w2PartB_MoazamHakim.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IS 445 Week 4 Assignment (Part -II)\n",
    "#### Submitted by: Moazam I. Hakim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_columns', None)\n",
    "pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Agency Name                object\n",
       "Location Name              object\n",
       "Address                    object\n",
       "City                       object\n",
       "Zip code                    int64\n",
       "County                     object\n",
       "Congress Dist               int64\n",
       "Congressional Full Name    object\n",
       "Rep Dist                    int64\n",
       "Rep Full Name              object\n",
       "Senate Dist                 int64\n",
       "Senator Full Name          object\n",
       "Bldg Status                object\n",
       "Year Acquired               int64\n",
       "Year Constructed            int64\n",
       "Square Footage              int64\n",
       "Total Floors                int64\n",
       "Floors Above Grade          int64\n",
       "Floors Below Grade          int64\n",
       "Usage Description          object\n",
       "Usage Description 2        object\n",
       "Usage Description 3        object\n",
       "dtype: object"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "buildings = pd.read_csv('https://uiuc-ischool-dataviz.github.io/spring2019online/week02/building_inventory.csv')\n",
    "buildings.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Preview the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Agency Name</th>\n",
       "      <th>Location Name</th>\n",
       "      <th>Address</th>\n",
       "      <th>City</th>\n",
       "      <th>Zip code</th>\n",
       "      <th>County</th>\n",
       "      <th>Congress Dist</th>\n",
       "      <th>Congressional Full Name</th>\n",
       "      <th>Rep Dist</th>\n",
       "      <th>Rep Full Name</th>\n",
       "      <th>Senate Dist</th>\n",
       "      <th>Senator Full Name</th>\n",
       "      <th>Bldg Status</th>\n",
       "      <th>Year Acquired</th>\n",
       "      <th>Year Constructed</th>\n",
       "      <th>Square Footage</th>\n",
       "      <th>Total Floors</th>\n",
       "      <th>Floors Above Grade</th>\n",
       "      <th>Floors Below Grade</th>\n",
       "      <th>Usage Description</th>\n",
       "      <th>Usage Description 2</th>\n",
       "      <th>Usage Description 3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Department of Natural Resources</td>\n",
       "      <td>Anderson Lake Conservation Area - Fulton County</td>\n",
       "      <td>Anderson Lake C.a.</td>\n",
       "      <td>Astoria</td>\n",
       "      <td>61501</td>\n",
       "      <td>Fulton</td>\n",
       "      <td>17</td>\n",
       "      <td>Cheri Bustos</td>\n",
       "      <td>93</td>\n",
       "      <td>Hammond Norine K.</td>\n",
       "      <td>47</td>\n",
       "      <td>Jil Tracy</td>\n",
       "      <td>In Use</td>\n",
       "      <td>1975</td>\n",
       "      <td>1975</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Department of Natural Resources</td>\n",
       "      <td>Anderson Lake Conservation Area - Fulton County</td>\n",
       "      <td>Anderson Lake C.a.</td>\n",
       "      <td>Astoria</td>\n",
       "      <td>61501</td>\n",
       "      <td>Fulton</td>\n",
       "      <td>17</td>\n",
       "      <td>Cheri Bustos</td>\n",
       "      <td>93</td>\n",
       "      <td>Hammond Norine K.</td>\n",
       "      <td>47</td>\n",
       "      <td>Jil Tracy</td>\n",
       "      <td>In Use</td>\n",
       "      <td>2004</td>\n",
       "      <td>2004</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Department of Natural Resources</td>\n",
       "      <td>Anderson Lake Conservation Area - Fulton County</td>\n",
       "      <td>Anderson Lake C.a.</td>\n",
       "      <td>Astoria</td>\n",
       "      <td>61501</td>\n",
       "      <td>Fulton</td>\n",
       "      <td>17</td>\n",
       "      <td>Cheri Bustos</td>\n",
       "      <td>93</td>\n",
       "      <td>Hammond Norine K.</td>\n",
       "      <td>47</td>\n",
       "      <td>Jil Tracy</td>\n",
       "      <td>In Use</td>\n",
       "      <td>2004</td>\n",
       "      <td>2004</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Department of Natural Resources</td>\n",
       "      <td>Anderson Lake Conservation Area - Fulton County</td>\n",
       "      <td>Anderson Lake C.a.</td>\n",
       "      <td>Astoria</td>\n",
       "      <td>61501</td>\n",
       "      <td>Fulton</td>\n",
       "      <td>17</td>\n",
       "      <td>Cheri Bustos</td>\n",
       "      <td>93</td>\n",
       "      <td>Hammond Norine K.</td>\n",
       "      <td>47</td>\n",
       "      <td>Jil Tracy</td>\n",
       "      <td>In Use</td>\n",
       "      <td>2004</td>\n",
       "      <td>2004</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Department of Natural Resources</td>\n",
       "      <td>Anderson Lake Conservation Area - Fulton County</td>\n",
       "      <td>Anderson Lake C.a.</td>\n",
       "      <td>Astoria</td>\n",
       "      <td>61501</td>\n",
       "      <td>Fulton</td>\n",
       "      <td>17</td>\n",
       "      <td>Cheri Bustos</td>\n",
       "      <td>93</td>\n",
       "      <td>Hammond Norine K.</td>\n",
       "      <td>47</td>\n",
       "      <td>Jil Tracy</td>\n",
       "      <td>In Use</td>\n",
       "      <td>2004</td>\n",
       "      <td>2004</td>\n",
       "      <td>144</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Unusual</td>\n",
       "      <td>Not provided</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Agency Name  \\\n",
       "0  Department of Natural Resources   \n",
       "1  Department of Natural Resources   \n",
       "2  Department of Natural Resources   \n",
       "3  Department of Natural Resources   \n",
       "4  Department of Natural Resources   \n",
       "\n",
       "                                     Location Name             Address  \\\n",
       "0  Anderson Lake Conservation Area - Fulton County  Anderson Lake C.a.   \n",
       "1  Anderson Lake Conservation Area - Fulton County  Anderson Lake C.a.   \n",
       "2  Anderson Lake Conservation Area - Fulton County  Anderson Lake C.a.   \n",
       "3  Anderson Lake Conservation Area - Fulton County  Anderson Lake C.a.   \n",
       "4  Anderson Lake Conservation Area - Fulton County  Anderson Lake C.a.   \n",
       "\n",
       "      City  Zip code  County  Congress Dist Congressional Full Name  Rep Dist  \\\n",
       "0  Astoria     61501  Fulton             17            Cheri Bustos        93   \n",
       "1  Astoria     61501  Fulton             17            Cheri Bustos        93   \n",
