Merged_Zipcodes.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Code</th>\n",
       "      <th>Mean</th>\n",
       "      <th>Median</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11211</td>\n",
       "      <td>150.991682</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>182.400477</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10009</td>\n",
       "      <td>177.778549</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10003</td>\n",
       "      <td>220.328891</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11206</td>\n",
       "      <td>102.391970</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11238</td>\n",
       "      <td>144.082211</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11221</td>\n",
       "      <td>95.713076</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10011</td>\n",
       "      <td>242.854346</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11216</td>\n",
       "      <td>111.900207</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10014</td>\n",
       "      <td>252.500823</td>\n",
       "      <td>210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10019</td>\n",
       "      <td>229.525049</td>\n",
       "      <td>189.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10025</td>\n",
       "      <td>183.937929</td>\n",
       "      <td>145.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10012</td>\n",
       "      <td>255.219760</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11222</td>\n",
       "      <td>140.432536</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>11237</td>\n",
       "      <td>91.916442</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10036</td>\n",
       "      <td>218.437125</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10016</td>\n",
       "      <td>237.572914</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>11215</td>\n",
       "      <td>162.932613</td>\n",
       "      <td>139.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11249</td>\n",
       "      <td>176.330328</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10031</td>\n",
       "      <td>104.395633</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10027</td>\n",
       "      <td>128.709048</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11205</td>\n",
       "      <td>165.375414</td>\n",
       "      <td>115.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10029</td>\n",
       "      <td>126.461440</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>11217</td>\n",
       "      <td>165.974973</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10023</td>\n",
       "      <td>234.262821</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10024</td>\n",
       "      <td>205.716110</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11201</td>\n",
       "      <td>180.651959</td>\n",
       "      <td>155.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>10128</td>\n",
       "      <td>184.365154</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>11226</td>\n",
       "      <td>92.680582</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10013</td>\n",
       "      <td>294.459468</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Code        Mean  Median\n",
       "0      11211  150.991682   129.0\n",
       "1      10002  182.400477   150.0\n",
       "2      10009  177.778549   150.0\n",
       "3      10003  220.328891   180.0\n",
       "4      11206  102.391970    80.0\n",
       "5      11238  144.082211   120.0\n",
       "6      11221   95.713076    75.0\n",
       "7      10011  242.854346   200.0\n",
       "8      11216  111.900207    90.0\n",
       "9      10014  252.500823   210.0\n",
       "10     10019  229.525049   189.0\n",
       "11     10025  183.937929   145.0\n",
       "12     10012  255.219760   200.0\n",
       "13     11222  140.432536   120.0\n",
       "14     11237   91.916442    75.0\n",
       "15     10036  218.437125   175.0\n",
       "16     10016  237.572914   185.0\n",
       "17     11215  162.932613   139.0\n",
       "18     11249  176.330328   140.0\n",
       "19     10031  104.395633    80.0\n",
       "20     10027  128.709048   110.0\n",
       "21     11205  165.375414   115.0\n",
       "22     10029  126.461440   100.0\n",
       "23     11217  165.974973   140.0\n",
       "24     10023  234.262821   190.0\n",
       "25     10024  205.716110   175.0\n",
       "26     11201  180.651959   155.0\n",
       "27     10128  184.365154   150.0\n",
       "28     11226   92.680582    75.0\n",
       "29     10013  294.459468   185.0"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#Import 2016 CSV\n",
    "df_15 = pd.read_csv(\"2015_Top30zipcodes.csv\")\n",
    "\n",
    "#Remove random column\n",
    "df_2015 = df_15[['Zip Code','Mean', 'Median']]\n",
    "df_2015"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Code</th>\n",
       "      <th>Mean</th>\n",
       "      <th>Median</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11211</td>\n",
       "      <td>143.768193</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>168.815366</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11206</td>\n",
       "      <td>94.994238</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10009</td>\n",
       "      <td>165.071030</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11221</td>\n",
       "      <td>89.587325</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10003</td>\n",
       "      <td>218.895993</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11238</td>\n",
       "      <td>138.259867</td>\n",
       "      <td>106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>11216</td>\n",
       "      <td>110.022522</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11222</td>\n",
       "      <td>128.623164</td>\n",
       "      <td>109.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10025</td>\n",
       "      <td>158.431274</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10019</td>\n",
       "      <td>215.508512</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10011</td>\n",
       "      <td>225.796276</td>\n",
       "      <td>199.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>11237</td>\n",
       "      <td>86.114981</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10012</td>\n",
       "      <td>230.587597</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10014</td>\n",
       "      <td>239.303179</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10036</td>\n",
       "      <td>212.077208</td>\n",
       "      <td>165.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10031</td>\n",
       "      <td>99.883374</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>11215</td>\n",
       "      <td>150.024911</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10027</td>\n",
       "      <td>121.078350</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10016</td>\n",
       "      <td>214.245595</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10029</td>\n",
       "      <td>127.426550</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11249</td>\n",
       "      <td>172.929537</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>11205</td>\n",
       "      <td>154.145494</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>11217</td>\n",
       "      <td>164.352042</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>11225</td>\n",
       "      <td>94.748649</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>11226</td>\n",
       "      <td>84.754190</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11233</td>\n",
       "      <td>105.371874</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>10023</td>\n",
       "      <td>223.957771</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>10024</td>\n",
       "      <td>199.247779</td>\n",
       "      <td>165.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>11201</td>\n",
       "      <td>166.963918</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Code        Mean  Median\n",
       "0      11211  143.768193   119.0\n",
       "1      10002  168.815366   135.0\n",
       "2      11206   94.994238    75.0\n",
       "3      10009  165.071030   135.0\n",
       "4      11221   89.587325    70.0\n",
       "5      10003  218.895993   169.0\n",
       "6      11238  138.259867   106.0\n",
       "7      11216  110.022522    85.0\n",
       "8      11222  128.623164   109.0\n",
       "9      10025  158.431274   119.0\n",
       "10     10019  215.508512   175.0\n",
       "11     10011  225.796276   199.0\n",
       "12     11237   86.114981    69.0\n",
       "13     10012  230.587597   190.0\n",
       "14     10014  239.303179   200.0\n",
       "15     10036  212.077208   165.0\n",
       "16     10031   99.883374    75.0\n",
       "17     11215  150.024911   130.0\n",
       "18     10027  121.078350   100.0\n",
       "19     10016  214.245595   175.0\n",
       "20     10029  127.426550   100.0\n",
       "21     11249  172.929537   130.0\n",
       "22     11205  154.145494   100.0\n",
       "23     11217  164.352042   130.0\n",
       "24     11225   94.748649    80.0\n",
       "25     11226   84.754190    70.0\n",
       "26     11233  105.371874    95.0\n",
       "27     10023  223.957771   180.0\n",
       "28     10024  199.247779   165.0\n",
       "29     11201  166.963918   150.0"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Import 2016 CSV\n",
    "df_16 = pd.read_csv(\"2016_Top30zipcodes.csv\")\n",
    "\n",
    "#Remove random column\n",
    "df_2016 = df_16[['Zip Code','Mean', 'Median']]\n",
