Hypothesis_Testing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's say we have an hypothesis: \"In the United States, university towns have their mean housing prices less effected by recessions, compared to regular towns\".\n",
    "\n",
    "First, we need to get the data:\n",
    "\n",
    "From the [Zillow research data site](http://www.zillow.com/research/data/) we take housing data for the United States, [all homes at a city level](http://files.zillowstatic.com/research/public/City/City_Zhvi_AllHomes.csv).\n",
    "\n",
    "Then, we take the list of university towns from [university towns in the United States](https://en.wikipedia.org/wiki/List_of_college_towns#College_towns_in_the_United_States).\n",
    "\n",
    "Then, we take the [GDP over time](http://www.bea.gov/national/index.htm#gdp) (we use the data from 2000 onward).\n",
    "\n",
    "Now, we import pandas, numpy and ttest_ind (from scipy.stats):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy.stats import ttest_ind"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we get the list of the university towns:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>State</th>\n",
       "      <th>RegionName</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Auburn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Florence</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Jacksonville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Livingston</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Montevallo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Troy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Tuscaloosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Tuskegee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>Fairbanks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Flagstaff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Tempe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Tucson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Arkadelphia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Conway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Fayetteville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Jonesboro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Magnolia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Monticello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Russellville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Searcy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>California</td>\n",
       "      <td>Angwin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>California</td>\n",
       "      <td>Arcata</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>California</td>\n",
       "      <td>Berkeley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>California</td>\n",
       "      <td>Chico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>California</td>\n",
       "      <td>Claremont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>California</td>\n",
       "      <td>Cotati</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>California</td>\n",
       "      <td>Davis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>California</td>\n",
       "      <td>Irvine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>California</td>\n",
       "      <td>Isla Vista</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>California</td>\n",
       "      <td>University Park, Los Angeles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>Wise</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>Chesapeake</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Bellingham</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Cheney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Ellensburg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Pullman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Washington</td>\n",
       "      <td>University District, Seattle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Athens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Buckhannon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Fairmont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Glenville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Huntington</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Montgomery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Morgantown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Shepherdstown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>West Liberty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Appleton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Eau Claire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Green Bay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>La Crosse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Madison</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Menomonie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Milwaukee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Oshkosh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Platteville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>River Falls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Stevens Point</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Waukesha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Whitewater</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Laramie</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>517 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             State                    RegionName\n",
       "0          Alabama                        Auburn\n",
       "1          Alabama                      Florence\n",
       "2          Alabama                  Jacksonville\n",
       "3          Alabama                    Livingston\n",
       "4          Alabama                    Montevallo\n",
       "5          Alabama                          Troy\n",
       "6          Alabama                    Tuscaloosa\n",
       "7          Alabama                      Tuskegee\n",
       "8           Alaska                     Fairbanks\n",
       "9          Arizona                     Flagstaff\n",
       "10         Arizona                         Tempe\n",
       "11         Arizona                        Tucson\n",
       "12        Arkansas                   Arkadelphia\n",
       "13        Arkansas                        Conway\n",
       "14        Arkansas                  Fayetteville\n",
       "15        Arkansas                     Jonesboro\n",
       "16        Arkansas                      Magnolia\n",
       "17        Arkansas                    Monticello\n",
       "18        Arkansas                  Russellville\n",
       "19        Arkansas                        Searcy\n",
       "20      California                        Angwin\n",
       "21      California                        Arcata\n",
       "22      California                      Berkeley\n",
       "23      California                         Chico\n",
       "24      California                     Claremont\n",
       "25      California                        Cotati\n",
       "26      California                         Davis\n",
       "27      California                        Irvine\n",
       "28      California                    Isla Vista\n",
       "29      California  University Park, Los Angeles\n",
       "..             ...                           ...\n",
       "487       Virginia                          Wise\n",
       "488       Virginia                    Chesapeake\n",
       "489     Washington                    Bellingham\n",
       "490     Washington                        Cheney\n",
       "491     Washington                    Ellensburg\n",
       "492     Washington                       Pullman\n",
       "493     Washington  University District, Seattle\n",
       "494  West Virginia                        Athens\n",
       "495  West Virginia                    Buckhannon\n",
       "496  West Virginia                      Fairmont\n",
       "497  West Virginia                     Glenville\n",
       "498  West Virginia                    Huntington\n",
       "499  West Virginia                    Montgomery\n",
       "500  West Virginia                    Morgantown\n",
       "501  West Virginia                 Shepherdstown\n",
       "502  West Virginia                  West Liberty\n",
       "503      Wisconsin                      Appleton\n",
       "504      Wisconsin                    Eau Claire\n",
       "505      Wisconsin                     Green Bay\n",
       "506      Wisconsin                     La Crosse\n",
       "507      Wisconsin                       Madison\n",
       "508      Wisconsin                     Menomonie\n",
       "509      Wisconsin                     Milwaukee\n",
       "510      Wisconsin                       Oshkosh\n",
       "511      Wisconsin                   Platteville\n",
       "512      Wisconsin                   River Falls\n",
       "513      Wisconsin                 Stevens Point\n",
       "514      Wisconsin                      Waukesha\n",
       "515      Wisconsin                    Whitewater\n",
       "516        Wyoming                       Laramie\n",
       "\n",
       "[517 rows x 2 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_list_of_university_towns():\n",
    "    \n",
    "    # read the data to a table\n",
    "    university_towns = pd.read_table('university_towns.txt', header=None, sep='\\ \\(.*', names=[\"State\", \"RegionName\"], engine='python').\\\n",
    "    fillna(method='ffill', axis=1)\n",
    "    \n",
    "    # clean the 'State' column\n",
    "    university_towns.State = university_towns.State.replace(to_replace=r'^[^[]*$', value=np.NaN, regex=True)\\\n",
    "    .replace(to_replace=r'\\[.*', value='', regex=True).fillna(method='ffill')\n",
    "    \n",
    "    # clean the 'RegionName' column\n",
    "    university_towns.RegionName = university_towns.RegionName.replace(to_replace=r'^.*\\[.*$', value='Delete', regex=True)\n",
    "    \n",
    "    # make final corrections\n",
    "    university_towns = university_towns.drop(university_towns[university_towns['RegionName']=='Delete'].index)\\\n",
    "    .replace(to_replace=r'\\n', value='', regex=True).reset_index().drop('index', axis=1)\n",
    "    \n",
    "    return university_towns\n",
    "get_list_of_university_towns()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I chose to use a multi-line approace to 'get_list_of_university_towns()' function.\n",
    "As I wrote in the _README.md_ file, one can write almost everything in one line (in pandas).\n",
    "I have another implementation to this function, a one-line implementation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>RegionName</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Auburn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Florence</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Jacksonville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Livingston</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Montevallo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Troy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Tuscaloosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Tuskegee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>Fairbanks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Flagstaff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Tempe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Tucson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Arkadelphia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Conway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Fayetteville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Jonesboro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Magnolia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Monticello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Russellville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Searcy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>California</td>\n",
       "      <td>Angwin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>California</td>\n",
       "      <td>Arcata</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>California</td>\n",
       "      <td>Berkeley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>California</td>\n",
       "      <td>Chico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>California</td>\n",
       "      <td>Claremont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>California</td>\n",
       "      <td>Cotati</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>California</td>\n",
       "      <td>Davis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>California</td>\n",
       "      <td>Irvine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>California</td>\n",
       "      <td>Isla Vista</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>California</td>\n",
       "      <td>University Park, Los Angeles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>Wise</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>Chesapeake</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Bellingham</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Cheney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Ellensburg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Pullman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Washington</td>\n",
       "      <td>University District, Seattle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Athens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Buckhannon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Fairmont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Glenville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Huntington</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Montgomery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Morgantown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Shepherdstown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>West Liberty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Appleton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Eau Claire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Green Bay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>La Crosse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Madison</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Menomonie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Milwaukee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Oshkosh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Platteville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>River Falls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Stevens Point</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Waukesha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Whitewater</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Laramie</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>517 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             State                    RegionName\n",
       "0          Alabama                        Auburn\n",
       "1          Alabama                      Florence\n",
       "2          Alabama                  Jacksonville\n",
       "3          Alabama                    Livingston\n",
       "4          Alabama                    Montevallo\n",
       "5          Alabama                          Troy\n",
       "6          Alabama                    Tuscaloosa\n",
       "7          Alabama                      Tuskegee\n",
       "8           Alaska                     Fairbanks\n",
       "9          Arizona                     Flagstaff\n",
       "10         Arizona                         Tempe\n",
       "11         Arizona                        Tucson\n",
       "12        Arkansas                   Arkadelphia\n",
       "13        Arkansas                        Conway\n",
       "14        Arkansas                  Fayetteville\n",
       "15        Arkansas                     Jonesboro\n",
       "16        Arkansas                      Magnolia\n",
       "17        Arkansas                    Monticello\n",
       "18        Arkansas                  Russellville\n",
       "19        Arkansas                        Searcy\n",
       "20      California                        Angwin\n",
       "21      California                        Arcata\n",
       "22      California                      Berkeley\n",
       "23      California                         Chico\n",
       "24      California                     Claremont\n",
       "25      California                        Cotati\n",
       "26      California                         Davis\n",
       "27      California                        Irvine\n",
       "28      California                    Isla Vista\n",
       "29      California  University Park, Los Angeles\n",
       "..             ...                           ...\n",
       "487       Virginia                          Wise\n",
       "488       Virginia                    Chesapeake\n",
       "489     Washington                    Bellingham\n",
       "490     Washington                        Cheney\n",
       "491     Washington                    Ellensburg\n",
       "492     Washington                       Pullman\n",
       "493     Washington  University District, Seattle\n",
       "494  West Virginia                        Athens\n",
       "495  West Virginia                    Buckhannon\n",
