columbus_air_quality.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location</th>\n",
       "      <th>city</th>\n",
       "      <th>country</th>\n",
       "      <th>utc</th>\n",
       "      <th>local</th>\n",
       "      <th>parameter</th>\n",
       "      <th>value</th>\n",
       "      <th>unit</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>attribution</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12906</th>\n",
       "      <td>Columbus Airport</td>\n",
       "      <td>Columbus</td>\n",
       "      <td>US</td>\n",
       "      <td>2016-03-15T06:00:00.000Z</td>\n",
       "      <td>2016-03-15T01:00:00-05:00</td>\n",
       "      <td>pm25</td>\n",
       "      <td>25.100</td>\n",
       "      <td>µg/m³</td>\n",
       "      <td>32.5214</td>\n",
       "      <td>-84.9436</td>\n",
       "      <td>[{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12907</th>\n",
       "      <td>Columbus Airport</td>\n",
       "      <td>Columbus</td>\n",
       "      <td>US</td>\n",
       "      <td>2016-03-15T05:00:00.000Z</td>\n",
       "      <td>2016-03-15T00:00:00-05:00</td>\n",
       "      <td>pm25</td>\n",
       "      <td>15.600</td>\n",
       "      <td>µg/m³</td>\n",
       "      <td>32.5214</td>\n",
       "      <td>-84.9436</td>\n",
       "      <td>[{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12908</th>\n",
       "      <td>Columbus Airport</td>\n",
       "      <td>Columbus</td>\n",
       "      <td>US</td>\n",
       "      <td>2016-03-15T05:00:00.000Z</td>\n",
       "      <td>2016-03-15T00:00:00-05:00</td>\n",
       "      <td>o3</td>\n",
       "      <td>0.027</td>\n",
       "      <td>ppm</td>\n",
       "      <td>32.5214</td>\n",
       "      <td>-84.9436</td>\n",
       "      <td>[{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12909</th>\n",
       "      <td>Columbus Airport</td>\n",
       "      <td>Columbus</td>\n",
       "      <td>US</td>\n",
       "      <td>2016-03-15T04:00:00.000Z</td>\n",
       "      <td>2016-03-14T23:00:00-05:00</td>\n",
       "      <td>pm25</td>\n",
       "      <td>11.700</td>\n",
       "      <td>µg/m³</td>\n",
       "      <td>32.5214</td>\n",
       "      <td>-84.9436</td>\n",
       "      <td>[{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12910</th>\n",
       "      <td>Columbus Airport</td>\n",
       "      <td>Columbus</td>\n",
       "      <td>US</td>\n",
       "      <td>2016-03-15T04:00:00.000Z</td>\n",
       "      <td>2016-03-14T23:00:00-05:00</td>\n",
       "      <td>o3</td>\n",
       "      <td>0.016</td>\n",
       "      <td>ppm</td>\n",
       "      <td>32.5214</td>\n",
       "      <td>-84.9436</td>\n",
       "      <td>[{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               location      city country                       utc  \\\n",
       "12906  Columbus Airport  Columbus      US  2016-03-15T06:00:00.000Z   \n",
       "12907  Columbus Airport  Columbus      US  2016-03-15T05:00:00.000Z   \n",
       "12908  Columbus Airport  Columbus      US  2016-03-15T05:00:00.000Z   \n",
       "12909  Columbus Airport  Columbus      US  2016-03-15T04:00:00.000Z   \n",
       "12910  Columbus Airport  Columbus      US  2016-03-15T04:00:00.000Z   \n",
       "\n",
       "                           local parameter   value   unit  latitude  \\\n",
       "12906  2016-03-15T01:00:00-05:00      pm25  25.100  µg/m³   32.5214   \n",
       "12907  2016-03-15T00:00:00-05:00      pm25  15.600  µg/m³   32.5214   \n",
       "12908  2016-03-15T00:00:00-05:00        o3   0.027    ppm   32.5214   \n",
       "12909  2016-03-14T23:00:00-05:00      pm25  11.700  µg/m³   32.5214   \n",
       "12910  2016-03-14T23:00:00-05:00        o3   0.016    ppm   32.5214   \n",
       "\n",
       "       longitude                                        attribution  \n",
       "12906   -84.9436  [{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...  \n",
       "12907   -84.9436  [{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...  \n",
       "12908   -84.9436  [{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...  \n",
       "12909   -84.9436  [{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...  \n",
       "12910   -84.9436  [{\"name\":\"US EPA AirNow\",\"url\":\"http://www.air...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aq = pd.read_csv('openaq.csv')\n",
    "aq = pd.DataFrame(aq)\n",
    "aq.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>parameter</th>\n",
       "      <th>o3</th>\n",
       "      <th>pm25</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>local</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-03-14T23:00:00-05:00</th>\n",
       "      <td>0.016</td>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T00:00:00-05:00</th>\n",
       "      <td>0.027</td>\n",
       "      <td>15.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T01:00:00-05:00</th>\n",
       "      <td>0.030</td>\n",
       "      <td>25.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T02:00:00-05:00</th>\n",
       "      <td>0.028</td>\n",
       "      <td>20.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T03:00:00-05:00</th>\n",
       "      <td>0.023</td>\n",
       "      <td>23.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T04:00:00-05:00</th>\n",
       "      <td>0.018</td>\n",
       "      <td>18.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T05:00:00-05:00</th>\n",
       "      <td>0.014</td>\n",
       "      <td>28.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T06:00:00-05:00</th>\n",
       "      <td>0.008</td>\n",
       "      <td>21.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T07:00:00-05:00</th>\n",
       "      <td>0.002</td>\n",
       "      <td>23.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T08:00:00-05:00</th>\n",
       "      <td>0.010</td>\n",
       "      <td>24.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T09:00:00-05:00</th>\n",
       "      <td>0.022</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T10:00:00-05:00</th>\n",
       "      <td>0.030</td>\n",
       "      <td>15.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T11:00:00-05:00</th>\n",
       "      <td>0.041</td>\n",
       "      <td>15.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T12:00:00-05:00</th>\n",
       "      <td>0.050</td>\n",
       "      <td>19.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T13:00:00-05:00</th>\n",
       "      <td>0.052</td>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T14:00:00-05:00</th>\n",
       "      <td>0.050</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T15:00:00-05:00</th>\n",
       "      <td>0.054</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T16:00:00-05:00</th>\n",
       "      <td>0.056</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T17:00:00-05:00</th>\n",
       "      <td>0.053</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T18:00:00-05:00</th>\n",
       "      <td>0.049</td>\n",
       "      <td>11.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T19:00:00-05:00</th>\n",
       "      <td>0.046</td>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T20:00:00-05:00</th>\n",
       "      <td>0.042</td>\n",
       "      <td>11.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T21:00:00-05:00</th>\n",
       "      <td>0.043</td>\n",
       "      <td>12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T22:00:00-05:00</th>\n",
       "      <td>0.039</td>\n",
       "      <td>13.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15T23:00:00-05:00</th>\n",
       "      <td>0.039</td>\n",
       "      <td>12.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-16T00:00:00-05:00</th>\n",
       "      <td>0.037</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-16T01:00:00-05:00</th>\n",
       "      <td>0.034</td>\n",
       "      <td>13.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-16T02:00:00-05:00</th>\n",
       "      <td>0.032</td>\n",
       "      <td>13.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-16T03:00:00-05:00</th>\n",
       "      <td>0.029</td>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-16T04:00:00-05:00</th>\n",
       "      <td>0.026</td>\n",
       "      <td>16.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-10T23:00:00-05:00</th>\n",
       "      <td>0.043</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T00:00:00-05:00</th>\n",
       "      <td>0.041</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T01:00:00-05:00</th>\n",
       "      <td>0.039</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T02:00:00-05:00</th>\n",
       "      <td>0.039</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T03:00:00-05:00</th>\n",
       "      <td>0.038</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T04:00:00-05:00</th>\n",
       "      <td>0.038</td>\n",
       "      <td>0.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T05:00:00-05:00</th>\n",
       "      <td>0.037</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T06:00:00-05:00</th>\n",
       "      <td>0.034</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T07:00:00-05:00</th>\n",
       "      <td>0.033</td>\n",
       "      <td>1.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T08:00:00-05:00</th>\n",
       "      <td>0.036</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T09:00:00-05:00</th>\n",
       "      <td>0.040</td>\n",
       "      <td>0.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T10:00:00-05:00</th>\n",
       "      <td>0.042</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T11:00:00-05:00</th>\n",
       "      <td>0.043</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T12:00:00-05:00</th>\n",
       "      <td>0.047</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T13:00:00-05:00</th>\n",
       "      <td>0.050</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T14:00:00-05:00</th>\n",
       "      <td>0.052</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T15:00:00-05:00</th>\n",
       "      <td>0.053</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T16:00:00-05:00</th>\n",
       "      <td>0.052</td>\n",
       "      <td>1.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T17:00:00-05:00</th>\n",
       "      <td>0.047</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T18:00:00-05:00</th>\n",
       "      <td>0.045</td>\n",
       "      <td>12.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T19:00:00-05:00</th>\n",
       "      <td>0.041</td>\n",
       "      <td>19.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T20:00:00-05:00</th>\n",
       "      <td>0.041</td>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T21:00:00-05:00</th>\n",
       "      <td>0.040</td>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T22:00:00-05:00</th>\n",
       "      <td>0.036</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-11T23:00:00-05:00</th>\n",
       "      <td>0.033</td>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T08:00:00-05:00</th>\n",
       "      <td>0.026</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T09:00:00-05:00</th>\n",
       "      <td>0.027</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T10:00:00-05:00</th>\n",
       "      <td>0.029</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T11:00:00-05:00</th>\n",
       "      <td>0.032</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T12:00:00-05:00</th>\n",
       "      <td>0.031</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7870 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "parameter                     o3  pm25\n",
       "local                                 \n",
       "2016-03-14T23:00:00-05:00  0.016  11.7\n",
       "2016-03-15T00:00:00-05:00  0.027  15.6\n",
       "2016-03-15T01:00:00-05:00  0.030  25.1\n",
       "2016-03-15T02:00:00-05:00  0.028  20.7\n",
       "2016-03-15T03:00:00-05:00  0.023  23.7\n",
       "2016-03-15T04:00:00-05:00  0.018  18.6\n",
       "2016-03-15T05:00:00-05:00  0.014  28.4\n",
       "2016-03-15T06:00:00-05:00  0.008  21.4\n",
       "2016-03-15T07:00:00-05:00  0.002  23.3\n",
       "2016-03-15T08:00:00-05:00  0.010  24.3\n",
       "2016-03-15T09:00:00-05:00  0.022  22.0\n",
       "2016-03-15T10:00:00-05:00  0.030  15.7\n",
       "2016-03-15T11:00:00-05:00  0.041  15.4\n",
       "2016-03-15T12:00:00-05:00  0.050  19.8\n",
       "2016-03-15T13:00:00-05:00  0.052   7.4\n",
       "2016-03-15T14:00:00-05:00  0.050   NaN\n",
       "2016-03-15T15:00:00-05:00  0.054   4.2\n",
       "2016-03-15T16:00:00-05:00  0.056   NaN\n",
       "2016-03-15T17:00:00-05:00  0.053   NaN\n",
       "2016-03-15T18:00:00-05:00  0.049  11.1\n",
       "2016-03-15T19:00:00-05:00  0.046  10.8\n",
       "2016-03-15T20:00:00-05:00  0.042  11.4\n",
       "2016-03-15T21:00:00-05:00  0.043  12.8\n",
       "2016-03-15T22:00:00-05:00  0.039  13.3\n",
       "2016-03-15T23:00:00-05:00  0.039  12.3\n",
       "2016-03-16T00:00:00-05:00  0.037  12.4\n",
       "2016-03-16T01:00:00-05:00  0.034  13.3\n",
       "2016-03-16T02:00:00-05:00  0.032  13.6\n",
       "2016-03-16T03:00:00-05:00  0.029  15.5\n",
       "2016-03-16T04:00:00-05:00  0.026  16.8\n",
       "...                          ...   ...\n",
       "2017-03-10T23:00:00-05:00  0.043   NaN\n",
       "2017-03-11T00:00:00-05:00  0.041   NaN\n",
       "2017-03-11T01:00:00-05:00  0.039   0.7\n",
       "2017-03-11T02:00:00-05:00  0.039   1.5\n",
       "2017-03-11T03:00:00-05:00  0.038   0.2\n",
       "2017-03-11T04:00:00-05:00  0.038   0.8\n",
       "2017-03-11T05:00:00-05:00  0.037   1.5\n",
       "2017-03-11T06:00:00-05:00  0.034   1.8\n",
       "2017-03-11T07:00:00-05:00  0.033   1.1\n",
       "2017-03-11T08:00:00-05:00  0.036   2.0\n",
       "2017-03-11T09:00:00-05:00  0.040   0.7\n",
       "2017-03-11T10:00:00-05:00  0.042   NaN\n",
       "2017-03-11T11:00:00-05:00  0.043   1.5\n",
       "2017-03-11T12:00:00-05:00  0.047   NaN\n",
       "2017-03-11T13:00:00-05:00  0.050   NaN\n",
       "2017-03-11T14:00:00-05:00  0.052   NaN\n",
       "2017-03-11T15:00:00-05:00  0.053   NaN\n",
       "2017-03-11T16:00:00-05:00  0.052   1.3\n",
       "2017-03-11T17:00:00-05:00  0.047   2.2\n",
       "2017-03-11T18:00:00-05:00  0.045  12.1\n",
       "2017-03-11T19:00:00-05:00  0.041  19.8\n",
       "2017-03-11T20:00:00-05:00  0.041   7.2\n",
       "2017-03-11T21:00:00-05:00  0.040   7.3\n",
       "2017-03-11T22:00:00-05:00  0.036   9.4\n",
       "2017-03-11T23:00:00-05:00  0.033   9.4\n",
       "2017-03-14T08:00:00-05:00  0.026   3.9\n",
       "2017-03-14T09:00:00-05:00  0.027   2.6\n",
       "2017-03-14T10:00:00-05:00  0.029   3.0\n",
       "2017-03-14T11:00:00-05:00  0.032   0.4\n",
       "2017-03-14T12:00:00-05:00  0.031   NaN\n",
       "\n",
       "[7870 rows x 2 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aq = aq.pivot(index='local',columns='parameter',values='value')\n",
    "aq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>parameter</th>\n",
       "      <th>o3</th>\n",
       "      <th>pm25</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>local</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-03-14T08:00:00-05:00</th>\n",
       "      <td>0.026</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T09:00:00-05:00</th>\n",
       "      <td>0.027</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T10:00:00-05:00</th>\n",
       "      <td>0.029</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T11:00:00-05:00</th>\n",
       "      <td>0.032</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-14T12:00:00-05:00</th>\n",
       "      <td>0.031</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "parameter                     o3  pm25\n",
       "local                                 \n",
       "2017-03-14T08:00:00-05:00  0.026   3.9\n",
       "2017-03-14T09:00:00-05:00  0.027   2.6\n",
       "2017-03-14T10:00:00-05:00  0.029   3.0\n",
       "2017-03-14T11:00:00-05:00  0.032   0.4\n",
       "2017-03-14T12:00:00-05:00  0.031   NaN"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aq = aq.drop('2016-03-14T23:00:00-05:00')\n",
    "aq.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>parameter</th>\n",
       "      <th>o3</th>\n",
       "      <th>pm25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5361.000000</td>\n",
       "      <td>7548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.031307</td>\n",
       "      <td>8.603630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.014412</td>\n",
       "      <td>8.044855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.021000</td>\n",
       "      <td>4.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.032000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.042000</td>\n",
       "      <td>10.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.083000</td>\n",
       "      <td>127.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "parameter           o3         pm25\n",
       "count      5361.000000  7548.000000\n",
       "mean          0.031307     8.603630\n",
       "std           0.014412     8.044855\n",
       "min           0.000000     0.200000\n",
       "25%           0.021000     4.200000\n",
       "50%           0.032000     7.000000\n",
       "75%           0.042000    10.900000\n",
       "max           0.083000   127.000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aq.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rng = pd.date_range('03/15/2016', periods=len(aq), freq='H')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>parameter</th>\n",
       "      <th>o3</th>\n",
       "      <th>pm25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-02-05 16:00:00</th>\n",
       "      <td>0.026</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-05 17:00:00</th>\n",
       "      <td>0.027</td>\n",
       "      <td>2.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-05 18:00:00</th>\n",
       "      <td>0.029</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-05 19:00:00</th>\n",
       "      <td>0.032</td>\n",
       "      <td>0.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-05 20:00:00</th>\n",
       "      <td>0.031</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "parameter               o3  pm25\n",
       "2017-02-05 16:00:00  0.026   3.9\n",
       "2017-02-05 17:00:00  0.027   2.6\n",
       "2017-02-05 18:00:00  0.029   3.0\n",
       "2017-02-05 19:00:00  0.032   0.4\n",
       "2017-02-05 20:00:00  0.031   NaN"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aq_ts = aq.set_index(rng)\n",
    "aq_ts.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>parameter</th>\n",
       "      <th>o3</th>\n",
       "      <th>pm25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5361.000000</td>\n",
       "      <td>7548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.031307</td>\n",
       "      <td>8.603630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.014412</td>\n",
       "      <td>8.044855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.021000</td>\n",
       "      <td>4.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.032000</td>\n",
       "      <td>7.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.042000</td>\n",
       "      <td>10.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.083000</td>\n",
       "      <td>127.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "parameter           o3         pm25\n",
       "count      5361.000000  7548.000000\n",
       "mean          0.031307     8.603630\n",
       "std           0.014412     8.044855\n",
       "min           0.000000     0.200000\n",
       "25%           0.021000     4.200000\n",
       "50%           0.032000     7.000000\n",
       "75%           0.042000    10.900000\n",
       "max           0.083000   127.000000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aq_ts.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Q26KxcQ+VFt1OeLZtezvZubN/in9PT6/90CR27Gihq70z7X4A7e1dKetIQ0NL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\npZtRG1VGRfuYby843fW+0TI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AfwKTzGsM2p71Gmeb93eDeY+HAz0ebF4OnGqedgQwTms9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\nqqIzAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a032da58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(aq_ts.o3)\n",
    "plt.title('O3 Over Time')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KjbZ+nwskZexbqLi0l7Hn4KnITobODdt2xz/Bos0hXLCnpvvH6zMM7p7gcshj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\nQcgixKgLgiBkEWLUBUEQsoj/B703EyRcK6O9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a074f6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a083acf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(aq_ts.pm25)\n",
    "plt.title('PM2.5 Over Time')\n",
    "plt.show()\n",
    "plt.savefig('pm25_over_time.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\ipykernel\\__main__.py:2: FutureWarning: pd.rolling_mean is deprecated for Series and will be removed in a future version, replace with \n",
      "\tSeries.rolling(window=24,min_periods=12,center=False).mean()\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2017-02-04 20:00:00    5.846667\n",
       "2017-02-04 21:00:00    3.880000\n",
       "2017-02-04 22:00:00    2.446667\n",
       "2017-02-04 23:00:00    2.380000\n",
       "2017-02-05 00:00:00    2.153333\n",
       "2017-02-05 01:00:00    1.820000\n",
       "2017-02-05 02:00:00    1.685714\n",
       "2017-02-05 03:00:00    1.673333\n",
       "2017-02-05 04:00:00    1.673333\n",
       "2017-02-05 05:00:00    1.728571\n",
       "2017-02-05 06:00:00    1.838462\n",
       "2017-02-05 07:00:00    1.838462\n",
       "2017-02-05 08:00:00    1.800000\n",
       "2017-02-05 09:00:00    1.826667\n",
       "2017-02-05 10:00:00    2.468750\n",
       "2017-02-05 11:00:00    3.593750\n",
       "2017-02-05 12:00:00    3.805882\n",
       "2017-02-05 13:00:00    3.841176\n",
       "2017-02-05 14:00:00    4.182353\n",
       "2017-02-05 15:00:00    4.472222\n",
       "2017-02-05 16:00:00    4.442105\n",
       "2017-02-05 17:00:00    4.542105\n",
       "2017-02-05 18:00:00    4.621053\n",
       "2017-02-05 19:00:00    4.631579\n",
       "2017-02-05 20:00:00    4.844444\n",
       "Freq: H, Name: pm25, dtype: float64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Calculating a 24-hour rolling average to determine conformance with the NAAQS for PM2.5.\n",
    "avg_pm25 = pd.rolling_mean(aq_ts.pm25, window=24, min_periods=12, freq=None, center=False)\n",
    "avg_pm25.tail(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    7858.000000\n",
       "mean        8.551608\n",
       "std         5.571366\n",
       "min         1.450000\n",
       "25%         5.334837\n",
       "50%         7.452083\n",
       "75%        10.337500\n",
       "max        80.462500\n",
       "Name: pm25, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_pm25.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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o/+7ufu/vzs5Wurp6Rylm5RlvOcb7/LUkh8hQW3JUUoaRZAqA4eHkqI65rV0HkaP4scMo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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a07adb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the rolling 24-hour average PM2.5 values, with the NAAQS shown as the red horizontal line.\n",
    "fig = plt.figure()\n",
    "plt.plot(avg_pm25)\n",
    "plt.plot(('2016-03-15 00:00:00','2017-02-05 20:00:00'),(35,35),'r-')\n",
    "plt.title('Rolling 24-hr Avg PM2.5 Compared to NAAQS')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "fig.savefig('rolling_pm25.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\ipykernel\\__main__.py:1: FutureWarning: pd.rolling_mean is deprecated for Series and will be removed in a future version, replace with \n",
      "\tSeries.rolling(window=8,min_periods=4,center=False).mean()\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2017-02-04 20:00:00    0.040625\n",
       "2017-02-04 21:00:00    0.039875\n",
       "2017-02-04 22:00:00    0.038625\n",
       "2017-02-04 23:00:00    0.037375\n",
       "2017-02-05 00:00:00    0.036750\n",
       "2017-02-05 01:00:00    0.036875\n",
       "2017-02-05 02:00:00    0.037250\n",
       "2017-02-05 03:00:00    0.037875\n",
       "2017-02-05 04:00:00    0.039000\n",
       "2017-02-05 05:00:00    0.040625\n",
       "2017-02-05 06:00:00    0.042875\n",
       "2017-02-05 07:00:00    0.045375\n",
       "2017-02-05 08:00:00    0.047375\n",
       "2017-02-05 09:00:00    0.048250\n",
       "2017-02-05 10:00:00    0.048625\n",
       "2017-02-05 11:00:00    0.048375\n",
       "2017-02-05 12:00:00    0.047625\n",
       "2017-02-05 13:00:00    0.046375\n",
       "2017-02-05 14:00:00    0.044375\n",
       "2017-02-05 15:00:00    0.041875\n",
       "2017-02-05 16:00:00    0.038625\n",
       "2017-02-05 17:00:00    0.036125\n",
       "2017-02-05 18:00:00    0.034125\n",
       "2017-02-05 19:00:00    0.033000\n",
       "2017-02-05 20:00:00    0.031750\n",
       "Freq: H, Name: o3, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_o3 = pd.rolling_mean(aq_ts.o3, window=8, min_periods=4, freq=None, center=False)\n",
    "avg_o3.tail(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    5438.000000\n",
       "mean        0.031280\n",
       "std         0.011946\n",
       "min         0.000500\n",
       "25%         0.022750\n",
       "50%         0.031500\n",
       "75%         0.039875\n",
       "max         0.073375\n",
       "Name: o3, dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "avg_o3.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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09jU04+BxKE0FZfnarB1kFRdfX3+S6/7yXMaxlrZunjdXbLjtQZl1jy/7KY82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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a0909c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the rolling 8-hour average O3 values, with the NAAQS shown as the red horizontal line.\n",
    "fig = plt.figure()\n",
    "plt.plot(avg_o3)\n",
    "plt.plot(('2016-03-15 00:00:00','2017-02-05 20:00:00'),(0.070,0.070),'r-')\n",
    "plt.title('Rolling 8-hr Avg O3 Compared to NAAQS')\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "fig.savefig('rolling_o3.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2016-05-18 01:00:00    0.073375\n",
       "2016-05-18 02:00:00    0.073125\n",
       "2016-05-18 00:00:00    0.071250\n",
       "2016-04-15 11:00:00    0.067875\n",
       "2016-05-18 03:00:00    0.067750\n",
       "2016-05-18 23:00:00    0.065750\n",
       "2016-04-15 12:00:00    0.065625\n",
       "2016-04-16 10:00:00    0.065375\n",
       "2016-05-19 00:00:00    0.065125\n",
       "2016-04-16 11:00:00    0.065000\n",
       "2016-05-18 22:00:00    0.065000\n",
       "2016-05-17 23:00:00    0.064625\n",
       "2016-06-02 00:00:00    0.064375\n",
       "2016-06-02 22:00:00    0.063750\n",
       "2016-06-02 01:00:00    0.063375\n",
       "Name: o3, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Finding the fourth highest daily maximum 8-hour average O3. It is 0.0679.\n",
    "top_o3 = avg_o3.sort_values(ascending=False)\n",
    "top_o3.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "##Start of Section 2: North vs. South Columbus.##"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>State Code</th>\n",
       "      <th>County Code</th>\n",
       "      <th>Site Number</th>\n",
       "      <th>Parameter Code</th>\n",
       "      <th>POC</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Datum</th>\n",
       "      <th>Parameter Name</th>\n",
       "      <th>Duration Description</th>\n",
       "      <th>...</th>\n",
       "      <th>AQI</th>\n",
       "      <th>Daily Criteria Indicator</th>\n",
       "      <th>Tribe Name</th>\n",
       "      <th>State Name</th>\n",
       "      <th>County Name</th>\n",
       "      <th>City Name</th>\n",
       "      <th>Local Site Name</th>\n",
       "      <th>Address</th>\n",
       "      <th>MSA or CBSA Name</th>\n",
