6-clustering/example-clustering-states.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finding similar states - clustering using scikit-learn and pandas\n",
    "\n",
    "On this notebook we'll use pandas to load and process data from the US states, after that we'll use scikit-learn to cluster states based on census statistics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#First import pandas and KMeans from scikit-learn\n",
    "import pandas as pd\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "#Configure the plotting library\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (15, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Load county data - this also contains state-level data\n",
    "\n",
    "#The first file contains the actual statistics, but the columns have codes\n",
    "county_facts = pd.read_csv('../kaggle-data/county_facts.csv', index_col=['fips', 'area_name'])\n",
    "#The second file translates from codes to the meaning of each column\n",
    "county_facts_columns = pd.read_csv('../kaggle-data/county_facts_dictionary.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>column_name</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PST045214</td>\n",
       "      <td>Population, 2014 estimate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PST040210</td>\n",
       "      <td>Population, 2010 (April 1) estimates base</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>PST120214</td>\n",
       "      <td>Population, percent change - April 1, 2010 to ...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>POP010210</td>\n",
       "      <td>Population, 2010</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AGE135214</td>\n",
       "      <td>Persons under 5 years, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AGE295214</td>\n",
       "      <td>Persons under 18 years, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AGE775214</td>\n",
       "      <td>Persons 65 years and over, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SEX255214</td>\n",
       "      <td>Female persons, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>RHI125214</td>\n",
       "      <td>White alone, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>RHI225214</td>\n",
       "      <td>Black or African American alone, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>RHI325214</td>\n",
       "      <td>American Indian and Alaska Native alone, perce...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>RHI425214</td>\n",
       "      <td>Asian alone, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>RHI525214</td>\n",
       "      <td>Native Hawaiian and Other Pacific Islander alo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>RHI625214</td>\n",
       "      <td>Two or More Races, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>RHI725214</td>\n",
       "      <td>Hispanic or Latino, percent, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>RHI825214</td>\n",
       "      <td>White alone, not Hispanic or Latino, percent, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>POP715213</td>\n",
       "      <td>Living in same house 1 year &amp; over, percent, 2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>POP645213</td>\n",
       "      <td>Foreign born persons, percent, 2009-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>POP815213</td>\n",
       "      <td>Language other than English spoken at home, pc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>EDU635213</td>\n",
       "      <td>High school graduate or higher, percent of per...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>EDU685213</td>\n",
       "      <td>Bachelor's degree or higher, percent of person...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>VET605213</td>\n",
       "      <td>Veterans, 2009-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>LFE305213</td>\n",
       "      <td>Mean travel time to work (minutes), workers ag...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>HSG010214</td>\n",
       "      <td>Housing units, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>HSG445213</td>\n",
       "      <td>Homeownership rate, 2009-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>HSG096213</td>\n",
       "      <td>Housing units in multi-unit structures, percen...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>HSG495213</td>\n",
       "      <td>Median value of owner-occupied housing units, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>HSD410213</td>\n",
       "      <td>Households, 2009-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>HSD310213</td>\n",
       "      <td>Persons per household, 2009-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>INC910213</td>\n",
       "      <td>Per capita money income in past 12 months (201...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>INC110213</td>\n",
       "      <td>Median household income, 2009-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>PVY020213</td>\n",
       "      <td>Persons below poverty level, percent, 2009-2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>BZA010213</td>\n",
       "      <td>Private nonfarm establishments, 2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>BZA110213</td>\n",
       "      <td>Private nonfarm employment,  2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>BZA115213</td>\n",
       "      <td>Private nonfarm employment, percent change, 20...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>NES010213</td>\n",
       "      <td>Nonemployer establishments, 2013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>SBO001207</td>\n",
       "      <td>Total number of firms, 2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>SBO315207</td>\n",
       "      <td>Black-owned firms, percent, 2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>SBO115207</td>\n",
       "      <td>American Indian- and Alaska Native-owned firms...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>SBO215207</td>\n",
       "      <td>Asian-owned firms, percent, 2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>SBO515207</td>\n",
       "      <td>Native Hawaiian- and Other Pacific Islander-ow...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>SBO415207</td>\n",
       "      <td>Hispanic-owned firms, percent, 2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>SBO015207</td>\n",
       "      <td>Women-owned firms, percent, 2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>MAN450207</td>\n",
       "      <td>Manufacturers shipments, 2007 ($1,000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>WTN220207</td>\n",
       "      <td>Merchant wholesaler sales, 2007 ($1,000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>RTN130207</td>\n",
       "      <td>Retail sales, 2007 ($1,000)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>RTN131207</td>\n",
       "      <td>Retail sales per capita, 2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>AFN120207</td>\n",
       "      <td>Accommodation and food services sales, 2007 ($...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>BPS030214</td>\n",
       "      <td>Building permits, 2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>LND110210</td>\n",
       "      <td>Land area in square miles, 2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>POP060210</td>\n",
       "      <td>Population per square mile, 2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   column_name                                        description\n",
       "0    PST045214                          Population, 2014 estimate\n",
       "1    PST040210          Population, 2010 (April 1) estimates base\n",
       "2    PST120214  Population, percent change - April 1, 2010 to ...\n",
       "3    POP010210                                   Population, 2010\n",
       "4    AGE135214               Persons under 5 years, percent, 2014\n",
       "5    AGE295214              Persons under 18 years, percent, 2014\n",
       "6    AGE775214           Persons 65 years and over, percent, 2014\n",
       "7    SEX255214                      Female persons, percent, 2014\n",
       "8    RHI125214                         White alone, percent, 2014\n",
       "9    RHI225214     Black or African American alone, percent, 2014\n",
       "10   RHI325214  American Indian and Alaska Native alone, perce...\n",
       "11   RHI425214                         Asian alone, percent, 2014\n",
       "12   RHI525214  Native Hawaiian and Other Pacific Islander alo...\n",
       "13   RHI625214                   Two or More Races, percent, 2014\n",
       "14   RHI725214                  Hispanic or Latino, percent, 2014\n",
       "15   RHI825214  White alone, not Hispanic or Latino, percent, ...\n",
       "16   POP715213  Living in same house 1 year & over, percent, 2...\n",
       "17   POP645213           Foreign born persons, percent, 2009-2013\n",
       "18   POP815213  Language other than English spoken at home, pc...\n",
       "19   EDU635213  High school graduate or higher, percent of per...\n",
       "20   EDU685213  Bachelor's degree or higher, percent of person...\n",
       "21   VET605213                                Veterans, 2009-2013\n",
       "22   LFE305213  Mean travel time to work (minutes), workers ag...\n",
       "23   HSG010214                                Housing units, 2014\n",
       "24   HSG445213                      Homeownership rate, 2009-2013\n",
       "25   HSG096213  Housing units in multi-unit structures, percen...\n",
       "26   HSG495213  Median value of owner-occupied housing units, ...\n",
       "27   HSD410213                              Households, 2009-2013\n",
       "28   HSD310213                   Persons per household, 2009-2013\n",
       "29   INC910213  Per capita money income in past 12 months (201...\n",
       "30   INC110213                 Median household income, 2009-2013\n",
       "31   PVY020213    Persons below poverty level, percent, 2009-2013\n",
       "32   BZA010213               Private nonfarm establishments, 2013\n",
       "33   BZA110213                  Private nonfarm employment,  2013\n",
       "34   BZA115213  Private nonfarm employment, percent change, 20...\n",
       "35   NES010213                   Nonemployer establishments, 2013\n",
       "36   SBO001207                        Total number of firms, 2007\n",
       "37   SBO315207                   Black-owned firms, percent, 2007\n",
       "38   SBO115207  American Indian- and Alaska Native-owned firms...\n",
       "39   SBO215207                   Asian-owned firms, percent, 2007\n",
       "40   SBO515207  Native Hawaiian- and Other Pacific Islander-ow...\n",
       "41   SBO415207                Hispanic-owned firms, percent, 2007\n",
       "42   SBO015207                   Women-owned firms, percent, 2007\n",
       "43   MAN450207             Manufacturers shipments, 2007 ($1,000)\n",
       "44   WTN220207           Merchant wholesaler sales, 2007 ($1,000)\n",
       "45   RTN130207                        Retail sales, 2007 ($1,000)\n",
       "46   RTN131207                      Retail sales per capita, 2007\n",
       "47   AFN120207  Accommodation and food services sales, 2007 ($...\n",
       "48   BPS030214                             Building permits, 2014\n",