       "2  Astoria     61501  Fulton             17            Cheri Bustos        93   \n",
       "3  Astoria     61501  Fulton             17            Cheri Bustos        93   \n",
       "4  Astoria     61501  Fulton             17            Cheri Bustos        93   \n",
       "\n",
       "       Rep Full Name  Senate Dist Senator Full Name Bldg Status  \\\n",
       "0  Hammond Norine K.           47         Jil Tracy      In Use   \n",
       "1  Hammond Norine K.           47         Jil Tracy      In Use   \n",
       "2  Hammond Norine K.           47         Jil Tracy      In Use   \n",
       "3  Hammond Norine K.           47         Jil Tracy      In Use   \n",
       "4  Hammond Norine K.           47         Jil Tracy      In Use   \n",
       "\n",
       "   Year Acquired  Year Constructed  Square Footage  Total Floors  \\\n",
       "0           1975              1975             144             1   \n",
       "1           2004              2004             144             1   \n",
       "2           2004              2004             144             1   \n",
       "3           2004              2004             144             1   \n",
       "4           2004              2004             144             1   \n",
       "\n",
       "   Floors Above Grade  Floors Below Grade Usage Description  \\\n",
       "0                   1                   0           Unusual   \n",
       "1                   1                   0           Unusual   \n",
       "2                   1                   0           Unusual   \n",
       "3                   1                   0           Unusual   \n",
       "4                   1                   0           Unusual   \n",
       "\n",
       "  Usage Description 2 Usage Description 3  \n",
       "0             Unusual        Not provided  \n",
       "1             Unusual        Not provided  \n",
       "2             Unusual        Not provided  \n",
       "3             Unusual        Not provided  \n",
       "4             Unusual        Not provided  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Drop Missing Values or Incorrect Congress Districted marked as District Zero\n",
    "drop_missing_dist=buildings.index[buildings[\"Congress Dist\"] == 0].tolist()\n",
    "buildings=buildings.drop(buildings.index[drop_missing_dist])\n",
    "buildings.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization I - Total square footage as a function of congressional district (\"Congress Dist\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Square Footage</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congress Dist</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2351762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6285684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1293687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>317741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1809022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Square Footage\n",
       "Congress Dist                \n",
       "1                     2351762\n",
       "2                     6285684\n",
       "3                     1293687\n",
       "4                      317741\n",
       "5                     1809022"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_congressdist = buildings.groupby(['Congress Dist'])[[\"Square Footage\"]].sum()\n",
    "by_congressdist.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x18b0cd916c8>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "by_congressdist.plot.bar(y='Square Footage', rot=0, title=\"Total Square Footage by Congressional District\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observations\n",
    "The data from the csv file has been represented to visualize the Square Footage in each Congresstional District used by various state agencies. I used the group by feature of pandas to organize the dataframe and extract the information i needed for this. This visualization was pretty easy and didnot involve a lot of transformation and changes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization II - Average square footage per floor as a function of congressional district"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Square Footage</th>\n",
       "      <th>Total Floors</th>\n",
       "      <th>Avg_Square Footage Per Floor</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Congress Dist</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2351762</td>\n",
       "      <td>134</td>\n",
       "      <td>17550.462687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6285684</td>\n",
       "      <td>647</td>\n",
       "      <td>9715.122102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1293687</td>\n",
       "      <td>72</td>\n",
       "      <td>17967.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>317741</td>\n",
       "      <td>21</td>\n",
       "      <td>15130.523810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1809022</td>\n",
       "      <td>113</td>\n",
       "      <td>16009.044248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>145659</td>\n",
       "      <td>28</td>\n",
       "      <td>5202.107143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>9211651</td>\n",
       "      <td>517</td>\n",
       "      <td>17817.506770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1461548</td>\n",
       "      <td>312</td>\n",
       "      <td>4684.448718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>77978</td>\n",
       "      <td>11</td>\n",
       "      <td>7088.909091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>929267</td>\n",
       "      <td>213</td>\n",
       "      <td>4362.755869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3467894</td>\n",
       "      <td>411</td>\n",
       "      <td>8437.698297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12444775</td>\n",
       "      <td>2339</td>\n",
       "      <td>5320.553655</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>31849251</td>\n",
       "      <td>2896</td>\n",
       "      <td>10997.669544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>857108</td>\n",
       "      <td>319</td>\n",
       "      <td>2686.858934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7209934</td>\n",
       "      <td>1872</td>\n",
       "      <td>3851.460470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8725880</td>\n",
       "      <td>1654</td>\n",
       "      <td>5275.622733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>4347743</td>\n",
       "      <td>924</td>\n",
       "      <td>4705.349567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>8120838</td>\n",
       "      <td>1800</td>\n",
