8348  'Asian/Pacific Islander/Asian-American'  \n",
       "8349  'Asian/Pacific Islander/Asian-American'  \n",
       "8350              European/Caucasian-American  \n",
       "8351               'Latino/Hispanic American'  \n",
       "8352                                    Other  \n",
       "8353               'Latino/Hispanic American'  \n",
       "8354  'Asian/Pacific Islander/Asian-American'  \n",
       "8355  'Asian/Pacific Islander/Asian-American'  \n",
       "8356  'Asian/Pacific Islander/Asian-American'  \n",
       "8357               'Latino/Hispanic American'  \n",
       "8358  'Asian/Pacific Islander/Asian-American'  \n",
       "8359              European/Caucasian-American  \n",
       "8360              European/Caucasian-American  \n",
       "8361              European/Caucasian-American  \n",
       "8362              European/Caucasian-American  \n",
       "8363  'Asian/Pacific Islander/Asian-American'  \n",
       "8364               'Latino/Hispanic American'  \n",
       "8365              European/Caucasian-American  \n",
       "8366              European/Caucasian-American  \n",
       "8367                                    Other  \n",
       "8368              European/Caucasian-American  \n",
       "8369              European/Caucasian-American  \n",
       "8370  'Asian/Pacific Islander/Asian-American'  \n",
       "8371  'Asian/Pacific Islander/Asian-American'  \n",
       "8372              European/Caucasian-American  \n",
       "8373               'Latino/Hispanic American'  \n",
       "8374                                    Other  \n",
       "8375               'Latino/Hispanic American'  \n",
       "8376  'Asian/Pacific Islander/Asian-American'  \n",
       "8377  'Asian/Pacific Islander/Asian-American'  \n",
       "\n",
       "[8378 rows x 4 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d[['field', 'gender', 'race','race_o']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline \n",
    "np.random.seed(sum(map(ord, \"distributions\")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "unsupported operand type(s) for /: 'str' and 'int'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-14-54045f9cbaa6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdistplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0md\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'attractive_important'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#Have to change the series type to int or float(changes done further for other attributes)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mC:\\Program Files\\Anaconda3\\lib\\site-packages\\seaborn\\distributions.py\u001b[0m in \u001b[0;36mdistplot\u001b[1;34m(a, bins, hist, kde, rug, fit, hist_kws, kde_kws, rug_kws, fit_kws, color, vertical, norm_hist, axlabel, label, ax)\u001b[0m\n\u001b[0;32m    189\u001b[0m             \u001b[0mline\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    190\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 191\u001b[1;33m             \u001b[0mline\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    192\u001b[0m         \u001b[0mcolor\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_color\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    193\u001b[0m         \u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Program Files\\Anaconda3\\lib\\site-packages\\numpy\\core\\_methods.py\u001b[0m in \u001b[0;36m_mean\u001b[1;34m(a, axis, dtype, out, keepdims)\u001b[0m\n\u001b[0;32m     80\u001b[0m             \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mret\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdtype\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtype\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mret\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mrcount\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     81\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 82\u001b[1;33m         \u001b[0mret\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mret\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mrcount\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     83\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     84\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mret\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'str' and 'int'"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAD8CAYAAAB0IB+mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npCYMviQ18f+GmWq6NWLIwgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaef1dd630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(d['attractive_important']) #Have to change the series type to int or float(changes done further for other attributes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d['attractive_important']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print (type(d['attractive_important']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Imputing missing values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d_replace = d.replace('?','0.0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_replace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "d_replace.iloc[:, :].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "X = d.iloc[:, :].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 1, 'female', ..., 1, 0, 0],\n",
       "       [0, 1, 'female', ..., 1, 0, 0],\n",
       "       [1, 1, 'female', ..., 1, 1, 1],\n",
       "       ..., \n",
       "       [1, 21, 'male', ..., 0, 0, 0],\n",
       "       [1, 21, 'male', ..., 0, 1, 0],\n",
       "       [1, 21, 'male', ..., 0, 1, 0]], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Correct value to put of imputing is np.nan (Null value of NumPy package)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d_replace = d.replace('?',np.nan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>has_null</th>\n",
       "      <th>wave</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>age_o</th>\n",
       "      <th>d_age</th>\n",
       "      <th>d_d_age</th>\n",
       "      <th>race</th>\n",
       "      <th>race_o</th>\n",
       "      <th>samerace</th>\n",
       "      <th>...</th>\n",
       "      <th>d_expected_num_interested_in_me</th>\n",
       "      <th>d_expected_num_matches</th>\n",
       "      <th>like</th>\n",
       "      <th>guess_prob_liked</th>\n",
       "      <th>d_like</th>\n",
       "      <th>d_guess_prob_liked</th>\n",
       "      <th>met</th>\n",
       "      <th>decision</th>\n",
       "      <th>decision_o</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>30</td>\n",
       "      <td>9</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>28</td>\n",
       "      <td>7</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8348</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8349</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8350</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8351</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8352</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8353</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8354</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8355</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8356</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8358</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8359</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8360</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8362</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8363</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8368</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8369</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8370</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8371</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8372</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8373</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8375</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8377</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8378 rows × 123 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      has_null  wave  gender age age_o  d_age d_d_age  \\\n",
       "0            0     1  female  21    27      6   [4-6]   \n",
       "1            0     1  female  21    22      1   [0-1]   \n",
       "2            1     1  female  21    22      1   [0-1]   \n",
       "3            0     1  female  21    23      2   [2-3]   \n",
       "4            0     1  female  21    24      3   [2-3]   \n",
       "5            0     1  female  21    25      4   [4-6]   \n",
       "6            0     1  female  21    30      9  [7-37]   \n",
       "7            1     1  female  21    27      6   [4-6]   \n",
       "8            0     1  female  21    28      7  [7-37]   \n",
       "9            0     1  female  21    24      3   [2-3]   \n",
       "10           0     1  female  24    27      3   [2-3]   \n",
       "11           0     1  female  24    22      2   [2-3]   \n",
       "12           0     1  female  24    22      2   [2-3]   \n",
       "13           0     1  female  24    23      1   [0-1]   \n",
       "14           0     1  female  24    24      0   [0-1]   \n",
       "15           0     1  female  24    25      1   [0-1]   \n",
       "16           0     1  female  24    30      6   [4-6]   \n",
       "17           0     1  female  24    27      3   [2-3]   \n",
       "18           0     1  female  24    28      4   [4-6]   \n",
       "19           0     1  female  24    24      0   [0-1]   \n",
       "20           1     1  female  25    27      2   [2-3]   \n",
       "21           1     1  female  25    22      3   [2-3]   \n",
       "22           1     1  female  25    22      3   [2-3]   \n",
       "23           1     1  female  25    23      2   [2-3]   \n",
       "24           1     1  female  25    24      1   [0-1]   \n",
       "25           1     1  female  25    25      0   [0-1]   \n",
       "26           1     1  female  25    30      5   [4-6]   \n",
       "27           1     1  female  25    27      2   [2-3]   \n",
       "28           1     1  female  25    28      3   [2-3]   \n",
       "29           1     1  female  25    24      1   [0-1]   \n",
       "...        ...   ...     ...  ..   ...    ...     ...   \n",
       "8348         1    21    male  27    27      0   [0-1]   \n",
       "8349         1    21    male  27    25      2   [2-3]   \n",
       "8350         1    21    male  27    24      3   [2-3]   \n",
       "8351         1    21    male  27    26      1   [0-1]   \n",
       "8352         1    21    male  27    24      3   [2-3]   \n",
       "8353         1    21    male  27    29      2   [2-3]   \n",
       "8354         1    21    male  27    22      5   [4-6]   \n",
       "8355         1    21    male  27    22      5   [4-6]   \n",
       "8356         1    21    male  25    28      3   [2-3]   \n",
       "8357         1    21    male  25    26      1   [0-1]   \n",
       "8358         1    21    male  25    23      2   [2-3]   \n",
       "8359         1    21    male  25   NaN     25  [7-37]   \n",
       "8360         1    21    male  25    23      2   [2-3]   \n",
       "8361         1    21    male  25    23      2   [2-3]   \n",
       "8362         1    21    male  25    23      2   [2-3]   \n",
       "8363         1    21    male  25    27      2   [2-3]   \n",
       "8364         1    21    male  25    30      5   [4-6]   \n",
       "8365         1    21    male  25    23      2   [2-3]   \n",
       "8366         1    21    male  25    26      1   [0-1]   \n",
       "8367         1    21    male  25    28      3   [2-3]   \n",
       "8368         1    21    male  25    26      1   [0-1]   \n",
       "8369         1    21    male  25    22      3   [2-3]   \n",
       "8370         1    21    male  25    27      2   [2-3]   \n",
       "8371         1    21    male  25    25      0   [0-1]   \n",
       "8372         1    21    male  25    24      1   [0-1]   \n",
       "8373         1    21    male  25    26      1   [0-1]   \n",
       "8374         1    21    male  25    24      1   [0-1]   \n",
       "8375         1    21    male  25    29      4   [4-6]   \n",
       "8376         1    21    male  25    22      3   [2-3]   \n",
       "8377         1    21    male  25    22      3   [2-3]   \n",
       "\n",
       "                                         race  \\\n",
       "0     'Asian/Pacific Islander/Asian-American'   \n",
       "1     'Asian/Pacific Islander/Asian-American'   \n",
       "2     'Asian/Pacific Islander/Asian-American'   \n",
       "3     'Asian/Pacific Islander/Asian-American'   \n",
       "4     'Asian/Pacific Islander/Asian-American'   \n",
       "5     'Asian/Pacific Islander/Asian-American'   \n",
       "6     'Asian/Pacific Islander/Asian-American'   \n",
       "7     'Asian/Pacific Islander/Asian-American'   \n",
       "8     'Asian/Pacific Islander/Asian-American'   \n",
       "9     'Asian/Pacific Islander/Asian-American'   \n",
       "10                European/Caucasian-American   \n",
       "11                European/Caucasian-American   \n",
       "12                European/Caucasian-American   \n",
       "13                European/Caucasian-American   \n",
       "14                European/Caucasian-American   \n",
       "15                European/Caucasian-American   \n",
       "16                European/Caucasian-American   \n",
       "17                European/Caucasian-American   \n",
       "18                European/Caucasian-American   \n",
       "19                European/Caucasian-American   \n",
       "20                European/Caucasian-American   \n",
       "21                European/Caucasian-American   \n",
       "22                European/Caucasian-American   \n",
       "23                European/Caucasian-American   \n",
       "24                European/Caucasian-American   \n",
       "25                European/Caucasian-American   \n",
       "26                European/Caucasian-American   \n",
       "27                European/Caucasian-American   \n",
       "28                European/Caucasian-American   \n",
       "29                European/Caucasian-American   \n",
       "...                                       ...   \n",
       "8348                 'Black/African American'   \n",
       "8349                 'Black/African American'   \n",
       "8350                 'Black/African American'   \n",
       "8351                 'Black/African American'   \n",
       "8352                 'Black/African American'   \n",
       "8353                 'Black/African American'   \n",
       "8354                 'Black/African American'   \n",
       "8355                 'Black/African American'   \n",
       "8356              European/Caucasian-American   \n",
       "8357              European/Caucasian-American   \n",
       "8358              European/Caucasian-American   \n",
       "8359              European/Caucasian-American   \n",
       "8360              European/Caucasian-American   \n",
       "8361              European/Caucasian-American   \n",
       "8362              European/Caucasian-American   \n",
       "8363              European/Caucasian-American   \n",
       "8364              European/Caucasian-American   \n",
       "8365              European/Caucasian-American   \n",
       "8366              European/Caucasian-American   \n",
       "8367              European/Caucasian-American   \n",
       "8368              European/Caucasian-American   \n",
       "8369              European/Caucasian-American   \n",
       "8370              European/Caucasian-American   \n",
       "8371              European/Caucasian-American   \n",
       "8372              European/Caucasian-American   \n",
       "8373              European/Caucasian-American   \n",
       "8374              European/Caucasian-American   \n",
       "8375              European/Caucasian-American   \n",
       "8376              European/Caucasian-American   \n",
       "8377              European/Caucasian-American   \n",
       "\n",
       "                                       race_o  samerace  ...   \\\n",
       "0                 European/Caucasian-American         0  ...    \n",
       "1                 European/Caucasian-American         0  ...    \n",