       "      <th>Data Source</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>27</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>41</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>58</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>37</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>45</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>27</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>60</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>33</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>33</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>52</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>17</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>58</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>58</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>57</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>37</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>62</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>63</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>33</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>18</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>45</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>27</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>34</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>51</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>35</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>52</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>55</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>51</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>45</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>28</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>39</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>85</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>60</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>54</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>12</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>129</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>19</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>36</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>31</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>14</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>21</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>38</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>24</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>38</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>11</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>52</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>1</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.483543</td>\n",
       "      <td>-84.980977</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Health Department</td>\n",
       "      <td>Muscogee City Health Department, 1958 8th Aven...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>117 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     State Code  County Code  Site Number  Parameter Code  POC   Latitude  \\\n",
       "0            13          215            1           88101    1  32.483543   \n",
       "1            13          215            1           88101    1  32.483543   \n",
       "2            13          215            1           88101    1  32.483543   \n",
       "3            13          215            1           88101    1  32.483543   \n",
       "4            13          215            1           88101    1  32.483543   \n",
       "5            13          215            1           88101    1  32.483543   \n",
       "6            13          215            1           88101    1  32.483543   \n",
       "7            13          215            1           88101    1  32.483543   \n",
       "8            13          215            1           88101    1  32.483543   \n",
       "9            13          215            1           88101    1  32.483543   \n",
       "10           13          215            1           88101    1  32.483543   \n",
       "11           13          215            1           88101    1  32.483543   \n",
       "12           13          215            1           88101    1  32.483543   \n",
       "13           13          215            1           88101    1  32.483543   \n",
       "14           13          215            1           88101    1  32.483543   \n",
       "15           13          215            1           88101    1  32.483543   \n",
       "16           13          215            1           88101    1  32.483543   \n",
       "17           13          215            1           88101    1  32.483543   \n",
       "18           13          215            1           88101    1  32.483543   \n",
       "19           13          215            1           88101    1  32.483543   \n",
       "20           13          215            1           88101    1  32.483543   \n",
       "21           13          215            1           88101    1  32.483543   \n",
       "22           13          215            1           88101    1  32.483543   \n",
       "23           13          215            1           88101    1  32.483543   \n",
       "24           13          215            1           88101    1  32.483543   \n",
       "25           13          215            1           88101    1  32.483543   \n",
       "26           13          215            1           88101    1  32.483543   \n",
       "27           13          215            1           88101    1  32.483543   \n",
       "28           13          215            1           88101    1  32.483543   \n",
       "29           13          215            1           88101    1  32.483543   \n",
       "..          ...          ...          ...             ...  ...        ...   \n",
       "87           13          215            1           88101    1  32.483543   \n",
       "88           13          215            1           88101    1  32.483543   \n",
       "89           13          215            1           88101    1  32.483543   \n",
       "90           13          215            1           88101    1  32.483543   \n",
       "91           13          215            1           88101    1  32.483543   \n",
       "92           13          215            1           88101    1  32.483543   \n",
       "93           13          215            1           88101    1  32.483543   \n",
       "94           13          215            1           88101    1  32.483543   \n",
       "95           13          215            1           88101    1  32.483543   \n",
       "96           13          215            1           88101    1  32.483543   \n",
       "97           13          215            1           88101    1  32.483543   \n",
       "98           13          215            1           88101    1  32.483543   \n",
       "99           13          215            1           88101    1  32.483543   \n",
       "100          13          215            1           88101    1  32.483543   \n",
       "101          13          215            1           88101    1  32.483543   \n",
       "102          13          215            1           88101    1  32.483543   \n",
       "103          13          215            1           88101    1  32.483543   \n",
       "104          13          215            1           88101    1  32.483543   \n",
       "105          13          215            1           88101    1  32.483543   \n",
       "106          13          215            1           88101    1  32.483543   \n",
       "107          13          215            1           88101    1  32.483543   \n",
       "108          13          215            1           88101    1  32.483543   \n",
       "109          13          215            1           88101    1  32.483543   \n",
       "110          13          215            1           88101    1  32.483543   \n",
       "111          13          215            1           88101    1  32.483543   \n",
       "112          13          215            1           88101    1  32.483543   \n",
       "113          13          215            1           88101    1  32.483543   \n",
       "114          13          215            1           88101    1  32.483543   \n",
       "115          13          215            1           88101    1  32.483543   \n",
       "116          13          215            1           88101    1  32.483543   \n",
       "\n",
       "     Longitude  Datum            Parameter Name Duration Description  \\\n",
       "0   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "1   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "2   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "3   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "4   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "5   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "6   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "7   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "8   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "9   -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "10  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "11  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "12  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "13  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "14  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "15  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "16  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "17  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "18  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "19  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "20  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "21  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "22  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "23  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "24  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "25  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "26  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "27  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "28  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "29  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "..         ...    ...                       ...                  ...   \n",
       "87  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "88  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "89  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "90  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "91  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "92  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "93  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "94  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "95  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "96  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "97  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "98  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "99  -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "100 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "101 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "102 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "103 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "104 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "105 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "106 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "107 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "108 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "109 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "110 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "111 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "112 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "113 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "114 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "115 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "116 -84.980977  WGS84  PM2.5 - Local Conditions              24 HOUR   \n",
       "\n",
       "         ...        AQI Daily Criteria Indicator  Tribe Name  State Name  \\\n",
       "0        ...         27                        Y         NaN     Georgia   \n",
       "1        ...         18                        Y         NaN     Georgia   \n",
       "2        ...         18                        Y         NaN     Georgia   \n",
       "3        ...          9                        Y         NaN     Georgia   \n",
       "4        ...         41                        Y         NaN     Georgia   \n",
       "5        ...         28                        Y         NaN     Georgia   \n",
       "6        ...         21                        Y         NaN     Georgia   \n",
       "7        ...         58                        Y         NaN     Georgia   \n",
       "8        ...         37                        Y         NaN     Georgia   \n",
       "9        ...         45                        Y         NaN     Georgia   \n",
       "10       ...         23                        Y         NaN     Georgia   \n",
       "11       ...         27                        Y         NaN     Georgia   \n",
       "12       ...         13                        Y         NaN     Georgia   \n",
       "13       ...         60                        Y         NaN     Georgia   \n",
       "14       ...         33                        Y         NaN     Georgia   \n",
       "15       ...         33                        Y         NaN     Georgia   \n",
       "16       ...         52                        Y         NaN     Georgia   \n",
       "17       ...         17                        Y         NaN     Georgia   \n",
       "18       ...         50                        Y         NaN     Georgia   \n",
       "19       ...         58                        Y         NaN     Georgia   \n",
       "20       ...         20                        Y         NaN     Georgia   \n",
       "21       ...         58                        Y         NaN     Georgia   \n",
       "22       ...         57                        Y         NaN     Georgia   \n",
       "23       ...         37                        Y         NaN     Georgia   \n",
       "24       ...         62                        Y         NaN     Georgia   \n",
       "25       ...         24                        Y         NaN     Georgia   \n",
       "26       ...         63                        Y         NaN     Georgia   \n",
       "27       ...         33                        Y         NaN     Georgia   \n",
       "28       ...         18                        Y         NaN     Georgia   \n",
       "29       ...         50                        Y         NaN     Georgia   \n",
       "..       ...        ...                      ...         ...         ...   \n",
       "87       ...         45                        Y         NaN     Georgia   \n",
       "88       ...         27                        Y         NaN     Georgia   \n",
       "89       ...         16                        Y         NaN     Georgia   \n",
       "90       ...         34                        Y         NaN     Georgia   \n",
       "91       ...         51                        Y         NaN     Georgia   \n",
       "92       ...         35                        Y         NaN     Georgia   \n",
       "93       ...         20                        Y         NaN     Georgia   \n",
       "94       ...         52                        Y         NaN     Georgia   \n",
       "95       ...         55                        Y         NaN     Georgia   \n",
       "96       ...         51                        Y         NaN     Georgia   \n",
       "97       ...         45                        Y         NaN     Georgia   \n",
       "98       ...         28                        Y         NaN     Georgia   \n",
       "99       ...         39                        Y         NaN     Georgia   \n",
       "100      ...         85                        Y         NaN     Georgia   \n",
       "101      ...         60                        Y         NaN     Georgia   \n",
       "102      ...         54                        Y         NaN     Georgia   \n",
       "103      ...         12                        Y         NaN     Georgia   \n",
       "104      ...        129                        Y         NaN     Georgia   \n",
       "105      ...         19                        Y         NaN     Georgia   \n",
       "106      ...         36                        Y         NaN     Georgia   \n",
       "107      ...         31                        Y         NaN     Georgia   \n",
       "108      ...         14                        Y         NaN     Georgia   \n",
       "109      ...         21                        Y         NaN     Georgia   \n",
       "110      ...         38                        Y         NaN     Georgia   \n",
       "111      ...         24                        Y         NaN     Georgia   \n",
       "112      ...         38                        Y         NaN     Georgia   \n",
       "113      ...         11                        Y         NaN     Georgia   \n",
       "114      ...         52                        Y         NaN     Georgia   \n",
       "115      ...         44                        Y         NaN     Georgia   \n",
       "116      ...         23                        Y         NaN     Georgia   \n",
       "\n",
       "    County Name             City Name             Local Site Name  \\\n",
       "0      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "1      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "2      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "3      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "4      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "5      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "6      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "7      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "8      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "9      Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "10     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "11     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "12     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "13     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "14     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "15     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "16     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "17     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "18     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "19     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "20     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "21     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "22     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "23     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "24     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "25     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "26     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "27     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "28     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "29     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "..          ...                   ...                         ...   \n",
       "87     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "88     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "89     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "90     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "91     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "92     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "93     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "94     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "95     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "96     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "97     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "98     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "99     Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "100    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "101    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "102    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "103    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "104    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "105    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "106    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "107    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "108    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "109    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "110    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "111    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "112    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "113    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "114    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "115    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "116    Muscogee  Columbus (Remainder)  Columbus-Health Department   \n",
       "\n",
       "                                               Address  MSA or CBSA Name  \\\n",
       "0    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "1    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "2    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "3    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "4    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "5    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "6    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "7    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "8    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "9    Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "10   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "11   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "12   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "13   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "14   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "15   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "16   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "17   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "18   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "19   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "20   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "21   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "22   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "23   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "24   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "25   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "26   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "27   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "28   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "29   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "..                                                 ...               ...   \n",
       "87   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "88   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "89   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "90   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "91   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "92   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "93   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "94   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "95   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "96   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "97   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "98   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "99   Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "100  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "101  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "102  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "103  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "104  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "105  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "106  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "107  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "108  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "109  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "110  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "111  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "112  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "113  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "114  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "115  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "116  Muscogee City Health Department, 1958 8th Aven...   Columbus, GA-AL   \n",
       "\n",
       "       Data Source  \n",
       "0    AQS Data Mart  \n",
       "1    AQS Data Mart  \n",
       "2    AQS Data Mart  \n",
       "3    AQS Data Mart  \n",
       "4    AQS Data Mart  \n",
       "5    AQS Data Mart  \n",
       "6    AQS Data Mart  \n",
       "7    AQS Data Mart  \n",
       "8    AQS Data Mart  \n",
       "9    AQS Data Mart  \n",
       "10   AQS Data Mart  \n",
       "11   AQS Data Mart  \n",
       "12   AQS Data Mart  \n",
       "13   AQS Data Mart  \n",
       "14   AQS Data Mart  \n",
       "15   AQS Data Mart  \n",
       "16   AQS Data Mart  \n",
       "17   AQS Data Mart  \n",
       "18   AQS Data Mart  \n",
       "19   AQS Data Mart  \n",
       "20   AQS Data Mart  \n",
       "21   AQS Data Mart  \n",
       "22   AQS Data Mart  \n",
       "23   AQS Data Mart  \n",
       "24   AQS Data Mart  \n",
       "25   AQS Data Mart  \n",
       "26   AQS Data Mart  \n",
       "27   AQS Data Mart  \n",
       "28   AQS Data Mart  \n",
       "29   AQS Data Mart  \n",
       "..             ...  \n",
       "87   AQS Data Mart  \n",
       "88   AQS Data Mart  \n",
       "89   AQS Data Mart  \n",
       "90   AQS Data Mart  \n",
       "91   AQS Data Mart  \n",
       "92   AQS Data Mart  \n",
       "93   AQS Data Mart  \n",
       "94   AQS Data Mart  \n",
       "95   AQS Data Mart  \n",
       "96   AQS Data Mart  \n",
       "97   AQS Data Mart  \n",
       "98   AQS Data Mart  \n",
       "99   AQS Data Mart  \n",
       "100  AQS Data Mart  \n",
       "101  AQS Data Mart  \n",
       "102  AQS Data Mart  \n",
       "103  AQS Data Mart  \n",
       "104  AQS Data Mart  \n",
       "105  AQS Data Mart  \n",
       "106  AQS Data Mart  \n",
       "107  AQS Data Mart  \n",
       "108  AQS Data Mart  \n",
       "109  AQS Data Mart  \n",
       "110  AQS Data Mart  \n",
       "111  AQS Data Mart  \n",
       "112  AQS Data Mart  \n",
       "113  AQS Data Mart  \n",
       "114  AQS Data Mart  \n",
       "115  AQS Data Mart  \n",
       "116  AQS Data Mart  \n",
       "\n",
       "[117 rows x 34 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "north = pd.read_csv('north.csv')\n",
    "north = pd.DataFrame(north)\n",
    "north"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>north_PM25</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date (Local)</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1/1/2016</th>\n",
       "      <td>6.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/10/2016</th>\n",
       "      <td>2.2</td>\n",
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       "      <th>1/13/2016</th>\n",
       "      <td>9.8</td>\n",
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       "      <th>1/16/2016</th>\n",
       "      <td>6.7</td>\n",
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       "      <th>1/22/2016</th>\n",
       "      <td>5.0</td>\n",
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       "      <th>1/25/2016</th>\n",
       "      <td>15.5</td>\n",
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       "    <tr>\n",
       "      <th>1/28/2016</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/31/2016</th>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/4/2016</th>\n",
       "      <td>4.4</td>\n",
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       "    <tr>\n",
       "      <th>1/7/2016</th>\n",
       "      <td>4.2</td>\n",
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       "    <tr>\n",
       "      <th>10/12/2016</th>\n",
       "      <td>8.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/15/2016</th>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/18/2016</th>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/21/2016</th>\n",
       "      <td>4.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/24/2016</th>\n",
       "      <td>12.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/27/2016</th>\n",
       "      <td>14.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/3/2016</th>\n",
       "      <td>10.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/30/2016</th>\n",
       "      <td>12.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/6/2016</th>\n",
       "      <td>6.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/9/2016</th>\n",
       "      <td>3.8</td>\n",
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       "    <tr>\n",
       "      <th>11/11/2016</th>\n",
       "      <td>28.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/14/2016</th>\n",
       "      <td>16.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/17/2016</th>\n",