       "      <td>4511.576667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Square Footage  Total Floors  Avg_Square Footage Per Floor\n",
       "Congress Dist                                                            \n",
       "1                     2351762           134                  17550.462687\n",
       "2                     6285684           647                   9715.122102\n",
       "3                     1293687            72                  17967.875000\n",
       "4                      317741            21                  15130.523810\n",
       "5                     1809022           113                  16009.044248\n",
       "6                      145659            28                   5202.107143\n",
       "7                     9211651           517                  17817.506770\n",
       "8                     1461548           312                   4684.448718\n",
       "9                       77978            11                   7088.909091\n",
       "10                     929267           213                   4362.755869\n",
       "11                    3467894           411                   8437.698297\n",
       "12                   12444775          2339                   5320.553655\n",
       "13                   31849251          2896                  10997.669544\n",
       "14                     857108           319                   2686.858934\n",
       "15                    7209934          1872                   3851.460470\n",
       "16                    8725880          1654                   5275.622733\n",
       "17                    4347743           924                   4705.349567\n",
       "18                    8120838          1800                   4511.576667"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_congressdist_f = buildings.groupby(['Congress Dist'])[[\"Square Footage\",\"Total Floors\"]].sum()\n",
    "by_congressdist_f['Avg_Square Footage Per Floor'] = by_congressdist_f['Square Footage']/by_congressdist_f['Total Floors']\n",
    "by_congressdist_f.head(19)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x18b08990a88>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "by_congressdist_f.plot.bar(y='Avg_Square Footage Per Floor', rot=0, title=\"Average square footage per floor as a function of congressional district\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observation\n",
    "\n",
    "In this I first extracted the required information ie Congress District, total square footage and total number of floors in all the buildings. then I evaluated the Average using this information in a sepearte column in the data frame and used that to plot using Matplotlib. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization III - Square footage for the five most common departments (aka \"Agency Name\") as a function of year."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will first find the five most common departments by filtering and sorting the data in the dataframe. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Square Footage</th>\n",
       "      <th>Count</th>\n",
       "      <th>Mean Construction Year</th>\n",
       "      <th>Newest Construction Year</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agency Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Department of Natural Resources</th>\n",
       "      <td>3897070</td>\n",
       "      <td>3201</td>\n",
       "      <td>1872</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department of Corrections</th>\n",
       "      <td>15120750</td>\n",
       "      <td>1428</td>\n",
       "      <td>1944</td>\n",
       "      <td>2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department of Transportation</th>\n",
       "      <td>5604159</td>\n",
       "      <td>1124</td>\n",
       "      <td>1892</td>\n",
       "      <td>2019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department of Human Services</th>\n",
       "      <td>8093990</td>\n",
       "      <td>530</td>\n",
       "      <td>1939</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>University of Illinois</th>\n",
       "      <td>25018006</td>\n",
       "      <td>525</td>\n",
       "      <td>1955</td>\n",
       "      <td>2015</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Square Footage  Count  \\\n",
       "Agency Name                                              \n",
       "Department of Natural Resources         3897070   3201   \n",
       "Department of Corrections              15120750   1428   \n",
       "Department of Transportation            5604159   1124   \n",
       "Department of Human Services            8093990    530   \n",
       "University of Illinois                 25018006    525   \n",
       "\n",
       "                                 Mean Construction Year  \\\n",
       "Agency Name                                               \n",
       "Department of Natural Resources                    1872   \n",
       "Department of Corrections                          1944   \n",
       "Department of Transportation                       1892   \n",
       "Department of Human Services                       1939   \n",
       "University of Illinois                             1955   \n",
       "\n",
       "                                 Newest Construction Year  \n",
       "Agency Name                                                \n",
       "Department of Natural Resources                      2016  \n",
       "Department of Corrections                            2016  \n",
       "Department of Transportation                         2019  \n",
       "Department of Human Services                         2014  \n",
       "University of Illinois                               2015  "
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "buildings['Newest Construction Year'] = buildings['Year Constructed']\n",
    "by_mostcommon= (buildings.groupby('Agency Name', as_index=True)\n",
    "       .agg({'Square Footage':'sum','Agency Name':'count','Year Constructed':'mean', 'Newest Construction Year':'max'})\n",
    "       .rename(columns={'Agency Name':'Count', 'Year Constructed':'Mean Construction Year'} ))\n",
    "import numpy as np\n",
    "by_mostcommon=by_mostcommon.sort_values(by=['Count'],ascending=False)\n",
    "by_mostcommon['Mean Construction Year'] = by_mostcommon['Mean Construction Year'].apply(np.int64)\n",
    "df =by_mostcommon.head(5)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using Construction Year for comparison."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year Constructed</th>\n",
       "      <th>Square Footage</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agency Name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Department of Corrections</th>\n",
       "      <td>1858</td>\n",
