Recent Rent Analysis Based on Prices From Zillow.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading the Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import matplotlib.mlab as mlab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import bokeh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from scipy.stats import norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from subprocess import check_output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reading the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "price = pd.read_csv('./price.csv')\n",
    "sqft = pd.read_csv('./pricepersqft.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(13131, 81)\n"
     ]
    }
   ],
   "source": [
    "print(price.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(11919, 81)\n"
     ]
    }
   ],
   "source": [
    "print(sqft.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9670\n"
     ]
    }
   ],
   "source": [
    "print(price['City'].nunique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['City Code', 'City', 'Metro', 'County', 'State', 'Population Rank',\n",
      "       'November 2010', 'December 2010', 'January 2011', 'February 2011',\n",
      "       'March 2011', 'April 2011', 'May 2011', 'June 2011', 'July 2011',\n",
      "       'August 2011', 'September 2011', 'October 2011', 'November 2011',\n",
      "       'December 2011', 'January 2012', 'February 2012', 'March 2012',\n",
      "       'April 2012', 'May 2012', 'June 2012', 'July 2012', 'August 2012',\n",
      "       'September 2012', 'October 2012', 'November 2012', 'December 2012',\n",
      "       'January 2013', 'February 2013', 'March 2013', 'April 2013', 'May 2013',\n",
      "       'June 2013', 'July 2013', 'August 2013', 'September 2013',\n",
      "       'October 2013', 'November 2013', 'December 2013', 'January 2014',\n",
      "       'February 2014', 'March 2014', 'April 2014', 'May 2014', 'June 2014',\n",
      "       'July 2014', 'August 2014', 'September 2014', 'October 2014',\n",
      "       'November 2014', 'December 2014', 'January 2015', 'February 2015',\n",
      "       'March 2015', 'April 2015', 'May 2015', 'June 2015', 'July 2015',\n",
      "       'August 2015', 'September 2015', 'October 2015', 'November 2015',\n",
      "       'December 2015', 'January 2016', 'February 2016', 'March 2016',\n",
      "       'April 2016', 'May 2016', 'June 2016', 'July 2016', 'August 2016',\n",
      "       'September 2016', 'October 2016', 'November 2016', 'December 2016',\n",
      "       'January 2017'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(price.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    City Code           City              Metro         County State  \\\n",
      "0        6181       New York           New York         Queens    NY   \n",
      "1       12447    Los Angeles        Los Angeles    Los Angeles    CA   \n",
      "2       17426        Chicago            Chicago           Cook    IL   \n",
      "3       39051        Houston            Houston         Harris    TX   \n",
      "4       13271   Philadelphia       Philadelphia   Philadelphia    PA   \n",
      "5       40326        Phoenix            Phoenix       Maricopa    AZ   \n",
      "6       18959      Las Vegas          Las Vegas          Clark    NV   \n",
      "7        6915    San Antonio        San Antonio          Bexar    TX   \n",
      "8       54296      San Diego          San Diego      San Diego    CA   \n",
      "9       38128         Dallas  Dallas-Fort Worth         Dallas    TX   \n",
      "10      33839       San Jose           San Jose    Santa Clara    CA   \n",
      "11      25290   Jacksonville       Jacksonville          Duval    FL   \n",
      "12      20330  San Francisco      San Francisco  San Francisco    CA   \n",
      "13      32149   Indianapolis       Indianapolis         Marion    IN   \n",
      "14      10221         Austin             Austin         Travis    TX   \n",
      "15      18172     Fort Worth  Dallas-Fort Worth        Tarrant    TX   \n",
      "16      17762        Detroit            Detroit          Wayne    MI   \n",
      "17      10920       Columbus           Columbus       Franklin    OH   \n",
      "18      32811        Memphis            Memphis         Shelby    TN   \n",
      "19      24043      Charlotte          Charlotte    Mecklenburg    NC   \n",
      "\n",
      "    Population Rank  November 2010  December 2010  January 2011  \\\n",
      "0                 1            NaN            NaN           NaN   \n",
      "1                 2         2184.0         2184.0        2183.0   \n",
      "2                 3         1563.0         1555.0        1547.0   \n",
      "3                 4         1198.0         1199.0        1199.0   \n",
      "4                 5         1092.0         1099.0        1094.0   \n",
      "5                 6         1087.0         1080.0        1071.0   \n",
      "6                 7         1188.0         1183.0        1178.0   \n",
      "7                 8         1057.0         1043.0        1037.0   \n",
      "8                 9         2070.0         2059.0        2043.0   \n",
      "9                10         1114.0         1135.0        1156.0   \n",
      "10               11         2359.0         2367.0        2360.0   \n",
      "11               12         1006.0         1016.0        1023.0   \n",
      "12               13         3188.0         3207.0        3189.0   \n",
      "13               14          998.0          998.0         999.0   \n",
      "14               15         1293.0         1301.0        1312.0   \n",
      "15               16         1152.0         1160.0        1166.0   \n",
      "16               17          847.0          844.0         832.0   \n",
      "17               18          933.0          933.0         938.0   \n",
      "18               19          862.0          855.0         851.0   \n",
      "19               20         1024.0         1022.0        1024.0   \n",
      "\n",
      "    February 2011      ...       April 2016  May 2016  June 2016  July 2016  \\\n",
      "0             NaN      ...             2334      2339       2345       2344   \n",
      "1          2188.0      ...             2637      2662       2687       2704   \n",
      "2          1537.0      ...             1684      1686       1687       1685   \n",
      "3          1200.0      ...             1444      1446       1446       1443   \n",
      "4          1087.0      ...             1206      1211       1218       1222   \n",
      "5          1067.0      ...             1228      1236       1240       1240   \n",
      "6          1177.0      ...             1222      1225       1227       1227   \n",
      "7          1032.0      ...             1244      1245       1245       1241   \n",
      "8          2030.0      ...             2414      2428       2438       2442   \n",
      "9          1159.0      ...             1338      1347       1353       1358   \n",
      "10         2343.0      ...             3347      3368       3386       3391   \n",
      "11         1032.0      ...             1156      1155       1152       1148   \n",
      "12         3127.0      ...             4527      4519       4517       4511   \n",
      "13          997.0      ...             1067      1072       1076       1080   \n",
      "14         1325.0      ...             1790      1799       1807       1808   \n",
      "15         1166.0      ...             1346      1351       1354       1353   \n",
      "16          820.0      ...              753       752        749        746   \n",
      "17          942.0      ...             1124      1124       1125       1125   \n",
      "18          849.0      ...              849       849        848        848   \n",
      "19         1026.0      ...             1276      1283       1289       1289   \n",
      "\n",
      "    August 2016  September 2016  October 2016  November 2016  December 2016  \\\n",
      "0          2336            2324          2318           2321           2321   \n",
      "1          2716            2723          2731           2740           2748   \n",
      "2          1681            1675          1668           1656           1644   \n",
      "3          1440            1438          1437           1437           1435   \n",
      "4          1223            1220          1216           1211           1209   \n",
      "5          1238            1238          1239           1241           1244   \n",
      "6          1227            1228          1230           1234           1237   \n",
      "7          1236            1234          1235           1239           1245   \n",
      "8          2441            2442          2449           2457           2465   \n",
      "9          1364            1370          1377           1385           1389   \n",
      "10         3383            3363          3341           3320           3300   \n",
      "11         1143            1141          1142           1147           1150   \n",
      "12         4500            4488          4472           4457           4424   \n",
      "13         1082            1083          1084           1086           1084   \n",
      "14         1803            1795          1789           1788           1786   \n",
      "15         1351            1352          1357           1365           1371   \n",
      "16          746             746           747            748            749   \n",
      "17         1124            1124          1126           1127           1123   \n",
      "18          847             846           846            844            844   \n",
      "19         1287            1285          1285           1286           1290   \n",
      "\n",
      "    January 2017  \n",
      "0           2322  \n",
      "1           2753  \n",
      "2           1632  \n",
      "3           1430  \n",
      "4           1212  \n",
      "5           1247  \n",
      "6           1239  \n",
      "7           1250  \n",
      "8           2469  \n",
      "9           1391  \n",
      "10          3286  \n",
      "11          1151  \n",
      "12          4382  \n",
      "13          1078  \n",
      "14          1780  \n",
      "15          1375  \n",
      "16           750  \n",
      "17          1116  \n",
      "18           843  \n",
      "19          1294  \n",
      "\n",
      "[20 rows x 81 columns]\n"
     ]
    }
   ],
   "source": [
    "print(price.head(20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    City Code           City              Metro         County State  \\\n",
      "0        6181       New York           New York         Queens    NY   \n",
      "1       12447    Los Angeles        Los Angeles    Los Angeles    CA   \n",
      "2       17426        Chicago            Chicago           Cook    IL   \n",
      "3       39051        Houston            Houston         Harris    TX   \n",
      "4       13271   Philadelphia       Philadelphia   Philadelphia    PA   \n",
      "5       40326        Phoenix            Phoenix       Maricopa    AZ   \n",
      "6       18959      Las Vegas          Las Vegas          Clark    NV   \n",
      "7        6915    San Antonio        San Antonio          Bexar    TX   \n",
      "8       54296      San Diego          San Diego      San Diego    CA   \n",
      "9       38128         Dallas  Dallas-Fort Worth         Dallas    TX   \n",
      "10      33839       San Jose           San Jose    Santa Clara    CA   \n",
      "11      25290   Jacksonville       Jacksonville          Duval    FL   \n",
      "12      20330  San Francisco      San Francisco  San Francisco    CA   \n",
      "13      32149   Indianapolis       Indianapolis         Marion    IN   \n",
      "14      10221         Austin             Austin         Travis    TX   \n",
      "15      18172     Fort Worth  Dallas-Fort Worth        Tarrant    TX   \n",
      "16      17762        Detroit            Detroit          Wayne    MI   \n",
      "17      10920       Columbus           Columbus       Franklin    OH   \n",
      "18      32811        Memphis            Memphis         Shelby    TN   \n",
      "19      24043      Charlotte          Charlotte    Mecklenburg    NC   \n",
      "\n",
      "    Population Rank  November 2010  December 2010  January 2011  \\\n",
      "0                 1            NaN            NaN           NaN   \n",
      "1                 2          1.578          1.578         1.580   \n",
      "2                 3          1.244          1.248         1.254   \n",
      "3                 4          0.788          0.784         0.784   \n",
      "4                 5          0.854          0.858         0.858   \n",
      "5                 6          0.764          0.766         0.766   \n",
      "6                 7          0.750          0.750         0.748   \n",
      "7                 8          0.694          0.698         0.700   \n",
      "8                 9          1.492          1.494         1.492   \n",
      "9                10          0.802          0.810         0.818   \n",
      "10               11          1.542          1.546         1.540   \n",
      "11               12          0.688          0.690         0.692   \n",
      "12               13          2.502          2.526         2.516   \n",
      "13               14          0.716          0.716         0.714   \n",
      "14               15          0.876          0.880         0.886   \n",
      "15               16          0.686          0.688         0.690   \n",
      "16               17          0.816          0.816         0.808   \n",
      "17               18          0.726          0.728         0.730   \n",
      "18               19          0.624          0.624         0.620   \n",
      "19               20          0.650          0.652         0.654   \n",
      "\n",
      "    February 2011      ...       April 2016  May 2016  June 2016  July 2016  \\\n",
      "0             NaN      ...            1.806     1.810      1.816      1.824   \n",
      "1           1.582      ...            1.990     2.004      2.018      2.026   \n",
      "2           1.254      ...            1.354     1.362      1.370      1.374   \n",
      "3           0.786      ...            0.984     0.984      0.982      0.980   \n",
      "4           0.858      ...            0.948     0.956      0.962      0.964   \n",
      "5           0.766      ...            0.862     0.870      0.876      0.880   \n",
      "6           0.748      ...            0.768     0.770      0.772      0.774   \n",
      "7           0.700      ...            0.820     0.822      0.824      0.822   \n",
      "8           1.490      ...            1.772     1.782      1.788      1.792   \n",
      "9           0.824      ...            1.026     1.034      1.040      1.046   \n",
      "10          1.530      ...            2.224     2.234      2.242      2.246   \n",
      "11          0.694      ...            0.774     0.776      0.776      0.776   \n",
      "12          2.468      ...            3.594     3.590      3.588      3.580   \n",
      "13          0.710      ...            0.736     0.740      0.740      0.740   \n",
      "14          0.892      ...            1.180     1.184      1.188      1.188   \n",
      "15          0.692      ...            0.828     0.834      0.840      0.846   \n",
      "16          0.800      ...            0.756     0.754      0.752      0.750   \n",
      "17          0.732      ...            0.856     0.860      0.862      0.860   \n",
      "18          0.618      ...            0.632     0.632      0.630      0.630   \n",
      "19          0.656      ...            0.800     0.804      0.806      0.806   \n",
      "\n",
      "    August 2016  September 2016  October 2016  November 2016  December 2016  \\\n",