       "49   LND110210                    Land area in square miles, 2010\n",
       "50   POP060210                   Population per square mile, 2010"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Take a look at the columns\n",
    "county_facts_columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>state_abbreviation</th>\n",
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       "      <th>POP010210</th>\n",
       "      <th>AGE135214</th>\n",
       "      <th>AGE295214</th>\n",
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       "      <th>SEX255214</th>\n",
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       "      <th>LND110210</th>\n",
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       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <th>area_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th>United States</th>\n",
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       "      <td>318857056</td>\n",
       "      <td>308758105</td>\n",
       "      <td>3.3</td>\n",
       "      <td>308745538</td>\n",
       "      <td>6.2</td>\n",
       "      <td>23.1</td>\n",
       "      <td>14.5</td>\n",
       "      <td>50.8</td>\n",
       "      <td>77.4</td>\n",
       "      <td>...</td>\n",
       "      <td>8.3</td>\n",
       "      <td>28.8</td>\n",
       "      <td>5319456312</td>\n",
       "      <td>4174286516</td>\n",
       "      <td>3917663456</td>\n",
       "      <td>12990</td>\n",
       "      <td>613795732</td>\n",
       "      <td>1046363</td>\n",
       "      <td>3531905.43</td>\n",
       "      <td>87.4</td>\n",
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       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <th>Alabama</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4849377</td>\n",
       "      <td>4780127</td>\n",
       "      <td>1.4</td>\n",
       "      <td>4779736</td>\n",
       "      <td>6.1</td>\n",
       "      <td>22.8</td>\n",
       "      <td>15.3</td>\n",
       "      <td>51.5</td>\n",
       "      <td>69.7</td>\n",
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       "      <td>1.2</td>\n",
       "      <td>28.1</td>\n",
       "      <td>112858843</td>\n",
       "      <td>52252752</td>\n",
       "      <td>57344851</td>\n",
       "      <td>12364</td>\n",
       "      <td>6426342</td>\n",
       "      <td>13369</td>\n",
       "      <td>50645.33</td>\n",
       "      <td>94.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1001</th>\n",
       "      <th>Autauga County</th>\n",
       "      <td>AL</td>\n",
       "      <td>55395</td>\n",
       "      <td>54571</td>\n",
       "      <td>1.5</td>\n",
       "      <td>54571</td>\n",
       "      <td>6.0</td>\n",
       "      <td>25.2</td>\n",
       "      <td>13.8</td>\n",
       "      <td>51.4</td>\n",
       "      <td>77.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.7</td>\n",
       "      <td>31.7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>598175</td>\n",
       "      <td>12003</td>\n",
       "      <td>88157</td>\n",
       "      <td>131</td>\n",
       "      <td>594.44</td>\n",
       "      <td>91.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1003</th>\n",
       "      <th>Baldwin County</th>\n",
       "      <td>AL</td>\n",
       "      <td>200111</td>\n",
       "      <td>182265</td>\n",
       "      <td>9.8</td>\n",
       "      <td>182265</td>\n",
       "      <td>5.6</td>\n",
       "      <td>22.2</td>\n",
       "      <td>18.7</td>\n",
       "      <td>51.2</td>\n",
       "      <td>87.1</td>\n",
       "      <td>...</td>\n",
       "      <td>1.3</td>\n",
       "      <td>27.3</td>\n",
       "      <td>1410273</td>\n",
       "      <td>0</td>\n",
       "      <td>2966489</td>\n",
       "      <td>17166</td>\n",
       "      <td>436955</td>\n",
       "      <td>1384</td>\n",
       "      <td>1589.78</td>\n",
       "      <td>114.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <th>Barbour County</th>\n",
       "      <td>AL</td>\n",
       "      <td>26887</td>\n",
       "      <td>27457</td>\n",
       "      <td>-2.1</td>\n",
       "      <td>27457</td>\n",
       "      <td>5.7</td>\n",
       "      <td>21.2</td>\n",
       "      <td>16.5</td>\n",
       "      <td>46.6</td>\n",
       "      <td>50.2</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>188337</td>\n",
       "      <td>6334</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>884.88</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    state_abbreviation  PST045214  PST040210  PST120214  \\\n",
       "fips area_name                                                            \n",
       "0    United States                 NaN  318857056  308758105        3.3   \n",
       "1000 Alabama                       NaN    4849377    4780127        1.4   \n",
       "1001 Autauga County                 AL      55395      54571        1.5   \n",
       "1003 Baldwin County                 AL     200111     182265        9.8   \n",
       "1005 Barbour County                 AL      26887      27457       -2.1   \n",
       "\n",
       "                     POP010210  AGE135214  AGE295214  AGE775214  SEX255214  \\\n",
       "fips area_name                                                               \n",
       "0    United States   308745538        6.2       23.1       14.5       50.8   \n",
       "1000 Alabama           4779736        6.1       22.8       15.3       51.5   \n",
       "1001 Autauga County      54571        6.0       25.2       13.8       51.4   \n",
       "1003 Baldwin County     182265        5.6       22.2       18.7       51.2   \n",
       "1005 Barbour County      27457        5.7       21.2       16.5       46.6   \n",
       "\n",
       "                     RHI125214    ...      SBO415207  SBO015207   MAN450207  \\\n",
       "fips area_name                    ...                                         \n",
       "0    United States        77.4    ...            8.3       28.8  5319456312   \n",
       "1000 Alabama              69.7    ...            1.2       28.1   112858843   \n",
       "1001 Autauga County       77.9    ...            0.7       31.7           0   \n",
       "1003 Baldwin County       87.1    ...            1.3       27.3     1410273   \n",
       "1005 Barbour County       50.2    ...            0.0       27.0           0   \n",
       "\n",
       "                      WTN220207   RTN130207  RTN131207  AFN120207  BPS030214  \\\n",
       "fips area_name                                                                 \n",
       "0    United States   4174286516  3917663456      12990  613795732    1046363   \n",
       "1000 Alabama           52252752    57344851      12364    6426342      13369   \n",
       "1001 Autauga County           0      598175      12003      88157        131   \n",
       "1003 Baldwin County           0     2966489      17166     436955       1384   \n",
       "1005 Barbour County           0      188337       6334          0          8   \n",
       "\n",
       "                      LND110210  POP060210  \n",
       "fips area_name                              \n",
       "0    United States   3531905.43       87.4  \n",
       "1000 Alabama           50645.33       94.4  \n",
       "1001 Autauga County      594.44       91.8  \n",
       "1003 Baldwin County     1589.78      114.6  \n",
       "1005 Barbour County      884.88       31.0  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Let's take a look at some of the rows we have using head() pandas method\n",
    "county_facts.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data processing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`county_facts` contains data at the county and state level. Since we only want state-level data, we need to filter the rows. As you can see from the previous cell, county-level rows contain the `state_abbreviation`, the rest of the rows contain null. To get only state-level data we'll filter by rows that have a null value in `state_abbreviation` column but leave the first row out since it contains data for the entire country."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>state_abbreviation</th>\n",
       "      <th>PST045214</th>\n",
       "      <th>PST040210</th>\n",
       "      <th>PST120214</th>\n",
       "      <th>POP010210</th>\n",
       "      <th>AGE135214</th>\n",
       "      <th>AGE295214</th>\n",
       "      <th>AGE775214</th>\n",
       "      <th>SEX255214</th>\n",
       "      <th>RHI125214</th>\n",
       "      <th>...</th>\n",
       "      <th>SBO415207</th>\n",
       "      <th>SBO015207</th>\n",
       "      <th>MAN450207</th>\n",
       "      <th>WTN220207</th>\n",
       "      <th>RTN130207</th>\n",
       "      <th>RTN131207</th>\n",
       "      <th>AFN120207</th>\n",
       "      <th>BPS030214</th>\n",
       "      <th>LND110210</th>\n",
       "      <th>POP060210</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <th>area_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <th>Alabama</th>\n",
       "      <td>NaN</td>\n",
       "      <td>4849377</td>\n",
       "      <td>4780127</td>\n",
       "      <td>1.4</td>\n",
       "      <td>4779736</td>\n",
       "      <td>6.1</td>\n",
       "      <td>22.8</td>\n",
       "      <td>15.3</td>\n",
       "      <td>51.5</td>\n",
       "      <td>69.7</td>\n",
       "      <td>...</td>\n",
       "      <td>1.2</td>\n",
       "      <td>28.1</td>\n",
       "      <td>112858843</td>\n",
       "      <td>52252752</td>\n",
       "      <td>57344851</td>\n",
       "      <td>12364</td>\n",
       "      <td>6426342</td>\n",
       "      <td>13369</td>\n",
       "      <td>50645.33</td>\n",
       "      <td>94.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <th>Alaska</th>\n",
       "      <td>NaN</td>\n",
       "      <td>736732</td>\n",
       "      <td>710249</td>\n",
       "      <td>3.7</td>\n",
       "      <td>710231</td>\n",
       "      <td>7.4</td>\n",
       "      <td>25.3</td>\n",
       "      <td>9.4</td>\n",
       "      <td>47.4</td>\n",
       "      <td>66.9</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25.9</td>\n",
       "      <td>8204030</td>\n",
       "      <td>4563605</td>\n",
       "      <td>9303387</td>\n",
       "      <td>13635</td>\n",
       "      <td>1851293</td>\n",
       "      <td>1518</td>\n",
       "      <td>570640.95</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4000</th>\n",
       "      <th>Arizona</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6731484</td>\n",
       "      <td>6392310</td>\n",
       "      <td>5.3</td>\n",
       "      <td>6392017</td>\n",
       "      <td>6.4</td>\n",
       "      <td>24.1</td>\n",
       "      <td>15.9</td>\n",
       "      <td>50.3</td>\n",
       "      <td>83.7</td>\n",
       "      <td>...</td>\n",
       "      <td>10.7</td>\n",
       "      <td>28.1</td>\n",
       "      <td>57977827</td>\n",
       "      <td>57573459</td>\n",
       "      <td>86758801</td>\n",
       "      <td>13637</td>\n",
       "      <td>13268514</td>\n",
       "      <td>26997</td>\n",
       "      <td>113594.08</td>\n",
       "      <td>56.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5000</th>\n",
