Visual.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5"
   },
   "outputs": [],
   "source": [
    "#Importing the required modules\n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COMMUNITY AREA NAME</th>\n",
       "      <th>CENSUS BLOCK</th>\n",
       "      <th>BUILDING TYPE</th>\n",
       "      <th>BUILDING_SUBTYPE</th>\n",
       "      <th>KWH JANUARY 2010</th>\n",
       "      <th>KWH FEBRUARY 2010</th>\n",
       "      <th>KWH MARCH 2010</th>\n",
       "      <th>KWH APRIL 2010</th>\n",
       "      <th>KWH MAY 2010</th>\n",
       "      <th>KWH JUNE 2010</th>\n",
       "      <th>...</th>\n",
       "      <th>TOTAL POPULATION</th>\n",
       "      <th>TOTAL UNITS</th>\n",
       "      <th>AVERAGE STORIES</th>\n",
       "      <th>AVERAGE BUILDING AGE</th>\n",
       "      <th>AVERAGE HOUSESIZE</th>\n",
       "      <th>OCCUPIED UNITS</th>\n",
       "      <th>OCCUPIED UNITS PERCENTAGE</th>\n",
       "      <th>RENTER-OCCUPIED HOUSING UNITS</th>\n",
       "      <th>RENTER-OCCUPIED HOUSING PERCENTAGE</th>\n",
       "      <th>OCCUPIED HOUSING UNITS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Archer Heights</td>\n",
       "      <td>1.703157e+14</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Multi &lt; 7</td>\n",
       "      <td>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>89.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>71.33</td>\n",
       "      <td>3.87</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.9582</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.3910</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Ashburn</td>\n",
       "      <td>1.703170e+14</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Multi 7+</td>\n",
       "      <td>7334.0</td>\n",
       "      <td>7741.0</td>\n",
       "      <td>4214.0</td>\n",
       "      <td>4284.0</td>\n",
       "      <td>2518.0</td>\n",
       "      <td>4273.0</td>\n",
       "      <td>...</td>\n",
       "      <td>112.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>41.00</td>\n",
       "      <td>1.81</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.9254</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.8059</td>\n",
       "      <td>62.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Auburn Gresham</td>\n",
       "      <td>1.703171e+14</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Multi &lt; 7</td>\n",
       "      <td>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>102.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>86.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.7082</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.6759</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Austin</td>\n",
       "      <td>1.703125e+14</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Multi &lt; 7</td>\n",
       "      <td>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>121.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>84.00</td>\n",
       "      <td>2.95</td>\n",
       "      <td>41.0</td>\n",
       "      <td>0.7321</td>\n",
       "      <td>32.0</td>\n",
       "      <td>0.7800</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Austin</td>\n",
       "      <td>1.703125e+14</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Multi &lt; 7</td>\n",
       "      <td>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>62.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>85.00</td>\n",
       "      <td>3.26</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.8261</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.5790</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Austin</td>\n",
       "      <td>1.703125e+14</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>54.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>131.00</td>\n",
       "      <td>3.00</td>\n",
       "      <td>18.0</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.5560</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Austin</td>\n",
       "      <td>1.703125e+14</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>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>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>54.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Austin</td>\n",
       "      <td>1.703125e+14</td>\n",
       "      <td>Commercial</td>\n",
       "      <td>Multi &lt; 7</td>\n",
       "      <td>1470.0</td>\n",
       "      <td>1325.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>391.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>2204.0</td>\n",
       "      <td>...</td>\n",
       "      <td>64.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>131.00</td>\n",
       "      <td>1.02</td>\n",
       "      <td>59.0</td>\n",
       "      <td>0.9365</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Austin</td>\n",
       "      <td>1.703125e+14</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Multi 7+</td>\n",
       "      <td>2461.0</td>\n",
       "      <td>4888.0</td>\n",
       "      <td>2893.0</td>\n",
       "      <td>2737.0</td>\n",
       "      <td>2350.0</td>\n",
       "      <td>3037.0</td>\n",
       "      <td>...</td>\n",
       "      <td>79.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>99.00</td>\n",
       "      <td>2.93</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.8710</td>\n",
       "      <td>27.0</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>27.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Austin</td>\n",
       "      <td>1.703125e+14</td>\n",
       "      <td>Residential</td>\n",
       "      <td>Multi 7+</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>511.0</td>\n",
       "      <td>...</td>\n",
       "      <td>84.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>99.00</td>\n",
       "      <td>3.82</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.6667</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.7270</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 73 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  COMMUNITY AREA NAME  CENSUS BLOCK BUILDING TYPE BUILDING_SUBTYPE  \\\n",
       "0      Archer Heights  1.703157e+14   Residential        Multi < 7   \n",
       "1             Ashburn  1.703170e+14   Residential         Multi 7+   \n",
       "2      Auburn Gresham  1.703171e+14    Commercial        Multi < 7   \n",
       "3              Austin  1.703125e+14    Commercial        Multi < 7   \n",
       "4              Austin  1.703125e+14    Commercial        Multi < 7   \n",
       "5              Austin  1.703125e+14    Commercial       Commercial   \n",
       "6              Austin  1.703125e+14    Commercial       Commercial   \n",
       "7              Austin  1.703125e+14    Commercial        Multi < 7   \n",
       "8              Austin  1.703125e+14   Residential         Multi 7+   \n",
       "9              Austin  1.703125e+14   Residential         Multi 7+   \n",
       "\n",
       "   KWH JANUARY 2010  KWH FEBRUARY 2010  KWH MARCH 2010  KWH APRIL 2010  \\\n",
       "0               NaN                NaN             NaN             NaN   \n",
       "1            7334.0             7741.0          4214.0          4284.0   \n",
       "2               NaN                NaN             NaN             NaN   \n",
       "3               NaN                NaN             NaN             NaN   \n",
       "4               NaN                NaN             NaN             NaN   \n",
       "5               0.0                0.0             0.0             0.0   \n",
       "6               NaN                NaN             NaN             NaN   \n",
       "7            1470.0             1325.0           294.0           391.0   \n",
       "8            2461.0             4888.0          2893.0          2737.0   \n",
       "9               0.0                0.0             0.0             0.0   \n",
       "\n",
       "   KWH MAY 2010  KWH JUNE 2010  ...  TOTAL POPULATION  TOTAL UNITS  \\\n",
       "0           NaN            NaN  ...              89.0         24.0   \n",
       "1        2518.0         4273.0  ...             112.0         67.0   \n",
       "2           NaN            NaN  ...             102.0         48.0   \n",
       "3           NaN            NaN  ...             121.0         56.0   \n",
       "4           NaN            NaN  ...              62.0         23.0   \n",
       "5           0.0            0.0  ...              54.0         18.0   \n",
       "6           NaN            NaN  ...               0.0          0.0   \n",
       "7         366.0         2204.0  ...              64.0         63.0   \n",
       "8        2350.0         3037.0  ...              79.0         31.0   \n",
       "9           0.0          511.0  ...              84.0         33.0   \n",
       "\n",
       "   AVERAGE STORIES  AVERAGE BUILDING AGE  AVERAGE HOUSESIZE  OCCUPIED UNITS  \\\n",
       "0              2.0                 71.33               3.87            23.0   \n",
       "1              2.0                 41.00               1.81            62.0   \n",
       "2              3.0                 86.00               3.00            34.0   \n",
       "3              2.0                 84.00               2.95            41.0   \n",
       "4              2.0                 85.00               3.26            19.0   \n",
       "5              2.0                131.00               3.00            18.0   \n",
       "6              1.0                 54.00               0.00             0.0   \n",
       "7              2.0                131.00               1.02            59.0   \n",
       "8              3.0                 99.00               2.93            27.0   \n",
       "9              3.0                 99.00               3.82            22.0   \n",
       "\n",
       "   OCCUPIED UNITS PERCENTAGE RENTER-OCCUPIED HOUSING UNITS  \\\n",
       "0                     0.9582                           9.0   \n",
       "1                     0.9254                          50.0   \n",
       "2                     0.7082                          23.0   \n",
       "3                     0.7321                          32.0   \n",
       "4                     0.8261                          11.0   \n",
       "5                     1.0000                          10.0   \n",
       "6                        NaN                           0.0   \n",
       "7                     0.9365                          59.0   \n",
       "8                     0.8710                          27.0   \n",
       "9                     0.6667                          16.0   \n",
       "\n",
       "   RENTER-OCCUPIED HOUSING PERCENTAGE  OCCUPIED HOUSING UNITS  \n",
       "0                              0.3910                    23.0  \n",
       "1                              0.8059                    62.0  \n",
       "2                              0.6759                    34.0  \n",
       "3                              0.7800                    41.0  \n",
       "4                              0.5790                    19.0  \n",
       "5                              0.5560                    18.0  \n",
       "6                                 NaN                     0.0  \n",
       "7                              1.0000                    59.0  \n",
       "8                              1.0000                    27.0  \n",
       "9                              0.7270                    22.0  \n",
       "\n",
       "[10 rows x 73 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv(\"energy-usage-2010.csv\")\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_uuid": "e646d1659b86fdcb0515c2e4a9053dcdc4b9e9b1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 67051 entries, 0 to 67050\n",
      "Data columns (total 73 columns):\n",