      "0         1.828           1.836         1.844          1.858          1.866   \n",
      "1         2.032           2.038         2.042          2.048          2.056   \n",
      "2         1.378           1.380         1.380          1.380          1.376   \n",
      "3         0.976           0.974         0.974          0.976          0.976   \n",
      "4         0.964           0.966         0.968          0.972          0.974   \n",
      "5         0.882           0.884         0.886          0.890          0.892   \n",
      "6         0.772           0.774         0.774          0.778          0.780   \n",
      "7         0.822           0.822         0.824          0.830          0.834   \n",
      "8         1.794           1.796         1.802          1.808          1.814   \n",
      "9         1.048           1.050         1.054          1.060          1.062   \n",
      "10        2.246           2.240         2.232          2.224          2.210   \n",
      "11        0.776           0.774         0.776          0.776          0.778   \n",
      "12        3.564           3.542         3.518          3.498          3.466   \n",
      "13        0.740           0.738         0.738          0.738          0.736   \n",
      "14        1.186           1.186         1.188          1.190          1.190   \n",
      "15        0.850           0.852         0.854          0.860          0.862   \n",
      "16        0.748           0.748         0.748          0.748          0.750   \n",
      "17        0.858           0.858         0.860          0.862          0.864   \n",
      "18        0.628           0.628         0.628          0.626          0.626   \n",
      "19        0.808           0.808         0.812          0.814          0.816   \n",
      "\n",
      "    January 2017  \n",
      "0          1.872  \n",
      "1          2.064  \n",
      "2          1.374  \n",
      "3          0.974  \n",
      "4          0.974  \n",
      "5          0.894  \n",
      "6          0.780  \n",
      "7          0.836  \n",
      "8          1.816  \n",
      "9          1.064  \n",
      "10         2.200  \n",
      "11         0.778  \n",
      "12         3.442  \n",
      "13         0.736  \n",
      "14         1.190  \n",
      "15         0.864  \n",
      "16         0.750  \n",
      "17         0.866  \n",
      "18         0.626  \n",
      "19         0.816  \n",
      "\n",
      "[20 rows x 81 columns]\n"
     ]
    }
   ],
   "source": [
    "print(sqft.head(20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City Code</th>\n",
       "      <th>Population Rank</th>\n",
       "      <th>November 2010</th>\n",
       "      <th>December 2010</th>\n",
       "      <th>January 2011</th>\n",
       "      <th>February 2011</th>\n",
       "      <th>March 2011</th>\n",
       "      <th>April 2011</th>\n",
       "      <th>May 2011</th>\n",
       "      <th>June 2011</th>\n",
       "      <th>...</th>\n",
       "      <th>April 2016</th>\n",
       "      <th>May 2016</th>\n",
       "      <th>June 2016</th>\n",
       "      <th>July 2016</th>\n",
       "      <th>August 2016</th>\n",
       "      <th>September 2016</th>\n",
       "      <th>October 2016</th>\n",
       "      <th>November 2016</th>\n",
       "      <th>December 2016</th>\n",
       "      <th>January 2017</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>11348.000000</td>\n",
       "      <td>11348.000000</td>\n",
       "      <td>11348.000000</td>\n",
       "      <td>11500.000000</td>\n",
       "      <td>11673.000000</td>\n",
       "      <td>11722.000000</td>\n",
       "      <td>11732.000000</td>\n",
       "      <td>11732.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>13131.000000</td>\n",
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       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>78126.756454</td>\n",
       "      <td>6566.000000</td>\n",
       "      <td>1327.100458</td>\n",
       "      <td>1331.831953</td>\n",
       "      <td>1334.447744</td>\n",
       "      <td>1331.935217</td>\n",
       "      <td>1327.595819</td>\n",
       "      <td>1323.824518</td>\n",
       "      <td>1321.730822</td>\n",
       "      <td>1321.872826</td>\n",
       "      <td>...</td>\n",
       "      <td>1466.406519</td>\n",
       "      <td>1470.625695</td>\n",
       "      <td>1472.876856</td>\n",
       "      <td>1471.627370</td>\n",
       "      <td>1468.666667</td>\n",
       "      <td>1465.817988</td>\n",
       "      <td>1465.572157</td>\n",
       "      <td>1467.105247</td>\n",
       "      <td>1467.524636</td>\n",
       "      <td>1467.296550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>119604.910806</td>\n",
       "      <td>3790.737527</td>\n",
       "      <td>652.531343</td>\n",
       "      <td>655.822002</td>\n",
       "      <td>653.931315</td>\n",
       "      <td>647.853483</td>\n",
       "      <td>640.168818</td>\n",
       "      <td>636.392831</td>\n",
       "      <td>633.675563</td>\n",
       "      <td>631.981504</td>\n",
       "      <td>...</td>\n",
       "      <td>813.253498</td>\n",
       "      <td>815.322324</td>\n",
       "      <td>819.417181</td>\n",
       "      <td>823.317848</td>\n",
       "      <td>825.885842</td>\n",
       "      <td>826.421670</td>\n",
       "      <td>825.621199</td>\n",
       "      <td>824.678612</td>\n",
       "      <td>821.891626</td>\n",
       "      <td>820.707579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3300.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>547.000000</td>\n",
       "      <td>539.000000</td>\n",
       "      <td>536.000000</td>\n",
       "      <td>542.000000</td>\n",
       "      <td>535.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>533.000000</td>\n",
       "      <td>536.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>543.000000</td>\n",
       "      <td>548.000000</td>\n",
       "      <td>547.000000</td>\n",
       "      <td>544.000000</td>\n",
       "      <td>539.000000</td>\n",
       "      <td>532.000000</td>\n",
       "      <td>527.000000</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>517.000000</td>\n",
       "      <td>518.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>18803.000000</td>\n",
       "      <td>3283.500000</td>\n",
       "      <td>982.000000</td>\n",
       "      <td>984.750000</td>\n",
       "      <td>986.000000</td>\n",
       "      <td>984.000000</td>\n",
       "      <td>979.000000</td>\n",
       "      <td>973.000000</td>\n",
       "      <td>971.000000</td>\n",
       "      <td>972.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1041.000000</td>\n",
       "      <td>1044.000000</td>\n",
       "      <td>1046.000000</td>\n",
       "      <td>1043.500000</td>\n",
       "      <td>1038.000000</td>\n",
       "      <td>1034.000000</td>\n",
       "      <td>1032.000000</td>\n",
       "      <td>1033.000000</td>\n",
       "      <td>1034.000000</td>\n",
       "      <td>1035.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>34678.000000</td>\n",
       "      <td>6566.000000</td>\n",
       "      <td>1195.000000</td>\n",
       "      <td>1199.000000</td>\n",
       "      <td>1201.500000</td>\n",
       "      <td>1201.000000</td>\n",
       "      <td>1201.000000</td>\n",
       "      <td>1196.000000</td>\n",
       "      <td>1194.000000</td>\n",
       "      <td>1193.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1275.000000</td>\n",
       "      <td>1277.000000</td>\n",
       "      <td>1278.000000</td>\n",
       "      <td>1276.000000</td>\n",
       "      <td>1270.000000</td>\n",
       "      <td>1268.000000</td>\n",
       "      <td>1266.000000</td>\n",
       "      <td>1267.000000</td>\n",
       "      <td>1267.000000</td>\n",
       "      <td>1264.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51385.500000</td>\n",
       "      <td>9848.500000</td>\n",
       "      <td>1479.000000</td>\n",
       "      <td>1479.000000</td>\n",
       "      <td>1479.000000</td>\n",
       "      <td>1477.000000</td>\n",
       "      <td>1473.000000</td>\n",
       "      <td>1471.000000</td>\n",
       "      <td>1472.000000</td>\n",
       "      <td>1473.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1625.000000</td>\n",
       "      <td>1630.000000</td>\n",
       "      <td>1633.000000</td>\n",
       "      <td>1629.000000</td>\n",
       "      <td>1628.000000</td>\n",
       "      <td>1628.000000</td>\n",
       "      <td>1630.500000</td>\n",
       "      <td>1630.000000</td>\n",
       "      <td>1632.000000</td>\n",
       "      <td>1634.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>737791.000000</td>\n",
       "      <td>13131.000000</td>\n",
       "      <td>18787.000000</td>\n",
       "      <td>18848.000000</td>\n",
       "      <td>19054.000000</td>\n",
       "      <td>19019.000000</td>\n",
       "      <td>18997.000000</td>\n",
       "      <td>18939.000000</td>\n",
       "      <td>19119.000000</td>\n",
       "      <td>19442.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>21344.000000</td>\n",
       "      <td>20547.000000</td>\n",
       "      <td>20400.000000</td>\n",
       "      <td>20639.000000</td>\n",
       "      <td>20695.000000</td>\n",
       "      <td>20615.000000</td>\n",
       "      <td>20163.000000</td>\n",
       "      <td>19460.000000</td>\n",
       "      <td>18605.000000</td>\n",
       "      <td>17985.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 77 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           City Code  Population Rank  November 2010  December 2010  \\\n",
       "count   13131.000000     13131.000000   11348.000000   11348.000000   \n",
       "mean    78126.756454      6566.000000    1327.100458    1331.831953   \n",
       "std    119604.910806      3790.737527     652.531343     655.822002   \n",
       "min      3300.000000         1.000000     547.000000     539.000000   \n",
       "25%     18803.000000      3283.500000     982.000000     984.750000   \n",
       "50%     34678.000000      6566.000000    1195.000000    1199.000000   \n",
       "75%     51385.500000      9848.500000    1479.000000    1479.000000   \n",
       "max    737791.000000     13131.000000   18787.000000   18848.000000   \n",
       "\n",
       "       January 2011  February 2011    March 2011    April 2011      May 2011  \\\n",
       "count  11348.000000   11500.000000  11673.000000  11722.000000  11732.000000   \n",
       "mean    1334.447744    1331.935217   1327.595819   1323.824518   1321.730822   \n",
       "std      653.931315     647.853483    640.168818    636.392831    633.675563   \n",
       "min      536.000000     542.000000    535.000000    533.000000    533.000000   \n",
       "25%      986.000000     984.000000    979.000000    973.000000    971.000000   \n",
       "50%     1201.500000    1201.000000   1201.000000   1196.000000   1194.000000   \n",
       "75%     1479.000000    1477.000000   1473.000000   1471.000000   1472.000000   \n",
       "max    19054.000000   19019.000000  18997.000000  18939.000000  19119.000000   \n",
       "\n",
       "          June 2011      ...         April 2016      May 2016     June 2016  \\\n",
       "count  11732.000000      ...       13131.000000  13131.000000  13131.000000   \n",
       "mean    1321.872826      ...        1466.406519   1470.625695   1472.876856   \n",
       "std      631.981504      ...         813.253498    815.322324    819.417181   \n",
       "min      536.000000      ...         543.000000    548.000000    547.000000   \n",
       "25%      972.000000      ...        1041.000000   1044.000000   1046.000000   \n",
       "50%     1193.000000      ...        1275.000000   1277.000000   1278.000000   \n",
       "75%     1473.000000      ...        1625.000000   1630.000000   1633.000000   \n",
       "max    19442.000000      ...       21344.000000  20547.000000  20400.000000   \n",
       "\n",
       "          July 2016   August 2016  September 2016  October 2016  \\\n",
       "count  13131.000000  13131.000000    13131.000000  13131.000000   \n",
       "mean    1471.627370   1468.666667     1465.817988   1465.572157   \n",
       "std      823.317848    825.885842      826.421670    825.621199   \n",
       "min      544.000000    539.000000      532.000000    527.000000   \n",
       "25%     1043.500000   1038.000000     1034.000000   1032.000000   \n",
       "50%     1276.000000   1270.000000     1268.000000   1266.000000   \n",
       "75%     1629.000000   1628.000000     1628.000000   1630.500000   \n",
       "max    20639.000000  20695.000000    20615.000000  20163.000000   \n",
       "\n",
       "       November 2016  December 2016  January 2017  \n",
       "count   13131.000000   13131.000000  13131.000000  \n",
       "mean     1467.105247    1467.524636   1467.296550  \n",
       "std       824.678612     821.891626    820.707579  \n",
       "min       518.000000     517.000000    518.000000  \n",
       "25%      1033.000000    1034.000000   1035.000000  \n",
       "50%      1267.000000    1267.000000   1264.000000  \n",
       "75%      1630.000000    1632.000000   1634.000000  \n",
       "max     19460.000000   18605.000000  17985.000000  \n",
       "\n",
       "[8 rows x 77 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "price.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City Code</th>\n",
       "      <th>November 2010</th>\n",
       "      <th>December 2010</th>\n",
       "      <th>January 2011</th>\n",
       "      <th>February 2011</th>\n",
       "      <th>March 2011</th>\n",
       "      <th>April 2011</th>\n",
       "      <th>May 2011</th>\n",
       "      <th>June 2011</th>\n",
       "      <th>July 2011</th>\n",
       "      <th>...</th>\n",
       "      <th>August 2016</th>\n",
       "      <th>September 2016</th>\n",
       "      <th>October 2016</th>\n",
       "      <th>November 2016</th>\n",
       "      <th>December 2016</th>\n",
       "      <th>January 2017</th>\n",
       "      <th>Total Change</th>\n",
       "      <th>Percent Change</th>\n",
       "      <th>Year Change</th>\n",
       "      <th>Year Percent Change</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>11919.000000</td>\n",
       "      <td>10600.000000</td>\n",
       "      <td>10600.000000</td>\n",
       "      <td>10600.000000</td>\n",
       "      <td>10744.000000</td>\n",
       "      <td>10829.000000</td>\n",
       "      <td>10878.000000</td>\n",
       "      <td>10885.000000</td>\n",
       "      <td>10885.000000</td>\n",
       "      <td>10885.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>11919.000000</td>\n",
       "      <td>11919.000000</td>\n",
       "      <td>11919.000000</td>\n",
       "      <td>11919.000000</td>\n",
       "      <td>11919.000000</td>\n",
       "      <td>11919.000000</td>\n",
       "      <td>10600.000000</td>\n",
       "      <td>10600.000000</td>\n",
       "      <td>11919.000000</td>\n",
       "      <td>11919.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>77097.011998</td>\n",
       "      <td>0.860989</td>\n",
       "      <td>0.863896</td>\n",
       "      <td>0.865602</td>\n",
       "      <td>0.864939</td>\n",
       "      <td>0.862232</td>\n",
       "      <td>0.860946</td>\n",
       "      <td>0.859769</td>\n",
       "      <td>0.859848</td>\n",
       "      <td>0.859505</td>\n",
       "      <td>...</td>\n",
       "      <td>0.963645</td>\n",
       "      <td>0.962379</td>\n",
       "      <td>0.962570</td>\n",
       "      <td>0.963743</td>\n",
       "      <td>0.964275</td>\n",
       "      <td>0.964356</td>\n",
       "      <td>0.097617</td>\n",
       "      <td>0.107012</td>\n",
       "      <td>0.017929</td>\n",
       "      <td>0.017944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>118093.323482</td>\n",