       "      <td>13.6</td>\n",
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       "    <tr>\n",
       "      <th>11/2/2016</th>\n",
       "      <td>10.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/20/2016</th>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/23/2016</th>\n",
       "      <td>46.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/26/2016</th>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/29/2016</th>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/5/2016</th>\n",
       "      <td>6.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/8/2016</th>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6/8/2016</th>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/11/2016</th>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/14/2016</th>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/17/2016</th>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/2/2016</th>\n",
       "      <td>11.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/20/2016</th>\n",
       "      <td>9.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/23/2016</th>\n",
       "      <td>9.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/26/2016</th>\n",
       "      <td>5.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/29/2016</th>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/8/2016</th>\n",
       "      <td>8.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/1/2016</th>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/10/2016</th>\n",
       "      <td>3.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/13/2016</th>\n",
       "      <td>5.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/16/2016</th>\n",
       "      <td>5.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/19/2016</th>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/22/2016</th>\n",
       "      <td>6.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/25/2016</th>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/31/2016</th>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/4/2016</th>\n",
       "      <td>11.3</td>\n",
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       "    <tr>\n",
       "      <th>8/7/2016</th>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/12/2016</th>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/15/2016</th>\n",
       "      <td>6.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/18/2016</th>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/21/2016</th>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/24/2016</th>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/27/2016</th>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/3/2016</th>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/30/2016</th>\n",
       "      <td>5.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/6/2016</th>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/9/2016</th>\n",
       "      <td>15.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>117 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              north_PM25\n",
       "Date (Local)            \n",
       "1/1/2016             6.4\n",
       "1/10/2016            2.2\n",
       "1/13/2016            9.8\n",
       "1/16/2016            6.7\n",
       "1/22/2016            5.0\n",
       "1/25/2016           15.5\n",
       "1/28/2016            8.8\n",
       "1/31/2016           10.7\n",
       "1/4/2016             4.4\n",
       "1/7/2016             4.2\n",
       "10/12/2016           8.2\n",
       "10/15/2016          12.2\n",
       "10/18/2016           8.5\n",
       "10/21/2016           4.9\n",
       "10/24/2016          12.7\n",
       "10/27/2016          14.1\n",
       "10/3/2016           10.8\n",
       "10/30/2016          12.2\n",
       "10/6/2016            6.4\n",
       "10/9/2016            3.8\n",
       "11/11/2016          28.2\n",
       "11/14/2016          16.6\n",
       "11/17/2016          13.6\n",
       "11/2/2016           10.9\n",
       "11/20/2016           2.8\n",
       "11/23/2016          46.8\n",
       "11/26/2016           4.5\n",
       "11/29/2016           8.6\n",
       "11/5/2016            6.8\n",
       "11/8/2016            9.3\n",
       "...                  ...\n",
       "6/8/2016             7.2\n",
       "7/11/2016            7.7\n",
       "7/14/2016            6.2\n",
       "7/17/2016            4.1\n",
       "7/2/2016            11.9\n",
       "7/20/2016            9.4\n",
       "7/23/2016            9.6\n",
       "7/26/2016            5.5\n",
       "7/29/2016           11.7\n",
       "7/8/2016             8.1\n",
       "8/1/2016             6.6\n",
       "8/10/2016            3.5\n",
       "8/13/2016            5.2\n",
       "8/16/2016            5.8\n",
       "8/19/2016            6.1\n",
       "8/22/2016            6.8\n",
       "8/25/2016            9.5\n",
       "8/31/2016            5.1\n",
       "8/4/2016            11.3\n",
       "8/7/2016            11.5\n",
       "9/12/2016            7.0\n",
       "9/15/2016            6.8\n",
       "9/18/2016            6.7\n",
       "9/21/2016            7.4\n",
       "9/24/2016            7.1\n",
       "9/27/2016            9.0\n",
       "9/3/2016             5.1\n",
       "9/30/2016            5.9\n",
       "9/6/2016             9.8\n",
       "9/9/2016            15.7\n",
       "\n",
       "[117 rows x 1 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "north = north.pivot(index='Date (Local)',columns='Parameter Name',values='First Maximum Value')\n",
    "north.columns = ['north_PM25']\n",
    "north"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>State Code</th>\n",
       "      <th>County Code</th>\n",
       "      <th>Site Number</th>\n",
       "      <th>Parameter Code</th>\n",
       "      <th>POC</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
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       "      <th>Parameter Name</th>\n",
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       "      <th>State Name</th>\n",
       "      <th>County Name</th>\n",
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       "      <th>Local Site Name</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13</td>\n",
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       "      <td>11</td>\n",
       "      <td>88320</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
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       "      <td>OC PM2.5 LC TOR</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
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       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Zirconium PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <td>WGS84</td>\n",
       "      <td>Sodium Ion Pm2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
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       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88403</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Sulfate PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88104</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Aluminum PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
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       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88113</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Cobalt PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88168</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Strontium PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88103</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Arsenic PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88357</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>EC CSN_Rev Unadjusted PM2.5 LC TOT</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88154</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Selenium PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88374</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC1 CSN_Rev Unadjusted PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88375</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC2 CSN_Rev Unadjusted PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88180</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Potassium PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88377</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC4 CSN_Rev Unadjusted PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88370</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC CSN_Rev Unadjusted PM2.5 LC TOR</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88376</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC3 CSN_Rev Unadjusted PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88380</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>EC CSN_Rev Unadjusted PM2.5 LC TOR</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88321</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>EC PM2.5 LC TOR</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88378</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OP CSN_Rev Unadjusted PM2.5 LC TOR</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88388</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OP CSN_Rev Unadjusted PM2.5 LC TOT</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88384</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>EC2 CSN_Rev Unadjusted PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88383</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>EC1 CSN_Rev Unadjusted PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88324</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC1 PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88325</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC2 PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88326</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC3 PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88327</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OC4 PM2.5 LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88328</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OP PM2.5 LC TOR</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88379</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>OP PM2.5 LC TOT</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88381</td>\n",
       "      <td>5</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>EC PM2.5 LC TOT</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1160</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1161</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>47</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1162</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1163</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>35</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1164</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>44</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1165</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1166</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1167</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>58</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1168</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1169</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>55</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1170</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>16</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1171</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1172</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>113</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1173</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>38</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1174</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1175</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>37</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1176</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1177</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>13</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1178</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1179</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1180</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>42</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1181</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>25</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1182</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1183</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>36</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1184</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>9</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1185</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1186</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>53</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1187</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>14129</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>Lead (TSP) LC</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>.</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1188</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>41</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1189</th>\n",
       "      <td>13</td>\n",
       "      <td>215</td>\n",
       "      <td>11</td>\n",
       "      <td>88101</td>\n",
       "      <td>1</td>\n",
       "      <td>32.42905</td>\n",
       "      <td>-84.9316</td>\n",
       "      <td>WGS84</td>\n",
       "      <td>PM2.5 - Local Conditions</td>\n",
       "      <td>24 HOUR</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>Muscogee</td>\n",
       "      <td>Columbus (Remainder)</td>\n",
       "      <td>Columbus-Cusseta Road Elementary</td>\n",
       "      <td>Cusseta Road Elementary School,.4150 Cusseta R...</td>\n",
       "      <td>Columbus, GA-AL</td>\n",
       "      <td>AQS Data Mart</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1190 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      State Code  County Code  Site Number  Parameter Code  POC  Latitude  \\\n",
       "0             13          215           11           88320    5  32.42905   \n",
       "1             13          215           11           88185    5  32.42905   \n",
       "2             13          215           11           88302    5  32.42905   \n",
       "3             13          215           11           88403    5  32.42905   \n",
       "4             13          215           11           88104    5  32.42905   \n",
       "5             13          215           11           88113    5  32.42905   \n",
       "6             13          215           11           88168    5  32.42905   \n",
       "7             13          215           11           88103    5  32.42905   \n",
       "8             13          215           11           88357    5  32.42905   \n",
       "9             13          215           11           88154    5  32.42905   \n",
       "10            13          215           11           88374    5  32.42905   \n",
       "11            13          215           11           88375    5  32.42905   \n",
       "12            13          215           11           88180    5  32.42905   \n",
       "13            13          215           11           88377    5  32.42905   \n",
       "14            13          215           11           88370    5  32.42905   \n",
       "15            13          215           11           88376    5  32.42905   \n",
       "16            13          215           11           88380    5  32.42905   \n",
       "17            13          215           11           88321    5  32.42905   \n",
       "18            13          215           11           88378    5  32.42905   \n",
       "19            13          215           11           88388    5  32.42905   \n",
       "20            13          215           11           88384    5  32.42905   \n",
       "21            13          215           11           88383    5  32.42905   \n",
       "22            13          215           11           88324    5  32.42905   \n",
       "23            13          215           11           14129    1  32.42905   \n",
       "24            13          215           11           88325    5  32.42905   \n",
       "25            13          215           11           88326    5  32.42905   \n",
       "26            13          215           11           88327    5  32.42905   \n",
       "27            13          215           11           88328    5  32.42905   \n",
       "28            13          215           11           88379    5  32.42905   \n",
       "29            13          215           11           88381    5  32.42905   \n",
       "...          ...          ...          ...             ...  ...       ...   \n",
       "1160          13          215           11           88101    1  32.42905   \n",
       "1161          13          215           11           88101    1  32.42905   \n",
       "1162          13          215           11           14129    1  32.42905   \n",
       "1163          13          215           11           88101    1  32.42905   \n",
       "1164          13          215           11           88101    1  32.42905   \n",
       "1165          13          215           11           14129    1  32.42905   \n",
       "1166          13          215           11           88101    1  32.42905   \n",
       "1167          13          215           11           88101    1  32.42905   \n",
       "1168          13          215           11           14129    1  32.42905   \n",
       "1169          13          215           11           88101    1  32.42905   \n",
       "1170          13          215           11           88101    1  32.42905   \n",
       "1171          13          215           11           14129    1  32.42905   \n",
       "1172          13          215           11           88101    1  32.42905   \n",
       "1173          13          215           11           88101    1  32.42905   \n",
       "1174          13          215           11           14129    1  32.42905   \n",
       "1175          13          215           11           88101    1  32.42905   \n",
       "1176          13          215           11           14129    1  32.42905   \n",
       "1177          13          215           11           88101    1  32.42905   \n",
       "1178          13          215           11           88101    1  32.42905   \n",
       "1179          13          215           11           14129    1  32.42905   \n",
       "1180          13          215           11           88101    1  32.42905   \n",
       "1181          13          215           11           88101    1  32.42905   \n",
       "1182          13          215           11           14129    1  32.42905   \n",
       "1183          13          215           11           88101    1  32.42905   \n",
       "1184          13          215           11           88101    1  32.42905   \n",
       "1185          13          215           11           14129    1  32.42905   \n",
       "1186          13          215           11           88101    1  32.42905   \n",
       "1187          13          215           11           14129    1  32.42905   \n",
       "1188          13          215           11           88101    1  32.42905   \n",
       "1189          13          215           11           88101    1  32.42905   \n",
       "\n",
       "      Longitude  Datum                      Parameter Name  \\\n",
       "0      -84.9316  WGS84                     OC PM2.5 LC TOR   \n",
       "1      -84.9316  WGS84                  Zirconium PM2.5 LC   \n",
       "2      -84.9316  WGS84                 Sodium Ion Pm2.5 LC   \n",
       "3      -84.9316  WGS84                    Sulfate PM2.5 LC   \n",
       "4      -84.9316  WGS84                   Aluminum PM2.5 LC   \n",
       "5      -84.9316  WGS84                     Cobalt PM2.5 LC   \n",
       "6      -84.9316  WGS84                  Strontium PM2.5 LC   \n",
       "7      -84.9316  WGS84                    Arsenic PM2.5 LC   \n",
       "8      -84.9316  WGS84  EC CSN_Rev Unadjusted PM2.5 LC TOT   \n",
       "9      -84.9316  WGS84                   Selenium PM2.5 LC   \n",
       "10     -84.9316  WGS84     OC1 CSN_Rev Unadjusted PM2.5 LC   \n",
       "11     -84.9316  WGS84     OC2 CSN_Rev Unadjusted PM2.5 LC   \n",
       "12     -84.9316  WGS84                  Potassium PM2.5 LC   \n",
       "13     -84.9316  WGS84     OC4 CSN_Rev Unadjusted PM2.5 LC   \n",
       "14     -84.9316  WGS84  OC CSN_Rev Unadjusted PM2.5 LC TOR   \n",
       "15     -84.9316  WGS84     OC3 CSN_Rev Unadjusted PM2.5 LC   \n",
       "16     -84.9316  WGS84  EC CSN_Rev Unadjusted PM2.5 LC TOR   \n",
       "17     -84.9316  WGS84                     EC PM2.5 LC TOR   \n",
       "18     -84.9316  WGS84  OP CSN_Rev Unadjusted PM2.5 LC TOR   \n",
       "19     -84.9316  WGS84  OP CSN_Rev Unadjusted PM2.5 LC TOT   \n",
       "20     -84.9316  WGS84     EC2 CSN_Rev Unadjusted PM2.5 LC   \n",
       "21     -84.9316  WGS84     EC1 CSN_Rev Unadjusted PM2.5 LC   \n",
       "22     -84.9316  WGS84                        OC1 PM2.5 LC   \n",
       "23     -84.9316  WGS84                       Lead (TSP) LC   \n",
       "24     -84.9316  WGS84                        OC2 PM2.5 LC   \n",
       "25     -84.9316  WGS84                        OC3 PM2.5 LC   \n",
       "26     -84.9316  WGS84                        OC4 PM2.5 LC   \n",
       "27     -84.9316  WGS84                     OP PM2.5 LC TOR   \n",
       "28     -84.9316  WGS84                     OP PM2.5 LC TOT   \n",
       "29     -84.9316  WGS84                     EC PM2.5 LC TOT   \n",
       "...         ...    ...                                 ...   \n",
       "1160   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1161   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1162   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1163   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1164   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1165   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1166   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1167   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1168   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1169   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1170   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1171   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1172   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1173   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1174   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1175   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1176   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1177   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1178   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1179   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1180   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1181   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1182   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1183   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1184   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1185   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1186   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1187   -84.9316  WGS84                       Lead (TSP) LC   \n",
       "1188   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "1189   -84.9316  WGS84            PM2.5 - Local Conditions   \n",
       "\n",
       "     Duration Description      ...        AQI Daily Criteria Indicator  \\\n",
       "0                 24 HOUR      ...          .                        Y   \n",
       "1                 24 HOUR      ...          .                        Y   \n",
       "2                 24 HOUR      ...          .                        Y   \n",
       "3                 24 HOUR      ...          .                        Y   \n",
       "4                 24 HOUR      ...          .                        Y   \n",
       "5                 24 HOUR      ...          .                        Y   \n",
       "6                 24 HOUR      ...          .                        Y   \n",
       "7                 24 HOUR      ...          .                        Y   \n",
       "8                 24 HOUR      ...          .                        Y   \n",
       "9                 24 HOUR      ...          .                        Y   \n",
       "10                24 HOUR      ...          .                        Y   \n",
       "11                24 HOUR      ...          .                        Y   \n",
       "12                24 HOUR      ...          .                        Y   \n",
       "13                24 HOUR      ...          .                        Y   \n",
       "14                24 HOUR      ...          .                        Y   \n",
       "15                24 HOUR      ...          .                        Y   \n",
       "16                24 HOUR      ...          .                        Y   \n",
       "17                24 HOUR      ...          .                        Y   \n",
       "18                24 HOUR      ...          .                        Y   \n",
       "19                24 HOUR      ...          .                        Y   \n",
       "20                24 HOUR      ...          .                        Y   \n",
       "21                24 HOUR      ...          .                        Y   \n",
       "22                24 HOUR      ...          .                        Y   \n",
       "23                24 HOUR      ...          .                        Y   \n",
       "24                24 HOUR      ...          .                        Y   \n",
       "25                24 HOUR      ...          .                        Y   \n",
       "26                24 HOUR      ...          .                        Y   \n",
       "27                24 HOUR      ...          .                        Y   \n",
       "28                24 HOUR      ...          .                        Y   \n",
       "29                24 HOUR      ...          .                        Y   \n",
       "...                   ...      ...        ...                      ...   \n",
       "1160              24 HOUR      ...         56                        Y   \n",
       "1161              24 HOUR      ...         47                        Y   \n",
       "1162              24 HOUR      ...          .                        Y   \n",
       "1163              24 HOUR      ...         35                        Y   \n",
       "1164              24 HOUR      ...         44                        Y   \n",
       "1165              24 HOUR      ...          .                        Y   \n",
       "1166              24 HOUR      ...         97                        Y   \n",
       "1167              24 HOUR      ...         58                        Y   \n",
       "1168              24 HOUR      ...          .                        Y   \n",
       "1169              24 HOUR      ...         55                        Y   \n",
       "1170              24 HOUR      ...         16                        Y   \n",
       "1171              24 HOUR      ...          .                        Y   \n",
       "1172              24 HOUR      ...        113                        Y   \n",
       "1173              24 HOUR      ...         38                        Y   \n",
       "1174              24 HOUR      ...          .                        Y   \n",
       "1175              24 HOUR      ...         37                        Y   \n",
       "1176              24 HOUR      ...          .                        Y   \n",
       "1177              24 HOUR      ...         13                        Y   \n",
       "1178              24 HOUR      ...         23                        Y   \n",
       "1179              24 HOUR      ...          .                        Y   \n",
       "1180              24 HOUR      ...         42                        Y   \n",
       "1181              24 HOUR      ...         25                        Y   \n",
       "1182              24 HOUR      ...          .                        Y   \n",
       "1183              24 HOUR      ...         36                        Y   \n",
       "1184              24 HOUR      ...          9                        Y   \n",
       "1185              24 HOUR      ...          .                        Y   \n",
       "1186              24 HOUR      ...         53                        Y   \n",
       "1187              24 HOUR      ...          .                        Y   \n",
       "1188              24 HOUR      ...         41                        Y   \n",