       "2     'Asian/Pacific Islander/Asian-American'         1  ...    \n",
       "3                 European/Caucasian-American         0  ...    \n",
       "4                  'Latino/Hispanic American'         0  ...    \n",
       "5                 European/Caucasian-American         0  ...    \n",
       "6                 European/Caucasian-American         0  ...    \n",
       "7                 European/Caucasian-American         0  ...    \n",
       "8                 European/Caucasian-American         0  ...    \n",
       "9                 European/Caucasian-American         0  ...    \n",
       "10                European/Caucasian-American         1  ...    \n",
       "11                European/Caucasian-American         1  ...    \n",
       "12    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "13                European/Caucasian-American         1  ...    \n",
       "14                 'Latino/Hispanic American'         0  ...    \n",
       "15                European/Caucasian-American         1  ...    \n",
       "16                European/Caucasian-American         1  ...    \n",
       "17                European/Caucasian-American         1  ...    \n",
       "18                European/Caucasian-American         1  ...    \n",
       "19                European/Caucasian-American         1  ...    \n",
       "20                European/Caucasian-American         1  ...    \n",
       "21                European/Caucasian-American         1  ...    \n",
       "22    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "23                European/Caucasian-American         1  ...    \n",
       "24                 'Latino/Hispanic American'         0  ...    \n",
       "25                European/Caucasian-American         1  ...    \n",
       "26                European/Caucasian-American         1  ...    \n",
       "27                European/Caucasian-American         1  ...    \n",
       "28                European/Caucasian-American         1  ...    \n",
       "29                European/Caucasian-American         1  ...    \n",
       "...                                       ...       ...  ...    \n",
       "8348  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8349  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8350              European/Caucasian-American         0  ...    \n",
       "8351               'Latino/Hispanic American'         0  ...    \n",
       "8352                                    Other         0  ...    \n",
       "8353               'Latino/Hispanic American'         0  ...    \n",
       "8354  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8355  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8356  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8357               'Latino/Hispanic American'         0  ...    \n",
       "8358  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8359              European/Caucasian-American         1  ...    \n",
       "8360              European/Caucasian-American         1  ...    \n",
       "8361              European/Caucasian-American         1  ...    \n",
       "8362              European/Caucasian-American         1  ...    \n",
       "8363  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8364               'Latino/Hispanic American'         0  ...    \n",
       "8365              European/Caucasian-American         1  ...    \n",
       "8366              European/Caucasian-American         1  ...    \n",
       "8367                                    Other         0  ...    \n",
       "8368              European/Caucasian-American         1  ...    \n",
       "8369              European/Caucasian-American         1  ...    \n",
       "8370  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8371  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8372              European/Caucasian-American         1  ...    \n",
       "8373               'Latino/Hispanic American'         0  ...    \n",
       "8374                                    Other         0  ...    \n",
       "8375               'Latino/Hispanic American'         0  ...    \n",
       "8376  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8377  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "\n",
       "     d_expected_num_interested_in_me d_expected_num_matches like  \\\n",
       "0                              [0-3]                  [3-5]    7   \n",
       "1                              [0-3]                  [3-5]    7   \n",
       "2                              [0-3]                  [3-5]    7   \n",
       "3                              [0-3]                  [3-5]    7   \n",
       "4                              [0-3]                  [3-5]    6   \n",
       "5                              [0-3]                  [3-5]    6   \n",
       "6                              [0-3]                  [3-5]    6   \n",
       "7                              [0-3]                  [3-5]    6   \n",
       "8                              [0-3]                  [3-5]    7   \n",
       "9                              [0-3]                  [3-5]    6   \n",
       "10                             [4-9]                  [3-5]    6   \n",
       "11                             [4-9]                  [3-5]    7   \n",
       "12                             [4-9]                  [3-5]    6   \n",
       "13                             [4-9]                  [3-5]    7   \n",
       "14                             [4-9]                  [3-5]    8   \n",
       "15                             [4-9]                  [3-5]    6   \n",
       "16                             [4-9]                  [3-5]    8   \n",
       "17                             [4-9]                  [3-5]    5   \n",
       "18                             [4-9]                  [3-5]    5   \n",
       "19                             [4-9]                  [3-5]    8   \n",
       "20                             [0-3]                  [0-2]    8   \n",
       "21                             [0-3]                  [0-2]    8   \n",
       "22                             [0-3]                  [0-2]    8   \n",
       "23                             [0-3]                  [0-2]    8   \n",
       "24                             [0-3]                  [0-2]    9   \n",
       "25                             [0-3]                  [0-2]    8   \n",
       "26                             [0-3]                  [0-2]    8   \n",
       "27                             [0-3]                  [0-2]    8   \n",
       "28                             [0-3]                  [0-2]    9   \n",
       "29                             [0-3]                  [0-2]    8   \n",
       "...                              ...                    ...  ...   \n",
       "8348                           [0-3]                  [3-5]    8   \n",
       "8349                           [0-3]                  [3-5]    7   \n",
       "8350                           [0-3]                  [3-5]    6   \n",
       "8351                           [0-3]                  [3-5]    8   \n",
       "8352                           [0-3]                  [3-5]    6   \n",
       "8353                           [0-3]                  [3-5]    9   \n",
       "8354                           [0-3]                  [3-5]    8   \n",
       "8355                           [0-3]                  [3-5]    7   \n",
       "8356                           [0-3]                  [3-5]    8   \n",
       "8357                           [0-3]                  [3-5]    9   \n",
       "8358                           [0-3]                  [3-5]    4   \n",
       "8359                           [0-3]                  [3-5]  NaN   \n",
       "8360                           [0-3]                  [3-5]    9   \n",
       "8361                           [0-3]                  [3-5]    6   \n",
       "8362                           [0-3]                  [3-5]    8   \n",
       "8363                           [0-3]                  [3-5]    8   \n",
       "8364                           [0-3]                  [3-5]    7   \n",
       "8365                           [0-3]                  [3-5]    6   \n",
       "8366                           [0-3]                  [3-5]    6   \n",
       "8367                           [0-3]                  [3-5]    5   \n",
       "8368                           [0-3]                  [3-5]    4   \n",
       "8369                           [0-3]                  [3-5]    6   \n",
       "8370                           [0-3]                  [3-5]    6   \n",
       "8371                           [0-3]                  [3-5]    7   \n",
       "8372                           [0-3]                  [3-5]    4   \n",
       "8373                           [0-3]                  [3-5]    2   \n",
       "8374                           [0-3]                  [3-5]    4   \n",
       "8375                           [0-3]                  [3-5]    6   \n",
       "8376                           [0-3]                  [3-5]    5   \n",
       "8377                           [0-3]                  [3-5]    4   \n",
       "\n",
       "     guess_prob_liked  d_like d_guess_prob_liked  met decision decision_o  \\\n",
       "0                   6   [6-8]              [5-6]    0        1          0   \n",
       "1                   5   [6-8]              [5-6]    1        1          0   \n",
       "2                 NaN   [6-8]              [0-4]    1        1          1   \n",
       "3                   6   [6-8]              [5-6]    0        1          1   \n",
       "4                   6   [6-8]              [5-6]    0        1          1   \n",
       "5                   5   [6-8]              [5-6]    0        0          1   \n",
       "6                   5   [6-8]              [5-6]    0        1          0   \n",
       "7                   7   [6-8]             [7-10]  NaN        0          0   \n",
       "8                   7   [6-8]             [7-10]    0        1          1   \n",
       "9                   6   [6-8]              [5-6]    0        1          0   \n",
       "10                  4   [6-8]              [0-4]    0        0          0   \n",
       "11                  3   [6-8]              [0-4]    0        0          0   \n",
       "12                  7   [6-8]             [7-10]    0        0          1   \n",
       "13                  8   [6-8]             [7-10]    0        1          1   \n",
       "14                  6   [6-8]              [5-6]    1        0          1   \n",
       "15                  5   [6-8]              [5-6]    0        0          1   \n",
       "16                  7   [6-8]             [7-10]    0        1          0   \n",
       "17                  6   [0-5]              [5-6]    0        0          1   \n",
       "18                  6   [0-5]              [5-6]    0        1          1   \n",
       "19                  7   [6-8]             [7-10]    0        1          0   \n",
       "20                  7   [6-8]             [7-10]    1        0          0   \n",
       "21                  7   [6-8]             [7-10]    0        0          0   \n",
       "22                  7   [6-8]             [7-10]    0        0          1   \n",
       "23                  7   [6-8]             [7-10]    0        0          1   \n",
       "24                NaN  [9-10]              [0-4]    0        0          1   \n",
       "25                NaN   [6-8]              [0-4]    0        0          1   \n",
       "26                  7   [6-8]             [7-10]    0        0          0   \n",
       "27                  7   [6-8]             [7-10]    0        0          0   \n",
       "28                  7  [9-10]             [7-10]    0        0          1   \n",
       "29                  7   [6-8]             [7-10]    0        0          0   \n",
       "...               ...     ...                ...  ...      ...        ...   \n",
       "8348                7   [6-8]             [7-10]    0        0          1   \n",
       "8349                1   [6-8]              [0-4]    0        0          1   \n",
       "8350                7   [6-8]             [7-10]    0        0          1   \n",
       "8351                1   [6-8]              [0-4]    1        0          1   \n",
       "8352                1   [6-8]              [0-4]    1        0          0   \n",
       "8353                1  [9-10]              [0-4]    1        0          1   \n",
       "8354                5   [6-8]              [5-6]    0        0          1   \n",
       "8355                5   [6-8]              [5-6]    0        0          0   \n",
       "8356                5   [6-8]              [5-6]    0        1          1   \n",
       "8357                8  [9-10]             [7-10]    0        1          1   \n",
       "8358                6   [0-5]              [5-6]    0        0          1   \n",
       "8359              NaN   [0-5]              [0-4]  NaN        0          0   \n",
       "8360                6  [9-10]              [5-6]  NaN        1          1   \n",
       "8361                9   [6-8]             [7-10]    0        0          1   \n",
       "8362                7   [6-8]             [7-10]    0        1          1   \n",
       "8363                6   [6-8]              [5-6]    0        1          1   \n",
       "8364                6   [6-8]              [5-6]    0        1          0   \n",
       "8365                7   [6-8]             [7-10]    0        0          1   \n",
       "8366                4   [6-8]              [0-4]    0        0          0   \n",
       "8367                5   [0-5]              [5-6]    0        0          0   \n",
       "8368                5   [0-5]              [5-6]    0        0          1   \n",
       "8369                3   [6-8]              [0-4]    0        0          1   \n",
       "8370                6   [6-8]              [5-6]    0        0          1   \n",
       "8371                6   [6-8]              [5-6]    0        1          1   \n",
       "8372                4   [0-5]              [0-4]    0        0          0   \n",
       "8373                5   [0-5]              [5-6]    0        0          1   \n",
       "8374                4   [0-5]              [0-4]    0        0          0   \n",
       "8375                5   [6-8]              [5-6]    0        0          0   \n",
       "8376                5   [0-5]              [5-6]    0        0          1   \n",
       "8377                5   [0-5]              [5-6]    0        0          1   \n",
       "\n",
       "     match  \n",
       "0        0  \n",
       "1        0  \n",
       "2        1  \n",
       "3        1  \n",
       "4        1  \n",
       "5        0  \n",
       "6        0  \n",
       "7        0  \n",
       "8        1  \n",
       "9        0  \n",
       "10       0  \n",
       "11       0  \n",
       "12       0  \n",
       "13       1  \n",
       "14       0  \n",
       "15       0  \n",
       "16       0  \n",
       "17       0  \n",
       "18       1  \n",
       "19       0  \n",
       "20       0  \n",
       "21       0  \n",
       "22       0  \n",
       "23       0  \n",
       "24       0  \n",
       "25       0  \n",
       "26       0  \n",
       "27       0  \n",
       "28       0  \n",
       "29       0  \n",
       "...    ...  \n",
       "8348     0  \n",
       "8349     0  \n",
       "8350     0  \n",
       "8351     0  \n",
       "8352     0  \n",
       "8353     0  \n",
       "8354     0  \n",
       "8355     0  \n",
       "8356     1  \n",
       "8357     1  \n",
       "8358     0  \n",
       "8359     0  \n",
       "8360     1  \n",
       "8361     0  \n",
       "8362     1  \n",
       "8363     1  \n",
       "8364     0  \n",
       "8365     0  \n",
       "8366     0  \n",
       "8367     0  \n",
       "8368     0  \n",
       "8369     0  \n",
       "8370     0  \n",
       "8371     1  \n",
       "8372     0  \n",
       "8373     0  \n",
       "8374     0  \n",
       "8375     0  \n",
       "8376     0  \n",
       "8377     0  \n",
       "\n",
