insights to python.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# INSIGHTS FOR ARCGIS NOW WITH PYTHON(ARCGIS ONILNE, PANDAS, MATPLOTLIB, SEABORN.....)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To better understand trends in permit activity in Montgomery County, you'll create a new notebook in python 3 and add a dataset of permits issued since 2010 using arcGIS online. Before you begin your analysis, however, it's important to explore your data and understand what it shows and does not show. You'll familiarize yourself with the data's attributes, sort the data by type, and visualize spatial and temporal trends. In doing so, you'll gain context for your analysis and know exactly which questions you still need to ask to find out why growth is occurring where and when it is.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Connect your ArcGIS online organization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from arcgis import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "gis = GIS(\"https://deldev.maps.arcgis.com\", \"demo_deldev\", \"P@ssword123\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Accessing the content property of your gis object you can use the `search()` method. Search for **Commercial Permits since 2010** content made by other users by turning the outside_org to True.You can add name of the owner to you search to get more specific results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = gis.content.search('title: Commercial Permits since 2010 owner: rpeake_LearnGIS ', 'Feature layer',\n",
    "                           outside_org=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Importing the **display** module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The loop displays all the items"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "                    <div class=\"item_left\" style=\"width: 210px; float: left;\">\n",
       "                       <a href='https://deldev.maps.arcgis.com/home/item.html?id=1923d4e74ac947dab4f8c94d2c2a7a9c' target='_blank'>\n",
       "                        <img 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' width='200' height='133' class=\"itemThumbnail\">\n",
       "                       </a>\n",
       "                    </div>\n",
       "\n",
       "                    <div class=\"item_right\"     style=\"float: none; width: auto; overflow: hidden;\">\n",
       "                        <a href='https://deldev.maps.arcgis.com/home/item.html?id=1923d4e74ac947dab4f8c94d2c2a7a9c' target='_blank'><b>Commercial Permits since 2010</b>\n",
       "                        </a>\n",
       "                        <br/>Commercial building permits issued in Montgomery County, Maryland, since 2010.<img src='https://deldev.maps.arcgis.com/home/js/jsapi/esri/css/images/item_type_icons/featureshosted16.png' style=\"vertical-align:middle;\">Feature Layer Collection by rpeake_LearnGIS\n",
       "                        <br/>Last Modified: December 09, 2017\n",
       "                        <br/>0 comments, 375 views\n",
       "                    </div>\n",
       "                </div>\n",
       "                "
      ],
      "text/plain": [
       "<Item title:\"Commercial Permits since 2010\" type:Feature Layer Collection owner:rpeake_LearnGIS>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for item in data:\n",
    "    display(item)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Getting the first item"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "permits = data[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the item is a Feature Layer Collection, accessing the layers property will give us a list of FeatureLayer objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "permit_layer = permits.layers[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8171dcc0c6284f7b9603457f378fab35",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>MapView</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "MapView(basemaps=['dark-gray', 'dark-gray-vector', 'gray', 'gray-vector', 'hybrid', 'national-geographic', 'oceans', 'osm', 'satellite', 'streets', 'streets-navigation-vector', 'streets-night-vector', 'streets-relief-vector', 'streets-vector', 'terrain', 'topo', 'topo-vector'], center=[38.81819928400006, -76.15872999999993], zoom=9)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "permit_map = gis.map('Maryland', zoomlevel=9)\n",
    "permit_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](insights_images/image1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can add a number of different layer objects such as FeatureLayer, FeatureCollection, ImageryLayer, MapImageLayer to the map by calling the `add_layer()` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "permit_map.add_layer(permit_layer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert the layer into pandas dataframe to analyze it better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from arcgis.features import SpatialDataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdf = SpatialDataFrame.from_layer(permit_layer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`tail()` method gives the last 5 rows of the dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Applicatio</th>\n",
       "      <th>BldgAreaNu</th>\n",
       "      <th>Building_A</th>\n",
       "      <th>City</th>\n",
       "      <th>DeclValNu</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Declared_V</th>\n",
       "      <th>Descriptio</th>\n",
       "      <th>...</th>\n",
       "      <th>Pre_direct</th>\n",
       "      <th>State</th>\n",
       "      <th>Status</th>\n",
       "      <th>Street_Nam</th>\n",
       "      <th>Street_Num</th>\n",
       "      <th>Street_Suf</th>\n",
       "      <th>Use_Code</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11219</th>\n",
       "      <td>1391126400000</td>\n",
       "      <td>1015 SPRING ST</td>\n",
       "      <td>COMMERCIAL BUILDING</td>\n",
       "      <td>707.91</td>\n",
       "      <td>707.91</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>$42,000.00</td>\n",
       "      <td>Silver Spring Enterprise Zone\\n\\nAdd exterior ...</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>SPRING</td>\n",
       "      <td>1015</td>\n",
       "      <td>ST</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20910</td>\n",
       "      <td>{'x': -8574668.7047, 'y': 4721607.997599997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11220</th>\n",
       "      <td>1392076800000</td>\n",
       "      <td>26100 WOODFIELD RD</td>\n",
       "      <td>COMMERCIAL BUILDING</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "      <td>DAMASCUS</td>\n",
       "      <td>5875.0</td>\n",
       "      <td>5875.0</td>\n",
       "      <td>$5,875.00</td>\n",
       "      <td>PYLON SIGN</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>WOODFIELD</td>\n",
       "      <td>26100</td>\n",
       "      <td>RD</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20872</td>\n",
       "      <td>{'x': -8594080.2264, 'y': 4762636.6635000035, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11221</th>\n",
       "      <td>1392854400000</td>\n",
       "      <td>10520 MONTROSE AVE</td>\n",
       "      <td>COMMERCIAL BUILDING</td>\n",
       "      <td>728.00</td>\n",
       "      <td>728</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>31000.0</td>\n",
       "      <td>31000.0</td>\n",
       "      <td>$31,000.00</td>\n",
       "      <td>Remodeling a one story building with walk-out ...</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>MONTROSE</td>\n",
       "      <td>10520</td>\n",
       "      <td>AVE</td>\n",
       "      <td>ASSEMBLY BUILDING</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20814</td>\n",
       "      <td>{'x': -8582314.4798, 'y': 4725770.635600001, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11222</th>\n",
       "      <td>1394064000000</td>\n",
       "      <td>8500 RIVER RD</td>\n",
       "      <td>COMMERCIAL BUILDING</td>\n",
       "      <td>472.02</td>\n",
       "      <td>472.02</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>$1,000.00</td>\n",
       "      <td>TOTAL OF 17 GROUPED TENTS FOR 2014 QUICKEN LOA...</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>RIVER</td>\n",
       "      <td>8500</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8591206.0439, 'y': 4721680.315399997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11223</th>\n",
       "      <td>1394409600000</td>\n",
       "      <td>8500 RIVER RD</td>\n",
       "      <td>COMMERCIAL BUILDING</td>\n",
       "      <td>8461.55</td>\n",
       "      <td>8461.55</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>$1.00</td>\n",
       "      <td>1 GRANDSTAND &amp; MULTIPLE PLATFORMS FOR 2014 QUI...</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>RIVER</td>\n",
       "      <td>8500</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8591206.0439, 'y': 4721680.315399997, '...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Added_Date             Address           Applicatio  BldgAreaNu  \\\n",
       "11219  1391126400000      1015 SPRING ST  COMMERCIAL BUILDING      707.91   \n",
       "11220  1392076800000  26100 WOODFIELD RD  COMMERCIAL BUILDING        0.00   \n",
       "11221  1392854400000  10520 MONTROSE AVE  COMMERCIAL BUILDING      728.00   \n",
       "11222  1394064000000       8500 RIVER RD  COMMERCIAL BUILDING      472.02   \n",
       "11223  1394409600000       8500 RIVER RD  COMMERCIAL BUILDING     8461.55   \n",
       "\n",
       "      Building_A           City  DeclValNu  DeclValNu2  Declared_V  \\\n",
       "11219     707.91  SILVER SPRING    42000.0     42000.0  $42,000.00   \n",
       "11220          0       DAMASCUS     5875.0      5875.0   $5,875.00   \n",
       "11221        728       BETHESDA    31000.0     31000.0  $31,000.00   \n",
       "11222     472.02       BETHESDA     1000.0      1000.0   $1,000.00   \n",
       "11223    8461.55       BETHESDA        1.0         1.0       $1.00   \n",
       "\n",
       "                                              Descriptio  \\\n",
       "11219  Silver Spring Enterprise Zone\\n\\nAdd exterior ...   \n",
       "11220                                         PYLON SIGN   \n",
       "11221  Remodeling a one story building with walk-out ...   \n",
       "11222  TOTAL OF 17 GROUPED TENTS FOR 2014 QUICKEN LOA...   \n",
       "11223  1 GRANDSTAND & MULTIPLE PLATFORMS FOR 2014 QUI...   \n",
       "\n",
       "                             ...                          Pre_direct State  \\\n",
       "11219                        ...                                        MD   \n",
       "11220                        ...                                        MD   \n",
       "11221                        ...                                        MD   \n",
       "11222                        ...                                        MD   \n",
       "11223                        ...                                        MD   \n",
       "\n",
       "          Status Street_Nam  Street_Num Street_Suf  \\\n",
       "11219  Stop Work     SPRING        1015         ST   \n",
       "11220  Stop Work  WOODFIELD       26100         RD   \n",
       "11221  Stop Work   MONTROSE       10520        AVE   \n",
       "11222  Stop Work      RIVER        8500         RD   \n",
       "11223  Stop Work      RIVER        8500         RD   \n",
       "\n",
       "                             Use_Code  Work_Type ZIP_code  \\\n",
       "11219               BUSINESS BUILDING        ADD    20910   \n",
       "11220               BUSINESS BUILDING  CONSTRUCT    20872   \n",
       "11221               ASSEMBLY BUILDING        ADD    20814   \n",
       "11222  COMMERCIAL MISCELLANEOUS STRUC  CONSTRUCT    20817   \n",
       "11223  COMMERCIAL MISCELLANEOUS STRUC  CONSTRUCT    20817   \n",
       "\n",
       "                                                   SHAPE  \n",
       "11219  {'x': -8574668.7047, 'y': 4721607.997599997, '...  \n",
       "11220  {'x': -8594080.2264, 'y': 4762636.6635000035, ...  \n",
       "11221  {'x': -8582314.4798, 'y': 4725770.635600001, '...  \n",
       "11222  {'x': -8591206.0439, 'y': 4721680.315399997, '...  \n",
       "11223  {'x': -8591206.0439, 'y': 4721680.315399997, '...  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Added_Date', 'Address', 'Applicatio', 'BldgAreaNu', 'Building_A',\n",
       "       'City', 'DeclValNu', 'DeclValNu2', 'Declared_V', 'Descriptio', 'FID',\n",
       "       'Final_Date', 'Issue_Date', 'Location', 'Permit_Num', 'Post_direc',\n",
       "       'Pre_direct', 'State', 'Status', 'Street_Nam', 'Street_Num',\n",
       "       'Street_Suf', 'Use_Code', 'Work_Type', 'ZIP_code', 'SHAPE'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Added_Date</th>\n",
       "      <td>11224.0</td>\n",
       "      <td>1.380950e+12</td>\n",
       "      <td>6.564410e+10</td>\n",
       "      <td>1.262563e+12</td>\n",
       "      <td>1.324426e+12</td>\n",
       "      <td>1.382054e+12</td>\n",
       "      <td>1.438042e+12</td>\n",
       "      <td>1.492387e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BldgAreaNu</th>\n",
       "      <td>11224.0</td>\n",
       "      <td>9.241779e+03</td>\n",
       "      <td>3.950484e+04</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.550000e+02</td>\n",
       "      <td>1.537000e+03</td>\n",
       "      <td>4.000000e+03</td>\n",
       "      <td>1.548205e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DeclValNu</th>\n",
       "      <td>11224.0</td>\n",
       "      <td>7.847360e+05</td>\n",
       "      <td>1.152229e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.000000e+04</td>\n",
       "      <td>7.400000e+04</td>\n",
       "      <td>2.000000e+05</td>\n",
       "      <td>1.129634e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DeclValNu2</th>\n",
       "      <td>11224.0</td>\n",
       "      <td>7.847360e+05</td>\n",
       "      <td>1.152229e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.000000e+04</td>\n",
       "      <td>7.400000e+04</td>\n",
       "      <td>2.000000e+05</td>\n",
