gupta-tanya-assignment6.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import usual things\n",
    "import pandas as pd\n",
    "import bqplot\n",
    "import numpy as np\n",
    "import traitlets\n",
    "import ipywidgets\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import the data file\n",
    "building = pd.read_csv('building_inventory.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "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>...</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",
       "      <td>0</td>\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>...</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",
       "      <td>1</td>\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>...</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",
       "      <td>2</td>\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>...</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",
       "      <td>3</td>\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>...</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",
       "      <td>4</td>\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>...</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",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8857</td>\n",
       "      <td>Department of Transportation</td>\n",
       "      <td>Belvidere Maintenance Storage Facility - Boone...</td>\n",
       "      <td>9797 Illinois Rte. 76</td>\n",
       "      <td>Belvidere</td>\n",
       "      <td>61008</td>\n",
       "      <td>Boone</td>\n",
       "      <td>16</td>\n",
       "      <td>Adam Kinzinger</td>\n",
       "      <td>69</td>\n",
       "      <td>Sosnowski Joe</td>\n",
       "      <td>...</td>\n",
       "      <td>In Use</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>432</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Storage</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8858</td>\n",
       "      <td>Department of Transportation</td>\n",
       "      <td>Belvidere Maintenance Storage Facility - Boone...</td>\n",
       "      <td>9797 Illinois Rte 76</td>\n",
       "      <td>Belvidere</td>\n",
       "      <td>61008</td>\n",
       "      <td>Boone</td>\n",
       "      <td>16</td>\n",
       "      <td>Adam Kinzinger</td>\n",
       "      <td>69</td>\n",
       "      <td>Sosnowski Joe</td>\n",
       "      <td>...</td>\n",
       "      <td>In Use</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>330</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Storage</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8859</td>\n",
       "      <td>Department of Transportation</td>\n",
       "      <td>Quincy Maintenance Storage Facility</td>\n",
       "      <td>800 Koch's Lane</td>\n",
       "      <td>Quincy</td>\n",
       "      <td>62305</td>\n",
       "      <td>Adams</td>\n",
       "      <td>18</td>\n",
       "      <td>Darin M. LaHood</td>\n",
       "      <td>94</td>\n",
       "      <td>Frese Randy E.</td>\n",
       "      <td>...</td>\n",
       "      <td>In Use</td>\n",
       "      <td>0</td>\n",
       "      <td>1987</td>\n",
       "      <td>130</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Storage</td>\n",
       "      <td>High Hazard</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8860</td>\n",
       "      <td>Illinois Community College Board</td>\n",
       "      <td>Illinois Valley Community College - Oglesby</td>\n",
       "      <td>815 North Orlando Smith Avenue</td>\n",
       "      <td>Oglesby</td>\n",
       "      <td>61348</td>\n",
       "      <td>LaSalle</td>\n",
       "      <td>16</td>\n",
       "      <td>Adam Kinzinger</td>\n",
       "      <td>76</td>\n",
       "      <td>Long Jerry Lee</td>\n",
       "      <td>...</td>\n",
       "      <td>In Use</td>\n",
       "      <td>1971</td>\n",
       "      <td>1971</td>\n",
       "      <td>49552</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Education</td>\n",
       "      <td>Education</td>\n",
       "      <td>Not provided</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8861</td>\n",
       "      <td>Department of Military Affairs</td>\n",
       "      <td>Peoria Army Aviation Support Facility</td>\n",
       "      <td>2323 S. Airport Rd</td>\n",
       "      <td>Peoria</td>\n",
       "      <td>61607</td>\n",
       "      <td>Peoria</td>\n",
       "      <td>17</td>\n",
       "      <td>Cheri Bustos</td>\n",
       "      <td>92</td>\n",
       "      <td>Gordon-Booth Jehan</td>\n",
       "      <td>...</td>\n",
       "      <td>In Progress</td>\n",
       "      <td>0</td>\n",
       "      <td>2017</td>\n",
       "      <td>288</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Utiility &amp; Miscellan</td>\n",
       "      <td>Utiility &amp; Miscellan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8862 rows × 22 columns</p>\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",
       "8857      Department of Transportation   \n",
       "8858      Department of Transportation   \n",
       "8859      Department of Transportation   \n",
       "8860  Illinois Community College Board   \n",
       "8861    Department of Military Affairs   \n",
       "\n",
       "                                          Location Name  \\\n",
       "0       Anderson Lake Conservation Area - Fulton County   \n",
       "1       Anderson Lake Conservation Area - Fulton County   \n",
       "2       Anderson Lake Conservation Area - Fulton County   \n",
       "3       Anderson Lake Conservation Area - Fulton County   \n",