       "1189              24 HOUR      ...         23                        Y   \n",
       "\n",
       "      Tribe Name  State Name County Name             City Name  \\\n",
       "0            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "2            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "3            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "4            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "5            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "6            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "7            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "8            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "9            NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "10           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "11           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "12           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "13           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "14           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "15           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "16           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "17           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "18           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "19           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "20           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "21           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "22           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "23           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "24           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "25           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "26           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "27           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "28           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "29           NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "...          ...         ...         ...                   ...   \n",
       "1160         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1161         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1162         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1163         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1164         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1165         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1166         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1167         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1168         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1169         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1170         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1171         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1172         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1173         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1174         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1175         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1176         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1177         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1178         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1179         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1180         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1181         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1182         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1183         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1184         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1185         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1186         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1187         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1188         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "1189         NaN     Georgia    Muscogee  Columbus (Remainder)   \n",
       "\n",
       "                       Local Site Name  \\\n",
       "0     Columbus-Cusseta Road Elementary   \n",
       "1     Columbus-Cusseta Road Elementary   \n",
       "2     Columbus-Cusseta Road Elementary   \n",
       "3     Columbus-Cusseta Road Elementary   \n",
       "4     Columbus-Cusseta Road Elementary   \n",
       "5     Columbus-Cusseta Road Elementary   \n",
       "6     Columbus-Cusseta Road Elementary   \n",
       "7     Columbus-Cusseta Road Elementary   \n",
       "8     Columbus-Cusseta Road Elementary   \n",
       "9     Columbus-Cusseta Road Elementary   \n",
       "10    Columbus-Cusseta Road Elementary   \n",
       "11    Columbus-Cusseta Road Elementary   \n",
       "12    Columbus-Cusseta Road Elementary   \n",
       "13    Columbus-Cusseta Road Elementary   \n",
       "14    Columbus-Cusseta Road Elementary   \n",
       "15    Columbus-Cusseta Road Elementary   \n",
       "16    Columbus-Cusseta Road Elementary   \n",
       "17    Columbus-Cusseta Road Elementary   \n",
       "18    Columbus-Cusseta Road Elementary   \n",
       "19    Columbus-Cusseta Road Elementary   \n",
       "20    Columbus-Cusseta Road Elementary   \n",
       "21    Columbus-Cusseta Road Elementary   \n",
       "22    Columbus-Cusseta Road Elementary   \n",
       "23    Columbus-Cusseta Road Elementary   \n",
       "24    Columbus-Cusseta Road Elementary   \n",
       "25    Columbus-Cusseta Road Elementary   \n",
       "26    Columbus-Cusseta Road Elementary   \n",
       "27    Columbus-Cusseta Road Elementary   \n",
       "28    Columbus-Cusseta Road Elementary   \n",
       "29    Columbus-Cusseta Road Elementary   \n",
       "...                                ...   \n",
       "1160  Columbus-Cusseta Road Elementary   \n",
       "1161  Columbus-Cusseta Road Elementary   \n",
       "1162  Columbus-Cusseta Road Elementary   \n",
       "1163  Columbus-Cusseta Road Elementary   \n",
       "1164  Columbus-Cusseta Road Elementary   \n",
       "1165  Columbus-Cusseta Road Elementary   \n",
       "1166  Columbus-Cusseta Road Elementary   \n",
       "1167  Columbus-Cusseta Road Elementary   \n",
       "1168  Columbus-Cusseta Road Elementary   \n",
       "1169  Columbus-Cusseta Road Elementary   \n",
       "1170  Columbus-Cusseta Road Elementary   \n",
       "1171  Columbus-Cusseta Road Elementary   \n",
       "1172  Columbus-Cusseta Road Elementary   \n",
       "1173  Columbus-Cusseta Road Elementary   \n",
       "1174  Columbus-Cusseta Road Elementary   \n",
       "1175  Columbus-Cusseta Road Elementary   \n",
       "1176  Columbus-Cusseta Road Elementary   \n",
       "1177  Columbus-Cusseta Road Elementary   \n",
       "1178  Columbus-Cusseta Road Elementary   \n",
       "1179  Columbus-Cusseta Road Elementary   \n",
       "1180  Columbus-Cusseta Road Elementary   \n",
       "1181  Columbus-Cusseta Road Elementary   \n",
       "1182  Columbus-Cusseta Road Elementary   \n",
       "1183  Columbus-Cusseta Road Elementary   \n",
       "1184  Columbus-Cusseta Road Elementary   \n",
       "1185  Columbus-Cusseta Road Elementary   \n",
       "1186  Columbus-Cusseta Road Elementary   \n",
       "1187  Columbus-Cusseta Road Elementary   \n",
       "1188  Columbus-Cusseta Road Elementary   \n",
       "1189  Columbus-Cusseta Road Elementary   \n",
       "\n",
       "                                                Address  MSA or CBSA Name  \\\n",
       "0     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "2     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "3     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "4     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "5     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "6     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "7     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "8     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "9     Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "10    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "11    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "12    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "13    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "14    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "15    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "16    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "17    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "18    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "19    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "20    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "21    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "22    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "23    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "24    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "25    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "26    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "27    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "28    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "29    Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "...                                                 ...               ...   \n",
       "1160  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1161  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1162  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1163  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1164  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1165  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1166  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1167  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1168  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1169  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1170  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1171  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1172  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1173  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1174  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1175  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1176  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1177  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1178  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1179  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1180  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1181  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1182  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1183  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1184  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1185  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1186  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1187  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1188  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "1189  Cusseta Road Elementary School,.4150 Cusseta R...   Columbus, GA-AL   \n",
       "\n",
       "        Data Source  \n",
       "0     AQS Data Mart  \n",
       "1     AQS Data Mart  \n",
       "2     AQS Data Mart  \n",
       "3     AQS Data Mart  \n",
       "4     AQS Data Mart  \n",
       "5     AQS Data Mart  \n",
       "6     AQS Data Mart  \n",
       "7     AQS Data Mart  \n",
       "8     AQS Data Mart  \n",
       "9     AQS Data Mart  \n",
       "10    AQS Data Mart  \n",
       "11    AQS Data Mart  \n",
       "12    AQS Data Mart  \n",
       "13    AQS Data Mart  \n",
       "14    AQS Data Mart  \n",
       "15    AQS Data Mart  \n",
       "16    AQS Data Mart  \n",
       "17    AQS Data Mart  \n",
       "18    AQS Data Mart  \n",
       "19    AQS Data Mart  \n",
       "20    AQS Data Mart  \n",
       "21    AQS Data Mart  \n",
       "22    AQS Data Mart  \n",
       "23    AQS Data Mart  \n",
       "24    AQS Data Mart  \n",
       "25    AQS Data Mart  \n",
       "26    AQS Data Mart  \n",
       "27    AQS Data Mart  \n",
       "28    AQS Data Mart  \n",
       "29    AQS Data Mart  \n",
       "...             ...  \n",
       "1160  AQS Data Mart  \n",
       "1161  AQS Data Mart  \n",
       "1162  AQS Data Mart  \n",
       "1163  AQS Data Mart  \n",
       "1164  AQS Data Mart  \n",
       "1165  AQS Data Mart  \n",
       "1166  AQS Data Mart  \n",
       "1167  AQS Data Mart  \n",
       "1168  AQS Data Mart  \n",
       "1169  AQS Data Mart  \n",
       "1170  AQS Data Mart  \n",
       "1171  AQS Data Mart  \n",
       "1172  AQS Data Mart  \n",
       "1173  AQS Data Mart  \n",
       "1174  AQS Data Mart  \n",
       "1175  AQS Data Mart  \n",
       "1176  AQS Data Mart  \n",
       "1177  AQS Data Mart  \n",
       "1178  AQS Data Mart  \n",
       "1179  AQS Data Mart  \n",
       "1180  AQS Data Mart  \n",
       "1181  AQS Data Mart  \n",
       "1182  AQS Data Mart  \n",
       "1183  AQS Data Mart  \n",
       "1184  AQS Data Mart  \n",
       "1185  AQS Data Mart  \n",
       "1186  AQS Data Mart  \n",
       "1187  AQS Data Mart  \n",
       "1188  AQS Data Mart  \n",
       "1189  AQS Data Mart  \n",
       "\n",
       "[1190 rows x 34 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "south = pd.read_csv('south.csv')\n",
    "south = pd.DataFrame(south)\n",
    "south"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Parameter Name</th>\n",
       "      <th>Aluminum PM2.5 LC</th>\n",
       "      <th>Ammonium Ion PM2.5 LC</th>\n",
       "      <th>Antimony PM2.5 LC</th>\n",
       "      <th>Arsenic PM2.5 LC</th>\n",
       "      <th>Average Ambient Pressure for URG3000N</th>\n",
       "      <th>Average Ambient Temperature for URG3000N</th>\n",
       "      <th>Barium PM2.5 LC</th>\n",
       "      <th>Bromine PM2.5 LC</th>\n",
       "      <th>Cadmium PM2.5 LC</th>\n",
       "      <th>Calcium PM2.5 LC</th>\n",
       "      <th>...</th>\n",
       "      <th>Sodium PM2.5 LC</th>\n",
       "      <th>Strontium PM2.5 LC</th>\n",
       "      <th>Sulfate PM2.5 LC</th>\n",
       "      <th>Sulfur PM2.5 LC</th>\n",
       "      <th>Tin PM2.5 LC</th>\n",
       "      <th>Titanium PM2.5 LC</th>\n",
       "      <th>Total Nitrate PM2.5 LC</th>\n",
       "      <th>Vanadium PM2.5 LC</th>\n",
       "      <th>Zinc PM2.5 LC</th>\n",
       "      <th>Zirconium PM2.5 LC</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date (Local)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1/1/2016</th>\n",
       "      <td>0.020</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.031</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.026</td>\n",
       "      <td>0.002</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>0.016</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>0.006</td>\n",
       "      <td>2.47</td>\n",
       "      <td>0.873</td>\n",
       "      <td>0.022</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.009</td>\n",
       "      <td>-0.007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/10/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/13/2016</th>\n",
       "      <td>-0.014</td>\n",
       "      <td>0.05</td>\n",
       "      <td>-0.007</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.002</td>\n",
       "      <td>-0.005</td>\n",
       "      <td>0.024</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.67</td>\n",
       "      <td>0.315</td>\n",
       "      <td>0.030</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.34</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.018</td>\n",
       "      <td>-0.013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/16/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/19/2016</th>\n",
       "      <td>0.014</td>\n",
       "      <td>0.07</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.000</td>\n",
       "      <td>-0.009</td>\n",
       "      <td>0.021</td>\n",
       "      <td>...</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.41</td>\n",
       "      <td>0.145</td>\n",
       "      <td>-0.026</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/22/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/25/2016</th>\n",
       "      <td>0.005</td>\n",
       "      <td>0.44</td>\n",
       "      <td>-0.018</td>\n",
       "      <td>0.001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.012</td>\n",
       "      <td>...</td>\n",
       "      <td>0.059</td>\n",
       "      <td>-0.001</td>\n",
       "      <td>1.43</td>\n",
       "      <td>0.505</td>\n",
       "      <td>-0.014</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.33</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.007</td>\n",
       "      <td>0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/28/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/31/2016</th>\n",
       "      <td>-0.002</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.035</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.014</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.004</td>\n",
       "      <td>1.06</td>\n",
       "      <td>0.345</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.37</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.006</td>\n",
       "      <td>0.001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/4/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/7/2016</th>\n",
       "      <td>0.021</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.016</td>\n",
       "      <td>0.000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.012</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.023</td>\n",
       "      <td>...</td>\n",
       "      <td>0.085</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.46</td>\n",
       "      <td>0.150</td>\n",
       "      <td>-0.006</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.35</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.006</td>\n",
       "      <td>-0.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/12/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/15/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/18/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/21/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/24/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/27/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/3/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/30/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/6/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/9/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/11/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/14/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/17/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/2/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/20/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/23/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/26/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/5/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/8/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/14/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/17/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/2/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/20/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/23/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/26/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/29/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/5/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/8/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/1/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/10/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/13/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/16/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/19/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/22/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/25/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/28/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/31/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/4/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/7/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/12/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/15/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/18/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/21/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/24/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/27/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/3/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/30/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/6/2016</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>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/9/2016</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>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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>121 rows × 74 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Parameter Name  Aluminum PM2.5 LC  Ammonium Ion PM2.5 LC  Antimony PM2.5 LC  \\\n",
       "Date (Local)                                                                  \n",
       "1/1/2016                    0.020                   0.56              0.031   \n",
       "1/10/2016                     NaN                    NaN                NaN   \n",
       "1/13/2016                  -0.014                   0.05             -0.007   \n",
       "1/16/2016                     NaN                    NaN                NaN   \n",
       "1/19/2016                   0.014                   0.07             -0.006   \n",
       "1/22/2016                     NaN                    NaN                NaN   \n",
       "1/25/2016                   0.005                   0.44             -0.018   \n",
       "1/28/2016                     NaN                    NaN                NaN   \n",
       "1/31/2016                  -0.002                   0.10             -0.006   \n",
       "1/4/2016                      NaN                    NaN                NaN   \n",
       "1/7/2016                    0.021                   0.04              0.016   \n",
       "10/12/2016                    NaN                    NaN                NaN   \n",
       "10/15/2016                    NaN                    NaN                NaN   \n",
       "10/18/2016                    NaN                    NaN                NaN   \n",
       "10/21/2016                    NaN                    NaN                NaN   \n",
       "10/24/2016                    NaN                    NaN                NaN   \n",
       "10/27/2016                    NaN                    NaN                NaN   \n",
       "10/3/2016                     NaN                    NaN                NaN   \n",
       "10/30/2016                    NaN                    NaN                NaN   \n",
       "10/6/2016                     NaN                    NaN                NaN   \n",
       "10/9/2016                     NaN                    NaN                NaN   \n",
       "11/11/2016                    NaN                    NaN                NaN   \n",
       "11/14/2016                    NaN                    NaN                NaN   \n",
       "11/17/2016                    NaN                    NaN                NaN   \n",
       "11/2/2016                     NaN                    NaN                NaN   \n",
       "11/20/2016                    NaN                    NaN                NaN   \n",
       "11/23/2016                    NaN                    NaN                NaN   \n",
       "11/26/2016                    NaN                    NaN                NaN   \n",
       "11/5/2016                     NaN                    NaN                NaN   \n",
       "11/8/2016                     NaN                    NaN                NaN   \n",
       "...                           ...                    ...                ...   \n",
       "7/14/2016                     NaN                    NaN                NaN   \n",
       "7/17/2016                     NaN                    NaN                NaN   \n",
       "7/2/2016                      NaN                    NaN                NaN   \n",
       "7/20/2016                     NaN                    NaN                NaN   \n",
       "7/23/2016                     NaN                    NaN                NaN   \n",
       "7/26/2016                     NaN                    NaN                NaN   \n",
       "7/29/2016                     NaN                    NaN                NaN   \n",
       "7/5/2016                      NaN                    NaN                NaN   \n",
       "7/8/2016                      NaN                    NaN                NaN   \n",
       "8/1/2016                      NaN                    NaN                NaN   \n",
       "8/10/2016                     NaN                    NaN                NaN   \n",
       "8/13/2016                     NaN                    NaN                NaN   \n",
       "8/16/2016                     NaN                    NaN                NaN   \n",
       "8/19/2016                     NaN                    NaN                NaN   \n",
       "8/22/2016                     NaN                    NaN                NaN   \n",
       "8/25/2016                     NaN                    NaN                NaN   \n",
       "8/28/2016                     NaN                    NaN                NaN   \n",
       "8/31/2016                     NaN                    NaN                NaN   \n",
       "8/4/2016                      NaN                    NaN                NaN   \n",
       "8/7/2016                      NaN                    NaN                NaN   \n",
       "9/12/2016                     NaN                    NaN                NaN   \n",
       "9/15/2016                     NaN                    NaN                NaN   \n",
       "9/18/2016                     NaN                    NaN                NaN   \n",
       "9/21/2016                     NaN                    NaN                NaN   \n",
       "9/24/2016                     NaN                    NaN                NaN   \n",
       "9/27/2016                     NaN                    NaN                NaN   \n",
       "9/3/2016                      NaN                    NaN                NaN   \n",
       "9/30/2016                     NaN                    NaN                NaN   \n",
       "9/6/2016                      NaN                    NaN                NaN   \n",
       "9/9/2016                      NaN                    NaN                NaN   \n",
       "\n",
       "Parameter Name  Arsenic PM2.5 LC  Average Ambient Pressure for URG3000N  \\\n",
       "Date (Local)                                                              \n",
       "1/1/2016                   0.000                                    NaN   \n",
       "1/10/2016                    NaN                                    NaN   \n",
       "1/13/2016                  0.000                                    NaN   \n",
       "1/16/2016                    NaN                                    NaN   \n",
       "1/19/2016                  0.000                                    NaN   \n",
       "1/22/2016                    NaN                                    NaN   \n",
       "1/25/2016                  0.001                                    NaN   \n",
       "1/28/2016                    NaN                                    NaN   \n",
       "1/31/2016                  0.000                                    NaN   \n",
       "1/4/2016                     NaN                                    NaN   \n",
       "1/7/2016                   0.000                                    NaN   \n",
       "10/12/2016                   NaN                                    NaN   \n",
       "10/15/2016                   NaN                                    NaN   \n",
       "10/18/2016                   NaN                                    NaN   \n",
       "10/21/2016                   NaN                                    NaN   \n",
       "10/24/2016                   NaN                                    NaN   \n",
       "10/27/2016                   NaN                                    NaN   \n",
       "10/3/2016                    NaN                                    NaN   \n",
       "10/30/2016                   NaN                                    NaN   \n",
       "10/6/2016                    NaN                                    NaN   \n",
       "10/9/2016                    NaN                                    NaN   \n",
       "11/11/2016                   NaN                                    NaN   \n",
       "11/14/2016                   NaN                                    NaN   \n",