       "      <td>1.129634e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FID</th>\n",
       "      <td>11224.0</td>\n",
       "      <td>5.612500e+03</td>\n",
       "      <td>3.240234e+03</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>2.806750e+03</td>\n",
       "      <td>5.612500e+03</td>\n",
       "      <td>8.418250e+03</td>\n",
       "      <td>1.122400e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Issue_Date</th>\n",
       "      <td>10462.0</td>\n",
       "      <td>1.384331e+12</td>\n",
       "      <td>6.347793e+10</td>\n",
       "      <td>1.263514e+12</td>\n",
       "      <td>1.332374e+12</td>\n",
       "      <td>1.383696e+12</td>\n",
       "      <td>1.439942e+12</td>\n",
       "      <td>1.492387e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Permit_Num</th>\n",
       "      <td>11224.0</td>\n",
       "      <td>6.558061e+05</td>\n",
       "      <td>7.759285e+04</td>\n",
       "      <td>5.286310e+05</td>\n",
       "      <td>5.874375e+05</td>\n",
       "      <td>6.520735e+05</td>\n",
       "      <td>7.220032e+05</td>\n",
       "      <td>7.961930e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZIP_code</th>\n",
       "      <td>11224.0</td>\n",
       "      <td>2.084899e+04</td>\n",
       "      <td>5.581882e+02</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.083200e+04</td>\n",
       "      <td>2.087100e+04</td>\n",
       "      <td>2.090100e+04</td>\n",
       "      <td>2.177100e+04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              count          mean           std           min           25%  \\\n",
       "Added_Date  11224.0  1.380950e+12  6.564410e+10  1.262563e+12  1.324426e+12   \n",
       "BldgAreaNu  11224.0  9.241779e+03  3.950484e+04  0.000000e+00  2.550000e+02   \n",
       "DeclValNu   11224.0  7.847360e+05  1.152229e+07  0.000000e+00  2.000000e+04   \n",
       "DeclValNu2  11224.0  7.847360e+05  1.152229e+07  0.000000e+00  2.000000e+04   \n",
       "FID         11224.0  5.612500e+03  3.240234e+03  1.000000e+00  2.806750e+03   \n",
       "Issue_Date  10462.0  1.384331e+12  6.347793e+10  1.263514e+12  1.332374e+12   \n",
       "Permit_Num  11224.0  6.558061e+05  7.759285e+04  5.286310e+05  5.874375e+05   \n",
       "ZIP_code    11224.0  2.084899e+04  5.581882e+02  0.000000e+00  2.083200e+04   \n",
       "\n",
       "                     50%           75%           max  \n",
       "Added_Date  1.382054e+12  1.438042e+12  1.492387e+12  \n",
       "BldgAreaNu  1.537000e+03  4.000000e+03  1.548205e+06  \n",
       "DeclValNu   7.400000e+04  2.000000e+05  1.129634e+09  \n",
       "DeclValNu2  7.400000e+04  2.000000e+05  1.129634e+09  \n",
       "FID         5.612500e+03  8.418250e+03  1.122400e+04  \n",
       "Issue_Date  1.383696e+12  1.439942e+12  1.492387e+12  \n",
       "Permit_Num  6.520735e+05  7.220032e+05  7.961930e+05  \n",
       "ZIP_code    2.087100e+04  2.090100e+04  2.177100e+04  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Added_Date      int64\n",
       "Address        object\n",
       "Applicatio     object\n",
       "BldgAreaNu    float64\n",
       "Building_A     object\n",
       "City           object\n",
       "DeclValNu     float64\n",
       "DeclValNu2    float64\n",
       "Declared_V     object\n",
       "Descriptio     object\n",
       "FID             int64\n",
       "Final_Date     object\n",
       "Issue_Date    float64\n",
       "Location       object\n",
       "Permit_Num      int64\n",
       "Post_direc     object\n",
       "Pre_direct     object\n",
       "State          object\n",
       "Status         object\n",
       "Street_Nam     object\n",
       "Street_Num     object\n",
       "Street_Suf     object\n",
       "Use_Code       object\n",
       "Work_Type      object\n",
       "ZIP_code        int64\n",
       "SHAPE          object\n",
       "dtype: object"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['CONSTRUCT', 'ALTER', 'COMMERCIAL CHANGE OF USE',\n",
       "       'RESTORE AND / OR REPAIR', 'ADD', 'BUILD FOUNDATION', 'INSTALL',\n",
       "       'REPLACE', 'CONSTRUCT SHEETING/SHORING', 'FINAL ONLY AP',\n",
       "       'REMOVE AND REPLACE', 'OCCUPY', 'DEMOLISH'], dtype=object)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf['Work_Type'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Finaled', 'Issued', 'Open', 'Stop Work'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf['Status'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['MULTI-FAMILY DWELLING', 'RESTAURANT', 'BUSINESS BUILDING',\n",
       "       'MERCANTILE BUILDING', 'PLACE OF WORSHIP', 'ASSEMBLY BUILDING',\n",
       "       'STORAGE BUILDING', 'GARAGE', 'INSTITUTIONAL BUILDING',\n",
       "       'COMMERCIAL MISCELLANEOUS STRUC', 'INDUSTRIAL BUILDING',\n",
       "       'EDUCATIONAL BUILDING', 'TOWER', 'SWIMMING POOL', 'FENCE', 'BANK',\n",
       "       'SHED', 'MULTI-FAMILY SENIOR CITIZEN BL', 'RETAINING WALL',\n",
       "       'TRAILER', 'HOSPITAL', 'BIOSCIENCE', 'TOWNHOUSE', 'HOTEL',\n",
       "       'FACTORY', 'BOARDING HOUSE', 'SWIMMING POOL & FENCE',\n",
       "       'UTILITY, MISCELLANEOUS', 'THEATER',\n",
       "       'MULTIFAMILY DWELLING HIGH RISE', 'MULTIFAMILY DWELLING LOW RISE',\n",
       "       'MISCELLANEOUS STRUCTURE', 'OWNERSHIP UNIT'], dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf['Use_Code'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`groupby()` method groups the rows per the column and does calculation for example count in the following code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "permit_by_type = sdf.groupby(['Use_Code']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\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>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Applicatio</th>\n",
       "      <th>BldgAreaNu</th>\n",
       "      <th>Building_A</th>\n",
       "      <th>City</th>\n",
       "      <th>DeclValNu</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Declared_V</th>\n",
       "      <th>Descriptio</th>\n",
       "      <th>...</th>\n",
       "      <th>Post_direc</th>\n",
       "      <th>Pre_direct</th>\n",
       "      <th>State</th>\n",
       "      <th>Status</th>\n",
       "      <th>Street_Nam</th>\n",
       "      <th>Street_Num</th>\n",
       "      <th>Street_Suf</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Use_Code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ASSEMBLY BUILDING</th>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>...</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "      <td>394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BANK</th>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>...</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BIOSCIENCE</th>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>...</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOARDING HOUSE</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BUSINESS BUILDING</th>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>...</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Added_Date  Address  Applicatio  BldgAreaNu  Building_A  \\\n",
       "Use_Code                                                                     \n",
       "ASSEMBLY BUILDING         394      394         394         394         394   \n",
       "BANK                       87       87          87          87          87   \n",
       "BIOSCIENCE                 39       39          39          39          39   \n",
       "BOARDING HOUSE              3        3           3           3           3   \n",
       "BUSINESS BUILDING        3461     3461        3461        3461        3461   \n",
       "\n",
       "                   City  DeclValNu  DeclValNu2  Declared_V  Descriptio  ...    \\\n",
       "Use_Code                                                                ...     \n",
       "ASSEMBLY BUILDING   394        394         394         394         394  ...     \n",
       "BANK                 87         87          87          87          87  ...     \n",
       "BIOSCIENCE           39         39          39          39          39  ...     \n",
       "BOARDING HOUSE        3          3           3           3           3  ...     \n",
       "BUSINESS BUILDING  3461       3461        3461        3461        3461  ...     \n",
       "\n",
       "                   Post_direc  Pre_direct  State  Status  Street_Nam  \\\n",
       "Use_Code                                                               \n",
       "ASSEMBLY BUILDING         394         394    394     394         394   \n",
       "BANK                       87          87     87      87          87   \n",
       "BIOSCIENCE                 39          39     39      39          39   \n",
       "BOARDING HOUSE              3           3      3       3           3   \n",
       "BUSINESS BUILDING        3461        3461   3461    3461        3461   \n",
       "\n",
       "                   Street_Num  Street_Suf  Work_Type  ZIP_code  SHAPE  \n",
       "Use_Code                                                               \n",
       "ASSEMBLY BUILDING         394         394        394       394    394  \n",
       "BANK                       87          87         87        87     87  \n",
       "BIOSCIENCE                 39          39         39        39     39  \n",
       "BOARDING HOUSE              3           3          3         3      3  \n",
       "BUSINESS BUILDING        3461        3461       3461      3461   3461  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "permit_by_type.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The table is not sorted propeely.Use the `sort()` method to sort it from highest count to lowest count. The most common use code, Business Building, has almost twice as many permits as the second highest, Multi-family Dwelling. The top four use codes together comprise the majority of all permits, so these use codes may be the most important to focus on in your analysis later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "permit_by_type.sort_values(by=['State'], ascending=False, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "        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>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Applicatio</th>\n",
       "      <th>BldgAreaNu</th>\n",
       "      <th>Building_A</th>\n",
       "      <th>City</th>\n",
       "      <th>DeclValNu</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Declared_V</th>\n",
       "      <th>Descriptio</th>\n",
       "      <th>...</th>\n",
       "      <th>Post_direc</th>\n",
       "      <th>Pre_direct</th>\n",
       "      <th>State</th>\n",
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       "      <th>Street_Nam</th>\n",
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       "      <th>Street_Suf</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Use_Code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BUSINESS BUILDING</th>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>...</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTI-FAMILY DWELLING</th>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>...</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COMMERCIAL MISCELLANEOUS STRUC</th>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>...</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MERCANTILE BUILDING</th>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>...</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOWNHOUSE</th>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>...</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "      <td>680</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Added_Date  Address  Applicatio  BldgAreaNu  \\\n",
       "Use_Code                                                                      \n",
       "BUSINESS BUILDING                     3461     3461        3461        3461   \n",
       "MULTI-FAMILY DWELLING                 1838     1838        1838        1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197     1197        1197        1197   \n",
       "MERCANTILE BUILDING                   1016     1016        1016        1016   \n",
       "TOWNHOUSE                              680      680         680         680   \n",
       "\n",
       "                                Building_A  City  DeclValNu  DeclValNu2  \\\n",
       "Use_Code                                                                  \n",
       "BUSINESS BUILDING                     3461  3461       3461        3461   \n",
       "MULTI-FAMILY DWELLING                 1838  1838       1838        1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197  1197       1197        1197   \n",
       "MERCANTILE BUILDING                   1016  1016       1016        1016   \n",
       "TOWNHOUSE                              680   680        680         680   \n",
       "\n",
       "                                Declared_V  Descriptio  ...    Post_direc  \\\n",
       "Use_Code                                                ...                 \n",
       "BUSINESS BUILDING                     3461        3461  ...          3461   \n",
       "MULTI-FAMILY DWELLING                 1838        1838  ...          1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197        1197  ...          1197   \n",
       "MERCANTILE BUILDING                   1016        1016  ...          1016   \n",
       "TOWNHOUSE                              680         680  ...           680   \n",
       "\n",
       "                                Pre_direct  State  Status  Street_Nam  \\\n",
       "Use_Code                                                                \n",
       "BUSINESS BUILDING                     3461   3461    3461        3461   \n",
       "MULTI-FAMILY DWELLING                 1838   1838    1838        1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197   1197    1197        1197   \n",
       "MERCANTILE BUILDING                   1016   1016    1016        1016   \n",
       "TOWNHOUSE                              680    680     680         680   \n",
       "\n",
       "                                Street_Num  Street_Suf  Work_Type  ZIP_code  \\\n",