    "df_2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Code</th>\n",
       "      <th>Mean_2015</th>\n",
       "      <th>Median_2015</th>\n",
       "      <th>Mean_2016</th>\n",
       "      <th>Median_2016</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11211</td>\n",
       "      <td>150.991682</td>\n",
       "      <td>129.0</td>\n",
       "      <td>143.768193</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>182.400477</td>\n",
       "      <td>150.0</td>\n",
       "      <td>168.815366</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10009</td>\n",
       "      <td>177.778549</td>\n",
       "      <td>150.0</td>\n",
       "      <td>165.071030</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10003</td>\n",
       "      <td>220.328891</td>\n",
       "      <td>180.0</td>\n",
       "      <td>218.895993</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11206</td>\n",
       "      <td>102.391970</td>\n",
       "      <td>80.0</td>\n",
       "      <td>94.994238</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11238</td>\n",
       "      <td>144.082211</td>\n",
       "      <td>120.0</td>\n",
       "      <td>138.259867</td>\n",
       "      <td>106.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11221</td>\n",
       "      <td>95.713076</td>\n",
       "      <td>75.0</td>\n",
       "      <td>89.587325</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10011</td>\n",
       "      <td>242.854346</td>\n",
       "      <td>200.0</td>\n",
       "      <td>225.796276</td>\n",
       "      <td>199.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11216</td>\n",
       "      <td>111.900207</td>\n",
       "      <td>90.0</td>\n",
       "      <td>110.022522</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10014</td>\n",
       "      <td>252.500823</td>\n",
       "      <td>210.0</td>\n",
       "      <td>239.303179</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10019</td>\n",
       "      <td>229.525049</td>\n",
       "      <td>189.0</td>\n",
       "      <td>215.508512</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10025</td>\n",
       "      <td>183.937929</td>\n",
       "      <td>145.0</td>\n",
       "      <td>158.431274</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10012</td>\n",
       "      <td>255.219760</td>\n",
       "      <td>200.0</td>\n",
       "      <td>230.587597</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11222</td>\n",
       "      <td>140.432536</td>\n",
       "      <td>120.0</td>\n",
       "      <td>128.623164</td>\n",
       "      <td>109.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>11237</td>\n",
       "      <td>91.916442</td>\n",
       "      <td>75.0</td>\n",
       "      <td>86.114981</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10036</td>\n",
       "      <td>218.437125</td>\n",
       "      <td>175.0</td>\n",
       "      <td>212.077208</td>\n",
       "      <td>165.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10016</td>\n",
       "      <td>237.572914</td>\n",
       "      <td>185.0</td>\n",
       "      <td>214.245595</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>11215</td>\n",
       "      <td>162.932613</td>\n",
       "      <td>139.0</td>\n",
       "      <td>150.024911</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11249</td>\n",
       "      <td>176.330328</td>\n",
       "      <td>140.0</td>\n",
       "      <td>172.929537</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10031</td>\n",
       "      <td>104.395633</td>\n",
       "      <td>80.0</td>\n",
       "      <td>99.883374</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10027</td>\n",
       "      <td>128.709048</td>\n",
       "      <td>110.0</td>\n",
       "      <td>121.078350</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11205</td>\n",
       "      <td>165.375414</td>\n",
       "      <td>115.0</td>\n",
       "      <td>154.145494</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10029</td>\n",
       "      <td>126.461440</td>\n",
       "      <td>100.0</td>\n",
       "      <td>127.426550</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>11217</td>\n",
       "      <td>165.974973</td>\n",
       "      <td>140.0</td>\n",
       "      <td>164.352042</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10023</td>\n",
       "      <td>234.262821</td>\n",
       "      <td>190.0</td>\n",
       "      <td>223.957771</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10024</td>\n",
       "      <td>205.716110</td>\n",
       "      <td>175.0</td>\n",
       "      <td>199.247779</td>\n",
       "      <td>165.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11201</td>\n",
       "      <td>180.651959</td>\n",
       "      <td>155.0</td>\n",
       "      <td>166.963918</td>\n",
       "      <td>150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>10128</td>\n",
       "      <td>184.365154</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>11226</td>\n",
       "      <td>92.680582</td>\n",
       "      <td>75.0</td>\n",
       "      <td>84.754190</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10013</td>\n",
       "      <td>294.459468</td>\n",
       "      <td>185.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>11225</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.748649</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>11233</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.371874</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Code   Mean_2015  Median_2015   Mean_2016  Median_2016\n",
       "0      11211  150.991682        129.0  143.768193        119.0\n",
       "1      10002  182.400477        150.0  168.815366        135.0\n",
       "2      10009  177.778549        150.0  165.071030        135.0\n",
       "3      10003  220.328891        180.0  218.895993        169.0\n",
       "4      11206  102.391970         80.0   94.994238         75.0\n",
       "5      11238  144.082211        120.0  138.259867        106.0\n",
       "6      11221   95.713076         75.0   89.587325         70.0\n",
       "7      10011  242.854346        200.0  225.796276        199.0\n",
       "8      11216  111.900207         90.0  110.022522         85.0\n",
       "9      10014  252.500823        210.0  239.303179        200.0\n",
       "10     10019  229.525049        189.0  215.508512        175.0\n",
       "11     10025  183.937929        145.0  158.431274        119.0\n",
       "12     10012  255.219760        200.0  230.587597        190.0\n",
       "13     11222  140.432536        120.0  128.623164        109.0\n",
       "14     11237   91.916442         75.0   86.114981         69.0\n",
       "15     10036  218.437125        175.0  212.077208        165.0\n",
       "16     10016  237.572914        185.0  214.245595        175.0\n",
       "17     11215  162.932613        139.0  150.024911        130.0\n",
       "18     11249  176.330328        140.0  172.929537        130.0\n",
       "19     10031  104.395633         80.0   99.883374         75.0\n",
       "20     10027  128.709048        110.0  121.078350        100.0\n",
       "21     11205  165.375414        115.0  154.145494        100.0\n",
       "22     10029  126.461440        100.0  127.426550        100.0\n",
       "23     11217  165.974973        140.0  164.352042        130.0\n",
       "24     10023  234.262821        190.0  223.957771        180.0\n",
       "25     10024  205.716110        175.0  199.247779        165.0\n",
       "26     11201  180.651959        155.0  166.963918        150.0\n",
       "27     10128  184.365154        150.0         NaN          NaN\n",
       "28     11226   92.680582         75.0   84.754190         70.0\n",
       "29     10013  294.459468        185.0         NaN          NaN\n",
       "30     11225         NaN          NaN   94.748649         80.0\n",
       "31     11233         NaN          NaN  105.371874         95.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merge 2015 and 2016\n",
    "df_1516 = pd.merge(df_2015, df_2016, on=\"Zip Code\", how=\"outer\", suffixes=(\"_2015\", \"_2016\"))\n",
    "df_1516"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Code</th>\n",
       "      <th>Mean</th>\n",
       "      <th>Median</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11211</td>\n",
       "      <td>145.759296</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11221</td>\n",
       "      <td>88.334267</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11206</td>\n",
       "      <td>94.821426</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11216</td>\n",
       "      <td>107.358035</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10002</td>\n",
       "      <td>174.141667</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10009</td>\n",
       "      <td>166.544186</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11238</td>\n",
       "      <td>135.210127</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10003</td>\n",
       "      <td>220.491229</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11222</td>\n",
       "      <td>124.135188</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10019</td>\n",
       "      <td>215.059272</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11237</td>\n",
       "      <td>80.728763</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10025</td>\n",
       "      <td>166.183255</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10011</td>\n",
       "      <td>225.691729</td>\n",