       "11/17/2016                   NaN                                    NaN   \n",
       "11/2/2016                    NaN                                    NaN   \n",
       "11/20/2016                   NaN                                    NaN   \n",
       "11/23/2016                   NaN                                    NaN   \n",
       "11/26/2016                   NaN                                    NaN   \n",
       "11/5/2016                    NaN                                    NaN   \n",
       "11/8/2016                    NaN                                    NaN   \n",
       "...                          ...                                    ...   \n",
       "7/14/2016                    NaN                                    NaN   \n",
       "7/17/2016                    NaN                                    NaN   \n",
       "7/2/2016                     NaN                                    NaN   \n",
       "7/20/2016                    NaN                                    NaN   \n",
       "7/23/2016                    NaN                                    NaN   \n",
       "7/26/2016                    NaN                                    NaN   \n",
       "7/29/2016                    NaN                                    NaN   \n",
       "7/5/2016                     NaN                                    NaN   \n",
       "7/8/2016                     NaN                                    NaN   \n",
       "8/1/2016                     NaN                                    NaN   \n",
       "8/10/2016                    NaN                                    NaN   \n",
       "8/13/2016                    NaN                                    NaN   \n",
       "8/16/2016                    NaN                                    NaN   \n",
       "8/19/2016                    NaN                                    NaN   \n",
       "8/22/2016                    NaN                                    NaN   \n",
       "8/25/2016                    NaN                                    NaN   \n",
       "8/28/2016                    NaN                                    NaN   \n",
       "8/31/2016                    NaN                                    NaN   \n",
       "8/4/2016                     NaN                                    NaN   \n",
       "8/7/2016                     NaN                                    NaN   \n",
       "9/12/2016                    NaN                                    NaN   \n",
       "9/15/2016                    NaN                                    NaN   \n",
       "9/18/2016                    NaN                                    NaN   \n",
       "9/21/2016                    NaN                                    NaN   \n",
       "9/24/2016                    NaN                                    NaN   \n",
       "9/27/2016                    NaN                                    NaN   \n",
       "9/3/2016                     NaN                                    NaN   \n",
       "9/30/2016                    NaN                                    NaN   \n",
       "9/6/2016                     NaN                                    NaN   \n",
       "9/9/2016                     NaN                                    NaN   \n",
       "\n",
       "Parameter Name  Average Ambient Temperature for URG3000N  Barium PM2.5 LC  \\\n",
       "Date (Local)                                                                \n",
       "1/1/2016                                             NaN           -0.026   \n",
       "1/10/2016                                            NaN              NaN   \n",
       "1/13/2016                                            NaN            0.003   \n",
       "1/16/2016                                            NaN              NaN   \n",
       "1/19/2016                                            NaN            0.020   \n",
       "1/22/2016                                            NaN              NaN   \n",
       "1/25/2016                                            NaN            0.006   \n",
       "1/28/2016                                            NaN              NaN   \n",
       "1/31/2016                                            NaN            0.035   \n",
       "1/4/2016                                             NaN              NaN   \n",
       "1/7/2016                                             NaN            0.012   \n",
       "10/12/2016                                           NaN              NaN   \n",
       "10/15/2016                                           NaN              NaN   \n",
       "10/18/2016                                           NaN              NaN   \n",
       "10/21/2016                                           NaN              NaN   \n",
       "10/24/2016                                           NaN              NaN   \n",
       "10/27/2016                                           NaN              NaN   \n",
       "10/3/2016                                            NaN              NaN   \n",
       "10/30/2016                                           NaN              NaN   \n",
       "10/6/2016                                            NaN              NaN   \n",
       "10/9/2016                                            NaN              NaN   \n",
       "11/11/2016                                           NaN              NaN   \n",
       "11/14/2016                                           NaN              NaN   \n",
       "11/17/2016                                           NaN              NaN   \n",
       "11/2/2016                                            NaN              NaN   \n",
       "11/20/2016                                           NaN              NaN   \n",
       "11/23/2016                                           NaN              NaN   \n",
       "11/26/2016                                           NaN              NaN   \n",
       "11/5/2016                                            NaN              NaN   \n",
       "11/8/2016                                            NaN              NaN   \n",
       "...                                                  ...              ...   \n",
       "7/14/2016                                            NaN              NaN   \n",
       "7/17/2016                                            NaN              NaN   \n",
       "7/2/2016                                             NaN              NaN   \n",
       "7/20/2016                                            NaN              NaN   \n",
       "7/23/2016                                            NaN              NaN   \n",
       "7/26/2016                                            NaN              NaN   \n",
       "7/29/2016                                            NaN              NaN   \n",
       "7/5/2016                                             NaN              NaN   \n",
       "7/8/2016                                             NaN              NaN   \n",
       "8/1/2016                                             NaN              NaN   \n",
       "8/10/2016                                            NaN              NaN   \n",
       "8/13/2016                                            NaN              NaN   \n",
       "8/16/2016                                            NaN              NaN   \n",
       "8/19/2016                                            NaN              NaN   \n",
       "8/22/2016                                            NaN              NaN   \n",
       "8/25/2016                                            NaN              NaN   \n",
       "8/28/2016                                            NaN              NaN   \n",
       "8/31/2016                                            NaN              NaN   \n",
       "8/4/2016                                             NaN              NaN   \n",
       "8/7/2016                                             NaN              NaN   \n",
       "9/12/2016                                            NaN              NaN   \n",
       "9/15/2016                                            NaN              NaN   \n",
       "9/18/2016                                            NaN              NaN   \n",
       "9/21/2016                                            NaN              NaN   \n",
       "9/24/2016                                            NaN              NaN   \n",
       "9/27/2016                                            NaN              NaN   \n",
       "9/3/2016                                             NaN              NaN   \n",
       "9/30/2016                                            NaN              NaN   \n",
       "9/6/2016                                             NaN              NaN   \n",
       "9/9/2016                                             NaN              NaN   \n",
       "\n",
       "Parameter Name  Bromine PM2.5 LC  Cadmium PM2.5 LC  Calcium PM2.5 LC  \\\n",
       "Date (Local)                                                           \n",
       "1/1/2016                   0.002            -0.005             0.016   \n",
       "1/10/2016                    NaN               NaN               NaN   \n",
       "1/13/2016                  0.002            -0.005             0.024   \n",
       "1/16/2016                    NaN               NaN               NaN   \n",
       "1/19/2016                  0.000            -0.009             0.021   \n",
       "1/22/2016                    NaN               NaN               NaN   \n",
       "1/25/2016                  0.000             0.005             0.012   \n",
       "1/28/2016                    NaN               NaN               NaN   \n",
       "1/31/2016                  0.000             0.012             0.014   \n",
       "1/4/2016                     NaN               NaN               NaN   \n",
       "1/7/2016                   0.002             0.001             0.023   \n",
       "10/12/2016                   NaN               NaN               NaN   \n",
       "10/15/2016                   NaN               NaN               NaN   \n",
       "10/18/2016                   NaN               NaN               NaN   \n",
       "10/21/2016                   NaN               NaN               NaN   \n",
       "10/24/2016                   NaN               NaN               NaN   \n",
       "10/27/2016                   NaN               NaN               NaN   \n",
       "10/3/2016                    NaN               NaN               NaN   \n",
       "10/30/2016                   NaN               NaN               NaN   \n",
       "10/6/2016                    NaN               NaN               NaN   \n",
       "10/9/2016                    NaN               NaN               NaN   \n",
       "11/11/2016                   NaN               NaN               NaN   \n",
       "11/14/2016                   NaN               NaN               NaN   \n",
       "11/17/2016                   NaN               NaN               NaN   \n",
       "11/2/2016                    NaN               NaN               NaN   \n",
       "11/20/2016                   NaN               NaN               NaN   \n",
       "11/23/2016                   NaN               NaN               NaN   \n",
       "11/26/2016                   NaN               NaN               NaN   \n",
       "11/5/2016                    NaN               NaN               NaN   \n",
       "11/8/2016                    NaN               NaN               NaN   \n",
       "...                          ...               ...               ...   \n",
       "7/14/2016                    NaN               NaN               NaN   \n",
       "7/17/2016                    NaN               NaN               NaN   \n",
       "7/2/2016                     NaN               NaN               NaN   \n",
       "7/20/2016                    NaN               NaN               NaN   \n",
       "7/23/2016                    NaN               NaN               NaN   \n",
       "7/26/2016                    NaN               NaN               NaN   \n",
       "7/29/2016                    NaN               NaN               NaN   \n",
       "7/5/2016                     NaN               NaN               NaN   \n",
       "7/8/2016                     NaN               NaN               NaN   \n",
       "8/1/2016                     NaN               NaN               NaN   \n",
       "8/10/2016                    NaN               NaN               NaN   \n",
       "8/13/2016                    NaN               NaN               NaN   \n",
       "8/16/2016                    NaN               NaN               NaN   \n",
       "8/19/2016                    NaN               NaN               NaN   \n",
       "8/22/2016                    NaN               NaN               NaN   \n",
       "8/25/2016                    NaN               NaN               NaN   \n",
       "8/28/2016                    NaN               NaN               NaN   \n",
       "8/31/2016                    NaN               NaN               NaN   \n",
       "8/4/2016                     NaN               NaN               NaN   \n",
       "8/7/2016                     NaN               NaN               NaN   \n",
       "9/12/2016                    NaN               NaN               NaN   \n",
       "9/15/2016                    NaN               NaN               NaN   \n",
       "9/18/2016                    NaN               NaN               NaN   \n",
       "9/21/2016                    NaN               NaN               NaN   \n",
       "9/24/2016                    NaN               NaN               NaN   \n",
       "9/27/2016                    NaN               NaN               NaN   \n",
       "9/3/2016                     NaN               NaN               NaN   \n",
       "9/30/2016                    NaN               NaN               NaN   \n",
       "9/6/2016                     NaN               NaN               NaN   \n",
       "9/9/2016                     NaN               NaN               NaN   \n",
       "\n",
       "Parameter Name         ...          Sodium PM2.5 LC  Strontium PM2.5 LC  \\\n",
       "Date (Local)           ...                                                \n",
       "1/1/2016               ...                   -0.001               0.006   \n",
       "1/10/2016              ...                      NaN                 NaN   \n",
       "1/13/2016              ...                    0.000               0.001   \n",
       "1/16/2016              ...                      NaN                 NaN   \n",
       "1/19/2016              ...                    0.036               0.001   \n",
       "1/22/2016              ...                      NaN                 NaN   \n",
       "1/25/2016              ...                    0.059              -0.001   \n",
       "1/28/2016              ...                      NaN                 NaN   \n",
       "1/31/2016              ...                    0.000               0.004   \n",
       "1/4/2016               ...                      NaN                 NaN   \n",
       "1/7/2016               ...                    0.085               0.003   \n",
       "10/12/2016             ...                      NaN                 NaN   \n",
       "10/15/2016             ...                      NaN                 NaN   \n",
       "10/18/2016             ...                      NaN                 NaN   \n",
       "10/21/2016             ...                      NaN                 NaN   \n",
       "10/24/2016             ...                      NaN                 NaN   \n",
       "10/27/2016             ...                      NaN                 NaN   \n",
       "10/3/2016              ...                      NaN                 NaN   \n",
       "10/30/2016             ...                      NaN                 NaN   \n",
       "10/6/2016              ...                      NaN                 NaN   \n",
       "10/9/2016              ...                      NaN                 NaN   \n",
       "11/11/2016             ...                      NaN                 NaN   \n",
       "11/14/2016             ...                      NaN                 NaN   \n",
       "11/17/2016             ...                      NaN                 NaN   \n",
       "11/2/2016              ...                      NaN                 NaN   \n",
       "11/20/2016             ...                      NaN                 NaN   \n",
       "11/23/2016             ...                      NaN                 NaN   \n",
       "11/26/2016             ...                      NaN                 NaN   \n",
       "11/5/2016              ...                      NaN                 NaN   \n",
       "11/8/2016              ...                      NaN                 NaN   \n",
       "...                    ...                      ...                 ...   \n",
       "7/14/2016              ...                      NaN                 NaN   \n",
       "7/17/2016              ...                      NaN                 NaN   \n",
       "7/2/2016               ...                      NaN                 NaN   \n",
       "7/20/2016              ...                      NaN                 NaN   \n",
       "7/23/2016              ...                      NaN                 NaN   \n",
       "7/26/2016              ...                      NaN                 NaN   \n",
       "7/29/2016              ...                      NaN                 NaN   \n",
       "7/5/2016               ...                      NaN                 NaN   \n",
       "7/8/2016               ...                      NaN                 NaN   \n",
       "8/1/2016               ...                      NaN                 NaN   \n",
       "8/10/2016              ...                      NaN                 NaN   \n",
       "8/13/2016              ...                      NaN                 NaN   \n",
       "8/16/2016              ...                      NaN                 NaN   \n",
       "8/19/2016              ...                      NaN                 NaN   \n",
       "8/22/2016              ...                      NaN                 NaN   \n",
       "8/25/2016              ...                      NaN                 NaN   \n",
       "8/28/2016              ...                      NaN                 NaN   \n",
       "8/31/2016              ...                      NaN                 NaN   \n",
       "8/4/2016               ...                      NaN                 NaN   \n",
       "8/7/2016               ...                      NaN                 NaN   \n",
       "9/12/2016              ...                      NaN                 NaN   \n",
       "9/15/2016              ...                      NaN                 NaN   \n",
       "9/18/2016              ...                      NaN                 NaN   \n",
       "9/21/2016              ...                      NaN                 NaN   \n",
       "9/24/2016              ...                      NaN                 NaN   \n",
       "9/27/2016              ...                      NaN                 NaN   \n",
       "9/3/2016               ...                      NaN                 NaN   \n",
       "9/30/2016              ...                      NaN                 NaN   \n",
       "9/6/2016               ...                      NaN                 NaN   \n",
       "9/9/2016               ...                      NaN                 NaN   \n",
       "\n",
       "Parameter Name  Sulfate PM2.5 LC  Sulfur PM2.5 LC  Tin PM2.5 LC  \\\n",
       "Date (Local)                                                      \n",
       "1/1/2016                    2.47            0.873         0.022   \n",
       "1/10/2016                    NaN              NaN           NaN   \n",
       "1/13/2016                   0.67            0.315         0.030   \n",
       "1/16/2016                    NaN              NaN           NaN   \n",
       "1/19/2016                   0.41            0.145        -0.026   \n",
       "1/22/2016                    NaN              NaN           NaN   \n",
       "1/25/2016                   1.43            0.505        -0.014   \n",
       "1/28/2016                    NaN              NaN           NaN   \n",
       "1/31/2016                   1.06            0.345         0.009   \n",
       "1/4/2016                     NaN              NaN           NaN   \n",
       "1/7/2016                    0.46            0.150        -0.006   \n",
       "10/12/2016                   NaN              NaN           NaN   \n",
       "10/15/2016                   NaN              NaN           NaN   \n",
       "10/18/2016                   NaN              NaN           NaN   \n",
       "10/21/2016                   NaN              NaN           NaN   \n",
       "10/24/2016                   NaN              NaN           NaN   \n",
       "10/27/2016                   NaN              NaN           NaN   \n",
       "10/3/2016                    NaN              NaN           NaN   \n",
       "10/30/2016                   NaN              NaN           NaN   \n",
       "10/6/2016                    NaN              NaN           NaN   \n",
       "10/9/2016                    NaN              NaN           NaN   \n",
       "11/11/2016                   NaN              NaN           NaN   \n",
       "11/14/2016                   NaN              NaN           NaN   \n",
       "11/17/2016                   NaN              NaN           NaN   \n",
       "11/2/2016                    NaN              NaN           NaN   \n",
       "11/20/2016                   NaN              NaN           NaN   \n",
       "11/23/2016                   NaN              NaN           NaN   \n",
       "11/26/2016                   NaN              NaN           NaN   \n",
       "11/5/2016                    NaN              NaN           NaN   \n",
       "11/8/2016                    NaN              NaN           NaN   \n",
       "...                          ...              ...           ...   \n",
       "7/14/2016                    NaN              NaN           NaN   \n",
       "7/17/2016                    NaN              NaN           NaN   \n",
       "7/2/2016                     NaN              NaN           NaN   \n",
       "7/20/2016                    NaN              NaN           NaN   \n",
       "7/23/2016                    NaN              NaN           NaN   \n",
       "7/26/2016                    NaN              NaN           NaN   \n",
       "7/29/2016                    NaN              NaN           NaN   \n",
       "7/5/2016                     NaN              NaN           NaN   \n",
       "7/8/2016                     NaN              NaN           NaN   \n",
       "8/1/2016                     NaN              NaN           NaN   \n",
       "8/10/2016                    NaN              NaN           NaN   \n",
       "8/13/2016                    NaN              NaN           NaN   \n",
       "8/16/2016                    NaN              NaN           NaN   \n",
       "8/19/2016                    NaN              NaN           NaN   \n",
       "8/22/2016                    NaN              NaN           NaN   \n",
       "8/25/2016                    NaN              NaN           NaN   \n",
       "8/28/2016                    NaN              NaN           NaN   \n",
       "8/31/2016                    NaN              NaN           NaN   \n",
       "8/4/2016                     NaN              NaN           NaN   \n",
       "8/7/2016                     NaN              NaN           NaN   \n",
       "9/12/2016                    NaN              NaN           NaN   \n",
       "9/15/2016                    NaN              NaN           NaN   \n",
       "9/18/2016                    NaN              NaN           NaN   \n",
       "9/21/2016                    NaN              NaN           NaN   \n",
       "9/24/2016                    NaN              NaN           NaN   \n",
       "9/27/2016                    NaN              NaN           NaN   \n",
       "9/3/2016                     NaN              NaN           NaN   \n",
       "9/30/2016                    NaN              NaN           NaN   \n",
       "9/6/2016                     NaN              NaN           NaN   \n",
       "9/9/2016                     NaN              NaN           NaN   \n",
       "\n",
       "Parameter Name  Titanium PM2.5 LC  Total Nitrate PM2.5 LC  Vanadium PM2.5 LC  \\\n",
       "Date (Local)                                                                   \n",
       "1/1/2016                    0.005                    0.37              0.000   \n",
       "1/10/2016                     NaN                     NaN                NaN   \n",
       "1/13/2016                   0.004                    0.34              0.000   \n",
       "1/16/2016                     NaN                     NaN                NaN   \n",
       "1/19/2016                   0.002                    0.72              0.000   \n",
       "1/22/2016                     NaN                     NaN                NaN   \n",
       "1/25/2016                   0.000                    0.33              0.000   \n",
       "1/28/2016                     NaN                     NaN                NaN   \n",
       "1/31/2016                   0.003                    0.37              0.000   \n",
       "1/4/2016                      NaN                     NaN                NaN   \n",
       "1/7/2016                    0.004                    0.35              0.001   \n",
       "10/12/2016                    NaN                     NaN                NaN   \n",
       "10/15/2016                    NaN                     NaN                NaN   \n",
       "10/18/2016                    NaN                     NaN                NaN   \n",
       "10/21/2016                    NaN                     NaN                NaN   \n",
       "10/24/2016                    NaN                     NaN                NaN   \n",
       "10/27/2016                    NaN                     NaN                NaN   \n",
       "10/3/2016                     NaN                     NaN                NaN   \n",
       "10/30/2016                    NaN                     NaN                NaN   \n",
       "10/6/2016                     NaN                     NaN                NaN   \n",
       "10/9/2016                     NaN                     NaN                NaN   \n",
       "11/11/2016                    NaN                     NaN                NaN   \n",
       "11/14/2016                    NaN                     NaN                NaN   \n",
       "11/17/2016                    NaN                     NaN                NaN   \n",
       "11/2/2016                     NaN                     NaN                NaN   \n",
       "11/20/2016                    NaN                     NaN                NaN   \n",
       "11/23/2016                    NaN                     NaN                NaN   \n",
       "11/26/2016                    NaN                     NaN                NaN   \n",
       "11/5/2016                     NaN                     NaN                NaN   \n",
       "11/8/2016                     NaN                     NaN                NaN   \n",
       "...                           ...                     ...                ...   \n",
       "7/14/2016                     NaN                     NaN                NaN   \n",
       "7/17/2016                     NaN                     NaN                NaN   \n",
       "7/2/2016                      NaN                     NaN                NaN   \n",
       "7/20/2016                     NaN                     NaN                NaN   \n",
       "7/23/2016                     NaN                     NaN                NaN   \n",
       "7/26/2016                     NaN                     NaN                NaN   \n",
       "7/29/2016                     NaN                     NaN                NaN   \n",
       "7/5/2016                      NaN                     NaN                NaN   \n",
       "7/8/2016                      NaN                     NaN                NaN   \n",
       "8/1/2016                      NaN                     NaN                NaN   \n",
       "8/10/2016                     NaN                     NaN                NaN   \n",
       "8/13/2016                     NaN                     NaN                NaN   \n",
       "8/16/2016                     NaN                     NaN                NaN   \n",
       "8/19/2016                     NaN                     NaN                NaN   \n",
       "8/22/2016                     NaN                     NaN                NaN   \n",