       "      <th>Arkansas</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2966369</td>\n",
       "      <td>2915958</td>\n",
       "      <td>1.7</td>\n",
       "      <td>2915918</td>\n",
       "      <td>6.5</td>\n",
       "      <td>23.8</td>\n",
       "      <td>15.7</td>\n",
       "      <td>50.9</td>\n",
       "      <td>79.7</td>\n",
       "      <td>...</td>\n",
       "      <td>2.3</td>\n",
       "      <td>24.5</td>\n",
       "      <td>60735582</td>\n",
       "      <td>29659789</td>\n",
       "      <td>32974282</td>\n",
       "      <td>11602</td>\n",
       "      <td>3559795</td>\n",
       "      <td>7666</td>\n",
       "      <td>52035.48</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6000</th>\n",
       "      <th>California</th>\n",
       "      <td>NaN</td>\n",
       "      <td>38802500</td>\n",
       "      <td>37254503</td>\n",
       "      <td>4.2</td>\n",
       "      <td>37253956</td>\n",
       "      <td>6.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>12.9</td>\n",
       "      <td>50.3</td>\n",
       "      <td>73.2</td>\n",
       "      <td>...</td>\n",
       "      <td>16.5</td>\n",
       "      <td>30.3</td>\n",
       "      <td>491372092</td>\n",
       "      <td>598456486</td>\n",
       "      <td>455032270</td>\n",
       "      <td>12561</td>\n",
       "      <td>80852787</td>\n",
       "      <td>83645</td>\n",
       "      <td>155779.22</td>\n",
       "      <td>239.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 52 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                state_abbreviation  PST045214  PST040210  PST120214  \\\n",
       "fips area_name                                                        \n",
       "1000 Alabama                   NaN    4849377    4780127        1.4   \n",
       "2000 Alaska                    NaN     736732     710249        3.7   \n",
       "4000 Arizona                   NaN    6731484    6392310        5.3   \n",
       "5000 Arkansas                  NaN    2966369    2915958        1.7   \n",
       "6000 California                NaN   38802500   37254503        4.2   \n",
       "\n",
       "                 POP010210  AGE135214  AGE295214  AGE775214  SEX255214  \\\n",
       "fips area_name                                                           \n",
       "1000 Alabama       4779736        6.1       22.8       15.3       51.5   \n",
       "2000 Alaska         710231        7.4       25.3        9.4       47.4   \n",
       "4000 Arizona       6392017        6.4       24.1       15.9       50.3   \n",
       "5000 Arkansas      2915918        6.5       23.8       15.7       50.9   \n",
       "6000 California   37253956        6.5       23.6       12.9       50.3   \n",
       "\n",
       "                 RHI125214    ...      SBO415207  SBO015207  MAN450207  \\\n",
       "fips area_name                ...                                        \n",
       "1000 Alabama          69.7    ...            1.2       28.1  112858843   \n",
       "2000 Alaska           66.9    ...            0.0       25.9    8204030   \n",
       "4000 Arizona          83.7    ...           10.7       28.1   57977827   \n",
       "5000 Arkansas         79.7    ...            2.3       24.5   60735582   \n",
       "6000 California       73.2    ...           16.5       30.3  491372092   \n",
       "\n",
       "                 WTN220207  RTN130207  RTN131207  AFN120207  BPS030214  \\\n",
       "fips area_name                                                           \n",
       "1000 Alabama      52252752   57344851      12364    6426342      13369   \n",
       "2000 Alaska        4563605    9303387      13635    1851293       1518   \n",
       "4000 Arizona      57573459   86758801      13637   13268514      26997   \n",
       "5000 Arkansas     29659789   32974282      11602    3559795       7666   \n",
       "6000 California  598456486  455032270      12561   80852787      83645   \n",
       "\n",
       "                 LND110210  POP060210  \n",
       "fips area_name                         \n",
       "1000 Alabama      50645.33       94.4  \n",
       "2000 Alaska      570640.95        1.2  \n",
       "4000 Arizona     113594.08       56.3  \n",
       "5000 Arkansas     52035.48       56.0  \n",
       "6000 California  155779.22      239.1  \n",
       "\n",
       "[5 rows x 52 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Subselect rows, let's just keep state level data\n",
    "df = county_facts[county_facts.state_abbreviation.isnull()][1:]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While we can cluster using all columns, let's subset them for now. Feel free to modify this piece of code and experiment with different column combinations!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Select columns that have to do with etnicity proportion\n",
    "df = df.filter(regex='RHI*')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The column names in our data are coded, since we are interested in the meaning of each column we are using, we need to replace the code for the actual meaning. The following cell achieves that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>White alone, percent, 2014</th>\n",
       "      <th>Black or African American alone, percent, 2014</th>\n",
       "      <th>American Indian and Alaska Native alone, percent, 2014</th>\n",
       "      <th>Asian alone, percent, 2014</th>\n",
       "      <th>Native Hawaiian and Other Pacific Islander alone, percent, 2014</th>\n",
       "      <th>Two or More Races, percent, 2014</th>\n",
       "      <th>Hispanic or Latino, percent, 2014</th>\n",
       "      <th>White alone, not Hispanic or Latino, percent, 2014</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <th>area_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <th>Alabama</th>\n",
       "      <td>69.7</td>\n",
       "      <td>26.7</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>66.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <th>Alaska</th>\n",
       "      <td>66.9</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14.8</td>\n",
       "      <td>6.1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>7.1</td>\n",
       "      <td>6.8</td>\n",
       "      <td>61.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4000</th>\n",
       "      <th>Arizona</th>\n",
       "      <td>83.7</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.3</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>30.5</td>\n",
       "      <td>56.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5000</th>\n",
       "      <th>Arkansas</th>\n",
       "      <td>79.7</td>\n",
       "      <td>15.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1.9</td>\n",
       "      <td>7.0</td>\n",
       "      <td>73.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6000</th>\n",
       "      <th>California</th>\n",
       "      <td>73.2</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>14.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.7</td>\n",
       "      <td>38.6</td>\n",
       "      <td>38.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 White alone, percent, 2014  \\\n",
       "fips area_name                                \n",
       "1000 Alabama                           69.7   \n",
       "2000 Alaska                            66.9   \n",
       "4000 Arizona                           83.7   \n",
       "5000 Arkansas                          79.7   \n",
       "6000 California                        73.2   \n",
       "\n",
       "                 Black or African American alone, percent, 2014  \\\n",
       "fips area_name                                                    \n",
       "1000 Alabama                                               26.7   \n",
       "2000 Alaska                                                 3.9   \n",
       "4000 Arizona                                                4.7   \n",
       "5000 Arkansas                                              15.6   \n",
       "6000 California                                             6.5   \n",
       "\n",
       "                 American Indian and Alaska Native alone, percent, 2014  \\\n",
       "fips area_name                                                            \n",
       "1000 Alabama                                                   0.7        \n",
       "2000 Alaska                                                   14.8        \n",
       "4000 Arizona                                                   5.3        \n",
       "5000 Arkansas                                                  1.0        \n",
       "6000 California                                                1.7        \n",
       "\n",
       "                 Asian alone, percent, 2014  \\\n",
       "fips area_name                                \n",
       "1000 Alabama                            1.3   \n",
       "2000 Alaska                             6.1   \n",
       "4000 Arizona                            3.3   \n",
       "5000 Arkansas                           1.5   \n",
       "6000 California                        14.4   \n",
       "\n",
       "                 Native Hawaiian and Other Pacific Islander alone, percent, 2014  \\\n",
       "fips area_name                                                                     \n",
       "1000 Alabama                                                   0.1                 \n",
       "2000 Alaska                                                    1.3                 \n",
       "4000 Arizona                                                   0.3                 \n",
       "5000 Arkansas                                                  0.3                 \n",
       "6000 California                                                0.5                 \n",
       "\n",
       "                 Two or More Races, percent, 2014  \\\n",
       "fips area_name                                      \n",
       "1000 Alabama                                  1.5   \n",
       "2000 Alaska                                   7.1   \n",
       "4000 Arizona                                  2.7   \n",
       "5000 Arkansas                                 1.9   \n",
       "6000 California                               3.7   \n",
       "\n",
       "                 Hispanic or Latino, percent, 2014  \\\n",
       "fips area_name                                       \n",
       "1000 Alabama                                   4.1   \n",
       "2000 Alaska                                    6.8   \n",
       "4000 Arizona                                  30.5   \n",
       "5000 Arkansas                                  7.0   \n",
       "6000 California                               38.6   \n",
       "\n",
       "                 White alone, not Hispanic or Latino, percent, 2014  \n",
       "fips area_name                                                       \n",
       "1000 Alabama                                                  66.2   \n",
       "2000 Alaska                                                   61.9   \n",
       "4000 Arizona                                                  56.2   \n",
       "5000 Arkansas                                                 73.4   \n",