       "      <td>195.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10031</td>\n",
       "      <td>95.558082</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10027</td>\n",
       "      <td>135.229297</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>11215</td>\n",
       "      <td>144.884473</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10036</td>\n",
       "      <td>213.932102</td>\n",
       "      <td>168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10029</td>\n",
       "      <td>129.885366</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10014</td>\n",
       "      <td>244.652423</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10012</td>\n",
       "      <td>224.176746</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>11249</td>\n",
       "      <td>170.654236</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11205</td>\n",
       "      <td>140.440341</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>11233</td>\n",
       "      <td>100.719001</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>10016</td>\n",
       "      <td>215.009782</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>11225</td>\n",
       "      <td>95.294381</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>11226</td>\n",
       "      <td>85.103783</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11217</td>\n",
       "      <td>163.994170</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>11201</td>\n",
       "      <td>174.439658</td>\n",
       "      <td>145.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>10032</td>\n",
       "      <td>92.665028</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10023</td>\n",
       "      <td>219.792201</td>\n",
       "      <td>182.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Code        Mean  Median\n",
       "0      11211  145.759296   113.0\n",
       "1      11221   88.334267    69.0\n",
       "2      11206   94.821426    75.0\n",
       "3      11216  107.358035    85.0\n",
       "4      10002  174.141667   129.0\n",
       "5      10009  166.544186   135.0\n",
       "6      11238  135.210127   100.0\n",
       "7      10003  220.491229   160.0\n",
       "8      11222  124.135188   100.0\n",
       "9      10019  215.059272   170.0\n",
       "10     11237   80.728763    65.0\n",
       "11     10025  166.183255   110.0\n",
       "12     10011  225.691729   195.0\n",
       "13     10031   95.558082    75.0\n",
       "14     10027  135.229297   100.0\n",
       "15     11215  144.884473   129.0\n",
       "16     10036  213.932102   168.0\n",
       "17     10029  129.885366    98.0\n",
       "18     10014  244.652423   200.0\n",
       "19     10012  224.176746   185.0\n",
       "20     11249  170.654236   135.0\n",
       "21     11205  140.440341    99.0\n",
       "22     11233  100.719001    80.0\n",
       "23     10016  215.009782   170.0\n",
       "24     11225   95.294381    80.0\n",
       "25     11226   85.103783    69.0\n",
       "26     11217  163.994170   130.0\n",
       "27     11201  174.439658   145.0\n",
       "28     10032   92.665028    70.0\n",
       "29     10023  219.792201   182.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Import 2017 CSV\n",
    "df_2017 = pd.read_csv('2017_Top30codes')\n",
    "df_2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Code</th>\n",
       "      <th>Mean_2015</th>\n",
       "      <th>Median_2015</th>\n",
       "      <th>Mean_2016</th>\n",
       "      <th>Median_2016</th>\n",
       "      <th>Mean</th>\n",
       "      <th>Median</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11211</td>\n",
       "      <td>150.991682</td>\n",
       "      <td>129.0</td>\n",
       "      <td>143.768193</td>\n",
       "      <td>119.0</td>\n",
       "      <td>145.759296</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>182.400477</td>\n",
       "      <td>150.0</td>\n",
       "      <td>168.815366</td>\n",
       "      <td>135.0</td>\n",
       "      <td>174.141667</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10009</td>\n",
       "      <td>177.778549</td>\n",
       "      <td>150.0</td>\n",
       "      <td>165.071030</td>\n",
       "      <td>135.0</td>\n",
       "      <td>166.544186</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10003</td>\n",
       "      <td>220.328891</td>\n",
       "      <td>180.0</td>\n",
       "      <td>218.895993</td>\n",
       "      <td>169.0</td>\n",
       "      <td>220.491229</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11206</td>\n",
       "      <td>102.391970</td>\n",
       "      <td>80.0</td>\n",
       "      <td>94.994238</td>\n",
       "      <td>75.0</td>\n",
       "      <td>94.821426</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11238</td>\n",
       "      <td>144.082211</td>\n",
       "      <td>120.0</td>\n",
       "      <td>138.259867</td>\n",
       "      <td>106.0</td>\n",
       "      <td>135.210127</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11221</td>\n",
       "      <td>95.713076</td>\n",
       "      <td>75.0</td>\n",
       "      <td>89.587325</td>\n",
       "      <td>70.0</td>\n",
       "      <td>88.334267</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10011</td>\n",
       "      <td>242.854346</td>\n",
       "      <td>200.0</td>\n",
       "      <td>225.796276</td>\n",
       "      <td>199.0</td>\n",
       "      <td>225.691729</td>\n",
       "      <td>195.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11216</td>\n",
       "      <td>111.900207</td>\n",
       "      <td>90.0</td>\n",
       "      <td>110.022522</td>\n",
       "      <td>85.0</td>\n",
       "      <td>107.358035</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10014</td>\n",
       "      <td>252.500823</td>\n",
       "      <td>210.0</td>\n",
       "      <td>239.303179</td>\n",
       "      <td>200.0</td>\n",
       "      <td>244.652423</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10019</td>\n",
       "      <td>229.525049</td>\n",
       "      <td>189.0</td>\n",
       "      <td>215.508512</td>\n",
       "      <td>175.0</td>\n",
       "      <td>215.059272</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10025</td>\n",
       "      <td>183.937929</td>\n",
       "      <td>145.0</td>\n",
       "      <td>158.431274</td>\n",
       "      <td>119.0</td>\n",
       "      <td>166.183255</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10012</td>\n",
       "      <td>255.219760</td>\n",
       "      <td>200.0</td>\n",
       "      <td>230.587597</td>\n",
       "      <td>190.0</td>\n",
       "      <td>224.176746</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11222</td>\n",
       "      <td>140.432536</td>\n",
       "      <td>120.0</td>\n",
       "      <td>128.623164</td>\n",
       "      <td>109.0</td>\n",
       "      <td>124.135188</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>11237</td>\n",
       "      <td>91.916442</td>\n",
       "      <td>75.0</td>\n",
       "      <td>86.114981</td>\n",
       "      <td>69.0</td>\n",
       "      <td>80.728763</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10036</td>\n",
       "      <td>218.437125</td>\n",
       "      <td>175.0</td>\n",
       "      <td>212.077208</td>\n",
       "      <td>165.0</td>\n",
       "      <td>213.932102</td>\n",
       "      <td>168.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10016</td>\n",
       "      <td>237.572914</td>\n",
       "      <td>185.0</td>\n",
       "      <td>214.245595</td>\n",
       "      <td>175.0</td>\n",
       "      <td>215.009782</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>11215</td>\n",
       "      <td>162.932613</td>\n",
       "      <td>139.0</td>\n",
       "      <td>150.024911</td>\n",
       "      <td>130.0</td>\n",
       "      <td>144.884473</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11249</td>\n",
       "      <td>176.330328</td>\n",
       "      <td>140.0</td>\n",
       "      <td>172.929537</td>\n",
       "      <td>130.0</td>\n",
       "      <td>170.654236</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10031</td>\n",
       "      <td>104.395633</td>\n",
       "      <td>80.0</td>\n",
       "      <td>99.883374</td>\n",
       "      <td>75.0</td>\n",
       "      <td>95.558082</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10027</td>\n",
       "      <td>128.709048</td>\n",
       "      <td>110.0</td>\n",
       "      <td>121.078350</td>\n",
       "      <td>100.0</td>\n",
       "      <td>135.229297</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11205</td>\n",
       "      <td>165.375414</td>\n",
       "      <td>115.0</td>\n",
       "      <td>154.145494</td>\n",
       "      <td>100.0</td>\n",
       "      <td>140.440341</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10029</td>\n",
       "      <td>126.461440</td>\n",
       "      <td>100.0</td>\n",
       "      <td>127.426550</td>\n",
       "      <td>100.0</td>\n",
       "      <td>129.885366</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>11217</td>\n",
       "      <td>165.974973</td>\n",
       "      <td>140.0</td>\n",
       "      <td>164.352042</td>\n",
       "      <td>130.0</td>\n",
       "      <td>163.994170</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10023</td>\n",
       "      <td>234.262821</td>\n",
       "      <td>190.0</td>\n",
       "      <td>223.957771</td>\n",
       "      <td>180.0</td>\n",
       "      <td>219.792201</td>\n",
       "      <td>182.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10024</td>\n",
       "      <td>205.716110</td>\n",