       "8/25/2016                     NaN                     NaN                NaN   \n",
       "8/28/2016                     NaN                     NaN                NaN   \n",
       "8/31/2016                     NaN                     NaN                NaN   \n",
       "8/4/2016                      NaN                     NaN                NaN   \n",
       "8/7/2016                      NaN                     NaN                NaN   \n",
       "9/12/2016                     NaN                     NaN                NaN   \n",
       "9/15/2016                     NaN                     NaN                NaN   \n",
       "9/18/2016                     NaN                     NaN                NaN   \n",
       "9/21/2016                     NaN                     NaN                NaN   \n",
       "9/24/2016                     NaN                     NaN                NaN   \n",
       "9/27/2016                     NaN                     NaN                NaN   \n",
       "9/3/2016                      NaN                     NaN                NaN   \n",
       "9/30/2016                     NaN                     NaN                NaN   \n",
       "9/6/2016                      NaN                     NaN                NaN   \n",
       "9/9/2016                      NaN                     NaN                NaN   \n",
       "\n",
       "Parameter Name  Zinc PM2.5 LC  Zirconium PM2.5 LC  \n",
       "Date (Local)                                       \n",
       "1/1/2016                0.009              -0.007  \n",
       "1/10/2016                 NaN                 NaN  \n",
       "1/13/2016               0.018              -0.013  \n",
       "1/16/2016                 NaN                 NaN  \n",
       "1/19/2016               0.024               0.014  \n",
       "1/22/2016                 NaN                 NaN  \n",
       "1/25/2016               0.007               0.003  \n",
       "1/28/2016                 NaN                 NaN  \n",
       "1/31/2016               0.006               0.001  \n",
       "1/4/2016                  NaN                 NaN  \n",
       "1/7/2016                0.006              -0.008  \n",
       "10/12/2016                NaN                 NaN  \n",
       "10/15/2016                NaN                 NaN  \n",
       "10/18/2016                NaN                 NaN  \n",
       "10/21/2016                NaN                 NaN  \n",
       "10/24/2016                NaN                 NaN  \n",
       "10/27/2016                NaN                 NaN  \n",
       "10/3/2016                 NaN                 NaN  \n",
       "10/30/2016                NaN                 NaN  \n",
       "10/6/2016                 NaN                 NaN  \n",
       "10/9/2016                 NaN                 NaN  \n",
       "11/11/2016                NaN                 NaN  \n",
       "11/14/2016                NaN                 NaN  \n",
       "11/17/2016                NaN                 NaN  \n",
       "11/2/2016                 NaN                 NaN  \n",
       "11/20/2016                NaN                 NaN  \n",
       "11/23/2016                NaN                 NaN  \n",
       "11/26/2016                NaN                 NaN  \n",
       "11/5/2016                 NaN                 NaN  \n",
       "11/8/2016                 NaN                 NaN  \n",
       "...                       ...                 ...  \n",
       "7/14/2016                 NaN                 NaN  \n",
       "7/17/2016                 NaN                 NaN  \n",
       "7/2/2016                  NaN                 NaN  \n",
       "7/20/2016                 NaN                 NaN  \n",
       "7/23/2016                 NaN                 NaN  \n",
       "7/26/2016                 NaN                 NaN  \n",
       "7/29/2016                 NaN                 NaN  \n",
       "7/5/2016                  NaN                 NaN  \n",
       "7/8/2016                  NaN                 NaN  \n",
       "8/1/2016                  NaN                 NaN  \n",
       "8/10/2016                 NaN                 NaN  \n",
       "8/13/2016                 NaN                 NaN  \n",
       "8/16/2016                 NaN                 NaN  \n",
       "8/19/2016                 NaN                 NaN  \n",
       "8/22/2016                 NaN                 NaN  \n",
       "8/25/2016                 NaN                 NaN  \n",
       "8/28/2016                 NaN                 NaN  \n",
       "8/31/2016                 NaN                 NaN  \n",
       "8/4/2016                  NaN                 NaN  \n",
       "8/7/2016                  NaN                 NaN  \n",
       "9/12/2016                 NaN                 NaN  \n",
       "9/15/2016                 NaN                 NaN  \n",
       "9/18/2016                 NaN                 NaN  \n",
       "9/21/2016                 NaN                 NaN  \n",
       "9/24/2016                 NaN                 NaN  \n",
       "9/27/2016                 NaN                 NaN  \n",
       "9/3/2016                  NaN                 NaN  \n",
       "9/30/2016                 NaN                 NaN  \n",
       "9/6/2016                  NaN                 NaN  \n",
       "9/9/2016                  NaN                 NaN  \n",
       "\n",
       "[121 rows x 74 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Unstacking the observations for south Columbus reveals each of the individual particulate components.\n",
    "#This data was not collected for north Columbus.\n",
    "south = south.pivot(index='Date (Local)',columns='Parameter Name',values='First Maximum Value')\n",
    "south"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>south_PM25</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date (Local)</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1/1/2016</th>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/10/2016</th>\n",
       "      <td>2.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/13/2016</th>\n",
       "      <td>7.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/16/2016</th>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/19/2016</th>\n",
       "      <td>5.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/22/2016</th>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/25/2016</th>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/28/2016</th>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/31/2016</th>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/4/2016</th>\n",
       "      <td>4.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1/7/2016</th>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/12/2016</th>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/15/2016</th>\n",
       "      <td>12.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/18/2016</th>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/21/2016</th>\n",
       "      <td>5.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/24/2016</th>\n",
       "      <td>47.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/27/2016</th>\n",
       "      <td>18.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/3/2016</th>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/30/2016</th>\n",
       "      <td>14.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/6/2016</th>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10/9/2016</th>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/11/2016</th>\n",
       "      <td>33.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/14/2016</th>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/17/2016</th>\n",
       "      <td>14.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/2/2016</th>\n",
       "      <td>11.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/20/2016</th>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/23/2016</th>\n",
       "      <td>40.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/26/2016</th>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/5/2016</th>\n",
       "      <td>8.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11/8/2016</th>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/14/2016</th>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/17/2016</th>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/2/2016</th>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/20/2016</th>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/23/2016</th>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/26/2016</th>\n",
       "      <td>5.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/29/2016</th>\n",
       "      <td>11.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/5/2016</th>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7/8/2016</th>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/1/2016</th>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/10/2016</th>\n",
       "      <td>3.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/13/2016</th>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/16/2016</th>\n",
       "      <td>6.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/19/2016</th>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/22/2016</th>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/25/2016</th>\n",
       "      <td>9.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/28/2016</th>\n",
       "      <td>7.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/31/2016</th>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/4/2016</th>\n",
       "      <td>11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8/7/2016</th>\n",
       "      <td>12.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/12/2016</th>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/15/2016</th>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/18/2016</th>\n",
       "      <td>7.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/21/2016</th>\n",
       "      <td>7.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/24/2016</th>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/27/2016</th>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/3/2016</th>\n",
       "      <td>5.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/30/2016</th>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/6/2016</th>\n",
       "      <td>9.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9/9/2016</th>\n",
       "      <td>15.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>121 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              south_PM25\n",
       "Date (Local)            \n",
       "1/1/2016             7.4\n",
       "1/10/2016            2.3\n",
       "1/13/2016            7.7\n",
       "1/16/2016            7.3\n",
       "1/19/2016            5.6\n",
       "1/22/2016            5.0\n",
       "1/25/2016            7.9\n",
       "1/28/2016            9.3\n",
       "1/31/2016            8.5\n",
       "1/4/2016             4.9\n",
       "1/7/2016             4.3\n",
       "10/12/2016           9.5\n",
       "10/15/2016          12.1\n",
       "10/18/2016           7.0\n",
       "10/21/2016           5.4\n",
       "10/24/2016          47.4\n",
       "10/27/2016          18.6\n",
       "10/3/2016           11.7\n",
       "10/30/2016          14.7\n",
       "10/6/2016            6.5\n",
       "10/9/2016            3.8\n",
       "11/11/2016          33.8\n",
       "11/14/2016          15.5\n",
       "11/17/2016          14.2\n",
       "11/2/2016           11.2\n",
       "11/20/2016           3.9\n",
       "11/23/2016          40.5\n",
       "11/26/2016           9.1\n",
       "11/5/2016            8.5\n",
       "11/8/2016           10.6\n",
       "...                  ...\n",
       "7/14/2016            6.2\n",
       "7/17/2016            4.2\n",
       "7/2/2016            12.0\n",
       "7/20/2016            9.0\n",
       "7/23/2016            8.0\n",
       "7/26/2016            5.2\n",
       "7/29/2016           11.7\n",
       "7/5/2016            10.4\n",
       "7/8/2016             8.3\n",
       "8/1/2016             6.5\n",
       "8/10/2016            3.3\n",
       "8/13/2016            4.4\n",
       "8/16/2016            6.1\n",
       "8/19/2016            6.7\n",
       "8/22/2016            7.1\n",
       "8/25/2016            9.3\n",
       "8/28/2016            7.3\n",
       "8/31/2016            5.3\n",
       "8/4/2016            11.5\n",
       "8/7/2016            12.0\n",
       "9/12/2016            7.1\n",
       "9/15/2016            6.7\n",
       "9/18/2016            7.2\n",
       "9/21/2016            7.1\n",
       "9/24/2016            7.4\n",
       "9/27/2016            8.0\n",
       "9/3/2016             5.1\n",
       "9/30/2016            6.7\n",
       "9/6/2016             9.7\n",
       "9/9/2016            15.5\n",
       "\n",
       "[121 rows x 1 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "south = pd.DataFrame(data = south['PM2.5 - Local Conditions'], dtype = None, copy = False)\n",
    "south.columns = ['south_PM25']\n",
    "south"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>south_PM25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>121.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9.519008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.337630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>6.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>7.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>11.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>47.400000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       south_PM25\n",
       "count  121.000000\n",
       "mean     9.519008\n",
       "std      6.337630\n",
       "min      2.200000\n",
       "25%      6.100000\n",
       "50%      7.900000\n",
       "75%     11.700000\n",
       "max     47.400000"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "south.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a0a2def0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Comparing distributions of PM2.5 values for north versus south Columbus. Red is south; blue is north.\n",
    "fig = plt.figure()\n",
    "plt.hist(north.north_PM25, bins=50, normed=1, alpha=0.5, color='b', label='North')\n",
    "plt.hist(south.south_PM25, bins=50, normed=1, alpha=0.5, color='r', label='South')\n",
    "plt.title('Distribution of PM2.5 Values in North vs. South Columbus')\n",
    "plt.xlabel('PM2.5 (mg/m3)')\n",
    "plt.ylabel('Frequency')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "fig.savefig('north_and_south_histogram.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2e9a1d1b2e8>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Nw+D6hum9BcNmo2DNWqK9vUQHBuYyXCFEjkq3p/BPwDuAw0qpbymlLs5gTGIGXf1BqsN+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\nra/SWm8H9gLvB36dD23DSnj3Aiil6rF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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a0a2d400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(north.north_PM25, bins=50, color='b', label='North')\n",
    "sns.distplot(south.south_PM25, bins=50, color='r', label='South')\n",
    "plt.xlabel('PM2.5 (mg/m3)')\n",
    "plt.ylabel('Frequency')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2e9a1d2df98>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QRjb6GlAMfEMpNTb2/gXgnyzQtt8A/6aUehFwAv9ArD1W+L5Nxio/\nkwA/Bn6ilHqZ2OyYTwGdmNw+WfJXCCEsSIZlhBDCgiTchRDCgiTchRDCgiTchRDCgiTchRDCgiTc\nhRDCgiTchRDCgv4/T+HrgeF0X64AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a0a22278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.kdeplot(north.north_PM25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\statsmodels\\nonparametric\\kdetools.py:20: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
      "  y = X[:m/2+1] + np.r_[0,X[m/2+1:],0]*1j\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2e9a08c1e48>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4z9S8bvYhUikthSzztZfGAXjLG0bqXElreLr497ld/RE/7zy6j5dOz/DyuXme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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9a081ff60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(south.south_PM25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>BURN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2016-01-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2016-01-04</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE  BURN\n",
       "0 2016-01-01     0\n",
       "1 2016-01-02     0\n",
       "2 2016-01-03     0\n",
       "3 2016-01-04     0\n",
       "4 2016-01-05     1"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "burns = pd.read_excel('prescribed_burn_dummy.xlsx')\n",
    "burns = pd.DataFrame(burns)\n",
    "burns.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rng2 = pd.date_range('01/01/2016', periods=len(burns), freq='D')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>BURN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-02</th>\n",
       "      <td>2016-01-02</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-03</th>\n",
       "      <td>2016-01-03</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-04</th>\n",
       "      <td>2016-01-04</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-05</th>\n",
       "      <td>2016-01-05</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 DATE  BURN\n",
       "2016-01-01 2016-01-01     0\n",
       "2016-01-02 2016-01-02     0\n",
       "2016-01-03 2016-01-03     0\n",
       "2016-01-04 2016-01-04     0\n",
       "2016-01-05 2016-01-05     1"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "burns_ts = burns.set_index(rng2)\n",
    "burns_ts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>north_PM25</th>\n",
       "      <th>south_PM25</th>\n",
       "      <th>DATE</th>\n",
       "      <th>BURN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date (Local)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>6.4</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-10</th>\n",
       "      <td>2.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2016-01-10</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-13</th>\n",
       "      <td>9.8</td>\n",
       "      <td>7.7</td>\n",
       "      <td>2016-01-13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-16</th>\n",
       "      <td>6.7</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2016-01-16</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-22</th>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2016-01-22</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              north_PM25  south_PM25       DATE  BURN\n",
       "Date (Local)                                         \n",
       "2016-01-01           6.4         7.4 2016-01-01     0\n",
       "2016-01-10           2.2         2.3 2016-01-10     0\n",
       "2016-01-13           9.8         7.7 2016-01-13     1\n",
       "2016-01-16           6.7         7.3 2016-01-16     0\n",
       "2016-01-22           5.0         5.0 2016-01-22     0"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "north_south = north.join(south)\n",
    "north_south = north_south.join(burns_ts)\n",
    "north_south.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>north_PM25</th>\n",
       "      <th>south_PM25</th>\n",
       "      <th>BURN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date (Local)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>6.4</td>\n",
       "      <td>7.4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-10</th>\n",
       "      <td>2.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-13</th>\n",
       "      <td>9.8</td>\n",
       "      <td>7.7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-16</th>\n",
       "      <td>6.7</td>\n",
       "      <td>7.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-22</th>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              north_PM25  south_PM25  BURN\n",
       "Date (Local)                              \n",
       "2016-01-01           6.4         7.4     0\n",
       "2016-01-10           2.2         2.3     0\n",
       "2016-01-13           9.8         7.7     1\n",
       "2016-01-16           6.7         7.3     0\n",
       "2016-01-22           5.0         5.0     0"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "north_south = north_south.drop('DATE', axis = 1)\n",
    "north_south.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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VF1qxqV9pRT3qQXoz1Hd+79eTPMM0FdZ1ocbk8qRfOu73krJkrRT1MoioEICfsMYVFTdM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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9bc7b0b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "plt.subplot(211)\n",
    "plt.plot_date(x=north_south.index, y=north_south.north_PM25, c='b')\n",
    "plt.subplot(212)\n",
    "plt.plot_date(x=north_south.index, y=north_south.south_PM25, c='r')\n",
    "plt.show()\n",
    "fig.savefig('north_south_time_series.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9bc870e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Days of prescribed burns\n",
    "plt.plot_date(x=north_south.index, y=north_south.BURN)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## Start of Linear Regression section##"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>USAF</th>\n",
       "      <th>WBAN</th>\n",
       "      <th>YR--MODAHRMN</th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DIR</th>\n",
       "      <th>SPD</th>\n",
       "      <th>GUS</th>\n",
       "      <th>CLG</th>\n",
       "      <th>SKC</th>\n",
       "      <th>...</th>\n",
       "      <th>SLP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>STP</th>\n",
       "      <th>MAX</th>\n",
       "      <th>MIN</th>\n",
       "      <th>PCP01</th>\n",
       "      <th>PCP06</th>\n",
       "      <th>PCP24</th>\n",
       "      <th>PCPXX</th>\n",
       "      <th>SD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060051</td>\n",
       "      <td>20160306</td>\n",
       "      <td>51</td>\n",
       "      <td>290</td>\n",
       "      <td>5</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1019.8</td>\n",
       "      <td>30.12</td>\n",
       "      <td>1005.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060151</td>\n",
       "      <td>20160306</td>\n",
       "      <td>151</td>\n",
       "      <td>320</td>\n",
       "      <td>5</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1020.6</td>\n",
       "      <td>30.14</td>\n",
       "      <td>1006.2</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060251</td>\n",
       "      <td>20160306</td>\n",
       "      <td>251</td>\n",
       "      <td>320</td>\n",
       "      <td>3</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.3</td>\n",
       "      <td>30.16</td>\n",
       "      <td>1006.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060351</td>\n",
       "      <td>20160306</td>\n",
       "      <td>351</td>\n",
       "      <td>***</td>\n",
       "      <td>0</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.2</td>\n",
       "      <td>30.16</td>\n",
       "      <td>1006.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060451</td>\n",
       "      <td>20160306</td>\n",
       "      <td>451</td>\n",
       "      <td>***</td>\n",
       "      <td>0</td>\n",
       "      <td>***</td>\n",
       "      <td>70</td>\n",
       "      <td>***</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.7</td>\n",
       "      <td>30.17</td>\n",
       "      <td>1007.2</td>\n",
       "      <td>66</td>\n",
       "      <td>35</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060551</td>\n",
       "      <td>20160306</td>\n",
       "      <td>551</td>\n",
       "      <td>***</td>\n",
       "      <td>0</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.5</td>\n",
       "      <td>30.17</td>\n",
       "      <td>1007.2</td>\n",
       "      <td>61</td>\n",
       "      <td>46</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060651</td>\n",
       "      <td>20160306</td>\n",
       "      <td>651</td>\n",
       "      <td>***</td>\n",
       "      <td>0</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022</td>\n",
       "      <td>30.18</td>\n",
       "      <td>1007.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060751</td>\n",
       "      <td>20160306</td>\n",
       "      <td>751</td>\n",
       "      <td>***</td>\n",
       "      <td>0</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.9</td>\n",
       "      <td>30.18</td>\n",
       "      <td>1007.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060851</td>\n",
       "      <td>20160306</td>\n",
       "      <td>851</td>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.8</td>\n",
       "      <td>30.18</td>\n",
       "      <td>1007.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603060951</td>\n",
       "      <td>20160306</td>\n",
       "      <td>951</td>\n",
       "      <td>***</td>\n",
       "      <td>0</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.2</td>\n",
       "      <td>30.19</td>\n",
       "      <td>1007.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061051</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1051</td>\n",
       "      <td>360</td>\n",
       "      <td>3</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1023</td>\n",
       "      <td>30.21</td>\n",
       "      <td>1008.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061151</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1151</td>\n",
       "      <td>320</td>\n",
       "      <td>6</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1024.4</td>\n",
       "      <td>30.25</td>\n",
       "      <td>1009.9</td>\n",
       "      <td>47</td>\n",
       "      <td>40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061251</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1251</td>\n",
       "      <td>320</td>\n",
       "      <td>7</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1025</td>\n",
       "      <td>30.27</td>\n",
       "      <td>1010.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061351</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1351</td>\n",
       "      <td>360</td>\n",
       "      <td>7</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1025.2</td>\n",
       "      <td>30.28</td>\n",
       "      <td>1010.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061451</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1451</td>\n",
       "      <td>20</td>\n",
       "      <td>9</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1025</td>\n",
       "      <td>30.28</td>\n",
       "      <td>1010.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061551</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1551</td>\n",
       "      <td>30</td>\n",
       "      <td>15</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1025.1</td>\n",
       "      <td>30.28</td>\n",
       "      <td>1010.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061651</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1651</td>\n",
       "      <td>20</td>\n",
       "      <td>9</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1024.7</td>\n",
       "      <td>30.27</td>\n",
       "      <td>1010.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061751</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1751</td>\n",
       "      <td>140</td>\n",
       "      <td>6</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1024</td>\n",
       "      <td>30.25</td>\n",
       "      <td>1009.9</td>\n",
       "      <td>65</td>\n",
       "      <td>40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061851</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1851</td>\n",
       "      <td>60</td>\n",
       "      <td>6</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.8</td>\n",
       "      <td>30.21</td>\n",
       "      <td>1008.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603061951</td>\n",
       "      <td>20160306</td>\n",
       "      <td>1951</td>\n",
       "      <td>60</td>\n",
       "      <td>8</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.2</td>\n",
       "      <td>30.19</td>\n",
       "      <td>1007.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603062051</td>\n",
       "      <td>20160306</td>\n",
       "      <td>2051</td>\n",
       "      <td>60</td>\n",
       "      <td>3</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.6</td>\n",
       "      <td>30.17</td>\n",
       "      <td>1007.2</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603062151</td>\n",
       "      <td>20160306</td>\n",
       "      <td>2151</td>\n",
       "      <td>990</td>\n",
       "      <td>5</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.5</td>\n",
       "      <td>30.17</td>\n",