       "      <td>7367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department of Corrections</th>\n",
       "      <td>1860</td>\n",
       "      <td>20160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department of Corrections</th>\n",
       "      <td>1863</td>\n",
       "      <td>15795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department of Corrections</th>\n",
       "      <td>1865</td>\n",
       "      <td>143955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Department of Corrections</th>\n",
       "      <td>1876</td>\n",
       "      <td>35080</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Year Constructed  Square Footage\n",
       "Agency Name                                                \n",
       "Department of Corrections              1858            7367\n",
       "Department of Corrections              1860           20160\n",
       "Department of Corrections              1863           15795\n",
       "Department of Corrections              1865          143955\n",
       "Department of Corrections              1876           35080"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected = buildings.groupby(['Agency Name', 'Year Constructed', 'Square Footage']).count().reset_index()\n",
    "selected=selected.set_index('Agency Name')\n",
    "SortedData = selected.loc[ ['Department of Natural Resources' , 'Department of Corrections', 'Department of Transportation', 'Department of Human Services', 'University of Illinois'] , : ]\n",
    "SortedData = (SortedData.groupby(['Agency Name', 'Year Constructed'])[[\"Square Footage\"]].sum()).reset_index()\n",
    "drop_missing=SortedData.index[SortedData[\"Year Constructed\"] == 0].tolist() # Drop entries with values Zero\n",
    "SortedData=SortedData.drop(SortedData.index[drop_missing])\n",
    "drop_missing=SortedData.index[SortedData[\"Square Footage\"] == 0].tolist() # Drop entries with values Zero\n",
    "SortedData=SortedData.drop(SortedData.index[drop_missing])\n",
    "SortedData=SortedData.set_index('Agency Name')\n",
    "SortedData.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18b0ceb3388>]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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p2y43s21mtiT8eXfKfZea2VozW2Vm56RsP93Mlob3XW1mFm4fZWa3htufNbN5KftcZGZrwp+LyvUeRUSkdimgiCpnhuJ64Nw0269y91PDn3sBzOxE4ALgpHCfH5lZffj4HwOXAMeHP4nnvBhocffjgKuAb4fPNRW4DHgjcAZwmZlNGfq3JyIitUzDRqPKFlC4++PAvjwf/gHgFnfvdPcNwFrgDDM7Epjo7k97MGn6jcD5KfvcEN6+HTg7zF6cAyxw933u3gIsIH1gIyIiUjRlKKLiqKH4vJm9FHaJJDIHs4EtKY/ZGm6bHd4euD2yj7v3AAeAaVmeaxAzu8TMFprZwubm5tLelYiI1BSN8oiqdEDxY+CVwKnADuDKcLuleaxn2V7sPtGN7te4+3x3nz9jxoxs7RYREYlQhiKqogGFu+9y91537wN+RlDjAEEWYW7KQ+cA28Ptc9Jsj+xjZg3AJIIulkzPJSIiMmQUUERVNKAIayISPggkRoDcBVwQjtx4BUHx5XPuvgNoNbMzw/qIC4E7U/ZJjOD4MPBwWGfxB+BdZjYl7FJ5V7hNRERkyKgoM6qhXE9sZjcDZwHTzWwrwciLs8zsVIIuiI3ApwHc/WUzuw1YDvQAn3P33vCpPkswYmQMcF/4A3AtcJOZrSXITFwQPtc+M/sG8Hz4uK+7e77FoSIiInlRhiKqbAGFu38szeZrszz+CuCKNNsXAien2d4BfCTDc10HXJd3Y0VERAqk5cujNFOmiIhIERRPRCmgEBERKYK6PKIUUIiIiBRBXR5RCihERESKoHgiSgGFiIhIEdTlEaWAQkREpAgKKKIUUIiIiBRBAUWUAgoREZEiaHGwKAUUIiIiRVCGIkoBhYiISBE0yiNKAYWIiEgRlKGIUkAhIiJSBAUUUQooREREiqAujygFFCIiIkXQ1NtRCihERESKoC6PKAUUIiIiRVCCIkoBhYiISBGUoYhSQCEiIlIE1VBEKaAQEREpguKJKAUUIiIiRVCXR5QCChERkSK4AooIBRQiIiJF6FWfR4QCChERkSIonohSQCEiIlIE1VBEKaAQEREpguKJKAUUIiIiRehVRBGhgEJERKQI6vKIUkAhIiJSBMUTUQooREREiqBho1EKKERERIqgLo8oBRQiIiJFUIIiqmwBhZldZ2a7zWxZyrbvmtlKM3vJzO4ws8nh9nlmdtjMloQ/P0nZ53QzW2pma83sajOzcPsoM7s13P6smc1L2eciM1sT/lxUrvcoIiK1S1NvR5UzQ3E9cO6AbQuAk939tcBq4NKU+9a5+6nhz2dStv8YuAQ4PvxJPOfFQIu7HwdcBXwbwMymApcBbwTOAC4zsylD+cZERERUQxFVtoDC3R8H9g3Y9oC794S/PgPMyfYcZnYkMNHdn/YgFLwROD+8+wPADeHt24Gzw+zFOcACd9/n7i0EQczAwEZERKQkiiei4qyh+BRwX8rvrzCzxWb2mJm9Jdw2G9ia8pit4bbEfVsAwiDlADAtdXuafURERIaEujyiGuJ4UTP7F6AH+GW4aQdwtLvvNbPTgd+Z2UmApdk98Qlmui/bPgPbcQlBdwpHH310/m9ARERqnkZ5RFU8QxEWSb4X+IuwGwN373T3veHtRcA64ASC7EJqt8gcYHt4eyswN3zOBmASQRdLcnuafSLc/Rp3n+/u82fMmDE0b1BERGpCb1/cLaguFQ0ozOxc4CvA+929PWX7DDOrD28fS1B8ud7ddwCtZnZmWB9xIXBnuNtdQGIEx4eBh8MA5Q/Au8xsSliM+a5wm4iIyJBRhiKqbF0eZnYzcBYw3cy2Eoy8uBQYBSwIR38+E47oeCvwdTPrAXqBz7h7oqDzswQjRsYQ1Fwk6i6uBW4ys7UEmYkLANx9n5l9A3g+fNzXU55LRERkSKiGIqpsAYW7fyzN5mszPPY3wG8y3LcQODnN9g7gIxn2uQ64Lu/GioiIFEirjUZppkwREZEiaNholAIKERGRIqjLI0oBhYiISBH6NMojQgGFiIhIEVRDEaWAQkREpAgaNhqlgEJERKQIiieiFFCIiIgUQRmKKAUUIiIiRdDy5VEKKERERIqgBEWUAgoREZEiqMsjSgGFiIhIEdTlEaWAQkREpAiKJ6JyBhQW+Esz+/fw96PN7IzyN01ERKR6aertqHwyFD8C3gQkVg9tBX5YthaJiIgMA6qhiMpn+fI3uvvrzWwxgLu3mFlTmdslIiJS1XoVT0Tkk6HoNrN6wAHMbAagJVFERKSmqcsjKp+A4mrgDuAIM7sCeAL4ZllbJSIiUuXU5RGVs8vD3X9pZouAswEDznf3FWVvmYiISBXT8uVROQMKM5sK7AZuTtnW6O7d5WyYiIhINdPy5VH5dHm8ADQDq4E14e0NZvaCmZ1ezsaJiIhUK9VQROUTUNwPvNvdp7v7NOA84DbgbwmGlIqIiNQcTWwVlU9AMd/d/5D4xd0fAN7q7s8Ao8rWMhERkSqmqbej8pmHYp+ZfQW4Jfz9o0BLOJRUJSkiIlKT1OURlU+G4uPAHOB3wJ3A0eG2euDPy9c0ERGR6qUERVQ+w0b3AH+X4e61Q9scERGR4UHzUETlM2x0BvDPwEnA6MR2d397GdslIiJS1VRDEZVPl8cvgZXAK4D/ADYCz5exTSIiIlVPCYqofAKKae5+LdDt7o+5+6eAM8vcLhERkaqmLo+ofEZ5JGbE3GFm7wG2ExRpiohIgQ539dLrzvhR+Xz9SjVTQBGVz1/0f5rZJODLwPeBicAXy9oqEZER6t/uXEZzayc3fOqMuJsiJVIJRVQ+AUWLux8ADgBvAzCzN5e1VSIiI9S+ti6aWzvjboYMAWUoovKpofh+nttERCQPGh0wMiigiMoYUJjZm8zsy8AMM/tSys/lBJNaZWVm15nZbjNblrJtqpktMLM14b9TUu671MzWmtkqMzsnZfvpZrY0vO9qM7Nw+ygzuzXc/qyZzUvZ56LwNdaY2UUFHhMRkbLq0brXI4I+xqhsGYomYDxBt8iElJ+DwIfzeO7rgXMHbPsq8JC7Hw88FP6OmZ0IXEAw18W5wI/Cqb0BfgxcAhwf/iSe82KC7pjjgKuAb4fPNRW4DHgjcAZwWWrgIiISN2UoRgZlKKIy1lC4+2PAY2Z2vbtvMrMJwWY/lM8Tu/vjqVmD0AeAs8LbNwCPAl8Jt9/i7p0ES6OvBc4ws43ARHd/GsDMbgTOB+4L97k8fK7bgR+E2YtzgAXuvi/cZwFBEHJzPu0WESm3HgUUI4ICiqh8aigmmNliYBnwspktMrOTi3y9me6+AyD894hw+2xgS8rjtobbZoe3B26P7OPuPQRFo9OyPNcgZnaJmS00s4XNzc1FviURkcIoQzEy6GOMyieguAb4krsf4+7HEAwfvWaI22FptnmW7cXuE93ofo27z3f3+TNmzMiroSIipVKGYmTo0+cYkU9AMc7dH0n84u6PAuOKfL1dZnYkQPjv7nD7VmBuyuPmEEygtZXoJFqJ7ZF9zKwBmATsy/JcIiJVQRmKkUFdHlH5BBTrzezfzGxe+POvwIYiX+8uIDHq4iKC5dAT2y8IR268gqD48rmwW6TVzM4M6yMuHLBP4rk+DDzsweL0fwDeZWZTwmLMd4XbRESqQnevhgeMBIoLo/KZ2OpTBIuC/ZagO+Fx4K9y7WRmNxMUYE43s60EIy++BdxmZhcDm4GPALj7y2Z2G7Ac6AE+5+694VN9lmDEyBiCYsz7wu3XAjeFBZz7CEaJ4O77zOwb9C9g9vVEgaaISDVQhmJkUIYiKmdA4e4twBfMbCLQV8Aoj49luOvsDI+/ArgizfaFwKAiUHfvIAxI0tx3HXBdPu0UEak01VCU7mBHNxNHN8baBtVQROXs8jCzU8JRHkspfZSHiEjNU4aiNC9u2c9pX1/A1pb2WNuhjzEqnxqKn1L+UR4iIjWjt89xpcuL1tzaSW+fx74miro8oio9ykNERFCWYijEfQwVT0TlU5S53sz+Dbgp/P0vKX6Uh4iIENRRNORcFUmyibsWpVcRRUQ+GYpPATMIRnn8FphOHqM8REQks7ivrkeCnt54j6G6PKIyZijM7EPu/lt3bzGzy8LRHiIiMgTivroeCeJetdUd3J1wEeyaly1D8a8ptx8qd0NERGqJMhSlq4ZjWAVNqBrZAgrLcFtEREoU99X1SNAdc5cHqNsjVbaizDFmdhpB0DE6vJ0MLNz9hXI3TkRkpKqGq+vhrhqOoQKKftkCih3A98LbO1NuQ7B659vL1SgRkZEu7oLCkaAasjyKJ/plDCjc/W2VbIiISC2phqvr4a4agjJ9jv3yGTYqIiJDTKM8SlcNJ3N1efRTQCEiEoNqOBkOd9UQlFVBE6qGAgoRkRhUQ///cFcNx1BrsvTLZ7VRM7O/NLN/D38/2szOKH/TRERGLmUoSqcaiuqST4biR8CbgI+Fv7cCPyxbi0REakA1pOuHu2o4mVdBE6pGPgHFG939c0AHQDgFd1NZWyUiMsJlOhku23aATXvbKtya4albXR5VJZ+AotvM6gnmnsDMZgDxf4oiIsNYpnT9V37zEv/9wOoKt2Z46q2GLg8FFEn5BBRXA3cAR5jZFcATwDfL2ioRkREuU4aiu7ePw109FW7N8FQN3UZV0ISqkW2mTMysDtgA/DNwNsHU2+e7+4oKtE1EZMTKNkKhGtaoGA6qYZRHnyKKpKwBhbv3mdmV7v4mYGWF2iQiMuJlKyishmLD4aAaMhTq8eiXT5fHA2b2Z6YF30VEhky2k2F3b/xX3sOBaiiqS9YMRehLwDigx8w6CLo93N0nlrVlIiIjWLYsRDVceQ8H1XCcNPV2v5wBhbtPqERDRERqSbaTYY8yFHmphhoKDRvtl0+GAjObAhwPjE5sc/fHy9UoEZGRrldFmSWrhlqTKmhC1cgZUJjZXwN/D8wBlgBnAk8Dby9v00SkFmza28bsyWNoqK+tpYWyTRtdDVfew4Gm3q4u+fwP/nvgDcAmd38bcBrQXNZWiUhNOHC4m3d87zHuW7Yz7qZUXNYaiio4UQ4HqqGoLvkEFB3u3gFgZqPcfSXwqvI2S0RqQUd3L929Tkt7V9xNqbisNRRVcKIcDqrhOCme6JdPDcVWM5sM/A5YYGYtwPbyNktEaklXT+2l+LNnKGrveBQjWx1K5dqgiCIhn1EeHwxvXm5mjwCTgPvL2ioRqSnVcKVZaVnnoajB41GMaiheVZdHv3yKMo9O+XVD+O8sYHNZWiQiNacWr8izXV3X4vEoRpzZgToLRngo9uuXTw3FPcDd4b8PAeuB+4p9QTN7lZktSfk5aGZfNLPLzWxbyvZ3p+xzqZmtNbNVZnZOyvbTzWxpeN/Vidk8zWyUmd0abn/WzOYV214RKb9quNKstOzzUNTe8ShGnJmt+rpg8mjNQ9EvZ0Dh7qe4+2vDf48HziBYcbQo7r7K3U9191OB04F2gtVMAa5K3Ofu9wKY2YnABcBJwLnAj8Ll1AF+DFxCMEfG8eH9ABcDLe5+HHAV8O1i2ysi5VeLwySzTRvdXYPHoxhxZnISq1GohqJfwQO/3f0FgmGkQ+FsYJ27b8rymA8At7h7p7tvANYCZ5jZkcBEd3/agxDxRuD8lH1uCG/fDpyttUhEqpcyFFE6SeUnzgxFmKBQl0eKfGoovpTyax3weoZuHooLgJtTfv+8mV0ILAS+7O4twGzgmZTHbA23dYe3B24n/HcLgLv3mNkBYBqwZ4jaLSJDqBYXw8oWNHT3Ou6OroOyi7eGQl0eA+WToZiQ8jOKoJbiA6W+sJk1Ae8Hfh1u+jHwSuBUYAdwZeKhaXb3LNuz7TOwDZeY2UIzW9jcrLm6ROJSizUDua6ulaXILc4uj/owoNDH1C+fYaP/UabXPg94wd13ha+zK3GHmf2MoBAUgszD3JT95hDMg7E1vD1we+o+W82sgWCo676BDXD3a4BrAObPn68/C5GY1GQNRY733NPnNNRnfUjNi7PLI5E80vLl/fLp8rgr2/3u/v4iX/tjpHR3mNmR7r4j/PWDwLLw9l3Ar8zse8BRBMWXz7l7r5m1mtmZwLPAhcD3U/a5iGDNkQ8DD7vyUiJVSzUUg3X39jG6URFFNrF2eesizpIAACAASURBVNQlMhS197ebST4zZW4gmHfiF+HvHwM2An8o9kXNbCzwTuDTKZu/Y2anEnRNbEzc5+4vm9ltwHKgB/icu/eG+3wWuB4YQzCUNTGc9VrgJjNbS5CZuKDYtopI+amGYrBa7AYqVJx/N/WqoRgkn4DiNHd/a8rvvzezx939a8W+qLu3ExRJpm77RJbHXwFckWb7QuDkNNs7gI8U2z4RqaxaPHnmzFDUYDdQoeLMUPQPG42tCVUnn6LMGWZ2bOIXM3sFMKN8TRKRWlOTGYocQZSKMnOrjmGj+pwS8slQ/APwqJmtD3+fRzCZlIjIkNBaHmnur8GsTaHiPEYaNjpYPqM87jez44FXh5tWuntneZslIiPF2698lL/+f8fy8TcenfExNZmhyNGlUYvHpFDVMPV2DcbCGWXs8jCzN5jZLIAwgHgd8HXgu2Y2tULtE5Fhbsu+djbubcv6mFo8eebMUOhMlVOcy5cnh43qc0rKVkPxU6ALwMzeCnyLYHrrA4RzN4iI5KOrJ8ecCzWY3s91IqrFIKtQ1dDloRqKftm6POrdPTEZ1EeBa9z9N8BvzGxJ+ZsmIiNFrpNjdw1e5amGonTVUJSpeKJftgxFfTjLJASLeD2ccl8+xZwiIkDugCLOKZTjknMeihoMsgqlia2qS7bA4GbgMTPbAxwG/ghgZscRdHuIiOQl10yYtXg1njtDUXtBVqHinKujTsuXD5IxoHD3K8zsIeBI4IGUqavrgL+rRONEZGTIVUNRi/UC+azlIdm5Q1+fJ7MFlaQuj8Gydl24+zNptq0uX3NEZCTqyllDUXsBRa6sTC0GWcXo6XOaYgko1OUxUD4zZYqIlCR3DUXtfSlrLY+hEddKtXVavnwQBRQiUnY5R3nU4Mkz9zwUylDkI66uobrw7Knly/spoBCRsuvu0clzoNzzUOhElY9ca6KUi6beHkwBhYiUXc4aihxFmyNRritrjR7IT1z1N8kuD31OSQooRKTsco7yqMEvZa3lMTTiCrwSdaBKJPVTQCEiZaeJrQarprU8Nu1t41BnT8VebyjFVbyqLo/BFFCISNnlCij6vPZSx7lHeVQuyProT5/hp4+tq9jrDaXYijI1bHQQBRQiUnb5FBjW2lwUueehqNyJqq2zh5b2roq93lCKa8XRxCiPGouDs1JAISJll6soE2pvVEPutTwqe6LMVedSreLOUKh4tp8CChEpu3wKDGutjqKaaihgGAcUqqGoGgooRKTs8jlZ1V6GorpmDx2uxz++ia00U+ZACihEpOzyylDUWg1FFRVlAnQO0wxFbDUU4bBRFWX2U0AhImXX3es5U8O1tnZFzpkyK93lMUy7nOL6u0ksR1Zro5OyUUAhIhWRK6U+XE9oxaq2DEVXT29FX2+oxLnMe52pyyOVAgoRqQitOBpVbWt5qIaicPV1pi6PFAooRKQicq84WlsZit6+7N1AGjaan7hqKADMTKuNplBAISIVkatLI84rzbhke8+Vnt9guAYUcWZW6gwUT/RTQCEiFZHrhFVr81BA9qCh0ifK4VrDEufEUnVmKspMoYBCRCpCRZmDZctQVL4oc3ge/1hrKMxUlJlCAYWIVISKMgfrzfKeNWw0P3Fmtsw0D0UqBRQiUhE5uzxqbGIryP6elaHIT6zDRjXKI0IBhYhURO5RHrX3xZyt/7/SGZvhGlDEWUMRdHnU3t9tJrEEFGa20cyWmtkSM1sYbptqZgvMbE3475SUx19qZmvNbJWZnZOy/fTwedaa2dVmwWotZjbKzG4Ntz9rZvMq/R5FJCpXwFCLXR7Zrq4r3eUxXIftxtvloRqKVHFmKN7m7qe6+/zw968CD7n78cBD4e+Y2YnABcBJwLnAj8ysPtznx8AlwPHhz7nh9ouBFnc/DrgK+HYF3o+IZJHrCni4ntBKke3qutLzK/T0+bAcsRD7TJnD8JiVSzV1eXwAuCG8fQNwfsr2W9y90903AGuBM8zsSGCiuz/twewwNw7YJ/FctwNnJ7IXIhIPTWw1WNYMRQwZm+FYmBn7sNE8uzzau3o40N5d5hbFK66AwoEHzGyRmV0Sbpvp7jsAwn+PCLfPBrak7Ls13DY7vD1we2Qfd+8BDgDTBjbCzC4xs4VmtrC5uXlI3piIpKeJrQbLloWII5U/HFccjbP2Jph6O7/HfvPeFVx8w/PlbVDMGmJ63Te7+3YzOwJYYGYrszw2XWbBs2zPtk90g/s1wDUA8+fPr71vM5EKyj1sdPidzEqVdR6KGAKs4ViYGe/U2/l3ebS0dbOrtaPMLYpXLBkKd98e/rsbuAM4A9gVdmMQ/rs7fPhWYG7K7nOA7eH2OWm2R/YxswZgErCvHO9FRPKjUR6DZStEjeN4DMdup3hrKAob5dHZPfyObyEqHlCY2Tgzm5C4DbwLWAbcBVwUPuwi4M7w9l3ABeHIjVcQFF8+F3aLtJrZmWF9xIUD9kk814eBhz3bKjwiUnbdPblW1xzZX7bpZB82WvnjMRwzFHGODiqkywOgo3t4LhGfrzi6PGYCd4Q1kg3Ar9z9fjN7HrjNzC4GNgMfAXD3l83sNmA50AN8zt0Tn8pngeuBMcB94Q/AtcBNZraWIDNxQSXemIhk1qkaikGqaXEwGJ5FmXH+3RQ6U+ZwrFEpRMUDCndfD7wuzfa9wNkZ9rkCuCLN9oXAyWm2dxAGJCJSHbo1bHSQrIuDxVAbMBwzFHHWUBTc5dHTh7szUgcdVtOwUREZwbSWx2DZp95WhiIfcS9fXmg8M5KzFAooRKQichZl1uBaHtW0fDkM1wzF8CnKBAUUIiIl68pxgsxVtDkSZR82qi6PfMQ/yqOwfTpHcGGmAgoRqYicXR61mKHIEmTF0uUxHAOKGLtp6uoKX75cGQoRkRLlLsqsnQxFQ11QlJd96u3Kn3iGY2Hs8OvyUIZCRKQkOafeHoYns2LVhwFF9sXBVJSZj+HW5dExgie3UkAhIhWRu8ujFjMUwTHZsq+d//vj+shjevqcSs/HNxzT8XF2lRWz2qgyFCIiJerKUXQ5HK+OizUwQ3Hfsh385z0rOHA4uhplpYOs4VlDEXeGosCAQhkKEZHSaHGwfg31wVfvwIBh4NTMlT5ZqoaiMHV1hQcUHcpQiIiURhNb9ctUQzEwoKj03BzDLUNRX2d0x1pDQRHDRofXMS6EAgoRqYjcE1vVTkCRaZTH4ZgzFMMtoGios/in3i7w71YZChGREuUq+KulLo9khmLAez7cNSCgqHSGYph9Bg11phqKKqKAQkQqImeGYpidzEpRtRmKYfYZ1NdZvMNGC1y+HIbnSJp8KaAQkYrINXFVLU1slW8Nhbo8smusr4t5HgoKHto78DMeSRRQiEhFaOrtfg116Ud5HO6KHgMVZWZXXwU1FL2aejtJAYWIVESuk5VGeVRBl8cwO9nFX0NRzPLlylCIiJRENRT9wgRFxhqKRMBR6WMylK/3Zz9+ihue2jhkz5dOQ+xdHkXMQ6GiTBGR0uQq+KulGgrD0g557AhHeeSzeFg5DGVR5ppdrazc2Tpkz5dOcAyHV0ChDIWISIm6c0y9XUvDRiH9CIVEhqIxnEmz0vUBQ93l0d7VM6TPN1BwDONevrywfZShEBEpkSa2imqoM3p7c3V5DO/Fwdq7yns13lBfN/zmoRhmdSqFUEAhIhWRLZ0eFNeN3C/adNJlKDqSGYqwy2OYr+VR7gxFQ9zzUJhR6IKwnRo2KiJSmmwnq4b6eKv149BQX5dxHorEsNLhPmy0rbO8J8/62GsoCl+crEMZChGR0mRL3zfW1Q27WRpLlbaGIlGUGVOGYqg/g4FTiQ+1hjqLdXRQcVNvK0MhIlKS3j7PeDXXUB9v6joO6UZ5DCzKrHQ30JBnKMrd5VEfc4airoguD2UoRESKZ8EFd8arycYw/V/oNMbDWfpRHsHxiWvY6FAXgZY/QxH3PBQUMQ+FMhQiIkVrCq+4M6XUE1fktTQXRbo5FJLzUCQyFMO9hqISw0Zj7vIoNEMy3GYjLYQCChEpu0RA0Z3hyzRZM1BD63lkm4eiYYQMG+3o7itrl0RjfbDaZ19MWQozrTaaSgGFiJRdY0P2DETyBJpj8quRpKGuLuM8FLEVZZZhFseB65MMpeSaKDF1ldXXabXRVAooRKTsEvMqZKuhgMoPk4xTtlEejXXxdHmUIyNSzrkokqu2xtRVpomtohRQiEjZNeZZQ1FLc1EEIxQGrOUxIENR6S6PcgzdbS/jXBRxd5UVU0OhDIWISAmSRZk5aihqacXRrDUUMQ0bzTa0t1jlLMzMtAx8pRQzU2ZPn4/YWWErHlCY2Vwze8TMVpjZy2b29+H2y81sm5ktCX/enbLPpWa21sxWmdk5KdtPN7Ol4X1XmwWD08xslJndGm5/1szmVfp9iki/pmQNRYYMRTLFX0MZinSjPLp7cYfGmIaNwtCPQijn0NG4ilcTihk2CuXJBFWDODIUPcCX3f01wJnA58zsxPC+q9z91PDnXoDwvguAk4BzgR+ZWX34+B8DlwDHhz/nhtsvBlrc/TjgKuDbFXhfIpJB/7BQZSgS0mUo+jw4BnEVZcLQn+zayhlQJFdljSmgqLOiCkJH6oqjFQ8o3H2Hu78Q3m4FVgCzs+zyAeAWd+909w3AWuAMMzsSmOjuT3tQZnsjcH7KPjeEt28Hzk5kL0Sk8hJFmV0ZRnHkCjhGooa6wWt5QNDtUWeGWWVrA3J1SxXrcFmLMuOtoTArfPlygM4yjKapBrHWUIRdEacBz4abPm9mL5nZdWY2Jdw2G9iSstvWcNvs8PbA7ZF93L0HOABMK8NbEJE85AoY4lpdM07pMhQQHelRyVR+oltqyDMUZSzKTNRQxPV3U29W1OyuncpQDC0zGw/8Bviiux8k6L54JXAqsAO4MvHQNLt7lu3Z9hnYhkvMbKGZLWxubi7wHYhIvnLVUDTENEwyTunW8oD+dHiwAmsFMxQN5clQtJdxVENydFCMRZnFvHSHMhRDx8waCYKJX7r7bwHcfZe797p7H/Az4Izw4VuBuSm7zwG2h9vnpNke2cfMGoBJwL6B7XD3a9x9vrvPnzFjxlC9PREZoDHvUR41lqFI834TGYKGDBmMcmkqU7dTe+dIHuVR3GsrQzFEwlqGa4EV7v69lO1Hpjzsg8Cy8PZdwAXhyI1XEBRfPufuO4BWMzszfM4LgTtT9rkovP1h4GGvpVWHpKz2HOqMbarf4SpZQ5FzLY+R+UWbTq6VMhvr6yqasWlsSNS5DHFAUZFRHnHVUASvr9kyA3FkKN4MfAJ4+4Ahot8Jh4C+BLwN+AcAd38ZuA1YDtwPfM7dE5/GZ4H/IyjUXAfcF26/FphmZmuBLwFfrcxbk5Fuw5423vRfD/Hgil1xN2VYaWoIBmZlykDUZg1F+qLMhKDLo/IZiqGeybESM2XGlaFIZEi0nkegodIv6O5PkL7G4d4s+1wBXJFm+0Lg5DTbO4CPlNBMkbTuXbqD7l5n8772uJsyrOSaeruhFjMUObo0GipelBkEfUO/4mglZsqMr8sDgrko6tOe1tIbqQGFZsoUKcB9y3YA0NLeFXNLhpdc/fNxTuQUl/o0E1ulaqy3yg4bzVE4W6xyTmzVP8oj3i4PTb8dUEAhkqfNe9tZtu0gAPvbu2NuzfCSuyizVjMUmd9vpqLNcmmqL08NRVsZizIbYi7KTAQ0+ZZQJII2ZShEatz9LwfZiYmjGxRQFKi/6DLD8uU1OsojV1FmKQHWnkOd3PXi9twPDJUyD8XizS0ZC5XLuXx5Q8yZrdQuj3yMSgYUylCI1LT7lu3klNmTOH7mBHV5FCjXCIKmmBbDilPOGor60oaN3rVkO1+4eTEtbfn9rRY7U+aGPW188EdP8dia9HP5lDNDUV8f7/wldYkujzwDitGNQZ2Kpt4WqWE7Dhxm8eb9nHvyLCaPaaRFGYqC1JtRZ7kntuoeYTUUL2xuYe+hzrT31dfV0ZslI9NQV1dSQJG4at7blv71Byo2Q5EYxbF9/+EM95dxYquYZ8pMDhvN85ApQyEi3L9sJwDnnTyLyWOb2K8MRcGaGjKn8PsXwxpZV26fuv55rnl8fdr7cmUgGodopsy9h/L7W81V51Ls66QLKLp7+3j7fz/KQyUOv457Yqv6Ars8kjUUylCI1K77lu3kVTMncOyM8UwZ26gujyI01tdlmdhqZM5D0dndx44DHWnvS1dDkTgOEGQolu84WNRaEan25tvlUeLU2/syvE66gOJwdy/r97SxZMv+ol4rIVl7E+Nqo5B/QFFnRlNDnabeFqlVu1s7eH7jPs47ZRYAU8Y10dHdN2KHfpVLU5Yiw+TV8QjLUEBQHJlOulEeiT52gC0t7exv7+apdXtLev18A4pRJS4Olul1sk1slenY5Kt/YquYh40WEPSNaqhThkKkVj3w8i7c4byTg9nhJ49tBDR0tFCN9XV0Z1i+vCFZlDmyMhSQ+aRZXxcsLJU6OiI1oEgErBv3tpX0+vvy7PJIzhVSdJdH+vfZ3tWbcQRIc2v6tvX2Od9/aA2tHdn/jzVUwWqjkP+wUQg+Y9VQiNSo+5ft5Njp4zhh5ngApoxtAjS5VaEaGyzj1W+9GWYjc7XRPRlO6Mk5FFLORmNSAorE1Xdza2lX8fvyLMqsqws+g2IzFJm6PCDz6prNGYKQNbtbuXLB6pxT3NcPs2GjoAyFSM1qaevi6fV7Oe+UWcn0ZiJDUWpA0drRzcEcV2AjSbYaCoDGCk81XSkt7V1piyvr06xDEQkowvqA3SUGFPl2eRhGU31d8UWZaV4nETSd+O9/YGeaWpI9Gd5b4vy862D2914Ny5dDYWt5jGqo08RWIrVowfJd9PZ5srsD+jMUpXZ5/NOvX+JTP3++pOcYTprq67Km0xuGaFRDtXFPf/WeblKm0U39AUXiZFlqhiLfUR4QFGYmTnYrdhxk4cZ9ee+7r61rUNfG2JT3s3LnwUH77DnUmbXodNfB9AWtCclRHrFNvR38W8jqw6Mb60ds/ZUCCpEs7lu2gzlTxnDSUROT24YqQ7H/cBcLN7Wwdvehkp5nuMg2bBQKmxnS3Use/VBJ6VL7/SfD1AxF/1dyIuAoNUORrStioFEpn9H/PriGr/52ad779vb5oIzb2Kb+9SfTZSg6e/o4lGXiq905MhRxz5RZX+AoD1CGQqQmHezo5om1e3j3KUcmuztg6DIUCXcs3jokz1PtgoAh+7wL+Q7/e+dVj/PzJzcOUcvKL10dRf9Kmf0nl2iXR/D1nKlbIF/5dnlA2C0Vnux6+pxtLYcLCtwGvtbYUf3vJ9Pw2Uw1JjA4Q/GDh9fw1Lo9yd/jr6EopstDRZkiNeehFbvo7nXOPXlWZPvoxnpGN9blPaVxLr9bvL2glOlw1VifuSgTwpkh88xQbN7Xnlz5dThIFxSkm5RpTKTLI7i/uTV7t0AuLe2DuyIyaWqI1rkc7u4tKHAe2L2S2uWRqfsi29DRXa3RfX72xw38emF/AJ4IuuKa2CpxnVHI649urNPU2yK15r6lO5k1cTSnzpk86L4pY5vYf7j0DIUZbNt/mGc35N9XPVw15ij4C2ooMn8xu3vki3vJlv1lWRq7rbOHXz27eUi7VNKdNBPp+u4Mw0YTAUdXbx8HSvhbS9cVkUm6osxtGabUTmfgiJLULo+MGYosGZhdBwcHU1tb2pO3k8cwphqKuuSw0UK6PJShEKkpbZ09PLa6mXNPnpWcDS/VUE2/fcrsSYwf1VAT3R7ZJraCsEsky5XeDx5ey/t/8ETy9+5eZ+GmoQ/EHl/dzNfuWMpLWw/kfOxDK3axeHNLzselCyiSozx604/yaKzr/3ouuTCzgNkyBwYUmQKBfF4nNUORroYCsmcounoGB1NbW/oDnLpwuHHcy5cX8vLKUMiQ277/MD98ZG1NpLqHo0dW7aazp4/zBnR3JATTb5eeoRjdWM95J8/i3qU7y3K1XU1yFV021lvWUSDbD3Tw8vaDkeP0dImzSKaTmBcinwmlvnXfSr63YHXOx6UbadFfUDi4hsK9v8YChmDoaAHreQzslsq06Fc+rzMutSgzQ5dHc462DRw6uvNgR6SNjSUuolaKTPNQ3LlkG8u3Dx7VAspQSBn86tnNfPcPq2oi1T0c3bdsJ9PHNzF/3tS0908Z2zRkE1t98PWzOdTZw4ISF0qqdsEoj8xf/G2dvZGCu0w27es/0T+9fugDiuTr7G3P+RgH1jfnDjyyjvJI0+XR2dObrA+Ayk1ulS5Dsf1AIV0e0f8TqTUhBw53p52GO9f02wNrL9yjQU66NVGeWreH933/ibIPz0xOvT3g9b9x93J+/Ni6tPuMaizvKI+tLe08ump3LENTFVDEZPGWIE16z9LtMbdEBuro7uWRlbt510mzkl/6A00e2zhkozzOfMU0jpo0mjteGNndHrlqKLbtP8zBjh4O5DiuG/cEJ/A6g5e2Hsg67LAUG/e2sfNAB1v2ZQ8sth84nPPLO+0ojzQjFBIn4MPdvcmluSFYT6YUhaznMThDMTRdHpC+2yPXKJZ0xZyp3R49fX2DApnVO1tZuu0Aa3aVd0h2pqm33WF9c/rXLvc8FA8u38Unf/48B4egxqtQCihi0NvnvLgl6J+9b+nOETmZz3D22Opm2rt6eXfKZFYDBQFF/tXz2dTVGeefNpvH1+wp+Uq0mjU1WF7Fc6t3t2a9f8Oe4AR/0lGT6O1zni9g8qVCbNrbztfvfpm//eULWR/nDhv2ZM9SpC3KTDNCIZGhONzdF+nyKDlDUcB6HoMyFAV1eUTbWWfRgDxtQJEjQ5Guuyc1oOjudW5fFATjza2dkf+Ta3L8LZUqUeaSbh6Kdc2H0n4/JOahKNc8Kqt2HWLy2EZmTBhVlufPRgFFDNbuPsShzh7eeeJM9rZ1qdujyty/bCeTxzbyxmPTd3dA0OXR59DaMTRXxx96/Wx6+5y7Xhy+Gau+PufOJdsyBsj5Tly1amcru1s7Mi4MlchQnH7MFBrrjWfKUEcBsGlvG+1dvSzfcTDnFWWubo90s0imzVCEAUVH19B1edTXWd4ZinSf0Y48Awqz3JNopaujyDYPBWTKUAzOGrV2dHPWdx/hV89tTm4r96RxZpknturo7kvbXTSqoQ53yjbN/OpdrZwwc0Jk7pxKUUARg0RV+D+84wTGNtVz90vD9yQy0rg7D67YxTteMzM59XE6kxOTWx0emjqK446YwGvnTOK3w7jb46VtB/j7W5ZkDIpydXkkrN7Vyt/csDDjLI2JYsnRjfWcNndK2eoo9hzqoq2zh94+Z/Wu7Fe6mdLbENQl9Pb5oJqb/hqKlKLMpuBv7nB3bzLggNKKMqeMbSxplMfOgx15ZVGnjG3K+ToDR4zUWeE1FADbWgafqJdvP0hbVy/PpVygrckjoFi0qSXnFN+Z1GUJKADWpQk0E1moTAumlcLdWb2zlVfNnDDkz50PBRQxWLx5P5PHNvKaIyfwjtfM5P5lO2MbRy1RHmYd5k4Zm/VxU5LTbw9dP+UHT5vNy9sPsmpncPJatKklZyp9oLte3B5bliNx0nl0VXPa+3PNlJmwamcrrR09PLpyd9pq+NTRF2e+chrLth0o2yJricLMlzNU7CesT/mcWju6I3UX08cFwefAK/F0S2+PaeyvoWgYomGjU8c1lVSU2ef5BTTTxjWlzcSkGtjlMXVcE+1dvWmLNRPSLRDWmqZuZsWO4DNatr1/uG8+GYrP/mIR375/ZWRbS1sXO/IoRk0EIne/lH6StXVpXn9UQ/C5lmPF0R0HOmjt7OGEWQooRqyn1u7hkVW7k78v3tLCaXMnY2a857VH0tLeXZbhb1I+k8uwhPn7XncUDXXGb8M5Kf7x1y/y/u8/kdfIB4CFG/fxxVsW80+/frHkIr5SPL6mOe28AIlZGHP1Ha/e1YoDbV29LNw4eI6HXQc7kye9Nx07jT6H59aXp9swcSJ9eXv2OSlSMxQ/fGQd7/vBE8mLhOlhX/bAK/Fsozw6unuTM2U21ltJGYqp45ryHjY6cKbMhHR1FIs2tUQW/Jo6rinrJFpmg7s8po8Pj01r+vZNGNXA7jyzByvDQHzDnjbawqHFm/a25Ryi2d3bx6JN0b+zb967gr/4v2dzvmZiCPOTa9P/H12XJnM1KmUkz1BbFWbSlKEYgdydHzy8ho//37N84ebF9PT2cbCjmzW7D/H6o6cA8KcnzGD8qAZ1ewwziQzFUExulTB9/Cj+9IQZ3Ll4O719TndvH62dPXzyuuf5fY6sw4HD3fz9LUuYNXE0PX3OTx9bP2TtKtT+9m6WbNk/aHtT/eCagXRa2ruTlf+PrNyd9bGnHT2Zpoa6sg4fhdwZinXNbclAqa2zh/3t3clgKHnSHBBQNKQ5HmNSAorE/VPGNnHgcHfyBHTnkm2s3X2Idc2H+OCPnszZZTBt/Ki8FwgbWJTZFF5Np5st8/K7XubSlG6paeODIDtTt8f08aMGZSgSxybdsFqAIyaOYveAQstMEhkKd5JzQPSlFMz29TnXP7kh7aigTXvbI1mgtq4e1je35ZwlNNErtTrDaJJ0GZJEhqIck1utDoOqE2aOH/LnzocCijI53NXLF25Zwn8/sJrXHDmR1o4eXti8nxe37McdTgsDitGN9bzzxJn84eVdefUvS3VILBDW0ja0qfYPvX4OOw92JDNW73jNEZw6dzJ/d/Nirn1iQ9p93J2v3bGUXQc7+NFfns75p87ml89uijVL8eiqwYFAoiYln+69REr7kTTPk2p0Yz2nHz2l7Bm+lTtas87GeKizh0tuWhQ5KSXaPj080Q7stujqCZ7vypSJsRLDRrt7PdnlkfhbS+z/r3cs47t/WMnqna0s3ryfB17OPn9Joisin1EFZnCwoyf52CMnjQbSz5bZ0+e8uGV/cibLaeOC4CBTNmTWxNEs3XaA/7x7tCsymwAAIABJREFUeXJb4thkCopmhgFyapAyYVRD2seu2NFf55Ku22Nd8yEu//1ybn42KNoceDye27CPBct3RbbnKvhNLXxMl5lJV0MxqqG8GYqZE0clM6iVpoCiDHYcOMyf//Rp7n5pO18599XccsmZ1NcZj67azeLN+zGD186dlHz8e197JAcOd2dMm0n1mTimEbOhzVAAnP2aI5gwuiHZ7TFxTCM3XnwG5540i2/cvZxv3rti0NXa7Yu2cs9LO/iHd54QBB9vP47uXueaMEvRV8BaDkOhoc7SBgLJgKIn/+r2dc1tbE6ZYGrgvAYAb3rlNFbsPJj2s3hp634u/e3SjMHATx5bxxduXoy788mfP8etz/ePEJg0pjF5+3B3Lxv2pL8KnTA6OMEtWL6LW1JGGCSyK5PGNFJfZywekLVJdC28mLI9MvV2IkMxLmhHIqDoc+ePa/Yk9384RxZn6rgmevqcg4eDIC3biez+ZTsBuG3hFiCY6XLi6IaMQ0f7vP+kOzWsFfnznz4dXfAsfE+zwuDk/57YwP4wEM+UvUmYOTHYJ7VocvaUMWkfm9pVkzopWWIuikSTFqzYxU1Pb+Ts7z0WCW5/+Mha/ubGhSxY3h+gPbN+L8u2Hcg4yid1npolmwdn5fYc6hw0r8roxjJmKMIRHnFRQDHEXtjcwvt/8CTrmw/xs0/M57NnvZJJYxo5/ZgpPLqqmcWbWzj+iPFMHN3/ZfWW42cwYXRDxsKeavbU2j184tpnueKe5dz90na27Gsv2/jqfDS3dnL7oq1lm5sgob7OmDh6aKbfTjW6sZ73nHIk9y/rn4p7dGM9P/yL1/OJM4/hmsfX86XbliSzWRv2tHHZXS9z5rFT+cyfvhKAedPHcf6ps/lFmKX45XObefO3Hs477V2q+fOmsGzbwUEZksZEMVpv9iuzxBXoKbODoPvR1f0nzHGjGpInoYQ3vXIa7vBMmjqKJ9bu4ebnNvPHNYMLRe9YvJVv3beSu17czktbD/D0ur38130rORQOBZ43LSjMTZwQM3V7HDujP718z9L+/8Nrdh/icHcvZsFMjve8tIMXUtb9SJ24KnGVPzrN8uUDMxQA7V29PBN28zy5dk/WYa3TxiW6IjrZvv8wp1z2QNoMEgTHF4gsDX/U5DHJya22trTzs8fXR4Lax9cEF0KJLg8g2bbgOYP3lMh2ADywfGe4T/BZfuvelfT1OUu3HmBtytwRR0wM7k