       "4       Anderson Lake Conservation Area - Fulton County   \n",
       "...                                                 ...   \n",
       "8857  Belvidere Maintenance Storage Facility - Boone...   \n",
       "8858  Belvidere Maintenance Storage Facility - Boone...   \n",
       "8859                Quincy Maintenance Storage Facility   \n",
       "8860        Illinois Valley Community College - Oglesby   \n",
       "8861              Peoria Army Aviation Support Facility   \n",
       "\n",
       "                             Address       City  Zip code   County  \\\n",
       "0                 Anderson Lake C.a.    Astoria     61501   Fulton   \n",
       "1                 Anderson Lake C.a.    Astoria     61501   Fulton   \n",
       "2                 Anderson Lake C.a.    Astoria     61501   Fulton   \n",
       "3                 Anderson Lake C.a.    Astoria     61501   Fulton   \n",
       "4                 Anderson Lake C.a.    Astoria     61501   Fulton   \n",
       "...                              ...        ...       ...      ...   \n",
       "8857           9797 Illinois Rte. 76  Belvidere     61008    Boone   \n",
       "8858            9797 Illinois Rte 76  Belvidere     61008    Boone   \n",
       "8859                 800 Koch's Lane     Quincy     62305    Adams   \n",
       "8860  815 North Orlando Smith Avenue    Oglesby     61348  LaSalle   \n",
       "8861              2323 S. Airport Rd     Peoria     61607   Peoria   \n",
       "\n",
       "      Congress Dist Congressional Full Name  Rep Dist       Rep Full Name  \\\n",
       "0                17            Cheri Bustos        93   Hammond Norine K.   \n",
       "1                17            Cheri Bustos        93   Hammond Norine K.   \n",
       "2                17            Cheri Bustos        93   Hammond Norine K.   \n",
       "3                17            Cheri Bustos        93   Hammond Norine K.   \n",
       "4                17            Cheri Bustos        93   Hammond Norine K.   \n",
       "...             ...                     ...       ...                 ...   \n",
       "8857             16          Adam Kinzinger        69       Sosnowski Joe   \n",
       "8858             16          Adam Kinzinger        69       Sosnowski Joe   \n",
       "8859             18         Darin M. LaHood        94      Frese Randy E.   \n",
       "8860             16          Adam Kinzinger        76      Long Jerry Lee   \n",
       "8861             17            Cheri Bustos        92  Gordon-Booth Jehan   \n",
       "\n",
       "      ...  Bldg Status Year Acquired Year Constructed  Square Footage  \\\n",
       "0     ...       In Use          1975             1975             144   \n",
       "1     ...       In Use          2004             2004             144   \n",
       "2     ...       In Use          2004             2004             144   \n",
       "3     ...       In Use          2004             2004             144   \n",
       "4     ...       In Use          2004             2004             144   \n",
       "...   ...          ...           ...              ...             ...   \n",
       "8857  ...       In Use             0                0             432   \n",
       "8858  ...       In Use             0                0             330   \n",
       "8859  ...       In Use             0             1987             130   \n",
       "8860  ...       In Use          1971             1971           49552   \n",
       "8861  ...  In Progress             0             2017             288   \n",
       "\n",
       "      Total Floors  Floors Above Grade  Floors Below Grade  \\\n",
       "0                1                   1                   0   \n",
       "1                1                   1                   0   \n",
       "2                1                   1                   0   \n",
       "3                1                   1                   0   \n",
       "4                1                   1                   0   \n",
       "...            ...                 ...                 ...   \n",
       "8857             1                   0                   0   \n",
       "8858             1                   0                   0   \n",
       "8859             1                   0                   0   \n",
       "8860             1                   1                   0   \n",
       "8861             1                   0                   0   \n",
       "\n",
       "         Usage Description   Usage Description 2 Usage Description 3  \n",
       "0                  Unusual               Unusual        Not provided  \n",
       "1                  Unusual               Unusual        Not provided  \n",
       "2                  Unusual               Unusual        Not provided  \n",
       "3                  Unusual               Unusual        Not provided  \n",
       "4                  Unusual               Unusual        Not provided  \n",
       "...                    ...                   ...                 ...  \n",
       "8857               Storage                   NaN                 NaN  \n",
       "8858               Storage                   NaN                 NaN  \n",
       "8859               Storage           High Hazard                 NaN  \n",
       "8860             Education             Education        Not provided  \n",
       "8861  Utiility & Miscellan  Utiility & Miscellan                 NaN  \n",
       "\n",
       "[8862 rows x 22 columns]"