       "496  West Virginia                      Fairmont\n",
       "497  West Virginia                     Glenville\n",
       "498  West Virginia                    Huntington\n",
       "499  West Virginia                    Montgomery\n",
       "500  West Virginia                    Morgantown\n",
       "501  West Virginia                 Shepherdstown\n",
       "502  West Virginia                  West Liberty\n",
       "503      Wisconsin                      Appleton\n",
       "504      Wisconsin                    Eau Claire\n",
       "505      Wisconsin                     Green Bay\n",
       "506      Wisconsin                     La Crosse\n",
       "507      Wisconsin                       Madison\n",
       "508      Wisconsin                     Menomonie\n",
       "509      Wisconsin                     Milwaukee\n",
       "510      Wisconsin                       Oshkosh\n",
       "511      Wisconsin                   Platteville\n",
       "512      Wisconsin                   River Falls\n",
       "513      Wisconsin                 Stevens Point\n",
       "514      Wisconsin                      Waukesha\n",
       "515      Wisconsin                    Whitewater\n",
       "516        Wyoming                       Laramie\n",
       "\n",
       "[517 rows x 2 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "def get_list_of_university_towns_2():\n",
    "    \n",
    "    university_towns = pd.read_table('university_towns.txt', header=None, sep='\\ \\(.*', names=[\"State\", \"RegionName\"], engine='python')\\\n",
    "    .fillna(method='ffill', axis=1).apply(lambda x: [re.sub(r'^[^[]*$','NaN', x[0]), x[1]], axis=1, result_type='broadcast')\\\n",
    "    .apply(lambda x: [re.sub(r'\\[.*','', x[0]), x[1]], axis=1, result_type='broadcast')\\\n",
    "    .replace(to_replace='NaN', value=np.NaN, regex=True).fillna(method='ffill')\\\n",
    "    .replace(to_replace=r'^.*\\[.*$', value='Delete', regex=True)\\\n",
    "    .query('RegionName != \"Delete\"').replace(to_replace=r'\\n', value='', regex=True)\\\n",
    "    .reset_index().drop('index', axis=1)\n",
    "    \n",
    "    return university_towns\n",
    "get_list_of_university_towns_2()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's check which approach is the fastest:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "66.9 ms ± 1.38 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 10\n",
    "get_list_of_university_towns() # multi-line solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "173 ms ± 1.73 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 10\n",
    "get_list_of_university_towns_2() # one-line solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that for this particular problem, the one-line solution is very slow compared to the multi-line solution.\n",
    "\n",
    "I also made a third solution, a two-line solution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State</th>\n",
       "      <th>RegionName</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Auburn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Florence</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Jacksonville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Livingston</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Montevallo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Troy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Tuscaloosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>Tuskegee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Alaska</td>\n",
       "      <td>Fairbanks</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Flagstaff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Tempe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Arizona</td>\n",
       "      <td>Tucson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Arkadelphia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Conway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Fayetteville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Jonesboro</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Magnolia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Monticello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Russellville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Searcy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>California</td>\n",
       "      <td>Angwin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>California</td>\n",
       "      <td>Arcata</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>California</td>\n",
       "      <td>Berkeley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>California</td>\n",
       "      <td>Chico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>California</td>\n",
       "      <td>Claremont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>California</td>\n",
       "      <td>Cotati</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>California</td>\n",
       "      <td>Davis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>California</td>\n",
       "      <td>Irvine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>California</td>\n",
       "      <td>Isla Vista</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>California</td>\n",
       "      <td>University Park, Los Angeles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>487</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>Wise</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>Chesapeake</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Bellingham</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Cheney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Ellensburg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>Washington</td>\n",
       "      <td>Pullman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>Washington</td>\n",
       "      <td>University District, Seattle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Athens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Buckhannon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Fairmont</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Glenville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Huntington</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Montgomery</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Morgantown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>Shepherdstown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>West Virginia</td>\n",
       "      <td>West Liberty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Appleton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Eau Claire</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Green Bay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>La Crosse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Madison</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Menomonie</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Milwaukee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Oshkosh</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Platteville</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>River Falls</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Stevens Point</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Waukesha</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>Whitewater</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>Wyoming</td>\n",
       "      <td>Laramie</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>517 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             State                    RegionName\n",
       "0          Alabama                        Auburn\n",
       "1          Alabama                      Florence\n",
       "2          Alabama                  Jacksonville\n",
       "3          Alabama                    Livingston\n",
       "4          Alabama                    Montevallo\n",
       "5          Alabama                          Troy\n",
       "6          Alabama                    Tuscaloosa\n",
       "7          Alabama                      Tuskegee\n",
       "8           Alaska                     Fairbanks\n",
       "9          Arizona                     Flagstaff\n",
       "10         Arizona                         Tempe\n",
       "11         Arizona                        Tucson\n",
       "12        Arkansas                   Arkadelphia\n",
       "13        Arkansas                        Conway\n",
       "14        Arkansas                  Fayetteville\n",
       "15        Arkansas                     Jonesboro\n",
       "16        Arkansas                      Magnolia\n",
       "17        Arkansas                    Monticello\n",
       "18        Arkansas                  Russellville\n",
       "19        Arkansas                        Searcy\n",
       "20      California                        Angwin\n",
       "21      California                        Arcata\n",
       "22      California                      Berkeley\n",
       "23      California                         Chico\n",
       "24      California                     Claremont\n",
       "25      California                        Cotati\n",
       "26      California                         Davis\n",
       "27      California                        Irvine\n",
       "28      California                    Isla Vista\n",
       "29      California  University Park, Los Angeles\n",
       "..             ...                           ...\n",
       "487       Virginia                          Wise\n",
       "488       Virginia                    Chesapeake\n",
       "489     Washington                    Bellingham\n",
       "490     Washington                        Cheney\n",
       "491     Washington                    Ellensburg\n",
       "492     Washington                       Pullman\n",
       "493     Washington  University District, Seattle\n",
       "494  West Virginia                        Athens\n",
       "495  West Virginia                    Buckhannon\n",
       "496  West Virginia                      Fairmont\n",
       "497  West Virginia                     Glenville\n",
       "498  West Virginia                    Huntington\n",
       "499  West Virginia                    Montgomery\n",
       "500  West Virginia                    Morgantown\n",
       "501  West Virginia                 Shepherdstown\n",
       "502  West Virginia                  West Liberty\n",
       "503      Wisconsin                      Appleton\n",
       "504      Wisconsin                    Eau Claire\n",
       "505      Wisconsin                     Green Bay\n",
       "506      Wisconsin                     La Crosse\n",
       "507      Wisconsin                       Madison\n",
       "508      Wisconsin                     Menomonie\n",
       "509      Wisconsin                     Milwaukee\n",
       "510      Wisconsin                       Oshkosh\n",
       "511      Wisconsin                   Platteville\n",
       "512      Wisconsin                   River Falls\n",
       "513      Wisconsin                 Stevens Point\n",
       "514      Wisconsin                      Waukesha\n",
       "515      Wisconsin                    Whitewater\n",
       "516        Wyoming                       Laramie\n",
       "\n",
       "[517 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_list_of_university_towns_3():\n",
    "\n",
    "    # read the data to a table\n",
    "    university_towns = pd.read_table('university_towns.txt', header=None, sep='\\ \\(.*', names=[\"State\", \"RegionName\"], engine='python')\\\n",
    "    .fillna(method='ffill', axis=1)\n",
    "    \n",
    "    # clean the data\n",
    "    university_towns = university_towns.assign(State=university_towns.State.replace(to_replace=r'^[^[]*$', value=np.NaN, regex=True)\\\n",
    "    .replace(to_replace=r'\\[.*', value='', regex=True).fillna(method='ffill'))\\\n",
    "    .assign(RegionName=university_towns.RegionName.replace(to_replace=r'^.*\\[.*$', value='Delete', regex=True))\\\n",
    "    .query('RegionName != \"Delete\"').replace(to_replace=r'\\n', value='', regex=True).reset_index().drop('index', axis=1)\n",
    "    \n",
    "    return university_towns\n",
    "get_list_of_university_towns_3()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see how well it performs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "67.7 ms ± 1.28 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 10\n",
    "get_list_of_university_towns_3() # two-line solution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that it performs very good, almost the same as the multi-line solution. The difference is in the 5 ms range, so if it is crucial to the program, we will choose the multi-line solution. if not, we can choose the two-line solution. \n",
    "\n",
    "By the way, the reason it takes the one-line solution a lot of time to get the work done, is the _apply_ attribut. I do not recomend using it unless you must.\n",
    "\n",
    "Let's continue with the testing.\n",
    "Now, we get the GDP levels of the US over time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Quarter</th>\n",
       "      <th>GDP</th>\n",
       "      <th>Real GDP</th>\n",
       "      <th>RealGDPastQuarter</th>\n",
       "      <th>RealGDPChangePercent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000q1</td>\n",
       "      <td>10031.0</td>\n",
       "      <td>12359.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000q2</td>\n",
       "      <td>10278.3</td>\n",
       "      <td>12592.5</td>\n",
       "      <td>12359.1</td>\n",
       "      <td>1.888487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000q3</td>\n",
       "      <td>10357.4</td>\n",
       "      <td>12607.7</td>\n",
       "      <td>12592.5</td>\n",
       "      <td>0.120707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000q4</td>\n",
       "      <td>10472.3</td>\n",
       "      <td>12679.3</td>\n",
       "      <td>12607.7</td>\n",
       "      <td>0.567907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2001q1</td>\n",
       "      <td>10508.1</td>\n",
       "      <td>12643.3</td>\n",
       "      <td>12679.3</td>\n",
       "      <td>-0.283927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2001q2</td>\n",
       "      <td>10638.4</td>\n",
       "      <td>12710.3</td>\n",
       "      <td>12643.3</td>\n",
       "      <td>0.529925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2001q3</td>\n",
       "      <td>10639.5</td>\n",
       "      <td>12670.1</td>\n",
       "      <td>12710.3</td>\n",
       "      <td>-0.316279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2001q4</td>\n",
       "      <td>10701.3</td>\n",
       "      <td>12705.3</td>\n",
       "      <td>12670.1</td>\n",
       "      <td>0.277819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2002q1</td>\n",
       "      <td>10834.4</td>\n",
       "      <td>12822.3</td>\n",
       "      <td>12705.3</td>\n",
       "      <td>0.920876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2002q2</td>\n",
       "      <td>10934.8</td>\n",
       "      <td>12893.0</td>\n",
       "      <td>12822.3</td>\n",
       "      <td>0.551383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2002q3</td>\n",
       "      <td>11037.1</td>\n",
       "      <td>12955.8</td>\n",
       "      <td>12893.0</td>\n",
       "      <td>0.487086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2002q4</td>\n",
       "      <td>11103.8</td>\n",
       "      <td>12964.0</td>\n",
       "      <td>12955.8</td>\n",
       "      <td>0.063292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2003q1</td>\n",
       "      <td>11230.1</td>\n",
       "      <td>13031.2</td>\n",
       "      <td>12964.0</td>\n",
       "      <td>0.518359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2003q2</td>\n",
       "      <td>11370.7</td>\n",
       "      <td>13152.1</td>\n",
       "      <td>13031.2</td>\n",
       "      <td>0.927773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2003q3</td>\n",
       "      <td>11625.1</td>\n",
       "      <td>13372.4</td>\n",
       "      <td>13152.1</td>\n",
       "      <td>1.675018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2003q4</td>\n",
       "      <td>11816.8</td>\n",
       "      <td>13528.7</td>\n",
       "      <td>13372.4</td>\n",
       "      <td>1.168825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2004q1</td>\n",
       "      <td>11988.4</td>\n",
       "      <td>13606.5</td>\n",
       "      <td>13528.7</td>\n",
       "      <td>0.575074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2004q2</td>\n",
       "      <td>12181.4</td>\n",
       "      <td>13706.2</td>\n",
       "      <td>13606.5</td>\n",
       "      <td>0.732738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2004q3</td>\n",
       "      <td>12367.7</td>\n",
       "      <td>13830.8</td>\n",
       "      <td>13706.2</td>\n",
       "      <td>0.909078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2004q4</td>\n",
       "      <td>12562.2</td>\n",
       "      <td>13950.4</td>\n",
       "      <td>13830.8</td>\n",
       "      <td>0.864737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2005q1</td>\n",
       "      <td>12813.7</td>\n",
       "      <td>14099.1</td>\n",
       "      <td>13950.4</td>\n",
       "      <td>1.065919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2005q2</td>\n",
       "      <td>12974.1</td>\n",
       "      <td>14172.7</td>\n",
       "      <td>14099.1</td>\n",