       "      <td>0.286088</td>\n",
       "      <td>0.286489</td>\n",
       "      <td>0.284910</td>\n",
       "      <td>0.281532</td>\n",
       "      <td>0.278903</td>\n",
       "      <td>0.277075</td>\n",
       "      <td>0.275870</td>\n",
       "      <td>0.275311</td>\n",
       "      <td>0.274526</td>\n",
       "      <td>...</td>\n",
       "      <td>0.380334</td>\n",
       "      <td>0.381100</td>\n",
       "      <td>0.381545</td>\n",
       "      <td>0.381775</td>\n",
       "      <td>0.381395</td>\n",
       "      <td>0.381297</td>\n",
       "      <td>0.143625</td>\n",
       "      <td>0.131925</td>\n",
       "      <td>0.045231</td>\n",
       "      <td>0.044913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>3300.000000</td>\n",
       "      <td>0.360000</td>\n",
       "      <td>0.358000</td>\n",
       "      <td>0.358000</td>\n",
       "      <td>0.358000</td>\n",
       "      <td>0.362000</td>\n",
       "      <td>0.366000</td>\n",
       "      <td>0.366000</td>\n",
       "      <td>0.366000</td>\n",
       "      <td>0.368000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.382000</td>\n",
       "      <td>0.378000</td>\n",
       "      <td>0.378000</td>\n",
       "      <td>0.378000</td>\n",
       "      <td>0.378000</td>\n",
       "      <td>0.378000</td>\n",
       "      <td>-0.842000</td>\n",
       "      <td>-0.440605</td>\n",
       "      <td>-0.542000</td>\n",
       "      <td>-0.247191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>18762.000000</td>\n",
       "      <td>0.676000</td>\n",
       "      <td>0.678000</td>\n",
       "      <td>0.680000</td>\n",
       "      <td>0.682000</td>\n",
       "      <td>0.680000</td>\n",
       "      <td>0.678000</td>\n",
       "      <td>0.678000</td>\n",
       "      <td>0.678000</td>\n",
       "      <td>0.678000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>0.728000</td>\n",
       "      <td>0.728000</td>\n",
       "      <td>0.728000</td>\n",
       "      <td>0.730000</td>\n",
       "      <td>0.732000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.026565</td>\n",
       "      <td>-0.008000</td>\n",
       "      <td>-0.008496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>34637.000000</td>\n",
       "      <td>0.796000</td>\n",
       "      <td>0.799000</td>\n",
       "      <td>0.802000</td>\n",
       "      <td>0.802000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.798000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.870000</td>\n",
       "      <td>0.870000</td>\n",
       "      <td>0.870000</td>\n",
       "      <td>0.870000</td>\n",
       "      <td>0.872000</td>\n",
       "      <td>0.872000</td>\n",
       "      <td>0.074000</td>\n",
       "      <td>0.094149</td>\n",
       "      <td>0.014000</td>\n",
       "      <td>0.015873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51298.500000</td>\n",
       "      <td>0.972000</td>\n",
       "      <td>0.974000</td>\n",
       "      <td>0.976000</td>\n",
       "      <td>0.972000</td>\n",
       "      <td>0.970000</td>\n",
       "      <td>0.968000</td>\n",
       "      <td>0.968000</td>\n",
       "      <td>0.968000</td>\n",
       "      <td>0.968000</td>\n",
       "      <td>...</td>\n",
       "      <td>1.080000</td>\n",
       "      <td>1.080000</td>\n",
       "      <td>1.082000</td>\n",
       "      <td>1.082000</td>\n",
       "      <td>1.080000</td>\n",
       "      <td>1.080000</td>\n",
       "      <td>0.144000</td>\n",
       "      <td>0.171582</td>\n",
       "      <td>0.040000</td>\n",
       "      <td>0.043147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>737791.000000</td>\n",
       "      <td>4.482000</td>\n",
       "      <td>4.508000</td>\n",
       "      <td>4.558000</td>\n",
       "      <td>4.564000</td>\n",
       "      <td>4.548000</td>\n",
       "      <td>4.536000</td>\n",
       "      <td>4.528000</td>\n",
       "      <td>4.536000</td>\n",
       "      <td>4.542000</td>\n",
       "      <td>...</td>\n",
       "      <td>6.476000</td>\n",
       "      <td>6.486000</td>\n",
       "      <td>6.476000</td>\n",
       "      <td>6.470000</td>\n",
       "      <td>6.440000</td>\n",
       "      <td>6.406000</td>\n",
       "      <td>1.924000</td>\n",
       "      <td>0.905512</td>\n",
       "      <td>0.628000</td>\n",
       "      <td>0.282572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 80 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           City Code  November 2010  December 2010  January 2011  \\\n",
       "count   11919.000000   10600.000000   10600.000000  10600.000000   \n",
       "mean    77097.011998       0.860989       0.863896      0.865602   \n",
       "std    118093.323482       0.286088       0.286489      0.284910   \n",
       "min      3300.000000       0.360000       0.358000      0.358000   \n",
       "25%     18762.000000       0.676000       0.678000      0.680000   \n",
       "50%     34637.000000       0.796000       0.799000      0.802000   \n",
       "75%     51298.500000       0.972000       0.974000      0.976000   \n",
       "max    737791.000000       4.482000       4.508000      4.558000   \n",
       "\n",
       "       February 2011    March 2011    April 2011      May 2011     June 2011  \\\n",
       "count   10744.000000  10829.000000  10878.000000  10885.000000  10885.000000   \n",
       "mean        0.864939      0.862232      0.860946      0.859769      0.859848   \n",
       "std         0.281532      0.278903      0.277075      0.275870      0.275311   \n",
       "min         0.358000      0.362000      0.366000      0.366000      0.366000   \n",
       "25%         0.682000      0.680000      0.678000      0.678000      0.678000   \n",
       "50%         0.802000      0.800000      0.800000      0.798000      0.800000   \n",
       "75%         0.972000      0.970000      0.968000      0.968000      0.968000   \n",
       "max         4.564000      4.548000      4.536000      4.528000      4.536000   \n",
       "\n",
       "          July 2011         ...            August 2016  September 2016  \\\n",
       "count  10885.000000         ...           11919.000000    11919.000000   \n",
       "mean       0.859505         ...               0.963645        0.962379   \n",
       "std        0.274526         ...               0.380334        0.381100   \n",
       "min        0.368000         ...               0.382000        0.378000   \n",
       "25%        0.678000         ...               0.730000        0.728000   \n",
       "50%        0.800000         ...               0.870000        0.870000   \n",
       "75%        0.968000         ...               1.080000        1.080000   \n",
       "max        4.542000         ...               6.476000        6.486000   \n",
       "\n",
       "       October 2016  November 2016  December 2016  January 2017  Total Change  \\\n",
       "count  11919.000000   11919.000000   11919.000000  11919.000000  10600.000000   \n",
       "mean       0.962570       0.963743       0.964275      0.964356      0.097617   \n",
       "std        0.381545       0.381775       0.381395      0.381297      0.143625   \n",
       "min        0.378000       0.378000       0.378000      0.378000     -0.842000   \n",
       "25%        0.728000       0.728000       0.730000      0.732000      0.020000   \n",
       "50%        0.870000       0.870000       0.872000      0.872000      0.074000   \n",
       "75%        1.082000       1.082000       1.080000      1.080000      0.144000   \n",
       "max        6.476000       6.470000       6.440000      6.406000      1.924000   \n",
       "\n",
       "       Percent Change   Year Change  Year Percent Change  \n",
       "count    10600.000000  11919.000000         11919.000000  \n",
       "mean         0.107012      0.017929             0.017944  \n",
       "std          0.131925      0.045231             0.044913  \n",
       "min         -0.440605     -0.542000            -0.247191  \n",
       "25%          0.026565     -0.008000            -0.008496  \n",
       "50%          0.094149      0.014000             0.015873  \n",
       "75%          0.171582      0.040000             0.043147  \n",
       "max          0.905512      0.628000             0.282572  \n",
       "\n",
       "[8 rows x 80 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sqft.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Looking at Specific Geographic Cities"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Los Angeles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "losAngeles = (price.loc[price['Metro'] == 'Los Angeles'])\n",
    "losAngelesppsqft = (sqft.loc[sqft['City Code'].isin(losAngeles['City Code'])])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty DataFrame\n",
      "Columns: [January 2011, February 2011, March 2011, April 2011, May 2011, June 2011, July 2011, August 2011, September 2011, October 2011, November 2011, December 2011, January 2012, February 2012, March 2012, April 2012, May 2012, June 2012, July 2012, August 2012, September 2012, October 2012, November 2012, December 2012, January 2013, February 2013, March 2013, April 2013, May 2013, June 2013, July 2013, August 2013, September 2013, October 2013, November 2013, December 2013, January 2014, February 2014, March 2014, April 2014, May 2014, June 2014, July 2014, August 2014, September 2014, October 2014, November 2014, December 2014, January 2015, February 2015, March 2015, April 2015, May 2015, June 2015, July 2015, August 2015, September 2015, October 2015, November 2015, December 2015, January 2016, February 2016, March 2016, April 2016, May 2016, June 2016, July 2016, August 2016, September 2016, October 2016, November 2016, December 2016, January 2017, Total Change, Percent Change, Year Change, Year Percent Change]\n",
      "Index: []\n",
      "\n",
      "[0 rows x 77 columns]\n"
     ]
    }
   ],
   "source": [
    "x = losAngeles.iloc[0:0,7:]               # date columns\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 January 2011  February 2011  March 2011  April 2011  \\\n",
      "Population Rank                                                        \n",
      "2                      2183.0         2188.0      2189.0      2189.0   \n",
      "37                     1968.0         1964.0      1960.0      1950.0   \n",
      "54                     2179.0         2170.0      2161.0      2159.0   \n",
      "55                     1996.0         1996.0      1995.0      1994.0   \n",
      "112                    2553.0         2568.0      2575.0      2574.0   \n",
      "129                    2378.0         2363.0      2341.0      2334.0   \n",
      "134                    2500.0         2501.0      2498.0      2493.0   \n",
      "145                    1598.0         1557.0      1526.0      1509.0   \n",
      "160                    2155.0         2146.0      2139.0      2141.0   \n",
      "168                    1630.0         1603.0      1578.0      1560.0   \n",
      "180                    2206.0         2209.0      2209.0      2206.0   \n",
      "181                    1715.0         1701.0      1676.0      1656.0   \n",
      "206                    2292.0         2294.0      2292.0      2295.0   \n",
      "207                    2510.0         2507.0      2503.0      2500.0   \n",
      "211                    2248.0         2252.0      2257.0      2259.0   \n",
      "220                    1933.0         1931.0      1926.0      1914.0   \n",
      "221                    2357.0         2360.0      2364.0      2369.0   \n",
      "226                    1622.0         1622.0      1622.0      1621.0   \n",
      "235                    1616.0         1619.0      1611.0      1602.0   \n",
      "263                    2047.0         2061.0      2078.0      2085.0   \n",
      "274                    2409.0         2414.0      2422.0      2424.0   \n",
      "291                    1790.0         1795.0      1806.0      1816.0   \n",
      "293                    1842.0         1834.0      1826.0      1823.0   \n",
      "295                    2399.0         2385.0      2364.0      2345.0   \n",
      "316                    1957.0         1962.0      1967.0      1963.0   \n",
      "340                    1698.0         1699.0      1701.0      1702.0   \n",
      "362                    2472.0         2477.0      2480.0      2485.0   \n",
      "387                    3466.0         3474.0      3450.0      3387.0   \n",
      "435                    2163.0         2154.0      2149.0      2149.0   \n",
      "442                    2072.0         2064.0      2056.0      2047.0   \n",
      "...                       ...            ...         ...         ...   \n",
      "3067                   1811.0         1800.0      1795.0      1792.0   \n",
      "3127                   3032.0         3032.0      3039.0      3041.0   \n",
      "3143                   2506.0         2520.0      2529.0      2530.0   \n",
      "3165                   1615.0         1612.0      1599.0      1587.0   \n",
      "3221                   1685.0         1686.0      1682.0      1677.0   \n",
      "3320                   2317.0         2306.0      2305.0      2306.0   \n",
      "3333                   8128.0         8140.0      8162.0      8156.0   \n",
      "3803                   2644.0         2633.0      2612.0      2586.0   \n",
      "3818                   2504.0         2502.0      2498.0      2489.0   \n",
      "3819                   5887.0         5993.0      6062.0      6107.0   \n",
      "3847                   1556.0         1525.0      1485.0      1449.0   \n",
      "3868                   1974.0         1971.0      1969.0      1964.0   \n",
      "4026                   1907.0         1893.0      1881.0      1867.0   \n",
      "4459                   1964.0         1954.0      1943.0      1924.0   \n",
      "4893                   2110.0         2114.0      2124.0      2131.0   \n",
      "5142                   3624.0         3648.0      3678.0      3698.0   \n",
      "5846                   3169.0         3188.0      3204.0      3173.0   \n",
      "6115                   4042.0         4048.0      4061.0      4051.0   \n",
      "6191                   2088.0         2090.0      2097.0      2101.0   \n",
      "6248                   3042.0         3009.0      2988.0      2967.0   \n",
      "6775                   2381.0         2347.0      2296.0      2245.0   \n",
      "6851                   2415.0         2422.0      2427.0      2428.0   \n",
      "7689                   2356.0         2338.0      2321.0      2308.0   \n",
      "9589                   1680.0         1660.0      1622.0      1583.0   \n",
      "9616                   4224.0         4246.0      4272.0      4292.0   \n",
      "9996                   1646.0         1632.0      1604.0      1581.0   \n",
      "10254                  9911.0         9994.0     10054.0     10075.0   \n",
      "11053                  9377.0         9371.0      9438.0      9466.0   \n",
      "11438                  4894.0         4920.0      4938.0      4940.0   \n",
      "13021                  1782.0         1775.0      1785.0      1787.0   \n",
      "\n",
      "                 May 2011  June 2011  July 2011  August 2011  September 2011  \\\n",
      "Population Rank                                                                \n",
      "2                  2188.0     2191.0     2189.0       2186.0          2183.0   \n",
      "37                 1946.0     1946.0     1950.0       1947.0          1941.0   \n",
      "54                 2163.0     2172.0     2177.0       2178.0          2177.0   \n",
      "55                 1992.0     1994.0     1994.0       1994.0          1989.0   \n",
      "112                2567.0     2567.0     2576.0       2592.0          2610.0   \n",
      "129                2326.0     2319.0     2305.0       2290.0          2280.0   \n",