      "COMMUNITY AREA NAME                    67051 non-null object\n",
      "CENSUS BLOCK                           66974 non-null float64\n",
      "BUILDING TYPE                          66974 non-null object\n",
      "BUILDING_SUBTYPE                       66974 non-null object\n",
      "KWH JANUARY 2010                       66180 non-null float64\n",
      "KWH FEBRUARY 2010                      66180 non-null float64\n",
      "KWH MARCH 2010                         66180 non-null float64\n",
      "KWH APRIL 2010                         66180 non-null float64\n",
      "KWH MAY 2010                           66180 non-null float64\n",
      "KWH JUNE 2010                          66180 non-null float64\n",
      "KWH JULY 2010                          66180 non-null float64\n",
      "KWH AUGUST 2010                        66180 non-null float64\n",
      "KWH SEPTEMBER 2010                     66180 non-null float64\n",
      "KWH OCTOBER 2010                       66180 non-null float64\n",
      "KWH NOVEMBER 2010                      66180 non-null float64\n",
      "KWH DECEMBER 2010                      66180 non-null float64\n",
      "TOTAL KWH                              66180 non-null float64\n",
      "ELECTRICITY ACCOUNTS                   66180 non-null object\n",
      "ZERO KWH ACCOUNTS                      67051 non-null int64\n",
      "THERM JANUARY 2010                     64821 non-null float64\n",
      "THERM FEBRUARY 2010                    62819 non-null float64\n",
      "THERM MARCH 2010                       65569 non-null float64\n",
      "TERM APRIL 2010                        65476 non-null float64\n",
      "THERM MAY 2010                         65194 non-null float64\n",
      "THERM JUNE 2010                        65284 non-null float64\n",
      "THERM JULY 2010                        65231 non-null float64\n",
      "THERM AUGUST 2010                      65143 non-null float64\n",
      "THERM SEPTEMBER 2010                   64769 non-null float64\n",
      "THERM OCTOBER 2010                     65329 non-null float64\n",
      "THERM NOVEMBER 2010                    65492 non-null float64\n",
      "THERM DECEMBER 2010                    65507 non-null float64\n",
      "TOTAL THERMS                           65755 non-null float64\n",
      "GAS ACCOUNTS                           65755 non-null object\n",
      "KWH TOTAL SQFT                         65901 non-null float64\n",
      "THERMS TOTAL SQFT                      65378 non-null float64\n",
      "KWH MEAN 2010                          66180 non-null float64\n",
      "KWH STANDARD DEVIATION 2010            57095 non-null float64\n",
      "KWH MINIMUM 2010                       66180 non-null float64\n",
      "KWH 1ST QUARTILE 2010                  66180 non-null float64\n",
      "KWH 2ND QUARTILE 2010                  66180 non-null float64\n",
      "KWH 3RD QUARTILE 2010                  66180 non-null float64\n",
      "KWH MAXIMUM 2010                       66180 non-null float64\n",
      "KWH SQFT MEAN 2010                     65901 non-null float64\n",
      "KWH SQFT STANDARD DEVIATION 2010       51666 non-null float64\n",
      "KWH SQFT MINIMUM 2010                  65901 non-null float64\n",
      "KWH SQFT 1ST QUARTILE 2010             65901 non-null float64\n",
      "KWH SQFT 2ND QUARTILE 2010             65901 non-null float64\n",
      "KWH SQFT 3RD QUARTILE 2010             65901 non-null float64\n",
      "KWH SQFT MAXIMUM 2010                  65901 non-null float64\n",
      "THERM MEAN 2010                        65755 non-null float64\n",
      "THERM STANDARD DEVIATION 2010          56821 non-null float64\n",
      "THERM MINIMUM 2010                     65755 non-null float64\n",
      "THERM 1ST QUARTILE 2010                65755 non-null float64\n",
      "THERM 2ND QUARTILE 2010                65755 non-null float64\n",
      "THERM 3RD QUARTILE 2010                65755 non-null float64\n",
      "THERM MAXIMUM 2010                     65755 non-null float64\n",
      "THERMS SQFT MEAN 2010                  65378 non-null float64\n",
      "THERMS SQFT STANDARD DEVIATION 2010    51367 non-null float64\n",
      "THERMS SQFT MINIMUM 2010               65378 non-null float64\n",
      "THERMS SQFT 1ST QUARTILE 2010          65378 non-null float64\n",
      "THERMS SQFT 2ND QUARTILE 2010          65378 non-null float64\n",
      "THERMS SQFT 3RD QUARTILE 2010          65378 non-null float64\n",
      "THERMS SQFT MAXIMUM 2010               65378 non-null float64\n",
      "TOTAL POPULATION                       67037 non-null float64\n",
      "TOTAL UNITS                            67037 non-null float64\n",
      "AVERAGE STORIES                        67051 non-null float64\n",
      "AVERAGE BUILDING AGE                   67051 non-null float64\n",
      "AVERAGE HOUSESIZE                      67037 non-null float64\n",
      "OCCUPIED UNITS                         67037 non-null float64\n",
      "OCCUPIED UNITS PERCENTAGE              64606 non-null float64\n",
      "RENTER-OCCUPIED HOUSING UNITS          67037 non-null float64\n",
      "RENTER-OCCUPIED HOUSING PERCENTAGE     64433 non-null float64\n",
      "OCCUPIED HOUSING UNITS                 67037 non-null float64\n",
      "dtypes: float64(67), int64(1), object(5)\n",
      "memory usage: 37.3+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "_uuid": "70b3fb5689cdb067c31b60ed6a939524c99ec503"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "West Town          2869\n",
       "Austin             2528\n",
       "Logan Square       2343\n",
       "Lakeview           2066\n",
       "Belmont Cragin     1812\n",
       "                   ... \n",
       "O'Hare              124\n",
       "Near South Side     120\n",
       "Burnside            116\n",
       "Oakland             108\n",
       "Riverdale            61\n",
       "Name: COMMUNITY AREA NAME, Length: 77, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Counting the number of occurrence of each Area\n",
    "df['COMMUNITY AREA NAME'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "_uuid": "ddc46925b3776a8c29848dd572326b3739aa5d89",
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CENSUS BLOCK</th>\n",
       "      <th>KWH JANUARY 2010</th>\n",
       "      <th>KWH FEBRUARY 2010</th>\n",
       "      <th>KWH MARCH 2010</th>\n",
       "      <th>KWH APRIL 2010</th>\n",
       "      <th>KWH MAY 2010</th>\n",
       "      <th>KWH JUNE 2010</th>\n",
       "      <th>KWH JULY 2010</th>\n",
       "      <th>KWH AUGUST 2010</th>\n",
       "      <th>KWH SEPTEMBER 2010</th>\n",
       "      <th>...</th>\n",
       "      <th>TOTAL POPULATION</th>\n",
       "      <th>TOTAL UNITS</th>\n",
       "      <th>AVERAGE STORIES</th>\n",
       "      <th>AVERAGE BUILDING AGE</th>\n",
       "      <th>AVERAGE HOUSESIZE</th>\n",
       "      <th>OCCUPIED UNITS</th>\n",
       "      <th>OCCUPIED UNITS PERCENTAGE</th>\n",
       "      <th>RENTER-OCCUPIED HOUSING UNITS</th>\n",
       "      <th>RENTER-OCCUPIED HOUSING PERCENTAGE</th>\n",
       "      <th>OCCUPIED HOUSING UNITS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COMMUNITY AREA NAME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Albany Park</th>\n",
       "      <td>1.963691e+17</td>\n",
       "      <td>8099814.0</td>\n",
       "      <td>8318671.0</td>\n",
       "      <td>8167825.0</td>\n",
       "      <td>8152326.0</td>\n",
       "      <td>10537220.0</td>\n",
       "      <td>14172588.0</td>\n",
       "      <td>14798474.0</td>\n",
       "      <td>12115646.0</td>\n",
       "      <td>9139269.0</td>\n",
       "      <td>...</td>\n",
       "      <td>145619.0</td>\n",
       "      <td>52066.0</td>\n",
       "      <td>2092.07</td>\n",
       "      <td>82331.91</td>\n",
       "      <td>4168.27</td>\n",
       "      <td>46871.0</td>\n",
       "      <td>1032.6859</td>\n",
       "      <td>30115.0</td>\n",
       "      <td>646.9883</td>\n",
       "      <td>46871.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Archer Heights</th>\n",
       "      <td>6.710438e+16</td>\n",
       "      <td>8999177.0</td>\n",
       "      <td>8700446.0</td>\n",
       "      <td>8275265.0</td>\n",
       "      <td>8519853.0</td>\n",
       "      <td>9163139.0</td>\n",
       "      <td>10777922.0</td>\n",
       "      <td>11499250.0</td>\n",
       "      <td>11148907.0</td>\n",
       "      <td>9248428.0</td>\n",
       "      <td>...</td>\n",
       "      <td>29591.0</td>\n",
       "      <td>9651.0</td>\n",
       "      <td>594.88</td>\n",
       "      <td>24096.87</td>\n",
       "      <td>1489.08</td>\n",
       "      <td>8773.0</td>\n",
       "      <td>333.7608</td>\n",
       "      <td>3835.0</td>\n",
       "      <td>155.5279</td>\n",
       "      <td>8773.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Armour Square</th>\n",
       "      <td>4.785876e+16</td>\n",
       "      <td>5528116.0</td>\n",
       "      <td>5463905.0</td>\n",
       "      <td>4914495.0</td>\n",
       "      <td>4942071.0</td>\n",
       "      <td>5119589.0</td>\n",
       "      <td>5615089.0</td>\n",
       "      <td>7439015.0</td>\n",
       "      <td>7065485.0</td>\n",
       "      <td>5698898.0</td>\n",
       "      <td>...</td>\n",
       "      <td>35884.0</td>\n",
       "      <td>14838.0</td>\n",
       "      <td>532.08</td>\n",
       "      <td>16630.31</td>\n",
       "      <td>888.04</td>\n",
       "      <td>13660.0</td>\n",
       "      <td>236.7815</td>\n",
       "      <td>9015.0</td>\n",
       "      <td>157.3031</td>\n",
       "      <td>13660.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ashburn</th>\n",
       "      <td>1.476648e+17</td>\n",
       "      <td>10784936.0</td>\n",
       "      <td>10657440.0</td>\n",
       "      <td>10168703.0</td>\n",
       "      <td>10448903.0</td>\n",
       "      <td>13935993.0</td>\n",
       "      <td>18845801.0</td>\n",
       "      <td>20510478.0</td>\n",
       "      <td>16050164.0</td>\n",
       "      <td>11894014.0</td>\n",
       "      <td>...</td>\n",
       "      <td>63033.0</td>\n",
       "      <td>21257.0</td>\n",
       "      <td>1173.39</td>\n",
       "      <td>43240.34</td>\n",
       "      <td>3335.43</td>\n",
       "      <td>20033.0</td>\n",
       "      <td>800.1712</td>\n",
       "      <td>3508.0</td>\n",
       "      <td>128.9627</td>\n",
       "      <td>20033.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Auburn Gresham</th>\n",
       "      <td>2.427019e+17</td>\n",
       "      <td>9494108.0</td>\n",
       "      <td>9534584.0</td>\n",
       "      <td>9208973.0</td>\n",
       "      <td>8950586.0</td>\n",
       "      <td>10746825.0</td>\n",
       "      <td>14160557.0</td>\n",
       "      <td>15024383.0</td>\n",
       "      <td>12789634.0</td>\n",
       "      <td>9844096.0</td>\n",
       "      <td>...</td>\n",
       "      <td>111768.0</td>\n",
       "      <td>48218.0</td>\n",
       "      <td>2227.19</td>\n",
       "      <td>99460.46</td>\n",
       "      <td>5067.91</td>\n",
       "      <td>41229.0</td>\n",
       "      <td>1186.7274</td>\n",
       "      <td>24217.0</td>\n",
       "      <td>668.9451</td>\n",
       "      <td>41229.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Austin</th>\n",
       "      <td>4.303806e+17</td>\n",
       "      <td>21506684.0</td>\n",
       "      <td>24292930.0</td>\n",
       "      <td>23662582.0</td>\n",
       "      <td>21966745.0</td>\n",
       "      <td>26016007.0</td>\n",
       "      <td>30798364.0</td>\n",
       "      <td>35240528.0</td>\n",
       "      <td>35215333.0</td>\n",
       "      <td>28395692.0</td>\n",
       "      <td>...</td>\n",
       "      <td>248791.0</td>\n",
       "      <td>98060.0</td>\n",