       "      <td>0.522019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2005q3</td>\n",
       "      <td>13205.4</td>\n",
       "      <td>14291.8</td>\n",
       "      <td>14172.7</td>\n",
       "      <td>0.840348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2005q4</td>\n",
       "      <td>13381.6</td>\n",
       "      <td>14373.4</td>\n",
       "      <td>14291.8</td>\n",
       "      <td>0.570957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2006q1</td>\n",
       "      <td>13648.9</td>\n",
       "      <td>14546.1</td>\n",
       "      <td>14373.4</td>\n",
       "      <td>1.201525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2006q2</td>\n",
       "      <td>13799.8</td>\n",
       "      <td>14589.6</td>\n",
       "      <td>14546.1</td>\n",
       "      <td>0.299049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2006q3</td>\n",
       "      <td>13908.5</td>\n",
       "      <td>14602.6</td>\n",
       "      <td>14589.6</td>\n",
       "      <td>0.089105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2006q4</td>\n",
       "      <td>14066.4</td>\n",
       "      <td>14716.9</td>\n",
       "      <td>14602.6</td>\n",
       "      <td>0.782737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2007q1</td>\n",
       "      <td>14233.2</td>\n",
       "      <td>14726.0</td>\n",
       "      <td>14716.9</td>\n",
       "      <td>0.061834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2007q2</td>\n",
       "      <td>14422.3</td>\n",
       "      <td>14838.7</td>\n",
       "      <td>14726.0</td>\n",
       "      <td>0.765313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2009q1</td>\n",
       "      <td>14383.9</td>\n",
       "      <td>14375.0</td>\n",
       "      <td>14577.0</td>\n",
       "      <td>-1.385745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2009q2</td>\n",
       "      <td>14340.4</td>\n",
       "      <td>14355.6</td>\n",
       "      <td>14375.0</td>\n",
       "      <td>-0.134957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2009q3</td>\n",
       "      <td>14384.1</td>\n",
       "      <td>14402.5</td>\n",
       "      <td>14355.6</td>\n",
       "      <td>0.326702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2009q4</td>\n",
       "      <td>14566.5</td>\n",
       "      <td>14541.9</td>\n",
       "      <td>14402.5</td>\n",
       "      <td>0.967888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2010q1</td>\n",
       "      <td>14681.1</td>\n",
       "      <td>14604.8</td>\n",
       "      <td>14541.9</td>\n",
       "      <td>0.432543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2010q2</td>\n",
       "      <td>14888.6</td>\n",
       "      <td>14745.9</td>\n",
       "      <td>14604.8</td>\n",
       "      <td>0.966121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2010q3</td>\n",
       "      <td>15057.7</td>\n",
       "      <td>14845.5</td>\n",
       "      <td>14745.9</td>\n",
       "      <td>0.675442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2010q4</td>\n",
       "      <td>15230.2</td>\n",
       "      <td>14939.0</td>\n",
       "      <td>14845.5</td>\n",
       "      <td>0.629820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2011q1</td>\n",
       "      <td>15238.4</td>\n",
       "      <td>14881.3</td>\n",
       "      <td>14939.0</td>\n",
       "      <td>-0.386237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2011q2</td>\n",
       "      <td>15460.9</td>\n",
       "      <td>14989.6</td>\n",
       "      <td>14881.3</td>\n",
       "      <td>0.727759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2011q3</td>\n",
       "      <td>15587.1</td>\n",
       "      <td>15021.1</td>\n",
       "      <td>14989.6</td>\n",
       "      <td>0.210146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2011q4</td>\n",
       "      <td>15785.3</td>\n",
       "      <td>15190.3</td>\n",
       "      <td>15021.1</td>\n",
       "      <td>1.126416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2012q1</td>\n",
       "      <td>15973.9</td>\n",
       "      <td>15291.0</td>\n",
       "      <td>15190.3</td>\n",
       "      <td>0.662923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2012q2</td>\n",
       "      <td>16121.9</td>\n",
       "      <td>15362.4</td>\n",
       "      <td>15291.0</td>\n",
       "      <td>0.466941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2012q3</td>\n",
       "      <td>16227.9</td>\n",
       "      <td>15380.8</td>\n",
       "      <td>15362.4</td>\n",
       "      <td>0.119773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2012q4</td>\n",
       "      <td>16297.3</td>\n",
       "      <td>15384.3</td>\n",
       "      <td>15380.8</td>\n",
       "      <td>0.022756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2013q1</td>\n",
       "      <td>16475.4</td>\n",
       "      <td>15491.9</td>\n",
       "      <td>15384.3</td>\n",
       "      <td>0.699414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2013q2</td>\n",
       "      <td>16541.4</td>\n",
       "      <td>15521.6</td>\n",
       "      <td>15491.9</td>\n",
       "      <td>0.191713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2013q3</td>\n",
       "      <td>16749.3</td>\n",
       "      <td>15641.3</td>\n",
       "      <td>15521.6</td>\n",
       "      <td>0.771183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2013q4</td>\n",
       "      <td>16999.9</td>\n",
       "      <td>15793.9</td>\n",
       "      <td>15641.3</td>\n",
       "      <td>0.975622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2014q1</td>\n",
       "      <td>17025.2</td>\n",
       "      <td>15747.0</td>\n",
       "      <td>15793.9</td>\n",
       "      <td>-0.296950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2014q2</td>\n",
       "      <td>17285.6</td>\n",
       "      <td>15900.8</td>\n",
       "      <td>15747.0</td>\n",
       "      <td>0.976694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2014q3</td>\n",
       "      <td>17569.4</td>\n",
       "      <td>16094.5</td>\n",
       "      <td>15900.8</td>\n",
       "      <td>1.218178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2014q4</td>\n",
       "      <td>17692.2</td>\n",
       "      <td>16186.7</td>\n",
       "      <td>16094.5</td>\n",
       "      <td>0.572867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2015q1</td>\n",
       "      <td>17783.6</td>\n",
       "      <td>16269.0</td>\n",
       "      <td>16186.7</td>\n",
       "      <td>0.508442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2015q2</td>\n",
       "      <td>17998.3</td>\n",
       "      <td>16374.2</td>\n",
       "      <td>16269.0</td>\n",
       "      <td>0.646629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2015q3</td>\n",
       "      <td>18141.9</td>\n",
       "      <td>16454.9</td>\n",
       "      <td>16374.2</td>\n",
       "      <td>0.492849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2015q4</td>\n",
       "      <td>18222.8</td>\n",
       "      <td>16490.7</td>\n",
       "      <td>16454.9</td>\n",
       "      <td>0.217564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2016q1</td>\n",
       "      <td>18281.6</td>\n",
       "      <td>16525.0</td>\n",
       "      <td>16490.7</td>\n",
       "      <td>0.207996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2016q2</td>\n",
       "      <td>18450.1</td>\n",
       "      <td>16583.1</td>\n",
       "      <td>16525.0</td>\n",
       "      <td>0.351589</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Quarter      GDP  Real GDP  RealGDPastQuarter  RealGDPChangePercent\n",
       "0   2000q1  10031.0   12359.1                NaN                   NaN\n",
       "1   2000q2  10278.3   12592.5            12359.1              1.888487\n",
       "2   2000q3  10357.4   12607.7            12592.5              0.120707\n",
       "3   2000q4  10472.3   12679.3            12607.7              0.567907\n",
       "4   2001q1  10508.1   12643.3            12679.3             -0.283927\n",
       "5   2001q2  10638.4   12710.3            12643.3              0.529925\n",
       "6   2001q3  10639.5   12670.1            12710.3             -0.316279\n",
       "7   2001q4  10701.3   12705.3            12670.1              0.277819\n",
       "8   2002q1  10834.4   12822.3            12705.3              0.920876\n",
       "9   2002q2  10934.8   12893.0            12822.3              0.551383\n",
       "10  2002q3  11037.1   12955.8            12893.0              0.487086\n",
       "11  2002q4  11103.8   12964.0            12955.8              0.063292\n",
       "12  2003q1  11230.1   13031.2            12964.0              0.518359\n",
       "13  2003q2  11370.7   13152.1            13031.2              0.927773\n",
       "14  2003q3  11625.1   13372.4            13152.1              1.675018\n",
       "15  2003q4  11816.8   13528.7            13372.4              1.168825\n",
       "16  2004q1  11988.4   13606.5            13528.7              0.575074\n",
       "17  2004q2  12181.4   13706.2            13606.5              0.732738\n",
       "18  2004q3  12367.7   13830.8            13706.2              0.909078\n",
       "19  2004q4  12562.2   13950.4            13830.8              0.864737\n",
       "20  2005q1  12813.7   14099.1            13950.4              1.065919\n",
       "21  2005q2  12974.1   14172.7            14099.1              0.522019\n",
       "22  2005q3  13205.4   14291.8            14172.7              0.840348\n",
       "23  2005q4  13381.6   14373.4            14291.8              0.570957\n",
       "24  2006q1  13648.9   14546.1            14373.4              1.201525\n",
       "25  2006q2  13799.8   14589.6            14546.1              0.299049\n",
       "26  2006q3  13908.5   14602.6            14589.6              0.089105\n",
       "27  2006q4  14066.4   14716.9            14602.6              0.782737\n",
       "28  2007q1  14233.2   14726.0            14716.9              0.061834\n",
       "29  2007q2  14422.3   14838.7            14726.0              0.765313\n",
       "..     ...      ...       ...                ...                   ...\n",
       "36  2009q1  14383.9   14375.0            14577.0             -1.385745\n",
       "37  2009q2  14340.4   14355.6            14375.0             -0.134957\n",
       "38  2009q3  14384.1   14402.5            14355.6              0.326702\n",
       "39  2009q4  14566.5   14541.9            14402.5              0.967888\n",
       "40  2010q1  14681.1   14604.8            14541.9              0.432543\n",
       "41  2010q2  14888.6   14745.9            14604.8              0.966121\n",
       "42  2010q3  15057.7   14845.5            14745.9              0.675442\n",
       "43  2010q4  15230.2   14939.0            14845.5              0.629820\n",
       "44  2011q1  15238.4   14881.3            14939.0             -0.386237\n",
       "45  2011q2  15460.9   14989.6            14881.3              0.727759\n",
       "46  2011q3  15587.1   15021.1            14989.6              0.210146\n",
       "47  2011q4  15785.3   15190.3            15021.1              1.126416\n",
       "48  2012q1  15973.9   15291.0            15190.3              0.662923\n",
       "49  2012q2  16121.9   15362.4            15291.0              0.466941\n",
       "50  2012q3  16227.9   15380.8            15362.4              0.119773\n",
       "51  2012q4  16297.3   15384.3            15380.8              0.022756\n",
       "52  2013q1  16475.4   15491.9            15384.3              0.699414\n",
       "53  2013q2  16541.4   15521.6            15491.9              0.191713\n",
       "54  2013q3  16749.3   15641.3            15521.6              0.771183\n",
       "55  2013q4  16999.9   15793.9            15641.3              0.975622\n",
       "56  2014q1  17025.2   15747.0            15793.9             -0.296950\n",
       "57  2014q2  17285.6   15900.8            15747.0              0.976694\n",
       "58  2014q3  17569.4   16094.5            15900.8              1.218178\n",
       "59  2014q4  17692.2   16186.7            16094.5              0.572867\n",
       "60  2015q1  17783.6   16269.0            16186.7              0.508442\n",
       "61  2015q2  17998.3   16374.2            16269.0              0.646629\n",
       "62  2015q3  18141.9   16454.9            16374.2              0.492849\n",
       "63  2015q4  18222.8   16490.7            16454.9              0.217564\n",
       "64  2016q1  18281.6   16525.0            16490.7              0.207996\n",
       "65  2016q2  18450.1   16583.1            16525.0              0.351589\n",
       "\n",
       "[66 rows x 5 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_GDP_level(): \n",
    "    # read the data to a table\n",
    "    GDP_level = pd.read_excel('gdplev.xls', skiprows=219, names=['Delete', 'Delete', 'Delete', 'Delete', 'Quarter', 'GDP', 'Real GDP', 'Delete'])\\\n",
    "    .drop('Delete', axis=1)\n",
    "    \n",
    "    # make the 'RealGDPastQuarter' column\n",
    "    GDP_level = GDP_level.assign(RealGDPastQuarter=GDP_level['Real GDP'].shift(1))\n",
    "    \n",
    "    # make the 'RealGDPChangePercent' column\n",
    "    GDP_level = GDP_level.assign(RealGDPChangePercent=((GDP_level['Real GDP']-GDP_level['RealGDPastQuarter'])/GDP_level['RealGDPastQuarter'])*100)\n",
    "    \n",
    "    return GDP_level\n",
    "get_GDP_level()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, with the GDP over time, we can find the start and end of the recession.\n",
    "\n",
    "We defined A _recession_ as a time frame that starts with two consecutive quarters of GDP decline, and ends with two consecutive quarters of GDP growth.\n",
    "\n",
    "Let's find the recession start:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2008q3'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_recession_start():\n",
    "    GDP_level = get_GDP_level()\n",
    "    c = list(GDP_level[GDP_level['RealGDPChangePercent']<0].index)\n",
    "    c = [c[a] for a in range(0, len(c)-1) if (c[a+1]-c[a]==1)|((c[a+1]-c[a]!=1)&(c[a]-c[a-1]==1))]\n",
    "    return GDP_level.loc[c[0], 'Quarter']\n",
    "get_recession_start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's find the recession end:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2009q4'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_recession_end():    \n",
    "    GDP_level = get_GDP_level()\n",
    "    c = list(GDP_level[GDP_level['RealGDPChangePercent']<0].index)\n",
    "    c = [c[a] for a in range(0, len(c)-1) if (c[a+1]-c[a]==1)|((c[a+1]-c[a]!=1)&(c[a]-c[a-1]==1))]\n",
    "    return GDP_level.loc[c[len(c)-1]+2, 'Quarter']\n",
    "get_recession_end()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's find the recession bottom (the quarter with the lowest GDP in the recession time frame):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2009q2'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_recession_bottom():    \n",
    "    GDP_level = get_GDP_level()\n",
    "    c = list(GDP_level[GDP_level['RealGDPChangePercent']<0].index)\n",
    "    c = [c[a] for a in range(0, len(c)-1) if (c[a+1]-c[a]==1)|((c[a+1]-c[a]!=1)&(c[a]-c[a-1]==1))]\n",
    "    return GDP_level.loc[GDP_level.loc[c, 'Real GDP'].idxmin(), 'Quarter']\n",
    "get_recession_bottom()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's get the housing data.\n",
    "\n",
    "We use a dictionary to map state acronyms to state names:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "states = {'OH': 'Ohio', 'KY': 'Kentucky', 'AS': 'American Samoa', 'NV': 'Nevada', 'WY': 'Wyoming', 'NA': 'National', 'AL': 'Alabama', 'MD': 'Maryland', 'AK': 'Alaska', 'UT': 'Utah', 'OR': 'Oregon', 'MT': 'Montana', 'IL': 'Illinois', 'TN': 'Tennessee', 'DC': 'District of Columbia', 'VT': 'Vermont', 'ID': 'Idaho', 'AR': 'Arkansas', 'ME': 'Maine', 'WA': 'Washington', 'HI': 'Hawaii', 'WI': 'Wisconsin', 'MI': 'Michigan', 'IN': 'Indiana', 'NJ': 'New Jersey', 'AZ': 'Arizona', 'GU': 'Guam', 'MS': 'Mississippi', 'PR': 'Puerto Rico', 'NC': 'North Carolina', 'TX': 'Texas', 'SD': 'South Dakota', 'MP': 'Northern Mariana Islands', 'IA': 'Iowa', 'MO': 'Missouri', 'CT': 'Connecticut', 'WV': 'West Virginia', 'SC': 'South Carolina', 'LA': 'Louisiana', 'KS': 'Kansas', 'NY': 'New York', 'NE': 'Nebraska', 'OK': 'Oklahoma', 'FL': 'Florida', 'CA': 'California', 'CO': 'Colorado', 'PA': 'Pennsylvania', 'DE': 'Delaware', 'NM': 'New Mexico', 'RI': 'Rhode Island', 'MN': 'Minnesota', 'VI': 'Virgin Islands', 'NH': 'New Hampshire', 'MA': 'Massachusetts', 'GA': 'Georgia', 'ND': 'North Dakota', 'VA': 'Virginia'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We read and clean the housing data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>2000q1</th>\n",
       "      <th>2000q2</th>\n",
       "      <th>2000q3</th>\n",
       "      <th>2000q4</th>\n",
       "      <th>2001q1</th>\n",
       "      <th>2001q2</th>\n",
       "      <th>2001q3</th>\n",
       "      <th>2001q4</th>\n",
       "      <th>2002q1</th>\n",
       "      <th>2002q2</th>\n",
       "      <th>...</th>\n",
       "      <th>2014q2</th>\n",
       "      <th>2014q3</th>\n",
       "      <th>2014q4</th>\n",
       "      <th>2015q1</th>\n",
       "      <th>2015q2</th>\n",
       "      <th>2015q3</th>\n",
       "      <th>2015q4</th>\n",
       "      <th>2016q1</th>\n",
       "      <th>2016q2</th>\n",
       "      <th>2016q3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>State</th>\n",