       "      <td>175.0</td>\n",
       "      <td>199.247779</td>\n",
       "      <td>165.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11201</td>\n",
       "      <td>180.651959</td>\n",
       "      <td>155.0</td>\n",
       "      <td>166.963918</td>\n",
       "      <td>150.0</td>\n",
       "      <td>174.439658</td>\n",
       "      <td>145.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>10128</td>\n",
       "      <td>184.365154</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>11226</td>\n",
       "      <td>92.680582</td>\n",
       "      <td>75.0</td>\n",
       "      <td>84.754190</td>\n",
       "      <td>70.0</td>\n",
       "      <td>85.103783</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10013</td>\n",
       "      <td>294.459468</td>\n",
       "      <td>185.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>11225</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.748649</td>\n",
       "      <td>80.0</td>\n",
       "      <td>95.294381</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>11233</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.371874</td>\n",
       "      <td>95.0</td>\n",
       "      <td>100.719001</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>10032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92.665028</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Code   Mean_2015  Median_2015   Mean_2016  Median_2016        Mean  \\\n",
       "0      11211  150.991682        129.0  143.768193        119.0  145.759296   \n",
       "1      10002  182.400477        150.0  168.815366        135.0  174.141667   \n",
       "2      10009  177.778549        150.0  165.071030        135.0  166.544186   \n",
       "3      10003  220.328891        180.0  218.895993        169.0  220.491229   \n",
       "4      11206  102.391970         80.0   94.994238         75.0   94.821426   \n",
       "5      11238  144.082211        120.0  138.259867        106.0  135.210127   \n",
       "6      11221   95.713076         75.0   89.587325         70.0   88.334267   \n",
       "7      10011  242.854346        200.0  225.796276        199.0  225.691729   \n",
       "8      11216  111.900207         90.0  110.022522         85.0  107.358035   \n",
       "9      10014  252.500823        210.0  239.303179        200.0  244.652423   \n",
       "10     10019  229.525049        189.0  215.508512        175.0  215.059272   \n",
       "11     10025  183.937929        145.0  158.431274        119.0  166.183255   \n",
       "12     10012  255.219760        200.0  230.587597        190.0  224.176746   \n",
       "13     11222  140.432536        120.0  128.623164        109.0  124.135188   \n",
       "14     11237   91.916442         75.0   86.114981         69.0   80.728763   \n",
       "15     10036  218.437125        175.0  212.077208        165.0  213.932102   \n",
       "16     10016  237.572914        185.0  214.245595        175.0  215.009782   \n",
       "17     11215  162.932613        139.0  150.024911        130.0  144.884473   \n",
       "18     11249  176.330328        140.0  172.929537        130.0  170.654236   \n",
       "19     10031  104.395633         80.0   99.883374         75.0   95.558082   \n",
       "20     10027  128.709048        110.0  121.078350        100.0  135.229297   \n",
       "21     11205  165.375414        115.0  154.145494        100.0  140.440341   \n",
       "22     10029  126.461440        100.0  127.426550        100.0  129.885366   \n",
       "23     11217  165.974973        140.0  164.352042        130.0  163.994170   \n",
       "24     10023  234.262821        190.0  223.957771        180.0  219.792201   \n",
       "25     10024  205.716110        175.0  199.247779        165.0         NaN   \n",
       "26     11201  180.651959        155.0  166.963918        150.0  174.439658   \n",
       "27     10128  184.365154        150.0         NaN          NaN         NaN   \n",
       "28     11226   92.680582         75.0   84.754190         70.0   85.103783   \n",
       "29     10013  294.459468        185.0         NaN          NaN         NaN   \n",
       "30     11225         NaN          NaN   94.748649         80.0   95.294381   \n",
       "31     11233         NaN          NaN  105.371874         95.0  100.719001   \n",
       "32     10032         NaN          NaN         NaN          NaN   92.665028   \n",
       "\n",
       "    Median  \n",
       "0    113.0  \n",
       "1    129.0  \n",
       "2    135.0  \n",
       "3    160.0  \n",
       "4     75.0  \n",
       "5    100.0  \n",
       "6     69.0  \n",
       "7    195.0  \n",
       "8     85.0  \n",
       "9    200.0  \n",
       "10   170.0  \n",
       "11   110.0  \n",
       "12   185.0  \n",
       "13   100.0  \n",
       "14    65.0  \n",
       "15   168.0  \n",
       "16   170.0  \n",
       "17   129.0  \n",
       "18   135.0  \n",
       "19    75.0  \n",
       "20   100.0  \n",
       "21    99.0  \n",
       "22    98.0  \n",
       "23   130.0  \n",
       "24   182.0  \n",
       "25     NaN  \n",
       "26   145.0  \n",
       "27     NaN  \n",
       "28    69.0  \n",
       "29     NaN  \n",
       "30    80.0  \n",
       "31    80.0  \n",
       "32    70.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merge 2015/2016 with 2017\n",
    "df_151617 = pd.merge(df_1516, df_2017, on=\"Zip Code\", how=\"outer\")\n",
    "df_151617\n",
    "#df_151617.rename(columns={'Mean': 'Mean_2017', 'Median': 'Median_2017'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Code</th>\n",
       "      <th>Mean</th>\n",
       "      <th>Median</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11211</td>\n",
       "      <td>146.840053</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11221</td>\n",
       "      <td>87.629931</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11206</td>\n",
       "      <td>96.825835</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11216</td>\n",
       "      <td>110.636435</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10002</td>\n",
       "      <td>171.128160</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10019</td>\n",
       "      <td>228.574660</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10009</td>\n",
       "      <td>170.691880</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>11238</td>\n",
       "      <td>137.844509</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10003</td>\n",
       "      <td>223.038827</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>11222</td>\n",
       "      <td>135.671584</td>\n",
       "      <td>109.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10025</td>\n",
       "      <td>166.790625</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>11237</td>\n",
       "      <td>79.219594</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10036</td>\n",
       "      <td>215.999462</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11215</td>\n",
       "      <td>147.097090</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10027</td>\n",
       "      <td>135.707510</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10016</td>\n",
       "      <td>219.999161</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10031</td>\n",
       "      <td>98.003266</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10011</td>\n",
       "      <td>235.382632</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11249</td>\n",
       "      <td>168.045567</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>11233</td>\n",
       "      <td>99.172214</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10012</td>\n",
       "      <td>226.860020</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>10014</td>\n",
       "      <td>256.992884</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10029</td>\n",
       "      <td>140.572068</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>11205</td>\n",
       "      <td>140.647674</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>11226</td>\n",
       "      <td>85.033461</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>11225</td>\n",
       "      <td>100.770975</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11217</td>\n",
       "      <td>162.188512</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>11213</td>\n",
       "      <td>109.699475</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>10023</td>\n",
       "      <td>219.262169</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10024</td>\n",
       "      <td>195.559349</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Code        Mean  Median\n",
       "0      11211  146.840053   110.0\n",
       "1      11221   87.629931    68.0\n",
       "2      11206   96.825835    75.0\n",
       "3      11216  110.636435    85.0\n",
       "4      10002  171.128160   130.0\n",
       "5      10019  228.574660   180.0\n",
       "6      10009  170.691880   140.0\n",
       "7      11238  137.844509   105.0\n",
       "8      10003  223.038827   169.0\n",
       "9      11222  135.671584   109.5\n",
       "10     10025  166.790625   110.0\n",
       "11     11237   79.219594    65.0\n",
       "12     10036  215.999462   170.0\n",
       "13     11215  147.097090   129.0\n",
       "14     10027  135.707510   100.0\n",
       "15     10016  219.999161   175.0\n",
       "16     10031   98.003266    75.0\n",
       "17     10011  235.382632   190.0\n",
       "18     11249  168.045567   135.0\n",
       "19     11233   99.172214    80.0\n",
       "20     10012  226.860020   185.0\n",
       "21     10014  256.992884   200.0\n",