       "      <td>4490.96</td>\n",
       "      <td>197151.64</td>\n",
       "      <td>9624.24</td>\n",
       "      <td>83773.0</td>\n",
       "      <td>2112.5868</td>\n",
       "      <td>53718.0</td>\n",
       "      <td>1346.1674</td>\n",
       "      <td>83773.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Avalon Park</th>\n",
       "      <td>5.722643e+16</td>\n",
       "      <td>2742619.0</td>\n",
       "      <td>2629352.0</td>\n",
       "      <td>2413518.0</td>\n",
       "      <td>2434028.0</td>\n",
       "      <td>2782662.0</td>\n",
       "      <td>3688298.0</td>\n",
       "      <td>3991451.0</td>\n",
       "      <td>3506747.0</td>\n",
       "      <td>2637194.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20093.0</td>\n",
       "      <td>8608.0</td>\n",
       "      <td>487.36</td>\n",
       "      <td>23101.54</td>\n",
       "      <td>1042.95</td>\n",
       "      <td>7767.0</td>\n",
       "      <td>292.4163</td>\n",
       "      <td>2575.0</td>\n",
       "      <td>97.8921</td>\n",
       "      <td>7767.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Avondale</th>\n",
       "      <td>1.680991e+17</td>\n",
       "      <td>9733228.0</td>\n",
       "      <td>9669355.0</td>\n",
       "      <td>9560428.0</td>\n",
       "      <td>8974441.0</td>\n",
       "      <td>10868366.0</td>\n",
       "      <td>14248133.0</td>\n",
       "      <td>15438828.0</td>\n",
       "      <td>13225706.0</td>\n",
       "      <td>10544025.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100963.0</td>\n",
       "      <td>40100.0</td>\n",
       "      <td>1754.60</td>\n",
       "      <td>81058.63</td>\n",
       "      <td>3170.56</td>\n",
       "      <td>35444.0</td>\n",
       "      <td>835.8067</td>\n",
       "      <td>22202.0</td>\n",
       "      <td>582.8485</td>\n",
       "      <td>35444.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Belmont Cragin</th>\n",
       "      <td>3.084355e+17</td>\n",
       "      <td>15661282.0</td>\n",
       "      <td>16844580.0</td>\n",
       "      <td>15791461.0</td>\n",
       "      <td>15443287.0</td>\n",
       "      <td>18480112.0</td>\n",
       "      <td>23403306.0</td>\n",
       "      <td>25867306.0</td>\n",
       "      <td>24148650.0</td>\n",
       "      <td>18072171.0</td>\n",
       "      <td>...</td>\n",
       "      <td>184432.0</td>\n",
       "      <td>56038.0</td>\n",
       "      <td>2839.92</td>\n",
       "      <td>125358.71</td>\n",
       "      <td>7847.84</td>\n",
       "      <td>51040.0</td>\n",
       "      <td>1602.9311</td>\n",
       "      <td>27629.0</td>\n",
       "      <td>911.7249</td>\n",
       "      <td>51040.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Beverly</th>\n",
       "      <td>9.639954e+16</td>\n",
       "      <td>5624419.0</td>\n",
       "      <td>5900692.0</td>\n",
       "      <td>5386120.0</td>\n",
       "      <td>5716720.0</td>\n",
       "      <td>7797878.0</td>\n",
       "      <td>11195282.0</td>\n",
       "      <td>10944642.0</td>\n",
       "      <td>8034612.0</td>\n",
       "      <td>6252626.0</td>\n",
       "      <td>...</td>\n",
       "      <td>40407.0</td>\n",
       "      <td>18212.0</td>\n",
       "      <td>917.99</td>\n",
       "      <td>38705.06</td>\n",
       "      <td>1862.07</td>\n",
       "      <td>16998.0</td>\n",
       "      <td>524.6463</td>\n",
       "      <td>6176.0</td>\n",
       "      <td>88.1821</td>\n",
       "      <td>16998.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 68 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     CENSUS BLOCK  KWH JANUARY 2010  KWH FEBRUARY 2010  \\\n",
       "COMMUNITY AREA NAME                                                      \n",
       "Albany Park          1.963691e+17         8099814.0          8318671.0   \n",
       "Archer Heights       6.710438e+16         8999177.0          8700446.0   \n",
       "Armour Square        4.785876e+16         5528116.0          5463905.0   \n",
       "Ashburn              1.476648e+17        10784936.0         10657440.0   \n",
       "Auburn Gresham       2.427019e+17         9494108.0          9534584.0   \n",
       "Austin               4.303806e+17        21506684.0         24292930.0   \n",
       "Avalon Park          5.722643e+16         2742619.0          2629352.0   \n",
       "Avondale             1.680991e+17         9733228.0          9669355.0   \n",
       "Belmont Cragin       3.084355e+17        15661282.0         16844580.0   \n",
       "Beverly              9.639954e+16         5624419.0          5900692.0   \n",
       "\n",
       "                     KWH MARCH 2010  KWH APRIL 2010  KWH MAY 2010  \\\n",
       "COMMUNITY AREA NAME                                                 \n",
       "Albany Park               8167825.0       8152326.0    10537220.0   \n",
       "Archer Heights            8275265.0       8519853.0     9163139.0   \n",
       "Armour Square             4914495.0       4942071.0     5119589.0   \n",
       "Ashburn                  10168703.0      10448903.0    13935993.0   \n",
       "Auburn Gresham            9208973.0       8950586.0    10746825.0   \n",
       "Austin                   23662582.0      21966745.0    26016007.0   \n",
       "Avalon Park               2413518.0       2434028.0     2782662.0   \n",
       "Avondale                  9560428.0       8974441.0    10868366.0   \n",
       "Belmont Cragin           15791461.0      15443287.0    18480112.0   \n",
       "Beverly                   5386120.0       5716720.0     7797878.0   \n",
       "\n",
       "                     KWH JUNE 2010  KWH JULY 2010  KWH AUGUST 2010  \\\n",
       "COMMUNITY AREA NAME                                                  \n",
       "Albany Park             14172588.0     14798474.0       12115646.0   \n",
       "Archer Heights          10777922.0     11499250.0       11148907.0   \n",
       "Armour Square            5615089.0      7439015.0        7065485.0   \n",
       "Ashburn                 18845801.0     20510478.0       16050164.0   \n",
       "Auburn Gresham          14160557.0     15024383.0       12789634.0   \n",
       "Austin                  30798364.0     35240528.0       35215333.0   \n",
       "Avalon Park              3688298.0      3991451.0        3506747.0   \n",
       "Avondale                14248133.0     15438828.0       13225706.0   \n",
       "Belmont Cragin          23403306.0     25867306.0       24148650.0   \n",
       "Beverly                 11195282.0     10944642.0        8034612.0   \n",
       "\n",
       "                     KWH SEPTEMBER 2010  ...  TOTAL POPULATION  TOTAL UNITS  \\\n",
       "COMMUNITY AREA NAME                      ...                                  \n",
       "Albany Park                   9139269.0  ...          145619.0      52066.0   \n",
       "Archer Heights                9248428.0  ...           29591.0       9651.0   \n",
       "Armour Square                 5698898.0  ...           35884.0      14838.0   \n",
       "Ashburn                      11894014.0  ...           63033.0      21257.0   \n",
       "Auburn Gresham                9844096.0  ...          111768.0      48218.0   \n",
       "Austin                       28395692.0  ...          248791.0      98060.0   \n",
       "Avalon Park                   2637194.0  ...           20093.0       8608.0   \n",
       "Avondale                     10544025.0  ...          100963.0      40100.0   \n",
       "Belmont Cragin               18072171.0  ...          184432.0      56038.0   \n",
       "Beverly                       6252626.0  ...           40407.0      18212.0   \n",
       "\n",
       "                     AVERAGE STORIES  AVERAGE BUILDING AGE  AVERAGE HOUSESIZE  \\\n",
       "COMMUNITY AREA NAME                                                             \n",
       "Albany Park                  2092.07              82331.91            4168.27   \n",
       "Archer Heights                594.88              24096.87            1489.08   \n",
       "Armour Square                 532.08              16630.31             888.04   \n",
       "Ashburn                      1173.39              43240.34            3335.43   \n",
       "Auburn Gresham               2227.19              99460.46            5067.91   \n",
       "Austin                       4490.96             197151.64            9624.24   \n",
       "Avalon Park                   487.36              23101.54            1042.95   \n",
       "Avondale                     1754.60              81058.63            3170.56   \n",
       "Belmont Cragin               2839.92             125358.71            7847.84   \n",
       "Beverly                       917.99              38705.06            1862.07   \n",
       "\n",
       "                     OCCUPIED UNITS  OCCUPIED UNITS PERCENTAGE  \\\n",
       "COMMUNITY AREA NAME                                              \n",
       "Albany Park                 46871.0                  1032.6859   \n",
       "Archer Heights               8773.0                   333.7608   \n",
       "Armour Square               13660.0                   236.7815   \n",
       "Ashburn                     20033.0                   800.1712   \n",
       "Auburn Gresham              41229.0                  1186.7274   \n",
       "Austin                      83773.0                  2112.5868   \n",
       "Avalon Park                  7767.0                   292.4163   \n",
       "Avondale                    35444.0                   835.8067   \n",
       "Belmont Cragin              51040.0                  1602.9311   \n",
       "Beverly                     16998.0                   524.6463   \n",
       "\n",
       "                     RENTER-OCCUPIED HOUSING UNITS  \\\n",
       "COMMUNITY AREA NAME                                  \n",
       "Albany Park                                30115.0   \n",
       "Archer Heights                              3835.0   \n",
       "Armour Square                               9015.0   \n",
       "Ashburn                                     3508.0   \n",
       "Auburn Gresham                             24217.0   \n",
       "Austin                                     53718.0   \n",
       "Avalon Park                                 2575.0   \n",
       "Avondale                                   22202.0   \n",
       "Belmont Cragin                             27629.0   \n",
       "Beverly                                     6176.0   \n",
       "\n",
       "                     RENTER-OCCUPIED HOUSING PERCENTAGE  \\\n",
       "COMMUNITY AREA NAME                                       \n",
       "Albany Park                                    646.9883   \n",
       "Archer Heights                                 155.5279   \n",
       "Armour Square                                  157.3031   \n",
       "Ashburn                                        128.9627   \n",
       "Auburn Gresham                                 668.9451   \n",
       "Austin                                        1346.1674   \n",
       "Avalon Park                                     97.8921   \n",
       "Avondale                                       582.8485   \n",
       "Belmont Cragin                                 911.7249   \n",
       "Beverly                                         88.1821   \n",
       "\n",
       "                     OCCUPIED HOUSING UNITS  \n",
       "COMMUNITY AREA NAME                          \n",
       "Albany Park                         46871.0  \n",
       "Archer Heights                       8773.0  \n",
       "Armour Square                       13660.0  \n",
       "Ashburn                             20033.0  \n",
       "Auburn Gresham                      41229.0  \n",