       "Use_Code                                                                      \n",
       "BUSINESS BUILDING                     3461        3461       3461      3461   \n",
       "MULTI-FAMILY DWELLING                 1838        1838       1838      1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197        1197       1197      1197   \n",
       "MERCANTILE BUILDING                   1016        1016       1016      1016   \n",
       "TOWNHOUSE                              680         680        680       680   \n",
       "\n",
       "                                SHAPE  \n",
       "Use_Code                               \n",
       "BUSINESS BUILDING                3461  \n",
       "MULTI-FAMILY DWELLING            1838  \n",
       "COMMERCIAL MISCELLANEOUS STRUC   1197  \n",
       "MERCANTILE BUILDING              1016  \n",
       "TOWNHOUSE                         680  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "permit_by_type.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "permit_by_status = sdf.groupby(sdf['Status']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Applicatio</th>\n",
       "      <th>BldgAreaNu</th>\n",
       "      <th>Building_A</th>\n",
       "      <th>City</th>\n",
       "      <th>DeclValNu</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Declared_V</th>\n",
       "      <th>Descriptio</th>\n",
       "      <th>...</th>\n",
       "      <th>Post_direc</th>\n",
       "      <th>Pre_direct</th>\n",
       "      <th>State</th>\n",
       "      <th>Street_Nam</th>\n",
       "      <th>Street_Num</th>\n",
       "      <th>Street_Suf</th>\n",
       "      <th>Use_Code</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Status</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Finaled</th>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>...</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "      <td>5341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Issued</th>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>...</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "      <td>4696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Open</th>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>...</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "      <td>757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Stop Work</th>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>...</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "      <td>430</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Added_Date  Address  Applicatio  BldgAreaNu  Building_A  City  \\\n",
       "Status                                                                     \n",
       "Finaled          5341     5341        5341        5341        5341  5341   \n",
       "Issued           4696     4696        4696        4696        4696  4696   \n",
       "Open              757      757         757         757         757   757   \n",
       "Stop Work         430      430         430         430         430   430   \n",
       "\n",
       "           DeclValNu  DeclValNu2  Declared_V  Descriptio  ...    Post_direc  \\\n",
       "Status                                                    ...                 \n",
       "Finaled         5341        5341        5341        5341  ...          5341   \n",
       "Issued          4696        4696        4696        4696  ...          4696   \n",
       "Open             757         757         757         757  ...           757   \n",
       "Stop Work        430         430         430         430  ...           430   \n",
       "\n",
       "           Pre_direct  State  Street_Nam  Street_Num  Street_Suf  Use_Code  \\\n",
       "Status                                                                       \n",
       "Finaled          5341   5341        5341        5341        5341      5341   \n",
       "Issued           4696   4696        4696        4696        4696      4696   \n",
       "Open              757    757         757         757         757       757   \n",
       "Stop Work         430    430         430         430         430       430   \n",
       "\n",
       "           Work_Type  ZIP_code  SHAPE  \n",
       "Status                                 \n",
       "Finaled         5341      5341   5341  \n",
       "Issued          4696      4696   4696  \n",
       "Open             757       757    757  \n",
       "Stop Work        430       430    430  \n",
       "\n",
       "[4 rows x 25 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "permit_by_status"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " There are only four permit statuses: Issued, Finaled, Open, and Stop Work. To visualize the number of permits for each status, you'll create a pie chart and  donut chart."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since the dataframe attributes just show the count of status, you can consider any attribute to for graph of the status count."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "status_count = permit_by_status[['City']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import matplotlib library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "% matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.1230119585990905,\n",
       " 1.1010958075523376,\n",
       " -1.1256150182608435,\n",
       " 1.1182148562865508)"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2564e788198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(status_count, labels=['Finaled', 'Issued', 'Open', 'Stop Work'])\n",
    "plt.axis('equal') # keeps the figure shape circle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-5.526617896007218, 5.501267518857486, -5.512895239312326, 5.564167256265628)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2564e8416a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.pie(permit_by_type['State'], radius=5)\n",
    "plt.legend(labels=['BUSINESS BUILDING', 'MULTI-FAMILY DWELLING',\n",
    "       'COMMERCIAL MISCELLANEOUS STRUC', 'MERCANTILE BUILDING', 'TOWNHOUSE',\n",
    "       'EDUCATIONAL BUILDING', 'RESTAURANT', 'ASSEMBLY BUILDING',\n",
    "       'STORAGE BUILDING', 'RETAINING WALL', 'PLACE OF WORSHIP', 'HOSPITAL',\n",
    "       'TRAILER', 'BANK', 'MULTI-FAMILY SENIOR CITIZEN BL', 'GARAGE',\n",
    "       'INDUSTRIAL BUILDING', 'SWIMMING POOL', 'HOTEL', 'BIOSCIENCE',\n",
    "       'MULTIFAMILY DWELLING LOW RISE', 'INSTITUTIONAL BUILDING', 'SHED',\n",
    "       'TOWER', 'MULTIFAMILY DWELLING HIGH RISE', 'FENCE',\n",
    "       'MISCELLANEOUS STRUCTURE', 'SWIMMING POOL & FENCE', 'FACTORY',\n",
    "       'BOARDING HOUSE', 'OWNERSHIP UNIT', 'THEATER',\n",
    "       'UTILITY, MISCELLANEOUS'], loc='upper right', bbox_to_anchor=(0.1, 0.1))\n",
    "plt.axis('equal') "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will show both as donuts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2564eba20f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a, b, c=[plt.cm.Blues, plt.cm.Reds, plt.cm.Greens]\n",
    " \n",
    "fig, ax = plt.subplots()\n",
    "ax.axis('equal')\n",
    "mypie, _ = ax.pie(permit_by_type['City'], radius=2, labeldistance=0.6, colors=[a(0.5), a(0.4), a(0.3), b(0.5), b(0.4), c(0.6), c(0.5), c(0.4), c(0.3), c(0.2)])\n",
    "plt.setp(mypie, width=0.1, edgecolor='white')\n",
    "plt.margins(0,0)\n",
    " \n",
    "# First Ring (inside)\n",
    "mypie2, _ = ax.pie(status_count, radius=2-0.4, colors=[a(0.6), b(0.6), c(0.6)] )\n",
    "plt.setp( mypie2, width=0.1, edgecolor='white')\n",
    " \n",
    "# show it\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2564e841e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_circle=plt.Circle((0,0), 0.7, color='white')\n",
    "plt.pie(status_count, labels=['Finaled', 'Issued', 'Open', 'Stop Work'], colors=['red','green','blue','skyblue'])\n",
    "p=plt.gcf()\n",
    "p.gca().add_artist(my_circle)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Currently, your map shows permits with a single symbol. However, it's helpful to visualize the spatial distribution of permit attributes. You'll change the map so that each permit's symbol represents its status."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "vdf = sdf[['Status', 'City', 'SHAPE']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e7085af70ea14328836653a1370381d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>MapView</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "MapView(basemaps=['dark-gray', 'dark-gray-vector', 'gray', 'gray-vector', 'hybrid', 'national-geographic', 'oceans', 'osm', 'satellite', 'streets', 'streets-navigation-vector', 'streets-night-vector', 'streets-relief-vector', 'streets-vector', 'terrain', 'topo', 'topo-vector'], center=[38.81819928400006, -76.15872999999993], zoom=8)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "map1 = gis.map('Maryland', zoomlevel=8)\n",
    "map1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](insights_images/image6.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\priyanka\\Anaconda3\\lib\\site-packages\\arcgis\\features\\_data\\geodataset\\geodataframe.py:351: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self['OBJECTID'] = list(range(1, self.shape[0] + 1))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vdf.plot(kind='map', map_widget = map1,\n",
    "        renderer_type='u', # specify the unique value renderer using its notation 'u'\n",
    "        col='Status'  # column to get unique values from\n",
    "       )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clean up the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before you begin analysis of your data, you'll hide attribute fields you don't intend to use, rename fields with unclear names, and filter your dataset to only show permits with the four most common use codes. These changes won't permanently affect the original dataset, but they will make the data easier to work with and understand."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**'Declared_V'**, **'Building_A'**, **'Applicatio'** attribute fields describe aspects of the data that aren't important for your analysis. You'll drop these fields."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdf.drop(['Declared_V', 'Building_A', 'Applicatio'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Added_Date', 'Address', 'BldgAreaNu', 'City', 'DeclValNu',\n",
       "       'DeclValNu2', 'Descriptio', 'FID', 'Final_Date', 'Issue_Date',\n",
       "       'Location', 'Permit_Num', 'Post_direc', 'Pre_direct', 'State', 'Status',\n",
       "       'Street_Nam', 'Street_Num', 'Street_Suf', 'Use_Code', 'Work_Type',\n",
       "       'ZIP_code', 'SHAPE'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The fields are no longer listed. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, you'll rename some of the attribute fields with shortened or unclear names so that their names are more descriptive."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdf.rename(columns={\"Descriptio\": \"Description\", \"BldgAreaNu\": \"Building_Area\", \"DeclValNu\": \"Declare_Value\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Added_Date', 'Address', 'Building_Area', 'City', 'Declare_Value',\n",
       "       'DeclValNu2', 'Description', 'FID', 'Final_Date', 'Issue_Date',\n",
       "       'Location', 'Permit_Num', 'Post_direc', 'Pre_direct', 'State', 'Status',\n",
       "       'Street_Nam', 'Street_Num', 'Street_Suf', 'Use_Code', 'Work_Type',\n",
       "       'ZIP_code', 'SHAPE'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "here are other fields that you may want to either rename or remove, but for the purposes of this lesson, these are enough. Next, you'll filter the permits to reduce the number of records in your analysis. As you saw previously, there are four types of permits that comprise over half the total number of permits. Focusing your analysis on just these four types will reduce the amount of data to analyze without ignoring the most important types of development. To remove the other use codes, you'll create a filter."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Applicatio</th>\n",
       "      <th>BldgAreaNu</th>\n",
       "      <th>Building_A</th>\n",
       "      <th>City</th>\n",
       "      <th>DeclValNu</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Declared_V</th>\n",
       "      <th>Descriptio</th>\n",
       "      <th>...</th>\n",
       "      <th>Post_direc</th>\n",
       "      <th>Pre_direct</th>\n",
       "      <th>State</th>\n",
       "      <th>Status</th>\n",
       "      <th>Street_Nam</th>\n",
       "      <th>Street_Num</th>\n",
       "      <th>Street_Suf</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Use_Code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BUSINESS BUILDING</th>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>...</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MULTI-FAMILY DWELLING</th>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>...</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COMMERCIAL MISCELLANEOUS STRUC</th>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>...</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MERCANTILE BUILDING</th>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>...</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Added_Date  Address  Applicatio  BldgAreaNu  \\\n",
       "Use_Code                                                                      \n",
       "BUSINESS BUILDING                     3461     3461        3461        3461   \n",
       "MULTI-FAMILY DWELLING                 1838     1838        1838        1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197     1197        1197        1197   \n",
       "MERCANTILE BUILDING                   1016     1016        1016        1016   \n",
       "\n",
       "                                Building_A  City  DeclValNu  DeclValNu2  \\\n",
       "Use_Code                                                                  \n",
       "BUSINESS BUILDING                     3461  3461       3461        3461   \n",
       "MULTI-FAMILY DWELLING                 1838  1838       1838        1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197  1197       1197        1197   \n",