      ]
     },
     "execution_count": 289,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "building"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " [17, 'Department of Corrections', 1518546],\n",
       " [17, 'Department of Human Services', 247839],\n",
       " [17, 'Department of Transportation', 430972],\n",
       " [17, 'Department of State Police', 50974],\n",
       " [17, 'Department of Military Affairs', 386238],\n",
       " [17, 'Department of Agriculture', 29350],\n",
       " [17, 'Governors State University', 0],\n",
       " [17, 'Department of Central Management Services', 151963],\n",
       " [17, 'Illinois State University', 0],\n",
       " [17, 'Historic Preservation Agency', 112777],\n",
       " [17, 'Department of Juvenile Justice', 227480],\n",
       " [17, 'Southern Illinois University', 0],\n",
       " [17, 'Illinois Medical District Commission', 0],\n",
       " [17, 'University of Illinois', 315626],\n",
       " [17, \"Department of Veterans' Affairs\", 0],\n",
       " [17, 'Chicago State University', 0],\n",
       " [17, 'Northern Illinois University', 0],\n",
       " [17, 'Office of the Secretary of State', 0],\n",
       " [17, 'Illinois Emergency Management Agency', 0],\n",
       " [17, 'Western Illinois University', 385896],\n",
       " [17, 'Eastern Illinois University', 0],\n",
       " [17, 'Northeastern Illinois University', 0],\n",
       " [17, 'Illinois Community College Board', 26700],\n",
       " [17, 'Illinois Board of Higher Education', 0],\n",
       " [17, 'IL State Board of Education', 0],\n",
       " [17, 'Department of Revenue', 0],\n",
       " [17, \"Governor's Office\", 0],\n",
       " [17, 'Office of the Attorney General', 60500],\n",
       " [17, 'Appellate Court / Fourth District', 0],\n",
       " [17, 'Department of Public Health', 0],\n",
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       " [17, 'Appellate Court / Third District', 0],\n",
       " [17, 'Appellate Court / Fifth District', 0],\n",
       " [17, 'Appellate Court / Second District', 0],\n",
       " [15, 'Department of Natural Resources', 574690],\n",
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       " [15, 'Department of Human Services', 394598],\n",
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       " [15, 'Department of Juvenile Justice', 209238],\n",
       " [15, 'Southern Illinois University', 0],\n",
       " [15, 'Illinois Medical District Commission', 0],\n",
       " [15, 'University of Illinois', 0],\n",
       " [15, \"Department of Veterans' Affairs\", 0],\n",
       " [15, 'Chicago State University', 0],\n",
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       " [15, 'Eastern Illinois University', 1164674],\n",
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       " [16, 'Department of Military Affairs', 342638],\n",
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       " [1, 'Office of the Secretary of State', 0],\n",
       " [1, 'Illinois Emergency Management Agency', 0],\n",
       " [1, 'Western Illinois University', 0],\n",
       " [1, 'Eastern Illinois University', 0],\n",
       " [1, 'Northeastern Illinois University', 0],\n",
       " [1, 'Illinois Community College Board', 0],\n",
       " [1, 'Illinois Board of Higher Education', 0],\n",
       " [1, 'IL State Board of Education', 0],\n",
       " [1, 'Department of Revenue', 0],\n",
       " [1, \"Governor's Office\", 0],\n",
       " [1, 'Office of the Attorney General', 0],\n",
       " [1, 'Appellate Court / Fourth District', 0],\n",
       " [1, 'Department of Public Health', 0],\n",
       " [1, 'Illinois Courts', 0],\n",
       " [1, 'Appellate Court / Third District', 0],\n",
       " [1, 'Appellate Court / Fifth District', 0],\n",
       " [1, 'Appellate Court / Second District', 0],\n",
       " [10, 'Department of Natural Resources', 200392],\n",
       " [10, 'Department of Corrections', 0],\n",
       " [10, 'Department of Human Services', 234642],\n",
       " [10, 'Department of Transportation', 3270],\n",
       " [10, 'Department of State Police', 6246],\n",
       " [10, 'Department of Military Affairs', 40852],\n",
       " [10, 'Department of Agriculture', 0],\n",
       " [10, 'Governors State University', 0],\n",
       " [10, 'Department of Central Management Services', 443865],\n",
       " [10, 'Illinois State University', 0],\n",
       " [10, 'Historic Preservation Agency', 0],\n",
       " [10, 'Department of Juvenile Justice', 0],\n",
       " [10, 'Southern Illinois University', 0],\n",
       " [10, 'Illinois Medical District Commission', 0],\n",
       " [10, 'University of Illinois', 0],\n",
       " [10, \"Department of Veterans' Affairs\", 0],\n",
       " [10, 'Chicago State University', 0],\n",
       " [10, 'Northern Illinois University', 0],\n",
       " [10, 'Office of the Secretary of State', 0],\n",
       " [10, 'Illinois Emergency Management Agency', 0],\n",
       " [10, 'Western Illinois University', 0],\n",
       " [10, 'Eastern Illinois University', 0],\n",
       " [10, 'Northeastern Illinois University', 0],\n",
       " [10, 'Illinois Community College Board', 0],\n",
       " [10, 'Illinois Board of Higher Education', 0],\n",
       " [10, 'IL State Board of Education', 0],\n",
       " [10, 'Department of Revenue', 0],\n",
       " [10, \"Governor's Office\", 0],\n",
       " [10, 'Office of the Attorney General', 0],\n",
       " [10, 'Appellate Court / Fourth District', 0],\n",
       " [10, 'Department of Public Health', 0],\n",
       " [10, 'Illinois Courts', 0],\n",