      "134                2492.0     2493.0     2493.0       2488.0          2484.0   \n",
      "145                1495.0     1480.0     1467.0       1456.0          1450.0   \n",
      "160                2144.0     2152.0     2154.0       2154.0          2150.0   \n",
      "168                1543.0     1527.0     1528.0       1525.0          1523.0   \n",
      "180                2204.0     2210.0     2217.0       2222.0          2217.0   \n",
      "181                1645.0     1635.0     1632.0       1638.0          1643.0   \n",
      "206                2293.0     2294.0     2281.0       2260.0          2244.0   \n",
      "207                2498.0     2497.0     2489.0       2481.0          2478.0   \n",
      "211                2262.0     2265.0     2266.0       2265.0          2260.0   \n",
      "220                1906.0     1897.0     1894.0       1882.0          1868.0   \n",
      "221                2376.0     2382.0     2388.0       2392.0          2401.0   \n",
      "226                1619.0     1608.0     1612.0       1616.0          1626.0   \n",
      "235                1595.0     1593.0     1605.0       1621.0          1641.0   \n",
      "263                2083.0     2074.0     2069.0       2061.0          2061.0   \n",
      "274                2427.0     2432.0     2436.0       2438.0          2437.0   \n",
      "291                1826.0     1826.0     1825.0       1823.0          1823.0   \n",
      "293                1822.0     1826.0     1831.0       1832.0          1829.0   \n",
      "295                2329.0     2315.0     2308.0       2301.0          2303.0   \n",
      "316                1961.0     1962.0     1970.0       1975.0          1976.0   \n",
      "340                1702.0     1697.0     1701.0       1705.0          1712.0   \n",
      "362                2486.0     2487.0     2487.0       2487.0          2494.0   \n",
      "387                3331.0     3294.0     3269.0       3236.0          3201.0   \n",
      "435                2150.0     2151.0     2147.0       2144.0          2144.0   \n",
      "442                2046.0     2045.0     2050.0       2043.0          2038.0   \n",
      "...                   ...        ...        ...          ...             ...   \n",
      "3067               1796.0     1797.0     1796.0       1795.0          1795.0   \n",
      "3127               3045.0     3051.0     3070.0       3098.0          3137.0   \n",
      "3143               2527.0     2529.0     2541.0       2557.0          2570.0   \n",
      "3165               1583.0     1576.0     1583.0       1590.0          1603.0   \n",
      "3221               1673.0     1671.0     1678.0       1690.0          1706.0   \n",
      "3320               2311.0     2317.0     2319.0       2317.0          2317.0   \n",
      "3333               8132.0     8083.0     8017.0       7952.0          7894.0   \n",
      "3803               2566.0     2544.0     2506.0       2472.0          2456.0   \n",
      "3818               2489.0     2497.0     2487.0       2473.0          2458.0   \n",
      "3819               6103.0     6090.0     6058.0       6019.0          5981.0   \n",
      "3847               1426.0     1407.0     1392.0       1374.0          1353.0   \n",
      "3868               1961.0     1963.0     1971.0       1975.0          1973.0   \n",
      "4026               1861.0     1852.0     1851.0       1841.0          1832.0   \n",
      "4459               1902.0     1886.0     1881.0       1880.0          1885.0   \n",
      "4893               2139.0     2143.0     2143.0       2129.0          2118.0   \n",
      "5142               3703.0     3692.0     3669.0       3642.0          3615.0   \n",
      "5846               3173.0     3154.0     3128.0       3080.0          3029.0   \n",
      "6115               4037.0     4012.0     4001.0       3997.0          4004.0   \n",
      "6191               2098.0     2098.0     2097.0       2099.0          2100.0   \n",
      "6248               2955.0     2918.0     2884.0       2850.0          2841.0   \n",
      "6775               2212.0     2201.0     2192.0       2191.0          2191.0   \n",
      "6851               2428.0     2436.0     2443.0       2446.0          2449.0   \n",
      "7689               2302.0     2299.0     2290.0       2275.0          2261.0   \n",
      "9589               1559.0     1544.0     1541.0       1556.0          1545.0   \n",
      "9616               4311.0     4315.0     4305.0       4284.0          4259.0   \n",
      "9996               1562.0     1546.0     1540.0       1535.0          1521.0   \n",
      "10254             10080.0    10091.0    10096.0      10125.0         10150.0   \n",
      "11053              9476.0     9425.0     9367.0       9309.0          9290.0   \n",
      "11438              4948.0     4949.0     4938.0       4924.0          4911.0   \n",
      "13021              1790.0     1772.0     1757.0       1710.0          1692.0   \n",
      "\n",
      "                 October 2011         ...           August 2016  \\\n",
      "Population Rank                       ...                         \n",
      "2                      2183.0         ...                  2716   \n",
      "37                     1925.0         ...                  2335   \n",
      "54                     2179.0         ...                  2582   \n",
      "55                     1986.0         ...                  2465   \n",
      "112                    2625.0         ...                  3134   \n",
      "129                    2274.0         ...                  2944   \n",
      "134                    2483.0         ...                  3045   \n",
      "145                    1442.0         ...                  1597   \n",
      "160                    2145.0         ...                  2541   \n",
      "168                    1504.0         ...                  1672   \n",
      "180                    2209.0         ...                  2530   \n",
      "181                    1644.0         ...                  1999   \n",
      "206                    2234.0         ...                  2719   \n",
      "207                    2472.0         ...                  2999   \n",
      "211                    2254.0         ...                  2683   \n",
      "220                    1850.0         ...                  2321   \n",
      "221                    2411.0         ...                  2871   \n",
      "226                    1626.0         ...                  2010   \n",
      "235                    1648.0         ...                  2038   \n",
      "263                    2055.0         ...                  2403   \n",
      "274                    2441.0         ...                  3028   \n",
      "291                    1826.0         ...                  2193   \n",
      "293                    1825.0         ...                  2191   \n",
      "295                    2307.0         ...                  3009   \n",
      "316                    1975.0         ...                  2304   \n",
      "340                    1709.0         ...                  2089   \n",
      "362                    2502.0         ...                  2996   \n",
      "387                    3191.0         ...                  4512   \n",
      "435                    2143.0         ...                  2491   \n",
      "442                    2027.0         ...                  2490   \n",
      "...                       ...         ...                   ...   \n",
      "3067                   1792.0         ...                  2146   \n",
      "3127                   3166.0         ...                  3991   \n",
      "3143                   2584.0         ...                  2936   \n",
      "3165                   1607.0         ...                  1980   \n",
      "3221                   1714.0         ...                  2040   \n",
      "3320                   2335.0         ...                  2653   \n",
      "3333                   7843.0         ...                  9157   \n",
      "3803                   2459.0         ...                  3112   \n",
      "3818                   2436.0         ...                  3088   \n",
      "3819                   5962.0         ...                  8188   \n",
      "3847                   1334.0         ...                  1503   \n",
      "3868                   1970.0         ...                  2287   \n",
      "4026                   1812.0         ...                  2242   \n",
      "4459                   1891.0         ...                  2299   \n",
      "4893                   2111.0         ...                  2536   \n",
      "5142                   3591.0         ...                  4669   \n",
      "5846                   2999.0         ...                  3906   \n",
      "6115                   4003.0         ...                  4671   \n",
      "6191                   2101.0         ...                  2445   \n",
      "6248                   2830.0         ...                  3398   \n",
      "6775                   2174.0         ...                  2498   \n",
      "6851                   2451.0         ...                  3061   \n",
      "7689                   2245.0         ...                  2729   \n",
      "9589                   1538.0         ...                  1692   \n",
      "9616                   4243.0         ...                  4904   \n",
      "9996                   1509.0         ...                  1821   \n",
      "10254                 10195.0         ...                 11936   \n",
      "11053                  9317.0         ...                 12824   \n",
      "11438                  4902.0         ...                  5653   \n",
      "13021                  1674.0         ...                  2134   \n",
      "\n",
      "                 September 2016  October 2016  November 2016  December 2016  \\\n",
      "Population Rank                                                               \n",
      "2                          2723          2731           2740           2748   \n",
      "37                         2334          2338           2350           2364   \n",
      "54                         2591          2598           2599           2602   \n",
      "55                         2461          2462           2465           2467   \n",
      "112                        3127          3125           3130           3136   \n",
      "129                        2946          2946           2945           2952   \n",
      "134                        3049          3052           3056           3062   \n",
      "145                        1612          1628           1636           1646   \n",
      "160                        2545          2551           2553           2557   \n",
      "168                        1683          1694           1700           1714   \n",
      "180                        2544          2553           2556           2551   \n",
      "181                        2001          2010           2018           2029   \n",
      "206                        2719          2722           2729           2734   \n",
      "207                        3013          3032           3043           3046   \n",
      "211                        2693          2700           2708           2717   \n",
      "220                        2322          2319           2321           2335   \n",
      "221                        2877          2882           2887           2901   \n",
      "226                        2016          2030           2053           2079   \n",
      "235                        2051          2068           2080           2092   \n",
      "263                        2406          2410           2420           2433   \n",
      "274                        3031          3032           3031           3026   \n",
      "291                        2199          2203           2214           2224   \n",
      "293                        2190          2193           2206           2223   \n",
      "295                        3012          3008           3003           3009   \n",
      "316                        2307          2313           2321           2328   \n",
      "340                        2098          2112           2129           2152   \n",
      "362                        3004          3012           3020           3026   \n",
      "387                        4486          4492           4528           4556   \n",
      "435                        2489          2493           2499           2506   \n",
      "442                        2492          2490           2491           2497   \n",
      "...                         ...           ...            ...            ...   \n",
      "3067                       2145          2149           2157           2164   \n",
      "3127                       4014          4020           4012           4012   \n",
      "3143                       2930          2925           2928           2932   \n",
      "3165                       1983          1990           1994           2004   \n",
      "3221                       2048          2062           2080           2105   \n",
      "3320                       2666          2675           2673           2669   \n",
      "3333                       9078          8981           8996           9069   \n",
      "3803                       3129          3140           3142           3131   \n",
      "3818                       3089          3103           3109           3108   \n",
      "3819                       8156          8122           8175           8269   \n",
      "3847                       1513          1530           1547           1562   \n",
      "3868                       2283          2286           2295           2309   \n",
      "4026                       2244          2252           2264           2283   \n",
      "4459                       2313          2325           2335           2349   \n",
      "4893                       2528          2523           2528           2533   \n",
      "5142                       4674          4702           4712           4686   \n",
      "5846                       3907          3919           3962           4002   \n",
      "6115                       4713          4762           4802           4834   \n",
      "6191                       2445          2437           2440           2447   \n",
      "6248                       3370          3362           3355           3332   \n",
      "6775                       2499          2503           2507           2511   \n",
      "6851                       3056          3055           3042           3019   \n",
      "7689                       2722          2721           2711           2695   \n",
      "9589                       1703          1723           1744           1761   \n",
      "9616                       4886          4868           4897           4946   \n",
      "9996                       1832          1852           1859           1858   \n",
      "10254                     11906         11901          11996          12172   \n",
      "11053                     12734         12586          12479          12444   \n",
      "11438                      5633          5624           5677           5765   \n",
      "13021                      2135          2129           2126           2127   \n",
      "\n",
      "                 January 2017  Total Change  Percent Change  Year Change  \\\n",
      "Population Rank                                                            \n",
      "2                        2753         569.0        0.260531          157   \n",
      "37                       2375         399.0        0.201923          121   \n",
      "54                       2608         427.0        0.195782          131   \n",