       "MERCANTILE BUILDING                   1016  1016       1016        1016   \n",
       "\n",
       "                                Declared_V  Descriptio  ...    Post_direc  \\\n",
       "Use_Code                                                ...                 \n",
       "BUSINESS BUILDING                     3461        3461  ...          3461   \n",
       "MULTI-FAMILY DWELLING                 1838        1838  ...          1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197        1197  ...          1197   \n",
       "MERCANTILE BUILDING                   1016        1016  ...          1016   \n",
       "\n",
       "                                Pre_direct  State  Status  Street_Nam  \\\n",
       "Use_Code                                                                \n",
       "BUSINESS BUILDING                     3461   3461    3461        3461   \n",
       "MULTI-FAMILY DWELLING                 1838   1838    1838        1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197   1197    1197        1197   \n",
       "MERCANTILE BUILDING                   1016   1016    1016        1016   \n",
       "\n",
       "                                Street_Num  Street_Suf  Work_Type  ZIP_code  \\\n",
       "Use_Code                                                                      \n",
       "BUSINESS BUILDING                     3461        3461       3461      3461   \n",
       "MULTI-FAMILY DWELLING                 1838        1838       1838      1838   \n",
       "COMMERCIAL MISCELLANEOUS STRUC        1197        1197       1197      1197   \n",
       "MERCANTILE BUILDING                   1016        1016       1016      1016   \n",
       "\n",
       "                                SHAPE  \n",
       "Use_Code                               \n",
       "BUSINESS BUILDING                3461  \n",
       "MULTI-FAMILY DWELLING            1838  \n",
       "COMMERCIAL MISCELLANEOUS STRUC   1197  \n",
       "MERCANTILE BUILDING              1016  \n",
       "\n",
       "[4 rows x 25 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "permit_by_type.head(4) # top 4 Use_Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "permit_by_type.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "array = ['BUSINESS BUILDING', 'MULTI-FAMILY DWELLING', 'COMMERCIAL MISCELLANEOUS STRUC', 'MERCANTILE BUILDING']\n",
    "filtered_code = permit_by_type.loc[permit_by_type['Use_Code'].isin(array)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Use_Code</th>\n",
       "      <th>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Applicatio</th>\n",
       "      <th>BldgAreaNu</th>\n",
       "      <th>Building_A</th>\n",
       "      <th>City</th>\n",
       "      <th>DeclValNu</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Declared_V</th>\n",
       "      <th>...</th>\n",
       "      <th>Post_direc</th>\n",
       "      <th>Pre_direct</th>\n",
       "      <th>State</th>\n",
       "      <th>Status</th>\n",
       "      <th>Street_Nam</th>\n",
       "      <th>Street_Num</th>\n",
       "      <th>Street_Suf</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>...</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "      <td>3461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>...</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "      <td>1838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>...</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "      <td>1197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>MERCANTILE BUILDING</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>...</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "      <td>1016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Use_Code  Added_Date  Address  Applicatio  \\\n",
       "0               BUSINESS BUILDING        3461     3461        3461   \n",
       "1           MULTI-FAMILY DWELLING        1838     1838        1838   \n",
       "2  COMMERCIAL MISCELLANEOUS STRUC        1197     1197        1197   \n",
       "3             MERCANTILE BUILDING        1016     1016        1016   \n",
       "\n",
       "   BldgAreaNu  Building_A  City  DeclValNu  DeclValNu2  Declared_V  ...    \\\n",
       "0        3461        3461  3461       3461        3461        3461  ...     \n",
       "1        1838        1838  1838       1838        1838        1838  ...     \n",
       "2        1197        1197  1197       1197        1197        1197  ...     \n",
       "3        1016        1016  1016       1016        1016        1016  ...     \n",
       "\n",
       "   Post_direc  Pre_direct  State  Status  Street_Nam  Street_Num  Street_Suf  \\\n",
       "0        3461        3461   3461    3461        3461        3461        3461   \n",
       "1        1838        1838   1838    1838        1838        1838        1838   \n",
       "2        1197        1197   1197    1197        1197        1197        1197   \n",
       "3        1016        1016   1016    1016        1016        1016        1016   \n",
       "\n",
       "   Work_Type  ZIP_code  SHAPE  \n",
       "0       3461      3461   3461  \n",
       "1       1838      1838   1838  \n",
       "2       1197      1197   1197  \n",
       "3       1016      1016   1016  \n",
       "\n",
       "[4 rows x 26 columns]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To visualize on map, the top 4 Use_Code, you can filer the dataframe with Use_Code containing only the top 4 atttribute value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = sdf.loc[sdf['Use_Code'].isin(array)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Building_Area</th>\n",
       "      <th>City</th>\n",
       "      <th>Declare_Value</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Description</th>\n",
       "      <th>FID</th>\n",
       "      <th>Final_Date</th>\n",
       "      <th>Issue_Date</th>\n",
       "      <th>...</th>\n",
       "      <th>Pre_direct</th>\n",
       "      <th>State</th>\n",
       "      <th>Status</th>\n",
       "      <th>Street_Nam</th>\n",
       "      <th>Street_Num</th>\n",
       "      <th>Street_Suf</th>\n",
       "      <th>Use_Code</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13536 WATERFORD HILLS BLVD</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP - Unit #D036 - BLDG #4</td>\n",
       "      <td>1</td>\n",
       "      <td>1.3316e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13536</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602565.104, 'y': 4747203.126800001, 's...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13538 WATERFORD HILLS BLVD</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit #D038 - BLDG #4</td>\n",
       "      <td>2</td>\n",
       "      <td>1.33177e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13538</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602567.5243, 'y': 4747204.106700003, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13540 WATERFORD HILLS BLVD</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP - Unit #D040 - BLDG #4</td>\n",
       "      <td>3</td>\n",
       "      <td>1.33177e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13540</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602569.9445, 'y': 4747205.0867, 'spati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13542 WATERFORD HILLS BLVD</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit #D042 - BLDG #4</td>\n",
       "      <td>4</td>\n",
       "      <td>1.33177e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13542</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602572.3648, 'y': 4747206.066600002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13544 WATERFORD HILLS BLVD</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP - Unit #D044 - BLDG #4</td>\n",
       "      <td>5</td>\n",
       "      <td>1.33177e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13544</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602574.7851, 'y': 4747207.046599999, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13546 WATERFORD HILLS BLVD</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit #D046 - BLDG #4</td>\n",
       "      <td>6</td>\n",
       "      <td>1.33177e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13546</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602577.2054, 'y': 4747208.026500002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13548 WATERFORD HILLS BLVD</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP - Unit #D048 - BLDG #4</td>\n",
       "      <td>7</td>\n",
       "      <td>1.33186e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13548</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602579.6257, 'y': 4747209.006499998, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13550 WATERFORD HILLS BLVD</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit #D050 - BLDG #4</td>\n",
       "      <td>8</td>\n",
       "      <td>1.33212e+12</td>\n",
       "      <td>1.310083e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WATERFORD HILLS</td>\n",
       "      <td>13550</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602582.0459, 'y': 4747209.986500002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13571 STATION ST</td>\n",
       "      <td>1246.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>105000.0</td>\n",
       "      <td>105000.0</td>\n",
       "      <td>MODEL: AZALEA - Unit E071 - BLDG #5</td>\n",
       "      <td>9</td>\n",
       "      <td>1.31604e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13571</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602620.0925, 'y': 4747129.934699997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13573 STATION ST</td>\n",
       "      <td>1783.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>125000.0</td>\n",
       "      <td>125000.0</td>\n",
       "      <td>MODEL: LAVENDER - Unit E073 - BLDG #5</td>\n",
       "      <td>10</td>\n",
       "      <td>1.31604e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13573</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602624.1207, 'y': 4747131.644100003, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13575 STATION ST</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit E075 - BLDG #5</td>\n",
       "      <td>11</td>\n",
       "      <td>1.31604e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13575</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602628.1489, 'y': 4747133.353399999, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13577 STATION ST</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP - Unit E077 - BLDG #5 - MPDU</td>\n",
       "      <td>12</td>\n",
       "      <td>1.33229e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13577</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602632.1771, 'y': 4747135.062700003, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13579 STATION ST</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit E079 - BLDG #5</td>\n",
       "      <td>13</td>\n",
       "      <td>1.31639e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13579</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602636.2053, 'y': 4747136.772100002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13581 STATION ST</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP - Unit E081 - BLDG #5 - MPDU</td>\n",
       "      <td>14</td>\n",
       "      <td>1.31639e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13581</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602640.2335, 'y': 4747138.481399998, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13583 STATION ST</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit E083 - BLDG #5</td>\n",
       "      <td>15</td>\n",
       "      <td>1.31639e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13583</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602644.2616, 'y': 4747140.190700002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13585 STATION ST</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP - Unit E085 - BLDG #5</td>\n",
       "      <td>16</td>\n",
       "      <td>1.31639e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13585</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602648.2898, 'y': 4747141.9001, 'spati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13587 STATION ST</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit E087 - BLDG #5</td>\n",
       "      <td>17</td>\n",
       "      <td>1.31648e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13587</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602652.318, 'y': 4747143.609399997, 's...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13589 STATION ST</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL: TULIP- Unit E089 - BLDG #5 - MPDU</td>\n",
       "      <td>18</td>\n",
       "      <td>1.31648e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13589</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602656.3462, 'y': 4747145.318800002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13591 STATION ST</td>\n",
       "      <td>1730.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>MODEL: ORCHID - Unit E091 - BLDG #5</td>\n",
       "      <td>19</td>\n",
       "      <td>1.31648e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13591</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602660.3744, 'y': 4747147.028099999, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13593 STATION ST</td>\n",
       "      <td>1336.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>MODEL:TULIP - Unit E093 - BLDG #5 - MPDU</td>\n",
       "      <td>20</td>\n",
       "      <td>1.31648e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13593</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602664.4026, 'y': 4747148.737400003, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13595 STATION ST</td>\n",
       "      <td>1783.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>125000.0</td>\n",
       "      <td>125000.0</td>\n",
       "      <td>MODEL: LLAVENDER - Unit E095 - BLDG #5</td>\n",
       "      <td>21</td>\n",
       "      <td>1.31674e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13595</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602668.4308, 'y': 4747150.446800001, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1262822400000</td>\n",