       "      <th>RegionName</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 rowspan=\"14\" valign=\"top\">Alaska</th>\n",
       "      <th>Anchor Point</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>157800.000000</td>\n",
       "      <td>158000.000000</td>\n",
       "      <td>155566.666667</td>\n",
       "      <td>154266.666667</td>\n",
       "      <td>154100.000000</td>\n",
       "      <td>153966.666667</td>\n",
       "      <td>154766.666667</td>\n",
       "      <td>156800.000000</td>\n",
       "      <td>161533.333333</td>\n",
       "      <td>161200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Anchorage</th>\n",
       "      <td>174633.333333</td>\n",
       "      <td>175266.666667</td>\n",
       "      <td>179566.666667</td>\n",
       "      <td>182833.333333</td>\n",
       "      <td>182766.666667</td>\n",
       "      <td>183933.333333</td>\n",
       "      <td>188566.666667</td>\n",
       "      <td>191866.666667</td>\n",
       "      <td>193966.666667</td>\n",
       "      <td>196700.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>278200.000000</td>\n",
       "      <td>280766.666667</td>\n",
       "      <td>281700.000000</td>\n",
       "      <td>284166.666667</td>\n",
       "      <td>287166.666667</td>\n",
       "      <td>290233.333333</td>\n",
       "      <td>291700.000000</td>\n",
       "      <td>293700.000000</td>\n",
       "      <td>294833.333333</td>\n",
       "      <td>294600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fairbanks</th>\n",
       "      <td>163200.000000</td>\n",
       "      <td>165033.333333</td>\n",
       "      <td>169300.000000</td>\n",
       "      <td>172800.000000</td>\n",
       "      <td>164433.333333</td>\n",
       "      <td>157800.000000</td>\n",
       "      <td>158200.000000</td>\n",
       "      <td>154666.666667</td>\n",
       "      <td>152766.666667</td>\n",
       "      <td>154533.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>209233.333333</td>\n",
       "      <td>207100.000000</td>\n",
       "      <td>207000.000000</td>\n",
       "      <td>207766.666667</td>\n",
       "      <td>206466.666667</td>\n",
       "      <td>208433.333333</td>\n",
       "      <td>209466.666667</td>\n",
       "      <td>209066.666667</td>\n",
       "      <td>212933.333333</td>\n",
       "      <td>215850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Homer</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>233033.333333</td>\n",
       "      <td>232900.000000</td>\n",
       "      <td>231066.666667</td>\n",
       "      <td>233500.000000</td>\n",
       "      <td>238100.000000</td>\n",
       "      <td>238933.333333</td>\n",
       "      <td>240500.000000</td>\n",
       "      <td>243166.666667</td>\n",
       "      <td>245166.666667</td>\n",
       "      <td>247600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Juneau</th>\n",
       "      <td>192466.666667</td>\n",
       "      <td>194300.000000</td>\n",
       "      <td>195166.666667</td>\n",
       "      <td>194166.666667</td>\n",
       "      <td>197166.666667</td>\n",
       "      <td>199533.333333</td>\n",
       "      <td>202433.333333</td>\n",
       "      <td>206300.000000</td>\n",
       "      <td>209066.666667</td>\n",
       "      <td>209866.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>328266.666667</td>\n",
       "      <td>331833.333333</td>\n",
       "      <td>333200.000000</td>\n",
       "      <td>335666.666667</td>\n",
       "      <td>337366.666667</td>\n",
       "      <td>325933.333333</td>\n",
       "      <td>319333.333333</td>\n",
       "      <td>318933.333333</td>\n",
       "      <td>319933.333333</td>\n",
       "      <td>319200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kenai</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>199466.666667</td>\n",
       "      <td>197966.666667</td>\n",
       "      <td>194600.000000</td>\n",
       "      <td>198500.000000</td>\n",
       "      <td>202700.000000</td>\n",
       "      <td>204766.666667</td>\n",
       "      <td>206433.333333</td>\n",
       "      <td>209633.333333</td>\n",
       "      <td>211666.666667</td>\n",
       "      <td>211950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ketchikan</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>196866.666667</td>\n",
       "      <td>197100.000000</td>\n",
       "      <td>197700.000000</td>\n",
       "      <td>198033.333333</td>\n",
       "      <td>196300.000000</td>\n",
       "      <td>196533.333333</td>\n",
       "      <td>196633.333333</td>\n",
       "      <td>195600.000000</td>\n",
       "      <td>205300.000000</td>\n",
       "      <td>206450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kodiak</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>256400.000000</td>\n",
       "      <td>256966.666667</td>\n",
       "      <td>257933.333333</td>\n",
       "      <td>258566.666667</td>\n",
       "      <td>256133.333333</td>\n",
       "      <td>256400.000000</td>\n",
       "      <td>256800.000000</td>\n",
       "      <td>255233.333333</td>\n",
       "      <td>270166.666667</td>\n",
       "      <td>271250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lakes</th>\n",
       "      <td>172733.333333</td>\n",
       "      <td>174133.333333</td>\n",
       "      <td>177266.666667</td>\n",
       "      <td>179133.333333</td>\n",
       "      <td>172400.000000</td>\n",
       "      <td>166000.000000</td>\n",
       "      <td>169500.000000</td>\n",
       "      <td>170766.666667</td>\n",
       "      <td>168766.666667</td>\n",
       "      <td>169900.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>228200.000000</td>\n",
       "      <td>233966.666667</td>\n",
       "      <td>236966.666667</td>\n",
       "      <td>239833.333333</td>\n",
       "      <td>240033.333333</td>\n",
       "      <td>242733.333333</td>\n",
       "      <td>244500.000000</td>\n",
       "      <td>250100.000000</td>\n",
       "      <td>250266.666667</td>\n",
       "      <td>250550.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Pole</th>\n",
       "      <td>157466.666667</td>\n",
       "      <td>159100.000000</td>\n",
       "      <td>162133.333333</td>\n",
       "      <td>165500.000000</td>\n",
       "      <td>159433.333333</td>\n",
       "      <td>149766.666667</td>\n",
       "      <td>151266.666667</td>\n",
       "      <td>151000.000000</td>\n",
       "      <td>150033.333333</td>\n",
       "      <td>151866.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>199933.333333</td>\n",
       "      <td>199400.000000</td>\n",
       "      <td>197366.666667</td>\n",
       "      <td>199066.666667</td>\n",
       "      <td>200300.000000</td>\n",
       "      <td>204100.000000</td>\n",
       "      <td>206400.000000</td>\n",
       "      <td>206633.333333</td>\n",
       "      <td>208166.666667</td>\n",
       "      <td>209300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Palmer</th>\n",
       "      <td>168766.666667</td>\n",
       "      <td>170566.666667</td>\n",
       "      <td>174233.333333</td>\n",
       "      <td>175533.333333</td>\n",
       "      <td>169466.666667</td>\n",
       "      <td>163233.333333</td>\n",
       "      <td>166933.333333</td>\n",
       "      <td>168933.333333</td>\n",
       "      <td>165300.000000</td>\n",
       "      <td>164800.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>225566.666667</td>\n",
       "      <td>228766.666667</td>\n",
       "      <td>229366.666667</td>\n",
       "      <td>234466.666667</td>\n",
       "      <td>237800.000000</td>\n",
       "      <td>239900.000000</td>\n",
       "      <td>241666.666667</td>\n",
       "      <td>246400.000000</td>\n",
       "      <td>245733.333333</td>\n",
       "      <td>244750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Seward</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>194600.000000</td>\n",
       "      <td>190533.333333</td>\n",
       "      <td>186600.000000</td>\n",
       "      <td>186800.000000</td>\n",
       "      <td>185533.333333</td>\n",
       "      <td>186433.333333</td>\n",
       "      <td>191000.000000</td>\n",
       "      <td>203600.000000</td>\n",
       "      <td>214666.666667</td>\n",
       "      <td>214950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Soldotna</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>210366.666667</td>\n",
       "      <td>209300.000000</td>\n",
       "      <td>207966.666667</td>\n",
       "      <td>213500.000000</td>\n",
       "      <td>217233.333333</td>\n",
       "      <td>220433.333333</td>\n",
       "      <td>219866.666667</td>\n",
       "      <td>223466.666667</td>\n",
       "      <td>223333.333333</td>\n",
       "      <td>222600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tanaina</th>\n",
       "      <td>160500.000000</td>\n",
       "      <td>163500.000000</td>\n",
       "      <td>166366.666667</td>\n",
       "      <td>168033.333333</td>\n",
       "      <td>158766.666667</td>\n",
       "      <td>149200.000000</td>\n",
       "      <td>150966.666667</td>\n",
       "      <td>151600.000000</td>\n",
       "      <td>153033.333333</td>\n",
       "      <td>156100.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>208900.000000</td>\n",
       "      <td>211000.000000</td>\n",
       "      <td>212466.666667</td>\n",
       "      <td>215200.000000</td>\n",
       "      <td>215633.333333</td>\n",
       "      <td>217700.000000</td>\n",
       "      <td>218800.000000</td>\n",
       "      <td>223100.000000</td>\n",
       "      <td>225200.000000</td>\n",
       "      <td>225500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"16\" valign=\"top\">Alabama</th>\n",
       "      <th>Adamsville</th>\n",
       "      <td>69033.333333</td>\n",
       "      <td>69166.666667</td>\n",
       "      <td>69800.000000</td>\n",
       "      <td>71966.666667</td>\n",
       "      <td>73466.666667</td>\n",
       "      <td>74000.000000</td>\n",
       "      <td>73333.333333</td>\n",
       "      <td>73100.000000</td>\n",
       "      <td>73333.333333</td>\n",
       "      <td>73133.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>77066.666667</td>\n",
       "      <td>75966.666667</td>\n",
       "      <td>71900.000000</td>\n",
       "      <td>71666.666667</td>\n",
       "      <td>73033.333333</td>\n",
       "      <td>73933.333333</td>\n",
       "      <td>73866.666667</td>\n",
       "      <td>74166.666667</td>\n",
       "      <td>74933.333333</td>\n",
       "      <td>74700.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alabaster</th>\n",
       "      <td>122133.333333</td>\n",
       "      <td>123066.666667</td>\n",
       "      <td>123166.666667</td>\n",
       "      <td>123700.000000</td>\n",
       "      <td>123233.333333</td>\n",
       "      <td>125133.333333</td>\n",
       "      <td>127766.666667</td>\n",
       "      <td>127200.000000</td>\n",
       "      <td>127300.000000</td>\n",
       "      <td>128000.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>147133.333333</td>\n",
       "      <td>147633.333333</td>\n",
       "      <td>148700.000000</td>\n",
       "      <td>148900.000000</td>\n",
       "      <td>149566.666667</td>\n",
       "      <td>150366.666667</td>\n",
       "      <td>151733.333333</td>\n",
       "      <td>153466.666667</td>\n",
       "      <td>155100.000000</td>\n",
       "      <td>155850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albertville</th>\n",
       "      <td>73966.666667</td>\n",
       "      <td>72600.000000</td>\n",
       "      <td>72833.333333</td>\n",
       "      <td>74200.000000</td>\n",
       "      <td>75900.000000</td>\n",
       "      <td>76000.000000</td>\n",
       "      <td>72066.666667</td>\n",
       "      <td>73566.666667</td>\n",
       "      <td>76533.333333</td>\n",
       "      <td>76366.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>84033.333333</td>\n",
       "      <td>84766.666667</td>\n",
       "      <td>86800.000000</td>\n",
       "      <td>88466.666667</td>\n",
       "      <td>89500.000000</td>\n",
       "      <td>90233.333333</td>\n",
       "      <td>91366.666667</td>\n",
       "      <td>92000.000000</td>\n",
       "      <td>92466.666667</td>\n",
       "      <td>92200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arab</th>\n",
       "      <td>83766.666667</td>\n",
       "      <td>81566.666667</td>\n",
       "      <td>81333.333333</td>\n",
       "      <td>82966.666667</td>\n",
       "      <td>84200.000000</td>\n",
       "      <td>84533.333333</td>\n",
       "      <td>81666.666667</td>\n",
       "      <td>83900.000000</td>\n",
       "      <td>87266.666667</td>\n",
       "      <td>87700.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>113366.666667</td>\n",
       "      <td>111700.000000</td>\n",
       "      <td>111600.000000</td>\n",
       "      <td>110166.666667</td>\n",
       "      <td>109433.333333</td>\n",
       "      <td>110900.000000</td>\n",
       "      <td>112233.333333</td>\n",
       "      <td>110033.333333</td>\n",
       "      <td>110100.000000</td>\n",
       "      <td>112000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ardmore</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>140533.333333</td>\n",
       "      <td>139566.666667</td>\n",
       "      <td>140900.000000</td>\n",
       "      <td>143233.333333</td>\n",
       "      <td>143000.000000</td>\n",
       "      <td>144600.000000</td>\n",
       "      <td>143966.666667</td>\n",
       "      <td>142566.666667</td>\n",
       "      <td>143233.333333</td>\n",
       "      <td>141950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Axis</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>111066.666667</td>\n",
       "      <td>111833.333333</td>\n",
       "      <td>111800.000000</td>\n",
       "      <td>109533.333333</td>\n",
       "      <td>109666.666667</td>\n",
       "      <td>110033.333333</td>\n",
       "      <td>109600.000000</td>\n",
       "      <td>110266.666667</td>\n",
       "      <td>112200.000000</td>\n",
       "      <td>112750.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Baileyton</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>87666.666667</td>\n",
       "      <td>90033.333333</td>\n",
       "      <td>94100.000000</td>\n",
       "      <td>94600.000000</td>\n",
       "      <td>95666.666667</td>\n",
       "      <td>96833.333333</td>\n",
       "      <td>97233.333333</td>\n",
       "      <td>96766.666667</td>\n",
       "      <td>98900.000000</td>\n",
       "      <td>102200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bay Minette</th>\n",
       "      <td>81700.000000</td>\n",
       "      <td>78533.333333</td>\n",
       "      <td>79133.333333</td>\n",
       "      <td>81300.000000</td>\n",
       "      <td>85700.000000</td>\n",
       "      <td>87266.666667</td>\n",
       "      <td>85900.000000</td>\n",
       "      <td>85000.000000</td>\n",
       "      <td>84066.666667</td>\n",
       "      <td>84566.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>113333.333333</td>\n",
       "      <td>110600.000000</td>\n",
       "      <td>109900.000000</td>\n",
       "      <td>111100.000000</td>\n",
       "      <td>114300.000000</td>\n",
       "      <td>118533.333333</td>\n",
       "      <td>121433.333333</td>\n",
       "      <td>120266.666667</td>\n",
       "      <td>118333.333333</td>\n",
       "      <td>118500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bayou La Batre</th>\n",
       "      <td>44066.666667</td>\n",
       "      <td>44500.000000</td>\n",
       "      <td>44266.666667</td>\n",
       "      <td>43666.666667</td>\n",
       "      <td>42500.000000</td>\n",
       "      <td>43333.333333</td>\n",
       "      <td>45433.333333</td>\n",
       "      <td>45400.000000</td>\n",
       "      <td>45400.000000</td>\n",
       "      <td>45566.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>49800.000000</td>\n",
       "      <td>51000.000000</td>\n",
       "      <td>51766.666667</td>\n",
       "      <td>50733.333333</td>\n",
       "      <td>50500.000000</td>\n",
       "      <td>50133.333333</td>\n",
       "      <td>48933.333333</td>\n",
       "      <td>48566.666667</td>\n",
       "      <td>47833.333333</td>\n",
       "      <td>47400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bessemer</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>54600.000000</td>\n",
       "      <td>55333.333333</td>\n",
       "      <td>54733.333333</td>\n",
       "      <td>55200.000000</td>\n",
       "      <td>57200.000000</td>\n",
       "      <td>58633.333333</td>\n",
       "      <td>59433.333333</td>\n",
       "      <td>59766.666667</td>\n",
       "      <td>59866.666667</td>\n",
       "      <td>59800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Birmingham</th>\n",
       "      <td>54033.333333</td>\n",
       "      <td>54400.000000</td>\n",
       "      <td>54966.666667</td>\n",
       "      <td>56066.666667</td>\n",
       "      <td>56833.333333</td>\n",
       "      <td>57600.000000</td>\n",
       "      <td>58433.333333</td>\n",
       "      <td>58700.000000</td>\n",
       "      <td>59500.000000</td>\n",
       "      <td>59866.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>61733.333333</td>\n",