       "Austin                              83773.0  \n",
       "Avalon Park                          7767.0  \n",
       "Avondale                            35444.0  \n",
       "Belmont Cragin                      51040.0  \n",
       "Beverly                             16998.0  \n",
       "\n",
       "[10 rows x 68 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Total enrgy consumption of each  Area\n",
    "sdf=df.groupby(['COMMUNITY AREA NAME']).sum()\n",
    "sdf.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "_uuid": "1e313fbe6fc4d0a92d2f9ee2b938110d95081361"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Near West Side', 'Near North Side', 'Loop', 'Lakeview', 'Austin',\n",
      "       'West Town', 'Portage Park', 'Lincoln Park', 'Rogers Park',\n",
      "       'South Lawndale'],\n",
      "      dtype='object', name='COMMUNITY AREA NAME')\n"
     ]
    }
   ],
   "source": [
    "#Area which comsumes more THERMS energy\n",
    "sdf.nlargest(10, 'TOTAL THERMS')\n",
    "lig=sdf.nlargest(10, 'TOTAL THERMS').index\n",
    "print(lig)\n",
    "dfl=df[df['COMMUNITY AREA NAME'].isin(lig)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "_uuid": "8cd29df11ee77eaedb1d5ab36f55f799ccbb7f8e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Loop', 'Near North Side', 'Near West Side', 'Near South Side',\n",
      "       'Woodlawn', 'Lakeview', 'Lincoln Park', 'West Town', 'Austin',\n",
      "       'South Lawndale'],\n",
      "      dtype='object', name='COMMUNITY AREA NAME')\n"
     ]
    }
   ],
   "source": [
    "#Area which comsumes more energy\n",
    "sdf.nlargest(10, 'TOTAL KWH')\n",
    "lig=sdf.nlargest(10, 'TOTAL KWH').index\n",
    "print(lig)\n",
    "dfl=df[df['COMMUNITY AREA NAME'].isin(lig)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_uuid": "9854991923974f44fe335bbe251e2cadfa93f801"
   },
   "source": [
    "Here  we see that 8  Areas are common to both the result for maximum consumtipon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "_uuid": "28b575d020b9c2a7bcffd3afde1bc5d6c1a58c09"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Fuller Park', 'Burnside', 'Oakland', 'Hegewisch', 'Washington Park',\n",
      "       'Riverdale', 'O'Hare', 'Montclare', 'Armour Square', 'Edison Park'],\n",
      "      dtype='object', name='COMMUNITY AREA NAME')\n"
     ]
    }
   ],
   "source": [
    "#Area which comsumes less THERMS energy\n",
    "sdf.nsmallest(10, 'TOTAL THERMS').iloc[:10]\n",
    "lis=sdf.nsmallest(10, 'TOTAL THERMS').index\n",
    "print(lis)\n",
    "dfs=df[df['COMMUNITY AREA NAME'].isin(lis)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "_uuid": "f8cf2b24d30a33465ec6f0ec594040094e607c4f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Oakland', 'Fuller Park', 'Burnside', 'Washington Park', 'Hegewisch',\n",
      "       'Avalon Park', 'Edison Park', 'Montclare', 'West Garfield Park',\n",
      "       'East Side'],\n",
      "      dtype='object', name='COMMUNITY AREA NAME')\n"
     ]
    }
   ],
   "source": [
    "#Area which comsumes less energy\n",
    "sdf.nsmallest(10, 'TOTAL KWH').iloc[:10]\n",
    "lis=sdf.nsmallest(10, 'TOTAL KWH').index\n",
    "print(lis)\n",
    "dfs=df[df['COMMUNITY AREA NAME'].isin(lis)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_uuid": "5f7b1661119b6674836baad589498058da5b57e4"
   },
   "source": [
    "Here also we see that 7 out of 10  Areas are common thus we'll focus only analysis of one consumption "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "_uuid": "dec5ec57650c200c058e18234a8cfbf82eff35ff"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Area which consume more power')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=2,figsize=(20,10))\n",
    "sns.countplot(x='BUILDING TYPE',data=dfs,hue='COMMUNITY AREA NAME', ax=axs[0])\n",
    "axs[0].legend(loc='upper right')\n",
    "axs[0].set_title(\"Area which consume less power\")\n",
    "\n",
    "sns.countplot(x='BUILDING TYPE',data=dfl,hue='COMMUNITY AREA NAME', ax=axs[1])\n",
    "axs[1].legend(loc='upper right')\n",
    "axs[1].set_title(\"Area which consume more power\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_uuid": "ee29c6f1fff20f122daf7ebe13df339d0ee5c8b0"
   },
   "source": [
    "From the above graphs we see that the Area which consume more power is mainly due to the reason that they have more number of plots than the area which consume less power.\n",
    "\n",
    "It is not the population comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "_uuid": "d4c17e4bac8d01c4448067daeba748e96ec0eb4b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Area which consume more power')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=2,figsize=(20,15))\n",
    "sns.barplot(x=dfs['BUILDING TYPE'],y=dfs['TOTAL KWH'],hue=dfs['COMMUNITY AREA NAME'], ax=axs[0], ci=None)\n",
    "sns.barplot(x='BUILDING TYPE',y='TOTAL KWH',data=dfl,hue='COMMUNITY AREA NAME', ax=axs[1], ci=None)\n",
    "\n",
    "axs[0].legend(loc='upper right')\n",
    "axs[0].set_ylim(0,700000)\n",
    "axs[0].set_title(\"Area which consume less power\")\n",
    "axs[0].legend(loc=0)\n",
    "\n",
    "axs[1].legend(loc=0)\n",
    "axs[1].set_ylim(0,700000)\n",
    "axs[1].set_title(\"Area which consume more power\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_uuid": "c02fb2c6da1d7d3f3bd4d55de58582993b65c34d"
   },
   "source": [
    "From the above graph it seems that though the count for **Residential** category is more as seens above but the more consumtion is been done by **Commercial** plots for both type of Area "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "_uuid": "13ae05d6615e81752c4df115e42f48963c485f0f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Area which consume more power')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jCJIAAAAAGEWQBAAAAMAogiQAAAAARhEkAQAAADCKIAkAAACAUQRJAAAAAIwiSAIAAABgFEESAAAAAKMIkgAAAAAYRZAEAAAAwCiCJAAAAABGESQBAAAAMIogCQAAAIBRBEkAAAAAjCJIAgAAAGAUQRIAAAAAowiSAAAAABhFkAQAAADAKIIkAAAAAEYRJAEAAAAwiiAJAAAAgFEESQAAAACMIkgCAAAAYBRBEgAAAACjCJIAAAAAGEWQBAAAAMAogiQAAAAARlm0IKmq3lpVF1TVqVNtL6+qr1fVl6vqA1W1/dS051XVaVX1jaq6/2LVBQAAAMCmWcweSYck2WtW29FJbt3dt03yzSTPS5Kq2j3JI5PcarjP66tqq0WsDQAAAICNtGhBUncfl+SHs9o+3t0XDaPHJ9l5GN47ybu7+9fdfUaS05LcebFqAwAAAGDjLec1kv48yUeH4Z2SnDM17dyh7TKq6oCqWldV69avX7/IJQIAAAAwY1mCpKp6QZKLkrxzpmmO2Xqu+3b3wd29trvXrlmzZrFKBAAAAGCWrZd6hVW1X5IHJblvd8+ERecm2WVqtp2TnLfUtQEAAAAwvyXtkVRVeyV5TpKHdPcvpiYdmeSRVXWVqrpxkt2SfH4pawMAAABgYYvWI6mq3pVkzyQ7VNW5SV6Uya+0XSXJ0VWVJMd395O6+ytVdViSr2Zyyttfd/fFi1UbAAAAABtv0YKk7n7UHM1vWWD+g5IctFj1AAAAAHD5LOevtgEAAACwigiSAAAAABhFkAQAAADAKIIkAAAAAEYRJAEAAAAwiiAJAAAAgFEESQAAAACMIkgCAAAAYBRBEgAAAACjCJIAAAAAGEWQBAAAAMAogiQAAAAARhEkAQAAADCKIAkAAACAUQRJAAAAAIwiSAIAAABgFEESAAAAAKMIkgAAAAAYRZAEAAAAwCiCJAAAAABGESQBAAAAMIogCQAAAIBRBEkAAAAAjLL1fBOq6owkPd00Nd7dfdPFLAwAAACAlWXeICnJ2lnjV0qyb5JnJjlp0SoCAAAAYEWaN0jq7h8kSVVdKcmfJXlWkpOT/FF3f3VpygMAAABgpVjo1LYrJ/nzJE9L8tkke3f3t5eqMAAAAABWloVObTsjyUVJXpPk7CR7VNUeMxO7+/2LXBsAAAAAK8hCQdInMrm49h7DbVonESQBAAAAbEEWukbS/ktYBwAAAAAr3JUWmlhVt66qQ6tqXVV9YRi+zVIVBwAAAMDKMW+QVFV7J/lAkmMzuej2XwzD7x+mAQAAALAFWegaSS9O8ofdfeZU25eq6lNJPjjcAAAAANhCLHRq25VnhUhJkqHtyotVEAAAAAAr00JB0m+q6oazG6vqRkkuWrySAAAAAFiJFgqSXpTkE1W1f1XdZrjw9uOSfDzJCze04Kp6a1VdUFWnTrVdp6qOrqpvDX+vPbRXVf1rVZ1WVV+uqjtc3gcGAAAAwOY1b5DU3UckeXiS+yQ5JMnbh+F9h2kbckiSvWa1PTfJJ7t7tySfHMaT5AFJdhtuByR5w+hHAAAAAMCSWOhi2+nuLyV57KYsuLuPq6pdZzXvnWTPYfjQJMckec7Q/vbu7iTHV9X2VXWD7v7upqwbAAAAgM1v3iCpqj6UpOeb3t0P2YT1XW8mHOru71bVdYf2nZKcMzXfuUPbZYKkqjogk15LueENL3MJJwAAAAAWyUI9kl6xZFUkNUfbnCFWdx+c5OAkWbt27bxBFwAAAACb10JB0uO6e//NvL7vzZyyVlU3SHLB0H5ukl2m5ts5yXmbed0AAAAAXA4L/WrbbRdhfUcm2W8Y3i/JB6faHzv8ettdkvzE9ZEAAAAAVpaFeiRdtapun7lPO0t3f3GhBVfVuzK5sPYOVXVukhcleUmSw6rq8UnOzuRX4ZLkI0kemOS0JL9I8riNeAwAAAAALIGFgqSdkrwy81+/6D4LLbi7HzXPpPvOMW8n+euFlgcAAADA8looSDqtuxcMiwAAAADYcix0jSQAAAAAuMRCQdJz5mqsql2q6lmLVA8AAAAAK9S8QVJ3f3xmuKp2qKq/rKrjkhyT5HpLUBsAAAAAK8i810iqqmskeViSP01y8yQfSHKT7t55iWoDAAAAYAVZ6GLbFyT5fJK/S/LZ7u6qetjSlAUAAADASrPQNZKen2TbJG9I8ryquunSlAQAAADASrTQNZJe3d2/l+QhSSrJEUl2rKrnVNXNl6pAAAAAAFaGhXokJUm6+/TuPqi7b5PkTkmuleSji14ZAAAAACvKQtdIuozuPiXJKVW15+KUAwAAAMBKtcEeSfPwy20AAAAAW5hNDZIAAAAA2MLMe2pbVf3xfJOSbLc45QAAAACwUi10jaQHLzDtqM1dCAAAAAAr27xBUnc/bikLAQAAAGBlW+jUtqfPauok30/y2e4+Y1GrAgAAAGDFWehi29eYdbtmkrVJPlpVj1yC2gAAAABYQRY6te0f5mqvqusk+USSdy9WUQDA5fe6Z3xouUu4wvubVy50SUkAgCuehXokzam7f5jJL7cBAAAAsAXZ6CCpqu6T5EeLUAsAAAAAK9hCF9s+JZMLbE+7TpLzkjx2MYsCAAAAYOWZN0hK8qBZ453kB93980WsBwAAAIAVaqEg6XtJnpTkZklOSfKW7r5oSaoCAAAAYMVZ6BpJhyZZm0mI9IAkr1ySigAAAABYkRbqkbR7d98mSarqLUk+vzQlAQAAALASLdQj6TczA05pAwAAAGChHkl7VNVPk9Qwvt3UeHf3NRe9OgAAAABWjHmDpO7eaikLAQAAAGBlW6hHUpKkqu6d5FZJOslXuvuYxS4KAAAAgJVn3iCpqnZK8v4kv0pyYiantO1bVdsleVh3f2dpSgRWu7u99m7LXcIV3uee/LnlLgEAANgCLNQj6XVJ3tDdh0w3VtVjk7w+yd6LWBcAAAAAK8xCv9q2++wQKUm6++1JbrloFQEAAACwIi0UJM15se2qutJ80wAAAAC44looSPpQVb2pqq420zAM/3uSjyx6ZQAAAACsKAsFSc9O8pMkZ1XViVW1LsmZSX6a5JmXZ6VV9bSq+kpVnVpV76qqbavqxlV1QlV9q6reU1XbXJ51AAAAALB5zRskdfdvuvuZSXZJsn+SP09yo+5+Znf/76aucPg1uKckWdvdt87kNLlHJnlpkld3925JfpTk8Zu6DgAAAAA2v3mDpKrarao+mOQLSZ6f5Afd/YvNtN6tk2xXVVsnuWqS7ya5T5LDh+mHJnnoZloXAAAAAJvBQqe2vTXJUUn+JMkXk7x2c6ywu7+T5BVJzs4kQPpJkhOT/Li7LxpmOzfJTnPdv6oOqKp1VbVu/fr1m6MkAAAAAEZYKEi6Rne/qbu/0d0vT7Lr5lhhVV07yd5JbpxkxyRXS/KAOWbtue7f3Qd399ruXrtmzZrNURIAAAAAI2y9wLRtq+r2SWoY3256vLu/uInr/IMkZ3T3+iSpqvcnuWuS7atq66FX0s5JztvE5QMAAACwCBYKkr6b5FVT4+dPjXcm1zTaFGcnuUtVXTXJL5PcN8m6JJ9Osk+SdyfZL8kHN3H5AAAAACyCeYOk7r73Yqywu0+oqsMzue7SRUlOSnJwkg8neXdV/ePQ9pbFWD8AAAAAm2ahHkmLprtflORFs5pPT3LnxVrnHZ/19sVaNFNOfPljl7sEAAAAYJEsdLFtAAAAALjEJgVJVbXj5i4EAAAAgJVtU3skHb9ZqwAAAABgxdvUIKk2axUAAAAArHibGiT1Zq0CAAAAgBVv3l9tq6rXZu7AqJJsv2gVAQAAALAizRskJVm3idMAAAAAuAKaN0jq7kPnaq+qbZM8eNEqAgAAAGBFGnWNpKraqqoeUFVvT3JWkkcsblkAAAAArDQLndqWqrpnkj9N8kdJPp/kbklu3N2/WILaAAAAAFhBFrrY9rlJzk7yhiTP6u4Lq+oMIRIAAADAlmmhU9vel2SnTE5je3BVXS1z/4obAAAAAFuAeYOk7v7bJLsmeVWSeyf5ZpI1VbVvVV19acoDAAAAYKVY8GLbPfGp7n5CJqHSnyZ5aJIzF780AAAAAFaSeYOkqjpkery7f9PdH+ruP02yy2IXBgAAAMDKslCPpNvON6G7f7kItQAAAACwgs37q21JrlpVt09Sc03s7i8uTkkAAAAArEQLBUk7JXll5g6SOsl9FqUiAAAAAFakhYKk07pbWAQAAABAkg38ahsAAAAAzFioR9JzkqSqtk1ys0xOZ/t2d/9qKQoDAAAAYGVZqEfSp6vqZUnOTXJoknckOaeqXlZVV16S6gAAAABYMRYKkl6W5DpJbtzdd+zu2ye5aZLtk7xiKYoDAAAAYOVYKEh6UJIndPeFMw3d/dMkf5nkgYtdGAAAAAAry0JBUnd3z9F4cSbXSwIAAABgC7JQkPTVqnrs7MaqekySry9eSQAAAACsRAv9atuTkxxeVX+e5MRMeiHdKcl2SR62BLUBAAAAsIIsFCR9sLvvUFX3TbJ7kkry0e7+5NKUBgAAAMBKslCQVEkyBEfCIwAAAIAt3EJB0pqqevp8E7v7VYtQDwAAAAAr1EJB0lZJrp6hZxIsp7NffJvlLuEK74YvPGW5SwAAAGCFWyhI+m53v3jJKgEAAABgRbvSAtP0RAIAAADgEgsFSfddsioAAAAAWPHmDZK6+4dLWQgAAAAAK9tCPZIWTVVtX1WHV9XXq+prVfX7VXWdqjq6qr41/L32ctQGAAAAwNyWJUhK8i9J/qu7b5lkjyRfS/LcJJ/s7t2SfHIYBwAAAGCFWPIgqaqumeSeSd6SJN39v9394yR7Jzl0mO3QJA9d6toAAAAAmN9y9Ei6SZL1Sd5WVSdV1Zur6mpJrtfd302S4e9157pzVR1QVeuqat369euXrmoAAACALdzWy7TOOyR5cnefUFX/ko04ja27D05ycJKsXbu2F6dEAAAAYKnscfjHlruEK7wv7XP/zbKc5eiRdG6Sc7v7hGH88EyCpe9V1Q2SZPh7wTLUBgAAAMA8ljxI6u7zk5xTVbcYmu6b5KtJjkyy39C2X5IPLnVtAAAAAMxvOU5tS5InJ3lnVW2T5PQkj8sk1Dqsqh6f5OwkD1+m2gAAAACYw7IESd19cpK1c0y671LXAgAAAMA4y3GNJAAAAABWIUESAAAAAKMIkgAAAAAYRZAEAAAAwCiCJAAAAABGWZZfbQMAgCuqrx30qeUu4Qrvd19wn+UuAWCLpUcSAAAAAKMIkgAAAAAYRZAEAAAAwCiCJAAAAABGESQBAAAAMIogCQAAAIBRtl7uAgAA+G0HPWaf5S5hi/CCdxy+3CUAwKqjRxIAAAAAowiSAAAAABhFkAQAAADAKIIkAAAAAEZxsW0AAIDBgQceuNwlXOHZxrC66ZEEAAAAwCiCJAAAAABGESQBAAAAMIogCQAAAIBRBEkAAAAAjCJIAgAAAGAUQRIAAAAAowiSAAAAABhFkAQAAADAKIIkAAAAAEYRJAEAAAAwiiAJAAAAgFEESQAAAACMIkgCAAAAYBRBEgAAAACjCJIAAAAAGGXZgqSq2qqqTqqqo4bxG1fVCVX1rap6T1Vts1y1AQAAAHBZy9kj6W+TfG1q/KVJXt3duyX5UZLHL0tVAAAAAMxpWYKkqto5yR8lefMwXknuk+TwYZZDkzx0OWoDAAAAYG7L1SPpNUmeneT/hvHfSfLj7r5oGD83yU5z3bGqDqiqdVW1bv369YtfKQAAAABJliFIqqoHJbmgu0+cbp5j1p7r/t19cHev7e61a9asWZQaAQAAALisrZdhnXdL8pCqemCSbZNcM5MeSttX1dZDr6Sdk5y3DLUBAAAAMI8l75HU3c/r7p27e9ckj0zyqe5+dJJPJ9lnmG2/JB9c6toAAAAAmN9y/mrbbM9J8vSqOi2Taya9ZZnrAQAAAGDKcpzadonuPibJMcPw6UnuvJz1AAAAADC/ldQjCQAAAIAVTJAEAAAAwCiCJAAAAABGESQBAAAAMIogCQAAAIBRBEkAAAAAjCJIAgAAAGAUQRIAAAAAowiSAAAAABhFkAQAAADAKIIkAAAAAEYRJAEAAAAwiiAJAAAAgFEESQAAAACMIkgCAAAAYBRBEgAAAJ7oZj8AACAASURBVACjCJIAAAAAGEWQBAAAAMAogiQAAAAARhEkAQAAADCKIAkAAACAUQRJAAAAAIwiSAIAAABgFEESAAAAAKMIkgAAAAAYRZAEAAAAwCiCJAAAAABGESQBAAAAMIogCQAAAIBRBEkAAAAAjCJIAgAAAGAUQRIAAAAAowiSAAAAABhFkAQAAADAKEseJFXVLlX16ar6WlV9par+dmi/TlUdXVXfGv5ee6lrAwAAAGB+y9Ej6aIkz+ju301ylyR/XVW7J3lukk92925JPjmMAwAAALBCLHmQ1N3f7e4vDsMXJvlakp2S7J3k0GG2Q5M8dKlrAwAAAGB+y3qNpKraNcntk5yQ5Hrd/d1kEjYlue7yVQYAAADAbMsWJFXV1ZO8L8lTu/unG3G/A6pqXVWtW79+/eIVCAAAAMBvWZYgqaqunEmI9M7ufv/Q/L2qusEw/QZJLpjrvt19cHev7e61a9asWZqCAQAAAFiWX22rJG9J8rXuftXUpCOT7DcM75fkg0tdGwAAAADz23oZ1nm3JH+W5JSqOnloe36SlyQ5rKoen+TsJA9fhtoAAAAAmMeSB0nd/dkkNc/k+y5lLQAAAACMt6y/2gYAAADA6iFIAgAAAGAUQRIAAAAAowiSAAAAABhFkAQAAADAKIIkAAAAAEYRJAEAAAAwiiAJAAAAgFEESQAAAACMIkgCAAAAYBRBEgAAAACjCJIAAAAAGEWQBAAAAMAogiQAAAAARhEkAQAAADCKIAkAAACAUQRJAAAAAIwiSAIAAABgFEESAAAAAKMIkgAAAAAYRZAEAAAAwCiCJAAAAABGESQBAAAAMIogCQAAAIBRBEkAAAAAjCJIAgAAAGAUQRIAAAAAowiSAAAAABhFkAQAAADAKIIkAAAAAEYRJAEAAAAwiiAJAAAAgFEESQAAAACMIkgCAAAAYBRBEgAAAACjrLggqar2qqpvVNVpVfXc5a4HAAAAgIkVFSRV1VZJ/i3JA5LsnuRRVbX78lYFAAAAQLLCgqQkd05yWnef3t3/m+TdSfZe5poAAAAASFLdvdw1XKKq9kmyV3f/xTD+Z0l+r7v/ZmqeA5IcMIzeIsk3lrzQpbNDku8vdxFsMvtv9bLvVjf7b/Wy71Y3+291s/9WL/tudbP/Vq8r+r67UXevmWvC1ktdyQbUHG2/lXR198FJDl6acpZXVa3r7rXLXQebxv5bvey71c3+W73su9XN/lvd7L/Vy75b3ey/1WtL3ncr7dS2c5PsMjW+c5LzlqkWAAAAAKastCDpC0l2q6obV9U2SR6Z5MhlrgkAAACArLBT27r7oqr6myQfS7JVkrd291eWuazltEWcwncFZv+tXvbd6mb/rV723epm/61u9t/qZd+tbvbf6rXF7rsVdbFtAAAAAFaulXZqGwAAAAArlCAJAAAAgFEESZtBVV1cVSdP3Z67CcvYs6ruOs+061XVUVX1par6alV9ZGjfsaoOn+c+x1TVFvlThHMZs4+GfXDUMPyQTdmPG1HPMVX1jWGffq6qbrGR9z+kqvZZrPpWuqrqqvqPqfGtq2r9zP7bhOVtX1V/NWK+LXq7L6aq2rmqPlhV36qqb1fVvww/ujDf/HvOtb+rav+qet1mqunAqnrm5ljWUquqV1fVU6fGP1ZVb54af2VVPX0TlvvUqrrqPNO2rqp/GvbhzP/aF2zCOu5RVV8Z7r/TfMe5qfl3rapT55k257FwS/sfPMcxcNcNzH9mVe0wDP/scq57i9rWS2Fqf36pqr443/vHzbzO/56n3f5ZwOzXz+Y8Rm1kHW+uqt038j5zHmdXi0U8Dl7y/3FW++X67LDQ8XUTlrX/8L745OGz4xM28v6rfd8/bPiscMvLsYx531tswrKukMdBQdLm8cvuvt3U7SWbsIw9k8z3RuDFSY7u7j26e/ckz02S7j6vu1fck2qF2qh91N1HbuJ+3BiP7u49khya5OVj71RVK+oi+cvk50luXVXbDeN/mOQ7l2N52yfZYJC0seyrcaqqkrw/yRHdvVuSmye5epKDlrWw1e2/MxxTqupKSXZIcqup6XdN8rlNWO5Tk8z3Rvcfk+yY5Dbdfbsk90hy5Y1ZeFVtleTRSV4x/K/+ziIe57ak/8Gzj4FnLsZKamKu95Zb0rZeCjP7c48kz0vyzxtz5+F1tlG6e9HDKhZPd/9Fd391uetYYot1HJzTZvjssNDxdVO8ZzgW75nkn6rqemPudAX5v/uoJJ/N5BfgV4or3HFQkLSIquqFVfWFqjq1qg4ePiylqp4ypMNfrqp3D98MPinJ04bk+B6zFnWDJOfOjHT3l4flXJKUVtV2w7K+XFXvSTLzATtVdb+q+p/hW6v3VtXVF/WBryJVtVdVfb2qPpvkj6faL/nGqKoePuzDL1XVcUPbtlX1tqo6papOqqp7T93v/VX1XzX5Vv5lI8o4LsnNhvvP95w5pibf9B+b5G9nPYb/NyTVW9rr+aNJ/mgYflSSd81MqKrrVNURw+vh+Kq67dB+YFW9ddiep1fVU4a7vCTJTYfX38uHeZ897N8vVdVl3hiM3VdVtaaq3jfM+4WqutvibZJV6z5JftXdb0uS7r44ydOS/HlV7V5Vnxn+f835zXtV3Wl4Hd5kVvuDq+qEYdonZt5ELfA8SFW9oCbfGn0iyUZ9Y7TCfC6XfjlxqySnJrmwqq5dVVdJ8rtJTkqSqnrW8Nz8clX9w9B2tar68PD8P7WqHjFspx2TfLqqPj29spp8i/qEJE/u7l8lSXdf2N0HTs1zRFWdWJPeRgdMtf+sql5cVSdk8qF43yQvrKp3zjrObVVVL5+q9YmzH/RCx8IFbJH/g2tWz4ia9HzecwP3meu5smtVfa2qXp/ki0l2WWARW+S2XmTXTPKj5LK9CKrqdVW1/zB85rDNP5vk4cN2fmlVfb6qvlnDe8+qutXQdvKwn3cb2n82/K1huV+tqg8nue7U+u5YVccOr/OPVdUNlmojrEbzvT8Y2o8ejnlvrKqz6tIego+Z2j9vHP4v7ltVrxqm/21VnT4M33TY35f0zhzmP2R43Z1SVU8bpt+sJsfJmV5uNx3KvHpVHV6T98rvnHmdrhKjjoNVdfWq+uTwuE+pqr2TuY+DU8t+8tT8txzmn/7scEhV/WtV/XdN3mfsM7RfqapeX5Pj4FFV9ZGq2qfmOL5W1aOG5Z9aVS+dWXFNjpkHDXUdXxsIiLr7giTfTnKjqrrzUNNJw99bTNX+3qr6UJKPT9+/5nmPtVLV5HPu3ZI8PlNBUlW9p6oeODV+SFX9SU2OYRt6n+lz31y62+1y3pJcnOTkqdsjhvbrTM3zH0kePAyfl+Qqw/D2w98DkzxznuXfP8mPk3w6yQuS7Di075rk1GH46UneOgzfNslFSdZmkr4fl+Rqw7TnJHnhcm+zlbCPkmyb5JwkuyWpJIclOWqYf/8krxuGT0my06z99YwkbxuGb5nk7GF5+yc5Pcm1hvGzkuwyRz3HJFk7DD8rk28NFnrOHJPk9VPTDkmyT5KXJXljMvkFxi3lluRnw/P88GE7n5zJNy4z+++1SV40DN8nycnD8IGZfEN1leG18YNMekxc8loa5nvAMN9Vp/fLzHbfyH31n0nuPgzfMMnXlnv7rbRbkqckefUc7ScN+3nbYXy3JOuG4T2THJXJm8QTk9xwaJ9+7V575rWR5C+SvHIDz4M7Dq/3q2by4ey0zPN/eTXckpw5POeemMmXFf8vyQMzeYN13DDP/TL56drK5Mulo5LcM8mfJHnT1LKuNbXMHeZY122TnLSBemZeR9tl8ob+d4bxTrLv1HzTr7NLXptJDkjyd8PwVZKsS3LjjDgWzlHLMdmC/gfnt4+BH5j9WhnGj0qy5+z9nORnG3iu7Jrk/5LcZZ51b1Hbeon359eT/CTJHYf2PTMcB4fx1yXZf2qfPnvWfpn5n/jAJJ8Yhl+byTfnSbJNku1mPQ/+OMnRSbbK5IPvj4f9c+VM/q+uGeZ7xMxrcUu+5bLvP8/OpceoOd8fDPvtecPwXpn8j9whk+DjQ0muPEx7fZLHJrl+ki8MbYcn+UKSnZLsl+Sfp/b32kyOc0dP1TfzvvaEJA8bhrfN5Di45/D82nl4zf/PTL2r5ZZxx8Gtk1xzGN4hk2N/ZeHj4JOH4b9K8uZheP+pfXtIkvcO2233JKcN7fsk+cjQfv1MQuB9ppY78393x+G5smao71NJHjpM61z6//JlGY6Lsx73dC03SXJBkutk8t5m66H9D5K8b2r+c3PpcXrPzPEeazXckjwmyVuG4f9Ocodh+GFJDh2Gt8nkM+B2w3N9rveZu+bS9xY+981xW7FdpVaZX/ak6+Bs966qZ2fyBL1Okq9kcgD4cpJ3VtURSY7Y0MK7+2NDCrxXJh9wT6qqW8+a7Z5J/nWY/8tV9eWh/S6Z/AP73BBybpPJgWBLc5l9VFW3S3JGd39rGH9HJh9UZvtckkOq6rBMTr9Jkrtn8mYr3f31qjork9NxkuST3f2TYZlfTXKjTP5ZzfbOqvplhgPS0DbfcyZJ3jPr/n+f5ITunqvmK7zheb5rJr2RPjJr8t0zeQOQ7v5UVf1OVV1rmPbh7v51kl9X1QVJ5vom5w8yOWD8YljGD+eYZ+y++oMku099iXfNqrpGd184+sFe8VUmb4zmaq8kbxperxfn0tdZMnlTfXCS+3X3eXPcf+ck76nJt+LbJDljatpcz4N7ZPIh+xdJUlVHXr6Htexmvo29a5JXZfLB4q6ZfDCYud7J/YbbScP41TN5I/WZJK8YvgU9qrs/szErrqrHZfIt2u8kuWt3n5PkKVX1sGGWXYb1/CCT/fq+EYu9X5Lb1qXXCbjWsIxvTs0z37FwLlvS/+D53qdsjPmeK2cnOau7j1/gvlvStl4Kl+zPqvr9JG+f433hXGZv15n3NCdm8qEpmbxHfEFV7Zzk/TPvkabcM8m7etJz9Lyq+tTQfoskt05y9HC82yrJd8c/pCus33rt1aSH2Mx12+Z8f5DJe5iHJUl3/1dV/WiYft9MgqAvDPfZLskF3X3+0KvmGpn8b/3PTPbTPXLpPp5xepKbVNVrk3w4yceH++3U3R8Y1vmrodYk+Xx3nzuMn5zJ8+Szl3ObLKUxx8HK5NSve2YSiu+UyXuCUzL/cXD6tfPHmdsR3f1/Sb461Wvo7kneO7SfX7N69065U5Jjunt9klTVOzPZp0ck+d9MQp6Z9f/hPMt4RFXdPcmvkzyxu39YVbskObQmPQ07v336+dGz3u9u6D3WSvWoJK8Zht89jH8xkzMZ/rUmvdH2yiRI/OXw+eB187zPnOFz3xwESYukqrbN5JuCtd19TlUdmElSmUxOx7lnkock+fuq+v/s3XmYbFV5L/7vyxDBSETiUZFBjGLikICKQ36OaBKHaNAbNaARNUZjfprBqHFMJN6QmMQpmmiuxgHigMQhosGII4pXQSAI4oiKgqAcVASDA+B7/9i7pWi66+xzON2nOefzeZ5+umrtvdd+u6q6uvpba6267dK9XGn8xX5zkjfXMGz5nhmePK6y21KlZHhiOGSTfpCt31K32VV36H5SVd0lw/122vhEM29o749mLl+R5X/PHtXdJy9c2cBjJhnWBZr1qSR3rKrdlgk6tgXHJHlRhndOfn6mfan7Z+G+nnL/LBdsDBs37r7aLsmvdvcPluuPnJkx+FtQVT+X4QXxo5J8K8l+GW7LH87sdn6G2/32GUZ6LvaKJC/p7mNqmLJz2My25R4HG3xOuBZZWB/ilzOMADonw7tqFyd53bhPZXjH+v8sPriq7pjhndu/rarjuvsFc851VpK9F0LSHqYpvr6GaWnbj7f/r2X4Xbi0qj6SK39nfjj+U7ohleFd4PctqnOfRftNvQ+39efgy3PVJQ52Wm7H0ZKPlfH2X3zbLLat39Yrprs/UcO0p3XZ8H26+HZdeB786XNgd7+5hmmmv5nkfVX1+939oUXHLfd688zu/tVN+DG2VUu+PliY3rKEyjCi4tlLbPtEkscl+UKGNwJ+L8mvZnjO/6nu/m5V7ZdhtsOTM0wl/tMsb+pr2rVqyt/BR2X4/bljd19WVWdnGKHyxTl/B6/2u7OE2duuFn3fkHn7XdbjMJUNnP+t3f2URW3/O8mHu/uh43P3R2a2LX5+2NBrrDWnqn4+w0yE21VVZwi0u6r+vLt/OL72uF+GEZMLS2I8Ncu/zvxp13NOu83+37fl59ZtvRYeCBfWMFfzp3NjMwx5+3CSP8+wyO/1klySZJelOqqq+9S4iv/4rsEtMrwDOOujGZ4IM74r9Stj+yeT3K2qFuZiXreqlkpat0WfT3LzunIe+JJhW1XdortP7O6/THJhhn9uZ2/vW2UYNvuFa1jPko+ZOf4rw9o+/zk+LrZFr0vygu4+Y1H77P1z7yQXdvfFc/pZ/Pt3XIb1eRZ+73ZbtP/G3FfHJfnpH/IxiOSqPpjkulV1aDKshZPkxRmG8u6Y5Pzx3btHZ3hRsOCiDP/s/E0tvbbL9XPlIuyPmVDHR5M8tIZ1dnZJ8uCN/1HWlI8neVCS73T3FeMLj10z/HOxMDL1fRke69dLkho+Je1GVXXTJJd29xszhLV3GPdf8m/VOIrrtRne1dtp7Gv7DCPBkuG++O4YIv1ShtGyG+t9Sf6wqnYc+79VVf3son2W+1s4xbb2HHx2kv1rWLNjryR33sD+Sz5WNvHc29ptvWLG36ftM4zu+1qGES7XGd9lv+8m9PcLSb7S3S/P8GbN4t+hjyY5uIa1dnZPcuDY/oUk62oYIZWq2nHKG6XbuOVeH5yQIeBJVf1GhmnayfC38mELv3c1rAd5s3HbR5M8ffz+3xnulx8tjJSYOccNk2zX3W/PMMLhDuPro3Or6iHjPtepzfTpYWvAlL+D188wsuuyGta+uVmSzPk7eE2ckOS3x+fdG2d4I3TB7N/XE5Pcq6puOP4tPSTJ8Zvh/LOvix67gX039BprLXpYkiO7+2bdvU9375VhNPrdx+1HZQhc75Hhb1oy3CbLvc5c4P++JVzbUuW1aucahnsu+K/uflZVvSbDsMizM6SIyfDgfOP4B74yrAtyUQ2Lm72thgXe/mjR8Mk7ZnhxvvBO079296cWvQv7qgzv/p6eYQ72SUnS3etrGEb7lhqG8iXJ83LVqQDbguXuoydm+IW8MMOT+1JDw/+hhiGgleGP+KczhFD/UlVnZHgH8LHd/aPl30TasPFxsNRjZt4x/z4+mRxTVQ/c1ka9jMOt/3GJTYflyt+HS7OBEKG7v13Dx3F+Jsl7u/sZ4wu6k6vqxxmmzj1nZv+Nua/+OMk/j7XskOGP0ZMm/ojbhO7uGqY8vbKq/iLD89zCbb53krdX1cMzrBP3P4uO/VZVPTjJe6vq9xZ1fViSf6+qb2QI1W++gTpOrWGB5tMy/EO2UdO51qAzMqz38OZFbdfr7guTpLuPq6pbJ/nE+Pz1/QzrC9wyw3PfT5JcluQPx+NfneG2Pr+7D8xVPTfDu52fqapLkvwgw6eTnJfhnc0njb8HX8hwf2ysf80wreLU8R379UkesmifJf8WTrENPgd/PMML7DMyvFN/6ryd5zxWpowmW9zXtnZbb26zr2kqyWPGUX3n1DAN//QkX8qV0xA3xu8k+d2quizJNzN8cvCsd2Z4x/+MDK8lj0+S7v5xDdNOXz6+xt0hw/SSMzehhm3Fcq8P/irD6/bfyXD7np/kku6+sKqel2E62nYZnpufnCv/Xu2VYbrOFVV1TobXqovtkeE5cmEwwcLopkcn+T9V9YKx34dv/h93i9jg38Ekb0ry7qo6OVeuPZYMo5iW+jt4Tbw9Q8D7mQy/PydmmGaXLPr7WlXPzvC6p5Ic293v2gzn//sMU9v+LMO6S3Mtfo3V3SduhhpW0iEZwpZZb0/yyAy/I8clOTLJMd3943H7KzPndebMPv7vW2RhEVIAAAC2oPGN3yu6+/JxhNer+pqvccYaUVXX6+7v1zAN66Qkd+vub27pumBjGZEEAACwNuyd5Ohx1NCPkzxhC9fD5vWeqto1w9Tv/y1E4trKiCQAAAAAJrHYNgAAAACTCJIAAAAAmESQBAAAAMAkgiQAYNVV1U2q6qiq+nJVfbaqjq2qW43bbltVH6qqL1bVl6rqL2r8nN2qemxVdVXdd6avh45tDxuvf6Sqvl4zn81bVf9RVd8fL9+7qt6zqJ43LDr+5JltB1TVR2aPrarHVdVp49ePq+qM8fK/j3XvPHP8f1bVwcvcDv9YVd+Y+TjuhZ9x/djf56vqqTPbDhv3P23ma9d5/S06373H2+rBM23vqap7z1xfV1WXVdUfLDr27Kr62KK206rqMzN9f29Rbb+2VB0AwLWXIAkAWFVjwPPOJB/p7lt0922SPCfJjccA5pgkL+zuWyXZL8n/l+T/n+nijCSHzFw/OMmnF53moiR3G8+3a5LdN7LMG1XVA5bb2N2v7+79x4/lPi/JgeP1hyd5R5Lnjud+SJIdu/uoxX2MYc9Dk5yT5J6LNr917PtuSZ5bVXvNbHvpwrnHr4sm9Dfr3IX6lvHwJJ/MVW/jBbss1FJVt15i+8cW1faBOecBAK6FBEkAwGo7MMll3f0vCw3dfVp3fyzJI5N8vLuPG9svTfKUJM+aOf5jSe5cVTtW1fWS3DLJaYvOcVSGgClJ/leGcGdj/EOS523kMQtekOThVbV/khcmefIy+x2Y5DNJXpWlQ5t097eTnJVpQdgG+xt9Osn3qurXl9l+SJKnJdmzqvZYtO3oJL8zs99bJtQFAGxFBEkAwGq7XZJTltl228XbuvvLSa5XVT+30JTkA0nul+SgDCOYFvtgkntW1fYZAqW3bmSNn0jyo6o6cCOPWwi/np7ko0mO6u4vLbPrQhDzziQPqqodF+9QVXsn2SnJ6TPNT52ZOvbhjelvxl9niaBsHG10k+4+KVcNjRa8LUMwlyQPTvLuRdvvsWhq2y3m1AAAXAsJkgCAtaQyBEVLmW1fGHF0cJYeFXNFkhMyBCE7d/fZy/SzXP/JMmHLFN397gzT61651Paq+pkkD0zyH919cZITk/zGzC6/U1VnJvlKkn/s7h/ObJud2nbgxP4W1/ex8bh7LNp0cIYAKRlu48Ujm76T5Lvjmk+fS3Lpou2Lp7Z9ebkaAIBrJ0ESALDazkxyxznbDphtqKpfSPL97r5koW0cMXO7JDfs7i8u09dRSV6RK4ORBd9OcoNFbbsluXC2obs/lGE00F2X/Unm+8n4tZT7J7l+kjOq6uwkd89VQ5u3dvdtk9wjyYur6iYbONeG+lvK4bn6WkmHJHns2McxSfarqn0X7fPWJP8c09oAYJskSAIAVtuHklynqp6w0FBVd6qqeyV5U5K7L3za17j49suT/P0S/Tw7wyLdy/lYkr/N1QOPLyW56cJi0VV1swyLei9eZykZwpY/n/JDbaRDkvx+d+/T3fskuXmS36iq687u1N2fSPJvSf5kc/S3qO/jMgRq+yVJVf1ikp/t7j1m+vnbXLnW1IJ3Zrg/3jflBwUAti6CJABgVXV3Z/h0sV+vqi+PU7gOS3Jed/8gw7pHz6uqL2T4hLZPJfmnJfp5b3d/eHH77Hm6+0XdvXik0Y+S/G6S11fVaRnW/fn97v7eEn0cm2T9Jv6oSxrDnfsl+c+Z8/xPhql4D17ikL9L8riq2mW8/tRF6xDdZiP7m3V4kj3Hy4dkCIlmvT2LRjZ19yXd/Xfd/eMl+lu8RtLDNnB+AOBapobXcgAAAAAwnxFJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATCJIAgAAAGASQRIAAAAAkwiSAAAAAJhEkAQAAADAJIIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAGxRVdVVdctltj2qqo6b0MdhVfXGzV8dAACzBEkAsJWrqo9U1Xer6jpbupaN1d1v6u7f2NJ1AAAwECQBwFasqvZJco8kneS3NrDv9qtQEluJa/vjpap22NI1AMC1kSAJALZuhyb5ZJI3JHnM7IaqekNVvaqqjq2q/0lyYFVdp6peVFVfr6pvVdW/VNXO4/43qKr3VNX6cYTTe6pqz6VOWlWPq6p3z1w/q6qOnrl+TlXtP3PIr1XVl8Z+/7mqatzvsVV1wsxxt62q91fVd8b6njPTx89U1ZFVdUlVnVlVByx3oyzXz/jzv6yqzhu/XrYwkquq7l1V51bV06rqgqo6v6oeN9PnA6vqs+P5v1FVT1/qZxjbfjqdb7wfXllV762q71fVx6vqJuO5v1tVn6+q288ce9Oqevt4P3y1qv54zs+5sX3fehzBdtF4G/7Wor4mP16WqOWx4/lfUVXfG89930U/1zHjfXJWVT1hbN+pqn5QVTccrz+vqi6vqp8br/91Vb1s5v5b7vG7cP89s6q+meT1y91uAMDyBEkAsHU7NMmbxq/7VdWNF21/ZJLDk+yS5IQkf5fkVkn2T3LLJHsk+ctx3+0y/PN9syR7J/lBkn9a5rzHJ7lHVW1XVbsn2THJ3ZKkqn4hyfWSnD6z/4OS3CnJfkkekeR+izusql2SfCDJfyW56VjfB2d2+a0kRyXZNckxy9W2gX6em+Su48+/X5I7J3nezOE3SXL98XZ5fJJ/rqobjNtem+QPunuXJLdL8qFlbpulPGI8zw2T/CjJJ5KcOl5/W5KXjLVvl+TdST491nDfJH9aVVe7vTah7x3Hvo9LcqMkf5TkTVX1izN9bczjZSl3SfKV8dzPT/KOqtpt3PaWJOdmuE8eluRvW2AARwAAIABJREFUquq+3f3DJJ9Kcq9xv3sm+VrGx9N4/fjx8obquUmS3TI8hp84p04AYBmCJADYSlXV3TP8w3x0d5+S5MsZgoBZ7+ruj3f3TzKEDE9I8tTu/k53X5Lkb5IcnCTd/e3ufnt3XzpuOzxX/nN/Fd39lSSXZPiH/l5J3pfkG1X1S+P1j43nXPDC7r6ou7+e5MPjcYs9KMk3u/vF3f3D7r6ku0+c2X5Cdx/b3Vck+bcMQdBS5vXzqCQv6O4Lunt9kr9K8uiZYy8bt1/W3ccm+X6SX5zZdpuq+rnu/m53n7rM+Zfyzu4+ZQxN3pnkh9195PizvDXJwqihOyVZ190v6O4fj7fzazLeR9ew77tmCPheOPb9oSTvSXLITF+THy/LuCDJy8bb761JvpDkN6tqryR3T/LM8T45Lcm/5srb/vgk96phOtqvJHn5eH2n8Tb52DiKbUP1/CTJ87v7R939gzl1AgDLMDccALZej0lyXHdfOF5/89j20pl9zpm5vC7JdZOcMvxPniSpJNsnSVVddzz2/kkWRuHsUlXbj6HEYscnuXeGkSHHJ7koQ4j0q7lyBMmCb85cvjRDoLHYXhnCsOUs7mOnqtqhuy/fiH5ummG0y4KvjW0Lvr2ov9lafzvDyJ8XVtXpSZ7V3Z+YU++sb81c/sES1xfOcbMkN62qi2a2b5/kY5uh75smOWdRwPe1DKN6Fkx+vCzjG93di/q/6fi1EP7MbluYnnh8hpFTd0hyRpL3ZxgBdtckZ3X3hVV1own1rB8DNQBgEwmSAGArNK4L84gk24/rwSTJdZLsWlX7dfenx7bZf+ovzBAs3La7v7FEt0/LMPrmLt39zRrWOPrvDP+sL+X4JA9OcvMMI0MuyjDi51ez/JS4ec7JVUfHbKp5/ZyXIaw5c7y+99i2Qd39qSQHjVPEnpLk6Ayh1f9kCDiSJFV1k00rO8lQ+1e7e99r0MdyzkuyV1VtNxMm7Z3kizP7bMzjZSl7VFXNhEl7Z5iGeF6S3apql5kwae8kC/3+3wyPvYcmOb67P1tVeyf5zVwZSk6pp5dpBwAmMrUNALZOD0lyRZLbZJgmtn+SW2cYuXLoUgeM4cFrkrx0HN2RqtpjZv2dXTL8o37RuK7N8zdQw/FJDkyyc3efO577/kl+PkMAtbHek+QmVfWn46LKu1TVXTZzP29J8ryqWjcu7vyXSd64oQ6r6meq6lFVdf3uvizJxRlu/2RYz+i2VbX/OBXrsE2oecFJSS4eF4zeuaq2r6rbVdWdrkGfC07MEHr9eVXtWFX3zhAEHrXUzhMeL0u5UZI/Hvt/eIbH5LHdfU6GsOhvx8W1fyXDGlRvGs91aZJTkjw5VwZH/zfJHyxc38R6AICNJEgCgK3TY5K8vru/3t3fXPjKMBLoUbX8R58/M8lZST5ZVRdnWJR6YQ2glyXZOcPIj09mWKx6Wd39xQxrCH1svH5xhoWWP77MVLi5xpEqv54h3Phmki9lCKo2Zz9/neTkDAuBn5FhUeq/ntj1o5OcPd5uT0ryu+P5vpjkBRluyy9lWKR6k4y324MzBINfzXBf/GuGBcCvke7+cYYFyx8w9vvKJId29+fnHDbv8bKUE5PsO/Z/eJKHdfe3x22HJNknw+ikd2ZYy+j9M8cen2HR9pNmru+S5KPXoB4AYCPVVaepAwDA5ldVj03y+9199y1dCwCw6YxIAgAAAGASQRIAAAAAk5jaBgAAAMAkRiQBAAAAMMlyn9hyrXDDG96w99lnny1dBgAAAMBW45RTTrmwu9ctte1aHSTts88+Ofnkk7d0GQAAAABbjar62nLbTG0DAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATLLDli4AAAAA2Lbt97b3bekStnqfftj9Nks/RiQBAAAAMIkgCQAAAIBJBEkAAAAATCJIAgAAAGASQRIAAAAAk6xYkFRVO1XVSVX16ao6s6r+amx/Q1V9tapOG7/2H9urql5eVWdV1elVdYeVqg0AAACAjbfDCvb9oyT36e7vV9WOSU6oqveO257R3W9btP8Dkuw7ft0lyavG7wAAAACsASs2IqkH3x+v7jh+9ZxDDkpy5HjcJ5PsWlW7r1R9AAAAAGycFV0jqaq2r6rTklyQ5P3dfeK46fBx+tpLq+o6Y9seSc6ZOfzcsW1xn0+sqpOr6uT169evZPkAAAAAzFjRIKm7r+ju/ZPsmeTOVXW7JM9O8ktJ7pRktyTPHHevpbpYos9Xd/cB3X3AunXrVqhyAAAAABZblU9t6+6Lknwkyf27+/xx+tqPkrw+yZ3H3c5NstfMYXsmOW816gMAAABgw1byU9vWVdWu4+Wdk/xaks8vrHtUVZXkIUk+Mx5yTJJDx09vu2uS73X3+StVHwAAAAAbZyU/tW33JEdU1fYZAquju/s9VfWhqlqXYSrbaUmeNO5/bJIHJjkryaVJHreCtQEAAACwkVYsSOru05Pcfon2+yyzfyd58krVAwAAAMA1syprJAEAAABw7SdIAgAAAGASQRIAAAAAkwiSAAAAAJhEkAQAAADAJIIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATCJIAgAAAGASQRIAAAAAkwiSAAAAAJhEkAQAAADAJIIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYJIdtnQBAKxdx9/zXlu6hK3evT56/JYuAQAAJjMiCQAAAIBJBEkAAAAATCJIAgAAAGASQRIAAAAAkwiSAAAAAJhkxYKkqtqpqk6qqk9X1ZlV9Vdj+82r6sSq+lJVvbWqfmZsv854/axx+z4rVRsAAAAAG28lRyT9KMl9unu/JPsnuX9V3TXJ3yV5aXfvm+S7SR4/7v/4JN/t7lsmeem4HwAAAABrxIoFST34/nh1x/Grk9wnydvG9iOSPGS8fNB4PeP2+1ZVrVR9AAAAAGycFV0jqaq2r6rTklyQ5P1Jvpzkou6+fNzl3CR7jJf3SHJOkozbv5fk55fo84lVdXJVnbx+/fqVLB8AAACAGSsaJHX3Fd29f5I9k9w5ya2X2m38vtToo75aQ/eru/uA7j5g3bp1m69YAAAAAOZalU9t6+6LknwkyV2T7FpVO4yb9kxy3nj53CR7Jcm4/fpJvrMa9QEAAACwYSv5qW3rqmrX8fLOSX4tyeeSfDjJw8bdHpPkXePlY8brGbd/qLuvNiIJAAAAgC1jhw3vssl2T3JEVW2fIbA6urvfU1WfTXJUVf11kv9O8tpx/9cm+beqOivDSKSDV7A2AAAAADbSigVJ3X16ktsv0f6VDOslLW7/YZKHr1Q9AAAAAFwzq7JGEgAAAADXfoIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATCJIAgAAAGASQRIAAAAAkwiSAAAAAJhEkAQAAADAJIIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEyyw5YuAABYGf/0tHdv6RK2ek958YO3dAkAAKvKiCQAAAAAJhEkAQAAADDJigVJVbVXVX24qj5XVWdW1Z+M7YdV1Teq6rTx64Ezxzy7qs6qqi9U1f1WqjYAAAAANt5KrpF0eZKndfepVbVLklOq6v3jtpd294tmd66q2yQ5OMltk9w0yQeq6lbdfcUK1ggAAADARCs2Iqm7z+/uU8fLlyT5XJI95hxyUJKjuvtH3f3VJGclufNK1QcAAADAxlmVNZKqap8kt09y4tj0lKo6vapeV1U3GNv2SHLOzGHnZn7wBAAAAMAqWvEgqaqul+TtSf60uy9O8qokt0iyf5Lzk7x4YdclDu8l+ntiVZ1cVSevX79+haoGAAAAYLEVDZKqascMIdKbuvsdSdLd3+ruK7r7J0lekyunr52bZK+Zw/dMct7iPrv71d19QHcfsG7dupUsHwAAAIAZK/mpbZXktUk+190vmWnffWa3hyb5zHj5mCQHV9V1qurmSfZNctJK1QcAAADAxlnJT227W5JHJzmjqk4b256T5JCq2j/DtLWzk/xBknT3mVV1dJLPZvjEtyf7xDYAAACAtWPFgqTuPiFLr3t07JxjDk9y+ErVBAAAAMCmW5VPbQMAAADg2k+QBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJPssNyGqvpqkp5tmrne3X2LlSwMAAAAgLVl2SApyQGLrm+X5BFJnp7kv1esIgAAAADWpGWDpO7+dpJU1XZJHp3kGUlOS/Kb3f3Z1SkPAAAAgLVi3tS2HZP8XpKnJjkhyUHd/eXVKgwAAACAtWXe1LavJrk8ycuSfD3JflW138LG7n7HCtcGAAAAwBoyL0j6QIbFtfcbv2Z1EkESAAAAwDZk3hpJj13FOgAAAABY47abt7GqbldVR1TVyVX1qfHyL69WcQAAAACsHcsGSVV1UJJ3Jjk+w6Lbvz9efse4DQAAAIBtyLw1kl6Q5Ne7++yZtk9X1YeSvGv8AgAAAGAbMW9q246LQqQkydi240oVBAAAAMDaNC9Iuqyq9l7cWFU3S3L5ypUEAAAAwFo0b2rb85N8oKr+JskpSTrJnZI8K8kzV6E2AAAAANaQZYOk7v6Pqvpqkqcl+aMkleTMJI/o7k+vUn0AAAAArBHzRiRlDIwOXaVaAAAAAFjDlg2SqurdGaazLam7f2tFKgIAAABgTZo3IulFq1YFAAAAAGvevCDpcd392NUqBAAAAIC1bbs5235l1aoAAAAAYM2bNyLpulV1+wyf1nY13X3qypQEAAAAwFo0L0jaI8mLs3SQ1EnusyIVAQAAALAmzQuSzupuYREAAAAASeavkQQAAAAAPzUvSHrmUo1VtVdVPWOF6gEAAABgjVo2SOru4xYuV9UNq+oPq+qjST6S5MarUBsAAAAAa8iyayRV1S5JHprkkUluleSdSX6hu/dcpdoAAAAAWEPmLbZ9QZKTkjwvyQnd3VX10NUpCwAAAIC1Zt4aSc9JslOSVyV5dlXdYnVKAgAAAGAtmrdG0ku7+y5JfitJJfmPJDetqmdW1a1Wq0AAAAAA1oZ5I5KSJN39le4+vLt/Ocmdklw/yXtXvDIAAAAA1pR5ayRdTXefkeSMqrr3ypQDAAAAwFq1wRFJy/DJbQAAAADbmE0Nkjaoqvaqqg9X1eeq6syq+pOxfbeqen9VfWn8foOxvarq5VV1VlWdXlV3WKnaAAAAANh4y05tq6r/tdymJDtP6PvyJE/r7lOrapckp1TV+5M8NskHu/uFVfWsJM9K8swkD0iy7/h1lwyfFneXqT8IAAAAACtr3hpJD56z7T0b6ri7z09y/nj5kqr6XJI9khyU5N7jbkck+UiGIOmgJEd2dyf5ZFXtWlW7j/0AAAAAsIUtGyR19+M210mqap8kt09yYpIbL4RD3X1+Vd1o3G2PJOfMHHbu2CZIAgAAAFgD5k1t+7NFTZ3kwiQndPdXp56gqq6X5O1J/rS7L66qZXddoq2X6O+JSZ6YJHvvvffUMgAAAAC4huYttr3Loq+fS3JAkvdW1cFTOq+qHTOESG/q7neMzd+qqt3H7bsnuWBsPzfJXjOH75nkvMV9dveru/uA7j5g3bp1U8oAAAAAYDOYN7Xtr5Zqr6rdknwgyVHzOq5h6NFrk3yuu18ys+mYJI9J8sLx+7tm2p9SVUdlWGT7e9ZHAgAAAFg75i22vaTu/k7NmZ82425JHp3kjKo6bWx7ToYA6eiqenySryd5+Ljt2CQPTHJWkkuTbLY1mgAAAAC45jY6SKqq+yT57ob26+4TsvS6R0ly3yX27yRP3th6AAAAAFgd8xbbPiNXX+x6twzrFh26kkUBAAAAsPbMG5H0oEXXO8m3u/t/VrAeAAAAANaoeUHSt5I8Kcktk5yR5LXdffmqVAUAAADAmrPdnG1HJDkgQ4j0gCQvXpWKAAAAAFiT5o1Iuk13/3KSVNVrk5y0OiUBAAAAsBbNG5F02cIFU9oAAAAAmDciab+qujhJjdd3nrne3f1zK14dAAAAAGvGskFSd2+/moUAAAAAsLbNG5GUJKmqA5PcNkknObO7P7LSRQEAAACw9iwbJFXVHknekeSHSU7JMKXtEVW1c5KHdvc3VqdEAAAAANaCeSOS/inJq7r7DbONVXVoklcmOWgF6wIAAABgjZn3qW23WRwiJUl3H5nkl1asIgAAAADWpHlB0pKLbVfVdsttAwAAAGDrNS9IendVvaaqfnahYbz8L0mOXfHKAAAAAFhT5gVJf57ke0m+VlWnVNXJSc5OcnGSp69CbQAAAACsIcsutt3dlyV5elX9RZJbZvjUtrO6+9LVKg4AAACAtWPZEUlVtW9VvSvJp5I8J8m3hUgAAAAA2655U9tel+Q9SX47yalJXrEqFQEAAACwJi07tS3JLt39mvHyP1TVqatREAAAAABr07wgaaequn2GtZGSZOfZ690tWAIAAADYhswLks5P8pKZ69+cud5J7rNSRQEAAACw9sz71LYDV7MQAAAAANa2eYttAwAAAMBPCZIAAAAAmGSTgqSquunmLgQAAACAtW1TRyR9crNWAQAAAMCat6lBUm3WKgAAAABY8zY1SOrNWgUAAAAAa94Oy22oqldk6cCokuy6YhUBAAAAsCYtGyQlOXkTtwEAAACwFVo2SOruI5Zqr6qdkjx4xSoCAAAAYE2atEZSVW1fVQ+oqiOTfC3J76xsWQAAAACsNfOmtqWq7pnkkUl+M8lJSe6W5Obdfekq1AY/9fUX/PKWLmGrt/dfnrGlSwAAAGCNm7fY9rlJvp7kVUme0d2XVNVXhUgAAAAA26Z5U9venmSPDNPYHlxVP5ulP8UNAAAAgG3AskFSd/9Jkn2SvCTJgUm+mGRdVT2iqq63OuUBAAAAsFbMXWy7Bx/q7idkCJUemeQhSc5e+dIAAAAAWEvmrZH0hu5+7ML17r4sybuTvLuqdl6F2gAA4Frnc4d/aEuXsNW79XPvs6VLANhmzRuR9CvLbejuH6xALQAAAACsYcuOSEpy3aq6fZJaamN3n7oyJQEAAACwFs0LkvZI8uIsHSR1krnjSavqdUkelOSC7r7d2HZYkickWT/u9pzuPnbc9uwkj09yRZI/7u73Tf8xgLXsbq+425YuYav38T/6+JYuAQAA2AbMC5LO6u5rMvn4DUn+KcmRi9pf2t0vmm2oqtskOTjJbZPcNMkHqupW3X3FNTg/AAAAAJvR3E9tuya6+6NJvjNx94OSHNXdP+ruryY5K8mdV6o2AAAAADbevCDpmUlSVTtV1e2q6rZVtdNmOOdTqur0qnpdVd1gbNsjyTkz+5w7tgEAAACwRswLkj5cVX+fIdQ5Iskbk5xTVX9fVTtu4vleleQWSfZPcn6GNZiS5ddhupqqemJVnVxVJ69fv36pXQAAAABYAfOCpL9PsluSm3f3Hbv79hlCoF2TvGjOccvq7m919xXd/ZMkr8mV09fOTbLXzK57JjlvmT5e3d0HdPcB69at25QyAAAAANgE84KkByV5QndfstDQ3Rcn+cMkD9yUk1XV7jNXH5rkM+PlY5IcXFXXqaqbJ9k3yUmbcg4AAAAAVsa8T23r7r7a9LLuvqKqlpx2Nquq3pLk3kluWFXnJnl+kntX1f4Zpq2dneQPxj7PrKqjk3w2yeVJnuwT2wAAAADWlnlB0mer6tDuPnK2sap+N8nnN9Rxdx+yRPNr5+x/eJLDN9QvAAAAAFvGvCDpj5K8rap+L8kpGUYR3SnJzhmmpQEAAACwDZkXJL2ru+9QVfdNcpsMn6z23u7+4OqUBgAAAMBaMi9IqiQZgyPhEQAAAMA2bl6QtK6q/my5jd39khWoBwAAAIA1al6QtH2S62UcmQQAAADAtm1ekHR+d79g1SoBAAAAYE3bbs42I5EAAAAA+Kl5QdJ9V60KAAAAANa8ZYOk7v7OahYCAAAAwNo2b0QSAAAAAPyUIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCQ7bOkCAAAA4Jo6+t/vvKVL2Oo94uEnbekSWAOMSAIAAABgEkESAAAAAJOY2gYAsMYc/rsP29IlbBOe+8a3bekSAOBax4gkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATLJiQVJVva6qLqiqz8y07VZV76+qL43fbzC2V1W9vKrOqqrTq+oOK1UXAAAAAJtmJUckvSHJ/Re1PSvJB7t73yQfHK8nyQOS7Dt+PTHJq1awLgAAAAA2wYoFSd390STfWdR8UJIjxstHJHnITPuRPfhkkl2raveVqg0AAACAjbfaayTduLvPT5Lx+43G9j2SnDOz37ljGwAAAABrxFpZbLuWaOsld6x6YlWdXFUnr1+/foXLAgAAAGDBDqt8vm9V1e7dff44de2Csf3cJHvN7LdnkvOW6qC7X53k1UlywAEHLBk2LeWOzzhy0ypmo5zyD4du6RIAAACAFbLaI5KOSfKY8fJjkrxrpv3Q8dPb7prkewtT4AAAAABYG1ZsRFJVvSXJvZPcsKrOTfL8JC9McnRVPT7J15M8fNz92CQPTHJWkkuTPG6l6gIAAABg06xYkNTdhyyz6b5L7NtJnrxStQAAAABwza2VxbYBAAAAWOMESQAAAABMstqf2gYAALBmHXbYYVu6hK2e2xiu3YxIAgAAAGASQRIAAAAAkwiSAAAAAJhEkAQAAADAJIIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATCJIAgAAAGASQRIAAAAAkwiSAAAAAJhEkAQAAADAJIIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADDJDlvipFV1dpJLklyR5PLuPqCqdkvy1iT7JDk7ySO6+7tboj4AAAAArm5Ljkg6sLv37+4DxuvPSvLB7t43yQfH6wAAAACsEWtpattBSY4YLx+R5CFbsBYAAAAAFtlSQVInOa6qTqmqJ45tN+7u85Nk/H6jpQ6sqidW1clVdfL69etXqVwAAAAAtsgaSUnu1t3nVdWNkry/qj4/9cDufnWSVyfJAQcc0CtVIAAAAABXtUVGJHX3eeP3C5K8M8mdk3yrqnZPkvH7BVuiNgAAAACWtupBUlX9bFXtsnA5yW8k+UySY5I8ZtztMUnetdq1AQAAALC8LTG17cZJ3llVC+d/c3f/V1V9KsnRVfX4JF9P8vAtUBsAAAAAy1j1IKm7v5JkvyXav53kvqtdDwAAAADTbKlPbQMAAADgWkaQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATCJIAgAAAGASQRIAAAAAkwiSAAAAAJhEkAQAAADAJIIkAAAAACYRJAEAAAAwiSAJAAAAgEkESQAAAABMIkgCAAAAYBJBEgAAAACTCJIAAAAAmESQBAAAAMAkgiQAAAAAJhEkAQAAADCJIAkAAACASQRJAAAAAEwiSAIAAABgEkESAAAAAJMIkgAAAACYRJAEAAAAwCSCJAAAAAAmESQBAAAAMIkgCQAAAIBJBEkAAAAATCJIAgAA/l97dx43R1HncfzzJQYiVxATJdyIAQloogRYrpBIQHBBiMKSqKxBI6CigkbXXdx9gRdyqaxRELIYYV0TkGNDEBM5QgKJnIZcGkIgCuIqhwQQDYe//aNq8nSGmXlmHvLMPPM83/fr9bye7uruqp6uruqa6uoeMzOzurgjyczMzMzMzMzM6tLjOpIkHSFphaSHJH2p1ftjZmZmZmZmZmZJj+pIktQP+B5wJDAMmCBpWGv3yszMzMzMzMzMoId1JAH7Ag9FxMMR8SIwHTimxftkZmZmZmZmZmaAIqLV+7COpOOAIyJiUp4/EdgvIk4rrHMycHKe3R1Y0fQdbZ5BwJOt3gnrMudf+3LetTfnX/ty3rU35197c/61L+dde3P+ta/ennc7RcTgSgte1+w96YQqhK3X0xURlwKXNmd3WkvSvREd7xPCAAATuElEQVQxstX7YV3j/Gtfzrv25vxrX8679ub8a2/Ov/blvGtvzr/21Zfzrqc92vYYsENhfnvg8Rbti5mZmZmZmZmZFfS0jqR7gKGSdpG0MTAemNnifTIzMzMzMzMzM3rYo20R8bKk04DZQD/g8ohY1uLdaqU+8QhfL+b8a1/Ou/bm/Gtfzrv25vxrb86/9uW8a2/Ov/bVZ/OuR71s28zMzMzMzMzMeq6e9mibmZmZmZmZmZn1UO5IMjMzMzMzMzOzurgjqQkkjZMUkt7Wxe2PlTSsMP8VSWM33B72XZKeb2DdsyRN3gBpOv8aUCmPJJ0q6Z83cDpzJdX9852SJkp6QtIiScslfbzB9EZLmtX4nvYMuU67sDA/WdJZPTWtfLwPKMxPk3RcHdudKWmZpMU5r/fL4VOL9XJh/YmSpjSyb31BI3Wt1adZZVDStyWdXpifLWlqYf5CSZ/rQrynS9q0yrKjJP1K0gO5fj0lh1es+yXtLGlpo/vQCtXqlC7E09U6rellsZ56sTfWnc0uO5Kuy+fUQ5LW5OlFxfPEGtNdeViWxrqy22hbtK9ocpuz1XV027Q73ZHUHBOAO0i/QtcVxwLrTpyI+I+IuHlD7Jg1n/PvtYuISyLiilbvBzAjIkYAo4FvSHpzPRtJ6lE/dNBFa4H3Sxq0ISOtcmxeU1o5ztFAQ41pSfsDRwHvioh3AGOBRwEiYlJELO/K/phtIM0qgwvIZUfSRsAgYM/C8gOAO7uQ1OlApS/D/UkvLz06IoYD7wTmQo+q+7ukVp3SBaNpsE6zpmtq2YmIcblNMgmYHxEj8t+CLqRhSXfloTWmKde7VtfR7dbudEdSN5O0OXAg8DFyR1L5SARJUyRNzNPfzHffFku6IPdkvg84P/dK7lrWc71a0tmS7pe0RF0c9WQdJB0t6a58N/TmSp0Dkj4u6SZJr8958nNJ90maL+ltkgbmvNkor7+ppEcl9S/Lv70l3Z63nS1piKQ3SbovLx+ee+F3zPOrKt2F6mtUGB2W796cK+luSQ9KOjiH98tlaEkuT5/O4YfmvF0i6XJJm1SI/3lJX1e6G/7LzjqIIuJPwCpgJ0n7SlqQ01ggafcc50RJV0u6AZhTlt4+ef23bJAD1Bwvk77snVG+QNJgSddIuif/HZjDGz42daS1k6Rbch7fUigr0yR9S9JtwAzgVOCMXI8enDcflffjYVW+SzQEeDIi1gJExJMR8XiOf91dQ0kn5XPvdlJ9X/M4WFIj72rl6SW5nn1Q0lGt/QQt16wyeCcdjeE9gaXAc5LekOvPPYBf5Xi+kNNbLOnsHLaZpBtzfbpU0gmSPgNsC9yWy2jRFqRfFX4KICLWRsSKHFex7t87x7kQ+FThs/eTdH5hP07pysHtJrXqlIrXJqW2xKA8PTLXPTvTtTqtIlVp9+R92UrJU8qjwSRdKWlsPm+uVWoDrZR0XiHOavViPW2s3lJ3NrvsVCXpsHyuLJF0maSNJR0g6aq8/AOS/qLUTt1M0socfofSd5O7Ja1Q3xvdVE8eLsp1ztJ8fE8AyOWmWvgUpe97NwJvqpSwpIsl3as0OqV0Tuwr6do8fYykv+a8HCDp4RxesV3c5pp1vWt1Hd1e7c6I8F83/gEfBv4rTy8A3kXqoZxVWGcKMBHYGlgB635Nb6v8fxpwXGH9dfPAauDTefqTwNRWf+Z2+gOerxD2hkIeTAIuzNNnAZOB04CZwCY5/BZgaJ7eD7g1T/8vMCZPn1DKm1L+Af3zOTG4sM7leXoZsGVO6x7gQ8BOwMJWH7MekkdnAZPz9NxCHr0XuDlPfwK4Bnhdnt8aGEDq2d8th10BnF6IZ2SeDtLdcIDzgC9X2IeJwJQ8/RbgTzmNLQtpjgWuKaz/GLB1nh8NzCI1UO4Ddmz1sW40X/JnXQ0MzGXjrLzsf4CD8vSOwK/zdF3HpsG0bgA+kqc/Clyfp6fl49uv/JwpLL+adENlGPBQhXQ3BxYBDwLfBw4pLJsLjCRd9H8HDAY2JjU6p9Q6Dn3xj8rluFre1crTn+c8G5rPmQGt/mytPKZNLIOrczynkBrHXyXVtwcC8/I6h5Ma+sp5NAsYBXwAuKwQ18BCnIOqpDeVVKf+hHT92yiHryvHwOJSmQTOB5bm6ZPJdTawCXAvsEur8yvvT8U6hdrXpnXHKdc5c8uPRaF81KzTSudNhbBq7Z5LgH8E9iK1RS7L4SvzZ5kIPJzPvwHAb4EdqF0vVktrIr2w7mx22cnLR7P+94xN8/m1a57/Mal92R9YlcO+k/N4P+BQ4Mocfgdwbp5+H/DzVh/TnpaHOZ9+AfQD3pzP/SE1wt9fCN8WeIaO73Vz6WiLltqL/XL4O0id7I/k8Atynh0IHAL8pBDHq9rF7fxHk653tLiOrpZ+8dygB7U7e8PjFT3dBFLlDDA9z99YZd1ngb8BU3MPdb3vT7k2/7+PVDnZa7M9MEPSEFIBfaSw7ERS5XNsRLykNOLsAOBqSaV1SiNcZpA6h24jjUb7flk6u5MaZ7/I2/YD/pCXLSBdGEYB3wCOIDUw5m+Yj9jrFMvAznl6LHBJRLwMEBFPSxpOugA/mNf5EelO9ndY34t0lL/7gMOqpHuCpINIQ25PyWnsAPxI0lBSh1T/wvq/iIinC/N7kBqPh0e+49BOIuJZSVcAnwH+Wlg0FhhWKBNbStqCdPGv99jUm9b+dNR7V5I6/kqujohXanyE6yPi78DySnfFI+J5SXsDBwNjSPXClyJiWmG1/UiNhicAJM0AdsvLKh6HiHiuxj71JdXyrlaeXpXzbGW++/o2UqOrT2piGSzdlT8A+BawXZ5eQ7peQfoyfDh5hAWpQTyUdN26QNK5pC+3nV7HImKSpLfnzzGZVAdPLC2XNJB0s+32HHQlcGRhP95RuNs7MO9H8VreEtXqFNIxq+fa1JmadVoN1do980ntkN8CFwMnS9oOeDp/FoBbImINgKTlpJteg6heL9ZqY5X0prqzqWWnij2AlRGxKs9fAXwsIqZI+l2uD0aSzrdRwGas396s1MbqSzrLw4NInTivAH/Mo0T2qRE+qhD+uKRbq6T7T5JOJnUeDQGGRcRipXdg7QHsm/dnFOk7RK/Os2Zc71pdR7dbu9MdSd1I0huBdwN7SQpSIQ/SaJbiY4UDACLiZUn7ku4EjCfdLXh3HUmtzf9fwXm6IXwX+FZEzJQ0mtSjXLIUGEFqCD1CysdnIj2TXm4mcI6krYG9gfILhYBlEbF/hW3nkyqRnUgjm/6FdO607cuZu1mlMiDSMSsS9Xkpcnc+tcvVjIg4rSzsq8BtETEuD22dW1j2l7J1/0Aq/+8E2q4jKfsOcD/ww0LYRsD+EVG80CPpu9R/bOpNq1wxzzuLc21huuK5kRt6c4G5kpYAHyHdVaqWZlHF42BVVTuOUWOdatv0Jc0og6X3hLyddB18FPg86QbY5aXogXMi4gflG+eG8XtJ18Q5EfGVzj5URCwBlki6knS9nViMkup5L9JI7dmdpdEKVeqUWp2hL9PRZhzQSfSd1mlVVGv3zCN9WdoROBMYRxpRXfzCWkyzeL2slj+12lglvanubHrZqaDWuTCfNOrsBdII+0tJI5iKbZu+/j2jszw8tMp2tY57zWuXpF1Inej7RMSfJU2jo/zPJ3WcvwTcTGqT9Mvrl/TWPOv2612r6+h2anf6HUnd6zjgiojYKSJ2jogd6LjzMkzSJvmu2qGw7n1KAyPiZ6QX6ZU6J54jvTPAmmMg8Ps8/ZGyZb8iDW2dKWnbiHgWeETS8bDuuefhkHqVgbuBi0h3kspHRqwABiu9WA2l59JLL/CbR3oscmXuuX6a1JDwC/3qNwc4VflFerlD7zfAzpLemtc5Ebi9yvZdVTx/Jnay7jOkBtw3coO67eQ7OleR3gNXModCI1RSqS5r5NjUm9YCOn7I4EOkYfiVNFyPSto938kqGUG6M190FzBa0huVXhJ8fGFZteNgSbW8q5Wnx0vaSNKupEdKVzRjR3uyJpXBO0kvAH06Il7JaW5FGj22MK8zG/hobssgaTuld/5tC7wQEf9NehTjXXn9imVS0uZl9eGryl1EPAOsySNCIZ0nJbOBT+TyiKTdJG3WwGftNjXqlFrXptWkm1GQHpUp2ZBtw4rtnoh4lDS6aGhEPEwqi5PpfHR0rXqxVhurpDfVnU0rOzUsB4aq4z2MH6bj/JoHfA5YEBH/B2xDegTuN134rL1VZ3k4jzRCvZ+kwaQRQnd3Ej4+hw8hjTwptyWps2NNHrlyZGHZPNL3xIV5VMobSaNzl23oD97TdPf1rtV1dLu1O92R1L0mANeVhV0DfJBUCBaTnlMuDWXdApglaTHp5Cy9UGw68AWlF3zt2u173bdsKumxwt/nSHfHrpY0H3iyfIOIKDWkblR6udqHgI9JeoBUiR9TWH0G6YI9o0I8L5I6G8/N2y4iv9AvIlbn1ebl/3eQRj79+TV+3nZUKY/qMZX0DPHifHw/GBF/A04i5e8S4O+kd0BsSOeR7hzeSbpDVFNE/BE4GvieuvgToz3AhaQvGyWfAUYqvTR0OemdAtDgsWkgrZNyvXki8Nkq290AjNP6Lz3szOakYdHLc/zDKLt7HhF/yGELSXcG7y/bt0rHoS+qVI6r5V2tPF1Buj7eBJyay7R1fxlckuP/ZVnYmoh4EiAi5pDez7Aw168/JbVr3g7cLWkRaVTL1/L2lwI36dUvDBbwRaUX+y4Czqbyl4CTSPXmQtZ/zGEq6Yvz/ZKWAj+g59yRr1indHJtOhu4KLdJijekulKnQePtnrtI7+uA1IG0HdU77IFO68VaaZX0prqzmWWnooh4gfTF+9oc/1rgsrx4IemxqVJ7cykd30ss6SwPryN9p3uA9PTBF3OnXK3wlTmOi6lwQzMiHiDlwzLSqKfijeS7SO9cKuXZYmBxYSR9b9ed17tW19Ft1e5U3znnzMzMrF0pDe2fFRE/bfW+mJmZmfVlHpFkZmZmZmZmZmZ18YgkMzMzMzMzMzOri0ckmZmZmZmZmZlZXdyRZGZmZmZmZmZmdXFHkpmZmZmZmZmZ1cUdSWZmZtZ0kraRNF3SqvxTtz+TtFtetqekWyU9KGmlpH+XpLxsoqSQdGghrnE57Lg8P1fS70rb5LDrJT2fp0dLmlW2P9PKtr+3sGykpLnFbSWdlH/Wd5GkFyUtydNX5/1+fWH7GyWNr3IcLpL0e0kbFcImSnoix/cbSWcUlp2V119U+NuqVnxl6Y3Ox+roQtgsSaML84MlvSTplLJtV+efOC6GLZK0tBD3mrJ9G1tpP8zMzKx9uSPJzMzMmip38FwHzI2IXSNiGPBvwJtzB8xM4JsRsRswHDgA+GQhiiXAhML8eOCBsmSeAQ7M6W0FDGlwN98k6chqCyPihxExIiJGAI8DY/L88cC1wJk57WOB/hExvTyO3NkzDngUGFW2eEaO+0DgTEk7FJZ9u5R2/numjviKHivtXxXHA79k/WNcskVpXyTtUWH5/LJ9u7lGOmZmZtaG3JFkZmZmzTYGeCkiLikFRMSiiJgPfBC4MyLm5PAXgNOALxW2nw/sK6m/pM2BtwKLytKYTupgAng/qXOnEecDX25wm5KvAMdLGgF8E/hUlfXGAEuBi6ncaUNEPAU8RH0dYZ3Glz0ArJF0WJXlE4DPA9tL2q5s2VXACYX1flLHfpmZmVkv4o4kMzMza7a9gPuqLNuzfFlErAI2l7RlKQi4GXgPcAxpBFO5W4BRkvqROpRmNLiPC4G1ksY0uF2p82syMA+YHhErq6xa6oi5DjhKUv/yFSTtCAwAFheCzyg8OnZbI/EVfI0KHWV5tNE2EXE363calfyU1DEHcDRwQ9nyg8sebdu1xj6YmZlZG3JHkpmZmfUkInUUVVIML404Gk/lUTGvAHeQOkJeHxGrq8RTLX6o0tlSj4i4gfR43fcrLZe0MfBe4PqIeBa4Czi8sMoJkpYBDwMXRcTfCsuKj7aNqTO+8v2bn7c7uGzReFIHEqRjXD6y6Wngz/mdT78GXihbXv5o26pq+2BmZmbtyR1JZmZm1mzLgL1rLBtZDJD0FuD5iHiuFJZHzOwFDIqIB6vENR34Lh0dIyVPAW8oC9saeLIYEBG3kkYD/UPVT1Lb3/NfJUcAA4ElklYDB7F+p82MiNgTOBi4UNI2naTVWXyVfJ1XvytpAjAxxzETGC5paNk6M4Dv4cfazMzM+iR3JJmZmVmz3QpsIunjpQBJ+0g6BPgxcFDp177yy7f/EzivQjz/SnpJdzXzgXN4dYfHSmDb0suiJe1Eeql3+XuWIHW2fLGeD9WgCcCkiNg5InYGdgEOl7RpcaWIWAhcCXx2Q8RXFvccUofacABJuwObRcR2hXjOoeNdUyXXkfJjdj0f1MzMzHoXdySZmZlZU0VEkH5d7DBJq/IjXGcBj0fEX0nvPfqypBWkX2i7B5hSIZ6bIuK28vBiOhFxQUSUjzRaC3wY+KGkRaT3/kyKiDUV4vgZ8EQXP2pFuXPnPcCNhXT+QnoU7+gKm5wLnCRpizx/Rtl7iIY1GF/R14Ht8/QEUidR0TWUjWyKiOci4tyIeLFCfOXvSDquk/TNzMyszSi15czMzMzMzMzMzGrziCQzMzMzMzMzM6uLO5LMzMzMzMzMzKwu7kgyMzMzMzMzM7O6uCPJzMzMzMzMzMzq4o4kMzMzMzMzMzOrizuSzMzMzMzMzMysLu5IMjMzMzMzMzOzuvw/SdwWJ02K1zsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=2,figsize=(20,15))\n",
    "sns.barplot(x='COMMUNITY AREA NAME',y='TOTAL POPULATION',data=dfs, ax=axs[0], ci=None)\n",
    "sns.barplot(x='COMMUNITY AREA NAME',y='TOTAL POPULATION',data=dfl, ax=axs[1], ci=None)\n",
    "\n",
    "\n",
    "axs[0].set_title(\"Area which consume less power\")\n",
    "\n",
    "axs[1].set_title(\"Area which consume more power\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_uuid": "8d4f235fb3315dda393bf66c716ba3925a635f9e"
   },
   "source": [
    "Population play an important role in the region which consume more power apart from these region being more of commercial space as seen above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "_uuid": "1674f48ac8b0b40de8886570be186ad7825b8c8d"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>KWH JANUARY 2010</th>\n",
       "      <th>KWH FEBRUARY 2010</th>\n",
       "      <th>KWH MARCH 2010</th>\n",
       "      <th>KWH APRIL 2010</th>\n",
       "      <th>KWH MAY 2010</th>\n",
       "      <th>KWH JUNE 2010</th>\n",
       "      <th>KWH JULY 2010</th>\n",
       "      <th>KWH AUGUST 2010</th>\n",
       "      <th>KWH SEPTEMBER 2010</th>\n",
       "      <th>KWH OCTOBER 2010</th>\n",
       "      <th>KWH NOVEMBER 2010</th>\n",
       "      <th>KWH DECEMBER 2010</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COMMUNITY AREA NAME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Austin</th>\n",
       "      <td>21506684.0</td>\n",
       "      <td>24292930.0</td>\n",
       "      <td>23662582.0</td>\n",
       "      <td>21966745.0</td>\n",
       "      <td>26016007.0</td>\n",
       "      <td>30798364.0</td>\n",
       "      <td>35240528.0</td>\n",
       "      <td>35215333.0</td>\n",
       "      <td>28395692.0</td>\n",
       "      <td>24912923.0</td>\n",
       "      <td>30410118.0</td>\n",
       "      <td>36644917.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Avalon Park</th>\n",
       "      <td>2742619.0</td>\n",
       "      <td>2629352.0</td>\n",
       "      <td>2413518.0</td>\n",
       "      <td>2434028.0</td>\n",
       "      <td>2782662.0</td>\n",
       "      <td>3688298.0</td>\n",
       "      <td>3991451.0</td>\n",
       "      <td>3506747.0</td>\n",
       "      <td>2637194.0</td>\n",
       "      <td>2679234.0</td>\n",
       "      <td>3868365.0</td>\n",
       "      <td>4367912.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burnside</th>\n",
       "      <td>1120345.0</td>\n",
       "      <td>1110407.0</td>\n",
       "      <td>1102426.0</td>\n",
       "      <td>1089560.0</td>\n",
       "      <td>1287721.0</td>\n",
       "      <td>1495791.0</td>\n",
       "      <td>1567598.0</td>\n",
       "      <td>1292817.0</td>\n",
       "      <td>1109799.0</td>\n",
       "      <td>1142035.0</td>\n",
       "      <td>1444386.0</td>\n",
       "      <td>1564108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>East Side</th>\n",
       "      <td>3635448.0</td>\n",
       "      <td>3701266.0</td>\n",
       "      <td>3350270.0</td>\n",
       "      <td>3476031.0</td>\n",
       "      <td>4738304.0</td>\n",
       "      <td>6510207.0</td>\n",
       "      <td>6768643.0</td>\n",
       "      <td>5079652.0</td>\n",
       "      <td>3807306.0</td>\n",
       "      <td>3949137.0</td>\n",
       "      <td>5460683.0</td>\n",
       "      <td>5338953.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Edison Park</th>\n",
       "      <td>2461976.0</td>\n",
       "      <td>2619240.0</td>\n",
       "      <td>2610050.0</td>\n",
       "      <td>2902832.0</td>\n",
       "      <td>3890866.0</td>\n",
       "      <td>5411282.0</td>\n",
       "      <td>5684115.0</td>\n",
       "      <td>3975806.0</td>\n",
       "      <td>2772883.0</td>\n",
       "      <td>3068880.0</td>\n",
       "      <td>3778499.0</td>\n",
       "      <td>3987141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fuller Park</th>\n",
       "      <td>1128288.0</td>\n",
       "      <td>1132120.0</td>\n",
       "      <td>1098838.0</td>\n",
       "      <td>1076348.0</td>\n",
       "      <td>1237369.0</td>\n",
       "      <td>1305163.0</td>\n",
       "      <td>1516609.0</td>\n",
       "      <td>1475511.0</td>\n",
       "      <td>1222902.0</td>\n",
       "      <td>1171600.0</td>\n",
       "      <td>1329071.0</td>\n",
       "      <td>1510706.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hegewisch</th>\n",
       "      <td>1565474.0</td>\n",
       "      <td>1741986.0</td>\n",
       "      <td>1664753.0</td>\n",
       "      <td>1907687.0</td>\n",
       "      <td>2215826.0</td>\n",
       "      <td>2943318.0</td>\n",
       "      <td>3740674.0</td>\n",
       "      <td>3375732.0</td>\n",
       "      <td>2427933.0</td>\n",
       "      <td>2064173.0</td>\n",
       "      <td>2378460.0</td>\n",
       "      <td>2726024.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lakeview</th>\n",
       "      <td>28973867.0</td>\n",
       "      <td>28080784.0</td>\n",
       "      <td>27041453.0</td>\n",
       "      <td>27146909.0</td>\n",
       "      <td>35238262.0</td>\n",
       "      <td>48053388.0</td>\n",
       "      <td>50988194.0</td>\n",
       "      <td>43701704.0</td>\n",
       "      <td>32736483.0</td>\n",
       "      <td>30807295.0</td>\n",
       "      <td>37528357.0</td>\n",
       "      <td>43957540.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lincoln Park</th>\n",
       "      <td>28662486.0</td>\n",
       "      <td>27244024.0</td>\n",
       "      <td>25282095.0</td>\n",
       "      <td>25102611.0</td>\n",
       "      <td>31425713.0</td>\n",
       "      <td>39478559.0</td>\n",
       "      <td>42920332.0</td>\n",
       "      <td>41420785.0</td>\n",
       "      <td>31834193.0</td>\n",
       "      <td>28368218.0</td>\n",
       "      <td>33736525.0</td>\n",
       "      <td>40731118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loop</th>\n",
       "      <td>208427935.0</td>\n",
       "      <td>187892942.0</td>\n",
       "      <td>172160266.0</td>\n",
       "      <td>162138188.0</td>\n",
       "      <td>188765284.0</td>\n",
       "      <td>206538589.0</td>\n",
       "      <td>218759187.0</td>\n",
       "      <td>205527275.0</td>\n",
       "      <td>181730058.0</td>\n",
       "      <td>167072912.0</td>\n",
       "      <td>206344917.0</td>\n",
       "      <td>250443823.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montclare</th>\n",
       "      <td>2903912.0</td>\n",
       "      <td>2977102.0</td>\n",
       "      <td>3040513.0</td>\n",
       "      <td>2991329.0</td>\n",
       "      <td>3766737.0</td>\n",
       "      <td>5193001.0</td>\n",
       "      <td>5893586.0</td>\n",
       "      <td>4911788.0</td>\n",
       "      <td>3599544.0</td>\n",
       "      <td>3272338.0</td>\n",
       "      <td>4003336.0</td>\n",
       "      <td>4497505.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Near North Side</th>\n",
       "      <td>144229369.0</td>\n",
       "      <td>134469938.0</td>\n",
       "      <td>118268260.0</td>\n",
       "      <td>112000092.0</td>\n",
       "      <td>131051613.0</td>\n",
       "      <td>151429911.0</td>\n",
       "      <td>164105236.0</td>\n",
       "      <td>158465269.0</td>\n",
       "      <td>136066286.0</td>\n",
       "      <td>119297677.0</td>\n",
       "      <td>145194095.0</td>\n",
       "      <td>179874978.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Near South Side</th>\n",
       "      <td>37062958.0</td>\n",
       "      <td>39913708.0</td>\n",
       "      <td>39633790.0</td>\n",
       "      <td>36534435.0</td>\n",
       "      <td>45097266.0</td>\n",
       "      <td>43242650.0</td>\n",
       "      <td>52102662.0</td>\n",
       "      <td>46385893.0</td>\n",
       "      <td>46229325.0</td>\n",
       "      <td>40925901.0</td>\n",
       "      <td>46217054.0</td>\n",
       "      <td>48232775.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Near West Side</th>\n",