       "22     10029  140.572068    95.0\n",
       "23     11205  140.647674    99.0\n",
       "24     11226   85.033461    69.0\n",
       "25     11225  100.770975    83.0\n",
       "26     11217  162.188512   130.0\n",
       "27     11213  109.699475    77.0\n",
       "28     10023  219.262169   180.0\n",
       "29     10024  195.559349   159.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Import 2018 CSV\n",
    "df_18 = pd.read_csv('2018_Top30zipcodes_edited.csv')\n",
    "\n",
    "#Remove random column\n",
    "df_2018 = df_18[['Zip Code','Mean', 'Median']]\n",
    "df_2018\n",
    "\n",
    "df_2018\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Code</th>\n",
       "      <th>Mean_2015</th>\n",
       "      <th>Median_2015</th>\n",
       "      <th>Mean_2016</th>\n",
       "      <th>Median_2016</th>\n",
       "      <th>Mean_2017</th>\n",
       "      <th>Median_2017</th>\n",
       "      <th>Mean_2018</th>\n",
       "      <th>Median_2018</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11211</td>\n",
       "      <td>150.991682</td>\n",
       "      <td>129.0</td>\n",
       "      <td>143.768193</td>\n",
       "      <td>119.0</td>\n",
       "      <td>145.759296</td>\n",
       "      <td>113.0</td>\n",
       "      <td>146.840053</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10002</td>\n",
       "      <td>182.400477</td>\n",
       "      <td>150.0</td>\n",
       "      <td>168.815366</td>\n",
       "      <td>135.0</td>\n",
       "      <td>174.141667</td>\n",
       "      <td>129.0</td>\n",
       "      <td>171.128160</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10009</td>\n",
       "      <td>177.778549</td>\n",
       "      <td>150.0</td>\n",
       "      <td>165.071030</td>\n",
       "      <td>135.0</td>\n",
       "      <td>166.544186</td>\n",
       "      <td>135.0</td>\n",
       "      <td>170.691880</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10003</td>\n",
       "      <td>220.328891</td>\n",
       "      <td>180.0</td>\n",
       "      <td>218.895993</td>\n",
       "      <td>169.0</td>\n",
       "      <td>220.491229</td>\n",
       "      <td>160.0</td>\n",
       "      <td>223.038827</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11206</td>\n",
       "      <td>102.391970</td>\n",
       "      <td>80.0</td>\n",
       "      <td>94.994238</td>\n",
       "      <td>75.0</td>\n",
       "      <td>94.821426</td>\n",
       "      <td>75.0</td>\n",
       "      <td>96.825835</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11238</td>\n",
       "      <td>144.082211</td>\n",
       "      <td>120.0</td>\n",
       "      <td>138.259867</td>\n",
       "      <td>106.0</td>\n",
       "      <td>135.210127</td>\n",
       "      <td>100.0</td>\n",
       "      <td>137.844509</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>11221</td>\n",
       "      <td>95.713076</td>\n",
       "      <td>75.0</td>\n",
       "      <td>89.587325</td>\n",
       "      <td>70.0</td>\n",
       "      <td>88.334267</td>\n",
       "      <td>69.0</td>\n",
       "      <td>87.629931</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10011</td>\n",
       "      <td>242.854346</td>\n",
       "      <td>200.0</td>\n",
       "      <td>225.796276</td>\n",
       "      <td>199.0</td>\n",
       "      <td>225.691729</td>\n",
       "      <td>195.0</td>\n",
       "      <td>235.382632</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11216</td>\n",
       "      <td>111.900207</td>\n",
       "      <td>90.0</td>\n",
       "      <td>110.022522</td>\n",
       "      <td>85.0</td>\n",
       "      <td>107.358035</td>\n",
       "      <td>85.0</td>\n",
       "      <td>110.636435</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10014</td>\n",
       "      <td>252.500823</td>\n",
       "      <td>210.0</td>\n",
       "      <td>239.303179</td>\n",
       "      <td>200.0</td>\n",
       "      <td>244.652423</td>\n",
       "      <td>200.0</td>\n",
       "      <td>256.992884</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10019</td>\n",
       "      <td>229.525049</td>\n",
       "      <td>189.0</td>\n",
       "      <td>215.508512</td>\n",
       "      <td>175.0</td>\n",
       "      <td>215.059272</td>\n",
       "      <td>170.0</td>\n",
       "      <td>228.574660</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10025</td>\n",
       "      <td>183.937929</td>\n",
       "      <td>145.0</td>\n",
       "      <td>158.431274</td>\n",
       "      <td>119.0</td>\n",
       "      <td>166.183255</td>\n",
       "      <td>110.0</td>\n",
       "      <td>166.790625</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10012</td>\n",
       "      <td>255.219760</td>\n",
       "      <td>200.0</td>\n",
       "      <td>230.587597</td>\n",
       "      <td>190.0</td>\n",
       "      <td>224.176746</td>\n",
       "      <td>185.0</td>\n",
       "      <td>226.860020</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11222</td>\n",
       "      <td>140.432536</td>\n",
       "      <td>120.0</td>\n",
       "      <td>128.623164</td>\n",
       "      <td>109.0</td>\n",
       "      <td>124.135188</td>\n",
       "      <td>100.0</td>\n",
       "      <td>135.671584</td>\n",
       "      <td>109.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>11237</td>\n",
       "      <td>91.916442</td>\n",
       "      <td>75.0</td>\n",
       "      <td>86.114981</td>\n",
       "      <td>69.0</td>\n",
       "      <td>80.728763</td>\n",
       "      <td>65.0</td>\n",
       "      <td>79.219594</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10036</td>\n",
       "      <td>218.437125</td>\n",
       "      <td>175.0</td>\n",
       "      <td>212.077208</td>\n",
       "      <td>165.0</td>\n",
       "      <td>213.932102</td>\n",
       "      <td>168.0</td>\n",
       "      <td>215.999462</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10016</td>\n",
       "      <td>237.572914</td>\n",
       "      <td>185.0</td>\n",
       "      <td>214.245595</td>\n",
       "      <td>175.0</td>\n",
       "      <td>215.009782</td>\n",
       "      <td>170.0</td>\n",
       "      <td>219.999161</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>11215</td>\n",
       "      <td>162.932613</td>\n",
       "      <td>139.0</td>\n",
       "      <td>150.024911</td>\n",
       "      <td>130.0</td>\n",
       "      <td>144.884473</td>\n",
       "      <td>129.0</td>\n",
       "      <td>147.097090</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>11249</td>\n",
       "      <td>176.330328</td>\n",
       "      <td>140.0</td>\n",
       "      <td>172.929537</td>\n",
       "      <td>130.0</td>\n",
       "      <td>170.654236</td>\n",
       "      <td>135.0</td>\n",
       "      <td>168.045567</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10031</td>\n",
       "      <td>104.395633</td>\n",
       "      <td>80.0</td>\n",
       "      <td>99.883374</td>\n",
       "      <td>75.0</td>\n",
       "      <td>95.558082</td>\n",
       "      <td>75.0</td>\n",
       "      <td>98.003266</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>10027</td>\n",
       "      <td>128.709048</td>\n",
       "      <td>110.0</td>\n",
       "      <td>121.078350</td>\n",
       "      <td>100.0</td>\n",
       "      <td>135.229297</td>\n",
       "      <td>100.0</td>\n",
       "      <td>135.707510</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11205</td>\n",
       "      <td>165.375414</td>\n",
       "      <td>115.0</td>\n",
       "      <td>154.145494</td>\n",
       "      <td>100.0</td>\n",
       "      <td>140.440341</td>\n",
       "      <td>99.0</td>\n",
       "      <td>140.647674</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>10029</td>\n",
       "      <td>126.461440</td>\n",
       "      <td>100.0</td>\n",
       "      <td>127.426550</td>\n",
       "      <td>100.0</td>\n",
       "      <td>129.885366</td>\n",
       "      <td>98.0</td>\n",
       "      <td>140.572068</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>11217</td>\n",
       "      <td>165.974973</td>\n",
       "      <td>140.0</td>\n",
       "      <td>164.352042</td>\n",
       "      <td>130.0</td>\n",
       "      <td>163.994170</td>\n",
       "      <td>130.0</td>\n",
       "      <td>162.188512</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10023</td>\n",
       "      <td>234.262821</td>\n",
       "      <td>190.0</td>\n",
       "      <td>223.957771</td>\n",
       "      <td>180.0</td>\n",
       "      <td>219.792201</td>\n",
       "      <td>182.0</td>\n",
       "      <td>219.262169</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10024</td>\n",
       "      <td>205.716110</td>\n",
       "      <td>175.0</td>\n",
       "      <td>199.247779</td>\n",
       "      <td>165.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>195.559349</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11201</td>\n",
       "      <td>180.651959</td>\n",
       "      <td>155.0</td>\n",
       "      <td>166.963918</td>\n",
       "      <td>150.0</td>\n",
       "      <td>174.439658</td>\n",
       "      <td>145.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>10128</td>\n",
       "      <td>184.365154</td>\n",
       "      <td>150.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>11226</td>\n",
       "      <td>92.680582</td>\n",
       "      <td>75.0</td>\n",
       "      <td>84.754190</td>\n",
       "      <td>70.0</td>\n",
       "      <td>85.103783</td>\n",
       "      <td>69.0</td>\n",