       "      <td>1007.2</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603062251</td>\n",
       "      <td>20160306</td>\n",
       "      <td>2251</td>\n",
       "      <td>***</td>\n",
       "      <td>0</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1021.8</td>\n",
       "      <td>30.18</td>\n",
       "      <td>1007.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603062351</td>\n",
       "      <td>20160306</td>\n",
       "      <td>2351</td>\n",
       "      <td>140</td>\n",
       "      <td>3</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.3</td>\n",
       "      <td>30.19</td>\n",
       "      <td>1007.9</td>\n",
       "      <td>71</td>\n",
       "      <td>64</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603070051</td>\n",
       "      <td>20160307</td>\n",
       "      <td>51</td>\n",
       "      <td>80</td>\n",
       "      <td>6</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.8</td>\n",
       "      <td>30.21</td>\n",
       "      <td>1008.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      USAF   WBAN  YR--MODAHRMN      DATE  TIME  DIR SPD  GUS  CLG  SKC ...  \\\n",
       "0   722255  93842  201603060051  20160306    51  290   5  ***  722  CLR ...   \n",
       "1   722255  93842  201603060151  20160306   151  320   5  ***  722  CLR ...   \n",
       "2   722255  93842  201603060251  20160306   251  320   3  ***  722  CLR ...   \n",
       "3   722255  93842  201603060351  20160306   351  ***   0  ***  722  CLR ...   \n",
       "4   722255  93842  201603060451  20160306   451  ***   0  ***   70  *** ...   \n",
       "5   722255  93842  201603060551  20160306   551  ***   0  ***  722  CLR ...   \n",
       "6   722255  93842  201603060651  20160306   651  ***   0  ***  722  CLR ...   \n",
       "7   722255  93842  201603060751  20160306   751  ***   0  ***  722  CLR ...   \n",
       "8   722255  93842  201603060851  20160306   851   20   3  ***  722  CLR ...   \n",
       "9   722255  93842  201603060951  20160306   951  ***   0  ***  722  CLR ...   \n",
       "10  722255  93842  201603061051  20160306  1051  360   3  ***  722  CLR ...   \n",
       "11  722255  93842  201603061151  20160306  1151  320   6  ***  722  CLR ...   \n",
       "12  722255  93842  201603061251  20160306  1251  320   7  ***  722  CLR ...   \n",
       "13  722255  93842  201603061351  20160306  1351  360   7  ***  722  CLR ...   \n",
       "14  722255  93842  201603061451  20160306  1451   20   9  ***  722  CLR ...   \n",
       "15  722255  93842  201603061551  20160306  1551   30  15  ***  722  CLR ...   \n",
       "16  722255  93842  201603061651  20160306  1651   20   9  ***  722  CLR ...   \n",
       "17  722255  93842  201603061751  20160306  1751  140   6  ***  722  CLR ...   \n",
       "18  722255  93842  201603061851  20160306  1851   60   6  ***  722  CLR ...   \n",
       "19  722255  93842  201603061951  20160306  1951   60   8  ***  722  CLR ...   \n",
       "20  722255  93842  201603062051  20160306  2051   60   3  ***  722  CLR ...   \n",
       "21  722255  93842  201603062151  20160306  2151  990   5  ***  722  CLR ...   \n",
       "22  722255  93842  201603062251  20160306  2251  ***   0  ***  722  CLR ...   \n",
       "23  722255  93842  201603062351  20160306  2351  140   3  ***  722  CLR ...   \n",
       "24  722255  93842  201603070051  20160307    51   80   6  ***  722  CLR ...   \n",
       "\n",
       "       SLP    ALT     STP  MAX  MIN PCP01  PCP06  PCP24  PCPXX  SD  \n",
       "0   1019.8  30.12  1005.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "1   1020.6  30.14  1006.2  ***  ***   0.0  *****  *****  *****  **  \n",
       "2   1021.3  30.16  1006.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "3   1021.2  30.16  1006.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "4   1021.7  30.17  1007.2   66   35   0.0  *****  *****  *****  **  \n",
       "5   1021.5  30.17  1007.2   61   46   0.0  *****  *****  *****  **  \n",
       "6     1022  30.18  1007.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "7   1021.9  30.18  1007.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "8   1021.8  30.18  1007.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "9   1022.2  30.19  1007.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "10    1023  30.21  1008.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "11  1024.4  30.25  1009.9   47   40   0.0  *****  *****  *****  **  \n",
       "12    1025  30.27  1010.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "13  1025.2  30.28  1010.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "14    1025  30.28  1010.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "15  1025.1  30.28  1010.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "16  1024.7  30.27  1010.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "17    1024  30.25  1009.9   65   40   0.0  *****  *****  *****  **  \n",
       "18  1022.8  30.21  1008.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "19  1022.2  30.19  1007.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "20  1021.6  30.17  1007.2  ***  ***   0.0  *****  *****  *****  **  \n",
       "21  1021.5  30.17  1007.2  ***  ***   0.0  *****  *****  *****  **  \n",
       "22  1021.8  30.18  1007.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "23  1022.3  30.19  1007.9   71   64   0.0  *****  *****  *****  **  \n",
       "24  1022.8  30.21  1008.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "\n",
       "[25 rows x 35 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Uploading weather data recorded by the National Weather Service at Columbus Airport.\n",
    "#Observations are made at 9 minutes til the hour, every hour.\n",
    "weather = pd.read_excel('columbus_weather.xlsx')\n",
    "weather = pd.DataFrame(weather)\n",
    "weather.head(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "      <td>722255</td>\n",
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       "      <td>201603070951</td>\n",
       "      <td>20160307</td>\n",
       "      <td>951</td>\n",
       "      <td>90</td>\n",
       "      <td>3</td>\n",
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       "      <td>CLR</td>\n",
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       "      <td>1024.3</td>\n",
       "      <td>30.25</td>\n",
       "      <td>1009.9</td>\n",
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       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>722255</td>\n",
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       "      <td>722255</td>\n",
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       "      <td>1151</td>\n",
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       "      <td>1251</td>\n",
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       "      <td>CLR</td>\n",
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       "      <td>***</td>\n",
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       "      <td>1027.1</td>\n",
       "      <td>30.34</td>\n",
       "      <td>1012.9</td>\n",
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       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
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       "      <th>40</th>\n",
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       "      <td>20160307</td>\n",
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       "      <td>8</td>\n",
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       "      <td>***</td>\n",
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       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
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       "      <th>41</th>\n",
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       "      <td>20160307</td>\n",
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       "      <td>1011.3</td>\n",
       "      <td>68</td>\n",
       "      <td>41</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
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       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>722255</td>\n",
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       "      <td>20160307</td>\n",
       "      <td>1851</td>\n",
       "      <td>210</td>\n",
       "      <td>9</td>\n",
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       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1024.2</td>\n",
       "      <td>30.25</td>\n",
       "      <td>1009.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
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       "      <td>201603071951</td>\n",
       "      <td>20160307</td>\n",
       "      <td>1951</td>\n",
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       "      <td>7</td>\n",
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       "      <td>30.23</td>\n",
       "      <td>1009.2</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603072051</td>\n",
       "      <td>20160307</td>\n",
       "      <td>2051</td>\n",
       "      <td>190</td>\n",
       "      <td>5</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.8</td>\n",
       "      <td>30.21</td>\n",
       "      <td>1008.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603072151</td>\n",
       "      <td>20160307</td>\n",
       "      <td>2151</td>\n",
       "      <td>170</td>\n",
       "      <td>7</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.4</td>\n",
       "      <td>30.2</td>\n",
       "      <td>1008.2</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603072251</td>\n",
       "      <td>20160307</td>\n",
       "      <td>2251</td>\n",
       "      <td>180</td>\n",
       "      <td>10</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.5</td>\n",
       "      <td>30.2</td>\n",
       "      <td>1008.2</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603072351</td>\n",
       "      <td>20160307</td>\n",
       "      <td>2351</td>\n",
       "      <td>160</td>\n",
       "      <td>6</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.9</td>\n",
       "      <td>30.21</td>\n",
       "      <td>1008.6</td>\n",
       "      <td>72</td>\n",
       "      <td>66</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>25 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      USAF   WBAN  YR--MODAHRMN      DATE  TIME  DIR SPD  GUS  CLG  SKC ...  \\\n",
       "23  722255  93842  201603062351  20160306  2351  140   3  ***  722  CLR ...   \n",
       "24  722255  93842  201603070051  20160307    51   80   6  ***  722  CLR ...   \n",
       "25  722255  93842  201603070151  20160307   151  100   5  ***  722  CLR ...   \n",
       "26  722255  93842  201603070251  20160307   251   90   5  ***  722  CLR ...   \n",
       "27  722255  93842  201603070351  20160307   351   70   5  ***  722  CLR ...   \n",
       "28  722255  93842  201603070451  20160307   451  ***   0  ***  722  CLR ...   \n",
       "29  722255  93842  201603070551  20160307   551  ***   0  ***  722  CLR ...   \n",
       "30  722255  93842  201603070651  20160307   651  ***   0  ***  722  CLR ...   \n",
       "31  722255  93842  201603070751  20160307   751   70   3  ***  722  CLR ...   \n",
       "32  722255  93842  201603070851  20160307   851   90   5  ***  722  CLR ...   \n",
       "33  722255  93842  201603070951  20160307   951   90   3  ***  722  CLR ...   \n",
       "34  722255  93842  201603071051  20160307  1051   60   3  ***  722  CLR ...   \n",
       "35  722255  93842  201603071151  20160307  1151   90   5  ***  722  CLR ...   \n",
       "36  722255  93842  201603071251  20160307  1251   80   3  ***  722  CLR ...   \n",
       "37  722255  93842  201603071351  20160307  1351  130   7  ***  722  CLR ...   \n",
       "38  722255  93842  201603071451  20160307  1451  170   7  ***  722  CLR ...   \n",
       "39  722255  93842  201603071551  20160307  1551  190  13  ***  722  CLR ...   \n",
       "40  722255  93842  201603071651  20160307  1651  190   8  ***  722  CLR ...   \n",
       "41  722255  93842  201603071751  20160307  1751  200   9  ***  722  CLR ...   \n",
       "42  722255  93842  201603071851  20160307  1851  210   9  ***  722  CLR ...   \n",
       "43  722255  93842  201603071951  20160307  1951  160   7  ***  722  CLR ...   \n",
       "44  722255  93842  201603072051  20160307  2051  190   5  ***  722  CLR ...   \n",
       "45  722255  93842  201603072151  20160307  2151  170   7  ***  722  CLR ...   \n",
       "46  722255  93842  201603072251  20160307  2251  180  10  ***  722  CLR ...   \n",
       "47  722255  93842  201603072351  20160307  2351  160   6  ***  722  CLR ...   \n",
       "\n",
       "       SLP    ALT     STP  MAX  MIN PCP01  PCP06  PCP24  PCPXX  SD  \n",
       "23  1022.3  30.19  1007.9   71   64   0.0  *****  *****  *****  **  \n",
       "24  1022.8  30.21  1008.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "25  1023.3  30.23  1009.2  ***  ***   0.0  *****  *****  *****  **  \n",
       "26  1023.8  30.24  1009.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "27  1024.1  30.25  1009.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "28  1023.7  30.24  1009.6   71   40   0.0  *****  *****  *****  **  \n",
       "29  1023.9  30.24  1009.6   65   46   0.0  *****  *****  *****  **  \n",
       "30  1023.8  30.24  1009.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "31  1023.7  30.24  1009.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "32  1023.7  30.24  1009.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "33  1024.3  30.25  1009.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "34  1024.8  30.27  1010.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "35  1025.2  30.28  1010.9   48   42   0.0  *****  *****  *****  **  \n",
       "36  1026.2  30.31  1011.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "37  1026.6  30.32  1012.3  ***  ***   0.0  *****  *****  *****  **  \n",
       "38    1027  30.33  1012.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "39  1027.1  30.34  1012.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "40  1026.6  30.32  1012.3  ***  ***   0.0  *****  *****  *****  **  \n",
       "41  1025.6  30.29  1011.3   68   41   0.0  *****  *****  *****  **  \n",
       "42  1024.2  30.25  1009.9  ***  ***   0.0  *****  *****  *****  **  \n",
       "43  1023.3  30.23  1009.2  ***  ***   0.0  *****  *****  *****  **  \n",
       "44  1022.8  30.21  1008.6  ***  ***   0.0  *****  *****  *****  **  \n",
       "45  1022.4   30.2  1008.2  ***  ***   0.0  *****  *****  *****  **  \n",
       "46  1022.5   30.2  1008.2  ***  ***   0.0  *****  *****  *****  **  \n",
       "47  1022.9  30.21  1008.6   72   66   0.0  *****  *****  *****  **  \n",
       "\n",
       "[25 rows x 35 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Dropping the first 22 rows to get a clean start for the time series at midnight of March 7, 2016.\n",
    "weather = weather.drop(weather.index[0:23])\n",
    "weather.head(25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>USAF</th>\n",
       "      <th>WBAN</th>\n",
       "      <th>YR--MODAHRMN</th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>CLG</th>\n",
       "      <th>VSB</th>\n",
       "      <th>PCP01</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>9286.0</td>\n",
       "      <td>9286.0</td>\n",
       "      <td>9.286000e+03</td>\n",
       "      <td>9.286000e+03</td>\n",
       "      <td>9286.000000</td>\n",
       "      <td>9286.000000</td>\n",
       "      <td>9286.000000</td>\n",
       "      <td>9286.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>722255.0</td>\n",
       "      <td>93842.0</td>\n",
       "      <td>2.016290e+11</td>\n",
       "      <td>2.016290e+07</td>\n",
       "      <td>1201.215378</td>\n",
       "      <td>542.498815</td>\n",
       "      <td>9.685602</td>\n",
       "      <td>0.004544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.947250e+07</td>\n",
       "      <td>3.947250e+03</td>\n",
       "      <td>692.362720</td>\n",
       "      <td>299.958762</td>\n",
       "      <td>1.326208</td>\n",
       "      <td>0.039348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>722255.0</td>\n",
       "      <td>93842.0</td>\n",
       "      <td>2.016031e+11</td>\n",
       "      <td>2.016031e+07</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>722255.0</td>\n",
       "      <td>93842.0</td>\n",
       "      <td>2.016061e+11</td>\n",
       "      <td>2.016061e+07</td>\n",
       "      <td>651.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>722255.0</td>\n",
       "      <td>93842.0</td>\n",
       "      <td>2.016092e+11</td>\n",
       "      <td>2.016092e+07</td>\n",
       "      <td>1201.000000</td>\n",
       "      <td>722.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>722255.0</td>\n",
       "      <td>93842.0</td>\n",
       "      <td>2.016122e+11</td>\n",
       "      <td>2.016122e+07</td>\n",
       "      <td>1851.000000</td>\n",
       "      <td>722.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>722255.0</td>\n",
       "      <td>93842.0</td>\n",
       "      <td>2.017033e+11</td>\n",
       "      <td>2.017033e+07</td>\n",
       "      <td>2351.000000</td>\n",
       "      <td>722.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>1.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           USAF     WBAN  YR--MODAHRMN          DATE         TIME  \\\n",
       "count    9286.0   9286.0  9.286000e+03  9.286000e+03  9286.000000   \n",
       "mean   722255.0  93842.0  2.016290e+11  2.016290e+07  1201.215378   \n",
       "std         0.0      0.0  3.947250e+07  3.947250e+03   692.362720   \n",
       "min    722255.0  93842.0  2.016031e+11  2.016031e+07    51.000000   \n",
       "25%    722255.0  93842.0  2.016061e+11  2.016061e+07   651.000000   \n",
       "50%    722255.0  93842.0  2.016092e+11  2.016092e+07  1201.000000   \n",
       "75%    722255.0  93842.0  2.016122e+11  2.016122e+07  1851.000000   \n",
       "max    722255.0  93842.0  2.017033e+11  2.017033e+07  2351.000000   \n",
       "\n",
       "               CLG          VSB        PCP01  \n",
       "count  9286.000000  9286.000000  9286.000000  \n",
       "mean    542.498815     9.685602     0.004544  \n",
       "std     299.958762     1.326208     0.039348  \n",
       "min       1.000000     0.000000     0.000000  \n",
       "25%     100.000000    10.000000     0.000000  \n",
       "50%     722.000000    10.000000     0.000000  \n",
       "75%     722.000000    10.000000     0.000000  \n",
       "max     722.000000    10.000000     1.500000  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weather.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "rng = pd.date_range('03/07/2016', periods=len(weather), freq='H')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>USAF</th>\n",
       "      <th>WBAN</th>\n",
       "      <th>YR--MODAHRMN</th>\n",
       "      <th>DATE</th>\n",
       "      <th>TIME</th>\n",
       "      <th>DIR</th>\n",
       "      <th>SPD</th>\n",
       "      <th>GUS</th>\n",
       "      <th>CLG</th>\n",
       "      <th>SKC</th>\n",
       "      <th>...</th>\n",
       "      <th>SLP</th>\n",
       "      <th>ALT</th>\n",
       "      <th>STP</th>\n",
       "      <th>MAX</th>\n",
       "      <th>MIN</th>\n",
       "      <th>PCP01</th>\n",
       "      <th>PCP06</th>\n",
       "      <th>PCP24</th>\n",
       "      <th>PCPXX</th>\n",
       "      <th>SD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-03-07 00:00:00</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603062351</td>\n",
       "      <td>20160306</td>\n",
       "      <td>2351</td>\n",
       "      <td>140</td>\n",
       "      <td>3</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.3</td>\n",
       "      <td>30.19</td>\n",
       "      <td>1007.9</td>\n",
       "      <td>71</td>\n",
       "      <td>64</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 01:00:00</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603070051</td>\n",
       "      <td>20160307</td>\n",
       "      <td>51</td>\n",
       "      <td>80</td>\n",
       "      <td>6</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1022.8</td>\n",
       "      <td>30.21</td>\n",
       "      <td>1008.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 02:00:00</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603070151</td>\n",
       "      <td>20160307</td>\n",
       "      <td>151</td>\n",
       "      <td>100</td>\n",
       "      <td>5</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1023.3</td>\n",
       "      <td>30.23</td>\n",
       "      <td>1009.2</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 03:00:00</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603070251</td>\n",
       "      <td>20160307</td>\n",
       "      <td>251</td>\n",
       "      <td>90</td>\n",
       "      <td>5</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1023.8</td>\n",
       "      <td>30.24</td>\n",
       "      <td>1009.6</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 04:00:00</th>\n",
       "      <td>722255</td>\n",
       "      <td>93842</td>\n",
       "      <td>201603070351</td>\n",
       "      <td>20160307</td>\n",
       "      <td>351</td>\n",
       "      <td>70</td>\n",
       "      <td>5</td>\n",
       "      <td>***</td>\n",
       "      <td>722</td>\n",
       "      <td>CLR</td>\n",
       "      <td>...</td>\n",
       "      <td>1024.1</td>\n",
       "      <td>30.25</td>\n",
       "      <td>1009.9</td>\n",
       "      <td>***</td>\n",
       "      <td>***</td>\n",
       "      <td>0.0</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>*****</td>\n",
       "      <td>**</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 35 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       USAF   WBAN  YR--MODAHRMN      DATE  TIME  DIR SPD  \\\n",
       "2016-03-07 00:00:00  722255  93842  201603062351  20160306  2351  140   3   \n",
       "2016-03-07 01:00:00  722255  93842  201603070051  20160307    51   80   6   \n",
       "2016-03-07 02:00:00  722255  93842  201603070151  20160307   151  100   5   \n",
       "2016-03-07 03:00:00  722255  93842  201603070251  20160307   251   90   5   \n",
       "2016-03-07 04:00:00  722255  93842  201603070351  20160307   351   70   5   \n",
       "\n",
       "                     GUS  CLG  SKC ...     SLP    ALT     STP  MAX  MIN PCP01  \\\n",
       "2016-03-07 00:00:00  ***  722  CLR ...  1022.3  30.19  1007.9   71   64   0.0   \n",
       "2016-03-07 01:00:00  ***  722  CLR ...  1022.8  30.21  1008.6  ***  ***   0.0   \n",
       "2016-03-07 02:00:00  ***  722  CLR ...  1023.3  30.23  1009.2  ***  ***   0.0   \n",
       "2016-03-07 03:00:00  ***  722  CLR ...  1023.8  30.24  1009.6  ***  ***   0.0   \n",
       "2016-03-07 04:00:00  ***  722  CLR ...  1024.1  30.25  1009.9  ***  ***   0.0   \n",
       "\n",
       "                     PCP06  PCP24  PCPXX  SD  \n",
       "2016-03-07 00:00:00  *****  *****  *****  **  \n",
       "2016-03-07 01:00:00  *****  *****  *****  **  \n",
       "2016-03-07 02:00:00  *****  *****  *****  **  \n",
       "2016-03-07 03:00:00  *****  *****  *****  **  \n",
       "2016-03-07 04:00:00  *****  *****  *****  **  \n",
       "\n",
       "[5 rows x 35 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Constructing a time series. This also rounds up the hourly observations, e.g. 13:59 becomes 14:00.\n",
    "weather_ts = weather.set_index(rng)\n",
    "weather_ts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#Replacing '*****' values with 0\n",
    "weather_ts = weather_ts.replace(to_replace='*****',value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "weather_ts = weather_ts.replace(to_replace='T*****',value=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "weather_ts = weather_ts.replace(to_replace='***',value='CLR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "weather_ts.loc[weather_ts.SPD == 'CLR', 'SPD'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "weather_ts.loc[weather_ts.TEMP == '****', 'TEMP'] = 'NaN'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "weather_ts.loc[weather_ts.DEWP == '****', 'DEWP'] = 'NaN'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "weather_ts.to_excel('weather_ts.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPD</th>\n",
       "      <th>SKC</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>DEWP</th>\n",
       "      <th>PCP01</th>\n",
       "      <th>PCP06</th>\n",
       "      <th>PCP24</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-03-07 00:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65</td>\n",
       "      <td>29</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 01:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>60</td>\n",
       "      <td>32</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 02:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>58</td>\n",
       "      <td>33</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 03:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>56</td>\n",
       "      <td>34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 04:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>51</td>\n",
       "      <td>35</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 05:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>48</td>\n",
       "      <td>36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 06:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>46</td>\n",
       "      <td>36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 07:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>47</td>\n",
       "      <td>36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 08:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>47</td>\n",
       "      <td>36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 09:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>45</td>\n",
       "      <td>36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 10:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>43</td>\n",
       "      <td>36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 11:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>45</td>\n",
       "      <td>37</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 12:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>44</td>\n",
       "      <td>37</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 13:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>47</td>\n",
       "      <td>39</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 14:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>50</td>\n",
       "      <td>42</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 15:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>57</td>\n",
       "      <td>42</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 16:00:00</th>\n",
       "      <td>13</td>\n",
       "      <td>CLR</td>\n",
       "      <td>62</td>\n",
       "      <td>41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 17:00:00</th>\n",
       "      <td>8</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65</td>\n",
       "      <td>41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 18:00:00</th>\n",
       "      <td>9</td>\n",
       "      <td>CLR</td>\n",
       "      <td>67</td>\n",
       "      <td>40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 19:00:00</th>\n",
       "      <td>9</td>\n",
       "      <td>CLR</td>\n",
       "      <td>69</td>\n",
       "      <td>40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 20:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>71</td>\n",
       "      <td>39</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 21:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>71</td>\n",
       "      <td>37</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 22:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>72</td>\n",
       "      <td>37</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 23:00:00</th>\n",
       "      <td>10</td>\n",
       "      <td>CLR</td>\n",
       "      <td>71</td>\n",
       "      <td>36</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-08 00:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>66</td>\n",
       "      <td>38</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-08 01:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>63</td>\n",
       "      <td>38</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-08 02:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>61</td>\n",
       "      <td>40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-08 03:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>60</td>\n",
       "      <td>40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-08 04:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>57</td>\n",