       " [10, 'Appellate Court / Third District', 0],\n",
       " [10, 'Appellate Court / Fifth District', 0],\n",
       " [10, 'Appellate Court / Second District', 0],\n",
       " [5, 'Department of Natural Resources', 0],\n",
       " [5, 'Department of Corrections', 0],\n",
       " [5, 'Department of Human Services', 362890],\n",
       " [5, 'Department of Transportation', 112120],\n",
       " [5, 'Department of State Police', 0],\n",
       " [5, 'Department of Military Affairs', 0],\n",
       " [5, 'Department of Agriculture', 0],\n",
       " [5, 'Governors State University', 0],\n",
       " [5, 'Department of Central Management Services', 9932],\n",
       " [5, 'Illinois State University', 0],\n",
       " [5, 'Historic Preservation Agency', 0],\n",
       " [5, 'Department of Juvenile Justice', 0],\n",
       " [5, 'Southern Illinois University', 0],\n",
       " [5, 'Illinois Medical District Commission', 0],\n",
       " [5, 'University of Illinois', 0],\n",
       " [5, \"Department of Veterans' Affairs\", 185525],\n",
       " [5, 'Chicago State University', 0],\n",
       " [5, 'Northern Illinois University', 0],\n",
       " [5, 'Office of the Secretary of State', 28452],\n",
       " [5, 'Illinois Emergency Management Agency', 0],\n",
       " [5, 'Western Illinois University', 0],\n",
       " [5, 'Eastern Illinois University', 0],\n",
       " [5, 'Northeastern Illinois University', 1110103],\n",
       " [5, 'Illinois Community College Board', 0],\n",
       " [5, 'Illinois Board of Higher Education', 0],\n",
       " [5, 'IL State Board of Education', 0],\n",
       " [5, 'Department of Revenue', 0],\n",
       " [5, \"Governor's Office\", 0],\n",
       " [5, 'Office of the Attorney General', 0],\n",
       " [5, 'Appellate Court / Fourth District', 0],\n",
       " [5, 'Department of Public Health', 0],\n",
       " [5, 'Illinois Courts', 0],\n",
       " [5, 'Appellate Court / Third District', 0],\n",
       " [5, 'Appellate Court / Fifth District', 0],\n",
       " [5, 'Appellate Court / Second District', 0],\n",
       " [4, 'Department of Natural Resources', 0],\n",
       " [4, 'Department of Corrections', 0],\n",
       " [4, 'Department of Human Services', 0],\n",
       " [4, 'Department of Transportation', 34982],\n",
       " [4, 'Department of State Police', 0],\n",
       " [4, 'Department of Military Affairs', 224959],\n",
       " [4, 'Department of Agriculture', 0],\n",
       " [4, 'Governors State University', 0],\n",
       " [4, 'Department of Central Management Services', 0],\n",
       " [4, 'Illinois State University', 0],\n",
       " [4, 'Historic Preservation Agency', 57800],\n",
       " [4, 'Department of Juvenile Justice', 0],\n",
       " [4, 'Southern Illinois University', 0],\n",
       " [4, 'Illinois Medical District Commission', 0],\n",
       " [4, 'University of Illinois', 0],\n",
       " [4, \"Department of Veterans' Affairs\", 0],\n",
       " [4, 'Chicago State University', 0],\n",
       " [4, 'Northern Illinois University', 0],\n",
       " [4, 'Office of the Secretary of State', 0],\n",
       " [4, 'Illinois Emergency Management Agency', 0],\n",
       " [4, 'Western Illinois University', 0],\n",
       " [4, 'Eastern Illinois University', 0],\n",
       " [4, 'Northeastern Illinois University', 0],\n",
       " [4, 'Illinois Community College Board', 0],\n",
       " [4, 'Illinois Board of Higher Education', 0],\n",
       " [4, 'IL State Board of Education', 0],\n",
       " [4, 'Department of Revenue', 0],\n",
       " [4, \"Governor's Office\", 0],\n",
       " [4, 'Office of the Attorney General', 0],\n",
       " [4, 'Appellate Court / Fourth District', 0],\n",
       " [4, 'Department of Public Health', 0],\n",
       " [4, 'Illinois Courts', 0],\n",
       " [4, 'Appellate Court / Third District', 0],\n",
       " [4, 'Appellate Court / Fifth District', 0],\n",
       " [4, 'Appellate Court / Second District', 0]]"
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#data transofrmation\n",
    "list_ = []\n",
    "\n",
    "for i in range(len(building['Congress Dist'].unique())):\n",
    "    df = building.loc[building['Congress Dist'] == building['Congress Dist'].unique()[i]]\n",
    "    for j in range(len(building['Agency Name'].unique())):\n",
    "        sum_ = df.loc[df['Agency Name'] == building['Agency Name'].unique()[j], 'Square Footage'].sum()\n",
    "        list_.append([building['Congress Dist'].unique()[i],building['Agency Name'].unique()[j],sum_])\n",
    "list_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "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",
       "    .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>Congress Dist</th>\n",
       "      <th>Agency Name</th>\n",
       "      <th>Square Footage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>Department of Natural Resources</td>\n",
       "      <td>402882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>Department of Corrections</td>\n",
       "      <td>1518546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>Department of Human Services</td>\n",
       "      <td>247839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>Department of Transportation</td>\n",
       "      <td>430972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>Department of State Police</td>\n",
       "      <td>50974</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>660</td>\n",
       "      <td>4</td>\n",
       "      <td>Department of Public Health</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>661</td>\n",