       "      <td>13597 STATION ST</td>\n",
       "      <td>1329.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>105000.0</td>\n",
       "      <td>105000.0</td>\n",
       "      <td>MODEL: AZALEA - Unit E0097 - BLDG #5</td>\n",
       "      <td>22</td>\n",
       "      <td>1.31674e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>STATION</td>\n",
       "      <td>13597</td>\n",
       "      <td>ST</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8602672.459, 'y': 4747152.156099997, 's...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1262908800000</td>\n",
       "      <td>10500 WESTLAKE DR</td>\n",
       "      <td>11079.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>179100.0</td>\n",
       "      <td>179100.0</td>\n",
       "      <td>Interior Alterations/REVISION 08/17/2010 Archi...</td>\n",
       "      <td>23</td>\n",
       "      <td>1.28926e+12</td>\n",
       "      <td>1.273104e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WESTLAKE</td>\n",
       "      <td>10500</td>\n",
       "      <td>DR</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8588008.4738, 'y': 4725613.291599996, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1262908800000</td>\n",
       "      <td>10506 WESTLAKE DR</td>\n",
       "      <td>11079.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>164175.0</td>\n",
       "      <td>164175.0</td>\n",
       "      <td>Interior Alterations REVISION 08/17/210 Arichi...</td>\n",
       "      <td>24</td>\n",
       "      <td>1.28926e+12</td>\n",
       "      <td>1.273104e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WESTLAKE</td>\n",
       "      <td>10506</td>\n",
       "      <td>DR</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8588014.8937, 'y': 4725590.658699997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1262908800000</td>\n",
       "      <td>10520 WESTLAKE DR</td>\n",
       "      <td>11079.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>164175.0</td>\n",
       "      <td>164175.0</td>\n",
       "      <td>Interior Alterations Revision 08/17/2010 Archi...</td>\n",
       "      <td>25</td>\n",
       "      <td>1.29237e+12</td>\n",
       "      <td>1.273104e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WESTLAKE</td>\n",
       "      <td>10520</td>\n",
       "      <td>DR</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8588004.6145, 'y': 4725626.622400001, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1262908800000</td>\n",
       "      <td>10524 WESTLAKE DR</td>\n",
       "      <td>11079.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>164175.0</td>\n",
       "      <td>164175.0</td>\n",
       "      <td>Interior Alterations (Office) REVISION 08/17/2...</td>\n",
       "      <td>26</td>\n",
       "      <td>1.29194e+12</td>\n",
       "      <td>1.273104e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WESTLAKE</td>\n",
       "      <td>10524</td>\n",
       "      <td>DR</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8588002.2915, 'y': 4725636.7326000035, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1263254400000</td>\n",
       "      <td>4980 WYACONDA RD</td>\n",
       "      <td>12095.000</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>Change of Use: Business to Business/Factory.</td>\n",
       "      <td>28</td>\n",
       "      <td>1.28866e+12</td>\n",
       "      <td>1.268784e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>WYACONDA</td>\n",
       "      <td>4980</td>\n",
       "      <td>RD</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>COMMERCIAL CHANGE OF USE</td>\n",
       "      <td>20852</td>\n",
       "      <td>{'x': -8582701.5775, 'y': 4728190.869199999, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1263340800000</td>\n",
       "      <td>14201 GEORGIA AVE</td>\n",
       "      <td>3500.000</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>FIRE REPAIR BACK TO ORIGINAL CONDITION ONLY - ...</td>\n",
       "      <td>29</td>\n",
       "      <td>1.2795e+12</td>\n",
       "      <td>1.272240e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>GEORGIA AVE</td>\n",
       "      <td>14201</td>\n",
       "      <td></td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>RESTORE AND / OR REPAIR</td>\n",
       "      <td>20906</td>\n",
       "      <td>{'x': -8580465.7479, 'y': 4734381.686899997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1263427200000</td>\n",
       "      <td>18101 TOWN CENTER DR</td>\n",
       "      <td>13070.000</td>\n",
       "      <td>OLNEY</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>Canopy additions, facade renovation and sidewa...</td>\n",
       "      <td>30</td>\n",
       "      <td>1.29669e+12</td>\n",
       "      <td>1.266883e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>TOWN CENTER</td>\n",
       "      <td>18101</td>\n",
       "      <td>DR</td>\n",
       "      <td>MERCANTILE BUILDING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20832</td>\n",
       "      <td>{'x': -8578472.1944, 'y': 4743436.653700002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1263513600000</td>\n",
       "      <td>12630 VEIRS MILL RD</td>\n",
       "      <td>0.000</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>Attach 4 panel antennas &amp; equipment panel on r...</td>\n",
       "      <td>33</td>\n",
       "      <td>1.28148e+12</td>\n",
       "      <td>1.270512e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Finaled</td>\n",
       "      <td>VEIRS MILL</td>\n",
       "      <td>12630</td>\n",
       "      <td>RD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20853</td>\n",
       "      <td>{'x': -8582163.3885, 'y': 4730714.9619999975, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11161</th>\n",
       "      <td>1408406400000</td>\n",
       "      <td>7100 WISCONSIN AVE</td>\n",
       "      <td>0.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>960470.0</td>\n",
       "      <td>960470.0</td>\n",
       "      <td></td>\n",
       "      <td>11162</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.415837e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>WISCONSIN</td>\n",
       "      <td>7100</td>\n",
       "      <td>AVE</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT SHEETING/SHORING</td>\n",
       "      <td>20814</td>\n",
       "      <td>{'x': -8581882.3573, 'y': 4718849.4969, 'spati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11162</th>\n",
       "      <td>1374710400000</td>\n",
       "      <td>5600 SUNDOWN RD</td>\n",
       "      <td>6404.870</td>\n",
       "      <td>GAITHERSBURG</td>\n",
       "      <td>380000.0</td>\n",
       "      <td>380000.0</td>\n",
       "      <td></td>\n",
       "      <td>11163</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.379462e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>SUNDOWN</td>\n",
       "      <td>5600</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20882</td>\n",
       "      <td>{'x': -8583400.0036, 'y': 4752878.059199996, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11165</th>\n",
       "      <td>1408579200000</td>\n",
       "      <td>8000 FLOWER AVE</td>\n",
       "      <td>1990.000</td>\n",
       "      <td>TAKOMA PARK</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>Built out for future tenent</td>\n",
       "      <td>11166</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.425427e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>FLOWER</td>\n",
       "      <td>8000</td>\n",
       "      <td>AVE</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20912</td>\n",
       "      <td>{'x': -8571729.0356, 'y': 4720085.679799996, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11166</th>\n",
       "      <td>1408665600000</td>\n",
       "      <td>7101 DEMOCRACY BLVD</td>\n",
       "      <td>250.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>Mechanical screen around RTU   **Structural an...</td>\n",
       "      <td>11167</td>\n",
       "      <td>1.42595e+12</td>\n",
       "      <td>1.410826e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>DEMOCRACY</td>\n",
       "      <td>7101</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8587952.034, 'y': 4724840.1963, 'spatia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11169</th>\n",
       "      <td>1378425600000</td>\n",
       "      <td>11800 ROCKVILLE PIKE</td>\n",
       "      <td>200.000</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>Pylon Structure at properties corner.</td>\n",
       "      <td>11170</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.389658e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>11800</td>\n",
       "      <td>PIKE</td>\n",
       "      <td>MERCANTILE BUILDING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20852</td>\n",
       "      <td>{'x': -8584375.9321, 'y': 4728840.8301, 'spati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11171</th>\n",
       "      <td>1408665600000</td>\n",
       "      <td>300 NORWOOD RD</td>\n",
       "      <td>0.000</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>Install (3) T-Mobile antennas &amp; (1) Cabinet Po...</td>\n",
       "      <td>11172</td>\n",
       "      <td>1.44055e+12</td>\n",
       "      <td>1.410134e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>NORWOOD</td>\n",
       "      <td>300</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20905</td>\n",
       "      <td>{'x': -8573240.8754, 'y': 4738027.215499997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11172</th>\n",
       "      <td>1379030400000</td>\n",
       "      <td>19750 GERMANTOWN RD</td>\n",
       "      <td>167.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>10600.0</td>\n",
       "      <td>10600.0</td>\n",
       "      <td>FOUNDATION FOR RELOCATION OF SIGN==EUROMOTORCARS</td>\n",
       "      <td>11173</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.395187e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>19750</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8601040.4838, 'y': 4747536.214900002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11175</th>\n",
       "      <td>1408665600000</td>\n",
       "      <td>18200 FLOWER HILL WAY</td>\n",
       "      <td>0.000</td>\n",
       "      <td>GAITHERSBURG</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>aDDING ATENNAS</td>\n",
       "      <td>11176</td>\n",
       "      <td>1.44063e+12</td>\n",
       "      <td>1.409616e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>FLOWER HILL</td>\n",
       "      <td>18200</td>\n",
       "      <td>WAY</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20877</td>\n",
       "      <td>{'x': -8589928.5028, 'y': 4743948.7739999965, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11176</th>\n",
       "      <td>1379030400000</td>\n",
       "      <td>7051 CARROLL AVE</td>\n",
       "      <td>10.000</td>\n",
       "      <td>TAKOMA PARK</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>INSTALL 2 NEW CABINETS ON EXISTING STEEL PLAFT...</td>\n",
       "      <td>11177</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.381190e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>CARROLL</td>\n",
       "      <td>7051</td>\n",
       "      <td>AVE</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20912</td>\n",
       "      <td>{'x': -8572801.6509, 'y': 4718097.278399996, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11183</th>\n",
       "      <td>1379462400000</td>\n",
       "      <td>807 DALEVIEW DR</td>\n",
       "      <td>90.000</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>SIGN</td>\n",
       "      <td>11184</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.386547e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>DALEVIEW</td>\n",
       "      <td>807</td>\n",
       "      <td>DR</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20901</td>\n",
       "      <td>{'x': -8571032.764, 'y': 4722526.0353000015, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11185</th>\n",
       "      <td>1379548800000</td>\n",
       "      <td>7108 BRADLEY BLVD</td>\n",
       "      <td>880.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>Awning</td>\n",
       "      <td>11186</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.392854e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>BRADLEY</td>\n",
       "      <td>7108</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8587896.3727, 'y': 4722470.339599997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11187</th>\n",
       "      <td>1379980800000</td>\n",
       "      <td>15401 FREDERICK RD</td>\n",
       "      <td>1383.000</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>Addition - DARCARS 355 VOLVO - Auto Sales &amp; Se...</td>\n",
       "      <td>11188</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.381363e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>FREDERICK</td>\n",
       "      <td>15401</td>\n",
       "      <td>RD</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20855</td>\n",
       "      <td>{'x': -8589333.9495, 'y': 4737188.444399998, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11190</th>\n",
       "      <td>1380672000000</td>\n",
       "      <td>7101 DEMOCRACY BLVD</td>\n",
       "      <td>162.000</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>Temporary Canopy 5 months @ Food Court - (Abov...</td>\n",
       "      <td>11191</td>\n",
       "      <td>1.41022e+12</td>\n",
       "      <td>1.382314e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>DEMOCRACY</td>\n",
       "      <td>7101</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MERCANTILE BUILDING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8587952.034, 'y': 4724840.1963, 'spatia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11198</th>\n",
       "      <td>1381968000000</td>\n",
       "      <td>7300 AIRPARK RD</td>\n",
       "      <td>14142.940</td>\n",
       "      <td>GAITHERSBURG</td>\n",
       "      <td>750000.0</td>\n",
       "      <td>750000.0</td>\n",
       "      <td>MNCPPC-Laytonia Recreational Park Shelter\\n\\nC...</td>\n",