       "[8378 rows x 123 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d_replace"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Code for imputing missing value:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>has_null</th>\n",
       "      <th>wave</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>age_o</th>\n",
       "      <th>d_age</th>\n",
       "      <th>d_d_age</th>\n",
       "      <th>race</th>\n",
       "      <th>race_o</th>\n",
       "      <th>samerace</th>\n",
       "      <th>...</th>\n",
       "      <th>d_expected_num_interested_in_me</th>\n",
       "      <th>d_expected_num_matches</th>\n",
       "      <th>like</th>\n",
       "      <th>guess_prob_liked</th>\n",
       "      <th>d_like</th>\n",
       "      <th>d_guess_prob_liked</th>\n",
       "      <th>met</th>\n",
       "      <th>decision</th>\n",
       "      <th>decision_o</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>25</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>30</td>\n",
       "      <td>9</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>27</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>28</td>\n",
       "      <td>7</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8348</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8349</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8350</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8351</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8352</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8353</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8354</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8355</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8356</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8358</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8359</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8360</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8362</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8363</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8368</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8369</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8370</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8371</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8372</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8373</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8375</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8377</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8378 rows × 123 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      has_null  wave  gender age age_o  d_age d_d_age  \\\n",
       "0            0     1  female  21    27      6   [4-6]   \n",
       "1            0     1  female  21    22      1   [0-1]   \n",
       "2            1     1  female  21    22      1   [0-1]   \n",
       "3            0     1  female  21    23      2   [2-3]   \n",
       "4            0     1  female  21    24      3   [2-3]   \n",
       "5            0     1  female  21    25      4   [4-6]   \n",
       "6            0     1  female  21    30      9  [7-37]   \n",
       "7            1     1  female  21    27      6   [4-6]   \n",
       "8            0     1  female  21    28      7  [7-37]   \n",
       "9            0     1  female  21    24      3   [2-3]   \n",
       "10           0     1  female  24    27      3   [2-3]   \n",
       "11           0     1  female  24    22      2   [2-3]   \n",
       "12           0     1  female  24    22      2   [2-3]   \n",
       "13           0     1  female  24    23      1   [0-1]   \n",
       "14           0     1  female  24    24      0   [0-1]   \n",
       "15           0     1  female  24    25      1   [0-1]   \n",
       "16           0     1  female  24    30      6   [4-6]   \n",
       "17           0     1  female  24    27      3   [2-3]   \n",
       "18           0     1  female  24    28      4   [4-6]   \n",
       "19           0     1  female  24    24      0   [0-1]   \n",
       "20           1     1  female  25    27      2   [2-3]   \n",
       "21           1     1  female  25    22      3   [2-3]   \n",
       "22           1     1  female  25    22      3   [2-3]   \n",
       "23           1     1  female  25    23      2   [2-3]   \n",
       "24           1     1  female  25    24      1   [0-1]   \n",
       "25           1     1  female  25    25      0   [0-1]   \n",
       "26           1     1  female  25    30      5   [4-6]   \n",
       "27           1     1  female  25    27      2   [2-3]   \n",
       "28           1     1  female  25    28      3   [2-3]   \n",
       "29           1     1  female  25    24      1   [0-1]   \n",
       "...        ...   ...     ...  ..   ...    ...     ...   \n",
       "8348         1    21    male  27    27      0   [0-1]   \n",
       "8349         1    21    male  27    25      2   [2-3]   \n",
       "8350         1    21    male  27    24      3   [2-3]   \n",
       "8351         1    21    male  27    26      1   [0-1]   \n",
       "8352         1    21    male  27    24      3   [2-3]   \n",
       "8353         1    21    male  27    29      2   [2-3]   \n",
       "8354         1    21    male  27    22      5   [4-6]   \n",
       "8355         1    21    male  27    22      5   [4-6]   \n",
       "8356         1    21    male  25    28      3   [2-3]   \n",
       "8357         1    21    male  25    26      1   [0-1]   \n",
       "8358         1    21    male  25    23      2   [2-3]   \n",
       "8359         1    21    male  25    27     25  [7-37]   \n",
       "8360         1    21    male  25    23      2   [2-3]   \n",
       "8361         1    21    male  25    23      2   [2-3]   \n",
       "8362         1    21    male  25    23      2   [2-3]   \n",
       "8363         1    21    male  25    27      2   [2-3]   \n",
       "8364         1    21    male  25    30      5   [4-6]   \n",
       "8365         1    21    male  25    23      2   [2-3]   \n",
       "8366         1    21    male  25    26      1   [0-1]   \n",
       "8367         1    21    male  25    28      3   [2-3]   \n",
       "8368         1    21    male  25    26      1   [0-1]   \n",
       "8369         1    21    male  25    22      3   [2-3]   \n",
       "8370         1    21    male  25    27      2   [2-3]   \n",
       "8371         1    21    male  25    25      0   [0-1]   \n",
       "8372         1    21    male  25    24      1   [0-1]   \n",
       "8373         1    21    male  25    26      1   [0-1]   \n",
       "8374         1    21    male  25    24      1   [0-1]   \n",
       "8375         1    21    male  25    29      4   [4-6]   \n",
       "8376         1    21    male  25    22      3   [2-3]   \n",
       "8377         1    21    male  25    22      3   [2-3]   \n",
       "\n",
       "                                         race  \\\n",
       "0     'Asian/Pacific Islander/Asian-American'   \n",
       "1     'Asian/Pacific Islander/Asian-American'   \n",
       "2     'Asian/Pacific Islander/Asian-American'   \n",
       "3     'Asian/Pacific Islander/Asian-American'   \n",
       "4     'Asian/Pacific Islander/Asian-American'   \n",
       "5     'Asian/Pacific Islander/Asian-American'   \n",
       "6     'Asian/Pacific Islander/Asian-American'   \n",
       "7     'Asian/Pacific Islander/Asian-American'   \n",
       "8     'Asian/Pacific Islander/Asian-American'   \n",
       "9     'Asian/Pacific Islander/Asian-American'   \n",
       "10                European/Caucasian-American   \n",
       "11                European/Caucasian-American   \n",
       "12                European/Caucasian-American   \n",
       "13                European/Caucasian-American   \n",
       "14                European/Caucasian-American   \n",
       "15                European/Caucasian-American   \n",
       "16                European/Caucasian-American   \n",
       "17                European/Caucasian-American   \n",
       "18                European/Caucasian-American   \n",
       "19                European/Caucasian-American   \n",
       "20                European/Caucasian-American   \n",
       "21                European/Caucasian-American   \n",
       "22                European/Caucasian-American   \n",
       "23                European/Caucasian-American   \n",
       "24                European/Caucasian-American   \n",
       "25                European/Caucasian-American   \n",
       "26                European/Caucasian-American   \n",
       "27                European/Caucasian-American   \n",
       "28                European/Caucasian-American   \n",
       "29                European/Caucasian-American   \n",
       "...                                       ...   \n",
       "8348                 'Black/African American'   \n",
       "8349                 'Black/African American'   \n",
       "8350                 'Black/African American'   \n",
       "8351                 'Black/African American'   \n",
       "8352                 'Black/African American'   \n",
       "8353                 'Black/African American'   \n",
       "8354                 'Black/African American'   \n",
       "8355                 'Black/African American'   \n",
       "8356              European/Caucasian-American   \n",
       "8357              European/Caucasian-American   \n",
       "8358              European/Caucasian-American   \n",
       "8359              European/Caucasian-American   \n",
       "8360              European/Caucasian-American   \n",
       "8361              European/Caucasian-American   \n",
       "8362              European/Caucasian-American   \n",
       "8363              European/Caucasian-American   \n",
       "8364              European/Caucasian-American   \n",
       "8365              European/Caucasian-American   \n",
       "8366              European/Caucasian-American   \n",
       "8367              European/Caucasian-American   \n",
       "8368              European/Caucasian-American   \n",
       "8369              European/Caucasian-American   \n",
       "8370              European/Caucasian-American   \n",
       "8371              European/Caucasian-American   \n",
       "8372              European/Caucasian-American   \n",
       "8373              European/Caucasian-American   \n",
       "8374              European/Caucasian-American   \n",
       "8375              European/Caucasian-American   \n",
       "8376              European/Caucasian-American   \n",
       "8377              European/Caucasian-American   \n",
       "\n",
       "                                       race_o  samerace  ...   \\\n",
       "0                 European/Caucasian-American         0  ...    \n",
       "1                 European/Caucasian-American         0  ...    \n",
       "2     'Asian/Pacific Islander/Asian-American'         1  ...    \n",
       "3                 European/Caucasian-American         0  ...    \n",
       "4                  'Latino/Hispanic American'         0  ...    \n",
       "5                 European/Caucasian-American         0  ...    \n",
       "6                 European/Caucasian-American         0  ...    \n",
       "7                 European/Caucasian-American         0  ...    \n",
       "8                 European/Caucasian-American         0  ...    \n",
       "9                 European/Caucasian-American         0  ...    \n",
       "10                European/Caucasian-American         1  ...    \n",
       "11                European/Caucasian-American         1  ...    \n",
       "12    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "13                European/Caucasian-American         1  ...    \n",
       "14                 'Latino/Hispanic American'         0  ...    \n",
       "15                European/Caucasian-American         1  ...    \n",
       "16                European/Caucasian-American         1  ...    \n",
       "17                European/Caucasian-American         1  ...    \n",
       "18                European/Caucasian-American         1  ...    \n",
       "19                European/Caucasian-American         1  ...    \n",
       "20                European/Caucasian-American         1  ...    \n",
       "21                European/Caucasian-American         1  ...    \n",
       "22    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "23                European/Caucasian-American         1  ...    \n",
       "24                 'Latino/Hispanic American'         0  ...    \n",
       "25                European/Caucasian-American         1  ...    \n",
       "26                European/Caucasian-American         1  ...    \n",
       "27                European/Caucasian-American         1  ...    \n",
       "28                European/Caucasian-American         1  ...    \n",
       "29                European/Caucasian-American         1  ...    \n",
       "...                                       ...       ...  ...    \n",
       "8348  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8349  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8350              European/Caucasian-American         0  ...    \n",
       "8351               'Latino/Hispanic American'         0  ...    \n",
       "8352                                    Other         0  ...    \n",
       "8353               'Latino/Hispanic American'         0  ...    \n",
       "8354  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8355  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8356  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8357               'Latino/Hispanic American'         0  ...    \n",
       "8358  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8359              European/Caucasian-American         1  ...    \n",
       "8360              European/Caucasian-American         1  ...    \n",
       "8361              European/Caucasian-American         1  ...    \n",
       "8362              European/Caucasian-American         1  ...    \n",
       "8363  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8364               'Latino/Hispanic American'         0  ...    \n",
       "8365              European/Caucasian-American         1  ...    \n",
       "8366              European/Caucasian-American         1  ...    \n",
       "8367                                    Other         0  ...    \n",
       "8368              European/Caucasian-American         1  ...    \n",
       "8369              European/Caucasian-American         1  ...    \n",
       "8370  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8371  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8372              European/Caucasian-American         1  ...    \n",
       "8373               'Latino/Hispanic American'         0  ...    \n",
       "8374                                    Other         0  ...    \n",
       "8375               'Latino/Hispanic American'         0  ...    \n",
       "8376  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8377  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "\n",
       "     d_expected_num_interested_in_me d_expected_num_matches like  \\\n",
       "0                              [0-3]                  [3-5]    7   \n",
       "1                              [0-3]                  [3-5]    7   \n",
       "2                              [0-3]                  [3-5]    7   \n",
       "3                              [0-3]                  [3-5]    7   \n",
       "4                              [0-3]                  [3-5]    6   \n",
       "5                              [0-3]                  [3-5]    6   \n",
       "6                              [0-3]                  [3-5]    6   \n",
       "7                              [0-3]                  [3-5]    6   \n",
       "8                              [0-3]                  [3-5]    7   \n",
       "9                              [0-3]                  [3-5]    6   \n",
       "10                             [4-9]                  [3-5]    6   \n",
       "11                             [4-9]                  [3-5]    7   \n",
       "12                             [4-9]                  [3-5]    6   \n",
       "13                             [4-9]                  [3-5]    7   \n",
       "14                             [4-9]                  [3-5]    8   \n",