       "      <td>4</td>\n",
       "      <td>Illinois Courts</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>662</td>\n",
       "      <td>4</td>\n",
       "      <td>Appellate Court / Third District</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>663</td>\n",
       "      <td>4</td>\n",
       "      <td>Appellate Court / Fifth District</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>664</td>\n",
       "      <td>4</td>\n",
       "      <td>Appellate Court / Second District</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>665 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Congress Dist                        Agency Name  Square Footage\n",
       "0               17    Department of Natural Resources          402882\n",
       "1               17          Department of Corrections         1518546\n",
       "2               17       Department of Human Services          247839\n",
       "3               17       Department of Transportation          430972\n",
       "4               17         Department of State Police           50974\n",
       "..             ...                                ...             ...\n",
       "660              4        Department of Public Health               0\n",
       "661              4                    Illinois Courts               0\n",
       "662              4   Appellate Court / Third District               0\n",
       "663              4   Appellate Court / Fifth District               0\n",
       "664              4  Appellate Court / Second District               0\n",
       "\n",
       "[665 rows x 3 columns]"
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#conversion of the transformed data back to a dataframe\n",
    "building_new = pd.DataFrame(list_,columns = ['Congress Dist','Agency Name','Square Footage'])\n",
    "building_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "       [  649139,  2594507,  1579965,   638311,   113685,   426121,\n",
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       "       [  571050,   931578,   192934,  1034012,   272619,   920736,\n",
       "         2000832,        0,  1003106,  2960272,   795120,    36538,\n",
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       "               0,        0,   913236,    45120,        0,    16400,\n",
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       "       [   24105,        0,        0,    29996,        0,        0,\n",
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       "       [   40249,        0,   372784,    55578,     8239,        0,\n",
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       "               0,        0,        0,        0,    43330],\n",
       "       [    8228,        0,        0,    69750,        0,        0,\n",
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       "       [   59050,    49572,  1253943,   287509,        0,   226500,\n",
       "               0,        0,        0,        0,   287000,        0,\n",
       "               0,        0,  3643049,   479061,        0,        0,\n",
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       "       [       0,        0,   449547,   118143,        0,   564580,\n",
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       "       [  200392,        0,   234642,     3270,     6246,    40852,\n",
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       "       [       0,        0,   362890,   112120,        0,        0,\n",
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       "           28452,        0,        0,        0,  1110103,        0,\n",
       "               0,        0,        0,        0,        0,        0,\n",
       "               0,        0,        0,        0,        0],\n",
       "       [       0,        0,        0,    34982,        0,   224959,\n",
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       "               0,        0,        0,        0,        0,        0,\n",
       "               0,        0,        0,        0,        0]], dtype=int64)"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#transforming the square footage column\n",
    "square_footage = building_new['Square Footage'].to_numpy()\n",
    "square_footage = square_footage.reshape(19,35)\n",
    "square_footage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "b5a9f1376cc647c2a4396299c1d1e974",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value=''), Figure(axes=[ColorAxis(orientation='vertical', scale=ColorScale(), side='right…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#grid heat map\n",
    "from bqplot import pyplot\n",
    "# 2. scales - linear scales\n",
    "x_sc = bqplot.OrdinalScale()\n",
    "y_sc = bqplot.OrdinalScale()\n",
    "c_sc = bqplot.ColorScale()\n",
    "\n",
    "# 3. axis\n",
    "ax_x = bqplot.Axis(scale = x_sc, label='Agency Name')\n",
    "ax_y = bqplot.Axis(scale = y_sc, orientation='vertical', label='Congress Dist')\n",
    "ax_col = bqplot.ColorAxis(scale = c_sc, orientation='vertical', side='right') \n",
    "# 4. Marks\n",
    "heat_map = bqplot.GridHeatMap(color = square_footage, #change\n",
    "                              row = building_new['Congress Dist'].unique(), #change\n",
    "                              column = building_new['Agency Name'].unique(), #change\n",
    "                              scales = {'color':c_sc, 'row':y_sc, 'column':x_sc},\n",
    "                             interactions={'click':'select'},\n",
    "                             anchor_style={'fill':'blue'})\n",