       "      <td>11199</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.429574e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>AIRPARK</td>\n",
       "      <td>7300</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20879</td>\n",
       "      <td>{'x': -8588345.5658, 'y': 4745387.9278, 'spati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11199</th>\n",
       "      <td>1382400000000</td>\n",
       "      <td>11802 ROCKVILLE PIKE</td>\n",
       "      <td>1002.000</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>Addition (Margie's Case) Also has a Alteration...</td>\n",
       "      <td>11200</td>\n",
       "      <td>1.41385e+12</td>\n",
       "      <td>1.391645e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>11802</td>\n",
       "      <td>PIKE</td>\n",
       "      <td>MERCANTILE BUILDING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20852</td>\n",
       "      <td>{'x': -8584376.1884, 'y': 4728841.343500003, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11202</th>\n",
       "      <td>1383177600000</td>\n",
       "      <td>20300 CENTURY BLVD</td>\n",
       "      <td>427.000</td>\n",
       "      <td>GERMANTOWN</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>Install antennas &amp; equipment on rooftop of MFD</td>\n",
       "      <td>11203</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.385510e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>CENTURY</td>\n",
       "      <td>20300</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20874</td>\n",
       "      <td>{'x': -8600819.0063, 'y': 4748803.194700003, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11205</th>\n",
       "      <td>1384214400000</td>\n",
       "      <td>2400 LAYTONSVILLE RD</td>\n",
       "      <td>252.830</td>\n",
       "      <td>LAYTONSVILLE</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>T-MOBILE application to replace six antennas w...</td>\n",
       "      <td>11206</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.385078e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>LAYTONSVILLE</td>\n",
       "      <td>2400</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20882</td>\n",
       "      <td>{'x': -8587475.8252, 'y': 4752130.380800001, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11206</th>\n",
       "      <td>1384214400000</td>\n",
       "      <td>4301 BROOKEVILLE RD</td>\n",
       "      <td>252.830</td>\n",
       "      <td>BROOKEVILLE</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>T-MOBILE application to replace six antennas w...</td>\n",
       "      <td>11207</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.385078e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>BROOKEVILLE</td>\n",
       "      <td>4301</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20833</td>\n",
       "      <td>{'x': -8581296.1621, 'y': 4748063.476099998, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11207</th>\n",
       "      <td>1384214400000</td>\n",
       "      <td>20315 GEORGIA AVE</td>\n",
       "      <td>252.830</td>\n",
       "      <td>BROOKEVILLE</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>T-MOBILE application to replace six antennas w...</td>\n",
       "      <td>11208</td>\n",
       "      <td>1.39838e+12</td>\n",
       "      <td>1.385510e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>GEORGIA</td>\n",
       "      <td>20315</td>\n",
       "      <td>AVE</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20833</td>\n",
       "      <td>{'x': -8578854.201, 'y': 4748802.5251, 'spatia...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11208</th>\n",
       "      <td>1384214400000</td>\n",
       "      <td>211 EDNOR RD</td>\n",
       "      <td>252.830</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>T-MOBILE application to replace six antennas w...</td>\n",
       "      <td>11209</td>\n",
       "      <td>1.39951e+12</td>\n",
       "      <td>1.385078e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>EDNOR</td>\n",
       "      <td>211</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20905</td>\n",
       "      <td>{'x': -8573745.5575, 'y': 4739901.545299999, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11209</th>\n",
       "      <td>1384300800000</td>\n",
       "      <td>16700 BARNESVILLE RD</td>\n",
       "      <td>505.647</td>\n",
       "      <td>BOYDS</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>Remove &amp; replace 6 antenna with 6 new like for...</td>\n",
       "      <td>11210</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.385078e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>BARNESVILLE</td>\n",
       "      <td>16700</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20841</td>\n",
       "      <td>{'x': -8610366.3746, 'y': 4751881.873899996, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11214</th>\n",
       "      <td>1387411200000</td>\n",
       "      <td>5601 FISHERS LN</td>\n",
       "      <td>17065.850</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>673077.0</td>\n",
       "      <td>673077.0</td>\n",
       "      <td>UNDERGROUND WATER STORAGE TANK for Computer Da...</td>\n",
       "      <td>11215</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.392163e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>FISHERS</td>\n",
       "      <td>5601</td>\n",
       "      <td>LN</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20852</td>\n",
       "      <td>{'x': -8584113.2207, 'y': 4730673.688000001, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11215</th>\n",
       "      <td>1387756800000</td>\n",
       "      <td>1306 AUTUMN BROOK AVE</td>\n",
       "      <td>200.000</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>2200.0</td>\n",
       "      <td>2200.0</td>\n",
       "      <td>DECK</td>\n",
       "      <td>11216</td>\n",
       "      <td>1.39743e+12</td>\n",
       "      <td>1.389830e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>AUTUMN BROOK</td>\n",
       "      <td>1306</td>\n",
       "      <td>AVE</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20906</td>\n",
       "      <td>{'x': -8574968.2897, 'y': 4732366.564300001, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11216</th>\n",
       "      <td>1387756800000</td>\n",
       "      <td>13307 TIVOLI LAKE BLVD</td>\n",
       "      <td>200.000</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>2200.0</td>\n",
       "      <td>2200.0</td>\n",
       "      <td>DECK</td>\n",
       "      <td>11217</td>\n",
       "      <td>1.39743e+12</td>\n",
       "      <td>1.389830e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>TIVOLI LAKE</td>\n",
       "      <td>13307</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20906</td>\n",
       "      <td>{'x': -8575010.4573, 'y': 4732435.254600003, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11217</th>\n",
       "      <td>1388448000000</td>\n",
       "      <td>12305 OLD COLUMBIA PIKE</td>\n",
       "      <td>2789.070</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>110000.0</td>\n",
       "      <td>CONCRETE PATIO FOR OUTDOOR GRILLING INCLUDING ...</td>\n",
       "      <td>11218</td>\n",
       "      <td>1.39951e+12</td>\n",
       "      <td>1.396310e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>OLD COLUMBIA</td>\n",
       "      <td>12305</td>\n",
       "      <td>PIKE</td>\n",
       "      <td>MULTI-FAMILY DWELLING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20904</td>\n",
       "      <td>{'x': -8568264.9142, 'y': 4729971.782700002, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11218</th>\n",
       "      <td>1388620800000</td>\n",
       "      <td>9609 MEDICAL CENTER DR</td>\n",
       "      <td>2069.430</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>124000.0</td>\n",
       "      <td>124000.0</td>\n",
       "      <td>ATTACH TWELVE 72\"\"-HIGH PANEL ANTENNAS AT THE ...</td>\n",
       "      <td>11219</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.430093e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>MEDICAL CENTER</td>\n",
       "      <td>9609</td>\n",
       "      <td>DR</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20850</td>\n",
       "      <td>{'x': -8593482.3159, 'y': 4736689.023100004, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11219</th>\n",
       "      <td>1391126400000</td>\n",
       "      <td>1015 SPRING ST</td>\n",
       "      <td>707.910</td>\n",
       "      <td>SILVER SPRING</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>Silver Spring Enterprise Zone\\n\\nAdd exterior ...</td>\n",
       "      <td>11220</td>\n",
       "      <td>1.40625e+12</td>\n",
       "      <td>1.392682e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>SPRING</td>\n",
       "      <td>1015</td>\n",
       "      <td>ST</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ADD</td>\n",
       "      <td>20910</td>\n",
       "      <td>{'x': -8574668.7047, 'y': 4721607.997599997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11220</th>\n",
       "      <td>1392076800000</td>\n",
       "      <td>26100 WOODFIELD RD</td>\n",
       "      <td>0.000</td>\n",
       "      <td>DAMASCUS</td>\n",
       "      <td>5875.0</td>\n",
       "      <td>5875.0</td>\n",
       "      <td>PYLON SIGN</td>\n",
       "      <td>11221</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.394669e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>WOODFIELD</td>\n",
       "      <td>26100</td>\n",
       "      <td>RD</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20872</td>\n",
       "      <td>{'x': -8594080.2264, 'y': 4762636.6635000035, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11222</th>\n",
       "      <td>1394064000000</td>\n",
       "      <td>8500 RIVER RD</td>\n",
       "      <td>472.020</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>TOTAL OF 17 GROUPED TENTS FOR 2014 QUICKEN LOA...</td>\n",
       "      <td>11223</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.402445e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>RIVER</td>\n",
       "      <td>8500</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8591206.0439, 'y': 4721680.315399997, '...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11223</th>\n",
       "      <td>1394409600000</td>\n",
       "      <td>8500 RIVER RD</td>\n",
       "      <td>8461.550</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1 GRANDSTAND &amp; MULTIPLE PLATFORMS FOR 2014 QUI...</td>\n",
       "      <td>11224</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.402445e+12</td>\n",
       "      <td>...</td>\n",
       "      <td></td>\n",
       "      <td>MD</td>\n",
       "      <td>Stop Work</td>\n",
       "      <td>RIVER</td>\n",
       "      <td>8500</td>\n",
       "      <td>RD</td>\n",
       "      <td>COMMERCIAL MISCELLANEOUS STRUC</td>\n",
       "      <td>CONSTRUCT</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8591206.0439, 'y': 4721680.315399997, '...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7512 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Added_Date                     Address  Building_Area  \\\n",
       "0      1262822400000  13536 WATERFORD HILLS BLVD       1336.000   \n",
       "1      1262822400000  13538 WATERFORD HILLS BLVD       1730.000   \n",
       "2      1262822400000  13540 WATERFORD HILLS BLVD       1336.000   \n",
       "3      1262822400000  13542 WATERFORD HILLS BLVD       1730.000   \n",
       "4      1262822400000  13544 WATERFORD HILLS BLVD       1336.000   \n",
       "5      1262822400000  13546 WATERFORD HILLS BLVD       1730.000   \n",
       "6      1262822400000  13548 WATERFORD HILLS BLVD       1336.000   \n",
       "7      1262822400000  13550 WATERFORD HILLS BLVD       1730.000   \n",
       "8      1262822400000            13571 STATION ST       1246.000   \n",
       "9      1262822400000            13573 STATION ST       1783.000   \n",
       "10     1262822400000            13575 STATION ST       1730.000   \n",
       "11     1262822400000            13577 STATION ST       1336.000   \n",
       "12     1262822400000            13579 STATION ST       1730.000   \n",
       "13     1262822400000            13581 STATION ST       1336.000   \n",
       "14     1262822400000            13583 STATION ST       1730.000   \n",
       "15     1262822400000            13585 STATION ST       1336.000   \n",
       "16     1262822400000            13587 STATION ST       1730.000   \n",
       "17     1262822400000            13589 STATION ST       1336.000   \n",
       "18     1262822400000            13591 STATION ST       1730.000   \n",
       "19     1262822400000            13593 STATION ST       1336.000   \n",
       "20     1262822400000            13595 STATION ST       1783.000   \n",
       "21     1262822400000            13597 STATION ST       1329.000   \n",
       "22     1262908800000           10500 WESTLAKE DR      11079.000   \n",
       "23     1262908800000           10506 WESTLAKE DR      11079.000   \n",
       "24     1262908800000           10520 WESTLAKE DR      11079.000   \n",
       "25     1262908800000           10524 WESTLAKE DR      11079.000   \n",
       "27     1263254400000            4980 WYACONDA RD      12095.000   \n",
       "28     1263340800000           14201 GEORGIA AVE       3500.000   \n",
       "29     1263427200000        18101 TOWN CENTER DR      13070.000   \n",
       "32     1263513600000         12630 VEIRS MILL RD          0.000   \n",
       "...              ...                         ...            ...   \n",
       "11161  1408406400000          7100 WISCONSIN AVE          0.000   \n",
       "11162  1374710400000             5600 SUNDOWN RD       6404.870   \n",
       "11165  1408579200000             8000 FLOWER AVE       1990.000   \n",
       "11166  1408665600000         7101 DEMOCRACY BLVD        250.000   \n",
       "11169  1378425600000        11800 ROCKVILLE PIKE        200.000   \n",
       "11171  1408665600000              300 NORWOOD RD          0.000   \n",
       "11172  1379030400000         19750 GERMANTOWN RD        167.000   \n",
       "11175  1408665600000       18200 FLOWER HILL WAY          0.000   \n",