       "15                             [4-9]                  [3-5]    6   \n",
       "16                             [4-9]                  [3-5]    8   \n",
       "17                             [4-9]                  [3-5]    5   \n",
       "18                             [4-9]                  [3-5]    5   \n",
       "19                             [4-9]                  [3-5]    8   \n",
       "20                             [0-3]                  [0-2]    8   \n",
       "21                             [0-3]                  [0-2]    8   \n",
       "22                             [0-3]                  [0-2]    8   \n",
       "23                             [0-3]                  [0-2]    8   \n",
       "24                             [0-3]                  [0-2]    9   \n",
       "25                             [0-3]                  [0-2]    8   \n",
       "26                             [0-3]                  [0-2]    8   \n",
       "27                             [0-3]                  [0-2]    8   \n",
       "28                             [0-3]                  [0-2]    9   \n",
       "29                             [0-3]                  [0-2]    8   \n",
       "...                              ...                    ...  ...   \n",
       "8348                           [0-3]                  [3-5]    8   \n",
       "8349                           [0-3]                  [3-5]    7   \n",
       "8350                           [0-3]                  [3-5]    6   \n",
       "8351                           [0-3]                  [3-5]    8   \n",
       "8352                           [0-3]                  [3-5]    6   \n",
       "8353                           [0-3]                  [3-5]    9   \n",
       "8354                           [0-3]                  [3-5]    8   \n",
       "8355                           [0-3]                  [3-5]    7   \n",
       "8356                           [0-3]                  [3-5]    8   \n",
       "8357                           [0-3]                  [3-5]    9   \n",
       "8358                           [0-3]                  [3-5]    4   \n",
       "8359                           [0-3]                  [3-5]    7   \n",
       "8360                           [0-3]                  [3-5]    9   \n",
       "8361                           [0-3]                  [3-5]    6   \n",
       "8362                           [0-3]                  [3-5]    8   \n",
       "8363                           [0-3]                  [3-5]    8   \n",
       "8364                           [0-3]                  [3-5]    7   \n",
       "8365                           [0-3]                  [3-5]    6   \n",
       "8366                           [0-3]                  [3-5]    6   \n",
       "8367                           [0-3]                  [3-5]    5   \n",
       "8368                           [0-3]                  [3-5]    4   \n",
       "8369                           [0-3]                  [3-5]    6   \n",
       "8370                           [0-3]                  [3-5]    6   \n",
       "8371                           [0-3]                  [3-5]    7   \n",
       "8372                           [0-3]                  [3-5]    4   \n",
       "8373                           [0-3]                  [3-5]    2   \n",
       "8374                           [0-3]                  [3-5]    4   \n",
       "8375                           [0-3]                  [3-5]    6   \n",
       "8376                           [0-3]                  [3-5]    5   \n",
       "8377                           [0-3]                  [3-5]    4   \n",
       "\n",
       "     guess_prob_liked  d_like d_guess_prob_liked met decision decision_o match  \n",
       "0                   6   [6-8]              [5-6]   0        1          0     0  \n",
       "1                   5   [6-8]              [5-6]   1        1          0     0  \n",
       "2                   5   [6-8]              [0-4]   1        1          1     1  \n",
       "3                   6   [6-8]              [5-6]   0        1          1     1  \n",
       "4                   6   [6-8]              [5-6]   0        1          1     1  \n",
       "5                   5   [6-8]              [5-6]   0        0          1     0  \n",
       "6                   5   [6-8]              [5-6]   0        1          0     0  \n",
       "7                   7   [6-8]             [7-10]   0        0          0     0  \n",
       "8                   7   [6-8]             [7-10]   0        1          1     1  \n",
       "9                   6   [6-8]              [5-6]   0        1          0     0  \n",
       "10                  4   [6-8]              [0-4]   0        0          0     0  \n",
       "11                  3   [6-8]              [0-4]   0        0          0     0  \n",
       "12                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "13                  8   [6-8]             [7-10]   0        1          1     1  \n",
       "14                  6   [6-8]              [5-6]   1        0          1     0  \n",
       "15                  5   [6-8]              [5-6]   0        0          1     0  \n",
       "16                  7   [6-8]             [7-10]   0        1          0     0  \n",
       "17                  6   [0-5]              [5-6]   0        0          1     0  \n",
       "18                  6   [0-5]              [5-6]   0        1          1     1  \n",
       "19                  7   [6-8]             [7-10]   0        1          0     0  \n",
       "20                  7   [6-8]             [7-10]   1        0          0     0  \n",
       "21                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "22                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "23                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "24                  5  [9-10]              [0-4]   0        0          1     0  \n",
       "25                  5   [6-8]              [0-4]   0        0          1     0  \n",
       "26                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "27                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "28                  7  [9-10]             [7-10]   0        0          1     0  \n",
       "29                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "...               ...     ...                ...  ..      ...        ...   ...  \n",
       "8348                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8349                1   [6-8]              [0-4]   0        0          1     0  \n",
       "8350                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8351                1   [6-8]              [0-4]   1        0          1     0  \n",
       "8352                1   [6-8]              [0-4]   1        0          0     0  \n",
       "8353                1  [9-10]              [0-4]   1        0          1     0  \n",
       "8354                5   [6-8]              [5-6]   0        0          1     0  \n",
       "8355                5   [6-8]              [5-6]   0        0          0     0  \n",
       "8356                5   [6-8]              [5-6]   0        1          1     1  \n",
       "8357                8  [9-10]             [7-10]   0        1          1     1  \n",
       "8358                6   [0-5]              [5-6]   0        0          1     0  \n",
       "8359                5   [0-5]              [0-4]   0        0          0     0  \n",
       "8360                6  [9-10]              [5-6]   0        1          1     1  \n",
       "8361                9   [6-8]             [7-10]   0        0          1     0  \n",
       "8362                7   [6-8]             [7-10]   0        1          1     1  \n",
       "8363                6   [6-8]              [5-6]   0        1          1     1  \n",
       "8364                6   [6-8]              [5-6]   0        1          0     0  \n",
       "8365                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8366                4   [6-8]              [0-4]   0        0          0     0  \n",
       "8367                5   [0-5]              [5-6]   0        0          0     0  \n",
       "8368                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8369                3   [6-8]              [0-4]   0        0          1     0  \n",
       "8370                6   [6-8]              [5-6]   0        0          1     0  \n",
       "8371                6   [6-8]              [5-6]   0        1          1     1  \n",
       "8372                4   [0-5]              [0-4]   0        0          0     0  \n",
       "8373                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8374                4   [0-5]              [0-4]   0        0          0     0  \n",
       "8375                5   [6-8]              [5-6]   0        0          0     0  \n",
       "8376                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8377                5   [0-5]              [5-6]   0        0          1     0  \n",
       "\n",
       "[8378 rows x 123 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.base import TransformerMixin\n",
    "\n",
    "X = pd.DataFrame(d_replace)\n",
    "\n",
    "class DataFrameImputer(TransformerMixin):\n",
    "\n",
    "    def __init__(self):\n",
    "        \"\"\"Impute missing values.\n",
    "\n",
    "        Columns of dtype object are imputed with the most frequent value \n",
    "        in column.\n",
    "\n",
    "        Columns of other types are imputed with mean of column.\n",
    "\n",
    "        \"\"\"\n",
    "    def fit(self, X, y=None):\n",
    "\n",
    "        self.fill = pd.Series([X[c].value_counts().index[0]\n",
    "            if X[c].dtype == np.dtype('O') else X[c].mean() for c in X],\n",
    "            index=X.columns)\n",
    "\n",
    "        return self\n",
    "\n",
    "    def transform(self, X, y=None):\n",
    "        return X.fillna(self.fill)\n",
    "\n",
    "\n",
    "xt = DataFrameImputer().fit_transform(d_replace)\n",
    "\n",
    "xt\n",
    "\n",
    "#credits-https://stackoverflow.com/questions/25239958/impute-categorical-missing-values-in-scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>has_null</th>\n",
       "      <th>wave</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
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       "      <th>...</th>\n",
       "      <th>d_expected_num_interested_in_me</th>\n",
       "      <th>d_expected_num_matches</th>\n",
       "      <th>like</th>\n",
       "      <th>guess_prob_liked</th>\n",
       "      <th>d_like</th>\n",
       "      <th>d_guess_prob_liked</th>\n",
       "      <th>met</th>\n",
       "      <th>decision</th>\n",
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       "      <th>match</th>\n",
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       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
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       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
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       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>3</th>\n",
       "      <td>0</td>\n",
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       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
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       "      <td>[3-5]</td>\n",
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       "      <th>4</th>\n",
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       "      <td>21</td>\n",
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       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
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       "      <td>[3-5]</td>\n",
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       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
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       "      <td>0</td>\n",
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       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
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       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
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       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>3</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>6</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>27</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>28</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>24</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[4-9]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>5</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>9</td>\n",
       "      <td>7</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[0-2]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8348</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8349</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8350</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8351</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8352</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8353</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8354</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8355</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>27</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>'Black/African American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8356</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8358</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8359</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>25</td>\n",
       "      <td>[7-37]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8360</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>[9-10]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8362</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8363</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>30</td>\n",
       "      <td>5</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[7-10]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>4</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>28</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8368</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8369</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8370</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8371</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>25</td>\n",
       "      <td>0</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8372</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8373</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>Other</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8375</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>29</td>\n",
       "      <td>4</td>\n",
       "      <td>[4-6]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8377</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>male</td>\n",
       "      <td>25</td>\n",
       "      <td>22</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>[0-5]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8378 rows × 123 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      has_null  wave  gender age age_o  d_age d_d_age  \\\n",
       "0            0     1  female  21    27      6   [4-6]   \n",
       "1            0     1  female  21    22      1   [0-1]   \n",
       "2            1     1  female  21    22      1   [0-1]   \n",
       "3            0     1  female  21    23      2   [2-3]   \n",
       "4            0     1  female  21    24      3   [2-3]   \n",
       "5            0     1  female  21    25      4   [4-6]   \n",
       "6            0     1  female  21    30      9  [7-37]   \n",
       "7            1     1  female  21    27      6   [4-6]   \n",
       "8            0     1  female  21    28      7  [7-37]   \n",
       "9            0     1  female  21    24      3   [2-3]   \n",
       "10           0     1  female  24    27      3   [2-3]   \n",
       "11           0     1  female  24    22      2   [2-3]   \n",
       "12           0     1  female  24    22      2   [2-3]   \n",
       "13           0     1  female  24    23      1   [0-1]   \n",