    "                             #selected_style={'opacity':1.0},\n",
    "                             #unselected_style={'opacity':0.8})\n",
    "\n",
    "mySelectedLabel = ipywidgets.Label()\n",
    "def on_selected(change): # already modified for our 3d data\n",
    "    if len(change['owner'].selected) == 1:\n",
    "        i, j = change['owner'].selected[0]\n",
    "        v = square_footage[i,j] # this is a 2d array!!\n",
    "        mySelectedLabel.value = 'Weighted binning (log(duration in sec)) = ' + str(v)\n",
    "        ##### Add in what changes for our histogram\n",
    "        ####hist.sample = data3d[i,j]\n",
    "# make sure we are observing for changes in our heatmap\n",
    "heat_map.observe(on_selected, 'selected')\n",
    "        \n",
    "# figure!\n",
    "fig = bqplot.Figure(marks=[heat_map], axes=[ax_col, ax_y, ax_x])\n",
    "#fig\n",
    "\n",
    "# dashboard with my label\n",
    "myDashboard = ipywidgets.VBox([mySelectedLabel, fig])\n",
    "myDashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "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 Acquired</th>\n",
       "      <th>Zip code</th>\n",
       "      <th>Congress Dist</th>\n",
       "      <th>Rep Dist</th>\n",
       "      <th>Senate Dist</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1753</td>\n",
       "      <td>62241</td>\n",
       "      <td>12</td>\n",
       "      <td>116</td>\n",
       "      <td>58</td>\n",
       "      <td>1753</td>\n",
       "      <td>1200</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1802</td>\n",
       "      <td>124482</td>\n",
       "      <td>24</td>\n",
       "      <td>232</td>\n",
       "      <td>116</td>\n",
       "      <td>3604</td>\n",
       "      <td>4440</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1810</td>\n",
       "      <td>186688</td>\n",
       "      <td>36</td>\n",
       "      <td>348</td>\n",
       "      <td>174</td>\n",
       "      <td>5430</td>\n",
       "      <td>4033</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1832</td>\n",
       "      <td>62901</td>\n",
       "      <td>12</td>\n",
       "      <td>115</td>\n",
       "      <td>58</td>\n",
       "      <td>1832</td>\n",
       "      <td>120000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>1837</td>\n",
       "      <td>62471</td>\n",
       "      <td>15</td>\n",
       "      <td>107</td>\n",
       "      <td>54</td>\n",
       "      <td>1837</td>\n",
       "      <td>10302</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>167</td>\n",
       "      <td>2015</td>\n",
       "      <td>1241150</td>\n",
       "      <td>313</td>\n",
       "      <td>1972</td>\n",
       "      <td>991</td>\n",
       "      <td>40300</td>\n",
       "      <td>305093</td>\n",
       "      <td>31</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>168</td>\n",
       "      <td>2016</td>\n",
       "      <td>612267</td>\n",
       "      <td>117</td>\n",
       "      <td>840</td>\n",
       "      <td>423</td>\n",
       "      <td>20158</td>\n",
       "      <td>304839</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>169</td>\n",
       "      <td>2017</td>\n",
       "      <td>62526</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>6720</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>170</td>\n",
       "      <td>2018</td>\n",
       "      <td>244806</td>\n",
       "      <td>59</td>\n",
       "      <td>265</td>\n",
       "      <td>133</td>\n",
       "      <td>8072</td>\n",
       "      <td>17160</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>171</td>\n",
       "      <td>2019</td>\n",
       "      <td>125918</td>\n",
       "      <td>24</td>\n",
       "      <td>234</td>\n",
       "      <td>118</td>\n",
       "      <td>4038</td>\n",
       "      <td>1520</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>171 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year Acquired  Zip code  Congress Dist  Rep Dist  Senate Dist  \\\n",
       "1             1753     62241             12       116           58   \n",
       "2             1802    124482             24       232          116   \n",
       "3             1810    186688             36       348          174   \n",
       "4             1832     62901             12       115           58   \n",
       "5             1837     62471             15       107           54   \n",
       "..             ...       ...            ...       ...          ...   \n",
       "167           2015   1241150            313      1972          991   \n",
       "168           2016    612267            117       840          423   \n",
       "169           2017     62526              4         4            2   \n",
       "170           2018    244806             59       265          133   \n",
       "171           2019    125918             24       234          118   \n",
       "\n",
       "     Year Constructed  Square Footage  Total Floors  Floors Above Grade  \\\n",
       "1                1753            1200             1                   1   \n",
       "2                3604            4440             4                   3   \n",
       "3                5430            4033             5                   5   \n",
       "4                1832          120000             2                   1   \n",
       "5                1837           10302             4                   3   \n",
       "..                ...             ...           ...                 ...   \n",