      "55                       2473         479.0        0.240221           86   \n",
      "112                      3145         616.0        0.243575           80   \n",
      "129                      2959         579.0        0.243277          174   \n",
      "134                      3074         586.0        0.235531          161   \n",
      "145                      1651         -16.0       -0.009598          139   \n",
      "160                      2561         397.0        0.183457          103   \n",
      "168                      1727          53.0        0.031661          133   \n",
      "180                      2546         352.0        0.160438           93   \n",
      "181                      2038         318.0        0.184884          101   \n",
      "206                      2739         452.0        0.197639          112   \n",
      "207                      3045         543.0        0.217026          151   \n",
      "211                      2729         498.0        0.223218          188   \n",
      "220                      2356         398.0        0.203269          171   \n",
      "221                      2916         566.0        0.240851          210   \n",
      "226                      2101         457.0        0.277981          163   \n",
      "235                      2105         493.0        0.305831          171   \n",
      "263                      2443         394.0        0.192289           92   \n",
      "274                      3025         634.0        0.265161          139   \n",
      "291                      2235         444.0        0.247906          122   \n",
      "293                      2235         367.0        0.196467          100   \n",
      "295                      3019         622.0        0.259491          184   \n",
      "316                      2339         373.0        0.189725           65   \n",
      "340                      2171         456.0        0.265889          161   \n",
      "362                      3032         568.0        0.230519          155   \n",
      "387                      4560        1135.0        0.331387          130   \n",
      "435                      2516         338.0        0.155188           74   \n",
      "442                      2505         401.0        0.190589          134   \n",
      "...                       ...           ...             ...          ...   \n",
      "3067                     2175         371.0        0.205654           79   \n",
      "3127                     4009         971.0        0.319618          343   \n",
      "3143                     2937         453.0        0.182367          107   \n",
      "3165                     2018         386.0        0.236520           98   \n",
      "3221                     2126         425.0        0.249853          147   \n",
      "3320                     2657         310.0        0.132084          110   \n",
      "3333                     9199        1118.0        0.138349          319   \n",
      "3803                     3132         514.0        0.196333          149   \n",
      "3818                     3114         612.0        0.244604          216   \n",
      "3819                     8425        2641.0        0.456604          124   \n",
      "3847                     1573         -11.0       -0.006944          153   \n",
      "3868                     2318         345.0        0.174861           99   \n",
      "4026                     2295         347.0        0.178131          158   \n",
      "4459                     2359         368.0        0.184832          162   \n",
      "4893                     2537         419.0        0.197828          100   \n",
      "5142                     4623        1054.0        0.295321          -37   \n",
      "5846                     4075         998.0        0.324342          261   \n",
      "6115                     4853         801.0        0.197680          371   \n",
      "6191                     2457         370.0        0.177288           62   \n",
      "6248                     3303         252.0        0.082596         -296   \n",
      "6775                     2526         124.0        0.051624          115   \n",
      "6851                     2991         599.0        0.250418           89   \n",
      "7689                     2673         282.0        0.117942          -53   \n",
      "9589                     1780          92.0        0.054502          211   \n",
      "9616                     5013         822.0        0.196135          200   \n",
      "9996                     1849         196.0        0.118572          129   \n",
      "10254                   12428        2611.0        0.265967          443   \n",
      "11053                   12504        3190.0        0.342495          336   \n",
      "11438                    5838        1002.0        0.207196          565   \n",
      "13021                    2117         287.0        0.156831          112   \n",
      "\n",
      "                 Year Percent Change  \n",
      "Population Rank                       \n",
      "2                           0.060478  \n",
      "37                          0.053682  \n",
      "54                          0.052887  \n",
      "55                          0.036028  \n",
      "112                         0.026101  \n",
      "129                         0.062478  \n",
      "134                         0.055269  \n",
      "145                         0.091931  \n",
      "160                         0.041904  \n",
      "168                         0.083438  \n",
      "180                         0.037913  \n",
      "181                         0.052142  \n",
      "206                         0.042634  \n",
      "207                         0.052177  \n",
      "211                         0.073987  \n",
      "220                         0.078261  \n",
      "221                         0.077605  \n",
      "226                         0.084107  \n",
      "235                         0.088418  \n",
      "263                         0.039132  \n",
      "274                         0.048164  \n",
      "291                         0.057738  \n",
      "293                         0.046838  \n",
      "295                         0.064903  \n",
      "316                         0.028584  \n",
      "340                         0.080100  \n",
      "362                         0.053876  \n",
      "387                         0.029345  \n",
      "435                         0.030303  \n",
      "442                         0.056516  \n",
      "...                              ...  \n",
      "3067                        0.037691  \n",
      "3127                        0.093562  \n",
      "3143                        0.037809  \n",
      "3165                        0.051042  \n",
      "3221                        0.074280  \n",
      "3320                        0.043188  \n",
      "3333                        0.035923  \n",
      "3803                        0.049950  \n",
      "3818                        0.074534  \n",
      "3819                        0.014938  \n",
      "3847                        0.107746  \n",
      "3868                        0.044615  \n",
      "4026                        0.073935  \n",
      "4459                        0.073737  \n",
      "4893                        0.041034  \n",
      "5142                       -0.007940  \n",
      "5846                        0.068432  \n",
      "6115                        0.082776  \n",
      "6191                        0.025887  \n",
      "6248                       -0.082245  \n",
      "6775                        0.047698  \n",
      "6851                        0.030669  \n",
      "7689                       -0.019442  \n",
      "9589                        0.134481  \n",
      "9616                        0.041554  \n",
      "9996                        0.075000  \n",
      "10254                       0.036963  \n",
      "11053                       0.027613  \n",
      "11438                       0.107150  \n",
      "13021                       0.055860  \n",
      "\n",
      "[148 rows x 77 columns]\n"
     ]
    }
   ],
   "source": [
    "y = losAngeles.ix[:,7:]                 # year values\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### San Francisco"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "SF = (price.loc[price['Metro'] == 'San Francisco'])\n",
    "SFppsqft = (sqft.loc[sqft['City Code'].isin(SF['City Code'])])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty DataFrame\n",
      "Columns: [January 2011, February 2011, March 2011, April 2011, May 2011, June 2011, July 2011, August 2011, September 2011, October 2011, November 2011, December 2011, January 2012, February 2012, March 2012, April 2012, May 2012, June 2012, July 2012, August 2012, September 2012, October 2012, November 2012, December 2012, January 2013, February 2013, March 2013, April 2013, May 2013, June 2013, July 2013, August 2013, September 2013, October 2013, November 2013, December 2013, January 2014, February 2014, March 2014, April 2014, May 2014, June 2014, July 2014, August 2014, September 2014, October 2014, November 2014, December 2014, January 2015, February 2015, March 2015, April 2015, May 2015, June 2015, July 2015, August 2015, September 2015, October 2015, November 2015, December 2015, January 2016, February 2016, March 2016, April 2016, May 2016, June 2016, July 2016, August 2016, September 2016, October 2016, November 2016, December 2016, January 2017, Total Change, Percent Change, Year Change, Year Percent Change]\n",
      "Index: []\n",
      "\n",
      "[0 rows x 77 columns]\n"
     ]
    }
   ],
   "source": [
    "x = SF.iloc[0:0,7:]               # date columns\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                 January 2011  February 2011  March 2011  April 2011  \\\n",
      "Population Rank                                                        \n",
      "13                     3189.0         3127.0      3040.0      2970.0   \n",
      "43                     1816.0         1767.0      1729.0      1712.0   \n",
      "103                    2204.0         2188.0      2172.0      2163.0   \n",
      "150                    1884.0         1848.0      1809.0      1783.0   \n",
      "241                    1830.0         1825.0      1817.0      1819.0   \n",
      "258                    2255.0         2289.0      2324.0      2344.0   \n",
      "333                    2483.0         2535.0      2573.0      2607.0   \n",
      "335                    2307.0         2327.0      2333.0      2332.0   \n",
      "338                    1864.0         1847.0      1826.0      1809.0   \n",
      "365                    1777.0         1751.0      1716.0      1702.0   \n",
      "399                    2125.0         2132.0      2132.0      2129.0   \n",
      "441                    1599.0         1591.0      1571.0      1560.0   \n",
      "462                    2805.0         2779.0      2739.0      2738.0   \n",
      "491                    2081.0         2131.0      2199.0      2256.0   \n",
      "529                    1638.0         1617.0      1590.0      1578.0   \n",
      "554                    2532.0         2574.0      2639.0      2688.0   \n",
      "576                    2372.0         2395.0      2414.0      2435.0   \n",
      "619                    2537.0         2584.0      2624.0      2659.0   \n",
      "625                    2121.0         2128.0      2126.0      2115.0   \n",
      "643                    2153.0         2185.0      2214.0      2218.0   \n",
      "733                    2363.0         2390.0      2434.0      2450.0   \n",
      "750                    2095.0         2100.0      2103.0      2099.0   \n",
      "769                    2276.0         2313.0      2346.0      2365.0   \n",
      "892                    1580.0         1566.0      1548.0      1535.0   \n",
      "969                    3298.0         3304.0      3304.0      3338.0   \n",
      "996                    2173.0         2168.0      2168.0      2166.0   \n",
      "1042                   1851.0         1856.0      1863.0      1877.0   \n",
      "1079                   2063.0         2075.0      2076.0      2064.0   \n",
      "1166                   3849.0         3741.0      3643.0      3573.0   \n",
      "1233                   2275.0         2312.0      2354.0      2377.0   \n",
      "...                       ...            ...         ...         ...   \n",
      "3459                   3751.0         3818.0      3901.0      3994.0   \n",
      "3728                   3215.0         3220.0      3236.0      3306.0   \n",
      "3742                   4275.0         4350.0      4411.0      4443.0   \n",
      "3848                   8353.0         8188.0      8106.0      8093.0   \n",
      "4160                   7683.0         7050.0      6330.0      5924.0   \n",
      "4175                   2029.0         2049.0      2079.0      2070.0   \n",
      "4220                   1540.0         1551.0      1550.0      1548.0   \n",
      "4288                   2955.0         3020.0      3113.0      3143.0   \n",
      "4324                   2283.0         2324.0      2364.0      2394.0   \n",
      "4350                   6841.0         6708.0      6647.0      6649.0   \n",
      "4560                   3723.0         3531.0      3339.0      3237.0   \n",
      "4779                   1797.0         1786.0      1772.0      1772.0   \n",
      "5070                   2431.0         2454.0      2484.0      2505.0   \n",
      "5152                  11019.0        10781.0     10687.0     10698.0   \n",
      "5282                   2192.0         2203.0      2214.0      2213.0   \n",
      "5474                   6707.0         6121.0      5472.0      5096.0   \n",
      "5716                   4770.0         4413.0      4030.0      3831.0   \n",
      "6038                   2421.0         2449.0      2491.0      2542.0   \n",
      "6703                   2279.0         2303.0      2324.0      2334.0   \n",
      "7052                   7633.0         7445.0      7349.0      7322.0   \n",
      "7327                   2278.0         2300.0      2312.0      2325.0   \n",
      "7564                   4376.0         4287.0      4255.0      4271.0   \n",
      "9424                   3719.0         3657.0      3621.0      3581.0   \n",
      "9490                  11227.0        10285.0      9209.0      8544.0   \n",
      "9516                   3027.0         3007.0      2977.0      2965.0   \n",
      "9808                   1774.0         1754.0      1729.0      1717.0   \n",
      "11096                  2357.0         2387.0      2433.0      2466.0   \n",
      "12432                  2929.0         2931.0      2920.0      2929.0   \n",
      "12714                  9318.0         8454.0      7511.0      6907.0   \n",
      "13095                  8646.0         7995.0      7176.0      6633.0   \n",
      "\n",
      "                 May 2011  June 2011  July 2011  August 2011  September 2011  \\\n",
      "Population Rank                                                                \n",
      "13                 2916.0     2879.0     2848.0       2848.0          2868.0   \n",
      "43                 1698.0     1698.0     1703.0       1710.0          1711.0   \n",
      "103                2157.0     2148.0     2133.0       2110.0          2091.0   \n",
      "150                1754.0     1739.0     1737.0       1746.0          1752.0   \n",
      "241                1824.0     1833.0     1843.0       1849.0          1851.0   \n",
      "258                2356.0     2370.0     2360.0       2358.0          2340.0   \n",
      "333                2627.0     2644.0     2647.0       2650.0          2657.0   \n",
      "335                2342.0     2356.0     2364.0       2366.0          2360.0   \n",