       "      <td>85.033461</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>10013</td>\n",
       "      <td>294.459468</td>\n",
       "      <td>185.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>11225</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>94.748649</td>\n",
       "      <td>80.0</td>\n",
       "      <td>95.294381</td>\n",
       "      <td>80.0</td>\n",
       "      <td>100.770975</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>11233</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.371874</td>\n",
       "      <td>95.0</td>\n",
       "      <td>100.719001</td>\n",
       "      <td>80.0</td>\n",
       "      <td>99.172214</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>10032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>92.665028</td>\n",
       "      <td>70.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>11213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>109.699475</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Code   Mean_2015  Median_2015   Mean_2016  Median_2016   Mean_2017  \\\n",
       "0      11211  150.991682        129.0  143.768193        119.0  145.759296   \n",
       "1      10002  182.400477        150.0  168.815366        135.0  174.141667   \n",
       "2      10009  177.778549        150.0  165.071030        135.0  166.544186   \n",
       "3      10003  220.328891        180.0  218.895993        169.0  220.491229   \n",
       "4      11206  102.391970         80.0   94.994238         75.0   94.821426   \n",
       "5      11238  144.082211        120.0  138.259867        106.0  135.210127   \n",
       "6      11221   95.713076         75.0   89.587325         70.0   88.334267   \n",
       "7      10011  242.854346        200.0  225.796276        199.0  225.691729   \n",
       "8      11216  111.900207         90.0  110.022522         85.0  107.358035   \n",
       "9      10014  252.500823        210.0  239.303179        200.0  244.652423   \n",
       "10     10019  229.525049        189.0  215.508512        175.0  215.059272   \n",
       "11     10025  183.937929        145.0  158.431274        119.0  166.183255   \n",
       "12     10012  255.219760        200.0  230.587597        190.0  224.176746   \n",
       "13     11222  140.432536        120.0  128.623164        109.0  124.135188   \n",
       "14     11237   91.916442         75.0   86.114981         69.0   80.728763   \n",
       "15     10036  218.437125        175.0  212.077208        165.0  213.932102   \n",
       "16     10016  237.572914        185.0  214.245595        175.0  215.009782   \n",
       "17     11215  162.932613        139.0  150.024911        130.0  144.884473   \n",
       "18     11249  176.330328        140.0  172.929537        130.0  170.654236   \n",
       "19     10031  104.395633         80.0   99.883374         75.0   95.558082   \n",
       "20     10027  128.709048        110.0  121.078350        100.0  135.229297   \n",
       "21     11205  165.375414        115.0  154.145494        100.0  140.440341   \n",
       "22     10029  126.461440        100.0  127.426550        100.0  129.885366   \n",
       "23     11217  165.974973        140.0  164.352042        130.0  163.994170   \n",
       "24     10023  234.262821        190.0  223.957771        180.0  219.792201   \n",
       "25     10024  205.716110        175.0  199.247779        165.0         NaN   \n",
       "26     11201  180.651959        155.0  166.963918        150.0  174.439658   \n",
       "27     10128  184.365154        150.0         NaN          NaN         NaN   \n",
       "28     11226   92.680582         75.0   84.754190         70.0   85.103783   \n",
       "29     10013  294.459468        185.0         NaN          NaN         NaN   \n",
       "30     11225         NaN          NaN   94.748649         80.0   95.294381   \n",
       "31     11233         NaN          NaN  105.371874         95.0  100.719001   \n",
       "32     10032         NaN          NaN         NaN          NaN   92.665028   \n",
       "33     11213         NaN          NaN         NaN          NaN         NaN   \n",
       "\n",
       "    Median_2017   Mean_2018  Median_2018  \n",
       "0         113.0  146.840053        110.0  \n",
       "1         129.0  171.128160        130.0  \n",
       "2         135.0  170.691880        140.0  \n",
       "3         160.0  223.038827        169.0  \n",
       "4          75.0   96.825835         75.0  \n",
       "5         100.0  137.844509        105.0  \n",
       "6          69.0   87.629931         68.0  \n",
       "7         195.0  235.382632        190.0  \n",
       "8          85.0  110.636435         85.0  \n",
       "9         200.0  256.992884        200.0  \n",
       "10        170.0  228.574660        180.0  \n",
       "11        110.0  166.790625        110.0  \n",
       "12        185.0  226.860020        185.0  \n",
       "13        100.0  135.671584        109.5  \n",
       "14         65.0   79.219594         65.0  \n",
       "15        168.0  215.999462        170.0  \n",
       "16        170.0  219.999161        175.0  \n",
       "17        129.0  147.097090        129.0  \n",
       "18        135.0  168.045567        135.0  \n",
       "19         75.0   98.003266         75.0  \n",
       "20        100.0  135.707510        100.0  \n",
       "21         99.0  140.647674         99.0  \n",
       "22         98.0  140.572068         95.0  \n",
       "23        130.0  162.188512        130.0  \n",
       "24        182.0  219.262169        180.0  \n",
       "25          NaN  195.559349        159.0  \n",
       "26        145.0         NaN          NaN  \n",
       "27          NaN         NaN          NaN  \n",
       "28         69.0   85.033461         69.0  \n",
       "29          NaN         NaN          NaN  \n",
       "30         80.0  100.770975         83.0  \n",
       "31         80.0   99.172214         80.0  \n",
       "32         70.0         NaN          NaN  \n",
       "33          NaN  109.699475         77.0  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merge 2015/2016/2017 with 2018\n",
    "df_15161718 = pd.merge(df_151617, df_2018, on=\"Zip Code\", how=\"outer\", suffixes=(\"_2017\",\"_2018\"))\n",
    "df_15161718"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_15161718.to_csv('Merged_Top30codes.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Zip Codes</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Mean_2015</th>\n",
       "      <th>Median_2015</th>\n",
       "      <th>Mean_2016</th>\n",
       "      <th>Median_2016</th>\n",
       "      <th>Mean_2017</th>\n",
       "      <th>Median_2017</th>\n",
       "      <th>Mean_2018</th>\n",
       "      <th>Median_2018</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11206</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick and Williamsburg</td>\n",
       "      <td>102.391970</td>\n",
       "      <td>80</td>\n",
       "      <td>94.994238</td>\n",
       "      <td>75</td>\n",
       "      <td>94.821426</td>\n",
       "      <td>75</td>\n",
       "      <td>96.825835</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11221</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick and Williamsburg</td>\n",
       "      <td>95.713076</td>\n",
       "      <td>75</td>\n",
       "      <td>89.587325</td>\n",
       "      <td>70</td>\n",
       "      <td>88.334267</td>\n",
       "      <td>69</td>\n",
       "      <td>87.629931</td>\n",
       "      <td>68.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11237</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Bushwick and Williamsburg</td>\n",
       "      <td>91.916442</td>\n",
       "      <td>75</td>\n",
       "      <td>86.114981</td>\n",
       "      <td>69</td>\n",
       "      <td>80.728763</td>\n",
       "      <td>65</td>\n",
       "      <td>79.219594</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11216</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Central Brooklyn</td>\n",
       "      <td>111.900207</td>\n",
       "      <td>90</td>\n",
       "      <td>110.022522</td>\n",
       "      <td>85</td>\n",
       "      <td>107.358035</td>\n",
       "      <td>85</td>\n",
       "      <td>110.636435</td>\n",
       "      <td>85.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11238</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Central Brooklyn</td>\n",
       "      <td>144.082211</td>\n",
       "      <td>120</td>\n",
       "      <td>138.259867</td>\n",
       "      <td>106</td>\n",
       "      <td>135.210127</td>\n",
       "      <td>100</td>\n",
       "      <td>137.844509</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10027</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Central Harlem</td>\n",
       "      <td>128.709048</td>\n",
       "      <td>110</td>\n",
       "      <td>121.078350</td>\n",
       "      <td>100</td>\n",
       "      <td>135.229297</td>\n",
       "      <td>100</td>\n",
       "      <td>135.707509</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10011</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chelsea and Clinton</td>\n",
       "      <td>242.854346</td>\n",
       "      <td>200</td>\n",
       "      <td>225.796277</td>\n",
       "      <td>199</td>\n",
       "      <td>225.691729</td>\n",
       "      <td>195</td>\n",
       "      <td>235.382632</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10019</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chelsea and Clinton</td>\n",
       "      <td>229.525049</td>\n",
       "      <td>189</td>\n",
       "      <td>215.508512</td>\n",