       "11176  1379030400000            7051 CARROLL AVE         10.000   \n",
       "11183  1379462400000             807 DALEVIEW DR         90.000   \n",
       "11185  1379548800000           7108 BRADLEY BLVD        880.000   \n",
       "11187  1379980800000          15401 FREDERICK RD       1383.000   \n",
       "11190  1380672000000         7101 DEMOCRACY BLVD        162.000   \n",
       "11198  1381968000000             7300 AIRPARK RD      14142.940   \n",
       "11199  1382400000000        11802 ROCKVILLE PIKE       1002.000   \n",
       "11202  1383177600000          20300 CENTURY BLVD        427.000   \n",
       "11205  1384214400000        2400 LAYTONSVILLE RD        252.830   \n",
       "11206  1384214400000         4301 BROOKEVILLE RD        252.830   \n",
       "11207  1384214400000           20315 GEORGIA AVE        252.830   \n",
       "11208  1384214400000                211 EDNOR RD        252.830   \n",
       "11209  1384300800000        16700 BARNESVILLE RD        505.647   \n",
       "11214  1387411200000             5601 FISHERS LN      17065.850   \n",
       "11215  1387756800000       1306 AUTUMN BROOK AVE        200.000   \n",
       "11216  1387756800000      13307 TIVOLI LAKE BLVD        200.000   \n",
       "11217  1388448000000     12305 OLD COLUMBIA PIKE       2789.070   \n",
       "11218  1388620800000      9609 MEDICAL CENTER DR       2069.430   \n",
       "11219  1391126400000              1015 SPRING ST        707.910   \n",
       "11220  1392076800000          26100 WOODFIELD RD          0.000   \n",
       "11222  1394064000000               8500 RIVER RD        472.020   \n",
       "11223  1394409600000               8500 RIVER RD       8461.550   \n",
       "\n",
       "                City  Declare_Value  DeclValNu2  \\\n",
       "0         GERMANTOWN       103000.0    103000.0   \n",
       "1         GERMANTOWN       117000.0    117000.0   \n",
       "2         GERMANTOWN       103000.0    103000.0   \n",
       "3         GERMANTOWN       117000.0    117000.0   \n",
       "4         GERMANTOWN       103000.0    103000.0   \n",
       "5         GERMANTOWN       117000.0    117000.0   \n",
       "6         GERMANTOWN       103000.0    103000.0   \n",
       "7         GERMANTOWN       117000.0    117000.0   \n",
       "8         GERMANTOWN       105000.0    105000.0   \n",
       "9         GERMANTOWN       125000.0    125000.0   \n",
       "10        GERMANTOWN       117000.0    117000.0   \n",
       "11        GERMANTOWN       103000.0    103000.0   \n",
       "12        GERMANTOWN       117000.0    117000.0   \n",
       "13        GERMANTOWN       103000.0    103000.0   \n",
       "14        GERMANTOWN       117000.0    117000.0   \n",
       "15        GERMANTOWN       103000.0    103000.0   \n",
       "16        GERMANTOWN       117000.0    117000.0   \n",
       "17        GERMANTOWN       103000.0    103000.0   \n",
       "18        GERMANTOWN       117000.0    117000.0   \n",
       "19        GERMANTOWN       103000.0    103000.0   \n",
       "20        GERMANTOWN       125000.0    125000.0   \n",
       "21        GERMANTOWN       105000.0    105000.0   \n",
       "22          BETHESDA       179100.0    179100.0   \n",
       "23          BETHESDA       164175.0    164175.0   \n",
       "24          BETHESDA       164175.0    164175.0   \n",
       "25          BETHESDA       164175.0    164175.0   \n",
       "27         ROCKVILLE        15000.0     15000.0   \n",
       "28     SILVER SPRING        15000.0     15000.0   \n",
       "29             OLNEY       100000.0    100000.0   \n",
       "32         ROCKVILLE        10000.0     10000.0   \n",
       "...              ...            ...         ...   \n",
       "11161       BETHESDA       960470.0    960470.0   \n",
       "11162   GAITHERSBURG       380000.0    380000.0   \n",
       "11165    TAKOMA PARK        50000.0     50000.0   \n",
       "11166       BETHESDA        20000.0     20000.0   \n",
       "11169      ROCKVILLE        10000.0     10000.0   \n",
       "11171  SILVER SPRING        15000.0     15000.0   \n",
       "11172     GERMANTOWN        10600.0     10600.0   \n",
       "11175   GAITHERSBURG        15000.0     15000.0   \n",
       "11176    TAKOMA PARK        30000.0     30000.0   \n",
       "11183  SILVER SPRING         5000.0      5000.0   \n",
       "11185       BETHESDA        21000.0     21000.0   \n",
       "11187      ROCKVILLE       250000.0    250000.0   \n",
       "11190       BETHESDA         4500.0      4500.0   \n",
       "11198   GAITHERSBURG       750000.0    750000.0   \n",
       "11199      ROCKVILLE       200000.0    200000.0   \n",
       "11202     GERMANTOWN        50000.0     50000.0   \n",
       "11205   LAYTONSVILLE        15000.0     15000.0   \n",
       "11206    BROOKEVILLE        15000.0     15000.0   \n",
       "11207    BROOKEVILLE        15000.0     15000.0   \n",
       "11208  SILVER SPRING        15000.0     15000.0   \n",
       "11209          BOYDS        30000.0     30000.0   \n",
       "11214      ROCKVILLE       673077.0    673077.0   \n",
       "11215  SILVER SPRING         2200.0      2200.0   \n",
       "11216  SILVER SPRING         2200.0      2200.0   \n",
       "11217  SILVER SPRING       110000.0    110000.0   \n",
       "11218      ROCKVILLE       124000.0    124000.0   \n",
       "11219  SILVER SPRING        42000.0     42000.0   \n",
       "11220       DAMASCUS         5875.0      5875.0   \n",
       "11222       BETHESDA         1000.0      1000.0   \n",
       "11223       BETHESDA            1.0         1.0   \n",
       "\n",
       "                                             Description    FID   Final_Date  \\\n",
       "0                    MODEL: TULIP - Unit #D036 - BLDG #4      1   1.3316e+12   \n",
       "1                   MODEL: ORCHID - Unit #D038 - BLDG #4      2  1.33177e+12   \n",
       "2                    MODEL: TULIP - Unit #D040 - BLDG #4      3  1.33177e+12   \n",
       "3                   MODEL: ORCHID - Unit #D042 - BLDG #4      4  1.33177e+12   \n",
       "4                    MODEL: TULIP - Unit #D044 - BLDG #4      5  1.33177e+12   \n",
       "5                   MODEL: ORCHID - Unit #D046 - BLDG #4      6  1.33177e+12   \n",
       "6                    MODEL: TULIP - Unit #D048 - BLDG #4      7  1.33186e+12   \n",
       "7                   MODEL: ORCHID - Unit #D050 - BLDG #4      8  1.33212e+12   \n",
       "8                    MODEL: AZALEA - Unit E071 - BLDG #5      9  1.31604e+12   \n",
       "9                  MODEL: LAVENDER - Unit E073 - BLDG #5     10  1.31604e+12   \n",
       "10                   MODEL: ORCHID - Unit E075 - BLDG #5     11  1.31604e+12   \n",
       "11             MODEL: TULIP - Unit E077 - BLDG #5 - MPDU     12  1.33229e+12   \n",
       "12                   MODEL: ORCHID - Unit E079 - BLDG #5     13  1.31639e+12   \n",
       "13             MODEL: TULIP - Unit E081 - BLDG #5 - MPDU     14  1.31639e+12   \n",
       "14                   MODEL: ORCHID - Unit E083 - BLDG #5     15  1.31639e+12   \n",
       "15                    MODEL: TULIP - Unit E085 - BLDG #5     16  1.31639e+12   \n",
       "16                   MODEL: ORCHID - Unit E087 - BLDG #5     17  1.31648e+12   \n",
       "17              MODEL: TULIP- Unit E089 - BLDG #5 - MPDU     18  1.31648e+12   \n",
       "18                   MODEL: ORCHID - Unit E091 - BLDG #5     19  1.31648e+12   \n",
       "19              MODEL:TULIP - Unit E093 - BLDG #5 - MPDU     20  1.31648e+12   \n",
       "20                MODEL: LLAVENDER - Unit E095 - BLDG #5     21  1.31674e+12   \n",
       "21                  MODEL: AZALEA - Unit E0097 - BLDG #5     22  1.31674e+12   \n",
       "22     Interior Alterations/REVISION 08/17/2010 Archi...     23  1.28926e+12   \n",
       "23     Interior Alterations REVISION 08/17/210 Arichi...     24  1.28926e+12   \n",
       "24     Interior Alterations Revision 08/17/2010 Archi...     25  1.29237e+12   \n",
       "25     Interior Alterations (Office) REVISION 08/17/2...     26  1.29194e+12   \n",
       "27          Change of Use: Business to Business/Factory.     28  1.28866e+12   \n",
       "28     FIRE REPAIR BACK TO ORIGINAL CONDITION ONLY - ...     29   1.2795e+12   \n",
       "29     Canopy additions, facade renovation and sidewa...     30  1.29669e+12   \n",
       "32     Attach 4 panel antennas & equipment panel on r...     33  1.28148e+12   \n",
       "...                                                  ...    ...          ...   \n",
       "11161                                                     11162          NaN   \n",
       "11162                                                     11163          NaN   \n",
       "11165                        Built out for future tenent  11166          NaN   \n",
       "11166  Mechanical screen around RTU   **Structural an...  11167  1.42595e+12   \n",
       "11169              Pylon Structure at properties corner.  11170          NaN   \n",
       "11171  Install (3) T-Mobile antennas & (1) Cabinet Po...  11172  1.44055e+12   \n",
       "11172   FOUNDATION FOR RELOCATION OF SIGN==EUROMOTORCARS  11173          NaN   \n",
       "11175                                     aDDING ATENNAS  11176  1.44063e+12   \n",
       "11176  INSTALL 2 NEW CABINETS ON EXISTING STEEL PLAFT...  11177          NaN   \n",
       "11183                                               SIGN  11184          NaN   \n",
       "11185                                             Awning  11186          NaN   \n",
       "11187  Addition - DARCARS 355 VOLVO - Auto Sales & Se...  11188          NaN   \n",
       "11190  Temporary Canopy 5 months @ Food Court - (Abov...  11191  1.41022e+12   \n",
       "11198  MNCPPC-Laytonia Recreational Park Shelter\\n\\nC...  11199          NaN   \n",
       "11199  Addition (Margie's Case) Also has a Alteration...  11200  1.41385e+12   \n",
       "11202     Install antennas & equipment on rooftop of MFD  11203          NaN   \n",
       "11205  T-MOBILE application to replace six antennas w...  11206          NaN   \n",
       "11206  T-MOBILE application to replace six antennas w...  11207          NaN   \n",
       "11207  T-MOBILE application to replace six antennas w...  11208  1.39838e+12   \n",
       "11208  T-MOBILE application to replace six antennas w...  11209  1.39951e+12   \n",
       "11209  Remove & replace 6 antenna with 6 new like for...  11210          NaN   \n",
       "11214  UNDERGROUND WATER STORAGE TANK for Computer Da...  11215          NaN   \n",
       "11215                                               DECK  11216  1.39743e+12   \n",
       "11216                                               DECK  11217  1.39743e+12   \n",
       "11217  CONCRETE PATIO FOR OUTDOOR GRILLING INCLUDING ...  11218  1.39951e+12   \n",
       "11218  ATTACH TWELVE 72\"\"-HIGH PANEL ANTENNAS AT THE ...  11219          NaN   \n",
       "11219  Silver Spring Enterprise Zone\\n\\nAdd exterior ...  11220  1.40625e+12   \n",
       "11220                                         PYLON SIGN  11221          NaN   \n",
       "11222  TOTAL OF 17 GROUPED TENTS FOR 2014 QUICKEN LOA...  11223          NaN   \n",
       "11223  1 GRANDSTAND & MULTIPLE PLATFORMS FOR 2014 QUI...  11224          NaN   \n",
       "\n",
       "         Issue_Date                        ...                          \\\n",
       "0      1.310083e+12                        ...                           \n",
       "1      1.310083e+12                        ...                           \n",
       "2      1.310083e+12                        ...                           \n",
       "3      1.310083e+12                        ...                           \n",
       "4      1.310083e+12                        ...                           \n",
       "5      1.310083e+12                        ...                           \n",
       "6      1.310083e+12                        ...                           \n",
       "7      1.310083e+12                        ...                           \n",
       "8      1.300666e+12                        ...                           \n",
       "9      1.300666e+12                        ...                           \n",
       "10     1.300666e+12                        ...                           \n",
       "11     1.300666e+12                        ...                           \n",
       "12     1.300666e+12                        ...                           \n",
       "13     1.300666e+12                        ...                           \n",
       "14     1.300666e+12                        ...                           \n",
       "15     1.300666e+12                        ...                           \n",
       "16     1.300666e+12                        ...                           \n",
       "17     1.300666e+12                        ...                           \n",
       "18     1.300666e+12                        ...                           \n",
       "19     1.300666e+12                        ...                           \n",
       "20     1.300666e+12                        ...                           \n",
       "21     1.300666e+12                        ...                           \n",
       "22     1.273104e+12                        ...                           \n",
       "23     1.273104e+12                        ...                           \n",
       "24     1.273104e+12                        ...                           \n",
       "25     1.273104e+12                        ...                           \n",
       "27     1.268784e+12                        ...                           \n",
       "28     1.272240e+12                        ...                           \n",
       "29     1.266883e+12                        ...                           \n",
       "32     1.270512e+12                        ...                           \n",
       "...             ...                        ...                           \n",
       "11161  1.415837e+12                        ...                           \n",
       "11162  1.379462e+12                        ...                           \n",
       "11165  1.425427e+12                        ...                           \n",