      "338                1791.0     1783.0     1780.0       1777.0          1758.0   \n",
      "365                1699.0     1705.0     1711.0       1713.0          1708.0   \n",
      "399                2122.0     2108.0     2095.0       2077.0          2078.0   \n",
      "441                1558.0     1565.0     1576.0       1591.0          1600.0   \n",
      "462                2760.0     2789.0     2808.0       2810.0          2804.0   \n",
      "491                2303.0     2332.0     2340.0       2337.0          2336.0   \n",
      "529                1577.0     1581.0     1584.0       1584.0          1585.0   \n",
      "554                2726.0     2752.0     2765.0       2771.0          2780.0   \n",
      "576                2459.0     2492.0     2509.0       2520.0          2519.0   \n",
      "619                2686.0     2708.0     2722.0       2735.0          2753.0   \n",
      "625                2095.0     2065.0     2034.0       2004.0          1991.0   \n",
      "643                2213.0     2213.0     2199.0       2181.0          2164.0   \n",
      "733                2460.0     2463.0     2474.0       2490.0          2523.0   \n",
      "750                2091.0     2087.0     2086.0       2089.0          2095.0   \n",
      "769                2389.0     2415.0     2438.0       2452.0          2464.0   \n",
      "892                1533.0     1540.0     1555.0       1570.0          1580.0   \n",
      "969                3378.0     3401.0     3412.0       3419.0          3434.0   \n",
      "996                2159.0     2148.0     2132.0       2108.0          2088.0   \n",
      "1042               1886.0     1892.0     1890.0       1883.0          1875.0   \n",
      "1079               2038.0     1997.0     1956.0       1918.0          1901.0   \n",
      "1166               3539.0     3520.0     3519.0       3511.0          3496.0   \n",
      "1233               2403.0     2427.0     2453.0       2469.0          2489.0   \n",
      "...                   ...        ...        ...          ...             ...   \n",
      "3459               4060.0     4094.0     4096.0       4087.0          4089.0   \n",
      "3728               3367.0     3412.0     3431.0       3439.0          3456.0   \n",
      "3742               4472.0     4492.0     4498.0       4493.0          4487.0   \n",
      "3848               8101.0     8119.0     8119.0       8109.0          8106.0   \n",
      "4160               5698.0     5578.0     5533.0       5497.0          5530.0   \n",
      "4175               2059.0     2044.0     2052.0       2076.0          2126.0   \n",
      "4220               1544.0     1549.0     1552.0       1547.0          1541.0   \n",
      "4288               3122.0     3108.0     3117.0       3142.0          3167.0   \n",
      "4324               2415.0     2425.0     2412.0       2399.0          2396.0   \n",
      "4350               6644.0     6639.0     6605.0       6570.0          6539.0   \n",
      "4560               3166.0     3142.0     3136.0       3139.0          3160.0   \n",
      "4779               1778.0     1786.0     1790.0       1794.0          1797.0   \n",
      "5070               2521.0     2538.0     2556.0       2574.0          2576.0   \n",
      "5152              10716.0    10772.0    10805.0      10832.0         10864.0   \n",
      "5282               2203.0     2196.0     2191.0       2196.0          2197.0   \n",
      "5474               4833.0     4693.0     4674.0       4687.0          4726.0   \n",
      "5716               3717.0     3644.0     3593.0       3548.0          3561.0   \n",
      "6038               2576.0     2606.0     2607.0       2626.0          2668.0   \n",
      "6703               2351.0     2377.0     2412.0       2450.0          2481.0   \n",
      "7052               7352.0     7377.0     7363.0       7356.0          7360.0   \n",
      "7327               2336.0     2351.0     2351.0       2340.0          2320.0   \n",
      "7564               4303.0     4381.0     4469.0       4591.0          4690.0   \n",
      "9424               3516.0     3442.0     3385.0       3352.0          3362.0   \n",
      "9490               8072.0     7810.0     7724.0       7703.0          7743.0   \n",
      "9516               2983.0     3028.0     3081.0       3112.0          3112.0   \n",
      "9808               1716.0     1721.0     1726.0       1729.0          1729.0   \n",
      "11096              2494.0     2529.0     2566.0       2597.0          2590.0   \n",
      "12432              2959.0     3008.0     3065.0       3097.0          3104.0   \n",
      "12714              6516.0     6291.0     6197.0       6144.0          6149.0   \n",
      "13095              6211.0     5979.0     5889.0       5841.0          5811.0   \n",
      "\n",
      "                 October 2011         ...           August 2016  \\\n",
      "Population Rank                       ...                         \n",
      "13                     2907.0         ...                  4500   \n",
      "43                     1706.0         ...                  2883   \n",
      "103                    2088.0         ...                  3171   \n",
      "150                    1755.0         ...                  2629   \n",
      "241                    1856.0         ...                  2508   \n",
      "258                    2331.0         ...                  3535   \n",
      "333                    2675.0         ...                  3896   \n",
      "335                    2347.0         ...                  3443   \n",
      "338                    1736.0         ...                  2634   \n",
      "365                    1701.0         ...                  2114   \n",
      "399                    2094.0         ...                  3044   \n",
      "441                    1603.0         ...                  2361   \n",
      "462                    2793.0         ...                  4094   \n",
      "491                    2341.0         ...                  3281   \n",
      "529                    1586.0         ...                  2066   \n",
      "554                    2807.0         ...                  3704   \n",
      "576                    2533.0         ...                  3498   \n",
      "619                    2777.0         ...                  3895   \n",
      "625                    2005.0         ...                  3019   \n",
      "643                    2160.0         ...                  3415   \n",
      "733                    2560.0         ...                  3499   \n",
      "750                    2100.0         ...                  2471   \n",
      "769                    2471.0         ...                  3533   \n",
      "892                    1583.0         ...                  2281   \n",
      "969                    3453.0         ...                  4466   \n",
      "996                    2081.0         ...                  3107   \n",
      "1042                   1875.0         ...                  2584   \n",
      "1079                   1903.0         ...                  2935   \n",
      "1166                   3460.0         ...                  5430   \n",
      "1233                   2503.0         ...                  3687   \n",
      "...                       ...         ...                   ...   \n",
      "3459                   4116.0         ...                  5409   \n",
      "3728                   3489.0         ...                  4653   \n",
      "3742                   4509.0         ...                  6720   \n",
      "3848                   8146.0         ...                 11544   \n",
      "4160                   5565.0         ...                  7887   \n",
      "4175                   2202.0         ...                  3433   \n",
      "4220                   1536.0         ...                  2619   \n",
      "4288                   3210.0         ...                  4824   \n",
      "4324                   2413.0         ...                  3288   \n",
      "4350                   6555.0         ...                  8469   \n",
      "4560                   3195.0         ...                  4756   \n",
      "4779                   1806.0         ...                  2411   \n",
      "5070                   2584.0         ...                  3582   \n",
      "5152                  10931.0         ...                 17266   \n",
      "5282                   2196.0         ...                  2584   \n",
      "5474                   4733.0         ...                  7196   \n",
      "5716                   3557.0         ...                  5449   \n",
      "6038                   2717.0         ...                  3831   \n",
      "6703                   2492.0         ...                  3471   \n",
      "7052                   7424.0         ...                 10551   \n",
      "7327                   2302.0         ...                  3544   \n",
      "7564                   4748.0         ...                  5769   \n",
      "9424                   3405.0         ...                  5359   \n",
      "9490                   7789.0         ...                 12685   \n",
      "9516                   3129.0         ...                  4220   \n",
      "9808                   1727.0         ...                  2396   \n",
      "11096                  2580.0         ...                  3333   \n",
      "12432                  3127.0         ...                  4168   \n",
      "12714                  6159.0         ...                  9516   \n",
      "13095                  5788.0         ...                  9578   \n",
      "\n",
      "                 September 2016  October 2016  November 2016  December 2016  \\\n",
      "Population Rank                                                               \n",
      "13                         4488          4472           4457           4424   \n",
      "43                         2890          2895           2892           2886   \n",
      "103                        3169          3173           3173           3163   \n",
      "150                        2650          2669           2676           2674   \n",
      "241                        2528          2545           2550           2544   \n",
      "258                        3524          3503           3488           3472   \n",
      "333                        3884          3867           3854           3829   \n",
      "335                        3449          3459           3483           3490   \n",
      "338                        2653          2671           2688           2698   \n",
      "365                        2124          2128           2129           2133   \n",
      "399                        3042          3024           3008           2994   \n",
      "441                        2364          2367           2369           2375   \n",
      "462                        4072          4047           4035           4021   \n",
      "491                        3294          3291           3290           3283   \n",
      "529                        2081          2090           2095           2096   \n",
      "554                        3679          3660           3649           3643   \n",
      "576                        3487          3486           3496           3494   \n",
      "619                        3914          3938           3958           3972   \n",
      "625                        3006          2992           2987           2980   \n",
      "643                        3375          3324           3284           3252   \n",
      "733                        3521          3541           3541           3523   \n",
      "750                        2477          2480           2481           2481   \n",
      "769                        3529          3527           3533           3523   \n",
      "892                        2287          2297           2307           2321   \n",
      "969                        4463          4455           4450           4435   \n",
      "996                        3107          3093           3067           3045   \n",
      "1042                       2616          2646           2662           2660   \n",
      "1079                       2935          2930           2928           2923   \n",
      "1166                       5413          5392           5383           5378   \n",
      "1233                       3680          3662           3638           3598   \n",
      "...                         ...           ...            ...            ...   \n",
      "3459                       5422          5417           5410           5379   \n",
      "3728                       4661          4655           4645           4615   \n",
      "3742                       6694          6688           6696           6690   \n",
      "3848                      11405         11340          11429          11566   \n",
      "4160                       7829          7757           7631           7548   \n",
      "4175                       3424          3410           3382           3365   \n",
      "4220                       2614          2616           2629           2641   \n",
      "4288                       4831          4822           4778           4712   \n",
      "4324                       3281          3259           3249           3247   \n",
      "4350                       8388          8425           8547           8645   \n",
      "4560                       4795          4792           4730           4662   \n",
      "4779                       2420          2427           2436           2448   \n",
      "5070                       3579          3588           3612           3644   \n",
      "5152                      17059         16831          16714          16571   \n",
      "5282                       2589          2589           2591           2594   \n",
      "5474                       7182          7121           6969           6850   \n",
      "5716                       5475          5457           5406           5349   \n",
      "6038                       3850          3842           3825           3796   \n",
      "6703                       3487          3502           3511           3509   \n",
      "7052                      10341         10266          10341          10434   \n",
      "7327                       3536          3528           3529           3522   \n",
      "7564                       5714          5644           5584           5558   \n",
      "9424                       5347          5323           5306           5240   \n",
      "9490                      12580         12408          12099          11789   \n",
      "9516                       4241          4240           4215           4141   \n",
      "9808                       2412          2423           2428           2433   \n",
      "11096                      3325          3331           3334           3323   \n",
      "12432                      4176          4164           4142           4085   \n",
      "12714                      9417          9214           8931           8771   \n",
      "13095                      9520          9427           9322           9277   \n",
      "\n",
      "                 January 2017  Total Change  Percent Change  Year Change  \\\n",
      "Population Rank                                                            \n",
      "13                       4382        1194.0        0.374529         -165   \n",
      "43                       2882         988.0        0.521647          164   \n",
      "103                      3150         947.0        0.429868           62   \n",
      "150                      2668         746.0        0.388137          167   \n",
      "241                      2535         705.0        0.385246          105   \n",