       "14           0     1  female  24    24      0   [0-1]   \n",
       "15           0     1  female  24    25      1   [0-1]   \n",
       "16           0     1  female  24    30      6   [4-6]   \n",
       "17           0     1  female  24    27      3   [2-3]   \n",
       "18           0     1  female  24    28      4   [4-6]   \n",
       "19           0     1  female  24    24      0   [0-1]   \n",
       "20           1     1  female  25    27      2   [2-3]   \n",
       "21           1     1  female  25    22      3   [2-3]   \n",
       "22           1     1  female  25    22      3   [2-3]   \n",
       "23           1     1  female  25    23      2   [2-3]   \n",
       "24           1     1  female  25    24      1   [0-1]   \n",
       "25           1     1  female  25    25      0   [0-1]   \n",
       "26           1     1  female  25    30      5   [4-6]   \n",
       "27           1     1  female  25    27      2   [2-3]   \n",
       "28           1     1  female  25    28      3   [2-3]   \n",
       "29           1     1  female  25    24      1   [0-1]   \n",
       "...        ...   ...     ...  ..   ...    ...     ...   \n",
       "8348         1    21    male  27    27      0   [0-1]   \n",
       "8349         1    21    male  27    25      2   [2-3]   \n",
       "8350         1    21    male  27    24      3   [2-3]   \n",
       "8351         1    21    male  27    26      1   [0-1]   \n",
       "8352         1    21    male  27    24      3   [2-3]   \n",
       "8353         1    21    male  27    29      2   [2-3]   \n",
       "8354         1    21    male  27    22      5   [4-6]   \n",
       "8355         1    21    male  27    22      5   [4-6]   \n",
       "8356         1    21    male  25    28      3   [2-3]   \n",
       "8357         1    21    male  25    26      1   [0-1]   \n",
       "8358         1    21    male  25    23      2   [2-3]   \n",
       "8359         1    21    male  25    27     25  [7-37]   \n",
       "8360         1    21    male  25    23      2   [2-3]   \n",
       "8361         1    21    male  25    23      2   [2-3]   \n",
       "8362         1    21    male  25    23      2   [2-3]   \n",
       "8363         1    21    male  25    27      2   [2-3]   \n",
       "8364         1    21    male  25    30      5   [4-6]   \n",
       "8365         1    21    male  25    23      2   [2-3]   \n",
       "8366         1    21    male  25    26      1   [0-1]   \n",
       "8367         1    21    male  25    28      3   [2-3]   \n",
       "8368         1    21    male  25    26      1   [0-1]   \n",
       "8369         1    21    male  25    22      3   [2-3]   \n",
       "8370         1    21    male  25    27      2   [2-3]   \n",
       "8371         1    21    male  25    25      0   [0-1]   \n",
       "8372         1    21    male  25    24      1   [0-1]   \n",
       "8373         1    21    male  25    26      1   [0-1]   \n",
       "8374         1    21    male  25    24      1   [0-1]   \n",
       "8375         1    21    male  25    29      4   [4-6]   \n",
       "8376         1    21    male  25    22      3   [2-3]   \n",
       "8377         1    21    male  25    22      3   [2-3]   \n",
       "\n",
       "                                         race  \\\n",
       "0     'Asian/Pacific Islander/Asian-American'   \n",
       "1     'Asian/Pacific Islander/Asian-American'   \n",
       "2     'Asian/Pacific Islander/Asian-American'   \n",
       "3     'Asian/Pacific Islander/Asian-American'   \n",
       "4     'Asian/Pacific Islander/Asian-American'   \n",
       "5     'Asian/Pacific Islander/Asian-American'   \n",
       "6     'Asian/Pacific Islander/Asian-American'   \n",
       "7     'Asian/Pacific Islander/Asian-American'   \n",
       "8     'Asian/Pacific Islander/Asian-American'   \n",
       "9     'Asian/Pacific Islander/Asian-American'   \n",
       "10                European/Caucasian-American   \n",
       "11                European/Caucasian-American   \n",
       "12                European/Caucasian-American   \n",
       "13                European/Caucasian-American   \n",
       "14                European/Caucasian-American   \n",
       "15                European/Caucasian-American   \n",
       "16                European/Caucasian-American   \n",
       "17                European/Caucasian-American   \n",
       "18                European/Caucasian-American   \n",
       "19                European/Caucasian-American   \n",
       "20                European/Caucasian-American   \n",
       "21                European/Caucasian-American   \n",
       "22                European/Caucasian-American   \n",
       "23                European/Caucasian-American   \n",
       "24                European/Caucasian-American   \n",
       "25                European/Caucasian-American   \n",
       "26                European/Caucasian-American   \n",
       "27                European/Caucasian-American   \n",
       "28                European/Caucasian-American   \n",
       "29                European/Caucasian-American   \n",
       "...                                       ...   \n",
       "8348                 'Black/African American'   \n",
       "8349                 'Black/African American'   \n",
       "8350                 'Black/African American'   \n",
       "8351                 'Black/African American'   \n",
       "8352                 'Black/African American'   \n",
       "8353                 'Black/African American'   \n",
       "8354                 'Black/African American'   \n",
       "8355                 'Black/African American'   \n",
       "8356              European/Caucasian-American   \n",
       "8357              European/Caucasian-American   \n",
       "8358              European/Caucasian-American   \n",
       "8359              European/Caucasian-American   \n",
       "8360              European/Caucasian-American   \n",
       "8361              European/Caucasian-American   \n",
       "8362              European/Caucasian-American   \n",
       "8363              European/Caucasian-American   \n",
       "8364              European/Caucasian-American   \n",
       "8365              European/Caucasian-American   \n",
       "8366              European/Caucasian-American   \n",
       "8367              European/Caucasian-American   \n",
       "8368              European/Caucasian-American   \n",
       "8369              European/Caucasian-American   \n",
       "8370              European/Caucasian-American   \n",
       "8371              European/Caucasian-American   \n",
       "8372              European/Caucasian-American   \n",
       "8373              European/Caucasian-American   \n",
       "8374              European/Caucasian-American   \n",
       "8375              European/Caucasian-American   \n",
       "8376              European/Caucasian-American   \n",
       "8377              European/Caucasian-American   \n",
       "\n",
       "                                       race_o  samerace  ...   \\\n",
       "0                 European/Caucasian-American         0  ...    \n",
       "1                 European/Caucasian-American         0  ...    \n",
       "2     'Asian/Pacific Islander/Asian-American'         1  ...    \n",
       "3                 European/Caucasian-American         0  ...    \n",
       "4                  'Latino/Hispanic American'         0  ...    \n",
       "5                 European/Caucasian-American         0  ...    \n",
       "6                 European/Caucasian-American         0  ...    \n",
       "7                 European/Caucasian-American         0  ...    \n",
       "8                 European/Caucasian-American         0  ...    \n",
       "9                 European/Caucasian-American         0  ...    \n",
       "10                European/Caucasian-American         1  ...    \n",
       "11                European/Caucasian-American         1  ...    \n",
       "12    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "13                European/Caucasian-American         1  ...    \n",
       "14                 'Latino/Hispanic American'         0  ...    \n",
       "15                European/Caucasian-American         1  ...    \n",
       "16                European/Caucasian-American         1  ...    \n",
       "17                European/Caucasian-American         1  ...    \n",
       "18                European/Caucasian-American         1  ...    \n",
       "19                European/Caucasian-American         1  ...    \n",
       "20                European/Caucasian-American         1  ...    \n",
       "21                European/Caucasian-American         1  ...    \n",
       "22    'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "23                European/Caucasian-American         1  ...    \n",
       "24                 'Latino/Hispanic American'         0  ...    \n",
       "25                European/Caucasian-American         1  ...    \n",
       "26                European/Caucasian-American         1  ...    \n",
       "27                European/Caucasian-American         1  ...    \n",
       "28                European/Caucasian-American         1  ...    \n",
       "29                European/Caucasian-American         1  ...    \n",
       "...                                       ...       ...  ...    \n",
       "8348  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8349  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8350              European/Caucasian-American         0  ...    \n",
       "8351               'Latino/Hispanic American'         0  ...    \n",
       "8352                                    Other         0  ...    \n",
       "8353               'Latino/Hispanic American'         0  ...    \n",
       "8354  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8355  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8356  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8357               'Latino/Hispanic American'         0  ...    \n",
       "8358  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8359              European/Caucasian-American         1  ...    \n",
       "8360              European/Caucasian-American         1  ...    \n",
       "8361              European/Caucasian-American         1  ...    \n",
       "8362              European/Caucasian-American         1  ...    \n",
       "8363  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8364               'Latino/Hispanic American'         0  ...    \n",
       "8365              European/Caucasian-American         1  ...    \n",
       "8366              European/Caucasian-American         1  ...    \n",
       "8367                                    Other         0  ...    \n",
       "8368              European/Caucasian-American         1  ...    \n",
       "8369              European/Caucasian-American         1  ...    \n",
       "8370  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8371  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8372              European/Caucasian-American         1  ...    \n",
       "8373               'Latino/Hispanic American'         0  ...    \n",
       "8374                                    Other         0  ...    \n",
       "8375               'Latino/Hispanic American'         0  ...    \n",
       "8376  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "8377  'Asian/Pacific Islander/Asian-American'         0  ...    \n",
       "\n",
       "     d_expected_num_interested_in_me d_expected_num_matches like  \\\n",
       "0                              [0-3]                  [3-5]    7   \n",
       "1                              [0-3]                  [3-5]    7   \n",
       "2                              [0-3]                  [3-5]    7   \n",
       "3                              [0-3]                  [3-5]    7   \n",
       "4                              [0-3]                  [3-5]    6   \n",
       "5                              [0-3]                  [3-5]    6   \n",
       "6                              [0-3]                  [3-5]    6   \n",
       "7                              [0-3]                  [3-5]    6   \n",
       "8                              [0-3]                  [3-5]    7   \n",
       "9                              [0-3]                  [3-5]    6   \n",
       "10                             [4-9]                  [3-5]    6   \n",
       "11                             [4-9]                  [3-5]    7   \n",
       "12                             [4-9]                  [3-5]    6   \n",
       "13                             [4-9]                  [3-5]    7   \n",
       "14                             [4-9]                  [3-5]    8   \n",
       "15                             [4-9]                  [3-5]    6   \n",
       "16                             [4-9]                  [3-5]    8   \n",
       "17                             [4-9]                  [3-5]    5   \n",
       "18                             [4-9]                  [3-5]    5   \n",
       "19                             [4-9]                  [3-5]    8   \n",
       "20                             [0-3]                  [0-2]    8   \n",
       "21                             [0-3]                  [0-2]    8   \n",
       "22                             [0-3]                  [0-2]    8   \n",
       "23                             [0-3]                  [0-2]    8   \n",
       "24                             [0-3]                  [0-2]    9   \n",
       "25                             [0-3]                  [0-2]    8   \n",
       "26                             [0-3]                  [0-2]    8   \n",
       "27                             [0-3]                  [0-2]    8   \n",
       "28                             [0-3]                  [0-2]    9   \n",
       "29                             [0-3]                  [0-2]    8   \n",
       "...                              ...                    ...  ...   \n",
       "8348                           [0-3]                  [3-5]    8   \n",
       "8349                           [0-3]                  [3-5]    7   \n",
       "8350                           [0-3]                  [3-5]    6   \n",
       "8351                           [0-3]                  [3-5]    8   \n",
       "8352                           [0-3]                  [3-5]    6   \n",
       "8353                           [0-3]                  [3-5]    9   \n",
       "8354                           [0-3]                  [3-5]    8   \n",
       "8355                           [0-3]                  [3-5]    7   \n",
       "8356                           [0-3]                  [3-5]    8   \n",
       "8357                           [0-3]                  [3-5]    9   \n",
       "8358                           [0-3]                  [3-5]    4   \n",
       "8359                           [0-3]                  [3-5]    7   \n",
       "8360                           [0-3]                  [3-5]    9   \n",
       "8361                           [0-3]                  [3-5]    6   \n",
       "8362                           [0-3]                  [3-5]    8   \n",
       "8363                           [0-3]                  [3-5]    8   \n",
       "8364                           [0-3]                  [3-5]    7   \n",
       "8365                           [0-3]                  [3-5]    6   \n",
       "8366                           [0-3]                  [3-5]    6   \n",
       "8367                           [0-3]                  [3-5]    5   \n",
       "8368                           [0-3]                  [3-5]    4   \n",
       "8369                           [0-3]                  [3-5]    6   \n",
       "8370                           [0-3]                  [3-5]    6   \n",
       "8371                           [0-3]                  [3-5]    7   \n",
       "8372                           [0-3]                  [3-5]    4   \n",
       "8373                           [0-3]                  [3-5]    2   \n",
       "8374                           [0-3]                  [3-5]    4   \n",
       "8375                           [0-3]                  [3-5]    6   \n",
       "8376                           [0-3]                  [3-5]    5   \n",