       "      <td>60900.000000</td>\n",
       "      <td>59533.333333</td>\n",
       "      <td>59900.000000</td>\n",
       "      <td>61966.666667</td>\n",
       "      <td>62666.666667</td>\n",
       "      <td>63100.000000</td>\n",
       "      <td>62033.333333</td>\n",
       "      <td>61633.333333</td>\n",
       "      <td>61250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Boaz</th>\n",
       "      <td>70866.666667</td>\n",
       "      <td>70266.666667</td>\n",
       "      <td>70300.000000</td>\n",
       "      <td>71466.666667</td>\n",
       "      <td>72833.333333</td>\n",
       "      <td>71900.000000</td>\n",
       "      <td>68733.333333</td>\n",
       "      <td>69833.333333</td>\n",
       "      <td>72766.666667</td>\n",
       "      <td>72100.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>80933.333333</td>\n",
       "      <td>81866.666667</td>\n",
       "      <td>82866.666667</td>\n",
       "      <td>83966.666667</td>\n",
       "      <td>85266.666667</td>\n",
       "      <td>86033.333333</td>\n",
       "      <td>86566.666667</td>\n",
       "      <td>85966.666667</td>\n",
       "      <td>87366.666667</td>\n",
       "      <td>88600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brent</th>\n",
       "      <td>92933.333333</td>\n",
       "      <td>94333.333333</td>\n",
       "      <td>96166.666667</td>\n",
       "      <td>98333.333333</td>\n",
       "      <td>96533.333333</td>\n",
       "      <td>98500.000000</td>\n",
       "      <td>99366.666667</td>\n",
       "      <td>104100.000000</td>\n",
       "      <td>103800.000000</td>\n",
       "      <td>102533.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>93866.666667</td>\n",
       "      <td>97100.000000</td>\n",
       "      <td>100100.000000</td>\n",
       "      <td>102433.333333</td>\n",
       "      <td>101800.000000</td>\n",
       "      <td>97900.000000</td>\n",
       "      <td>95600.000000</td>\n",
       "      <td>94433.333333</td>\n",
       "      <td>91366.666667</td>\n",
       "      <td>87650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brighton</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>45366.666667</td>\n",
       "      <td>45133.333333</td>\n",
       "      <td>43766.666667</td>\n",
       "      <td>42500.000000</td>\n",
       "      <td>44233.333333</td>\n",
       "      <td>46266.666667</td>\n",
       "      <td>45766.666667</td>\n",
       "      <td>45033.333333</td>\n",
       "      <td>44433.333333</td>\n",
       "      <td>44000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Brookwood</th>\n",
       "      <td>92566.666667</td>\n",
       "      <td>95100.000000</td>\n",
       "      <td>98866.666667</td>\n",
       "      <td>99966.666667</td>\n",
       "      <td>101666.666667</td>\n",
       "      <td>103666.666667</td>\n",
       "      <td>101833.333333</td>\n",
       "      <td>99900.000000</td>\n",
       "      <td>99633.333333</td>\n",
       "      <td>100366.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>106633.333333</td>\n",
       "      <td>110233.333333</td>\n",
       "      <td>114366.666667</td>\n",
       "      <td>117700.000000</td>\n",
       "      <td>118700.000000</td>\n",
       "      <td>120066.666667</td>\n",
       "      <td>118533.333333</td>\n",
       "      <td>115233.333333</td>\n",
       "      <td>111966.666667</td>\n",
       "      <td>108650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Buhl</th>\n",
       "      <td>90800.000000</td>\n",
       "      <td>94600.000000</td>\n",
       "      <td>96500.000000</td>\n",
       "      <td>96566.666667</td>\n",
       "      <td>99266.666667</td>\n",
       "      <td>101966.666667</td>\n",
       "      <td>102000.000000</td>\n",
       "      <td>102733.333333</td>\n",
       "      <td>102533.333333</td>\n",
       "      <td>100100.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>119233.333333</td>\n",
       "      <td>132033.333333</td>\n",
       "      <td>138400.000000</td>\n",
       "      <td>141766.666667</td>\n",
       "      <td>141200.000000</td>\n",
       "      <td>141066.666667</td>\n",
       "      <td>145500.000000</td>\n",
       "      <td>139800.000000</td>\n",
       "      <td>135566.666667</td>\n",
       "      <td>128350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <th>Yorkville</th>\n",
       "      <td>139066.666667</td>\n",
       "      <td>134900.000000</td>\n",
       "      <td>135033.333333</td>\n",
       "      <td>140300.000000</td>\n",
       "      <td>148800.000000</td>\n",
       "      <td>155233.333333</td>\n",
       "      <td>161133.333333</td>\n",
       "      <td>162800.000000</td>\n",
       "      <td>164866.666667</td>\n",
       "      <td>172466.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>231500.000000</td>\n",
       "      <td>238133.333333</td>\n",
       "      <td>237766.666667</td>\n",
       "      <td>239133.333333</td>\n",
       "      <td>243066.666667</td>\n",
       "      <td>243066.666667</td>\n",
       "      <td>244800.000000</td>\n",
       "      <td>248466.666667</td>\n",
       "      <td>255200.000000</td>\n",
       "      <td>265950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"23\" valign=\"top\">West Virginia</th>\n",
       "      <th>Belle</th>\n",
       "      <td>51066.666667</td>\n",
       "      <td>51300.000000</td>\n",
       "      <td>52200.000000</td>\n",
       "      <td>51166.666667</td>\n",
       "      <td>51266.666667</td>\n",
       "      <td>51966.666667</td>\n",
       "      <td>50166.666667</td>\n",
       "      <td>49333.333333</td>\n",
       "      <td>48666.666667</td>\n",
       "      <td>49633.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>72900.000000</td>\n",
       "      <td>74066.666667</td>\n",
       "      <td>73133.333333</td>\n",
       "      <td>71966.666667</td>\n",
       "      <td>73566.666667</td>\n",
       "      <td>74233.333333</td>\n",
       "      <td>74600.000000</td>\n",
       "      <td>73266.666667</td>\n",
       "      <td>74066.666667</td>\n",
       "      <td>74550.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Charleston</th>\n",
       "      <td>59533.333333</td>\n",
       "      <td>59366.666667</td>\n",
       "      <td>59366.666667</td>\n",
       "      <td>59633.333333</td>\n",
       "      <td>60400.000000</td>\n",
       "      <td>59866.666667</td>\n",
       "      <td>61000.000000</td>\n",
       "      <td>60766.666667</td>\n",
       "      <td>59000.000000</td>\n",
       "      <td>58333.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>95433.333333</td>\n",
       "      <td>99733.333333</td>\n",
       "      <td>102466.666667</td>\n",
       "      <td>102900.000000</td>\n",
       "      <td>103233.333333</td>\n",
       "      <td>102133.333333</td>\n",
       "      <td>102466.666667</td>\n",
       "      <td>104733.333333</td>\n",
       "      <td>107133.333333</td>\n",
       "      <td>108150.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chesapeake</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>40550.000000</td>\n",
       "      <td>40433.333333</td>\n",
       "      <td>39633.333333</td>\n",
       "      <td>38633.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>66400.000000</td>\n",
       "      <td>65633.333333</td>\n",
       "      <td>65166.666667</td>\n",
       "      <td>64833.333333</td>\n",
       "      <td>66033.333333</td>\n",
       "      <td>67133.333333</td>\n",
       "      <td>66433.333333</td>\n",
       "      <td>67800.000000</td>\n",
       "      <td>69000.000000</td>\n",
       "      <td>67850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Clendenin</th>\n",
       "      <td>39966.666667</td>\n",
       "      <td>38200.000000</td>\n",
       "      <td>40500.000000</td>\n",
       "      <td>39000.000000</td>\n",
       "      <td>42700.000000</td>\n",
       "      <td>42233.333333</td>\n",
       "      <td>41700.000000</td>\n",
       "      <td>43800.000000</td>\n",
       "      <td>43433.333333</td>\n",
       "      <td>43833.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>82233.333333</td>\n",
       "      <td>82900.000000</td>\n",
       "      <td>83533.333333</td>\n",
       "      <td>81900.000000</td>\n",
       "      <td>80933.333333</td>\n",
       "      <td>79833.333333</td>\n",
       "      <td>81800.000000</td>\n",
       "      <td>84033.333333</td>\n",
       "      <td>87500.000000</td>\n",
       "      <td>88100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coal Fork</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43350.000000</td>\n",
       "      <td>43200.000000</td>\n",
       "      <td>43466.666667</td>\n",
       "      <td>43666.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>65933.333333</td>\n",
       "      <td>68133.333333</td>\n",
       "      <td>69366.666667</td>\n",
       "      <td>69700.000000</td>\n",
       "      <td>69933.333333</td>\n",
       "      <td>69933.333333</td>\n",
       "      <td>70466.666667</td>\n",
       "      <td>70266.666667</td>\n",
       "      <td>72700.000000</td>\n",
       "      <td>73200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cross Lanes</th>\n",
       "      <td>78133.333333</td>\n",
       "      <td>78066.666667</td>\n",
       "      <td>79233.333333</td>\n",
       "      <td>79466.666667</td>\n",
       "      <td>78800.000000</td>\n",
       "      <td>79366.666667</td>\n",
       "      <td>78100.000000</td>\n",
       "      <td>78766.666667</td>\n",
       "      <td>78733.333333</td>\n",
       "      <td>79100.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>123566.666667</td>\n",
       "      <td>124633.333333</td>\n",
       "      <td>126233.333333</td>\n",
       "      <td>126633.333333</td>\n",
       "      <td>126833.333333</td>\n",
       "      <td>126466.666667</td>\n",
       "      <td>126666.666667</td>\n",
       "      <td>126333.333333</td>\n",
       "      <td>125433.333333</td>\n",
       "      <td>124000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Davisville</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>65766.666667</td>\n",
       "      <td>66200.000000</td>\n",
       "      <td>65466.666667</td>\n",
       "      <td>64933.333333</td>\n",
       "      <td>64766.666667</td>\n",
       "      <td>62900.000000</td>\n",
       "      <td>63266.666667</td>\n",
       "      <td>64966.666667</td>\n",
       "      <td>66800.000000</td>\n",
       "      <td>69650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Dunbar</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>76566.666667</td>\n",
       "      <td>78866.666667</td>\n",
       "      <td>79100.000000</td>\n",
       "      <td>77833.333333</td>\n",
       "      <td>77433.333333</td>\n",
       "      <td>77333.333333</td>\n",
       "      <td>77100.000000</td>\n",
       "      <td>76533.333333</td>\n",
       "      <td>76800.000000</td>\n",
       "      <td>76300.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East Bank</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39750.000000</td>\n",
       "      <td>41366.666667</td>\n",
       "      <td>43233.333333</td>\n",
       "      <td>43333.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>69366.666667</td>\n",
       "      <td>70666.666667</td>\n",
       "      <td>71333.333333</td>\n",
       "      <td>69866.666667</td>\n",
       "      <td>69366.666667</td>\n",
       "      <td>67500.000000</td>\n",
       "      <td>65933.333333</td>\n",
       "      <td>66766.666667</td>\n",
       "      <td>67833.333333</td>\n",
       "      <td>69550.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elkview</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>97433.333333</td>\n",
       "      <td>101066.666667</td>\n",
       "      <td>102633.333333</td>\n",
       "      <td>102133.333333</td>\n",
       "      <td>102333.333333</td>\n",
       "      <td>100866.666667</td>\n",
       "      <td>101700.000000</td>\n",
       "      <td>103666.666667</td>\n",
       "      <td>107533.333333</td>\n",
       "      <td>110200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eskdale</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>69366.666667</td>\n",
       "      <td>69866.666667</td>\n",
       "      <td>70166.666667</td>\n",
       "      <td>68166.666667</td>\n",
       "      <td>68066.666667</td>\n",
       "      <td>66266.666667</td>\n",
       "      <td>65233.333333</td>\n",
       "      <td>64666.666667</td>\n",
       "      <td>66500.000000</td>\n",
       "      <td>68350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marmet</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>47800.000000</td>\n",
       "      <td>46800.000000</td>\n",
       "      <td>46533.333333</td>\n",
       "      <td>46000.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>68366.666667</td>\n",
       "      <td>68333.333333</td>\n",
       "      <td>69400.000000</td>\n",
       "      <td>68966.666667</td>\n",
       "      <td>67533.333333</td>\n",
       "      <td>67833.333333</td>\n",
       "      <td>68733.333333</td>\n",
       "      <td>70033.333333</td>\n",
       "      <td>73300.000000</td>\n",
       "      <td>75550.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mineral Wells</th>\n",
       "      <td>75533.333333</td>\n",
       "      <td>77233.333333</td>\n",
       "      <td>81966.666667</td>\n",
       "      <td>85300.000000</td>\n",
       "      <td>86700.000000</td>\n",
       "      <td>87133.333333</td>\n",
       "      <td>83666.666667</td>\n",
       "      <td>81500.000000</td>\n",
       "      <td>82833.333333</td>\n",
       "      <td>85033.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>116466.666667</td>\n",
       "      <td>119000.000000</td>\n",
       "      <td>120433.333333</td>\n",
       "      <td>117933.333333</td>\n",
       "      <td>118866.666667</td>\n",
       "      <td>120100.000000</td>\n",
       "      <td>120266.666667</td>\n",
       "      <td>121066.666667</td>\n",
       "      <td>122266.666667</td>\n",
       "      <td>122000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nitro</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>87366.666667</td>\n",
       "      <td>88633.333333</td>\n",
       "      <td>89400.000000</td>\n",
       "      <td>89900.000000</td>\n",
       "      <td>88833.333333</td>\n",
       "      <td>88000.000000</td>\n",
       "      <td>88900.000000</td>\n",
       "      <td>88000.000000</td>\n",
       "      <td>88800.000000</td>\n",
       "      <td>90250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parkersburg</th>\n",
       "      <td>54900.000000</td>\n",
       "      <td>55833.333333</td>\n",
       "      <td>56633.333333</td>\n",
       "      <td>56833.333333</td>\n",
       "      <td>57400.000000</td>\n",
       "      <td>57566.666667</td>\n",
       "      <td>57933.333333</td>\n",
       "      <td>58866.666667</td>\n",
       "      <td>59500.000000</td>\n",
       "      <td>59366.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>79333.333333</td>\n",
       "      <td>79500.000000</td>\n",
       "      <td>78933.333333</td>\n",
       "      <td>78233.333333</td>\n",
       "      <td>79066.666667</td>\n",
       "      <td>79600.000000</td>\n",
       "      <td>80666.666667</td>\n",
       "      <td>80100.000000</td>\n",
       "      <td>80066.666667</td>\n",
       "      <td>81500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Saint Albans</th>\n",
       "      <td>63833.333333</td>\n",
       "      <td>64700.000000</td>\n",
       "      <td>65200.000000</td>\n",
       "      <td>65900.000000</td>\n",
       "      <td>66366.666667</td>\n",
       "      <td>66466.666667</td>\n",
       "      <td>67266.666667</td>\n",
       "      <td>66100.000000</td>\n",
       "      <td>64600.000000</td>\n",
       "      <td>63866.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>91133.333333</td>\n",
       "      <td>93333.333333</td>\n",
       "      <td>94900.000000</td>\n",
       "      <td>96333.333333</td>\n",
       "      <td>95800.000000</td>\n",
       "      <td>95833.333333</td>\n",
       "      <td>97600.000000</td>\n",
       "      <td>99100.000000</td>\n",
       "      <td>100666.666667</td>\n",
       "      <td>100900.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sissonville</th>\n",
       "      <td>57200.000000</td>\n",
       "      <td>58200.000000</td>\n",
       "      <td>61200.000000</td>\n",
       "      <td>60700.000000</td>\n",
       "      <td>59000.000000</td>\n",
       "      <td>57133.333333</td>\n",
       "      <td>53566.666667</td>\n",
       "      <td>53833.333333</td>\n",
       "      <td>53400.000000</td>\n",
       "      <td>55633.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>97633.333333</td>\n",
       "      <td>103766.666667</td>\n",
       "      <td>106600.000000</td>\n",
       "      <td>103966.666667</td>\n",
       "      <td>99800.000000</td>\n",
       "      <td>100266.666667</td>\n",
       "      <td>102033.333333</td>\n",
       "      <td>104766.666667</td>\n",
       "      <td>107633.333333</td>\n",
       "      <td>109850.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Charleston</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>102266.666667</td>\n",
       "      <td>103933.333333</td>\n",
       "      <td>104966.666667</td>\n",
       "      <td>104933.333333</td>\n",