      "258                      3483        1299.0        0.594780            2   \n",
      "333                      3811        1429.0        0.599916            8   \n",
      "335                      3490        1260.0        0.565022           36   \n",
      "338                      2710         845.0        0.453083          234   \n",
      "365                      2139         355.0        0.198991          166   \n",
      "399                      2990         937.0        0.456405           95   \n",
      "441                      2380         781.0        0.488430          119   \n",
      "462                      4008        1193.0        0.423801         -117   \n",
      "491                      3272        1207.0        0.584504           14   \n",
      "529                      2098         486.0        0.301489          178   \n",
      "554                      3641        1116.0        0.441980            5   \n",
      "576                      3491        1193.0        0.519147          -12   \n",
      "619                      3985        1505.0        0.606855          178   \n",
      "625                      2981         921.0        0.447087           76   \n",
      "643                      3237        1096.0        0.511910          -85   \n",
      "733                      3488        1138.0        0.484255           68   \n",
      "750                      2479         392.0        0.187829           80   \n",
      "769                      3515        1304.0        0.589778          -14   \n",
      "892                      2325         737.0        0.464106          168   \n",
      "969                      4420        1196.0        0.370968            9   \n",
      "996                      3028         847.0        0.388354          111   \n",
      "1042                     2651         811.0        0.440761          159   \n",
      "1079                     2929         910.0        0.450718          103   \n",
      "1166                     5379        1526.0        0.396055          133   \n",
      "1233                     3573        1362.0        0.616011          -25   \n",
      "...                       ...           ...             ...          ...   \n",
      "3459                     5341        1608.0        0.430753          -54   \n",
      "3728                     4585        1416.0        0.446829           58   \n",
      "3742                     6665        2506.0        0.602549           49   \n",
      "3848                    11796        3336.0        0.394326          331   \n",
      "4160                     7551        -550.0       -0.067893         -286   \n",
      "4175                     3369        1293.0        0.622832           78   \n",
      "4220                     2657        1131.0        0.741153           37   \n",
      "4288                     4634        1665.0        0.560795         -212   \n",
      "4324                     3250         987.0        0.436147           99   \n",
      "4350                     8751        1755.0        0.250858         -128   \n",
      "4560                     4604         670.0        0.170310          -10   \n",
      "4779                     2454         660.0        0.367893          205   \n",
      "5070                     3658        1231.0        0.507211          222   \n",
      "5152                    16575        5422.0        0.486147         -380   \n",
      "5282                     2596         400.0        0.182149          101   \n",
      "5474                     6812        -317.0       -0.044466         -166   \n",
      "5716                     5357         296.0        0.058486          154   \n",
      "6038                     3770        1291.0        0.520775            8   \n",
      "6703                     3505        1285.0        0.578829           13   \n",
      "7052                    10626        2880.0        0.371805         -325   \n",
      "7327                     3516        1303.0        0.588793          111   \n",
      "7564                     5585        1140.0        0.256468          -99   \n",
      "9424                     5181        1357.0        0.354864         -236   \n",
      "9490                    11612        -240.0       -0.020250         -708   \n",
      "9516                     4077        1093.0        0.366287         -115   \n",
      "9808                     2441         651.0        0.363687          222   \n",
      "11096                    3301         953.0        0.405877           75   \n",
      "12432                    4036        1139.0        0.393165         -163   \n",
      "12714                    8760       -1207.0       -0.121100          108   \n",
      "13095                    9343         330.0        0.036614          -62   \n",
      "\n",
      "                 Year Percent Change  \n",
      "Population Rank                       \n",
      "13                         -0.036288  \n",
      "43                          0.060338  \n",
      "103                         0.020078  \n",
      "150                         0.066773  \n",
      "241                         0.043210  \n",
      "258                         0.000575  \n",
      "333                         0.002104  \n",
      "335                         0.010423  \n",
      "338                         0.094507  \n",
      "365                         0.084136  \n",
      "399                         0.032815  \n",
      "441                         0.052632  \n",
      "462                        -0.028364  \n",
      "491                         0.004297  \n",
      "529                         0.092708  \n",
      "554                         0.001375  \n",
      "576                        -0.003426  \n",
      "619                         0.046756  \n",
      "625                         0.026162  \n",
      "643                        -0.025587  \n",
      "733                         0.019883  \n",
      "750                         0.033347  \n",
      "769                        -0.003967  \n",
      "892                         0.077886  \n",
      "969                         0.002040  \n",
      "996                         0.038053  \n",
      "1042                        0.063804  \n",
      "1079                        0.036447  \n",
      "1166                        0.025353  \n",
      "1233                       -0.006948  \n",
      "...                              ...  \n",
      "3459                       -0.010009  \n",
      "3728                        0.012812  \n",
      "3742                        0.007406  \n",
      "3848                        0.028870  \n",
      "4160                       -0.036494  \n",
      "4175                        0.023701  \n",
      "4220                        0.014122  \n",
      "4288                       -0.043747  \n",
      "4324                        0.031419  \n",
      "4350                       -0.014416  \n",
      "4560                       -0.002167  \n",
      "4779                        0.091152  \n",
      "5070                        0.064610  \n",
      "5152                       -0.022412  \n",
      "5282                        0.040481  \n",
      "5474                       -0.023789  \n",
      "5716                        0.029598  \n",
      "6038                        0.002127  \n",
      "6703                        0.003723  \n",
      "7052                       -0.029678  \n",
      "7327                        0.032599  \n",
      "7564                       -0.017417  \n",
      "9424                       -0.043567  \n",
      "9490                       -0.057468  \n",
      "9516                       -0.027433  \n",
      "9808                        0.100045  \n",
      "11096                       0.023249  \n",
      "12432                      -0.038819  \n",
      "12714                       0.012483  \n",
      "13095                      -0.006592  \n",
      "\n",
      "[81 rows x 77 columns]\n"
     ]
    }
   ],
   "source": [
    "y = SF.iloc[:,7:]                 # year values\n",
    "print(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Looking for NA Values and Cleaning Them Up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19c800be9b0>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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b3ugv+to3gTNcK1k2AFZw9z/UcuJezlfdyl4k/ZShbsYtyFdvH2An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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c800d1390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(price.isnull(),yticklabels=False,cbar=False,cmap='hot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19c80518748>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2aj3UiDBgg3SNSajROBuq7BZCFdHc6fcR7r4iMvjrJZt2bzp+Lnc/Bxju7j9J23sim/A1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\nt4AzXCtZ1gOWc/c/NnLibs5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HWjY7G3rT8N20p452zAto4dlolpk+NGFmc6IX9b1T9/2S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\nBEHF/H8vZrfzU0z7MAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c8052ccc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(sqft.isnull(),yticklabels=False,cbar=False,cmap='viridis')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Time for some cleaning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "price = price.set_index('Population Rank')\n",
    "sqft = sqft.set_index('Population Rank')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "price['Total Change'] = price.loc[:,'January 2017'] - price.loc[:,'November 2010']\n",
    "price['Percent Change'] = (price.loc[:,'January 2017'] - price.loc[:,'November 2010']) / price.loc[:,'November 2010']\n",
    "price['Year Change'] = price.loc[:,'January 2017'] - price.loc[:,'January 2016']\n",
    "price['Year Percent Change'] = (price.loc[:,'January 2017'] - price.loc[:,'January 2016']) / price.loc[:,'January 2016']\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Price Change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean rent (Nov, 2010): 1327.1004582305252\n",
      "Mean rent (Jan, 2017): 1467.2965501485035\n",
      "------------------------------------------------------\n",
      "Mean total change: 137.95118082481494\n",
      "Mean percent change: 0.09376333101269745\n",
      "------------------------------------------------------\n",
      "Mean 1 year change: 17.547939989338207\n",
      "Mean 1 year percent change: 0.012141025197546347\n"
     ]
    }
   ],
   "source": [
    "print('Mean rent (Nov, 2010): ' + str(price['November 2010'].mean()))\n",
    "print('Mean rent (Jan, 2017): ' + str(price['January 2017'].mean()))\n",
    "print('------------------------------------------------------')\n",
    "print('Mean total change: ' + str(price['Total Change'].mean()))\n",
    "print('Mean percent change: ' + str(price['Percent Change'].mean()))\n",
    "print('------------------------------------------------------')\n",
    "print('Mean 1 year change: ' + str(price['Year Change'].mean()))\n",
    "print('Mean 1 year percent change: ' + str(price['Year Percent Change'].mean()))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Square Feet Change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "sqft['Total Change'] = sqft.loc[:,'January 2017'] - sqft.loc[:,'November 2010']\n",
    "sqft['Percent Change'] = (sqft.loc[:,'January 2017'] - sqft.loc[:,'November 2010']) / sqft.loc[:,'November 2010']\n",
    "sqft['Year Change'] = sqft.loc[:,'January 2017'] - sqft.loc[:,'January 2016']\n",
    "sqft['Year Percent Change'] = (sqft.loc[:,'January 2017'] - sqft.loc[:,'January 2016']) / sqft.loc[:,'January 2016']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>City Code</th>\n",
       "      <th>City</th>\n",
       "      <th>Metro</th>\n",
       "      <th>County</th>\n",
       "      <th>State</th>\n",
       "      <th>November 2010</th>\n",
       "      <th>December 2010</th>\n",
       "      <th>January 2011</th>\n",
       "      <th>February 2011</th>\n",
       "      <th>March 2011</th>\n",
       "      <th>...</th>\n",
       "      <th>August 2016</th>\n",
       "      <th>September 2016</th>\n",
       "      <th>October 2016</th>\n",
       "      <th>November 2016</th>\n",
       "      <th>December 2016</th>\n",
       "      <th>January 2017</th>\n",
       "      <th>Total Change</th>\n",
       "      <th>Percent Change</th>\n",
       "      <th>Year Change</th>\n",
       "      <th>Year Percent Change</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Population Rank</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6181</td>\n",
       "      <td>New York</td>\n",
       "      <td>New York</td>\n",
       "      <td>Queens</td>\n",
       "      <td>NY</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1.828</td>\n",
       "      <td>1.836</td>\n",
       "      <td>1.844</td>\n",
       "      <td>1.858</td>\n",
       "      <td>1.866</td>\n",
       "      <td>1.872</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.078</td>\n",
       "      <td>0.043478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>12447</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>CA</td>\n",
       "      <td>1.578</td>\n",
       "      <td>1.578</td>\n",
       "      <td>1.580</td>\n",
       "      <td>1.582</td>\n",
       "      <td>1.586</td>\n",
       "      <td>...</td>\n",
       "      <td>2.032</td>\n",
       "      <td>2.038</td>\n",
       "      <td>2.042</td>\n",
       "      <td>2.048</td>\n",
       "      <td>2.056</td>\n",
       "      <td>2.064</td>\n",
       "      <td>0.486</td>\n",
       "      <td>0.307985</td>\n",
       "      <td>0.116</td>\n",
       "      <td>0.059548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>17426</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Cook</td>\n",
       "      <td>IL</td>\n",
       "      <td>1.244</td>\n",
       "      <td>1.248</td>\n",
       "      <td>1.254</td>\n",
       "      <td>1.254</td>\n",
       "      <td>1.248</td>\n",
       "      <td>...</td>\n",
       "      <td>1.378</td>\n",
       "      <td>1.380</td>\n",
       "      <td>1.380</td>\n",
       "      <td>1.380</td>\n",
       "      <td>1.376</td>\n",
       "      <td>1.374</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.104502</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.026906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>39051</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Houston</td>\n",
       "      <td>Harris</td>\n",
       "      <td>TX</td>\n",
       "      <td>0.788</td>\n",
       "      <td>0.784</td>\n",
       "      <td>0.784</td>\n",
       "      <td>0.786</td>\n",
       "      <td>0.792</td>\n",
       "      <td>...</td>\n",
       "      <td>0.976</td>\n",
       "      <td>0.974</td>\n",
       "      <td>0.974</td>\n",
       "      <td>0.976</td>\n",
       "      <td>0.976</td>\n",
       "      <td>0.974</td>\n",
       "      <td>0.186</td>\n",
       "      <td>0.236041</td>\n",
       "      <td>-0.002</td>\n",
       "      <td>-0.002049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13271</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>PA</td>\n",
       "      <td>0.854</td>\n",
       "      <td>0.858</td>\n",
       "      <td>0.858</td>\n",
       "      <td>0.858</td>\n",
       "      <td>0.856</td>\n",
       "      <td>...</td>\n",
       "      <td>0.964</td>\n",
       "      <td>0.966</td>\n",
       "      <td>0.968</td>\n",
       "      <td>0.972</td>\n",
       "      <td>0.974</td>\n",
       "      <td>0.974</td>\n",
       "      <td>0.120</td>\n",
       "      <td>0.140515</td>\n",
       "      <td>0.040</td>\n",
       "      <td>0.042827</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 84 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 City Code          City         Metro        County State  \\\n",