       "      <td>41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-08 05:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>56</td>\n",
       "      <td>42</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 14:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>64</td>\n",
       "      <td>63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 15:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65</td>\n",
       "      <td>65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 16:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>67</td>\n",
       "      <td>65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 17:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>68</td>\n",
       "      <td>64</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 18:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>68</td>\n",
       "      <td>62</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 19:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>68</td>\n",
       "      <td>61</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 20:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>68</td>\n",
       "      <td>60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 21:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>71</td>\n",
       "      <td>60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 22:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>71</td>\n",
       "      <td>58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-26 23:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>71</td>\n",
       "      <td>57</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 00:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>68</td>\n",
       "      <td>59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 01:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>67</td>\n",
       "      <td>59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 02:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>66</td>\n",
       "      <td>60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 03:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65</td>\n",
       "      <td>60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 04:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>64</td>\n",
       "      <td>60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 05:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>63</td>\n",
       "      <td>59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 06:00:00</th>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>63</td>\n",
       "      <td>59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 07:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>63</td>\n",
       "      <td>58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 08:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>60</td>\n",
       "      <td>58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 09:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>61</td>\n",
       "      <td>58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 10:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>61</td>\n",
       "      <td>58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 11:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>62</td>\n",
       "      <td>58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 12:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>62</td>\n",
       "      <td>58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 13:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>63</td>\n",
       "      <td>59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 14:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>63</td>\n",
       "      <td>59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 15:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>64</td>\n",
       "      <td>60</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 16:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65</td>\n",
       "      <td>61</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 17:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>66</td>\n",
       "      <td>61</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 18:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65</td>\n",
       "      <td>62</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-27 19:00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>64</td>\n",
       "      <td>63</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    SPD  SKC TEMP DEWP  PCP01 PCP06 PCP24\n",
       "2016-03-07 00:00:00   3  CLR   65   29   0.00     0     0\n",
       "2016-03-07 01:00:00   6  CLR   60   32   0.00     0     0\n",
       "2016-03-07 02:00:00   5  CLR   58   33   0.00     0     0\n",
       "2016-03-07 03:00:00   5  CLR   56   34   0.00     0     0\n",
       "2016-03-07 04:00:00   5  CLR   51   35   0.00     0     0\n",
       "2016-03-07 05:00:00   0  CLR   48   36   0.00     0     0\n",
       "2016-03-07 06:00:00   0  CLR   46   36   0.00     0     0\n",
       "2016-03-07 07:00:00   0  CLR   47   36   0.00     0     0\n",
       "2016-03-07 08:00:00   3  CLR   47   36   0.00     0     0\n",
       "2016-03-07 09:00:00   5  CLR   45   36   0.00     0     0\n",
       "2016-03-07 10:00:00   3  CLR   43   36   0.00     0     0\n",
       "2016-03-07 11:00:00   3  CLR   45   37   0.00     0     0\n",
       "2016-03-07 12:00:00   5  CLR   44   37   0.00     0     0\n",
       "2016-03-07 13:00:00   3  CLR   47   39   0.00     0     0\n",
       "2016-03-07 14:00:00   7  CLR   50   42   0.00     0     0\n",
       "2016-03-07 15:00:00   7  CLR   57   42   0.00     0     0\n",
       "2016-03-07 16:00:00  13  CLR   62   41   0.00     0     0\n",
       "2016-03-07 17:00:00   8  CLR   65   41   0.00     0     0\n",
       "2016-03-07 18:00:00   9  CLR   67   40   0.00     0     0\n",
       "2016-03-07 19:00:00   9  CLR   69   40   0.00     0     0\n",
       "2016-03-07 20:00:00   7  CLR   71   39   0.00     0     0\n",
       "2016-03-07 21:00:00   5  CLR   71   37   0.00     0     0\n",
       "2016-03-07 22:00:00   7  CLR   72   37   0.00     0     0\n",
       "2016-03-07 23:00:00  10  CLR   71   36   0.00     0     0\n",
       "2016-03-08 00:00:00   6  CLR   66   38   0.00     0     0\n",
       "2016-03-08 01:00:00   5  CLR   63   38   0.00     0     0\n",
       "2016-03-08 02:00:00   0  CLR   61   40   0.00     0     0\n",
       "2016-03-08 03:00:00   5  CLR   60   40   0.00     0     0\n",
       "2016-03-08 04:00:00   5  CLR   57   41   0.00     0     0\n",
       "2016-03-08 05:00:00   0  CLR   56   42   0.00     0     0\n",
       "...                  ..  ...  ...  ...    ...   ...   ...\n",
       "2016-03-26 14:00:00   3  CLR   64   63   0.00     0     0\n",
       "2016-03-26 15:00:00   5  CLR   65   65   0.00     0     0\n",
       "2016-03-26 16:00:00   5  CLR   67   65   0.00     0     0\n",
       "2016-03-26 17:00:00   5  CLR   68   64   0.00     0     0\n",
       "2016-03-26 18:00:00   7  CLR   68   62   0.00  0.03     0\n",
       "2016-03-26 19:00:00   3  CLR   68   61   0.00     0     0\n",
       "2016-03-26 20:00:00   3  CLR   68   60   0.00     0     0\n",
       "2016-03-26 21:00:00   0  CLR   71   60   0.00     0     0\n",
       "2016-03-26 22:00:00   5  CLR   71   58   0.00     0     0\n",
       "2016-03-26 23:00:00   7  CLR   71   57   0.00     0     0\n",
       "2016-03-27 00:00:00   6  CLR   68   59   0.00     0     0\n",
       "2016-03-27 01:00:00   5  CLR   67   59   0.00     0     0\n",
       "2016-03-27 02:00:00   0  CLR   66   60   0.00     0     0\n",
       "2016-03-27 03:00:00   6  CLR   65   60   0.00     0     0\n",
       "2016-03-27 04:00:00   6  CLR   64   60   0.00     0     0\n",
       "2016-03-27 05:00:00   6  CLR   63   59   0.00     0     0\n",
       "2016-03-27 06:00:00   7  CLR   63   59   0.00     0     0\n",
       "2016-03-27 07:00:00   3  CLR   63   58   0.00     0     0\n",
       "2016-03-27 08:00:00   0  CLR   60   58   0.00     0     0\n",
       "2016-03-27 09:00:00   3  CLR   61   58   0.00     0     0\n",
       "2016-03-27 10:00:00   5  CLR   61   58   0.00     0     0\n",
       "2016-03-27 11:00:00   0  CLR   62   58   0.00     0     0\n",
       "2016-03-27 12:00:00   5  CLR   62   58   0.00     0  0.03\n",
       "2016-03-27 13:00:00   6  CLR   63   59   0.00     0     0\n",
       "2016-03-27 14:00:00   5  CLR   63   59   0.00     0     0\n",
       "2016-03-27 15:00:00   3  CLR   64   60   0.00     0     0\n",
       "2016-03-27 16:00:00   3  CLR   65   61   0.00     0     0\n",
       "2016-03-27 17:00:00   0  CLR   66   61   0.00     0     0\n",
       "2016-03-27 18:00:00   3  CLR   65   62   0.03  0.03     0\n",
       "2016-03-27 19:00:00   0  CLR   64   63   0.10     0     0\n",
       "\n",
       "[500 rows x 7 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Narrowing down the dataframe to just weather attributes relevant to air quality.\n",
    "weather_ts = pd.DataFrame(weather_ts, index=weather_ts.index, columns=['SPD','SKC','TEMP','DEWP','PCP01','PCP06','PCP24'])\n",
    "weather_ts.head(500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPD</th>\n",
       "      <th>SKC</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>DEWP</th>\n",
       "      <th>PCP01</th>\n",
       "      <th>PCP06</th>\n",
       "      <th>PCP24</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-03-07 00:00:00</th>\n",
       "      <td>3</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 01:00:00</th>\n",
       "      <td>6</td>\n",
       "      <td>CLR</td>\n",
       "      <td>60.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 02:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>58.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 03:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>56.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-07 04:00:00</th>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>51.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     SPD  SKC  TEMP  DEWP  PCP01  PCP06  PCP24\n",
       "2016-03-07 00:00:00    3  CLR  65.0  29.0    0.0    0.0    0.0\n",
       "2016-03-07 01:00:00    6  CLR  60.0  32.0    0.0    0.0    0.0\n",
       "2016-03-07 02:00:00    5  CLR  58.0  33.0    0.0    0.0    0.0\n",
       "2016-03-07 03:00:00    5  CLR  56.0  34.0    0.0    0.0    0.0\n",
       "2016-03-07 04:00:00    5  CLR  51.0  35.0    0.0    0.0    0.0"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_weather = pd.read_excel('columbus_weather_cleaned2.xlsx')\n",
    "final_weather = pd.DataFrame(final_weather)\n",
    "final_weather.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>o3</th>\n",
       "      <th>pm25</th>\n",
       "      <th>SPD</th>\n",
       "      <th>SKC</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>DEWP</th>\n",
       "      <th>PCP01</th>\n",
       "      <th>PCP06</th>\n",
       "      <th>PCP24</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-03-15 00:00:00</th>\n",
       "      <td>0.027</td>\n",
       "      <td>15.6</td>\n",
       "      <td>7</td>\n",
       "      <td>CLR</td>\n",
       "      <td>76.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15 01:00:00</th>\n",
       "      <td>0.030</td>\n",
       "      <td>25.1</td>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>73.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15 02:00:00</th>\n",
       "      <td>0.028</td>\n",
       "      <td>20.7</td>\n",
       "      <td>5</td>\n",
       "      <td>CLR</td>\n",
       "      <td>71.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15 03:00:00</th>\n",
       "      <td>0.023</td>\n",
       "      <td>23.7</td>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>69.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-15 04:00:00</th>\n",
       "      <td>0.018</td>\n",
       "      <td>18.6</td>\n",
       "      <td>0</td>\n",
       "      <td>CLR</td>\n",
       "      <td>65.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        o3  pm25  SPD  SKC  TEMP  DEWP  PCP01  PCP06  PCP24\n",
       "2016-03-15 00:00:00  0.027  15.6    7  CLR  76.0  54.0    0.0    0.0    0.0\n",
       "2016-03-15 01:00:00  0.030  25.1    5  CLR  73.0  54.0    0.0    0.0    0.0\n",
       "2016-03-15 02:00:00  0.028  20.7    5  CLR  71.0  55.0    0.0    0.0    0.0\n",
       "2016-03-15 03:00:00  0.023  23.7    0  CLR  69.0  55.0    0.0    0.0    0.0\n",
       "2016-03-15 04:00:00  0.018  18.6    0  CLR  65.0  55.0    0.0    0.0    0.0"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Merging the air quality and meteorological data into one dataframe, now that they share a time series index.\n",
    "merged = aq_ts.join(final_weather)\n",
    "merged.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>o3</th>\n",
       "      <th>pm25</th>\n",
       "      <th>SPD</th>\n",
       "      <th>TEMP</th>\n",
       "      <th>DEWP</th>\n",
       "      <th>PCP01</th>\n",
       "      <th>PCP06</th>\n",
       "      <th>PCP24</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5361.000000</td>\n",
       "      <td>7548.000000</td>\n",
       "      <td>7869.000000</td>\n",
       "      <td>7869.000000</td>\n",
       "      <td>7869.000000</td>\n",
       "      <td>7869.000000</td>\n",
       "      <td>7869.000000</td>\n",
       "      <td>7869.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.031307</td>\n",
       "      <td>8.603630</td>\n",
       "      <td>5.541111</td>\n",
       "      <td>68.995933</td>\n",
       "      <td>54.564494</td>\n",
       "      <td>0.004835</td>\n",
       "      <td>0.004837</td>\n",
       "      <td>0.004832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.014412</td>\n",
       "      <td>8.044855</td>\n",
       "      <td>4.286718</td>\n",
       "      <td>14.319170</td>\n",
       "      <td>14.983140</td>\n",
       "      <td>0.041816</td>\n",
       "      <td>0.061199</td>\n",
       "      <td>0.080535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.021000</td>\n",
       "      <td>4.200000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>44.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.032000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>58.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>0.042000</td>\n",
       "      <td>10.900000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>67.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>0.083000</td>\n",
       "      <td>127.000000</td>\n",
       "      <td>31.000000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>79.000000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>2.610000</td>\n",
       "      <td>3.790000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                o3         pm25          SPD         TEMP         DEWP  \\\n",
       "count  5361.000000  7548.000000  7869.000000  7869.000000  7869.000000   \n",
       "mean      0.031307     8.603630     5.541111    68.995933    54.564494   \n",
       "std       0.014412     8.044855     4.286718    14.319170    14.983140   \n",
       "min       0.000000     0.200000     0.000000    19.000000     4.000000   \n",
       "25%       0.021000     4.200000     3.000000    60.000000    44.000000   \n",
       "50%       0.032000     7.000000     6.000000    71.000000    58.000000   \n",
       "75%       0.042000    10.900000     8.000000    79.000000    67.000000   \n",
       "max       0.083000   127.000000    31.000000    98.000000    79.000000   \n",
       "\n",
       "             PCP01        PCP06        PCP24  \n",
       "count  7869.000000  7869.000000  7869.000000  \n",
       "mean      0.004835     0.004837     0.004832  \n",
       "std       0.041816     0.061199     0.080535  \n",
       "min       0.000000     0.000000     0.000000  \n",
       "25%       0.000000     0.000000     0.000000  \n",
       "50%       0.000000     0.000000     0.000000  \n",
       "75%       0.000000     0.000000     0.000000  \n",
       "max       1.500000     2.610000     3.790000  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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NrYMdRlIWX3YKPT4o/BgtvoFLlZz8nP0EmIOruvkxcBAwLpNAVPUIVZ2pqrOA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\n01XTdHT6qxrzu73+1T5DqRo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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9b8466550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the relationship (or lack thereof) between particulate matter and whether it rained in the past HOUR.\n",
    "#Is there a relationship here? Hard to tell.\n",
    "plt.scatter(merged.PCP01, merged.pm25)\n",
    "plt.xlabel('Precipitation in previous hour (inches)')\n",
    "plt.ylabel('Particulate matter concentration')\n",
    "plt.title('PM2.5 vs. 1-hr Recent Precipitation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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gY2Q4GaRaotqWsDbGlLogA8jfFpFPAbW4h9qEcNNNvz/cg4nIKUCTqj4gIrFk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\nk1GykQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9ba3b4b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the relationship (or lack thereof) between particulate matter and whether it rained in the past DAY.\n",
    "plt.scatter(merged.PCP24, merged.pm25)\n",
    "plt.xlabel('Precipitation in previous day (inches)')\n",
    "plt.ylabel('Particulate matter concentration')\n",
    "plt.title('PM2.5 vs. 1-day Recent Precipitation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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RBvxcLrIS0of4GS/K4EHgNFXtAJYCvyK/6mdfAC5xN42DwM2q+gbwExzFcB/wNVUdzKNt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\nKcMwKo8ZLSEOlbaS1jxOxi/K4B3AXQC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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9ba420b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the relationship (or lack thereof) between particulate matter and temperature.\n",
    "#Look at the highest PM value at any given temp.\n",
    "#Below 50 degrees, people DO NOT leave their houses, nor are forest fires likely.\n",
    "plt.scatter(merged.TEMP, merged.pm25)\n",
    "plt.xlabel('Temperature (deg F)')\n",
    "plt.ylabel('Particulate matter concentration')\n",
    "plt.title('PM2.5 vs. Temperature')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5Ie34+asq5qjKMCqKOMqgTlUvTrwnCVJOninFznk/lYfjSZpzblzzgm/a8RvX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\nxyvviZiUvfLsSPjuxCt/JuDgNq48iM6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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9ba5ed940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Parrticulate matter versus wind speed.\n",
    "#Now that's what I call a signal! Wind blows the smoke away!\n",
    "plt.scatter(merged.SPD, merged.pm25)\n",
    "plt.xlabel('Wind speed (mph)')\n",
    "plt.ylabel('Particulate matter concentration')\n",
    "plt.title('PM2.5 vs. Wind Speed')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2e9ba6548d0>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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o4cHHnuf4qTnWruzldVedzyvU6podo1GCwQogf6xYWikV1lqn3Dae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\nEEIA/x89hqwzjeAU/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9b9fe4ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#So why is the regression line so boring and flat?\n",
    "#There are still lots of low PM values at each given wind speed. These overpower the strength of the signal.\n",
    "sns.regplot(x=\"SPD\", y=\"pm25\", data=merged)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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HXt2yk6aGWiJD4cdPjpzROXqTL8TCvWxr7ckfLbxbMRcaVvo6AJM/pT6hpBDC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\nMcZkzYKJMcaYrFkwMcYYk7X/D1lIeF5yE3f9AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9ba13ab70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Pure noise. Rain has no clearing effect on ozone.\n",
    "#And in fact, lightning significantly ADDS to ground level ozone.\n",
    "plt.scatter(merged.PCP01, merged.o3)\n",
    "plt.xlabel('Precipitation in previous hour (inches)')\n",
    "plt.ylabel('Ozone concentration')\n",
    "plt.title('O3 vs. 1-hr Recent Precipitation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xeU65sxBfMMALLw7z2Wvso7vrTS2DxsohMZniE9++v6bpzZXGZttT/bx1fcp1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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9ba5559e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plotting the relationship (or lack thereof) between ozone and temperature.\n",
    "#Again, pretty much noise. Perhaps a peak around 70 degrees, ideal outdoor recreation temps.\n",
    "plt.scatter(merged.TEMP, merged.o3)\n",
    "plt.xlabel('Temperature (deg F)')\n",
    "plt.ylabel('Ozone concentration')\n",
    "plt.title('O3 vs. Temperature')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rKnxLq9BbX24r7coo5orM5jfopxnZ3N9igeVYACT79f4Bk54PFwzhuCY9m2f2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\nrAgWIYQQyvoXgYRzQTOEPWsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2e9ba782b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Since wind did such a good job dissipating PM, how about ozone? NOPE.\n",
    "plt.scatter(merged.SPD, merged.o3)\n",
    "plt.xlabel('Wind speed (mph)')\n",
    "plt.ylabel('O3 concentration')\n",
    "plt.title('O3 vs. Wind Speed')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import statsmodels.api as sm\n",
    "from statsmodels.formula.api import ols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                   pm25   R-squared:                       0.000\n",
      "Model:                            OLS   Adj. R-squared:                 -0.000\n",
      "Method:                 Least Squares   F-statistic:                   0.01499\n",
      "Date:                Tue, 11 Apr 2017   Prob (F-statistic):              0.903\n",
      "Time:                        20:04:37   Log-Likelihood:                -26447.\n",
      "No. Observations:                7548   AIC:                         5.290e+04\n",
      "Df Residuals:                    7546   BIC:                         5.291e+04\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [95.0% Conf. Int.]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      8.6581      0.454     19.050      0.000         7.767     9.549\n",
      "TEMP          -0.0008      0.006     -0.122      0.903        -0.013     0.012\n",
      "==============================================================================\n",
      "Omnibus:                     8673.553   Durbin-Watson:                   0.234\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):          1222277.723\n",
      "Skew:                           5.888   Prob(JB):                         0.00\n",
      "Kurtosis:                      64.219   Cond. No.                         345.\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "#Running a single variate regression between PM2.5 and temperature confirms\n",
    "#there is no meaningful relationship here.\n",
    "m = ols('pm25 ~ TEMP',merged).fit()\n",
    "print (m.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:                   pm25   R-squared:                       0.000\n",
      "Model:                            OLS   Adj. R-squared:                 -0.000\n",
      "Method:                 Least Squares   F-statistic:                 0.0009412\n",
      "Date:                Tue, 11 Apr 2017   Prob (F-statistic):              0.976\n",
      "Time:                        20:06:38   Log-Likelihood:                -26447.\n",
      "No. Observations:                7548   AIC:                         5.290e+04\n",
      "Df Residuals:                    7546   BIC:                         5.291e+04\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==============================================================================\n",
      "                 coef    std err          t      P>|t|      [95.0% Conf. Int.]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      8.6040      0.093     92.288      0.000         8.421     8.787\n",
      "PCP01         -0.0667      2.173     -0.031      0.976        -4.326     4.193\n",
      "==============================================================================\n",
      "Omnibus:                     8673.506   Durbin-Watson:                   0.234\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):          1222088.673\n",
      "Skew:                           5.888   Prob(JB):                         0.00\n",
      "Kurtosis:                      64.214   Cond. No.                         23.5\n",
      "==============================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n"
     ]
    }
   ],
   "source": [
    "#Again, pure noise when fitting PM2.5 based on 1-hour Preciptation. All the zero values skew it completely.\n",
    "m = ols('pm25 ~ PCP01',merged).fit()\n",
    "print (m.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Trying a multi-variate regression using all the attributes. First, need to drop PM2.5 from the dataframe.\n",
    "from sklearn.linear_model import LinearRegression\n",
    "X = merged.drop('pm25', axis = 1)\n",
    "X = merged.drop('SKC', axis = 1)\n",
    "X.head()\n",
    "lm = LinearRegression()\n",
    "lm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Input contains NaN, infinity or a value too large for dtype('float64').",
     "output_type": "error",
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      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-82-2ad2c8a225a1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mlm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mX\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmerged\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpm25\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32mC:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\sklearn\\linear_model\\base.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    510\u001b[0m         \u001b[0mn_jobs_\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mn_jobs\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    511\u001b[0m         X, y = check_X_y(X, y, accept_sparse=['csr', 'csc', 'coo'],\n\u001b[0;32m--> 512\u001b[0;31m                          y_numeric=True, multi_output=True)\n\u001b[0m\u001b[1;32m    513\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    514\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0msample_weight\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32mand\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0matleast_1d\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msample_weight\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndim\u001b[0m \u001b[1;33m>\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    519\u001b[0m     X = check_array(X, accept_sparse, dtype, order, copy, force_all_finite,\n\u001b[1;32m    520\u001b[0m                     \u001b[0mensure_2d\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mallow_nd\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mensure_min_samples\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 521\u001b[0;31m                     ensure_min_features, warn_on_dtype, estimator)\n\u001b[0m\u001b[1;32m    522\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mmulti_output\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    523\u001b[0m         y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False,\n",
      "\u001b[0;32mC:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)\u001b[0m\n\u001b[1;32m    405\u001b[0m                              % (array.ndim, estimator_name))\n\u001b[1;32m    406\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mforce_all_finite\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 407\u001b[0;31m             \u001b[0m_assert_all_finite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    408\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    409\u001b[0m     \u001b[0mshape_repr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_shape_repr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\MatthewNichols\\Anaconda3\\lib\\site-packages\\sklearn\\utils\\validation.py\u001b[0m in \u001b[0;36m_assert_all_finite\u001b[0;34m(X)\u001b[0m\n\u001b[1;32m     56\u001b[0m             and not np.isfinite(X).all()):\n\u001b[1;32m     57\u001b[0m         raise ValueError(\"Input contains NaN, infinity\"\n\u001b[0;32m---> 58\u001b[0;31m                          \" or a value too large for %r.\" % X.dtype)\n\u001b[0m\u001b[1;32m     59\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: Input contains NaN, infinity or a value too large for dtype('float64')."
     ]
    }
   ],
   "source": [
    "#Running into problems because of the presence of NaN values in some columns...\n",
    "lm.fit(X, merged.pm25)"
   ]
  }
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