       "6000 California                                               38.5   "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Rename columns to use their meaning instead their codename\n",
    "col_names = dict((k, v) for k,v in county_facts_columns.itertuples(index=False, name=None))\n",
    "df.rename(columns=col_names, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's run a KMeans algorithm with 4 clusters, feel free to experiment with different [clustering algorithms](http://scikit-learn.org/stable/modules/clustering.html) and different parameters (parameter change depending on the algorithm)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running a clustering algorithm with scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Run a clustering algorithm, group in 4 clusters\n",
    "model = KMeans(n_clusters=4)\n",
    "results = model.fit_predict(df.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Assign cluster number to our dataframe, this will help us identify which cluster was assigned to\n",
    "#every state\n",
    "df['cluster'] = results"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10f65c490>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tpweAE245PQCHcN1BVlU3JPmdJHcmeUWSn6mq71nXYByn5fQAcMItpweAE245PQCccMvp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\niCADAAAYIsgAAACGCDIAAIAh/wfgZM5YvNtNEQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e6dcfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Count the number of states assigned to each cluster\n",
    "df.cluster.value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x10f756e10>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JkiQ9MA7qIUmSJEmNWJDNQJJXt86gNUuybesMkjSbkuzTOoMml+R3WmfQmiV5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\nAAAMopABAAAMopABAAAMopABAAAM8g9rMMiDrpswLAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f737c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Let's take a look at how the algorithm clustered states\n",
    "df.groupby(df.cluster).mean().transpose().plot.bar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can se that cluster 0 has a much higher proportion of hispanics, cluster 3 of asians and clister 1 african americanas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>White alone, percent, 2014</th>\n",
       "      <th>Black or African American alone, percent, 2014</th>\n",
       "      <th>American Indian and Alaska Native alone, percent, 2014</th>\n",
       "      <th>Asian alone, percent, 2014</th>\n",
       "      <th>Native Hawaiian and Other Pacific Islander alone, percent, 2014</th>\n",
       "      <th>Two or More Races, percent, 2014</th>\n",
       "      <th>Hispanic or Latino, percent, 2014</th>\n",
       "      <th>White alone, not Hispanic or Latino, percent, 2014</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <th>area_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1000</th>\n",
       "      <th>Alabama</th>\n",
       "      <td>69.7</td>\n",
       "      <td>26.7</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>4.1</td>\n",
       "      <td>66.2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <th>Alaska</th>\n",
       "      <td>66.9</td>\n",
       "      <td>3.9</td>\n",
       "      <td>14.8</td>\n",
       "      <td>6.1</td>\n",
       "      <td>1.3</td>\n",
       "      <td>7.1</td>\n",
       "      <td>6.8</td>\n",
       "      <td>61.9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10000</th>\n",
       "      <th>Delaware</th>\n",
       "      <td>70.8</td>\n",
       "      <td>22.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>3.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.5</td>\n",
       "      <td>8.9</td>\n",
       "      <td>63.7</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11000</th>\n",
       "      <th>District Of Columbia</th>\n",
       "      <td>43.6</td>\n",
       "      <td>49.0</td>\n",
       "      <td>0.6</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.6</td>\n",
       "      <td>10.4</td>\n",
       "      <td>35.8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13000</th>\n",
       "      <th>Georgia</th>\n",
       "      <td>62.1</td>\n",
       "      <td>31.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.3</td>\n",
       "      <td>54.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17000</th>\n",
       "      <th>Illinois</th>\n",
       "      <td>77.5</td>\n",
       "      <td>14.7</td>\n",
       "      <td>0.6</td>\n",
       "      <td>5.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>16.7</td>\n",
       "      <td>62.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22000</th>\n",
       "      <th>Louisiana</th>\n",
       "      <td>63.4</td>\n",
       "      <td>32.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>4.8</td>\n",
       "      <td>59.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24000</th>\n",
       "      <th>Maryland</th>\n",
       "      <td>60.1</td>\n",
       "      <td>30.3</td>\n",
       "      <td>0.6</td>\n",
       "      <td>6.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>9.3</td>\n",
       "      <td>52.6</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28000</th>\n",
       "      <th>Mississippi</th>\n",
       "      <td>59.7</td>\n",
       "      <td>37.5</td>\n",
       "      <td>0.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>57.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34000</th>\n",
       "      <th>New Jersey</th>\n",
       "      <td>73.0</td>\n",
       "      <td>14.8</td>\n",
       "      <td>0.6</td>\n",
       "      <td>9.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>19.3</td>\n",
       "      <td>56.8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36000</th>\n",
       "      <th>New York</th>\n",
       "      <td>70.4</td>\n",
       "      <td>17.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.4</td>\n",
       "      <td>18.6</td>\n",
       "      <td>56.5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37000</th>\n",
       "      <th>North Carolina</th>\n",
       "      <td>71.5</td>\n",
       "      <td>22.1</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.7</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>9.0</td>\n",
       "      <td>64.1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45000</th>\n",
       "      <th>South Carolina</th>\n",
       "      <td>68.3</td>\n",
       "      <td>27.8</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>5.4</td>\n",
       "      <td>63.9</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51000</th>\n",
       "      <th>Virginia</th>\n",
       "      <td>70.5</td>\n",
       "      <td>19.7</td>\n",
       "      <td>0.5</td>\n",
       "      <td>6.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.8</td>\n",
       "      <td>8.9</td>\n",
       "      <td>63.1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            White alone, percent, 2014  \\\n",
       "fips  area_name                                          \n",
       "1000  Alabama                                     69.7   \n",
       "2000  Alaska                                      66.9   \n",
       "10000 Delaware                                    70.8   \n",
       "11000 District Of Columbia                        43.6   \n",
       "13000 Georgia                                     62.1   \n",
       "17000 Illinois                                    77.5   \n",
       "22000 Louisiana                                   63.4   \n",
       "24000 Maryland                                    60.1   \n",
       "28000 Mississippi                                 59.7   \n",
       "34000 New Jersey                                  73.0   \n",
       "36000 New York                                    70.4   \n",
       "37000 North Carolina                              71.5   \n",
       "45000 South Carolina                              68.3   \n",
       "51000 Virginia                                    70.5   \n",
       "\n",
       "                            Black or African American alone, percent, 2014  \\\n",
       "fips  area_name                                                              \n",
       "1000  Alabama                                                         26.7   \n",
       "2000  Alaska                                                           3.9   \n",
       "10000 Delaware                                                        22.2   \n",
       "11000 District Of Columbia                                            49.0   \n",
       "13000 Georgia                                                         31.5   \n",
       "17000 Illinois                                                        14.7   \n",
       "22000 Louisiana                                                       32.5   \n",
       "24000 Maryland                                                        30.3   \n",
       "28000 Mississippi                                                     37.5   \n",
       "34000 New Jersey                                                      14.8   \n",
       "36000 New York                                                        17.6   \n",
       "37000 North Carolina                                                  22.1   \n",
       "45000 South Carolina                                                  27.8   \n",
       "51000 Virginia                                                        19.7   \n",
       "\n",
       "                            American Indian and Alaska Native alone, percent, 2014  \\\n",
       "fips  area_name                                                                      \n",
       "1000  Alabama                                                             0.7        \n",
       "2000  Alaska                                                             14.8        \n",
       "10000 Delaware                                                            0.7        \n",
       "11000 District Of Columbia                                                0.6        \n",
       "13000 Georgia                                                             0.5        \n",
       "17000 Illinois                                                            0.6        \n",
       "22000 Louisiana                                                           0.8        \n",
       "24000 Maryland                                                            0.6        \n",
       "28000 Mississippi                                                         0.6        \n",
       "34000 New Jersey                                                          0.6        \n",
       "36000 New York                                                            1.0        \n",
       "37000 North Carolina                                                      1.6        \n",
       "45000 South Carolina                                                      0.5        \n",
       "51000 Virginia                                                            0.5        \n",
       "\n",
       "                            Asian alone, percent, 2014  \\\n",
       "fips  area_name                                          \n",
       "1000  Alabama                                      1.3   \n",