       "      <td>105333.333333</td>\n",
       "      <td>105600.000000</td>\n",
       "      <td>106066.666667</td>\n",
       "      <td>107233.333333</td>\n",
       "      <td>111666.666667</td>\n",
       "      <td>112950.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Upper Falls</th>\n",
       "      <td>53033.333333</td>\n",
       "      <td>52333.333333</td>\n",
       "      <td>52100.000000</td>\n",
       "      <td>50900.000000</td>\n",
       "      <td>50366.666667</td>\n",
       "      <td>49766.666667</td>\n",
       "      <td>49700.000000</td>\n",
       "      <td>50500.000000</td>\n",
       "      <td>51433.333333</td>\n",
       "      <td>53500.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>91733.333333</td>\n",
       "      <td>97833.333333</td>\n",
       "      <td>97433.333333</td>\n",
       "      <td>95300.000000</td>\n",
       "      <td>92933.333333</td>\n",
       "      <td>89700.000000</td>\n",
       "      <td>92100.000000</td>\n",
       "      <td>92766.666667</td>\n",
       "      <td>91433.333333</td>\n",
       "      <td>97600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vienna</th>\n",
       "      <td>72266.666667</td>\n",
       "      <td>74533.333333</td>\n",
       "      <td>75333.333333</td>\n",
       "      <td>76533.333333</td>\n",
       "      <td>77400.000000</td>\n",
       "      <td>77366.666667</td>\n",
       "      <td>77966.666667</td>\n",
       "      <td>78900.000000</td>\n",
       "      <td>78233.333333</td>\n",
       "      <td>78933.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>101700.000000</td>\n",
       "      <td>103700.000000</td>\n",
       "      <td>104133.333333</td>\n",
       "      <td>102133.333333</td>\n",
       "      <td>103800.000000</td>\n",
       "      <td>105733.333333</td>\n",
       "      <td>106400.000000</td>\n",
       "      <td>106433.333333</td>\n",
       "      <td>108766.666667</td>\n",
       "      <td>110800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>83900.000000</td>\n",
       "      <td>86033.333333</td>\n",
       "      <td>88333.333333</td>\n",
       "      <td>90466.666667</td>\n",
       "      <td>93500.000000</td>\n",
       "      <td>94933.333333</td>\n",
       "      <td>93166.666667</td>\n",
       "      <td>90933.333333</td>\n",
       "      <td>91266.666667</td>\n",
       "      <td>91000.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>126333.333333</td>\n",
       "      <td>130433.333333</td>\n",
       "      <td>134100.000000</td>\n",
       "      <td>133366.666667</td>\n",
       "      <td>131766.666667</td>\n",
       "      <td>130600.000000</td>\n",
       "      <td>129733.333333</td>\n",
       "      <td>131333.333333</td>\n",
       "      <td>133066.666667</td>\n",
       "      <td>135500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Waverly</th>\n",
       "      <td>62366.666667</td>\n",
       "      <td>62933.333333</td>\n",
       "      <td>65300.000000</td>\n",
       "      <td>66600.000000</td>\n",
       "      <td>67933.333333</td>\n",
       "      <td>69366.666667</td>\n",
       "      <td>68566.666667</td>\n",
       "      <td>68166.666667</td>\n",
       "      <td>67366.666667</td>\n",
       "      <td>67200.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>99933.333333</td>\n",
       "      <td>100400.000000</td>\n",
       "      <td>101433.333333</td>\n",
       "      <td>99233.333333</td>\n",
       "      <td>99566.666667</td>\n",
       "      <td>99733.333333</td>\n",
       "      <td>99900.000000</td>\n",
       "      <td>99766.666667</td>\n",
       "      <td>101000.000000</td>\n",
       "      <td>103000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Williamstown</th>\n",
       "      <td>82933.333333</td>\n",
       "      <td>85200.000000</td>\n",
       "      <td>86466.666667</td>\n",
       "      <td>87000.000000</td>\n",
       "      <td>86633.333333</td>\n",
       "      <td>86166.666667</td>\n",
       "      <td>85300.000000</td>\n",
       "      <td>84400.000000</td>\n",
       "      <td>84133.333333</td>\n",
       "      <td>84833.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>122533.333333</td>\n",
       "      <td>125033.333333</td>\n",
       "      <td>125866.666667</td>\n",
       "      <td>124766.666667</td>\n",
       "      <td>127566.666667</td>\n",
       "      <td>130033.333333</td>\n",
       "      <td>129466.666667</td>\n",
       "      <td>129333.333333</td>\n",
       "      <td>129666.666667</td>\n",
       "      <td>130600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">Wyoming</th>\n",
       "      <th>Bar Nunn</th>\n",
       "      <td>93033.333333</td>\n",
       "      <td>89666.666667</td>\n",
       "      <td>88900.000000</td>\n",
       "      <td>93500.000000</td>\n",
       "      <td>98833.333333</td>\n",
       "      <td>99900.000000</td>\n",
       "      <td>99100.000000</td>\n",
       "      <td>98333.333333</td>\n",
       "      <td>98633.333333</td>\n",
       "      <td>100866.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>199233.333333</td>\n",
       "      <td>200933.333333</td>\n",
       "      <td>201133.333333</td>\n",
       "      <td>206666.666667</td>\n",
       "      <td>208866.666667</td>\n",
       "      <td>211800.000000</td>\n",
       "      <td>211800.000000</td>\n",
       "      <td>210200.000000</td>\n",
       "      <td>208833.333333</td>\n",
       "      <td>207450.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burns</th>\n",
       "      <td>101533.333333</td>\n",
       "      <td>104566.666667</td>\n",
       "      <td>108366.666667</td>\n",
       "      <td>113000.000000</td>\n",
       "      <td>115833.333333</td>\n",
       "      <td>117200.000000</td>\n",
       "      <td>117800.000000</td>\n",
       "      <td>117633.333333</td>\n",
       "      <td>117333.333333</td>\n",
       "      <td>117233.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>168866.666667</td>\n",
       "      <td>161933.333333</td>\n",
       "      <td>160433.333333</td>\n",
       "      <td>162600.000000</td>\n",
       "      <td>163066.666667</td>\n",
       "      <td>164600.000000</td>\n",
       "      <td>164300.000000</td>\n",
       "      <td>168266.666667</td>\n",
       "      <td>171600.000000</td>\n",
       "      <td>170500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Casper</th>\n",
       "      <td>89233.333333</td>\n",
       "      <td>89600.000000</td>\n",
       "      <td>89733.333333</td>\n",
       "      <td>93166.666667</td>\n",
       "      <td>95500.000000</td>\n",
       "      <td>97633.333333</td>\n",
       "      <td>99433.333333</td>\n",
       "      <td>100633.333333</td>\n",
       "      <td>101733.333333</td>\n",
       "      <td>101533.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>175766.666667</td>\n",
       "      <td>177300.000000</td>\n",
       "      <td>181000.000000</td>\n",
       "      <td>182066.666667</td>\n",
       "      <td>182633.333333</td>\n",
       "      <td>183300.000000</td>\n",
       "      <td>182700.000000</td>\n",
       "      <td>184333.333333</td>\n",
       "      <td>185166.666667</td>\n",
       "      <td>184350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cheyenne</th>\n",
       "      <td>116866.666667</td>\n",
       "      <td>120033.333333</td>\n",
       "      <td>121533.333333</td>\n",
       "      <td>123633.333333</td>\n",
       "      <td>125533.333333</td>\n",
       "      <td>126300.000000</td>\n",
       "      <td>126466.666667</td>\n",
       "      <td>128133.333333</td>\n",
       "      <td>128466.666667</td>\n",
       "      <td>129633.333333</td>\n",
       "      <td>...</td>\n",
       "      <td>177466.666667</td>\n",
       "      <td>176733.333333</td>\n",
       "      <td>178766.666667</td>\n",
       "      <td>181700.000000</td>\n",
       "      <td>183266.666667</td>\n",
       "      <td>186766.666667</td>\n",
       "      <td>190666.666667</td>\n",
       "      <td>194433.333333</td>\n",
       "      <td>196500.000000</td>\n",
       "      <td>199100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Evansville</th>\n",
       "      <td>128033.333333</td>\n",
       "      <td>128766.666667</td>\n",
       "      <td>130833.333333</td>\n",
       "      <td>132066.666667</td>\n",
       "      <td>130566.666667</td>\n",
       "      <td>131433.333333</td>\n",
       "      <td>132400.000000</td>\n",
       "      <td>133466.666667</td>\n",
       "      <td>133300.000000</td>\n",
       "      <td>131066.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>296733.333333</td>\n",
       "      <td>305666.666667</td>\n",
       "      <td>309500.000000</td>\n",
       "      <td>307300.000000</td>\n",
       "      <td>303166.666667</td>\n",
       "      <td>300966.666667</td>\n",
       "      <td>304200.000000</td>\n",
       "      <td>309433.333333</td>\n",
       "      <td>309200.000000</td>\n",
       "      <td>309050.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pine Bluffs</th>\n",
       "      <td>93733.333333</td>\n",
       "      <td>95066.666667</td>\n",
       "      <td>94633.333333</td>\n",
       "      <td>98066.666667</td>\n",
       "      <td>103233.333333</td>\n",
       "      <td>104600.000000</td>\n",
       "      <td>106500.000000</td>\n",
       "      <td>104066.666667</td>\n",
       "      <td>102233.333333</td>\n",
       "      <td>103566.666667</td>\n",
       "      <td>...</td>\n",
       "      <td>148666.666667</td>\n",
       "      <td>154366.666667</td>\n",
       "      <td>158100.000000</td>\n",
       "      <td>163900.000000</td>\n",
       "      <td>167433.333333</td>\n",
       "      <td>167466.666667</td>\n",
       "      <td>169200.000000</td>\n",
       "      <td>166833.333333</td>\n",
       "      <td>163800.000000</td>\n",
       "      <td>157650.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10730 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                       2000q1         2000q2         2000q3  \\\n",
       "State         RegionName                                                      \n",
       "Alaska        Anchor Point                NaN            NaN            NaN   \n",
       "              Anchorage         174633.333333  175266.666667  179566.666667   \n",
       "              Fairbanks         163200.000000  165033.333333  169300.000000   \n",
       "              Homer                       NaN            NaN            NaN   \n",
       "              Juneau            192466.666667  194300.000000  195166.666667   \n",
       "              Kenai                       NaN            NaN            NaN   \n",
       "              Ketchikan                   NaN            NaN            NaN   \n",
       "              Kodiak                      NaN            NaN            NaN   \n",
       "              Lakes             172733.333333  174133.333333  177266.666667   \n",
       "              North Pole        157466.666667  159100.000000  162133.333333   \n",
       "              Palmer            168766.666667  170566.666667  174233.333333   \n",
       "              Seward                      NaN            NaN            NaN   \n",
       "              Soldotna                    NaN            NaN            NaN   \n",
       "              Tanaina           160500.000000  163500.000000  166366.666667   \n",
       "Alabama       Adamsville         69033.333333   69166.666667   69800.000000   \n",
       "              Alabaster         122133.333333  123066.666667  123166.666667   \n",
       "              Albertville        73966.666667   72600.000000   72833.333333   \n",
       "              Arab               83766.666667   81566.666667   81333.333333   \n",
       "              Ardmore                     NaN            NaN            NaN   \n",
       "              Axis                        NaN            NaN            NaN   \n",
       "              Baileyton                   NaN            NaN            NaN   \n",
       "              Bay Minette        81700.000000   78533.333333   79133.333333   \n",
       "              Bayou La Batre     44066.666667   44500.000000   44266.666667   \n",
       "              Bessemer                    NaN            NaN            NaN   \n",
       "              Birmingham         54033.333333   54400.000000   54966.666667   \n",
       "              Boaz               70866.666667   70266.666667   70300.000000   \n",
       "              Brent              92933.333333   94333.333333   96166.666667   \n",
       "              Brighton                    NaN            NaN            NaN   \n",
       "              Brookwood          92566.666667   95100.000000   98866.666667   \n",
       "              Buhl               90800.000000   94600.000000   96500.000000   \n",
       "...                                       ...            ...            ...   \n",
       "Wisconsin     Yorkville         139066.666667  134900.000000  135033.333333   \n",
       "West Virginia Belle              51066.666667   51300.000000   52200.000000   \n",
       "              Charleston         59533.333333   59366.666667   59366.666667   \n",
       "              Chesapeake                  NaN            NaN            NaN   \n",
       "              Clendenin          39966.666667   38200.000000   40500.000000   \n",
       "              Coal Fork                   NaN            NaN            NaN   \n",
       "              Cross Lanes        78133.333333   78066.666667   79233.333333   \n",
       "              Davisville                  NaN            NaN            NaN   \n",
       "              Dunbar                      NaN            NaN            NaN   \n",
       "              East Bank                   NaN            NaN            NaN   \n",
       "              Elkview                     NaN            NaN            NaN   \n",
       "              Eskdale                     NaN            NaN            NaN   \n",
       "              Marmet                      NaN            NaN            NaN   \n",
       "              Mineral Wells      75533.333333   77233.333333   81966.666667   \n",
       "              Nitro                       NaN            NaN            NaN   \n",
       "              Parkersburg        54900.000000   55833.333333   56633.333333   \n",
       "              Saint Albans       63833.333333   64700.000000   65200.000000   \n",
       "              Sissonville        57200.000000   58200.000000   61200.000000   \n",
       "              South Charleston            NaN            NaN            NaN   \n",
       "              Upper Falls        53033.333333   52333.333333   52100.000000   \n",
       "              Vienna             72266.666667   74533.333333   75333.333333   \n",
       "              Washington         83900.000000   86033.333333   88333.333333   \n",
       "              Waverly            62366.666667   62933.333333   65300.000000   \n",
       "              Williamstown       82933.333333   85200.000000   86466.666667   \n",
       "Wyoming       Bar Nunn           93033.333333   89666.666667   88900.000000   \n",
       "              Burns             101533.333333  104566.666667  108366.666667   \n",
       "              Casper             89233.333333   89600.000000   89733.333333   \n",
       "              Cheyenne          116866.666667  120033.333333  121533.333333   \n",
       "              Evansville        128033.333333  128766.666667  130833.333333   \n",
       "              Pine Bluffs        93733.333333   95066.666667   94633.333333   \n",
       "\n",
       "                                       2000q4         2001q1         2001q2  \\\n",
       "State         RegionName                                                      \n",
       "Alaska        Anchor Point                NaN            NaN            NaN   \n",
       "              Anchorage         182833.333333  182766.666667  183933.333333   \n",
       "              Fairbanks         172800.000000  164433.333333  157800.000000   \n",
       "              Homer                       NaN            NaN            NaN   \n",
       "              Juneau            194166.666667  197166.666667  199533.333333   \n",
       "              Kenai                       NaN            NaN            NaN   \n",
       "              Ketchikan                   NaN            NaN            NaN   \n",
       "              Kodiak                      NaN            NaN            NaN   \n",
       "              Lakes             179133.333333  172400.000000  166000.000000   \n",
       "              North Pole        165500.000000  159433.333333  149766.666667   \n",
       "              Palmer            175533.333333  169466.666667  163233.333333   \n",
       "              Seward                      NaN            NaN            NaN   \n",
       "              Soldotna                    NaN            NaN            NaN   \n",
       "              Tanaina           168033.333333  158766.666667  149200.000000   \n",
       "Alabama       Adamsville         71966.666667   73466.666667   74000.000000   \n",
       "              Alabaster         123700.000000  123233.333333  125133.333333   \n",
       "              Albertville        74200.000000   75900.000000   76000.000000   \n",
       "              Arab               82966.666667   84200.000000   84533.333333   \n",