       "Population Rank                                                              \n",
       "1                     6181      New York      New York        Queens    NY   \n",
       "2                    12447   Los Angeles   Los Angeles   Los Angeles    CA   \n",
       "3                    17426       Chicago       Chicago          Cook    IL   \n",
       "4                    39051       Houston       Houston        Harris    TX   \n",
       "5                    13271  Philadelphia  Philadelphia  Philadelphia    PA   \n",
       "\n",
       "                 November 2010  December 2010  January 2011  February 2011  \\\n",
       "Population Rank                                                              \n",
       "1                          NaN            NaN           NaN            NaN   \n",
       "2                        1.578          1.578         1.580          1.582   \n",
       "3                        1.244          1.248         1.254          1.254   \n",
       "4                        0.788          0.784         0.784          0.786   \n",
       "5                        0.854          0.858         0.858          0.858   \n",
       "\n",
       "                 March 2011         ...           August 2016  September 2016  \\\n",
       "Population Rank                     ...                                         \n",
       "1                       NaN         ...                 1.828           1.836   \n",
       "2                     1.586         ...                 2.032           2.038   \n",
       "3                     1.248         ...                 1.378           1.380   \n",
       "4                     0.792         ...                 0.976           0.974   \n",
       "5                     0.856         ...                 0.964           0.966   \n",
       "\n",
       "                 October 2016  November 2016  December 2016  January 2017  \\\n",
       "Population Rank                                                             \n",
       "1                       1.844          1.858          1.866         1.872   \n",
       "2                       2.042          2.048          2.056         2.064   \n",
       "3                       1.380          1.380          1.376         1.374   \n",
       "4                       0.974          0.976          0.976         0.974   \n",
       "5                       0.968          0.972          0.974         0.974   \n",
       "\n",
       "                 Total Change  Percent Change  Year Change  \\\n",
       "Population Rank                                              \n",
       "1                         NaN             NaN        0.078   \n",
       "2                       0.486        0.307985        0.116   \n",
       "3                       0.130        0.104502        0.036   \n",
       "4                       0.186        0.236041       -0.002   \n",
       "5                       0.120        0.140515        0.040   \n",
       "\n",
       "                 Year Percent Change  \n",
       "Population Rank                       \n",
       "1                           0.043478  \n",
       "2                           0.059548  \n",
       "3                           0.026906  \n",
       "4                          -0.002049  \n",
       "5                           0.042827  \n",
       "\n",
       "[5 rows x 84 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sqft.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### By Price"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plotr(data, group, column, bins=100):\n",
    "    plot = price.groupby(group)[column].mean().plot(kind='hist', bins=bins)\n",
    "    (mu, sigma) = norm.fit(price[column])\n",
    "    y = mlab.normpdf(bins, mu, sigma)\n",
    "    l = plt.plot(bins, y, 'r--', linewidth=2)\n",
    "    \n",
    "    plt.title('Mean {} Grouped by {}'.format(column, group))\n",
    "    plt.xlabel(column)\n",
    "    plt.ylabel('Numer of Occurrences')\n",
    "    \n",
    "    mn = price[column].mean()\n",
    "    plt.axvline(mn, color='r', linestyle='dashed', linewidth=1, label='mean')\n",
    "    plt.legend()\n",
    "    return plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19cf2271438>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Fha0bGG39lZQUxbbtxjT5zlMyjseUlM+XlBz1ocz50dQyJz1vbQXiKuBRM7uK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\niGSkAiEiIhmpQIiISEb/H2Ejnhnatw6WAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19cf2b0ea20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotr(price, 'City', 'Total Change', bins=100) # City Level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19c801ba5f8>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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sHSMMpdwmYxru3ifOYCIi0viyuTjrEeA+oF7j74isrMsPvDDpCCKpk03Rn+3u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\n6IuIFBEVfRGRIvL/vSJLjAqFb8EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c8054fe80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotr(price, 'Metro', 'Total Change') # Metro Level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19c801e93c8>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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qYnCvQUmHIJJquST3Be4+OPZIRDJMb98p6RBEUi2X5D7GzK4Fnidjjpga5pYR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\nSAH6f+D5gszpMIpAAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c8057c6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotr(price, 'State', 'Total Change', bins=25) # State Level"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x19cf3a7dac8>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Mq6/+I2vXVufVtk71JSBbLYP+QLWZHQbsBjwEtEl6vRxYBCyJHtecLiKS0vLlyyktLaVJ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\nwKnunhipYNtYUq5X37a9GTg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      "text/plain": [
       "<matplotlib.figure.Figure at 0x19cf4ddd6a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotr(price, 'City', 'Percent Change') # Correlation between City and Percentage Change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\atse\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kde.py:454: RuntimeWarning: invalid value encountered in greater\n",
      "  X = X[np.logical_and(X>clip[0], X<clip[1])] # won't work for two columns.\n",
      "C:\\Users\\atse\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kde.py:454: RuntimeWarning: invalid value encountered in less\n",
      "  X = X[np.logical_and(X>clip[0], X<clip[1])] # won't work for two columns.\n"
     ]
    },
    {
     "data": {
      "image/png": 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wjwbgc8DZwCXAt0VkdvRJzHAzcZnLdJy8qg6AvzZ15zkSpQrHpC0DYB3wCIAx\nZruInJJQdhzQZIzxAYjIZuBc4MwkdcqAm4FLE/ZxGrDFGBMAAiLSBJwE/DlZQNXVJTidjjRCzx6v\nt3A/IDMVW1vvCABrj2+kpsKTkX0WwnmrqytjXk0Jr+3rpaq6FJfTuiYqhNhSKeT4NLapK5T40kkG\nFUB/wvdhEXEaY0ITlPmByhR19gH7RCQxGSTbR1I+33AaYWeP11tOV1dhTk3MZGxvHPBRVeYmHBij\nq2v6/euFdN5OXFbDn15sYetfDrJ6aU1BxTaRQo5PY5u6XMeXKvGk0000ACTuwR5LBBOVlQN9k9SZ\nbP/xfag86h8MWIPHs+T+gvFOXml1Fb2sXUVKAeklgy3AZQAicgbwakLZTmCViNSIiBuri2jbJHXG\nex44R0Q8IlKJ1fX02tEeiMqs2XTn8URkcRUet4OXd3cTjUbzHY5SeZdOMrgfGBWRrViDxV8QkatE\n5BpjzBhwA/AoVhLYZIxpnahOsp0bY9qBO4BngSeAG40xo9M5KDV9s+1ms/GcDjsnr6yju3+UPa26\nNrJSk44ZGGMiwLXjNu9KKH8QeDCNOonlN4/7fiOwcfJwVa7M9pYBwNknNrL99Q42v3qIM9+2MN/h\nKJVXetOZmtD+9gGqy4uoLJu9s3yPW1JNTUURz+/sZDSQbEhLqblBk4E6Qt9ggL7BIEtm0Z3HE7Hb\nbZx1QiOjwTDbXmvLdzhK5ZUmA3WE/W2zv4so7uwTrTuQH3/+QJ4jUSq/NBmoI+w5ZN32sXzB7JxW\nmqi+uoRjFlbySlM33X0j+Q5HqbzRZKCOsKe1HxuwvDHlvX+zxjlr5gPwp5da8hyJUvmjyUC9RSQS\nZV+bn8a6Uko86dygPvOddlw9tZUenvxLK/7hYL7DUSovNBmot2jpGiQwFmbF/NnfRRTnctp57/kr\nCY5F+OMLB/MdjlJ5oclAvcWeQ9YNWCsWzI0uoriLT19CRYmLP73YwvCornOg5h5NBuot9rZag8dz\nqWUA4HE7ueS0xYwEwjz+oo4dqLlHk4F6i6ZDAxQXOWisK813KDm3/m0LKCt28ejzBxgY0rEDNbdo\nMlCHDY6M0dE7zPLGCuw2W77DybniIifvPnspI4Ewv312b77DUSqnNBmow/bG7i+Ya+MFida/bQGN\ntSU8/ddDtHQO5jscpXJGk4E6rKl1bg4eJ3I67HzogpVEo/A/T+zWx1urOUOTgTqsqaXPutlsjg0e\nj3fi8lrC/m50AAAVOUlEQVSOX1bD6/t9/HVPT77DUSonNBkoAALBMLtb+lncUE6px5XvcPLKZrPx\n4QtWYrPBL59oIhSO5DskpbJOk4ECwBzsIxyJsnppdb5DKQgLvGWsP3kBHb3DPPlSa77DUSrrNBko\nAF7f3wvA8Utr8hxJ4bjinGUUFzl5YMs+Bkf0RjQ1u2kyUICVDFxOO6sWzt3B4/EqStxcftZShkZD\nPLR1f77DUSqrNBko+gcDtHQNcczCSlxOR77DKSjvWLuQ6vIinvpLq96IpmY1TQaK15t9AKxepl1E\n47mcdi47YwnBUITH/qwPsVOz16TPKBYRO3AXsAYIAFcbY5oSyi8HvgaEgE3GmI3J6ojISuAeIAq8\nBlxvjImIyAZgHeCP7fYKY0x/ho5RTeL1fTpekMo5JzXy0Nb9/OmlFt55+mLKiuf2bCs1O6XTMrgS\n8BhjzgS+DNwaLxARF3A7cDFwHnCNiNSnqHMb8FVjzDmADbgitn0tcIkxZn3snyaCHIlGo7ze7KO8\nxMXCeWX5DqcguV0O3nn6YgLBMI/rI67VLJVOMlgHPAJgjNkOnJJQdhzQZIzxGWOCwGbg3BR11gJP\nx75+GLgw1opYBdwtIltE5BPTOyR1NJo7/Pj8AVYvrZmTzyNK1/qTrYfYPf5CCyOBUL7DUSrj0lnK\nqgJIvFIPi4jTGBOaoMwPVCarA9iMMdFxry0F7sRqNTiAJ0XkBWPMK8kCqq4uwZnngU6vt3AXiz+a\n2H63tRmAC09fkpNjmsnn7crzVvDTR3bxl729XHHuihxF9aaZfO7yqZBjg8KJL51kMAAkRmuPJYKJ\nysqBvmR1RCQywWuHgQ3GmGEAEXkCa6whaTLw+YbTCDt7vN5yurr8k78wD44mtkgkylMvHaTU42RJ\nXUnWj2mmn7fTxMv/Pv4G9z+5m9OlDoc9d/MvZvq5y5dCjg1yH1+qxJPOb/MW4DIAETkDeDWhbCew\nSkRqRMSN1UW0LUWdv4jI+tjXlwLPAscAW0TEERuDWAe8lNaRqWnZdcBH/2CQU46dh9OhE8smU1bs\nYt1JjfQMBHhhV1e+w1Eqo9L5BLgfGBWRrViDxV8QkatE5BpjzBhwA/AoVhLYZIxpnahObF//DHxd\nRLYBbuBXxpidwE+A7VjjCfcZY3Zk7hBVMtt3dABwxur6PEcyc1x86iJswCPPHdAnmqpZZdJuImNM\nBLh23OZdCeUPAg+mUQdjzBtYs47Gb/8e8L30QlaZMBYK8+IbndRUFLFqUVW+w5kx5lWX8Hbx8qLp\nYmezj9U6HVfNEto3MEe93NTDSCDM6cfV6yyio3TZGUsAeGDzPm0dqFlDk8EcFI1G+cN2axbRWSc2\n5jmamWdZYwVrVtTyRks/r+/35TscpTJCk8Ec9HJTN83tfk49dh4L5uDC95lw5TnLAfjts3u1daBm\nBU0Gc0wkGuW3z+7DBrx73bJ8hzNjLWkoZ+0xXvYcGuDVvboampr5NBnMMX95o4uDnYOcvrpeWwXT\ndMW6ZdiwVkMbDepdyWpm02Qwh4wGQ/zq6b3YbHD52UvzHc6Mt3BeGReduoi2nmF+8ugb2l2kZjRN\nBnNENBrlnod30dE7zIVrF9FYq62CTHj/+hUsa6xg2452nn2lLd/hKDVlmgzmiMdfbOH5nZ2sWFDB\nB87P/XN1Ziunw851VxxPSZGTnz72Bg9s3kdwLJzvsJQ6auk8m0jNcM/v7OB/n2iivMTFZ648UR89\nkWF1VcV85j0nsPHB1/nt5n08+8ohVi6swuW0MxoM09k7TK8/gMNuw+W0s7ShnHPWzOf4pTXY7XqP\nhyoMmgxmsWg0yu827+OBLfspcjv4zJUnUF1elO+wZqXVS2v41jVn8NDW/fzxhYM893rH4TK3y05t\nhYdIJMpoMMwLposXTBfeKg+fuOw4ZHF1HiNXyqLJYJZq6xni54/vZse+XuoqPXzu/Sex0KuL12RT\ncZGTD5y/knefvYzhQIixUBiX00FVmRtb7C7vaDTK/nY/T7/cyuZX2vnuz//CO89YzHvOWa4tNpVX\nmgxmmcGRMX7x+G6eeKmFcCTK8ctq+NTlq6kocec7tDmjyO2gyD3xehs2m41ljRUsa6zgnJPmc/eD\nO3h4+wF2t/Rz/XtOpLJUf04qPzQZzBKRSJRnXjnEb5/dx8BQEG+Vhw9fsIqTV9UdvipVhWXFgkpu\n/vhp3PvILp7f2cm/3/tnPvvek1jSUBiLnai5RZPBLNDeO8ym3++kqbUfj9vB+85bzsWnLsbl1G6H\nQldc5OTT7z6ehd4yfvPMXr710xe56sJVnLtmviZxlVOaDGawaDTK4y+28Kun9jAWinDqsfO4/oMn\nE9G7YWcUm83G35y1lIXzyvjxQ69z7yOGnc0+/vaiYyjX7j2VI5oMZqjAWJh7Ht7Fc693UFbs4uq/\nWc2px86jtrK4oJf5U8mdvLKOmz9+Gj96YAfP7+zk1b29vPvspbxj7cJ8h6bmAE0GM1BX3wj/9ZtX\nOdg5yIoFFXzmyhN1yugsUVvp4YtXvY0nXmrlgc37+OUTTTz83AEuOm0xb19ZS0NNiXYfqazQZDDD\nvLavhx/9bgdDoyHWnzyfj1x4jI4NzDJOh52LT13EWSc08Ptt+9n8Shu/frKJXz/ZRHV5EasWVjKv\nuoSqMjdFLgfhSNT6F4685Wu73UZFqZvqsiK81cXUVXpw2PV3RU1Mk8EMEQpH+MO2Zn63ZR8Ou41/\nuPRYzl0zP99hqSwqK3bxoQtW8d5zl/PGIT9PvXiQ3Qf7eH5n55T253TY8FYV01hbSkNNifWv1vq/\nrNiV4egtkUgU/8gY/uEgwbEIbqcdt9tBTXmR3ldRYDQZzACtXYP89+930tzup7q8iM+85wRWzK/M\nd1gqR1xOB+vXLuL4xVVEo1G6+kboHQjQNxQgOBbBYbfhcNhw2u2Hv3bY7YTCEfqHgvT5A3T4hmnv\ntf619Qwf8R5lxa7DiaExIUl4q4rT+tCORqP0DgRo6RqkpWuQ1q4hWroGaesZJhw58mmuToeNhppS\nljaWs3ppNauX1ui9MHk2aTIQETtwF7AGCABXG2OaEsovB74GhIBNxpiNyeqIyErgHiAKvAZcb4yJ\niMingE/H9vENY8xDGTzGjAhHIoyFIoTCUUpGxohEo1lfO/hAh5+HnzvA8zs7iEbh7BMa+MiFqyjx\nZOcqThU+m83GvOoS5lWXTKl+NBplYChoJYXeYdp73kwSe1r7aWrpf8vrHXYbdVXF1FcXU1VWREWp\nG6fDRjQKgWCYXv8o/pEQ+9sGGAm8dRab22VncX0ZtRUeykusLq1gKMxIIER77zCt3VbC2Bx72uvi\neWWsXlbD8UtrWLWwErdr4hv3si0SjRIIholGwWazbiKc7t96NGo9iiQcieJ0WM+oKrQuu3RaBlcC\nHmPMmSJyBnArcAWAiLiA24FTgSFgi4g8AJydpM5twFeNMU+JyA+BK0RkG/A54BTAA2wWkT8aYwIZ\nPdIE0ajVrxqK9bGOBEL4h8foHwriHwoyMBykzx+k1z+Kzx/A5w8wMBQk8frGBpR4nFSVFVFd/ua/\nmgrP4W3FbgculwO3047LaT/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      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c80bc5048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c81c5e358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "kb = price.groupby('Metro')['Total Change'].mean()\n",
    "plot = sns.kdeplot(kb)\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\atse\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kde.py:454: RuntimeWarning: invalid value encountered in greater\n",
      "  X = X[np.logical_and(X>clip[0], X<clip[1])] # won't work for two columns.\n",
      "C:\\Users\\atse\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kde.py:454: RuntimeWarning: invalid value encountered in less\n",
      "  X = X[np.logical_and(X>clip[0], X<clip[1])] # won't work for two columns.\n"
     ]
    },
    {
     "data": {
      "image/png": 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CfKQYDHBtXUTTpIuoz0VG2Bg7PIky51lZ40CYjhSDAW6r9s9FJFcR9YuP5yqS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\nIYQQwP8H1xP6zBfW9esAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c81cec7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x19c81d37b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "jan = price.groupby('State', as_index=True)['Total Change'].mean()\n",
    "plot = sns.kdeplot(jan)\n",
    "plt.show()\n",
    "plt.clf()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Locate the Highest Total Change Value (Investigate Skew)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum total change: -1367.0\n",
      "City Code              398547\n",
      "City         Town of Westerly\n",
      "Metro              Providence\n",
      "County             Washington\n",
      "State                      RI\n",
      "Name: 2285, dtype: object\n",
      "-------------------------------\n",
      "Maximum total change: 5422.0\n",
      "City Code            30280\n",
      "City              Atherton\n",
      "Metro        San Francisco\n",
      "County           San Mateo\n",
      "State                   CA\n",
      "Name: 5152, dtype: object\n"
     ]
    }
   ],
   "source": [
    "print('Minimum total change: ' + str(price['Total Change'].min()))\n",
    "print(price.loc[price['Total Change'].idxmin(),:].head(5))\n",
    "print('-------------------------------')\n",
    "print('Maximum total change: ' + str(price['Total Change'].max()))\n",
    "print(price.loc[price['Total Change'].idxmax(),:].head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "City Code                124901\n",
      "City             Jupiter Island\n",
      "Metro            Port St. Lucie\n",
      "County                   Martin\n",
      "State                        FL\n",
      "November 2010             18787\n",
      "December 2010             18848\n",
      "January 2011              19054\n",
      "February 2011             19019\n",
      "March 2011                18997\n",
      "Name: 12235, dtype: object\n",
      "17985\n"
     ]
    }
   ],
   "source": [
    "print(price.loc[price['January 2017'].idxmax(),:].head(10))\n",
    "print(price['January 2017'].max())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "State\n",
      "OR    408.746988\n",
      "DC    395.000000\n",
      "CO    390.910828\n",
      "CA    388.886179\n",
      "MA    358.000000\n",
      "HI    339.296296\n",
      "WA    292.334483\n",
      "WI    266.137681\n",
      "FL    257.677903\n",
      "NH    181.415094\n",
      "Name: Total Change, dtype: float64\n",
      "---------------------------------\n",
      "State\n",
      "MI   -32.180693\n",
      "WV   -21.578313\n",
      "LA    -7.397590\n",
      "IL    -6.361111\n",
      "NM    -1.206897\n",
      "DE     5.368421\n",
      "NY    24.535238\n",
      "IA    31.274194\n",
      "IN    32.467290\n",
      "PA    51.103659\n",
      "Name: Total Change, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(price.groupby('State')['Total Change'].mean().sort_values(ascending=False).head(10))\n",
    "print('---------------------------------')\n",
    "print(price.groupby('State')['Total Change'].mean().sort_values(ascending=True).head(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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