       "2000  Alaska                                       6.1   \n",
       "10000 Delaware                                     3.8   \n",
       "11000 District Of Columbia                         4.0   \n",
       "13000 Georgia                                      3.8   \n",
       "17000 Illinois                                     5.3   \n",
       "22000 Louisiana                                    1.8   \n",
       "24000 Maryland                                     6.4   \n",
       "28000 Mississippi                                  1.0   \n",
       "34000 New Jersey                                   9.4   \n",
       "36000 New York                                     8.5   \n",
       "37000 North Carolina                               2.7   \n",
       "45000 South Carolina                               1.5   \n",
       "51000 Virginia                                     6.3   \n",
       "\n",
       "                            Native Hawaiian and Other Pacific Islander alone, percent, 2014  \\\n",
       "fips  area_name                                                                               \n",
       "1000  Alabama                                                             0.1                 \n",
       "2000  Alaska                                                              1.3                 \n",
       "10000 Delaware                                                            0.1                 \n",
       "11000 District Of Columbia                                                0.2                 \n",
       "13000 Georgia                                                             0.1                 \n",
       "17000 Illinois                                                            0.1                 \n",
       "22000 Louisiana                                                           0.1                 \n",
       "24000 Maryland                                                            0.1                 \n",
       "28000 Mississippi                                                         0.1                 \n",
       "34000 New Jersey                                                          0.1                 \n",
       "36000 New York                                                            0.1                 \n",
       "37000 North Carolina                                                      0.1                 \n",
       "45000 South Carolina                                                      0.1                 \n",
       "51000 Virginia                                                            0.1                 \n",
       "\n",
       "                            Two or More Races, percent, 2014  \\\n",
       "fips  area_name                                                \n",
       "1000  Alabama                                            1.5   \n",
       "2000  Alaska                                             7.1   \n",
       "10000 Delaware                                           2.5   \n",
       "11000 District Of Columbia                               2.6   \n",
       "13000 Georgia                                            2.0   \n",
       "17000 Illinois                                           1.8   \n",
       "22000 Louisiana                                          1.5   \n",
       "24000 Maryland                                           2.6   \n",
       "28000 Mississippi                                        1.2   \n",
       "34000 New Jersey                                         2.1   \n",
       "36000 New York                                           2.4   \n",
       "37000 North Carolina                                     2.1   \n",
       "45000 South Carolina                                     1.7   \n",
       "51000 Virginia                                           2.8   \n",
       "\n",
       "                            Hispanic or Latino, percent, 2014  \\\n",
       "fips  area_name                                                 \n",
       "1000  Alabama                                             4.1   \n",
       "2000  Alaska                                              6.8   \n",
       "10000 Delaware                                            8.9   \n",
       "11000 District Of Columbia                               10.4   \n",
       "13000 Georgia                                             9.3   \n",
       "17000 Illinois                                           16.7   \n",
       "22000 Louisiana                                           4.8   \n",
       "24000 Maryland                                            9.3   \n",
       "28000 Mississippi                                         3.0   \n",
       "34000 New Jersey                                         19.3   \n",
       "36000 New York                                           18.6   \n",
       "37000 North Carolina                                      9.0   \n",
       "45000 South Carolina                                      5.4   \n",
       "51000 Virginia                                            8.9   \n",
       "\n",
       "                            White alone, not Hispanic or Latino, percent, 2014  \\\n",
       "fips  area_name                                                                  \n",
       "1000  Alabama                                                            66.2    \n",
       "2000  Alaska                                                             61.9    \n",
       "10000 Delaware                                                           63.7    \n",
       "11000 District Of Columbia                                               35.8    \n",
       "13000 Georgia                                                            54.3    \n",
       "17000 Illinois                                                           62.3    \n",
       "22000 Louisiana                                                          59.3    \n",
       "24000 Maryland                                                           52.6    \n",
       "28000 Mississippi                                                        57.3    \n",
       "34000 New Jersey                                                         56.8    \n",
       "36000 New York                                                           56.5    \n",
       "37000 North Carolina                                                     64.1    \n",
       "45000 South Carolina                                                     63.9    \n",
       "51000 Virginia                                                           63.1    \n",
       "\n",
       "                            cluster  \n",
       "fips  area_name                      \n",
       "1000  Alabama                     0  \n",
       "2000  Alaska                      0  \n",
       "10000 Delaware                    0  \n",
       "11000 District Of Columbia        0  \n",
       "13000 Georgia                     0  \n",
       "17000 Illinois                    0  \n",
       "22000 Louisiana                   0  \n",
       "24000 Maryland                    0  \n",
       "28000 Mississippi                 0  \n",
       "34000 New Jersey                  0  \n",
       "36000 New York                    0  \n",
       "37000 North Carolina              0  \n",
       "45000 South Carolina              0  \n",
       "51000 Virginia                    0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Let's see which states are in each cluster\n",
    "df[df.cluster==0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>White alone, percent, 2014</th>\n",
       "      <th>Black or African American alone, percent, 2014</th>\n",
       "      <th>American Indian and Alaska Native alone, percent, 2014</th>\n",
       "      <th>Asian alone, percent, 2014</th>\n",
       "      <th>Native Hawaiian and Other Pacific Islander alone, percent, 2014</th>\n",
       "      <th>Two or More Races, percent, 2014</th>\n",
       "      <th>Hispanic or Latino, percent, 2014</th>\n",
       "      <th>White alone, not Hispanic or Latino, percent, 2014</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <th>area_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4000</th>\n",
       "      <th>Arizona</th>\n",
       "      <td>83.7</td>\n",
       "      <td>4.7</td>\n",
       "      <td>5.3</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>30.5</td>\n",
       "      <td>56.2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6000</th>\n",
       "      <th>California</th>\n",
       "      <td>73.2</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1.7</td>\n",
       "      <td>14.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>3.7</td>\n",
       "      <td>38.6</td>\n",
       "      <td>38.5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12000</th>\n",
       "      <th>Florida</th>\n",
       "      <td>77.8</td>\n",
       "      <td>16.8</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>24.1</td>\n",
       "      <td>55.8</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32000</th>\n",
       "      <th>Nevada</th>\n",
       "      <td>76.2</td>\n",
       "      <td>9.1</td>\n",
       "      <td>1.6</td>\n",
       "      <td>8.3</td>\n",
       "      <td>0.7</td>\n",
       "      <td>4.0</td>\n",
       "      <td>27.8</td>\n",
       "      <td>51.5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35000</th>\n",
       "      <th>New Mexico</th>\n",
       "      <td>82.8</td>\n",
       "      <td>2.5</td>\n",
       "      <td>10.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.5</td>\n",
       "      <td>47.7</td>\n",
       "      <td>38.9</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48000</th>\n",
       "      <th>Texas</th>\n",
       "      <td>80.0</td>\n",
       "      <td>12.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>38.6</td>\n",
       "      <td>43.5</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  White alone, percent, 2014  \\\n",
       "fips  area_name                                \n",
       "4000  Arizona                           83.7   \n",
       "6000  California                        73.2   \n",
       "12000 Florida                           77.8   \n",
       "32000 Nevada                            76.2   \n",
       "35000 New Mexico                        82.8   \n",
       "48000 Texas                             80.0   \n",
       "\n",
       "                  Black or African American alone, percent, 2014  \\\n",
       "fips  area_name                                                    \n",
       "4000  Arizona                                                4.7   \n",
       "6000  California                                             6.5   \n",
       "12000 Florida                                               16.8   \n",
       "32000 Nevada                                                 9.1   \n",
       "35000 New Mexico                                             2.5   \n",
       "48000 Texas                                                 12.5   \n",
       "\n",
       "                  American Indian and Alaska Native alone, percent, 2014  \\\n",
       "fips  area_name                                                            \n",
       "4000  Arizona                                                   5.3        \n",