       "8377                           [0-3]                  [3-5]    4   \n",
       "\n",
       "     guess_prob_liked  d_like d_guess_prob_liked met decision decision_o match  \n",
       "0                   6   [6-8]              [5-6]   0        1          0     0  \n",
       "1                   5   [6-8]              [5-6]   1        1          0     0  \n",
       "2                   5   [6-8]              [0-4]   1        1          1     1  \n",
       "3                   6   [6-8]              [5-6]   0        1          1     1  \n",
       "4                   6   [6-8]              [5-6]   0        1          1     1  \n",
       "5                   5   [6-8]              [5-6]   0        0          1     0  \n",
       "6                   5   [6-8]              [5-6]   0        1          0     0  \n",
       "7                   7   [6-8]             [7-10]   0        0          0     0  \n",
       "8                   7   [6-8]             [7-10]   0        1          1     1  \n",
       "9                   6   [6-8]              [5-6]   0        1          0     0  \n",
       "10                  4   [6-8]              [0-4]   0        0          0     0  \n",
       "11                  3   [6-8]              [0-4]   0        0          0     0  \n",
       "12                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "13                  8   [6-8]             [7-10]   0        1          1     1  \n",
       "14                  6   [6-8]              [5-6]   1        0          1     0  \n",
       "15                  5   [6-8]              [5-6]   0        0          1     0  \n",
       "16                  7   [6-8]             [7-10]   0        1          0     0  \n",
       "17                  6   [0-5]              [5-6]   0        0          1     0  \n",
       "18                  6   [0-5]              [5-6]   0        1          1     1  \n",
       "19                  7   [6-8]             [7-10]   0        1          0     0  \n",
       "20                  7   [6-8]             [7-10]   1        0          0     0  \n",
       "21                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "22                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "23                  7   [6-8]             [7-10]   0        0          1     0  \n",
       "24                  5  [9-10]              [0-4]   0        0          1     0  \n",
       "25                  5   [6-8]              [0-4]   0        0          1     0  \n",
       "26                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "27                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "28                  7  [9-10]             [7-10]   0        0          1     0  \n",
       "29                  7   [6-8]             [7-10]   0        0          0     0  \n",
       "...               ...     ...                ...  ..      ...        ...   ...  \n",
       "8348                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8349                1   [6-8]              [0-4]   0        0          1     0  \n",
       "8350                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8351                1   [6-8]              [0-4]   1        0          1     0  \n",
       "8352                1   [6-8]              [0-4]   1        0          0     0  \n",
       "8353                1  [9-10]              [0-4]   1        0          1     0  \n",
       "8354                5   [6-8]              [5-6]   0        0          1     0  \n",
       "8355                5   [6-8]              [5-6]   0        0          0     0  \n",
       "8356                5   [6-8]              [5-6]   0        1          1     1  \n",
       "8357                8  [9-10]             [7-10]   0        1          1     1  \n",
       "8358                6   [0-5]              [5-6]   0        0          1     0  \n",
       "8359                5   [0-5]              [0-4]   0        0          0     0  \n",
       "8360                6  [9-10]              [5-6]   0        1          1     1  \n",
       "8361                9   [6-8]             [7-10]   0        0          1     0  \n",
       "8362                7   [6-8]             [7-10]   0        1          1     1  \n",
       "8363                6   [6-8]              [5-6]   0        1          1     1  \n",
       "8364                6   [6-8]              [5-6]   0        1          0     0  \n",
       "8365                7   [6-8]             [7-10]   0        0          1     0  \n",
       "8366                4   [6-8]              [0-4]   0        0          0     0  \n",
       "8367                5   [0-5]              [5-6]   0        0          0     0  \n",
       "8368                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8369                3   [6-8]              [0-4]   0        0          1     0  \n",
       "8370                6   [6-8]              [5-6]   0        0          1     0  \n",
       "8371                6   [6-8]              [5-6]   0        1          1     1  \n",
       "8372                4   [0-5]              [0-4]   0        0          0     0  \n",
       "8373                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8374                4   [0-5]              [0-4]   0        0          0     0  \n",
       "8375                5   [6-8]              [5-6]   0        0          0     0  \n",
       "8376                5   [0-5]              [5-6]   0        0          1     0  \n",
       "8377                5   [0-5]              [5-6]   0        0          1     0  \n",
       "\n",
       "[8378 rows x 123 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt #Successfully imputed missing values!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt.isnull().values.any() #Checking for null values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt.isnull().sum().sum() #No missing values!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 8378 entries, 0 to 8377\n",
      "Columns: 123 entries, has_null to match\n",
      "dtypes: int64(7), object(116)\n",
      "memory usage: 7.9+ MB\n"
     ]
    }
   ],
   "source": [
    "xt.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>has_null</th>\n",
       "      <th>wave</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>age_o</th>\n",
       "      <th>d_age</th>\n",
       "      <th>d_d_age</th>\n",
       "      <th>race</th>\n",
       "      <th>race_o</th>\n",
       "      <th>samerace</th>\n",
       "      <th>...</th>\n",
       "      <th>d_expected_num_interested_in_me</th>\n",
       "      <th>d_expected_num_matches</th>\n",
       "      <th>like</th>\n",
       "      <th>guess_prob_liked</th>\n",
       "      <th>d_like</th>\n",
       "      <th>d_guess_prob_liked</th>\n",
       "      <th>met</th>\n",
       "      <th>decision</th>\n",
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       "    </tr>\n",
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       "      <td>[4-6]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
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       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
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       "      <td>0</td>\n",
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       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "      <td>[0-1]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[0-4]</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "      <td>2</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>European/Caucasian-American</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>21</td>\n",
       "      <td>24</td>\n",
       "      <td>3</td>\n",
       "      <td>[2-3]</td>\n",
       "      <td>'Asian/Pacific Islander/Asian-American'</td>\n",
       "      <td>'Latino/Hispanic American'</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>[0-3]</td>\n",
       "      <td>[3-5]</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>[6-8]</td>\n",
       "      <td>[5-6]</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 123 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   has_null  wave  gender age age_o  d_age d_d_age  \\\n",
       "0         0     1  female  21    27      6   [4-6]   \n",
       "1         0     1  female  21    22      1   [0-1]   \n",
       "2         1     1  female  21    22      1   [0-1]   \n",
       "3         0     1  female  21    23      2   [2-3]   \n",
       "4         0     1  female  21    24      3   [2-3]   \n",
       "\n",
       "                                      race  \\\n",
       "0  'Asian/Pacific Islander/Asian-American'   \n",
       "1  'Asian/Pacific Islander/Asian-American'   \n",
       "2  'Asian/Pacific Islander/Asian-American'   \n",
       "3  'Asian/Pacific Islander/Asian-American'   \n",
       "4  'Asian/Pacific Islander/Asian-American'   \n",
       "\n",
       "                                    race_o  samerace  ...   \\\n",
       "0              European/Caucasian-American         0  ...    \n",
       "1              European/Caucasian-American         0  ...    \n",
       "2  'Asian/Pacific Islander/Asian-American'         1  ...    \n",
       "3              European/Caucasian-American         0  ...    \n",
       "4               'Latino/Hispanic American'         0  ...    \n",
       "\n",
       "  d_expected_num_interested_in_me d_expected_num_matches like  \\\n",
       "0                           [0-3]                  [3-5]    7   \n",
       "1                           [0-3]                  [3-5]    7   \n",
       "2                           [0-3]                  [3-5]    7   \n",
       "3                           [0-3]                  [3-5]    7   \n",
       "4                           [0-3]                  [3-5]    6   \n",
       "\n",
       "  guess_prob_liked d_like d_guess_prob_liked met decision decision_o match  \n",
       "0                6  [6-8]              [5-6]   0        1          0     0  \n",
       "1                5  [6-8]              [5-6]   1        1          0     0  \n",
       "2                5  [6-8]              [0-4]   1        1          1     1  \n",
       "3                6  [6-8]              [5-6]   0        1          1     1  \n",
       "4                6  [6-8]              [5-6]   0        1          1     1  \n",
       "\n",
       "[5 rows x 123 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>has_null</th>\n",
       "      <th>wave</th>\n",
       "      <th>d_age</th>\n",
       "      <th>samerace</th>\n",
       "      <th>decision</th>\n",
       "      <th>decision_o</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8378.00000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "      <td>8378.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.87491</td>\n",
       "      <td>11.350919</td>\n",
       "      <td>4.185605</td>\n",
       "      <td>0.395799</td>\n",
       "      <td>0.419909</td>\n",
       "      <td>0.419551</td>\n",
       "      <td>0.164717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.33084</td>\n",
       "      <td>5.995903</td>\n",
       "      <td>4.596171</td>\n",
       "      <td>0.489051</td>\n",
       "      <td>0.493573</td>\n",
       "      <td>0.493515</td>\n",
       "      <td>0.370947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.00000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>7.000000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         has_null         wave        d_age     samerace     decision  \\\n",
       "count  8378.00000  8378.000000  8378.000000  8378.000000  8378.000000   \n",
       "mean      0.87491    11.350919     4.185605     0.395799     0.419909   \n",
       "std       0.33084     5.995903     4.596171     0.489051     0.493573   \n",
       "min       0.00000     1.000000     0.000000     0.000000     0.000000   \n",
       "25%       1.00000     7.000000     1.000000     0.000000     0.000000   \n",
       "50%       1.00000    11.000000     3.000000     0.000000     0.000000   \n",
       "75%       1.00000    15.000000     5.000000     1.000000     1.000000   \n",
       "max       1.00000    21.000000    37.000000     1.000000     1.000000   \n",
       "\n",
       "        decision_o        match  \n",
       "count  8378.000000  8378.000000  \n",
       "mean      0.419551     0.164717  \n",
       "std       0.493515     0.370947  \n",
       "min       0.000000     0.000000  \n",
       "25%       0.000000     0.000000  \n",
       "50%       0.000000     0.000000  \n",
       "75%       1.000000     0.000000  \n",
       "max       1.000000     1.000000  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "has_null                          0.874910\n",
       "wave                             11.350919\n",
       "age                                    inf\n",
       "age_o                                  inf\n",
       "d_age                             4.185605\n",
       "samerace                          0.395799\n",
       "importance_same_race                   inf\n",
       "importance_same_religion               inf\n",
       "attractive                             inf\n",
       "sincere                                inf\n",
       "intelligence                           inf\n",
       "funny                                  inf\n",
       "ambition                               inf\n",
       "sports                                 inf\n",
       "tvsports                               inf\n",
       "exercise                               inf\n",
       "dining                                 inf\n",
       "museums                                inf\n",
       "art                                    inf\n",
       "hiking                                 inf\n",
       "gaming                                 inf\n",
       "clubbing                               inf\n",
       "reading                                inf\n",
       "tv                                     inf\n",
       "theater                                inf\n",
       "movies                                 inf\n",
       "concerts                               inf\n",
       "music                                  inf\n",
       "shopping                               inf\n",
       "yoga                                   inf\n",
       "expected_happy_with_sd_people          inf\n",
       "expected_num_interested_in_me          inf\n",
       "met                                    inf\n",
       "decision                          0.419909\n",
       "decision_o                        0.419551\n",
       "match                             0.164717\n",
       "dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['21', '24', '25', '23', '22', '26', '27', '30', '28', '29', '34',\n",
       "       '35', '32', '39', '20', '19', '18', '37', '33', '36', '31', '42',\n",
       "       '38', '55'], dtype=object)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt.age.unique() #Finding the range of ages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7      2056\n",
       "6      1709\n",
       "5      1319\n",
       "8      1274\n",
       "4       645\n",
       "9       412\n",
       "3       396\n",
       "2       223\n",
       "10      182\n",
       "1       110\n",
       "6.5      20\n",
       "8.5       9\n",
       "0         8\n",
       "7.5       6\n",
       "4.5       3\n",
       "9.5       3\n",
       "5.5       2\n",
       "9.7       1\n",
       "Name: like, dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt['like'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    6998\n",
       "1    1380\n",
       "Name: match, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt['match'].value_counts() #Counting the total number of matches and rejects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>like</th>\n",