       "      <td>175</td>\n",
       "      <td>215.059272</td>\n",
       "      <td>170</td>\n",
       "      <td>228.574660</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10036</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Chelsea and Clinton</td>\n",
       "      <td>218.437125</td>\n",
       "      <td>175</td>\n",
       "      <td>212.077208</td>\n",
       "      <td>165</td>\n",
       "      <td>213.932102</td>\n",
       "      <td>168</td>\n",
       "      <td>215.999462</td>\n",
       "      <td>170.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10029</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>East Harlem</td>\n",
       "      <td>126.461440</td>\n",
       "      <td>100</td>\n",
       "      <td>127.426550</td>\n",
       "      <td>100</td>\n",
       "      <td>129.885366</td>\n",
       "      <td>98</td>\n",
       "      <td>140.572068</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11226</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Flatbush</td>\n",
       "      <td>92.680582</td>\n",
       "      <td>75</td>\n",
       "      <td>84.754190</td>\n",
       "      <td>70</td>\n",
       "      <td>85.103783</td>\n",
       "      <td>69</td>\n",
       "      <td>85.033461</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10016</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Gramercy Park and Murray Hill</td>\n",
       "      <td>237.572914</td>\n",
       "      <td>185</td>\n",
       "      <td>214.245595</td>\n",
       "      <td>175</td>\n",
       "      <td>215.009782</td>\n",
       "      <td>170</td>\n",
       "      <td>219.999161</td>\n",
       "      <td>175.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>11211</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Greenpoint</td>\n",
       "      <td>150.991682</td>\n",
       "      <td>129</td>\n",
       "      <td>143.768193</td>\n",
       "      <td>119</td>\n",
       "      <td>145.759296</td>\n",
       "      <td>113</td>\n",
       "      <td>146.840053</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>11222</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Greenpoint</td>\n",
       "      <td>140.432536</td>\n",
       "      <td>120</td>\n",
       "      <td>128.623164</td>\n",
       "      <td>109</td>\n",
       "      <td>124.135188</td>\n",
       "      <td>100</td>\n",
       "      <td>135.671584</td>\n",
       "      <td>109.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10012</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Greenwich Village and Soho</td>\n",
       "      <td>255.219760</td>\n",
       "      <td>200</td>\n",
       "      <td>230.587597</td>\n",
       "      <td>190</td>\n",
       "      <td>224.176746</td>\n",
       "      <td>185</td>\n",
       "      <td>226.860020</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10014</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Greenwich Village and Soho</td>\n",
       "      <td>252.500823</td>\n",
       "      <td>210</td>\n",
       "      <td>239.303179</td>\n",
       "      <td>200</td>\n",
       "      <td>244.652423</td>\n",
       "      <td>200</td>\n",
       "      <td>256.992884</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10031</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Inwood and Washington Heights</td>\n",
       "      <td>104.395633</td>\n",
       "      <td>80</td>\n",
       "      <td>99.883374</td>\n",
       "      <td>75</td>\n",
       "      <td>95.558082</td>\n",
       "      <td>75</td>\n",
       "      <td>98.003266</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10002</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Lower East Side</td>\n",
       "      <td>182.400477</td>\n",
       "      <td>150</td>\n",
       "      <td>168.815366</td>\n",
       "      <td>135</td>\n",
       "      <td>174.141667</td>\n",
       "      <td>129</td>\n",
       "      <td>171.128160</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10003</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Lower East Side</td>\n",
       "      <td>220.328891</td>\n",
       "      <td>180</td>\n",
       "      <td>218.895993</td>\n",
       "      <td>169</td>\n",
       "      <td>220.491229</td>\n",
       "      <td>160</td>\n",
       "      <td>223.038827</td>\n",
       "      <td>169.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10009</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Lower East Side</td>\n",
       "      <td>177.778549</td>\n",
       "      <td>150</td>\n",
       "      <td>165.071030</td>\n",
       "      <td>135</td>\n",
       "      <td>166.544186</td>\n",
       "      <td>135</td>\n",
       "      <td>170.691880</td>\n",
       "      <td>140.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>11205</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "      <td>165.375414</td>\n",
       "      <td>115</td>\n",
       "      <td>154.145494</td>\n",
       "      <td>100</td>\n",
       "      <td>140.440341</td>\n",
       "      <td>99</td>\n",
       "      <td>140.647674</td>\n",
       "      <td>99.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>11215</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "      <td>162.932613</td>\n",
       "      <td>139</td>\n",
       "      <td>150.024912</td>\n",
       "      <td>130</td>\n",
       "      <td>144.884473</td>\n",
       "      <td>129</td>\n",
       "      <td>147.097090</td>\n",
       "      <td>129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>11217</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "      <td>165.974973</td>\n",
       "      <td>140</td>\n",
       "      <td>164.352042</td>\n",
       "      <td>130</td>\n",
       "      <td>163.994170</td>\n",
       "      <td>130</td>\n",
       "      <td>162.188512</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>10023</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>234.262821</td>\n",
       "      <td>190</td>\n",
       "      <td>223.957771</td>\n",
       "      <td>180</td>\n",
       "      <td>219.792201</td>\n",
       "      <td>182</td>\n",
       "      <td>219.262169</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10025</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>183.937928</td>\n",
       "      <td>145</td>\n",
       "      <td>158.431274</td>\n",
       "      <td>119</td>\n",
       "      <td>166.183255</td>\n",
       "      <td>110</td>\n",
       "      <td>166.790625</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>11233</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Central Brooklyn</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>105.371874</td>\n",
       "      <td>95</td>\n",
       "      <td>100.719001</td>\n",
       "      <td>80</td>\n",
       "      <td>99.172214</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>11225</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Flatbush</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>94.748649</td>\n",
       "      <td>80</td>\n",
       "      <td>95.294381</td>\n",
       "      <td>80</td>\n",
       "      <td>100.770975</td>\n",
       "      <td>83.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>11201</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "      <td>180.651959</td>\n",
       "      <td>155</td>\n",
       "      <td>166.963918</td>\n",
       "      <td>150</td>\n",
       "      <td>174.439658</td>\n",
       "      <td>145</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>10024</td>\n",
       "      <td>Manhattan</td>\n",
       "      <td>Upper West Side</td>\n",
       "      <td>205.716110</td>\n",
       "      <td>175</td>\n",
       "      <td>199.247779</td>\n",
       "      <td>165</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "      <td>195.559349</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Zip Codes    Borough                   Neighborhood   Mean_2015  \\\n",
       "0       11206   Brooklyn      Bushwick and Williamsburg  102.391970   \n",
       "1       11221   Brooklyn      Bushwick and Williamsburg   95.713076   \n",
       "2       11237   Brooklyn      Bushwick and Williamsburg   91.916442   \n",
       "3       11216   Brooklyn               Central Brooklyn  111.900207   \n",
       "4       11238   Brooklyn               Central Brooklyn  144.082211   \n",
       "5       10027  Manhattan                 Central Harlem  128.709048   \n",
       "6       10011  Manhattan            Chelsea and Clinton  242.854346   \n",
       "7       10019  Manhattan            Chelsea and Clinton  229.525049   \n",
       "8       10036  Manhattan            Chelsea and Clinton  218.437125   \n",
       "9       10029  Manhattan                    East Harlem  126.461440   \n",
       "10      11226   Brooklyn                       Flatbush   92.680582   \n",
       "11      10016  Manhattan  Gramercy Park and Murray Hill  237.572914   \n",
       "12      11211   Brooklyn                     Greenpoint  150.991682   \n",
       "13      11222   Brooklyn                     Greenpoint  140.432536   \n",
       "14      10012  Manhattan     Greenwich Village and Soho  255.219760   \n",
       "15      10014  Manhattan     Greenwich Village and Soho  252.500823   \n",
       "16      10031  Manhattan  Inwood and Washington Heights  104.395633   \n",
       "17      10002  Manhattan                Lower East Side  182.400477   \n",
       "18      10003  Manhattan                Lower East Side  220.328891   \n",
       "19      10009  Manhattan                Lower East Side  177.778549   \n",
       "20      11205   Brooklyn             Northwest Brooklyn  165.375414   \n",