       "167             40300          305093            31                   6   \n",
       "168             20158          304839            16                   2   \n",
       "169              2017            6720             1                   0   \n",
       "170              8072           17160             4                   0   \n",
       "171              4038            1520             2                   0   \n",
       "\n",
       "     Floors Below Grade  \n",
       "1                     0  \n",
       "2                     1  \n",
       "3                     0  \n",
       "4                     1  \n",
       "5                     1  \n",
       "..                  ...  \n",
       "167                   1  \n",
       "168                   0  \n",
       "169                   0  \n",
       "170                   0  \n",
       "171                   0  \n",
       "\n",
       "[171 rows x 10 columns]"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#preprocessing for creation of line plot\n",
    "building_line = building.groupby('Year Acquired').sum().reset_index()\n",
    "building_l = building_line[building_line['Year Acquired'] != 0]\n",
    "building_l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([   1200,    4440,    4033,  120000,   10302,    2010,   11752,\n",
       "         36918,    3256,     900,    4088,   65846,   21292,    2267,\n",
       "        255000,    2140,   66154,     750,   18124,   22367,    4847,\n",
       "         27417,   15795,  223494,    2700,    2864,    6403,   14900,\n",
       "         11000,    6600,    3808,  404280,   33071,  179833,    6671,\n",
       "         59266,    8725,   30157,  168370,  194823,   84924,   86334,\n",
       "          2325,  151480,   39590,   85000,  225677,  290165,  132907,\n",
       "         36760,  121475,  335835,  109486,  269725,  160584,   40964,\n",
       "        312886,   20374,  133285,  360252,  298283,  231411,  237722,\n",
       "        422812,  158710,  334106,  532051,  210013,   32976,   42603,\n",
       "         64878,  402059,  187510,  171594,  549360,  126337,  569198,\n",
       "       1088997,  637645,  528122,  792329,  841869, 1018630,  414073,\n",
       "         68963,  176049,  692530,  663400,  926296, 1113321,  351573,\n",
       "       1292200,  345810,  243070,   57618,   44602,  190079,   58800,\n",
       "        164730,  378407,  903558, 1191430,  585533, 1153988,  491496,\n",
       "        763932,  814221, 1160035,  926481,  945126, 1473793,  954710,\n",
       "        832336, 1283527, 2426638, 2511989, 4236653, 2172950, 2379212,\n",
       "       1666198, 2205873, 1983743, 2575624, 1889175, 1218179,  959956,\n",
       "       1395013, 1413192, 1176456,  959744,  381181,  413474, 1759081,\n",
       "        812991,  680566, 1952554, 2011732,  962247, 1355701,  486223,\n",
       "       2185700, 2209048, 1653847,  900610,  351998,  435657,  877396,\n",
       "       1351591, 1110664,  731394,  364417, 1248787, 1329954, 1036110,\n",
       "       1041629,  575251, 1494411,  621710,  995526,  160223,  259724,\n",
       "        378725,  152953,  250113,  391485,  664298,  305093,  304839,\n",
       "          6720,   17160,    1520], dtype=int64)"
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#further preprocessing\n",
    "square_foot = building_l['Square Footage'].to_numpy()\n",
    "square_foot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [],
   "source": [
    "# line plot creation\n",
    "fig_l = bqplot.pyplot.figure(title='Square Footage Acquired Per Year')\n",
    "axes_options = {'x': {'label': 'Year Acquired', 'tick_format': '0.0f'},\n",
    "                'y': {'label': 'Square Footage', 'tick_format': '0.0f'}}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [],
   "source": [
    "line = bqplot.pyplot.plot(x =building_l['Year Acquired'], y = square_foot, axes_options= axes_options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 298,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8713ff6b1d9841618d32c5838d27e0c0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(axes=[Axis(label='Year Acquired', scale=LinearScale(), side='bottom', tick_format='0.0f'), Axis(label='…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_l"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Things to think about\n",
    "\n",
    "Keeping the x and y axes as static on the line plot does not seem like an ideal thing to do because their ranges are dependent on the cell selected in the Grid Heat Map. Static ranges might either lead to missing values if the ranges don't consider the absolute minimum and the absolute maximum values or lead to very small and concentrated visualizations when the ranges include all the values that can be wtinessed.\n",
    "\n",
    "The style can definitely be changed based on how the dashboard creator wants to view the various components of the dashboard and the interactivity between these components. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 299,
   "metadata": {},
   "outputs": [],
   "source": [
    "#5. interactivity\n",
    "mySelectedLabel = ipywidgets.Label()\n",
    "def on_selected(change): # already modified for our 3d data\n",
    "    if len(change['owner'].selected) == 1:\n",
    "        i, j = change['owner'].selected[0]\n",
    "        v = square_footage[i,j] # this is a 2d array!!\n",
    "        mySelectedLabel.value = 'Total Square Footage: ' + str(v)\n",
    "        line.y = square_foot[i:j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [],
   "source": [