       "      <th>match</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8348</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8349</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8350</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8351</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8352</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8353</th>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8354</th>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8355</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8356</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8358</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8359</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8360</th>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8361</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8362</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8363</th>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8365</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8366</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8367</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8368</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8369</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8370</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8371</th>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8372</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8373</th>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8374</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8375</th>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8376</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8377</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8378 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     like  match\n",
       "0       7      0\n",
       "1       7      0\n",
       "2       7      1\n",
       "3       7      1\n",
       "4       6      1\n",
       "5       6      0\n",
       "6       6      0\n",
       "7       6      0\n",
       "8       7      1\n",
       "9       6      0\n",
       "10      6      0\n",
       "11      7      0\n",
       "12      6      0\n",
       "13      7      1\n",
       "14      8      0\n",
       "15      6      0\n",
       "16      8      0\n",
       "17      5      0\n",
       "18      5      1\n",
       "19      8      0\n",
       "20      8      0\n",
       "21      8      0\n",
       "22      8      0\n",
       "23      8      0\n",
       "24      9      0\n",
       "25      8      0\n",
       "26      8      0\n",
       "27      8      0\n",
       "28      9      0\n",
       "29      8      0\n",
       "...   ...    ...\n",
       "8348    8      0\n",
       "8349    7      0\n",
       "8350    6      0\n",
       "8351    8      0\n",
       "8352    6      0\n",
       "8353    9      0\n",
       "8354    8      0\n",
       "8355    7      0\n",
       "8356    8      1\n",
       "8357    9      1\n",
       "8358    4      0\n",
       "8359    7      0\n",
       "8360    9      1\n",
       "8361    6      0\n",
       "8362    8      1\n",
       "8363    8      1\n",
       "8364    7      0\n",
       "8365    6      0\n",
       "8366    6      0\n",
       "8367    5      0\n",
       "8368    4      0\n",
       "8369    6      0\n",
       "8370    6      0\n",
       "8371    7      1\n",
       "8372    4      0\n",
       "8373    2      0\n",
       "8374    4      0\n",
       "8375    6      0\n",
       "8376    5      0\n",
       "8377    4      0\n",
       "\n",
       "[8378 rows x 2 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt[['like', 'match']] #Countin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline \n",
    "np.random.seed(sum(map(ord, \"distributions\")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaeb84d780>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jNgP3jNWva09XXQq82C5l3QdsSLKy3RTf0GqSpClYMeCx3w38C+CxJI+02r8HPgTclWQL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\nUpf/D5maWldWj7cfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaeb861160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"match\", data=xt, palette=\"Greens_d\") #Count of matches w.r.t rejection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'xlf' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-33-2c73eebce5bb>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0msns\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mboxplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'match'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mxlf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mxt\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpalette\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"Reds_d\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;31m#Plotting the like rating with a match\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'xlf' is not defined"
     ]
    }
   ],
   "source": [
    "sns.boxplot(x='match', y=xlf, data=xt, palette=\"Reds_d\") #Plotting the like rating with a match"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "xl= np.array(xt.like)#Can't convert Series 'like' to 'int'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "xlf = xl.astype(float) #Convert the series values to float"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "sns.distplot(xlf) #Can plot this as all values are uniformly float"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "xa= np.array(xt.age)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "xaf = xa.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xaf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "xr= np.array(xt.race)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.boxplot(xaf, xt.race) #Comparision of race w.r.t ages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "European/Caucasian-American                4790\n",
       "'Asian/Pacific Islander/Asian-American'    1982\n",
       "'Latino/Hispanic American'                  664\n",
       "Other                                       522\n",
       "'Black/African American'                    420\n",
       "Name: race, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt['race'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaef761518>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0/1RVlyd5OvCNdgzArsDeVfVgG9uI9wD3VtVzWr83aOXvqqp72qrXxUl2qqoF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\nfiRJUq8YfiRJUq8YfiRJUq/8f6mnICssTlN+AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaef468b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(y=\"race\", data=xt, palette=\"Greens_d\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0a50940>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf0a156d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x=\"decision\", y=\"decision_o\", hue=\"match\", data=xt) #Match happens only when both of them decides as true"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0aa2f60>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PY6hdxwBAZr5Lc6e7SpI2A80UwwsR8WcRMbj2uhR4oaxgkqRqNFMMnwImAguBLuBw4KIy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\ni0GSVPD/AQOaRRAmjLUeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf0ab4470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x=\"decision\", y=\"decision_o\", hue=\"match\", data=xt, jitter = True) # clearer view"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Business                                     584\n",
       "MBA                                          468\n",
       "Law                                          462\n",
       "'Social Work'                                378\n",
       "'International Affairs'                      252\n",
       "'Electrical Engineering'                     164\n",
       "Psychology                                   139\n",
       "law                                          123\n",
       "Finance                                      113\n",
       "business                                     110\n",
       "Mathematics                                   95\n",
       "Film                                          92\n",
       "Sociology                                     88\n",
       "Biology                                       85\n",
       "Engineering                                   81\n",
       "'Business [MBA]'                              77\n",
       "'Clinical Psychology'                         76\n",
       "Biochemistry                                  70\n",
       "'Political Science'                           69\n",
       "Economics                                     67\n",
       "chemistry                                     57\n",
       "'School Psychology'                           56\n",
       "Physics                                       56\n",
       "'Operations Research'                         56\n",
       "Education                                     55\n",
       "medicine                                      52\n",
       "sociology                                     52\n",
       "'Mechanical Engineering'                      51\n",
       "'Urban Planning'                              50\n",
       "'Computer Science'                            48\n",
       "                                            ... \n",
       "'International Affairs - Economic Policy'     10\n",
       "'Arts Administration'                          9\n",
       "'elementary education'                         9\n",
       "'SIPA / MIA'                                   9\n",
       "'Instructional Media and Technology'           9\n",
       "'Philosophy [Ph.D.]'                           9\n",
       "'English Education'                            9\n",
       "'Conservation biology'                         9\n",
       "'Japanese Literature'                          9\n",
       "'Sociology and Education'                      9\n",
       "'Instructional Tech & Media'                   9\n",
       "Anthropology                                   9\n",
       "'art education'                                9\n",
       "'MA in Quantitative Methods'                   9\n",
       "'Early Childhood Education'                    9\n",
       "'Earth and Environmental Science'              9\n",
       "'American Studies'                             9\n",
       "biochemistry/genetics                          7\n",
       "'Biology PhD'                                  7\n",
       "epidemiology                                   7\n",
       "'Fundraising Management'                       6\n",
       "'art history'                                  6\n",
       "'math of finance'                              6\n",
       "'Business [Finance & Marketing]'               6\n",
       "'biomedical informatics'                       6\n",
       "'MFA  Poetry'                                  6\n",
       "'SOA -- writing'                               6\n",
       "Stats                                          6\n",
       "theory                                         5\n",
       "'marine geophysics'                            5\n",
       "Name: field, Length: 259, dtype: int64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xt['field'].value_counts() # Can't do categorical plotting due to excess information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0baf978>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf0afda20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=xt.age, orient=\"v\") #Age group of participating people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0a3b5f8>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7NTAwUHaMOWHkz6G3t7fkJHNDV1eXenp6yo6BaaDQ0fIWLFhQdgRgRlDoLYoVGJAezqED\nQCIodABIBIUOAImg0AEgERQ6ACSCQgeARFDoAJAICh0AEuGImL0vs2uSfjtrXwjkt1jS78sOAUzi\nTyKi7kOZZ7XQgbnKdl9EVMvOATSCUy4AkAgKHQASQaEDw3aVHQBoFOfQASARrNABIBEUOlqe7btt\n/6vtAduPl50HmC5OuaCl2W6T9G+S/krSGUlvSNoQEb8uNRgwDazQ0epWSBqIiFMR8UdJeyWtKTkT\nMC0UOlrdMkn/MWp8JpsDmg6FjlbnCeY4D4mmRKGj1Z2RdMuocYekcyVlARpCoaPVvSFpue3bbF8r\nab2kl0rOBEzLvLIDAGWKiEu2H5H0L5LaJD0TESdKjgVMC5ctAkAiOOUCAImg0AEgERQ6ACSCQgeA\nRFDoAJAICh0AEkGhA0AiKHQASMT/Ap2Us/K7FUZlAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf0b25400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(data=xt.age_o, orient=\"v\") #Age group of opposite people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0c02128>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ci7Mzm5YsAZKm+/j8s5F8/tlIy3ZSiBec3MwuhBDCLAkWQgghzJJgIYQQwiwJFkIIIcyy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\n2QsVLDJDvvwFUlw/d+Fy5i1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PdxNvfpnxCwADhgygY4uO9OzQk1Kvpy0N+vI1a2jVtGmS\nZV4eHixbvfopNZ701ZffcvDwQdw86lK/cS0W/D7PbJ1BAz7lzp3bNGham0bN6rF95zYqVnDGuWIl\nGjStzceD+1PDtWaa9kWI7E5SlCeSXVKU12rWnm2r/8DW1haA88mMTViKpCi3HElR/mwkRXnyJEX5\nC2zXumWZ3QUhRDYjl6GEEEKYJcFCCCGEWdk+WGSXMRkhsgvD36T8XWY12TpYODg4cOPGDQkYQjwn\ntNbcjorF+u6lzO6KSKNsPcBdtGhRQkNDCQ8PT1X5K7ciLdyjRxLU3Qzb1nWrjPtOcP9exmwnzj4q\nYzYE3IhM/uG+jJZRx6dlj02N9d1LOB2Ybb6oeK5YNFgopTyBHwBrYI7W+pvH1tsDvwIuwA2go9Y6\nxLhuGNATSAAGaK2Tz0SXAltbW0qWLJnq8l0H/5rWTfxnfrkmZti2+mTD2xOz0q2J6SWjjs+MPDZF\n1mGxr5xKKWvgR6A5UAHorJSq8FixnsAtrfXrwBTgW2PdCkAnoCLgCfxkbE8IIUQmsOT1iRrAGa31\nOa11LLAYaPNYmTbAAuPr5UATZUja0wZYrLWO0VqfB84Y2xNCCJEJLBksigCJR7FCjcuSLaO1jgfu\nAAVSWVcIIUQGseQF5uRSpD5+W9LTyqSmLkqp3kBv49tIpdSpx8s8r4pndgfMKwikOb+EW/r3I3nb\ntmbUlvhwsvky2UkWODbhPxyfbpbpR/Ky1vGZqv9ySwaLUCBxWtWiwOWnlAlVStkAeYCbqayL1noW\nMCsd+yyMlFJBqckXI0RmkOMz41nyMtReoLRSqqRSyg7DgHXAY2UCgG7G1+2ATdrwUEQA0EkpZa+U\nKgmUBvYghBAiU1jszEJrHa+U6g+sw3Dr7Dyt9TGl1BggSGsdAMwFflNKncFwRtHJWPeYUmopcByI\nB/pprRMs1VchhBApyzYpykX6Ukr1Nl7mE+K5I8dnxpNgIYQQwqxsnRtKCCFE+pBgkU0ppQYopU4o\npRZaqP3RSqmMy7khxFMopdyUUqmfi1f8J9k6keAL7gOgufEJeCGEeCZyZpENKaVmAqWAAKXU50qp\neUqpvUqpA0qpNsYy3ZVS/kqpVUqp80qp/kqpQcYyu5RS+Y3lehnrHlJKrVBKPZGCVSn1mlJqrVJq\nn1Jqm1KqXMbuscjqlFIllFInlVJzlFJHlVILlVJNlVLblVLBSqkaxn87jMfoDqVU2WTayZHc8S6e\nnQSLbEhr3QfDQ4yNgBwYnl+pbnw/USmVw1j0DeAtDHm3vgLuaa2rAjuBd4xlfLXW1bXWlYETGJI/\nPm4W8KHW2gX4FPjJMnsmsrnXMWSprgSUw3Bs1sNwTA0HTgINjMfoSODrZNr4nKcf7+IZyGWo7M8D\n8Eo0vuAAvGp8vVlrHQFEKKXuAKuMy49g+IMFeEMpNQ7IC+TE8NyMiVIqJ1AHWGbIAQmAvSV2RGR7\n57XWRwCUUseAjVprrZQ6ApTAkOFhgVKqNIb0P7bJtPG04/2EpTuf3UmwyP4U8KbWOkneLKVUTSAm\n0aIHid4/4NGxMR9oq7U+pJTqzpMpdqyA21rrKunbbfECMnc8jsXwBcdbKVUC2JJMG8ke7+LZyWWo\n7G8d8KEx9TtKqapprJ8L+FcpZQt0eXyl1voucF4p1d7YvlJKVX7GPguRnDxAmPF196eUedbjXTyF\nBIvsbyyG0/XDSqmjxvdp8QWwG1iP4ZpxcroAPZVSh4BjPDlviRDpYQIwXim1HUMKoeQ86/EunkKe\n4BZCCGGWnFkIIYQwS4KFEEIIsyRYCCGEMEuChRBCCLMkWAghhDBLgoUQmUQpNV8p1S6z+yFEakiw\nECKLUEpJxgWRaeTgEyIVlFJfYHj48BJwHdgH+AE/AoWAe0AvrfVJpdR84C7gChQGhmitlxufKp4G\nNAbOY0hN8bB9F2Ayhvxb14HuWut/lVJbgB1AXSAAmGTxnRUiGRIshDBDKeUKvAlUxfA3sx9DsJgF\n9NFaBxtzbf2EIRAAvIIhY2o5DB/yywFvoCzgDLwMHAfmGVOpTAPaaK3DlVIdMWQBftfYVl6tdUOL\n76gQKZBgIYR59YCVWuv7AEqpVRiymaaUbddfa/0AOK6Uetm4rAGwSGudAFxWSm0yLi+LIV38emNb\n1sC/idpakv67JETaSLAQwjyVzDJz2XYTZ1BNXD+5/DoKOKa1rv2UtqLMd1EIy5IBbiHM+wdorZRy\nMM7f0RLDGEVas+1uBToppayVUq9gmJwH4BRQSClV29iWrVKqokX2RIj/SIKFEGZorfdiGHc4BPgC\nQcAd0p5t1w8IxjC51Azgb2P7sUA74FtjWwcxXOIS4rkhWWeFSAWlVE6tdaRxDvKtQG+t9f7M7pcQ\nGUXGLIRInVlKqQoYBrYXSKAQLxo5sxBCCGGWjFkIIYQwS4KFEEIIsyRYCCGEMEuChRBCCLMkWAgh\nhDBLgoUQQgiz/g+1K2ilR/Y0MgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf0b2cb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"gender\", y=\"match\", hue=\"race\", data=xt) #Percentage of race of the participating gender got a