       "6000  California                                                1.7        \n",
       "12000 Florida                                                   0.5        \n",
       "32000 Nevada                                                    1.6        \n",
       "35000 New Mexico                                               10.4        \n",
       "48000 Texas                                                     1.0        \n",
       "\n",
       "                  Asian alone, percent, 2014  \\\n",
       "fips  area_name                                \n",
       "4000  Arizona                            3.3   \n",
       "6000  California                        14.4   \n",
       "12000 Florida                            2.8   \n",
       "32000 Nevada                             8.3   \n",
       "35000 New Mexico                         1.7   \n",
       "48000 Texas                              4.5   \n",
       "\n",
       "                  Native Hawaiian and Other Pacific Islander alone, percent, 2014  \\\n",
       "fips  area_name                                                                     \n",
       "4000  Arizona                                                   0.3                 \n",
       "6000  California                                                0.5                 \n",
       "12000 Florida                                                   0.1                 \n",
       "32000 Nevada                                                    0.7                 \n",
       "35000 New Mexico                                                0.2                 \n",
       "48000 Texas                                                     0.1                 \n",
       "\n",
       "                  Two or More Races, percent, 2014  \\\n",
       "fips  area_name                                      \n",
       "4000  Arizona                                  2.7   \n",
       "6000  California                               3.7   \n",
       "12000 Florida                                  2.0   \n",
       "32000 Nevada                                   4.0   \n",
       "35000 New Mexico                               2.5   \n",
       "48000 Texas                                    1.8   \n",
       "\n",
       "                  Hispanic or Latino, percent, 2014  \\\n",
       "fips  area_name                                       \n",
       "4000  Arizona                                  30.5   \n",
       "6000  California                               38.6   \n",
       "12000 Florida                                  24.1   \n",
       "32000 Nevada                                   27.8   \n",
       "35000 New Mexico                               47.7   \n",
       "48000 Texas                                    38.6   \n",
       "\n",
       "                  White alone, not Hispanic or Latino, percent, 2014  cluster  \n",
       "fips  area_name                                                                \n",
       "4000  Arizona                                                  56.2         3  \n",
       "6000  California                                               38.5         3  \n",
       "12000 Florida                                                  55.8         3  \n",
       "32000 Nevada                                                   51.5         3  \n",
       "35000 New Mexico                                               38.9         3  \n",
       "48000 Texas                                                    43.5         3  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.cluster==3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>White alone, percent, 2014</th>\n",
       "      <th>Black or African American alone, percent, 2014</th>\n",
       "      <th>American Indian and Alaska Native alone, percent, 2014</th>\n",
       "      <th>Asian alone, percent, 2014</th>\n",
       "      <th>Native Hawaiian and Other Pacific Islander alone, percent, 2014</th>\n",
       "      <th>Two or More Races, percent, 2014</th>\n",
       "      <th>Hispanic or Latino, percent, 2014</th>\n",
       "      <th>White alone, not Hispanic or Latino, percent, 2014</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fips</th>\n",
       "      <th>area_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5000</th>\n",
       "      <th>Arkansas</th>\n",
       "      <td>79.7</td>\n",
       "      <td>15.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1.9</td>\n",
       "      <td>7.0</td>\n",
       "      <td>73.4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8000</th>\n",
       "      <th>Colorado</th>\n",
       "      <td>87.7</td>\n",
       "      <td>4.5</td>\n",
       "      <td>1.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.9</td>\n",
       "      <td>21.2</td>\n",
       "      <td>69.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9000</th>\n",
       "      <th>Connecticut</th>\n",
       "      <td>81.2</td>\n",
       "      <td>11.5</td>\n",
       "      <td>0.5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>15.0</td>\n",
       "      <td>68.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16000</th>\n",
       "      <th>Idaho</th>\n",
       "      <td>93.5</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1.7</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>12.0</td>\n",
       "      <td>82.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18000</th>\n",
       "      <th>Indiana</th>\n",
       "      <td>86.1</td>\n",
       "      <td>9.6</td>\n",
       "      <td>0.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>6.6</td>\n",
       "      <td>80.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19000</th>\n",
       "      <th>Iowa</th>\n",
       "      <td>92.1</td>\n",
       "      <td>3.4</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>5.6</td>\n",
       "      <td>87.1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20000</th>\n",
       "      <th>Kansas</th>\n",
       "      <td>86.8</td>\n",
       "      <td>6.3</td>\n",
       "      <td>1.2</td>\n",
       "      <td>2.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.8</td>\n",
       "      <td>11.4</td>\n",
       "      <td>76.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21000</th>\n",
       "      <th>Kentucky</th>\n",
       "      <td>88.3</td>\n",
       "      <td>8.2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>3.4</td>\n",
       "      <td>85.4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23000</th>\n",
       "      <th>Maine</th>\n",
       "      <td>95.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.7</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>93.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25000</th>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>82.6</td>\n",
       "      <td>8.3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>6.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>10.8</td>\n",
       "      <td>74.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26000</th>\n",
       "      <th>Michigan</th>\n",
       "      <td>79.9</td>\n",
       "      <td>14.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>2.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.3</td>\n",
       "      <td>4.8</td>\n",
       "      <td>75.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27000</th>\n",
       "      <th>Minnesota</th>\n",
       "      <td>85.7</td>\n",
       "      <td>5.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>5.1</td>\n",
       "      <td>81.4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29000</th>\n",
       "      <th>Missouri</th>\n",
       "      <td>83.5</td>\n",
       "      <td>11.8</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>80.1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30000</th>\n",
       "      <th>Montana</th>\n",
       "      <td>89.4</td>\n",
       "      <td>0.6</td>\n",
       "      <td>6.6</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>3.5</td>\n",
       "      <td>86.7</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31000</th>\n",
       "      <th>Nebraska</th>\n",
       "      <td>89.4</td>\n",
       "      <td>4.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>2.2</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>10.2</td>\n",
       "      <td>80.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33000</th>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>94.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>3.3</td>\n",
       "      <td>91.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38000</th>\n",
       "      <th>North Dakota</th>\n",
       "      <td>89.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>5.4</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.2</td>\n",
       "      <td>86.6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39000</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>83.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>0.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>80.1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40000</th>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>75.1</td>\n",
       "      <td>7.7</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2.1</td>\n",
       "      <td>0.2</td>\n",
       "      <td>5.9</td>\n",
       "      <td>9.8</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41000</th>\n",
       "      <th>Oregon</th>\n",
       "      <td>87.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>4.3</td>\n",
       "      <td>0.4</td>\n",
       "      <td>3.6</td>\n",
       "      <td>12.5</td>\n",
       "      <td>77.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42000</th>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>82.9</td>\n",
       "      <td>11.6</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>6.6</td>\n",
       "      <td>77.9</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44000</th>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>85.1</td>\n",
       "      <td>7.7</td>\n",
       "      <td>0.9</td>\n",
       "      <td>3.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.6</td>\n",
       "      <td>14.0</td>\n",
       "      <td>74.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46000</th>\n",
       "      <th>South Dakota</th>\n",
       "      <td>85.7</td>\n",
       "      <td>1.9</td>\n",
       "      <td>8.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.2</td>\n",
       "      <td>3.6</td>\n",
       "      <td>83.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47000</th>\n",
       "      <th>Tennessee</th>\n",
       "      <td>78.9</td>\n",
       "      <td>17.1</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.7</td>\n",
       "      <td>5.0</td>\n",
       "      <td>74.6</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49000</th>\n",
       "      <th>Utah</th>\n",
       "      <td>91.4</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.4</td>\n",
       "      <td>13.5</td>\n",
       "      <td>79.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50000</th>\n",
       "      <th>Vermont</th>\n",
       "      <td>95.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>1.8</td>\n",