       "              Ardmore                     NaN            NaN            NaN   \n",
       "              Axis                        NaN            NaN            NaN   \n",
       "              Baileyton                   NaN            NaN            NaN   \n",
       "              Bay Minette        81300.000000   85700.000000   87266.666667   \n",
       "              Bayou La Batre     43666.666667   42500.000000   43333.333333   \n",
       "              Bessemer                    NaN            NaN            NaN   \n",
       "              Birmingham         56066.666667   56833.333333   57600.000000   \n",
       "              Boaz               71466.666667   72833.333333   71900.000000   \n",
       "              Brent              98333.333333   96533.333333   98500.000000   \n",
       "              Brighton                    NaN            NaN            NaN   \n",
       "              Brookwood          99966.666667  101666.666667  103666.666667   \n",
       "              Buhl               96566.666667   99266.666667  101966.666667   \n",
       "...                                       ...            ...            ...   \n",
       "Wisconsin     Yorkville         140300.000000  148800.000000  155233.333333   \n",
       "West Virginia Belle              51166.666667   51266.666667   51966.666667   \n",
       "              Charleston         59633.333333   60400.000000   59866.666667   \n",
       "              Chesapeake                  NaN            NaN            NaN   \n",
       "              Clendenin          39000.000000   42700.000000   42233.333333   \n",
       "              Coal Fork                   NaN            NaN            NaN   \n",
       "              Cross Lanes        79466.666667   78800.000000   79366.666667   \n",
       "              Davisville                  NaN            NaN            NaN   \n",
       "              Dunbar                      NaN            NaN            NaN   \n",
       "              East Bank                   NaN            NaN            NaN   \n",
       "              Elkview                     NaN            NaN            NaN   \n",
       "              Eskdale                     NaN            NaN            NaN   \n",
       "              Marmet                      NaN            NaN            NaN   \n",
       "              Mineral Wells      85300.000000   86700.000000   87133.333333   \n",
       "              Nitro                       NaN            NaN            NaN   \n",
       "              Parkersburg        56833.333333   57400.000000   57566.666667   \n",
       "              Saint Albans       65900.000000   66366.666667   66466.666667   \n",
       "              Sissonville        60700.000000   59000.000000   57133.333333   \n",
       "              South Charleston            NaN            NaN            NaN   \n",
       "              Upper Falls        50900.000000   50366.666667   49766.666667   \n",
       "              Vienna             76533.333333   77400.000000   77366.666667   \n",
       "              Washington         90466.666667   93500.000000   94933.333333   \n",
       "              Waverly            66600.000000   67933.333333   69366.666667   \n",
       "              Williamstown       87000.000000   86633.333333   86166.666667   \n",
       "Wyoming       Bar Nunn           93500.000000   98833.333333   99900.000000   \n",
       "              Burns             113000.000000  115833.333333  117200.000000   \n",
       "              Casper             93166.666667   95500.000000   97633.333333   \n",
       "              Cheyenne          123633.333333  125533.333333  126300.000000   \n",
       "              Evansville        132066.666667  130566.666667  131433.333333   \n",
       "              Pine Bluffs        98066.666667  103233.333333  104600.000000   \n",
       "\n",
       "                                       2001q3         2001q4         2002q1  \\\n",
       "State         RegionName                                                      \n",
       "Alaska        Anchor Point                NaN            NaN            NaN   \n",
       "              Anchorage         188566.666667  191866.666667  193966.666667   \n",
       "              Fairbanks         158200.000000  154666.666667  152766.666667   \n",
       "              Homer                       NaN            NaN            NaN   \n",
       "              Juneau            202433.333333  206300.000000  209066.666667   \n",
       "              Kenai                       NaN            NaN            NaN   \n",
       "              Ketchikan                   NaN            NaN            NaN   \n",
       "              Kodiak                      NaN            NaN            NaN   \n",
       "              Lakes             169500.000000  170766.666667  168766.666667   \n",
       "              North Pole        151266.666667  151000.000000  150033.333333   \n",
       "              Palmer            166933.333333  168933.333333  165300.000000   \n",
       "              Seward                      NaN            NaN            NaN   \n",
       "              Soldotna                    NaN            NaN            NaN   \n",
       "              Tanaina           150966.666667  151600.000000  153033.333333   \n",
       "Alabama       Adamsville         73333.333333   73100.000000   73333.333333   \n",
       "              Alabaster         127766.666667  127200.000000  127300.000000   \n",
       "              Albertville        72066.666667   73566.666667   76533.333333   \n",
       "              Arab               81666.666667   83900.000000   87266.666667   \n",
       "              Ardmore                     NaN            NaN            NaN   \n",
       "              Axis                        NaN            NaN            NaN   \n",
       "              Baileyton                   NaN            NaN            NaN   \n",
       "              Bay Minette        85900.000000   85000.000000   84066.666667   \n",
       "              Bayou La Batre     45433.333333   45400.000000   45400.000000   \n",
       "              Bessemer                    NaN            NaN            NaN   \n",
       "              Birmingham         58433.333333   58700.000000   59500.000000   \n",
       "              Boaz               68733.333333   69833.333333   72766.666667   \n",
       "              Brent              99366.666667  104100.000000  103800.000000   \n",
       "              Brighton                    NaN            NaN            NaN   \n",
       "              Brookwood         101833.333333   99900.000000   99633.333333   \n",
       "              Buhl              102000.000000  102733.333333  102533.333333   \n",
       "...                                       ...            ...            ...   \n",
       "Wisconsin     Yorkville         161133.333333  162800.000000  164866.666667   \n",
       "West Virginia Belle              50166.666667   49333.333333   48666.666667   \n",
       "              Charleston         61000.000000   60766.666667   59000.000000   \n",
       "              Chesapeake         40550.000000   40433.333333   39633.333333   \n",
       "              Clendenin          41700.000000   43800.000000   43433.333333   \n",
       "              Coal Fork          43350.000000   43200.000000   43466.666667   \n",
       "              Cross Lanes        78100.000000   78766.666667   78733.333333   \n",
       "              Davisville                  NaN            NaN            NaN   \n",
       "              Dunbar                      NaN            NaN            NaN   \n",
       "              East Bank          39750.000000   41366.666667   43233.333333   \n",
       "              Elkview                     NaN            NaN            NaN   \n",
       "              Eskdale                     NaN            NaN            NaN   \n",
       "              Marmet             47800.000000   46800.000000   46533.333333   \n",
       "              Mineral Wells      83666.666667   81500.000000   82833.333333   \n",
       "              Nitro                       NaN            NaN            NaN   \n",
       "              Parkersburg        57933.333333   58866.666667   59500.000000   \n",
       "              Saint Albans       67266.666667   66100.000000   64600.000000   \n",
       "              Sissonville        53566.666667   53833.333333   53400.000000   \n",
       "              South Charleston            NaN            NaN            NaN   \n",
       "              Upper Falls        49700.000000   50500.000000   51433.333333   \n",
       "              Vienna             77966.666667   78900.000000   78233.333333   \n",
       "              Washington         93166.666667   90933.333333   91266.666667   \n",
       "              Waverly            68566.666667   68166.666667   67366.666667   \n",
       "              Williamstown       85300.000000   84400.000000   84133.333333   \n",
       "Wyoming       Bar Nunn           99100.000000   98333.333333   98633.333333   \n",
       "              Burns             117800.000000  117633.333333  117333.333333   \n",
       "              Casper             99433.333333  100633.333333  101733.333333   \n",
       "              Cheyenne          126466.666667  128133.333333  128466.666667   \n",
       "              Evansville        132400.000000  133466.666667  133300.000000   \n",
       "              Pine Bluffs       106500.000000  104066.666667  102233.333333   \n",
       "\n",
       "                                       2002q2    ...            2014q2  \\\n",
       "State         RegionName                         ...                     \n",
       "Alaska        Anchor Point                NaN    ...     157800.000000   \n",
       "              Anchorage         196700.000000    ...     278200.000000   \n",
       "              Fairbanks         154533.333333    ...     209233.333333   \n",
       "              Homer                       NaN    ...     233033.333333   \n",
       "              Juneau            209866.666667    ...     328266.666667   \n",
       "              Kenai                       NaN    ...     199466.666667   \n",
       "              Ketchikan                   NaN    ...     196866.666667   \n",
       "              Kodiak                      NaN    ...     256400.000000   \n",
       "              Lakes             169900.000000    ...     228200.000000   \n",
       "              North Pole        151866.666667    ...     199933.333333   \n",
       "              Palmer            164800.000000    ...     225566.666667   \n",
       "              Seward                      NaN    ...     194600.000000   \n",
       "              Soldotna                    NaN    ...     210366.666667   \n",
       "              Tanaina           156100.000000    ...     208900.000000   \n",
       "Alabama       Adamsville         73133.333333    ...      77066.666667   \n",
       "              Alabaster         128000.000000    ...     147133.333333   \n",
       "              Albertville        76366.666667    ...      84033.333333   \n",
       "              Arab               87700.000000    ...     113366.666667   \n",
       "              Ardmore                     NaN    ...     140533.333333   \n",
       "              Axis                        NaN    ...     111066.666667   \n",
       "              Baileyton                   NaN    ...      87666.666667   \n",
       "              Bay Minette        84566.666667    ...     113333.333333   \n",
       "              Bayou La Batre     45566.666667    ...      49800.000000   \n",
       "              Bessemer                    NaN    ...      54600.000000   \n",
       "              Birmingham         59866.666667    ...      61733.333333   \n",
       "              Boaz               72100.000000    ...      80933.333333   \n",
       "              Brent             102533.333333    ...      93866.666667   \n",
       "              Brighton                    NaN    ...      45366.666667   \n",
       "              Brookwood         100366.666667    ...     106633.333333   \n",
       "              Buhl              100100.000000    ...     119233.333333   \n",
       "...                                       ...    ...               ...   \n",
       "Wisconsin     Yorkville         172466.666667    ...     231500.000000   \n",
       "West Virginia Belle              49633.333333    ...      72900.000000   \n",
       "              Charleston         58333.333333    ...      95433.333333   \n",
       "              Chesapeake         38633.333333    ...      66400.000000   \n",
       "              Clendenin          43833.333333    ...      82233.333333   \n",
       "              Coal Fork          43666.666667    ...      65933.333333   \n",
       "              Cross Lanes        79100.000000    ...     123566.666667   \n",
       "              Davisville                  NaN    ...      65766.666667   \n",
       "              Dunbar                      NaN    ...      76566.666667   \n",
       "              East Bank          43333.333333    ...      69366.666667   \n",
       "              Elkview                     NaN    ...      97433.333333   \n",
       "              Eskdale                     NaN    ...      69366.666667   \n",
       "              Marmet             46000.000000    ...      68366.666667   \n",
       "              Mineral Wells      85033.333333    ...     116466.666667   \n",
       "              Nitro                       NaN    ...      87366.666667   \n",
       "              Parkersburg        59366.666667    ...      79333.333333   \n",
       "              Saint Albans       63866.666667    ...      91133.333333   \n",
       "              Sissonville        55633.333333    ...      97633.333333   \n",
       "              South Charleston            NaN    ...     102266.666667   \n",
       "              Upper Falls        53500.000000    ...      91733.333333   \n",
       "              Vienna             78933.333333    ...     101700.000000   \n",
       "              Washington         91000.000000    ...     126333.333333   \n",
       "              Waverly            67200.000000    ...      99933.333333   \n",
       "              Williamstown       84833.333333    ...     122533.333333   \n",
       "Wyoming       Bar Nunn          100866.666667    ...     199233.333333   \n",
       "              Burns             117233.333333    ...     168866.666667   \n",
       "              Casper            101533.333333    ...     175766.666667   \n",
       "              Cheyenne          129633.333333    ...     177466.666667   \n",
       "              Evansville        131066.666667    ...     296733.333333   \n",
       "              Pine Bluffs       103566.666667    ...     148666.666667   \n",
       "\n",
       "                                       2014q3         2014q4         2015q1  \\\n",
       "State         RegionName                                                      \n",
       "Alaska        Anchor Point      158000.000000  155566.666667  154266.666667   \n",
       "              Anchorage         280766.666667  281700.000000  284166.666667   \n",
       "              Fairbanks         207100.000000  207000.000000  207766.666667   \n",
       "              Homer             232900.000000  231066.666667  233500.000000   \n",
       "              Juneau            331833.333333  333200.000000  335666.666667   \n",
       "              Kenai             197966.666667  194600.000000  198500.000000   \n",
       "              Ketchikan         197100.000000  197700.000000  198033.333333   \n",
       "              Kodiak            256966.666667  257933.333333  258566.666667   \n",
       "              Lakes             233966.666667  236966.666667  239833.333333   \n",
       "              North Pole        199400.000000  197366.666667  199066.666667   \n",
       "              Palmer            228766.666667  229366.666667  234466.666667   \n",
       "              Seward            190533.333333  186600.000000  186800.000000   \n",
       "              Soldotna          209300.000000  207966.666667  213500.000000   \n",
       "              Tanaina           211000.000000  212466.666667  215200.000000   \n",
       "Alabama       Adamsville         75966.666667   71900.000000   71666.666667   \n",
       "              Alabaster         147633.333333  148700.000000  148900.000000   \n",
       "              Albertville        84766.666667   86800.000000   88466.666667   \n",
       "              Arab              111700.000000  111600.000000  110166.666667   \n",
       "              Ardmore           139566.666667  140900.000000  143233.333333   \n",
       "              Axis              111833.333333  111800.000000  109533.333333   \n",
       "              Baileyton          90033.333333   94100.000000   94600.000000   \n",
       "              Bay Minette       110600.000000  109900.000000  111100.000000   \n",
       "              Bayou La Batre     51000.000000   51766.666667   50733.333333   \n",
       "              Bessemer           55333.333333   54733.333333   55200.000000   \n",
       "              Birmingham         60900.000000   59533.333333   59900.000000   \n",
       "              Boaz               81866.666667   82866.666667   83966.666667   \n",