match"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0c93198>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uPS5ffZzObcfuvdRp1pGKfi1o2OZdzl+0LinQPqA9o4ePpl2TdkyZaE1nsnbV\nWnvywFMnTnE7/DY9P+7J4sDF9vYOHzhMC78WBNQOwL+mPyeOnQCsKc2tP7dwOjXvRFOfpjSu0ZgV\nS1YAcPLsWbwbNOCDzz6jfMOG+L/9NnfuRs0P9khYeDibduzg+6FDmRv8OP3I2i1bqNeuHR0+/BAv\nPz8Gff01MxcupEaLFlRo3Jhjp04BcOXqFTp3bU/dhrWo27AWW7ZuAmKmwl+/cR1tO7a09TuM/3z0\nPtV9KlHDtzKLgq1XgX0H9Ma3QU2q1a7IiK8f5x7zrlQy1hT3np6epEuXLq4ff4LplYVKsZYuWml/\nPS9oLgH+zahQviI9jx3m8pXLZMuajd+m/kqXzl1pHtCC+/fvY3loidKGu7sH8+fPJ0OGDFy5coUK\nFSrQuLF14aXDhw8zffp0Jk6cSIsWLZg7dy5vvfUWV65cwc3NjYwZM0Zp6+rVq2zatInPPvuM7Nmz\ns3z5cjw8PDh8+DCtW7dm27ZthISEEBgYyObNm0mTJg2hoVHzZzZv3Y4dWzdTvbYvdRs05uzpU/Z9\ns6f9zpnTJ5kTspJUqVJx/fqTH1m+fv0aK5YGs2jVRkSEmzdiDs01qVeHt9s2B2DQV2OYPH0e3Tu3\nBeDCxSusDJzCwSPHadapB00b+rIg5E8OHT3O9hXzuXj5Kl41/enQMoAHDx7Q+9PhzP51LNleysLs\nBSEM+uo7JnwzDICbN24yJdAaKCwWCyeOnqDA69b0JIvnL6Z+QH28K3jTv2d/rl6+ykvZXmLm7zNp\n16UdjZo14v79+zy0RE2D4+7uzthfx5IufTquXb1GqwataBdcC4CjJ08yadQoxg4dSocPP2TBsmW0\nahxzMa1FK1ZQp0oVCubPT+aMGdm5dy+li1nT1/1z8CBbv/6azJkyUdLHh/bNm7N61ix++P13fvrj\nDwZ/Xp5PB/ej69vv8Ub5ipw5e5pW7ZqzbuVmIGoq/PUb19mP+c13I0mfPgN/Ld9g+zlZc1b17/sZ\nmTNlxmKx0Ly1P3v3/0OxIsWB2FPct2yZ+AtIabBQL4TAoLlMnvgHLi4u1PdrxMLFgXTu0AXvMuX4\nbuw3nD9/jgb1GvFq/qgrzxljGDBgAGvWrMHFxYWzZ89y8aI1HUb+/PkpXbo0YE0vfuLECQCWLVuG\nr+/jOY+1a9fi5eWFi4sL/fr1o1ixYty4cYMePXqwc+dOXF1d7anP//zzTzp16mTPfpslS5Z4n+PG\ndX/Rsm1H+wp/mTI9edn6dOnSk9rdg4F9e1Gtlg/Va8eco9l78DCDR4zlxs1bhIXfxqd6Jfu+Rn61\ncHFxoUih17h02bqQ1LpN22nZqINlAAAfsElEQVTRpD6urq78X47s1KhcHoBDR0+w9+ARGrSy5s21\nPHxIjuyPr/rq+dezv969YzclyzyeawoODGbsr2NxcXHBp4EPSxYuoW3ntpT2Ls34b8dz4dwFfBr4\nkO/VfFH6boxh9PDRbNu0DRcXFy5euMglW1rxvK+8QklbyovSRYty6uzZWL9HcxYvpnv79gA0q1+f\nOcHB9mBRpnhxctjSz+fPnZvatnxfxQoVsmeqXbPuLw4dPmhv79atW4SFWeddIqfCj2zNur/4adwv\n9veZbKnTgxbOZ8r034iIiODSpYscOnzQHixiS3HvDBosVIq3d/8/HD9xjBZtrePd9+8/IG+evHTu\n0IVmTd6kbGlvlq9cRsu3mvHNiDFUrVzNXndu4GwuX77M9u3bcXNzI1++fPb04o+SCoI1vfijYaiQ\nkBB69+5t3/doziKy0aNH8/LLL7Nr1y4ePnyIh21diSelzo4XEzN1+pOkSpWKmUFL2bR+DSFBgUz7\n7Rd+nTE/SpkuH37K7F++o2Sxwvw+M5A1G7fa90VJ1x0pv1xsxzfGULRQAf5aODXWvkROC79m5Rp7\nqvGD+w5y8vhJ3m5hnex+8OABufPmpm3ntjRs2pCSZUry159/0aVVF4Z+M5QKVSrY21k0dxGhV0OZ\ns2wObm5u1Pauzd3792P03dXVlTv37nHm/HladrcmLuzcsiVN6tZlzebN7D98GBHB8vAhIsLQPn0A\n7KnSIWbq9Edp5s3DhywOXBZrUHjSOiWGmD//k6dO8sOE71m6cCWZMmWiZ+/u3Lt3z74/thT3zqBz\nFirFm79gLn16fcy2DbvZtmE3u7ft5/zF85w+c4oTJ0+QN28+unTuSl2feuzbvzdK3Zs3b5I9e3bc\n3NxYtWoVJ0+ejPNYxhh2795tv+J4khs3bpAzZ05cXFyYMmWKfflVX19fJk2axO3b1hTb0Yeh4lKp\nag1m/jHZ/gsjrmGo8PAwbt26SbVaPnw8eBgH9v4To0xYWDg5Xram654xf1EsrURVpUJZZi8IwWKx\ncP7iZf7aYA0uhV7Lz+XQUDZts6aFf/DgAfsOHom1jU1rN1GxakXAOgTVo08Pe+ryNbvWcPH8Rc6e\nPsvpk6fJnTc37d5pR826NTm472CUdm7dusVLWV+ypm5ft5lzZ+JepDNXzpysnz+f9fPn83arVixY\ntozW/v7sXbmSf1asYP+qVeR95RU2bt/u8PvwSPVqNZk0+fG80T979ziuU7Umv0Sqc/36dcLCbpIm\nTRoyZMjApcuXWLE69kWknE2vLFSKF7hwHtN/mx1lW/26DQkMmsfDhw+ZO382qdxSkT3by3zUq2+U\ncs0C3qRzt7fw9vamdOnS9rThT7J9+3a8vLwc/oXfvXt3mjVrxuzZs6lZsyZp06YFwM/Pj507d+Lt\n7U3q1KmpX78+w4cPj9d5Nmv9FieOHyXAtzqp3Nxo3vot2nZ8J9ayt8PC6PFOe+7fu4cxho8HDo1R\nZtB/e1C1YRvy5MpJ8cKFuBUWd7pu/3p1WL1+C2VrB1Dw1XxUrWBNZJo6tRvTfxpN74FfcPPmLSIs\nFnq8046irxeIUj/0Siju7u6kS2+dmA0ODGbCtAlRytSpX4fgwGCMMQTNCcLNzY2s2bPGSGfeqGkj\n3mv/Hs19m1O4eGFeLfhq3N+8aOYsXsyHXaIuN9XY15fZixbRtH79eLXx+f++ot+n/6WGb2UsERYq\nvFGRkV+MjrNO75596Pfpf6lWpyKurq706fUxDeo1okSxklSrU5G8efJS3vuNBJ1LYtEU5ZFoivJn\n9yKkKI/LsGHDKFCgAK1atUr0fqT0FOVBc4K4eP4iXT6IbU3AZ6cpyjVFuVLPjU8//TS5u/Cv1bh5\nzDuS1PND5yyUUko5pMFCKaWUQxoslFJKOaTBQimllEMaLJRSSjmkwUKlWI9SlJ86fYpqdSrGu17w\n0sUcPHTA/n7gwIH8+efTPwj14MEDe5bZ6MndJk+eTA9bNtPx48fz++9Jc/v22K+/tKc8j68xE34n\n46tluBGPVOFPa+XSlUwcG3cCxIT6fuT3zI/2dLpKOL11ViUJv+VvOy6UAPObLHZc6CktWboYn9p1\neb2Q9QG8IUOGPFN769ato1KlSg7LdevW7ZmOkxAffNQvwXVmLQimbKniLAhZQfuWTRK9TxEREdSq\nW4tadWsletvq2WmwUClW5BTlsZky7Tf+mPYb9x/cJ3++V/n+2/Hs3buHpctD2LB5PaPHjmLS+N/p\n+9l3NGzYkObNm5MvXz46dOjAwoULefDgAbNnz6Zw4cKEhobSuXNnjh07Rpo0aZgwYQIlS1qvbJYs\nWUK9evXi7AvA4MGDSZcuHX369GHMmDGMHz+eVKlSUbRoUWbMmMG4b0Zw+uQJLl48z4VzZ+nc7QPe\nbNOO8PAwPni7PTdvXifiQQQ9/9ufWr71OHv6FN06tMLL+w12bt/KyzlyMvaX3/Hw8GRA7x72zLV7\ndv3Nl4M/4fbt26ROnZpVs8aTPl3aKH07euIUYeG3GfPpR4wYO9EeLH6fGcjCpSuxWCzsPXiEXl07\ncP/+A6bNXYh76tQETvmRLJkzcvTEKXp98jlXrl7D09ODH0cO5vUCr9K/Z38yZs7I/j37KVqiKIWK\nFOKfXf/w2RefceXyFQb3HcyZk2cAGPTVILzKedGjYw/OnzvPvbv3aN+lPS3atQCs6cnbdWnH6uWr\ncfdwZ9xv48iaLStp0qbB3cMd9Wx0GEqlWJFTlMemQb1GLF20klVL11GwQCGmzfiDct5vUNenHoMG\nDGHlkrXky5c/Rr1HKaHfe+89Ro0aBcCgQYPw8vJi9+7dDB8+nPa2bKUAq1atokaNGgDcuXOH0qVL\n278GDhwYa9++/PJL/v77b3bv3s348ePt2w8e2MePk6cxLTCE8d+N4tKFC7i7ezBm4m/MCV7JrzPn\nM2LoQHtyv5PHj9G6Q2eCVqwjfYYMLA+OmuPp/v379OnehX6DP2f+0tX8Mm0unrH8Yp0VGEIL//pU\neaMsh46e4NKVq/Z9ew8e5rdxI1i3eDqDvhpDGk8PNi+bwxtlSzF1jnU9hvf7/o/RQwewccksvvys\nDz37D7PXP3H0BJNmT+Lj/0VdLe7zTz6nXMVyBK4MZO7yufa05cNGD2PusrnMWTqHKT9P4Vqo9dHs\n27dvU6psKQJXBuJdwZvZf1hTvHTu3pn6TeKXokM9mV5ZqBfWgYP7+XLkMG7cvEH47XBqVovf8Eds\nKaHXrVvH3LnWRZVq1arF1atXuXHjBuHh4WTJksWeZdTT05OdO3fa25o8eTKxpakpWbIkbdu2pUmT\nJjRp8njIp5avHx4ennh4eFK+YhX27NpBtVo+fDtiGNs3b0JchEsXLnDl8iUAXsmdhyLFSgBQtEQp\nzp45FeU4J44dIWv27JSwrdSWLn16UrnejtGf2UEhzPr5O1xcXGhSrw7zFi2jW0frEqbVK5Unfbq0\npE+Xlgzp01HfpwYAxYoU5J99hwgLv82m7Ttp0/VxJt57tgywAH6N/HCNlPbjkc3rNvPV2K8Aa0bV\n9BnSA/DHz3/wZ4h1DunCuQucPH6SzFky45bajRqPjl2yGBvWbIjRpnp6GizUC6vnR935beIfFCta\nghmzp7Eh0iI0cYktJXRsOdZEhJCQEOrWrZvgvi1evJg1a9YQFBTE0KFD2bvXmg1XiJqgUERYFDiH\na1evMmvxn7i5ueFTqQz3bSmsU6eOmkb9XrRV4eKTEn3PvoMcOX6S+q2tOZsePHhAvjy57MHCPVq6\nbnd3W7pucSHCYuHhw4dkypCeLcvnxmwc8EwTM4X3k2xZv4WNazcyfdF0PNN40j6gPffvWgOPWyo3\n+7m4urpiibDE1ZRKIB2GUi+s8LAwsmfPwYMHD5g7/3FW2rTp0hEWHpagtqpVq8bUqdb1GlavXk3W\nrFnJkCFDvOcrInv48CGnT5+mZs2ajBgxwpam2tqflctDuHf3LtevhbJl03qKl/Qi7OZNsmTNak3H\nvWEd586cjvex8r9WkMsXL7Jn19+A9XsSfU2EmQuC+bR3dw5tXsahzcs4vmMV5y5c4qSDtN+PZEif\njny5X2HuwqWALY373gMOakGFqhWY/pt1TW2LxULYrTBu3bpFhowZ8EzjybHDx9i1Y1e8z1U9G6cG\nCxHxE5GDInJERGLcfiEi7iIy07Z/s4jks23PJyJ3RGSn7Wt89LpKJcTRY0coXb6Y/StoUSAf9xlA\nPf86tGgbQIECBe1lAxo15YfxY6ldrxonThyPV/uDBw9m27ZtlCxZkn79+vHbb79hsVg4fPiww7Tm\n0VksFt566y1KlCiBl5cXH374oX3FtBKlyvBexza09vejW8+PyJ4jBw0DmrN39y5aNKjD4sA5vBrp\nXBxJnTo1o36YyPCB/QmoW4N32jbn7r37UcrMXrAE/3q1o2zz96vN7AUh8T7Or99/xeQZ8yhXpyle\nNf1ZuGyVwzoDhg1gy/otNK7RmOa+zTl88DBVa1bFEmHBv6Y/Y74aQ6kypeLdB/VsnJaiXERcgUOA\nD3AG2Aq0Nsbsi1SmO1DSGNNNRFoBAcaYlragscgYUzy+x9MU5U+mKcqfTUJSQEe2bt06/vjjjygT\n1M/i/Q/7kiZtWjp1fT9R2nuS5EpR7myaovz5TVFeHjhijDlm69AMwB/YF6mMPzDY9noO8L089ZqS\nSj1fqlSpQpUqVZK7G0olCmcGi1eAyIOnZ4DoSzzZyxhjIkTkBvCSbV9+EfkbuAl8aoxZG/0AIvIu\n8C5Anjx5Erf3Sj1n3u/d13EhpZzEmXMWsV0hRB/zelKZ80AeY4wX0BuYJiIxxlKMMROMMd7GGO9s\n2bI9c4eVUkrFzpnB4gyQO9L7XED02yfsZUQkFZARCDXG3DPGXAUwxmwHjgKFnNhXpZRScXBmsNgK\nFBSR/CKSGmgFBEUrEwR0sL1uDqw0xhgRyWabIEdEXgUKAsec2FellFJxcNqchW0OogewFHAFJhlj\n9orIEGCbMSYI+AWYIiJHgFCsAQWgGjBERCIAC9DNGBPqrL4qpZSKm1Of4DbGBAPB0bYNjPT6LvBm\nLPXmArE/7qlUPJ07f5Z+n/6XQ4cP8vDhQ3xq12XQJ0M4dPggFy6ep04tXwBGfvMladOmpXvXD5K5\nx0o9vzTdh0oSO97tmqjtFZm6IM79xhg6vdueju068/sv07BYLHzUrxdfjBzK64WKsGv33/Zg8aws\nFkusuY2USkk03YdKkdauX4OHuzutW7QFrLmChg78nKnTpzBk+CAWLJxPLb+qBAZZEwEePHyQgBYN\nKVe5NBMn/WRvZ868mZQvX57SpUvTtWtXLBZrvqF06dIxcOBA3njjDTZu3Jj0J6hUEtNgoVKkg4cO\nULJE6Sjb0qfPQO7cefjwgz74Nwpg5ZK1NGlszSB75OghZkyZy5KFK/j626948OABhw4fJHDhfNav\nX8/OnTtxdXW1538KDw+nePHibN68WR+8Uy8EHYZSKdKTsqk+aXudWr64u7vj7u5O1qzZuHzlEmvX\n/8XuPbsoV64cYF2LInv27ID1SqVZs2bOPQmlniMaLFSK9HqhwiwOiXqn9q1bNzl37iyurjEvqN0j\npfJ2cXEhIsKCMdCieSvGjBsdo7yHh4fOU6gXig5DqRSpWpXq3Llzh1lzZgDWSehBQz+j5ZttyJY1\nuz3ld1yqVq7GouAgLl2yLiQUGhrKyZMnndpvpZ5XGixUiiQi/DpxCkGLA6lQrSwVq3vj7uHOgL6f\nUblSVQ4dPhhlgjs2rxcqTL8+n+Dr60vJkiXx8fHh/PnzSXgWSj0/dBhKJYkyE35yXCgB7sSjzCv/\nl4s/fp0RY7u7u3uc63Ov+fPx3U1NGjfl3fc7xygTnysTpVISvbJQSinlkAYLpZRSDmmwUEop5ZAG\nC6WUUg5psFBKKeWQBgullFIOabBQKZZ3pZIAnDp9irwFc1LLryo161ahQYAvR44eBmD9xnW07djy\nqdrPly8fV65ciXVf165dWb9+PQARERFkzZqV/v37Rymzdu1aihUrRunSpblzJ+bNwJUqVXqqfiXE\nn0sWUyxPNo4dOey0Y2zf9Q+9PxueqG3OnzGf70d+n6htqrjpcxYqSfw2MXF/GbXolSNB5fPmzcfK\nJWsB+P2PX/nu+28YO/rHRO1TZJs3b+aHH34AYNmyZbz++uvMmjWL4cOH23NTTZ06lT59+tCpU6co\ndR+lPN+wYYPT+vdI8IJ5lCn3BiFB83m/d99Ebz8iIoKypYpTtlTxRG9bJS29slAp1ktZssa6/VbY\nLTJmzBRj+46d22kQ4EvtetWiXH1YLBb69OlDiRIlKFmyJGPHjo1S786dO/j5+TFx4kQA9u/fT6FC\nhey5o6ZPn85//vMf8uTJw6ZNmwD4+eefmTVrFkOGDKFt27asXr2amjVr0qZNG0qUKAFY06A/MmLE\nCJr4VCOgbg2++WIIALOnTaFFQx8C6tbgP107cufObQAG9O7B8IH9aRtQn7qVvVm6OPpqxlbh4WH8\nvW0LQ0d+R8jC+fbtf23YQp1mHWnb9SOKV2nAp8NHM33eIqo0aEXZ2gEcPXEKgMtXQ2nVpReV67ek\ncv2WbNi6A4ChX4+je9/BNGjdhc7/GcBfG7YQ0L47AGHht+ny4aeUrR2Ad50Ali1aBsDgvoNp7tuc\nhtUaMnbE4+9vbe/ajB0xlqY+TWlcozHHDltXV3b3cCdN2jSxnpdyDr2yUClW5Ke0T548QS2/qoSF\nhXHnzh1CgpbHKF/wtYIsmB1MqlSp+GvtaoaPGMqkn35nwoQJHD9+nL///ptUqVIRGvp4hd+wsDBa\ntWpF+/btad++PQAhISH4+fkB1kCyYsUKfvrpJ65fv8706dOpWLEi77zzDuvWraNhw4Y0b96c1atX\ns2XLFv755x/y588fpV8hISEEBgYyPWgJnp5puH79GgA+9RrwZpt2AHw3cjjzZkylbacuAFy+dJEp\ncxdx7Mhherz9FnUbNI5xviuXhlClRi3yvfoaGTNlZt+eXRQtUQqAPfsOMmV1EFkyZaRIJT86tm7K\nusUz+P7nKfw4aRqjhvTjo4Ff8kGX9lQuX4ZTZ8/TqM277PprIQB/797Hyvm/4+npwV8bttiP+cW3\n48mYPh3bV1iD085b1ifhe/XvRabMmbBYLHRq3omD+w7yetHXAcicJTPzls9j2q/TmPTjJIZ9M4z6\nTerH70OgEo0GC/VCiDwMFRg0jz79PmTGlDlRyty8dZMPenfn2PGjiAgREREA/Pnnn3Tr1o1Uqaz/\nXbJkyWKv4+/vT9++fWnbtq1929KlS/n1118BWLRoETVr1iRNmjQ0a9aMoUOHMnr06Fgz1pYvXz5G\noHh0/E6dOuHpaf1LOlOmzAAcPrifMSO/4NbNm9y+HU7lajXtdWrXrY+LiwsFCr3O1SuXY/2eBAfN\no11n6wqG9Ro1IThovj1YlC1VjJwvZwMgf97c1KlunT8pVrgQf23YCsCqtZs4cOiovb1bYeHcCgsH\noIFvDTw9PWIcc+XaTUz5YaT9fcZMGQFYErSEWX/MwhJh4fLFyxw5dMQeLHwa+FiPXaoYy4NjBnmV\nNDRYqBdOXd969OrTI8b2r0YNp3LFqkye+AenTp+iacuGwJPXwACoXLkyISEhtGnTBhHh9u3bXL9+\nnf/7v/8DrENQ69evJ1++fABcvXqVVatWUadOnRhtpU2bNtZjPOn4n3zUkzETf6Nw0eLMnz2drRvX\n2/e5pU4dpX5016+Fsnn9Og4fPICI8NBiARE+GjAIAPdI9V1cxP7exeVxEH348CF/BU2NNSikTeMZ\n73M5c/IMv/74K7OWzCJjpoz079mf+3fv2/enth3b1cUVS4Ql1naV8+mchXrhbNmyibx588XYfvPW\nTXLmyAnAzNnT7Nt9fX0ZP368/Zdk5GGoIUOG8NJLL9G9u3VMftWqVdSsaf0L/+bNm6xbt45Tp05x\n4sQJTpw4wbhx45g+fXqC+uvr68ukSZPscxKPhqHCw8LIlv1lHjx4wOL5cxPU5rLFC2ncrAV/bvyb\n5Rt2sGLzLnLlzsOOLZvi3Ubt6pX4cfLj79Oufw44rFOneiV+/PVxnRvXbxAWFoZnGk/SZ0jPlctX\nWLtybYLORSUNDRbqhfBozqJm3SoMHzGUb0aMiVHm/W49+fyrITQMqIvl4eO/YN955x3y5MlDyZIl\nKVWqFNOmTYtS79tvv+Xu3bv07ds3ynzFvHnzqFWrFu7ujxdW8vf3JygoiHv37sW7735+fjRu3JgW\nDXxo6leDyT+NA+CDPv1o7e9Hl7bNyV+gQIK+H8FB86jtF3Xc36deQxYveHLK9ui+GdqfHbv24l0n\ngNI1GjNxykyHdfr9pyvXbtykTK0mlKvTlM3rN1O4WGGKFC9Co+qN+KTXJ3iV90rQuaikIbFdov4b\neXt7m23btj1TG2X/+3si9cax+elHOi6USFpnzpBkxxo+2zqymeF/gymQM6fTjnMnbcJunX0W2XPH\nvHPqScqUKcPmzZtxc3NL9H7sOx37Mx2J7TXXi0lyHIDjSbja4CvXkuxQz+3nc//+/RQpUiTKNhHZ\nbozxdlRX5yyUSkQ7duxI7i4o5RQ6DKWUUsohDRZKKaUc0mChnMOYWG/ZVEolj2f9/6jBQjmF5fx5\nbty/rwFDqeeAMYarV6/i4RHzmZj40glu5RS3p07jYts2XMmZE57wQNuzeOAenuhtPsnVsOcjB9GF\na2FJchyL3EyS4wBccUm6v1dtj6kkiefx8+nh4UGuXLme+jhODRYi4gd8B7gCPxtjvoy23x34HSgL\nXAVaGmNO2Pb1B94GLEBPY8xSZ/ZVJS4TFkb4TxOc1v6ecn2c1nZ0Pb5ulGTHistbSXRrd1Le1t0t\nGW7rTgop8fPptLAuIq7AOKAeUBRoLSJFoxV7G7hmjCkAjAa+stUtCrQCigF+wA+29pRSSiUDZ14D\nlgeOGGOOGWPuAzMA/2hl/IHfbK/nALXFmjjGH5hhjLlnjDkOHLG1p5RSKhk4M1i8ApyO9P6MbVus\nZYwxEcAN4KV41lVKKZVEnDmIF9usZvRbY55UJj51EZF3gXdtb8NE5GCCepiM8iZ3BxzLCiQ4v0SN\nxO9H7NauSaoj8cE3SXao58K/4LMJT/H5rOGcfsTu3/X5jNeP3JnB4gyQO9L7XMC5J5Q5IyKpgIxA\naDzrYoyZADhvFvUFJiLb4pMvRqnkoJ/PpOfMYaitQEERyS8iqbFOWEdf3zEI6GB73RxYaaw35gcB\nrUTEXUTyAwWBLSillEoWTruyMMZEiEgPYCnWW2cnGWP2isgQYJsxJgj4BZgiIkewXlG0stXdKyKz\ngH1ABPC+MUZXPVFKqWSSYlKUq8QlIu/ahvmUeu7o5zPpabBQSinlkOaGUkop5ZAGixRKRHqKyH4R\nmeqk9geLSNLlNFDqCUSkhogsSu5+pHSaSDDl6g7Usz0Br5RSz0SvLFIgERkPvAoEicgnIjJJRLaK\nyN8i4m8r01FEAkVkoYgcF5EeItLbVmaTiGSxletiq7tLROaKSIwUlyLymogsEZHtIrJWRAon7Rmr\nfzsRySciB0TkZxH5R0SmikgdEVkvIodFpLzta4PtM7pBRF6PpZ20sX3e1bPTYJECGWO6YX2IsSaQ\nFuvzK+Vs70eKSFpb0eJAG6x5tz4HbhtjvICNQHtbmXnGmHLGmFLAfqzJH6ObAHxgjCkL9AF+cM6Z\nqRSuANYs1SWBwlg/m1WwfqYGAAeAarbP6EBgeCxtfMKTP+/qGegwVMrnCzSONL/gAeSxvV5ljLkF\n3BKRG8BC2/Y9WP/DAhQXkWFAJiAd1udm7EQkHVAJmC2P161wd8aJqBTvuDFmD4CI7AVWGGOMiOwB\n8mHN8PCbiBTEmv7HLZY2nvR53+/szqd0GixSPgGaGWOi5M0SkTeAe5E2PYz0/iGPPxuTgSbGmF0i\n0pGYKXZcgOvGmNKJ2231AnL0eRyK9Q+cABHJB6yOpY1YP+/q2ekwVMq3FPjAlvodEfFKYP30wHkR\ncQPaRt9pjLkJHBeRN23ti4iUesY+KxWbjMBZ2+uOTyjzrJ939QQaLFK+oVgv13eLyD+29wnxGbAZ\nWI51zDg2bYG3RWQXsJeY65YolRhGAF+IyHqsKYRi86yfd/UE+gS3Ukoph/TKQimllEMaLJRSSjmk\nwUIppZRDGiyUUko5pMFCKaWUQxoslEomIjJZRJondz+Uig8NFkr9S4iIZlxQyUY/fErFg4h8hvXh\nw9PAFWA7MB8YB2QDbgNdjDEHRGQycBPwBnIAfY0xc2xPFY8FagHHsaameNR+WeAbrPm3rgAdjTHn\nRWQ1sAGoDAQBXzv9ZJWKhQYLpRwQEW+gGeCF9f/MDqzBYgLQzRhz2JZr6wesgQAgJ9aMqYWx/pKf\nAwQArwMlgJeBfcAkWyqVsYC/MeayiLTEmgW4s62tTMaY6k4/UaXioMFCKceqAAuMMXcARGQh1mym\ncWXbDTTGPAT2icjLtm3VgOnGGAtwTkRW2ra/jjVd/HJbW67A+UhtzUz8U1IqYTRYKOWYxLLNUbbd\nyBlUI9ePLb+OAHuNMRWf0Fa44y4q5Vw6wa2UY+uARiLiYVu/owHWOYqEZttdA7QSEVcRyYl1cR6A\ng0A2Ealoa8tNRIo55UyUekoaLJRywBizFeu8wy5gHrANuEHCs+3OBw5jXVzqR+AvW/v3gebAV7a2\ndmId4lLquaFZZ5WKBxFJZ4wJs61BvgZ41xizI7n7pVRS0TkLpeJngogUxTqx/ZsGCvWi0SsLpZRS\nDumchVJKKYc0WCillHJIg4VSSimHNFgopZRySIOFUkophzRYKKWUcuj/AVPJNr9SwSscAAAAAElF\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaef441c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"gender\", y=\"match\", hue=\"race_o\", data=xt) # Percentage of race of partner(opposite) gender got a match"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0cffe10>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zwiiBp8f05pL+8UeY0xyNuNhoJv1qEB8vTSbqI1dhJ0qED397Gn3aNqzk3Jkg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\nmteLyMNedzMRyRKRXx9jVotbVryIfCQ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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaeddd2978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pointplot(x=\"race\", y=\"match\", hue=\"gender\", data=xt) #Comparision of race getting matches with its corresponding gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0da44a8>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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mVT1BRELASyLylLf+fKBaVTftt89zgPOAE70AU+rNelhVb/eWucHb9k3evCHA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\n/j9b+/w+HWH9gwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf0ce5d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x=xt.match, y=xt.race) # Amount of matches got according to the race"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1aaf0e36a58>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qOktEvgTcDHxWVf/cyf5krFBA+zzc/OytUs7/0IX87PEl3FhZ3SchB8DngWnF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\n6ViCY4wxxpimYwmOMcYYY5rO/wfRmXfrOqzIZwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf0c02048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x=xt.match, y=xt.race_o) # Amount of matches got to the opposite race"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\Harsh $hinde'"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Implementation of Logistics Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "dsx = xt[[\"like\",\"intelligence\"]] # can put any attribute for consideration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = dsx\n",
    "y = xt[\"match\"] # Ultimately we need to fetch the likability of a match\n",
    "\n",
    "from sklearn.cross_validation import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)\n",
    "\n",
    "# Feature Scaling\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "sc = StandardScaler()\n",
    "X_train = sc.fit_transform(X_train)\n",
    "X_test = sc.transform(X_test)\n",
    "\n",
    "# Fitting Logistic Regression to the Training set\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "classifier = LogisticRegression(random_state = 0)\n",
    "classifier.fit(X_train, y_train)\n",
    "\n",
    "# Predicting the Test set results\n",
    "y_pred = classifier.predict(X_test)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hf0rbXngux7oORcnr8tezgbnAYZIOYehtPQhYMOkorT6VVtTjtTfrGC2u0gpi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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf272dd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Making the Confusion Matrix\n",
    "from sklearn.metrics import confusion_matrix\n",
    "cm = confusion_matrix(y_test, y_pred)\n",
    "\n",
    "# Visualising the Training set results\n",
    "from matplotlib.colors import ListedColormap\n",
    "X_set, y_set = X_train, y_train\n",
    "X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.01),\n",
    "                     np.arange(start = X_set[:, 1].min() - 1, stop = X_set[:, 1].max() + 1, step = 0.01))\n",
    "#plt.contourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape),\n",
    "             #alpha = 0.75, cmap = ListedColormap(('red', 'green')))\n",
    "plt.xlim(X1.min(), X1.max())\n",
    "plt.ylim(X2.min(), X2.max())\n",
    "for i, j in enumerate(np.unique(y_set)):\n",
    "    plt.scatter(X_set[y_set == j, 0], X_set[y_set == j, 1],\n",
    "                c = ListedColormap(('red', 'green'))(i), label = j) # Creating a scatterplot of match values\n",
    "plt.title('Logistic Regression (Training set)')\n",
    "plt.xlabel('like')\n",
    "plt.ylabel('intelligence')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1aaf1d80978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualising the Test set results\n",
    "from matplotlib.colors import ListedColormap\n",
    "X_set, y_set = X_test, y_test\n",
    "X1, X2 = np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.01),\n",
    "                     np.arange(start = X_set[:, 1].min() - 1, stop = X_set[:, 1].max() + 1, step = 0.01))\n",
    "#plt.contourf(X1, X2, classifier.predict(np.array([X1.ravel(), X2.ravel()]).T).reshape(X1.shape),\n",
    "             #alpha = 0.75,cmap = ListedColormap(() ))\n",
    "plt.xlim(X1.min(), X1.max())\n",
    "plt.ylim(X2.min(), X2.max())\n",
    "for i, j in enumerate(np.unique(y_set)):\n",
    "    plt.scatter(X_set[y_set == j, 0], X_set[y_set == j, 1],\n",
    "                c = ListedColormap(('red', 'green'))(i), label = j)\n",
    "plt.title('Logistic Regression (Test set)')\n",
    "plt.xlabel('Like')\n",
    "plt.ylabel('intelligence')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}