/9W5qTo2A61cTRDYO6HRZtauHFrQdY39wW+btYHnaZ/D7le/jxNc188EdPZpxePXXeu4UD6jAS73fdgEC0XBmK3j5nza5DsdVPgAKKIfXbF7ZywTXPMKaxnjs+92beceLM5H1nvWoGy3cc5JFVzZw2d0pkv6aGOs45aRYPLN857OZ4f2LtHv64Zg83PL2Jz/9qMW/5ziPM/88H+dT1z/O/D67h0VW7h2yZ73TcnZe3H+Dqh9bwgR8+yRuueJB//PWLXHTdc5EvpnKYMrZxSFYcHehDr59De1dvJM1bX2d8/QMn8U/nvIrfLdnOp65/npa2Lr5w82Ia6+u46qOnRq6WPv/24+jq6eOax9bT0tZFa0cPt6RcfRfrYEd3zv7st73qCAAeGzDaY+nW4Aou3Yk/VaJCfd70ccybNnZQHcUrpkdPKK+bM5kxjfWRk9hAiYmPEl7Y3MJXfrOUN8ybwqiGOn69KLgi39/ezfVPbQTgmGnjADhy8miaGuoyBhRHpZwoV+5sZcOeNjJNAfCLpzclb6d+Xg+vDI5VJKCoS2QoghP1lQ9ET2oPrgiOy+Hu3qzvPXHS3tfWxb62Lrp6+/hJhmmhx4cBxcqdrckr/iMnjebBFbvYsKeNB17exRX3rohkoBL1MokMBcBvX9iWvJ3oxklkGyCY2h76szCtnT08vHI3/3rnMv7mxkXJDMfMCcE+n7p+YfLvbtak7BM2jUvJYh0/cwL3LN3BN1K6WXr7PDkS6Y7Fg2uTHly+i/YwmN91sJPuXue2hVtYvLmFv7t5cWQtmdQuj0UDFqp7ZRhoDhzpkchQDPX025v3tdPZ0xfbCA9QQDEkevuc/7p3BV+67UVOP3oKd37uzYPSTmedcETy9rzp4wY9x3tfeyStHT38cfXw6/ZorDeWXX4Ov//8/+Mb55/M2159BFv2tfM/D63mkz9/ntO+sYA//e4jfCGsA1i0aV9JU88e7urloRW7+NodS3nTfz3Me65+gqseXI0BX37nCfzyr9/ImMZ6PvuLF7IORytV6oqj7j5kmZn5x0xhTpq0rpnxubcdx3c//FqeXr+Xt373EZZuO8C3/+wUjpwUffwrpo/j/NOCLEUinXzT05vSzifwxJo9XLVgdc7ivoMd3ZxxxYO87wdP8FSW7rnXHDkRgH+6/aXIl2+iGO4LNy/OOl12akHZ6cdM5ZFVzcmhtADzpkX//zQ11DF/3hSuf2ojf/JfD3HRdc/xrftWRob9PbB8VzL1fOBwN5fcuIhZE0dzzSfmc+7Js7hryfbkF3xitEAiQ7F9/2FOmDmeax5fz7rmQ+xr6+L+ZTuSn/fA2SCfWLuHyWMaOWba4Cvpu5fuSI4MSp0JM1FQmDjZAMkaikTXy6pdrZHMW2rG4t/uXBbpbkk1ddzgYsln1u/jsjuX8YEfPhn5jBJFmBCsugowPsymXvrbl5LzLfzsj4OLflPnbblv2Q4Oh//HEwuEzUoJKAaOqkg8Z09vXxC4hN0OqbM9JrI/qcNpUyWO04lHTUxuOy48qV/7xIZIpiLxt/7Ayzs51NkTeZ3D3b08uqqZppT3s7+9m2/cvZzfv7idG57emNxeb9Euj9T/X3OnjqGpvo61zRkyFEM8/Xbi/0icGYr01S2St4Md3fz9zYt5ZFUznzjzGP79fSemnRDpNUdOYMLoBlo7eki3PMSbj5vO5LGN3LN0RySzUUkd3b24Rxf0geBkeaizh72HuthzqJM9h7rY29bJntauZN1HU0Mdp8yZxClzJvGJM48BgvH4S7cd4MUtB3hxy34WbtyXnCOhvs541cwJvG7uZE6dO4nXzZ3M8UdMyLh2Rk9vH7cv2soDy3fx5No9dPb0Ma6pnrccP4OzX3MEZ73qiMiXwv9ecBqfuO5Z/uWOZXzvz19XllnjpoxtTFanf/Lnz/P0+r1MH9fE1PFNTB03Krgd/j593Cj+3/HTOWpy+v7fVHV1xodOm83VD69Ne/9H5s9l+oRRfO6XL/CJM4/h3AxThP/d24/nd4u3cWN4VbzjQAfzr3iQj75hLl8999WYGWt3t/LpmxbS1tXLNY+v58I/OYZL3nIs3b3O/z60hje+YirvOHEm40c10N7ZS0d3H6t2tvLx/3uWt7/6CC4979UcP+ALzKx/wab/vKf/yvA7H34dTfV13PXidv7ljqX8z0dPTdvu1GD8DfOm8JsXtnLO/zzOn71+DtAfkLelBCVnHjuNP67Zw/YDHUwe28RT69bzu8XbeNMrpwHBMtjffWAln37rK8O/4U5+8pevZ8q4Jj5y+lzuXBL8Xb71hBnJE2kiQ9HR3cesiWNYtu0gn/vlC7z/1KP4zv2r+OSfzEueYOdOHcOWfYeT79vMeNurjkhmO/5/e2ceXtVd5vHPm50kkJCEFAgJhEKBFgq0lNa2jpbazbrQUbs4tZ1RZ0Zn6lJ1HJxxqbWPo1W7iU5btQ6WsbXahdIdu8C0hZKwJBDWkJ2QhYRsN8lNbu47f5xzb04gQWISuLnP+3me+5xzf2f7fe859z3v7/1tyQmxdPb00RMIsqOqhUU5aeHpy714nROvwxHihy/tRXFenqFqkpx059qrntlFbkYyq98o5Vb3Pwj9VR4v7TrCP75/djh9jftcPPTGwXBaYtyJeQpFYLaUNYdtWyjKdM5ZqYP2cOj0OCkhe+KNYAyGd8TgUAQl3vMb3L/hwEkbxs6fOpH3yptZmJNGgdvDZq7HOX3w9QPhfISq/0JO5AV56bx6XOPW3IwJ1BzrCu+z3W0j8d9vHSIjJYHMlITw0Nsx4nRz3lfXzkK3qi42RkiMi+GRjWXcuCw3fN7EMYpQhAZfm3uGenhAlDsUInIt8CAQC/xaVX801L4H6zu45dEtpE2IJz05nrQJ8aS5y/QJCSekT0yMo6Kpk8+vKaCyqZN7Vi4c8CceJC98cF4264tqB+02Fx8bw7XnTeWF4iNUHPXhDwTp8Afo8Afo9AeIiRFSEuJITox1lgmxpCTGkZIYS0JszElfmH1BpanDT32bn7q2burdT11rN/Xtfupbu6lv7w5PdpU9MZG8jGR6+oJhJ2Kohz89OZ4PeKIvXiYmxXPp2VlcenZWOK2hrZuiGsfBKKpp4YXiWp5wS1bJCbEszEljSW46i2ekszg3jZz0CYgI2yqPseqZXcyYPIFbludx5YJsludnhL3947l8bhZ3fugc7ttwgLf2N5CflUJ+Viqzp6S46ynMykw5wXkaDpOTE8LGtLShg9zJE1iSO5lmn59mXw+HGpzSbKikFhsjfHjRND5/eT6Lc9NPeu4bLpgxpEMBTrXCtm9fNaBEezz5bluKZ3Y44eec9AkcbunikY1ldPf08W/XzucLa7eTFB/Lr25fxlMF1Ty6qYzHN1eycHoaWyuaeWJrFYlxMayYnx1+OX/7+gX4A0FWv1nKNQ9s4qaL8rjzqrkDrr337mu5+4US1m7pLzWnJsbxwM1LOXtKKj/bcICluemDOkPeEtbNy/OobenioTdKWV9US1pyfDhC4R3gKpQ3gJe+8n721Lbx97/dyrOu9tlTUli7pYrndtTy2ctmAf3jAbzvbGdyttrWbsfxT4zjxV1HmOWpWjl3+iT+vLeefXXtHHV724SchQVTJzE7K5Xq5i4unDmZreXNNPt6uGJ+v0ORlZpIVXMnmSnOaJKKDhgJczBCL1NvqXeH+1L72OKzws75lQuyw07jF9Zuo707wLbKY1y5wPlfhl7k63bWMjfbedlMS0sK99z41aaysE0KlcpD2zt7AgOc4P872F+A6AkEyctIGdShCD1r0B+h8BYWUhJiw2NFhEhwp06Pi5FBe7x5Bw/zOgUhFkybxHvlzWEHCuDs7P6XayifV8zL5ml3RNqZmclUNnUOqI65aNZkCiqO0eEPcPHsTDYdaCR7YmJ4LJDWrl5au3qZlZkcdgCX5k1mW+UxPvLzt3ln1YrwuXrdUVBv+81Wpqc71wjPKDvKjTL317eTl5FMcsKZe61HrUMhIrHAL4CrgBqgQESeV9U9g+2fEBdDIBjkUGMHrV29tHT1nrQbZ2yMIDgtvB//3MUDDNpQfPCcKawvqg0PvX08158/jScLqvngT9/6i+fyEhcjYQfDu+zqDdLQ1k1Du/8Ezz5GnHDi1ElJ5GUmszw/I9wKu7LJR1VzJymJCczNnkhWagKZqQlkpSaSmZpIZkoCUyYmMjk5YUCI9FTInpTEVecmcZUbhQkGlYomH0U1LRRVt7KzuoX/eaciXH+blZrA4hnppLot6e+/aQkXDTGl+PHcccUcpkxMZNfhVsobfbxTejRsSEJMT0tiVtZAJ+NUSU9OoLHdz5ef2EGTz8/1i6bzsxsXn7BfZ0+A2pYu/lBQzZNbq1lfVBs2WstmTh7kzI4zcOsleSe0t/FyKs7QHSvmhB2K2943k/962RkRcM3mSv68t4EjrV2s/dzFYcfvjhVzeej1g6x3x0V58OYlbK88xou76sL13knxsfz9Zfl8alkuD71+kLVbKlm38/CAqd4T4mL4zkfOZUdVCyW1bQMGZvqXK+ZQUHmMu9bv4cmC6nB6fKzQ26cnRDy+dvU8fD194W6zoRe9tyV/qAFniHOnT+LpL17K7b/dSlVTJzcty3UaXPoDJzhqsTHCJy6cwc/fKKW+tZtV180nIyWBRTn9Tt95njB6aMTLz1+ez6/fLgdxHJaNBxo5d9qk8NDPF+dnhAshmakJVDV3cs3Cqfz+vSp2H24Lv2BnT0kZdC6QUGjfO7ro3OxUDjZ0DCjtXzGv36EIzS3T0xcM3y/vf/SnbjuMWy+ZyU9e3U9iXAwpiXHOCJeq4QjENedN5X/eraCiqXPQqNrfLs3hyYJqDrd0sTg3naLqlgEjft6wNIfVb5bS2O4PP6feqMW1C6fx9PYafP7+tJVLp/NUYQ15mcmD/h6LZ6RRVNOKPxBkxuQJbnuQ/uMXTHOeG2/VxpwpJ5bWL5uTGbYDK5fk8ODrB6lr7SY1MY4Of4CPLp5OQcUx6tv83H5pBpsONHJRfgYvuo01L5mdwZayZpp8PeGC3FRPO5rrHthEm3sfzp6SSkltG4dbujjc0sXUSUnhKFDZUR8+f4DkhFhEhB1Vx9hX1868qROZd9ZEUhLj2FrezKObyshJT2JmZgqzspKZmZnCjMkTwoUpVScidqDuzPbwgCh2KIDlQKmqlgGIyJPAx4FBHYqZmcn88QuXDkjr7u2jpdPxRls6e8KORltXLy2dvfT0Bbn14pnkDVJXOhgr5jslBm+J3cvlc7K4/6bF9AY0HH1ITYwjJTGOoCo+fx++ngCd4WUAnztsrc/vLnv6nHR/H5OS4pibncVZkxzH4Sz3MzUtiazUxCGrF04nMTHC7CmpzJ6Syg1LnZB2TyDIvro2iqpb2FndSlFNS3jEOW/vmFM59y3L87jFk+bzB6ho8lF+1Ed5o7MsO+pjfVFt2AgAp+QoXThzMut2Hqa4poX5Uydx9XmDV1UlJ8QxJ3si/3n9uXz5yrk8VVjDY+7Lse8k7S7uWbno1ISehNlTUpkyMZHGdj83XeS8VPOzUlgxP5vfvF3ON6+dx6Vz+p/HOdmpPHTLUr585Rx2VrfyscXT+fiSHL770fN4r7yJLYeaWOEp+d71sfO4/dJZ3PvKvvALLERiXCwP3ryUD923kZkZ/f+R2BjhsduX8bvNldztNpYTgSmpidS6hj0nfcKAOux/v3Y+hZXHaO3sCTt93snD4mNjyEmfMCBkn5uRzLNfvIyDDe3kZ6WEnanrz5/Gi8VHBnTR/KTrUNS2dJObkcwPVi4coOX9c7M4f0Ya37xmPqueKabmWBdfv3oeC6ZNYmZmMiJOz4grF/RHJZLiY3ntzr9hUlI8TR097Khq4SOLpvF7dxyEUAQiyRNl8z4Ngz2Dq66bz+fWFLLnSFv4BZue3P+fuGlZLn8orA5rHIo52alcenYm++ra+fb1C/jaU0UcbGhn6iTHebhg5uSwjlDJ+sKZk8NtH/7hsnyeLKhm75E27vzQORRVtwzoWnrDBY5DsetwK8vzHUfT2+D8w4um8vT2Gg40tIejIbdeMpOnCmsoa/Sxcsl0nttZO6AX1devnsdtj22luKaF2VNSKa5pHdCOJNR253BLVziC4XW6r1s4lZd31w2Itq5c6jgURTUtLJvl9MTL9Tyrl8x2CoreqcC/dtU8bnxkM8U1reEeSd4uxrOyUiiuaaXT38einDRKatv49MV5/P69Kurauol3HcWHNx7i4Y2HiIsR0pPjTxiaPeTggNPz6fjhxr3VXqH/+JmqLg8TakwWbR/gkzjVHKHvnwFWH7fPPwGFQGFeXp6eDvy9faflOtFGa1ePHqxvH7PzB4NBberwa2FFkz63o0aP+fxjdi1V1d5An75WUqe7alrG9Dqqqh3dvbqj6piqqhaUN2l5Y4cGg0Etc5ejRUF5k35v3W7t6O4dkN7U4dfewODPfX1bl/7izYN6tL1bq5p8+rvNFaqqWnK4VaubfQP2be/u1aomJ+2RjaUn/Ha9gT7t6xtaz+ObK3Tj/gYNBoO6q6blhH2f3V6jZY0dA9JeKq7VZ7ZXD0grrm7RH7+894TfrtMfUFXVd0uP6q82HRqwrSfQpxtK6lRVdd3Ow/qHgioNBoP6k1f2aeVRn+6pbdW715doMBjUPxVW68b9DdrVE9DvPrdLW3w9uvnQUf3lm6UaDAb1/g37dVtls9a3dun31u1Wf2+f7qw6ppsPHdWunoB+b91uPVjfpgXlTfrd53aFz/nmvnqtb+3S/3imWBvanN/7Lff3+Nmr+7SwokmP+fz6g/Ul2hPo05eKa/Wpgirt6wvqj1/eq2WNHbqntlXvecHJ5+ObK3RDSZ129QT03lf2aouvRwsrmvSRjaWqqrr6jYPhc971vJPPP++p0z8VVmugL6j3vrJXDzW0a3ljh977ivN7/vbtMn2xuFbbunr0O8/t0vq2Lt1e2ayPbjwU/r3eLT2qzR1+/e5zu7S7N6CvldTp79+r1L6+oN7zQonur2vT8sYO/ZF7j/5YWK2vldRpa1ePrnq6SOtau3TfkTZ9qqBKVVUf2HBA3y09qo3t3brq6SLt6gnon/fUhbXf99p+LT0un4+9Xabriw5rMBjUNe+Wq8/fq9srm/WXb5aqv7dPH36rVHdWHdOO7l6977X92hPo09f31umz22s0GAzq3etL9J4XSvS/3yrVH728V7/1TLF+cW2hPvxWqb66+4iufuOgfv/5Er3zyR36wIYDGgwG9Wh7txZWNOvT26r1gQ0H9DvP7dJ/WbtNr7l/o379qZ36j2sK/ip7AhTqKL13Rc/gmAFjiYh8CrhGVT/vfv8MsFxVvzTY/suWLdPCwsLTmUXDMAzDOKOIyDZVXTYa54rmbqM1QK7n+wzAJswwDMMwjDEgmh2KAmCuiOSLSAJwM/D8Gc6TYRiGYUQlUdsoU1UDInIH8CpOt9HHVLXkDGfLMAzDMKKSqHUoAFT1JeClM50PwzAMw4h2ornKwzAMwzCM04Q5FIZhGIZhjBhzKAzDMAzDGDHmUBiGYRiGMWLMoTAMwzAMY8SYQ2EYhmEYxogxh8IwDMMwjBFjDoVhGIZhGCPGHArDMAzDMEZM1M42OlxEpBGoPE2XywKOnqZrnQ6iTQ9En6Zo0wPRpyna9ED0aYo2PQDzVHXiaJwoqofeHg6qOuV0XUtECkdruthIINr0QPRpijY9EH2aok0PRJ+maNMDjqbROpdVeRiGYRiGMWLMoTAMwzAMY8SYQ3FmePRMZ2CUiTY9EH2aok0PRJ+maNMD0acp2vTAKGqyRpmGYRiGYYwYi1AYhmEYhjFizKEwDMMwDGPEmEMxCojIYyLSICK7PWlLRGSLiOwUkUIRWe7Zdr6IbBaREhHZJSJJbvqF7vdSEXlIRORM6HHzcsqaRCReRNa4ed8rIt/yHBMRmobQs9i9D7tEZL2ITPJs+5ab5/0ico0nPSL0uHk5ZU0icpWIbHPTt4nICs8xEaFpuPfI3Z4nIh0i8g1PWkTocfMy3Ocuom3DMJ+58WAXckXkTTd/JSLyFTc9Q0Q2iMhBdznZc0xE24bhahpV26Cq9hnhB/gb4AJgtyftNeA6d/3DwFvuehxQDCx2v2cCse76VuB9gAAvh44fB5o+DTzpricDFcCsSNI0hJ4C4APu+meBH7jr5wJFQCKQDxwaR/doKE1Lgenu+kLgsOeYiNA0HD2e7U8DfwS+EWl6/op7FPG2YZh6xoNdmAZc4K5PBA64//97gVVu+irgx+56xNuGv0LTqNkGi1CMAqq6CWg+PhkIlTzSgFp3/WqgWFWL3GObVLVPRKYBk1R1szp38nfAyrHP/eAMU5MCKSISB0wAeoC2SNI0hJ55wCZ3fQPwCXf94ziG0K+q5UApsDyS9MDwNKnqDlUN3a8SIElEEiNJ0zDvESKyEijD0RNKixg9MGxNEW8bhqlnPNiFI6q63V1vB/YCOTg2YI272xpP/iLeNgxX02jaBnMoxo6vAj8RkWrgp0Ao3HcOoCLyqohsF5Fvuuk5QI3n+Bo3LZIYStOfAB9wBKgCfqqqzUS+pt3Ax9z1TwG57noOUO3ZL5TvSNcDQ2vy8glgh6r6iXxNg+oRkRTg34HvH7d/pOuBoe/ReLUNQ+kZV3ZBRGbhlNbfA85S1SPgvKCBbHe3cWUbTlGTlxHZBnMoxo4vAneqai5wJ/AbNz0OuBz4O3d5g4hciRNSOp5I69M7lKblQB8wHScM+HURmU3ka/os8K8isg0nNNjjpg+V70jXA0NrAkBEzgN+DPxzKGmQc0SSpqH0fB+4X1U7jts/0vXA0JrGq20YSs+4sQsikopTffZVVW072a6DpEWkbRiGptD+I7YNNpfH2HE78BV3/Y/Ar931GmCjqh4FEJGXcOok1wIzPMfPoL9KIVIYStOngVdUtRdoEJF3gGXA/xHBmlR1H06YGRE5B7je3VTDwJJ9KN81RLAeOKkmRGQG8Cxwm6oecpMjWtNJ9FwMfFJE7gXSgaCIdOMY0IjVA3/xuRt3tuEkesaFXRCReJzn5n9V9Rk3uV5EpqnqETf03+CmjwvbMExNo2YbLEIxdtQCH3DXVwAH3fVXgfNFJNmtW/wAsMcNQbWLyCVuS9rbgHWnO9N/gaE0VQErxCEFuATYF+maRCTbXcYA3wYedjc9D9zs1iPmA3OBrZGuB4bWJCLpwIvAt1T1ndD+ka5pKD2q+n5VnaWqs4AHgB+q6upI1wMnfe7GpW04iZ6Itwvu9X8D7FXV+zybnscpQOEu13nSI9o2DFfTqNqGkbYotY8CPIFTT9iL49V9DidkuQ2nRfB7wIWe/W/FafyyG7jXk77MTTsErMYdyTTSNQGpOBGLEmAP8G+RpmkIPV/BaQF9APiRN2/Af7p53o+nZXOk6BmuJhxD7wN2ej7ZkaRpuPfIc9xdDOzlERF6/srnLqJtwzCfufFgFy7HCeMXe/4XH8bpYfM6TqHpdSDDc0xE24bhahpN22BDbxuGYRiGMWKsysMwDMMwjBFjDoVhGIZhGCPGHArDMAzDMEaMORSGYRiGYYwYcygMwzAMwxgx5lAYhjEmuOMPvC0i13nSbhSRV85kvgzDGBus26hhGGOGiCzEGYtgKRCL08f9Wu0fjW8454pV1b5RzqJhGKOEORSGYYwp7vDYPiDFXc4EFuEM/X+Xqq5zJzF63N3aEY6cAAABLUlEQVQH4A5VfVdEPgh8D2cwpSWqeu7pzb1hGKeKORSGYYwp7rDL23EmjXoBKFHVte6Qv1txohcKBFW1W0TmAk+o6jLXoXgRWKjOdNGGYUQoNjmYYRhjiqr6ROQPQAdwI/BREfmGuzkJyMOZJ2a1iCzBmaHyHM8ptpozYRiRjzkUhmGcDoLuR4BPqOp+70YRuQuoBxbjNBbv9mz2naY8GoYxAqyXh2EYp5NXgS+5sxciIkvd9DTgiKoGgc/gNOA0DGMcYQ6FYRinkx8A8UCxiOx2vwP8ErhdRLbgVHdYVMIwxhnWKNMwDMMwjBFjEQrDMAzDMEaMORSGYRiGYYwYcygMwzAMwxgx5lAYhmEYhjFizKEwDMMwDGPEmENhGIZhGMaIMYfCMAzDMIwR8/9T0Gfq70GGZAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.pyplot import figure\n",
    "\n",
    "SortedData1 = selected.loc[ ['Department of Natural Resources'] , : ]\n",
    "x = SortedData1['Year Constructed']\n",
    "y = SortedData1['Square Footage']\n",
    "\n",
    "fig= plt.figure(figsize=(8, 6))\n",
    "ax= plt.axes()\n",
    "fig.suptitle('Department of Natural Resources')\n",
    "ax.set_ylabel('Square Footage')\n",
    "ax.set_xlabel('Year')\n",
    "plt.xlim(1850, 2020)\n",
    "ax.plot(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18b0bba2648>]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "SortedData2 = selected.loc[ ['Department of Corrections'] , : ]\n",
    "x = SortedData2['Year Constructed']\n",
    "y = SortedData2['Square Footage']\n",
    "\n",
    "fig= plt.figure(figsize=(8, 6))\n",
    "ax= plt.axes()\n",
    "fig.suptitle('Department of Corrections')\n",
    "ax.set_ylabel('Square Footage')\n",
    "ax.set_xlabel('Year')\n",
    "plt.xlim(1850, 2020)\n",
    "ax.plot(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18b0bbc7048>]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "SortedData3 = selected.loc[ ['Department of Transportation'] , : ]\n",
    "x = SortedData3['Year Constructed']\n",
    "y = SortedData3['Square Footage']\n",
    "\n",
    "fig= plt.figure(figsize=(8, 6))\n",
    "ax= plt.axes()\n",
    "fig.suptitle('Department of Transportation')\n",
    "ax.set_ylabel('Square Footage')\n",
    "ax.set_xlabel('Year')\n",
    "plt.xlim(1920, 2020)\n",
    "ax.plot(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18b0bc36348>]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "SortedData4 = selected.loc[ ['Department of Human Services'] , : ]\n",
    "x = SortedData4['Year Constructed']\n",
    "y = SortedData4['Square Footage']\n",
    "\n",
    "fig= plt.figure(figsize=(8, 6))\n",
    "ax= plt.axes()\n",
    "fig.suptitle('Department of Human Services')\n",
    "ax.set_ylabel('Square Footage')\n",
    "ax.set_xlabel('Year')\n",
    "plt.xlim(1850, 2020)\n",
    "ax.plot(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x18b0bccf348>]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.pyplot import figure\n",
    "\n",
    "SortedData5 = selected.loc[ ['University of Illinois'] , : ]\n",
    "x = SortedData5['Year Constructed']\n",
    "y = SortedData5['Square Footage']\n",
    "\n",
    "fig= plt.figure(figsize=(8, 6))\n",
    "ax= plt.axes()\n",
    "fig.suptitle('University of Illinois')\n",
    "ax.set_ylabel('Square Footage')\n",
    "ax.set_xlabel('Year')\n",
    "plt.xlim(1850, 2020)\n",
    "ax.plot(x, y)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Observations\n",
    "This was the most challenging visualization for me as I was not sure how to use the information we have to represent it. For this poart I first evasluated the top 5 most common agencies that featured for most number of buildings in the dataframe. After that I individually plotted data for each of the 5 agencies for the given period in dataset. I am comapring each Agency and how many square foots of space it added every year and plotting this info in 5 seperate graphs. I was facing a lot of difficulties in organizing this information according to the criterea i needed but after doing some research and practicing multiple code types I figured it out.\n",
    "I am also not sure about the methodology i have used to drop the entries with zero congress district, zero marked construction year or zero square footage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}