       "      <td>91419538.0</td>\n",
       "      <td>90722262.0</td>\n",
       "      <td>85415194.0</td>\n",
       "      <td>85277736.0</td>\n",
       "      <td>100232839.0</td>\n",
       "      <td>111521537.0</td>\n",
       "      <td>117192057.0</td>\n",
       "      <td>111970165.0</td>\n",
       "      <td>98315390.0</td>\n",
       "      <td>87198956.0</td>\n",
       "      <td>94789339.0</td>\n",
       "      <td>109499350.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oakland</th>\n",
       "      <td>1167476.0</td>\n",
       "      <td>1196113.0</td>\n",
       "      <td>1135873.0</td>\n",
       "      <td>1016543.0</td>\n",
       "      <td>1071981.0</td>\n",
       "      <td>1208318.0</td>\n",
       "      <td>1473224.0</td>\n",
       "      <td>1419228.0</td>\n",
       "      <td>1171270.0</td>\n",
       "      <td>1042316.0</td>\n",
       "      <td>1341302.0</td>\n",
       "      <td>1766215.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Lawndale</th>\n",
       "      <td>19125341.0</td>\n",
       "      <td>20114693.0</td>\n",
       "      <td>19695136.0</td>\n",
       "      <td>18767063.0</td>\n",
       "      <td>21033902.0</td>\n",
       "      <td>24139203.0</td>\n",
       "      <td>30225606.0</td>\n",
       "      <td>30250447.0</td>\n",
       "      <td>24461841.0</td>\n",
       "      <td>20694339.0</td>\n",
       "      <td>22567746.0</td>\n",
       "      <td>26209988.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington Park</th>\n",
       "      <td>1946212.0</td>\n",
       "      <td>1857078.0</td>\n",
       "      <td>1770734.0</td>\n",
       "      <td>1834367.0</td>\n",
       "      <td>2070284.0</td>\n",
       "      <td>2443962.0</td>\n",
       "      <td>2706306.0</td>\n",
       "      <td>2702028.0</td>\n",
       "      <td>2081182.0</td>\n",
       "      <td>2104917.0</td>\n",
       "      <td>2546973.0</td>\n",
       "      <td>3058598.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Garfield Park</th>\n",
       "      <td>2901535.0</td>\n",
       "      <td>3334146.0</td>\n",
       "      <td>3352718.0</td>\n",
       "      <td>3341948.0</td>\n",
       "      <td>3674921.0</td>\n",
       "      <td>4214593.0</td>\n",
       "      <td>4845585.0</td>\n",
       "      <td>4832251.0</td>\n",
       "      <td>4075111.0</td>\n",
       "      <td>3617657.0</td>\n",
       "      <td>4364056.0</td>\n",
       "      <td>5594075.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Town</th>\n",
       "      <td>20391005.0</td>\n",
       "      <td>23546121.0</td>\n",
       "      <td>22601647.0</td>\n",
       "      <td>22618359.0</td>\n",
       "      <td>27139696.0</td>\n",
       "      <td>34368673.0</td>\n",
       "      <td>39822476.0</td>\n",
       "      <td>39529444.0</td>\n",
       "      <td>30746598.0</td>\n",
       "      <td>26305048.0</td>\n",
       "      <td>29798733.0</td>\n",
       "      <td>36312423.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Woodlawn</th>\n",
       "      <td>36332823.0</td>\n",
       "      <td>37153475.0</td>\n",
       "      <td>33716893.0</td>\n",
       "      <td>34913486.0</td>\n",
       "      <td>38965734.0</td>\n",
       "      <td>47411278.0</td>\n",
       "      <td>46910100.0</td>\n",
       "      <td>47428883.0</td>\n",
       "      <td>42725472.0</td>\n",
       "      <td>36793933.0</td>\n",
       "      <td>37097007.0</td>\n",
       "      <td>43056692.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     KWH JANUARY 2010  KWH FEBRUARY 2010  KWH MARCH 2010  \\\n",
       "COMMUNITY AREA NAME                                                        \n",
       "Austin                     21506684.0         24292930.0      23662582.0   \n",
       "Avalon Park                 2742619.0          2629352.0       2413518.0   \n",
       "Burnside                    1120345.0          1110407.0       1102426.0   \n",
       "East Side                   3635448.0          3701266.0       3350270.0   \n",
       "Edison Park                 2461976.0          2619240.0       2610050.0   \n",
       "Fuller Park                 1128288.0          1132120.0       1098838.0   \n",
       "Hegewisch                   1565474.0          1741986.0       1664753.0   \n",
       "Lakeview                   28973867.0         28080784.0      27041453.0   \n",
       "Lincoln Park               28662486.0         27244024.0      25282095.0   \n",
       "Loop                      208427935.0        187892942.0     172160266.0   \n",
       "Montclare                   2903912.0          2977102.0       3040513.0   \n",
       "Near North Side           144229369.0        134469938.0     118268260.0   \n",
       "Near South Side            37062958.0         39913708.0      39633790.0   \n",
       "Near West Side             91419538.0         90722262.0      85415194.0   \n",
       "Oakland                     1167476.0          1196113.0       1135873.0   \n",
       "South Lawndale             19125341.0         20114693.0      19695136.0   \n",
       "Washington Park             1946212.0          1857078.0       1770734.0   \n",
       "West Garfield Park          2901535.0          3334146.0       3352718.0   \n",
       "West Town                  20391005.0         23546121.0      22601647.0   \n",
       "Woodlawn                   36332823.0         37153475.0      33716893.0   \n",
       "\n",
       "                     KWH APRIL 2010  KWH MAY 2010  KWH JUNE 2010  \\\n",
       "COMMUNITY AREA NAME                                                \n",
       "Austin                   21966745.0    26016007.0     30798364.0   \n",
       "Avalon Park               2434028.0     2782662.0      3688298.0   \n",
       "Burnside                  1089560.0     1287721.0      1495791.0   \n",
       "East Side                 3476031.0     4738304.0      6510207.0   \n",
       "Edison Park               2902832.0     3890866.0      5411282.0   \n",
       "Fuller Park               1076348.0     1237369.0      1305163.0   \n",
       "Hegewisch                 1907687.0     2215826.0      2943318.0   \n",
       "Lakeview                 27146909.0    35238262.0     48053388.0   \n",
       "Lincoln Park             25102611.0    31425713.0     39478559.0   \n",
       "Loop                    162138188.0   188765284.0    206538589.0   \n",
       "Montclare                 2991329.0     3766737.0      5193001.0   \n",
       "Near North Side         112000092.0   131051613.0    151429911.0   \n",
       "Near South Side          36534435.0    45097266.0     43242650.0   \n",
       "Near West Side           85277736.0   100232839.0    111521537.0   \n",
       "Oakland                   1016543.0     1071981.0      1208318.0   \n",
       "South Lawndale           18767063.0    21033902.0     24139203.0   \n",
       "Washington Park           1834367.0     2070284.0      2443962.0   \n",
       "West Garfield Park        3341948.0     3674921.0      4214593.0   \n",
       "West Town                22618359.0    27139696.0     34368673.0   \n",
       "Woodlawn                 34913486.0    38965734.0     47411278.0   \n",
       "\n",
       "                     KWH JULY 2010  KWH AUGUST 2010  KWH SEPTEMBER 2010  \\\n",
       "COMMUNITY AREA NAME                                                       \n",
       "Austin                  35240528.0       35215333.0          28395692.0   \n",
       "Avalon Park              3991451.0        3506747.0           2637194.0   \n",
       "Burnside                 1567598.0        1292817.0           1109799.0   \n",
       "East Side                6768643.0        5079652.0           3807306.0   \n",
       "Edison Park              5684115.0        3975806.0           2772883.0   \n",
       "Fuller Park              1516609.0        1475511.0           1222902.0   \n",
       "Hegewisch                3740674.0        3375732.0           2427933.0   \n",
       "Lakeview                50988194.0       43701704.0          32736483.0   \n",
       "Lincoln Park            42920332.0       41420785.0          31834193.0   \n",
       "Loop                   218759187.0      205527275.0         181730058.0   \n",
       "Montclare                5893586.0        4911788.0           3599544.0   \n",
       "Near North Side        164105236.0      158465269.0         136066286.0   \n",
       "Near South Side         52102662.0       46385893.0          46229325.0   \n",
       "Near West Side         117192057.0      111970165.0          98315390.0   \n",
       "Oakland                  1473224.0        1419228.0           1171270.0   \n",
       "South Lawndale          30225606.0       30250447.0          24461841.0   \n",
       "Washington Park          2706306.0        2702028.0           2081182.0   \n",
       "West Garfield Park       4845585.0        4832251.0           4075111.0   \n",
       "West Town               39822476.0       39529444.0          30746598.0   \n",
       "Woodlawn                46910100.0       47428883.0          42725472.0   \n",
       "\n",
       "                     KWH OCTOBER 2010  KWH NOVEMBER 2010  KWH DECEMBER 2010  \n",
       "COMMUNITY AREA NAME                                                          \n",
       "Austin                     24912923.0         30410118.0         36644917.0  \n",
       "Avalon Park                 2679234.0          3868365.0          4367912.0  \n",
       "Burnside                    1142035.0          1444386.0          1564108.0  \n",
       "East Side                   3949137.0          5460683.0          5338953.0  \n",
       "Edison Park                 3068880.0          3778499.0          3987141.0  \n",
       "Fuller Park                 1171600.0          1329071.0          1510706.0  \n",
       "Hegewisch                   2064173.0          2378460.0          2726024.0  \n",
       "Lakeview                   30807295.0         37528357.0         43957540.0  \n",
       "Lincoln Park               28368218.0         33736525.0         40731118.0  \n",
       "Loop                      167072912.0        206344917.0        250443823.0  \n",
       "Montclare                   3272338.0          4003336.0          4497505.0  \n",
       "Near North Side           119297677.0        145194095.0        179874978.0  \n",
       "Near South Side            40925901.0         46217054.0         48232775.0  \n",
       "Near West Side             87198956.0         94789339.0        109499350.0  \n",
       "Oakland                     1042316.0          1341302.0          1766215.0  \n",
       "South Lawndale             20694339.0         22567746.0         26209988.0  \n",
       "Washington Park             2104917.0          2546973.0          3058598.0  \n",
       "West Garfield Park          3617657.0          4364056.0          5594075.0  \n",
       "West Town                  26305048.0         29798733.0         36312423.0  \n",
       "Woodlawn                   36793933.0         37097007.0         43056692.0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Getting energy consumption for each month\n",
    "dft=pd.concat([dfs,dfl])\n",
    "dft=dft.groupby(['COMMUNITY AREA NAME']).sum()\n",
    "dft=dft.iloc[:,1:13]\n",
    "dft"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "_uuid": "8287ccfda925dd7199beb21dd54babb970d5dbc9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.matrix.ClusterGrid at 0x14a42edd5f8>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1440x432 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,6))\n",
    "sns.clustermap(dft,cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "_uuid": "c3ffd0391b356cedca5a58996810ad90568a9169"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}