       "      <td>93.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53000</th>\n",
       "      <th>Washington</th>\n",
       "      <td>80.7</td>\n",
       "      <td>4.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>8.2</td>\n",
       "      <td>0.7</td>\n",
       "      <td>4.5</td>\n",
       "      <td>12.2</td>\n",
       "      <td>70.4</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54000</th>\n",
       "      <th>West Virginia</th>\n",
       "      <td>93.7</td>\n",
       "      <td>3.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>92.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55000</th>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>87.8</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>6.5</td>\n",
       "      <td>82.2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56000</th>\n",
       "      <th>Wyoming</th>\n",
       "      <td>92.7</td>\n",
       "      <td>1.6</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.1</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.8</td>\n",
       "      <td>84.1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     White alone, percent, 2014  \\\n",
       "fips  area_name                                   \n",
       "5000  Arkansas                             79.7   \n",
       "8000  Colorado                             87.7   \n",
       "9000  Connecticut                          81.2   \n",
       "16000 Idaho                                93.5   \n",
       "18000 Indiana                              86.1   \n",
       "19000 Iowa                                 92.1   \n",
       "20000 Kansas                               86.8   \n",
       "21000 Kentucky                             88.3   \n",
       "23000 Maine                                95.0   \n",
       "25000 Massachusetts                        82.6   \n",
       "26000 Michigan                             79.9   \n",
       "27000 Minnesota                            85.7   \n",
       "29000 Missouri                             83.5   \n",
       "30000 Montana                              89.4   \n",
       "31000 Nebraska                             89.4   \n",
       "33000 New Hampshire                        94.0   \n",
       "38000 North Dakota                         89.1   \n",
       "39000 Ohio                                 83.0   \n",
       "40000 Oklahoma                             75.1   \n",
       "41000 Oregon                               87.9   \n",
       "42000 Pennsylvania                         82.9   \n",
       "44000 Rhode Island                         85.1   \n",
       "46000 South Dakota                         85.7   \n",
       "47000 Tennessee                            78.9   \n",
       "49000 Utah                                 91.4   \n",
       "50000 Vermont                              95.0   \n",
       "53000 Washington                           80.7   \n",
       "54000 West Virginia                        93.7   \n",
       "55000 Wisconsin                            87.8   \n",
       "56000 Wyoming                              92.7   \n",
       "\n",
       "                     Black or African American alone, percent, 2014  \\\n",
       "fips  area_name                                                       \n",
       "5000  Arkansas                                                 15.6   \n",
       "8000  Colorado                                                  4.5   \n",
       "9000  Connecticut                                              11.5   \n",
       "16000 Idaho                                                     0.8   \n",
       "18000 Indiana                                                   9.6   \n",
       "19000 Iowa                                                      3.4   \n",
       "20000 Kansas                                                    6.3   \n",
       "21000 Kentucky                                                  8.2   \n",
       "23000 Maine                                                     1.4   \n",
       "25000 Massachusetts                                             8.3   \n",
       "26000 Michigan                                                 14.2   \n",
       "27000 Minnesota                                                 5.9   \n",
       "29000 Missouri                                                 11.8   \n",
       "30000 Montana                                                   0.6   \n",
       "31000 Nebraska                                                  4.9   \n",
       "33000 New Hampshire                                             1.5   \n",
       "38000 North Dakota                                              2.1   \n",
       "39000 Ohio                                                     12.6   \n",
       "40000 Oklahoma                                                  7.7   \n",
       "41000 Oregon                                                    2.0   \n",
       "42000 Pennsylvania                                             11.6   \n",
       "44000 Rhode Island                                              7.7   \n",
       "46000 South Dakota                                              1.9   \n",
       "47000 Tennessee                                                17.1   \n",
       "49000 Utah                                                      1.3   \n",
       "50000 Vermont                                                   1.2   \n",
       "53000 Washington                                                4.1   \n",
       "54000 West Virginia                                             3.6   \n",
       "55000 Wisconsin                                                 6.6   \n",
       "56000 Wyoming                                                   1.6   \n",
       "\n",
       "                     American Indian and Alaska Native alone, percent, 2014  \\\n",
       "fips  area_name                                                               \n",
       "5000  Arkansas                                                     1.0        \n",
       "8000  Colorado                                                     1.6        \n",
       "9000  Connecticut                                                  0.5        \n",
       "16000 Idaho                                                        1.7        \n",
       "18000 Indiana                                                      0.4        \n",
       "19000 Iowa                                                         0.5        \n",
       "20000 Kansas                                                       1.2        \n",
       "21000 Kentucky                                                     0.3        \n",
       "23000 Maine                                                        0.7        \n",
       "25000 Massachusetts                                                0.5        \n",
       "26000 Michigan                                                     0.7        \n",
       "27000 Minnesota                                                    1.3        \n",
       "29000 Missouri                                                     0.5        \n",
       "30000 Montana                                                      6.6        \n",
       "31000 Nebraska                                                     1.4        \n",
       "33000 New Hampshire                                                0.3        \n",
       "38000 North Dakota                                                 5.4        \n",
       "39000 Ohio                                                         0.3        \n",
       "40000 Oklahoma                                                     9.0        \n",
       "41000 Oregon                                                       1.8        \n",
       "42000 Pennsylvania                                                 0.3        \n",
       "44000 Rhode Island                                                 0.9        \n",
       "46000 South Dakota                                                 8.9        \n",
       "47000 Tennessee                                                    0.4        \n",
       "49000 Utah                                                         1.5        \n",
       "50000 Vermont                                                      0.4        \n",
       "53000 Washington                                                   1.9        \n",
       "54000 West Virginia                                                0.2        \n",
       "55000 Wisconsin                                                    1.1        \n",
       "56000 Wyoming                                                      2.7        \n",
       "\n",
       "                     Asian alone, percent, 2014  \\\n",
       "fips  area_name                                   \n",
       "5000  Arkansas                              1.5   \n",
       "8000  Colorado                              3.1   \n",
       "9000  Connecticut                           4.5   \n",
       "16000 Idaho                                 1.4   \n",
       "18000 Indiana                               2.0   \n",
       "19000 Iowa                                  2.2   \n",
       "20000 Kansas                                2.8   \n",
       "21000 Kentucky                              1.4   \n",
       "23000 Maine                                 1.2   \n",
       "25000 Massachusetts                         6.3   \n",
       "26000 Michigan                              2.9   \n",
       "27000 Minnesota                             4.7   \n",
       "29000 Missouri                              1.9   \n",
       "30000 Montana                               0.8   \n",
       "31000 Nebraska                              2.2   \n",
       "33000 New Hampshire                         2.5   \n",
       "38000 North Dakota                          1.3   \n",
       "39000 Ohio                                  2.0   \n",
       "40000 Oklahoma                              2.1   \n",
       "41000 Oregon                                4.3   \n",
       "42000 Pennsylvania                          3.3   \n",
       "44000 Rhode Island                          3.5   \n",
       "46000 South Dakota                          1.3   \n",
       "47000 Tennessee                             1.7   \n",
       "49000 Utah                                  2.4   \n",
       "50000 Vermont                               1.6   \n",
       "53000 Washington                            8.2   \n",
       "54000 West Virginia                         0.8   \n",
       "55000 Wisconsin                             2.6   \n",
       "56000 Wyoming                               1.0   \n",
       "\n",
       "                     Native Hawaiian and Other Pacific Islander alone, percent, 2014  \\\n",
       "fips  area_name                                                                        \n",
       "5000  Arkansas                                                     0.3                 \n",
       "8000  Colorado                                                     0.2                 \n",
       "9000  Connecticut                                                  0.1                 \n",
       "16000 Idaho                                                        0.2                 \n",