       "21      11215   Brooklyn             Northwest Brooklyn  162.932613   \n",
       "22      11217   Brooklyn             Northwest Brooklyn  165.974973   \n",
       "23      10023  Manhattan                Upper West Side  234.262821   \n",
       "24      10025  Manhattan                Upper West Side  183.937928   \n",
       "25      11233   Brooklyn               Central Brooklyn    0.000000   \n",
       "26      11225   Brooklyn                       Flatbush    0.000000   \n",
       "27      11201   Brooklyn             Northwest Brooklyn  180.651959   \n",
       "28      10024  Manhattan                Upper West Side  205.716110   \n",
       "\n",
       "    Median_2015   Mean_2016  Median_2016   Mean_2017  Median_2017   Mean_2018  \\\n",
       "0            80   94.994238           75   94.821426           75   96.825835   \n",
       "1            75   89.587325           70   88.334267           69   87.629931   \n",
       "2            75   86.114981           69   80.728763           65   79.219594   \n",
       "3            90  110.022522           85  107.358035           85  110.636435   \n",
       "4           120  138.259867          106  135.210127          100  137.844509   \n",
       "5           110  121.078350          100  135.229297          100  135.707509   \n",
       "6           200  225.796277          199  225.691729          195  235.382632   \n",
       "7           189  215.508512          175  215.059272          170  228.574660   \n",
       "8           175  212.077208          165  213.932102          168  215.999462   \n",
       "9           100  127.426550          100  129.885366           98  140.572068   \n",
       "10           75   84.754190           70   85.103783           69   85.033461   \n",
       "11          185  214.245595          175  215.009782          170  219.999161   \n",
       "12          129  143.768193          119  145.759296          113  146.840053   \n",
       "13          120  128.623164          109  124.135188          100  135.671584   \n",
       "14          200  230.587597          190  224.176746          185  226.860020   \n",
       "15          210  239.303179          200  244.652423          200  256.992884   \n",
       "16           80   99.883374           75   95.558082           75   98.003266   \n",
       "17          150  168.815366          135  174.141667          129  171.128160   \n",
       "18          180  218.895993          169  220.491229          160  223.038827   \n",
       "19          150  165.071030          135  166.544186          135  170.691880   \n",
       "20          115  154.145494          100  140.440341           99  140.647674   \n",
       "21          139  150.024912          130  144.884473          129  147.097090   \n",
       "22          140  164.352042          130  163.994170          130  162.188512   \n",
       "23          190  223.957771          180  219.792201          182  219.262169   \n",
       "24          145  158.431274          119  166.183255          110  166.790625   \n",
       "25            0  105.371874           95  100.719001           80   99.172214   \n",
       "26            0   94.748649           80   95.294381           80  100.770975   \n",
       "27          155  166.963918          150  174.439658          145    0.000000   \n",
       "28          175  199.247779          165    0.000000            0  195.559349   \n",
       "\n",
       "    Median_2018  \n",
       "0          75.0  \n",
       "1          68.0  \n",
       "2          65.0  \n",
       "3          85.0  \n",
       "4         105.0  \n",
       "5         100.0  \n",
       "6         190.0  \n",
       "7         180.0  \n",
       "8         170.0  \n",
       "9          95.0  \n",
       "10         69.0  \n",
       "11        175.0  \n",
       "12        110.0  \n",
       "13        109.5  \n",
       "14        185.0  \n",
       "15        200.0  \n",
       "16         75.0  \n",
       "17        130.0  \n",
       "18        169.0  \n",
       "19        140.0  \n",
       "20         99.0  \n",
       "21        129.0  \n",
       "22        130.0  \n",
       "23        180.0  \n",
       "24        110.0  \n",
       "25         80.0  \n",
       "26         83.0  \n",
       "27          0.0  \n",
       "28        159.0  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create DF for the selected zipcodes\n",
    "final30 = pd.read_csv('Final_Trending_Zipcodes.csv')\n",
    "final30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bushwick and Williamsburg</td>\n",
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       "      <th>1</th>\n",
       "      <td>Bushwick and Williamsburg</td>\n",
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       "      <td>Bushwick and Williamsburg</td>\n",
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       "      <th>3</th>\n",
       "      <td>Central Brooklyn</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Central Brooklyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Central Harlem</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Chelsea and Clinton</td>\n",
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       "      <th>7</th>\n",
       "      <td>Chelsea and Clinton</td>\n",
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       "      <th>8</th>\n",
       "      <td>Chelsea and Clinton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>East Harlem</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Flatbush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Gramercy Park and Murray Hill</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Greenpoint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Greenpoint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Greenwich Village and Soho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Greenwich Village and Soho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Inwood and Washington Heights</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Lower East Side</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Lower East Side</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Lower East Side</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Upper West Side</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Upper West Side</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Central Brooklyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Flatbush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Upper West Side</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Neighborhood\n",
       "0       Bushwick and Williamsburg\n",
       "1       Bushwick and Williamsburg\n",
       "2       Bushwick and Williamsburg\n",
       "3                Central Brooklyn\n",
       "4                Central Brooklyn\n",
       "5                  Central Harlem\n",
       "6             Chelsea and Clinton\n",
       "7             Chelsea and Clinton\n",
       "8             Chelsea and Clinton\n",
       "9                     East Harlem\n",
       "10                       Flatbush\n",
       "11  Gramercy Park and Murray Hill\n",
       "12                     Greenpoint\n",
       "13                     Greenpoint\n",
       "14     Greenwich Village and Soho\n",
       "15     Greenwich Village and Soho\n",
       "16  Inwood and Washington Heights\n",
       "17                Lower East Side\n",
       "18                Lower East Side\n",
       "19                Lower East Side\n",
       "20             Northwest Brooklyn\n",
       "21             Northwest Brooklyn\n",
       "22             Northwest Brooklyn\n",
       "23                Upper West Side\n",
       "24                Upper West Side\n",
       "25               Central Brooklyn\n",
       "26                       Flatbush\n",
       "27             Northwest Brooklyn\n",
       "28                Upper West Side"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hood = final30[['Neighborhood']]\n",
    "hood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
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       "      <td>Bushwick and Williamsburg</td>\n",
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       "      <td>Greenpoint</td>\n",
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       "      <td>Inwood and Washington Heights</td>\n",
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       "      <th>17</th>\n",
       "      <td>Lower East Side</td>\n",
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       "      <th>20</th>\n",
       "      <td>Northwest Brooklyn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Upper West Side</td>\n",
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      "text/plain": [
       "                     Neighborhood\n",
       "0       Bushwick and Williamsburg\n",
       "3                Central Brooklyn\n",
       "5                  Central Harlem\n",
       "6             Chelsea and Clinton\n",
       "9                     East Harlem\n",
       "10                       Flatbush\n",
       "11  Gramercy Park and Murray Hill\n",
       "12                     Greenpoint\n",
       "14     Greenwich Village and Soho\n",
       "16  Inwood and Washington Heights\n",
       "17                Lower East Side\n",
       "20             Northwest Brooklyn\n",
       "23                Upper West Side"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hood.drop_duplicates(subset=['Neighborhood'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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