    "#grid heat map\n",
    "from bqplot import pyplot\n",
    "# scales - ordinal scales\n",
    "x_sc = bqplot.OrdinalScale()\n",
    "y_sc = bqplot.OrdinalScale()\n",
    "c_sc = bqplot.ColorScale()\n",
    "\n",
    "# axis\n",
    "ax_x = bqplot.Axis(scale = x_sc, label='Agency Name')\n",
    "ax_y = bqplot.Axis(scale = y_sc, orientation='vertical', label='Congress Dist')\n",
    "ax_col = bqplot.ColorAxis(scale = c_sc, orientation='vertical', side='right') \n",
    "\n",
    "# Marks\n",
    "heat_map = bqplot.GridHeatMap(color = square_footage, #change\n",
    "                              row = building_new['Congress Dist'].unique(), #change\n",
    "                              column = building_new['Agency Name'].unique(), #change\n",
    "                              scales = {'color':c_sc, 'row':y_sc, 'column':x_sc},\n",
    "                             interactions={'click':'select'},\n",
    "                             anchor_style={'fill':'blue'})\n",
    "                             #selected_style={'opacity':1.0},\n",
    "                             #unselected_style={'opacity':0.8})\n",
    "\n",
    "# make sure we are observing for changes in our heatmap\n",
    "heat_map.observe(on_selected, 'selected')\n",
    "        \n",
    "# figure!\n",
    "fig = bqplot.Figure(marks=[heat_map], axes=[ax_col, ax_y, ax_x])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [],
   "source": [
    "#line plot\n",
    "fig_l = bqplot.pyplot.figure(title='Square Footage Acquired Per Year')\n",
    "axes_options = {'x': {'label': 'Year Acquired', 'tick_format': '0.0f'},\n",
    "                'y': {'label': 'Square Footage', 'tick_format': '0.0f'}}\n",
    "line = bqplot.pyplot.plot(x =building_l['Year Acquired'], y = square_foot, axes_options= axes_options)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "df6610ad5b2948e585613c9dd4f3a32e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(Label(value=''), HBox(children=(Figure(axes=[ColorAxis(orientation='vertical', scale=ColorScale…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mess with some layout parameters (look a little like CSS stylings)\n",
    "fig.layout.min_width='500px'\n",
    "fig_l.layout.min_width='500px'\n",
    "\n",
    "figures = ipywidgets.HBox([fig, fig_l]) # figures side-by-side\n",
    "\n",
    "# label on top\n",
    "myDashboard = ipywidgets.VBox([mySelectedLabel, figures])\n",
    "myDashboard"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Transformation and Rescaling in the plots\n",
    "\n",
    "**1. For the Grid Heat Map, a lot of data transformations were done which are mentioned below.**\n",
    "\n",
    "First, unique values for Congressional District and Agency Names were compared to each other to see which Agency Names were a part of a specific Congressional District and which weren't. This helped in determining a particular value for the Square Footage which was greater than zero for Congressional Districts constituting specific Agencies. In case of agencies that were not a part of a specific Congressional District, the Square Footage was totalled to zero. \n",
    "\n",
    "All these changes were stored in the form of a list of list with the Congressional District, Agency Names and Sum of Square Footage values being stored in the same order. This list of list was then converted to a pandas dataframe with their original headers. \n",
    "\n",
    "Now, the Sum of Square Footage values were converted to a 2D Numpy array and this array was reshaped to correctly fit the Grid Heat Map with the 'Agency Names' as columns and 'Congressional District' as rows.\n",
    "\n",
    "\n",
    "\n",
    "**2. For the Line plot, following data tansformations were done.**\n",
    "\n",
    "First, groupby operation was performed on the 'Year Acquired' column of the original dataframe to obtain the Total Sum of Square Footage values for each 'Year Acquired' by using the SUM aggregate function.\n",
    "\n",
    "Further, the row with 'Year Acquired' equivalent to zero was removed from the dataframe to eliminate outliers.\n",
    "\n",
    "Then, the dataframe column represting the Total Sum of Square Footage values was converted to a numpy array to enable linking of the heat map with the line plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dealing with NaN entries in the dataset\n",
    "\n",
    "I was not faced with a situation where I had to deal with NaN values in the dataset. This might be due to the approaches I used which might have directly or indirectly prevented me from enountering NaN values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Aesthetic Choices Made\n",
    "\n",
    "The only aesthetic choice I made was with respect to the overall layout so that both the visualizations could be made to fit in a horizontal arrangement without looking messy. \n",
    "\n",
    "I found the default color scheme visually pleasing and hence, I stuck to it.\n",
    "\n",
    "The default plot sizes and label sizes seemed to be appropriate for the current arrangement as well.\n",
    "\n",
    "Given more time, I would have loved to experiment more with the color scheme of the grid heat map as well as the background and text color of the line plot. Apart from that, I would have experimented with various plot sizes to get rid of the messy overlap of Agency Names in the Grid Heat Map columns and with the awkward overlap of the y-axis label with the y-axis values of the line plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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