       "18000 Indiana                                                      0.1                 \n",
       "19000 Iowa                                                         0.1                 \n",
       "20000 Kansas                                                       0.1                 \n",
       "21000 Kentucky                                                     0.1                 \n",
       "23000 Maine                                                        0.0                 \n",
       "25000 Massachusetts                                                0.1                 \n",
       "26000 Michigan                                                     0.0                 \n",
       "27000 Minnesota                                                    0.1                 \n",
       "29000 Missouri                                                     0.1                 \n",
       "30000 Montana                                                      0.1                 \n",
       "31000 Nebraska                                                     0.1                 \n",
       "33000 New Hampshire                                                0.0                 \n",
       "38000 North Dakota                                                 0.1                 \n",
       "39000 Ohio                                                         0.1                 \n",
       "40000 Oklahoma                                                     0.2                 \n",
       "41000 Oregon                                                       0.4                 \n",
       "42000 Pennsylvania                                                 0.1                 \n",
       "44000 Rhode Island                                                 0.2                 \n",
       "46000 South Dakota                                                 0.1                 \n",
       "47000 Tennessee                                                    0.1                 \n",
       "49000 Utah                                                         1.0                 \n",
       "50000 Vermont                                                      0.0                 \n",
       "53000 Washington                                                   0.7                 \n",
       "54000 West Virginia                                                0.0                 \n",
       "55000 Wisconsin                                                    0.0                 \n",
       "56000 Wyoming                                                      0.1                 \n",
       "\n",
       "                     Two or More Races, percent, 2014  \\\n",
       "fips  area_name                                         \n",
       "5000  Arkansas                                    1.9   \n",
       "8000  Colorado                                    2.9   \n",
       "9000  Connecticut                                 2.2   \n",
       "16000 Idaho                                       2.3   \n",
       "18000 Indiana                                     1.9   \n",
       "19000 Iowa                                        1.7   \n",
       "20000 Kansas                                      2.8   \n",
       "21000 Kentucky                                    1.8   \n",
       "23000 Maine                                       1.6   \n",
       "25000 Massachusetts                               2.2   \n",
       "26000 Michigan                                    2.3   \n",
       "27000 Minnesota                                   2.3   \n",
       "29000 Missouri                                    2.1   \n",
       "30000 Montana                                     2.6   \n",
       "31000 Nebraska                                    2.0   \n",
       "33000 New Hampshire                               1.6   \n",
       "38000 North Dakota                                2.0   \n",
       "39000 Ohio                                        2.1   \n",
       "40000 Oklahoma                                    5.9   \n",
       "41000 Oregon                                      3.6   \n",
       "42000 Pennsylvania                                1.8   \n",
       "44000 Rhode Island                                2.6   \n",
       "46000 South Dakota                                2.2   \n",
       "47000 Tennessee                                   1.7   \n",
       "49000 Utah                                        2.4   \n",
       "50000 Vermont                                     1.8   \n",
       "53000 Washington                                  4.5   \n",
       "54000 West Virginia                               1.6   \n",
       "55000 Wisconsin                                   1.8   \n",
       "56000 Wyoming                                     2.0   \n",
       "\n",
       "                     Hispanic or Latino, percent, 2014  \\\n",
       "fips  area_name                                          \n",
       "5000  Arkansas                                     7.0   \n",
       "8000  Colorado                                    21.2   \n",
       "9000  Connecticut                                 15.0   \n",
       "16000 Idaho                                       12.0   \n",
       "18000 Indiana                                      6.6   \n",
       "19000 Iowa                                         5.6   \n",
       "20000 Kansas                                      11.4   \n",
       "21000 Kentucky                                     3.4   \n",
       "23000 Maine                                        1.5   \n",
       "25000 Massachusetts                               10.8   \n",
       "26000 Michigan                                     4.8   \n",
       "27000 Minnesota                                    5.1   \n",
       "29000 Missouri                                     4.0   \n",
       "30000 Montana                                      3.5   \n",
       "31000 Nebraska                                    10.2   \n",
       "33000 New Hampshire                                3.3   \n",
       "38000 North Dakota                                 3.2   \n",
       "39000 Ohio                                         3.5   \n",
       "40000 Oklahoma                                     9.8   \n",
       "41000 Oregon                                      12.5   \n",
       "42000 Pennsylvania                                 6.6   \n",
       "44000 Rhode Island                                14.0   \n",
       "46000 South Dakota                                 3.6   \n",
       "47000 Tennessee                                    5.0   \n",
       "49000 Utah                                        13.5   \n",
       "50000 Vermont                                      1.8   \n",
       "53000 Washington                                  12.2   \n",
       "54000 West Virginia                                1.5   \n",
       "55000 Wisconsin                                    6.5   \n",
       "56000 Wyoming                                      9.8   \n",
       "\n",
       "                     White alone, not Hispanic or Latino, percent, 2014  \\\n",
       "fips  area_name                                                           \n",
       "5000  Arkansas                                                    73.4    \n",
       "8000  Colorado                                                    69.0    \n",
       "9000  Connecticut                                                 68.8    \n",
       "16000 Idaho                                                       82.8    \n",
       "18000 Indiana                                                     80.3    \n",
       "19000 Iowa                                                        87.1    \n",
       "20000 Kansas                                                      76.8    \n",
       "21000 Kentucky                                                    85.4    \n",
       "23000 Maine                                                       93.8    \n",
       "25000 Massachusetts                                               74.3    \n",
       "26000 Michigan                                                    75.8    \n",
       "27000 Minnesota                                                   81.4    \n",
       "29000 Missouri                                                    80.1    \n",
       "30000 Montana                                                     86.7    \n",
       "31000 Nebraska                                                    80.5    \n",
       "33000 New Hampshire                                               91.3    \n",
       "38000 North Dakota                                                86.6    \n",
       "39000 Ohio                                                        80.1    \n",
       "40000 Oklahoma                                                    67.0    \n",
       "41000 Oregon                                                      77.0    \n",
       "42000 Pennsylvania                                                77.9    \n",
       "44000 Rhode Island                                                74.5    \n",
       "46000 South Dakota                                                83.0    \n",
       "47000 Tennessee                                                   74.6    \n",
       "49000 Utah                                                        79.3    \n",
       "50000 Vermont                                                     93.5    \n",
       "53000 Washington                                                  70.4    \n",
       "54000 West Virginia                                               92.5    \n",
       "55000 Wisconsin                                                   82.2    \n",
       "56000 Wyoming                                                     84.1    \n",
       "\n",
       "                     cluster  \n",
       "fips  area_name               \n",
       "5000  Arkansas             2  \n",
       "8000  Colorado             2  \n",
       "9000  Connecticut          2  \n",
       "16000 Idaho                2  \n",
       "18000 Indiana              2  \n",
       "19000 Iowa                 2  \n",
       "20000 Kansas               2  \n",
       "21000 Kentucky             2  \n",
       "23000 Maine                2  \n",
       "25000 Massachusetts        2  \n",
       "26000 Michigan             2  \n",
       "27000 Minnesota            2  \n",
       "29000 Missouri             2  \n",
       "30000 Montana              2  \n",
       "31000 Nebraska             2  \n",
       "33000 New Hampshire        2  \n",
       "38000 North Dakota         2  \n",
       "39000 Ohio                 2  \n",
       "40000 Oklahoma             2  \n",
       "41000 Oregon               2  \n",
       "42000 Pennsylvania         2  \n",
       "44000 Rhode Island         2  \n",
       "46000 South Dakota         2  \n",
       "47000 Tennessee            2  \n",
       "49000 Utah                 2  \n",
       "50000 Vermont              2  \n",
       "53000 Washington           2  \n",
       "54000 West Virginia        2  \n",
       "55000 Wisconsin            2  \n",
       "56000 Wyoming              2  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.cluster==2]"
   ]
  }
 ],
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