       "              Brent              97100.000000  100100.000000  102433.333333   \n",
       "              Brighton           45133.333333   43766.666667   42500.000000   \n",
       "              Brookwood         110233.333333  114366.666667  117700.000000   \n",
       "              Buhl              132033.333333  138400.000000  141766.666667   \n",
       "...                                       ...            ...            ...   \n",
       "Wisconsin     Yorkville         238133.333333  237766.666667  239133.333333   \n",
       "West Virginia Belle              74066.666667   73133.333333   71966.666667   \n",
       "              Charleston         99733.333333  102466.666667  102900.000000   \n",
       "              Chesapeake         65633.333333   65166.666667   64833.333333   \n",
       "              Clendenin          82900.000000   83533.333333   81900.000000   \n",
       "              Coal Fork          68133.333333   69366.666667   69700.000000   \n",
       "              Cross Lanes       124633.333333  126233.333333  126633.333333   \n",
       "              Davisville         66200.000000   65466.666667   64933.333333   \n",
       "              Dunbar             78866.666667   79100.000000   77833.333333   \n",
       "              East Bank          70666.666667   71333.333333   69866.666667   \n",
       "              Elkview           101066.666667  102633.333333  102133.333333   \n",
       "              Eskdale            69866.666667   70166.666667   68166.666667   \n",
       "              Marmet             68333.333333   69400.000000   68966.666667   \n",
       "              Mineral Wells     119000.000000  120433.333333  117933.333333   \n",
       "              Nitro              88633.333333   89400.000000   89900.000000   \n",
       "              Parkersburg        79500.000000   78933.333333   78233.333333   \n",
       "              Saint Albans       93333.333333   94900.000000   96333.333333   \n",
       "              Sissonville       103766.666667  106600.000000  103966.666667   \n",
       "              South Charleston  103933.333333  104966.666667  104933.333333   \n",
       "              Upper Falls        97833.333333   97433.333333   95300.000000   \n",
       "              Vienna            103700.000000  104133.333333  102133.333333   \n",
       "              Washington        130433.333333  134100.000000  133366.666667   \n",
       "              Waverly           100400.000000  101433.333333   99233.333333   \n",
       "              Williamstown      125033.333333  125866.666667  124766.666667   \n",
       "Wyoming       Bar Nunn          200933.333333  201133.333333  206666.666667   \n",
       "              Burns             161933.333333  160433.333333  162600.000000   \n",
       "              Casper            177300.000000  181000.000000  182066.666667   \n",
       "              Cheyenne          176733.333333  178766.666667  181700.000000   \n",
       "              Evansville        305666.666667  309500.000000  307300.000000   \n",
       "              Pine Bluffs       154366.666667  158100.000000  163900.000000   \n",
       "\n",
       "                                       2015q2         2015q3         2015q4  \\\n",
       "State         RegionName                                                      \n",
       "Alaska        Anchor Point      154100.000000  153966.666667  154766.666667   \n",
       "              Anchorage         287166.666667  290233.333333  291700.000000   \n",
       "              Fairbanks         206466.666667  208433.333333  209466.666667   \n",
       "              Homer             238100.000000  238933.333333  240500.000000   \n",
       "              Juneau            337366.666667  325933.333333  319333.333333   \n",
       "              Kenai             202700.000000  204766.666667  206433.333333   \n",
       "              Ketchikan         196300.000000  196533.333333  196633.333333   \n",
       "              Kodiak            256133.333333  256400.000000  256800.000000   \n",
       "              Lakes             240033.333333  242733.333333  244500.000000   \n",
       "              North Pole        200300.000000  204100.000000  206400.000000   \n",
       "              Palmer            237800.000000  239900.000000  241666.666667   \n",
       "              Seward            185533.333333  186433.333333  191000.000000   \n",
       "              Soldotna          217233.333333  220433.333333  219866.666667   \n",
       "              Tanaina           215633.333333  217700.000000  218800.000000   \n",
       "Alabama       Adamsville         73033.333333   73933.333333   73866.666667   \n",
       "              Alabaster         149566.666667  150366.666667  151733.333333   \n",
       "              Albertville        89500.000000   90233.333333   91366.666667   \n",
       "              Arab              109433.333333  110900.000000  112233.333333   \n",
       "              Ardmore           143000.000000  144600.000000  143966.666667   \n",
       "              Axis              109666.666667  110033.333333  109600.000000   \n",
       "              Baileyton          95666.666667   96833.333333   97233.333333   \n",
       "              Bay Minette       114300.000000  118533.333333  121433.333333   \n",
       "              Bayou La Batre     50500.000000   50133.333333   48933.333333   \n",
       "              Bessemer           57200.000000   58633.333333   59433.333333   \n",
       "              Birmingham         61966.666667   62666.666667   63100.000000   \n",
       "              Boaz               85266.666667   86033.333333   86566.666667   \n",
       "              Brent             101800.000000   97900.000000   95600.000000   \n",
       "              Brighton           44233.333333   46266.666667   45766.666667   \n",
       "              Brookwood         118700.000000  120066.666667  118533.333333   \n",
       "              Buhl              141200.000000  141066.666667  145500.000000   \n",
       "...                                       ...            ...            ...   \n",
       "Wisconsin     Yorkville         243066.666667  243066.666667  244800.000000   \n",
       "West Virginia Belle              73566.666667   74233.333333   74600.000000   \n",
       "              Charleston        103233.333333  102133.333333  102466.666667   \n",
       "              Chesapeake         66033.333333   67133.333333   66433.333333   \n",
       "              Clendenin          80933.333333   79833.333333   81800.000000   \n",
       "              Coal Fork          69933.333333   69933.333333   70466.666667   \n",
       "              Cross Lanes       126833.333333  126466.666667  126666.666667   \n",
       "              Davisville         64766.666667   62900.000000   63266.666667   \n",
       "              Dunbar             77433.333333   77333.333333   77100.000000   \n",
       "              East Bank          69366.666667   67500.000000   65933.333333   \n",
       "              Elkview           102333.333333  100866.666667  101700.000000   \n",
       "              Eskdale            68066.666667   66266.666667   65233.333333   \n",
       "              Marmet             67533.333333   67833.333333   68733.333333   \n",
       "              Mineral Wells     118866.666667  120100.000000  120266.666667   \n",
       "              Nitro              88833.333333   88000.000000   88900.000000   \n",
       "              Parkersburg        79066.666667   79600.000000   80666.666667   \n",
       "              Saint Albans       95800.000000   95833.333333   97600.000000   \n",
       "              Sissonville        99800.000000  100266.666667  102033.333333   \n",
       "              South Charleston  105333.333333  105600.000000  106066.666667   \n",
       "              Upper Falls        92933.333333   89700.000000   92100.000000   \n",
       "              Vienna            103800.000000  105733.333333  106400.000000   \n",
       "              Washington        131766.666667  130600.000000  129733.333333   \n",
       "              Waverly            99566.666667   99733.333333   99900.000000   \n",
       "              Williamstown      127566.666667  130033.333333  129466.666667   \n",
       "Wyoming       Bar Nunn          208866.666667  211800.000000  211800.000000   \n",
       "              Burns             163066.666667  164600.000000  164300.000000   \n",
       "              Casper            182633.333333  183300.000000  182700.000000   \n",
       "              Cheyenne          183266.666667  186766.666667  190666.666667   \n",
       "              Evansville        303166.666667  300966.666667  304200.000000   \n",
       "              Pine Bluffs       167433.333333  167466.666667  169200.000000   \n",
       "\n",
       "                                       2016q1         2016q2    2016q3  \n",
       "State         RegionName                                                \n",
       "Alaska        Anchor Point      156800.000000  161533.333333  161200.0  \n",
       "              Anchorage         293700.000000  294833.333333  294600.0  \n",
       "              Fairbanks         209066.666667  212933.333333  215850.0  \n",
       "              Homer             243166.666667  245166.666667  247600.0  \n",
       "              Juneau            318933.333333  319933.333333  319200.0  \n",
       "              Kenai             209633.333333  211666.666667  211950.0  \n",
       "              Ketchikan         195600.000000  205300.000000  206450.0  \n",
       "              Kodiak            255233.333333  270166.666667  271250.0  \n",
       "              Lakes             250100.000000  250266.666667  250550.0  \n",
       "              North Pole        206633.333333  208166.666667  209300.0  \n",
       "              Palmer            246400.000000  245733.333333  244750.0  \n",
       "              Seward            203600.000000  214666.666667  214950.0  \n",
       "              Soldotna          223466.666667  223333.333333  222600.0  \n",
       "              Tanaina           223100.000000  225200.000000  225500.0  \n",
       "Alabama       Adamsville         74166.666667   74933.333333   74700.0  \n",
       "              Alabaster         153466.666667  155100.000000  155850.0  \n",
       "              Albertville        92000.000000   92466.666667   92200.0  \n",
       "              Arab              110033.333333  110100.000000  112000.0  \n",
       "              Ardmore           142566.666667  143233.333333  141950.0  \n",
       "              Axis              110266.666667  112200.000000  112750.0  \n",
       "              Baileyton          96766.666667   98900.000000  102200.0  \n",
       "              Bay Minette       120266.666667  118333.333333  118500.0  \n",
       "              Bayou La Batre     48566.666667   47833.333333   47400.0  \n",
       "              Bessemer           59766.666667   59866.666667   59800.0  \n",
       "              Birmingham         62033.333333   61633.333333   61250.0  \n",
       "              Boaz               85966.666667   87366.666667   88600.0  \n",
       "              Brent              94433.333333   91366.666667   87650.0  \n",
       "              Brighton           45033.333333   44433.333333   44000.0  \n",
       "              Brookwood         115233.333333  111966.666667  108650.0  \n",
       "              Buhl              139800.000000  135566.666667  128350.0  \n",
       "...                                       ...            ...       ...  \n",
       "Wisconsin     Yorkville         248466.666667  255200.000000  265950.0  \n",
       "West Virginia Belle              73266.666667   74066.666667   74550.0  \n",
       "              Charleston        104733.333333  107133.333333  108150.0  \n",
       "              Chesapeake         67800.000000   69000.000000   67850.0  \n",
       "              Clendenin          84033.333333   87500.000000   88100.0  \n",
       "              Coal Fork          70266.666667   72700.000000   73200.0  \n",
       "              Cross Lanes       126333.333333  125433.333333  124000.0  \n",
       "              Davisville         64966.666667   66800.000000   69650.0  \n",
       "              Dunbar             76533.333333   76800.000000   76300.0  \n",
       "              East Bank          66766.666667   67833.333333   69550.0  \n",
       "              Elkview           103666.666667  107533.333333  110200.0  \n",
       "              Eskdale            64666.666667   66500.000000   68350.0  \n",
       "              Marmet             70033.333333   73300.000000   75550.0  \n",
       "              Mineral Wells     121066.666667  122266.666667  122000.0  \n",
       "              Nitro              88000.000000   88800.000000   90250.0  \n",
       "              Parkersburg        80100.000000   80066.666667   81500.0  \n",
       "              Saint Albans       99100.000000  100666.666667  100900.0  \n",
       "              Sissonville       104766.666667  107633.333333  109850.0  \n",
       "              South Charleston  107233.333333  111666.666667  112950.0  \n",
       "              Upper Falls        92766.666667   91433.333333   97600.0  \n",
       "              Vienna            106433.333333  108766.666667  110800.0  \n",
       "              Washington        131333.333333  133066.666667  135500.0  \n",
       "              Waverly            99766.666667  101000.000000  103000.0  \n",
       "              Williamstown      129333.333333  129666.666667  130600.0  \n",
       "Wyoming       Bar Nunn          210200.000000  208833.333333  207450.0  \n",
       "              Burns             168266.666667  171600.000000  170500.0  \n",
       "              Casper            184333.333333  185166.666667  184350.0  \n",
       "              Cheyenne          194433.333333  196500.000000  199100.0  \n",
       "              Evansville        309433.333333  309200.000000  309050.0  \n",
       "              Pine Bluffs       166833.333333  163800.000000  157650.0  \n",
       "\n",
       "[10730 rows x 67 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_housing_data():    \n",
    "    # read the data to a table \n",
    "    housing_data = pd.read_csv('City_Zhvi_AllHomes.csv', index_col=['State', 'RegionName']).sort_index()\n",
    "    \n",
    "    # reset the index\n",
    "    housing_data = housing_data.reset_index()\n",
    "    \n",
    "    # convert the state acronyms to state names\n",
    "    housing_data['State'] = housing_data['State'].map(states)\n",
    "    \n",
    "    # redefine the index\n",
    "    housing_data = housing_data.set_index(['State', 'RegionName'])\n",
    "    \n",
    "    # drop unnecessary columns\n",
    "    housing_data = housing_data.drop(housing_data.columns[0:49], axis=1)\n",
    "    \n",
    "    # convert the columns to datetime\n",
    "    housing_data.columns = pd.to_datetime(housing_data.columns)\n",
    "    \n",
    "    # resample the dataframe by quarters\n",
    "    housing_data = housing_data.resample('Q', axis=1).mean()\n",
    "    \n",
    "    # change the names of the columns\n",
    "    housing_data.columns = housing_data.columns.to_period('Q').strftime('%Fq%q')\n",
    "    \n",
    "    return housing_data\n",
    "get_housing_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we run the t-test to see if the alternative hypothesis (our hypothesis) is true or false:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(True, 0.008975587540604419, 'university town')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def run_ttest():\n",
    "    # get the list of university towns\n",
    "    university_towns = get_list_of_university_towns().set_index(['State', 'RegionName']).sort_index()\n",
    "    \n",
    "    # get the housing data\n",
    "    housing_data = get_housing_data().loc[:,[get_recession_start(),get_recession_bottom()]]\n",
    "    \n",
    "    # make a new column with the difference in GDP between recession bottom and recession start \n",
    "    housing_data['Percent Difference'] = ((housing_data[get_recession_bottom()] - housing_data[get_recession_start()])/housing_data[get_recession_start()])*100\n",
    "    \n",
    "    # make a dataframe of housing data of university towns\n",
    "    housing_data_university_towns = housing_data[housing_data.index.isin(university_towns.index)]\n",
    "    \n",
    "    # make a dataframe of housing data of non-university towns\n",
    "    housing_data_not_university_towns = housing_data[~housing_data.index.isin(university_towns.index)]\n",
    "    \n",
    "    # get the p value of the t-test\n",
    "    p = list(ttest_ind(housing_data_university_towns['Percent Difference'], housing_data_not_university_towns['Percent Difference'], nan_policy='omit'))[1]\n",
    "    \n",
    "    # find out which group performs  better\n",
    "    better = \"non-university town\" if abs(housing_data_not_university_towns['Percent Difference'].mean()) < abs(housing_data_university_towns['Percent Difference'].mean()) else \"university town\" \n",
    "    \n",
    "    # is the alternative hypothesis true? can we reject the null hypothesis?\n",
    "    different = True if p < 0.01 else False\n",
    "    \n",
    "    return (different,p,better)\n",
    "run_ttest()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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