       "11166  1.410826e+12                        ...                           \n",
       "11169  1.389658e+12                        ...                           \n",
       "11171  1.410134e+12                        ...                           \n",
       "11172  1.395187e+12                        ...                           \n",
       "11175  1.409616e+12                        ...                           \n",
       "11176  1.381190e+12                        ...                           \n",
       "11183  1.386547e+12                        ...                           \n",
       "11185  1.392854e+12                        ...                           \n",
       "11187  1.381363e+12                        ...                           \n",
       "11190  1.382314e+12                        ...                           \n",
       "11198  1.429574e+12                        ...                           \n",
       "11199  1.391645e+12                        ...                           \n",
       "11202  1.385510e+12                        ...                           \n",
       "11205  1.385078e+12                        ...                           \n",
       "11206  1.385078e+12                        ...                           \n",
       "11207  1.385510e+12                        ...                           \n",
       "11208  1.385078e+12                        ...                           \n",
       "11209  1.385078e+12                        ...                           \n",
       "11214  1.392163e+12                        ...                           \n",
       "11215  1.389830e+12                        ...                           \n",
       "11216  1.389830e+12                        ...                           \n",
       "11217  1.396310e+12                        ...                           \n",
       "11218  1.430093e+12                        ...                           \n",
       "11219  1.392682e+12                        ...                           \n",
       "11220  1.394669e+12                        ...                           \n",
       "11222  1.402445e+12                        ...                           \n",
       "11223  1.402445e+12                        ...                           \n",
       "\n",
       "      Pre_direct  State     Status       Street_Nam Street_Num Street_Suf  \\\n",
       "0                    MD    Finaled  WATERFORD HILLS      13536       BLVD   \n",
       "1                    MD    Finaled  WATERFORD HILLS      13538       BLVD   \n",
       "2                    MD    Finaled  WATERFORD HILLS      13540       BLVD   \n",
       "3                    MD    Finaled  WATERFORD HILLS      13542       BLVD   \n",
       "4                    MD    Finaled  WATERFORD HILLS      13544       BLVD   \n",
       "5                    MD    Finaled  WATERFORD HILLS      13546       BLVD   \n",
       "6                    MD    Finaled  WATERFORD HILLS      13548       BLVD   \n",
       "7                    MD    Finaled  WATERFORD HILLS      13550       BLVD   \n",
       "8                    MD    Finaled          STATION      13571         ST   \n",
       "9                    MD    Finaled          STATION      13573         ST   \n",
       "10                   MD    Finaled          STATION      13575         ST   \n",
       "11                   MD    Finaled          STATION      13577         ST   \n",
       "12                   MD    Finaled          STATION      13579         ST   \n",
       "13                   MD    Finaled          STATION      13581         ST   \n",
       "14                   MD    Finaled          STATION      13583         ST   \n",
       "15                   MD    Finaled          STATION      13585         ST   \n",
       "16                   MD    Finaled          STATION      13587         ST   \n",
       "17                   MD    Finaled          STATION      13589         ST   \n",
       "18                   MD    Finaled          STATION      13591         ST   \n",
       "19                   MD    Finaled          STATION      13593         ST   \n",
       "20                   MD    Finaled          STATION      13595         ST   \n",
       "21                   MD    Finaled          STATION      13597         ST   \n",
       "22                   MD    Finaled         WESTLAKE      10500         DR   \n",
       "23                   MD    Finaled         WESTLAKE      10506         DR   \n",
       "24                   MD    Finaled         WESTLAKE      10520         DR   \n",
       "25                   MD    Finaled         WESTLAKE      10524         DR   \n",
       "27                   MD    Finaled         WYACONDA       4980         RD   \n",
       "28                   MD    Finaled      GEORGIA AVE      14201              \n",
       "29                   MD    Finaled      TOWN CENTER      18101         DR   \n",
       "32                   MD    Finaled       VEIRS MILL      12630         RD   \n",
       "...          ...    ...        ...              ...        ...        ...   \n",
       "11161                MD  Stop Work        WISCONSIN       7100        AVE   \n",
       "11162                MD  Stop Work          SUNDOWN       5600         RD   \n",
       "11165                MD  Stop Work           FLOWER       8000        AVE   \n",
       "11166                MD  Stop Work        DEMOCRACY       7101       BLVD   \n",
       "11169                MD  Stop Work        ROCKVILLE      11800       PIKE   \n",
       "11171                MD  Stop Work          NORWOOD        300         RD   \n",
       "11172                MD  Stop Work       GERMANTOWN      19750         RD   \n",
       "11175                MD  Stop Work      FLOWER HILL      18200        WAY   \n",
       "11176                MD  Stop Work          CARROLL       7051        AVE   \n",
       "11183                MD  Stop Work         DALEVIEW        807         DR   \n",
       "11185                MD  Stop Work          BRADLEY       7108       BLVD   \n",
       "11187                MD  Stop Work        FREDERICK      15401         RD   \n",
       "11190                MD  Stop Work        DEMOCRACY       7101       BLVD   \n",
       "11198                MD  Stop Work          AIRPARK       7300         RD   \n",
       "11199                MD  Stop Work        ROCKVILLE      11802       PIKE   \n",
       "11202                MD  Stop Work          CENTURY      20300       BLVD   \n",
       "11205                MD  Stop Work     LAYTONSVILLE       2400         RD   \n",
       "11206                MD  Stop Work      BROOKEVILLE       4301         RD   \n",
       "11207                MD  Stop Work          GEORGIA      20315        AVE   \n",
       "11208                MD  Stop Work            EDNOR        211         RD   \n",
       "11209                MD  Stop Work      BARNESVILLE      16700         RD   \n",
       "11214                MD  Stop Work          FISHERS       5601         LN   \n",
       "11215                MD  Stop Work     AUTUMN BROOK       1306        AVE   \n",
       "11216                MD  Stop Work      TIVOLI LAKE      13307       BLVD   \n",
       "11217                MD  Stop Work     OLD COLUMBIA      12305       PIKE   \n",
       "11218                MD  Stop Work   MEDICAL CENTER       9609         DR   \n",
       "11219                MD  Stop Work           SPRING       1015         ST   \n",
       "11220                MD  Stop Work        WOODFIELD      26100         RD   \n",
       "11222                MD  Stop Work            RIVER       8500         RD   \n",
       "11223                MD  Stop Work            RIVER       8500         RD   \n",
       "\n",
       "                             Use_Code                   Work_Type ZIP_code  \\\n",
       "0               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "1               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "2               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "3               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "4               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "5               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "6               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "7               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "8               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "9               MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "10              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "11              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "12              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "13              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "14              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "15              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "16              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "17              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "18              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "19              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "20              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "21              MULTI-FAMILY DWELLING                   CONSTRUCT    20874   \n",
       "22              MULTI-FAMILY DWELLING                       ALTER    20817   \n",
       "23              MULTI-FAMILY DWELLING                       ALTER    20817   \n",
       "24              MULTI-FAMILY DWELLING                       ALTER    20817   \n",
       "25              MULTI-FAMILY DWELLING                       ALTER    20817   \n",
       "27                  BUSINESS BUILDING    COMMERCIAL CHANGE OF USE    20852   \n",
       "28              MULTI-FAMILY DWELLING     RESTORE AND / OR REPAIR    20906   \n",
       "29                MERCANTILE BUILDING                       ALTER    20832   \n",
       "32              MULTI-FAMILY DWELLING                       ALTER    20853   \n",
       "...                               ...                         ...      ...   \n",
       "11161  COMMERCIAL MISCELLANEOUS STRUC  CONSTRUCT SHEETING/SHORING    20814   \n",
       "11162  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20882   \n",
       "11165               BUSINESS BUILDING                       ALTER    20912   \n",
       "11166  COMMERCIAL MISCELLANEOUS STRUC                       ALTER    20817   \n",
       "11169             MERCANTILE BUILDING                   CONSTRUCT    20852   \n",
       "11171  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20905   \n",
       "11172  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20874   \n",
       "11175  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20877   \n",
       "11176               BUSINESS BUILDING                         ADD    20912   \n",
       "11183  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20901   \n",
       "11185  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20817   \n",
       "11187               BUSINESS BUILDING                         ADD    20855   \n",
       "11190             MERCANTILE BUILDING                   CONSTRUCT    20817   \n",
       "11198  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20879   \n",
       "11199             MERCANTILE BUILDING                   CONSTRUCT    20852   \n",
       "11202           MULTI-FAMILY DWELLING                         ADD    20874   \n",
       "11205  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20882   \n",
       "11206  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20833   \n",
       "11207  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20833   \n",
       "11208  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20905   \n",
       "11209  COMMERCIAL MISCELLANEOUS STRUC                         ADD    20841   \n",
       "11214  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20852   \n",
       "11215  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20906   \n",
       "11216  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20906   \n",
       "11217           MULTI-FAMILY DWELLING                   CONSTRUCT    20904   \n",
       "11218               BUSINESS BUILDING                         ADD    20850   \n",
       "11219               BUSINESS BUILDING                         ADD    20910   \n",
       "11220               BUSINESS BUILDING                   CONSTRUCT    20872   \n",
       "11222  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20817   \n",
       "11223  COMMERCIAL MISCELLANEOUS STRUC                   CONSTRUCT    20817   \n",
       "\n",
       "                                                   SHAPE  \n",
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       "\n",
       "[7512 rows x 23 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_filter = df[['City', 'SHAPE', 'Use_Code']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_map = gis.map('Maryland', zoomlevel=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e5a2f021b21348868c09a5eb0f2c5e34",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>MapView</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "MapView(basemaps=['dark-gray', 'dark-gray-vector', 'gray', 'gray-vector', 'hybrid', 'national-geographic', 'oceans', 'osm', 'satellite', 'streets', 'streets-navigation-vector', 'streets-night-vector', 'streets-relief-vector', 'streets-vector', 'terrain', 'topo', 'topo-vector'], center=[38.81819928400006, -76.15872999999993], zoom=8)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filtered_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](insights_images/image7.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\priyanka\\Anaconda3\\lib\\site-packages\\arcgis\\features\\_data\\geodataset\\geodataframe.py:351: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self['OBJECTID'] = list(range(1, self.shape[0] + 1))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_filter.plot(kind='map', map_widget = filtered_map,\n",
    "        renderer_type='u', # specify the unique value renderer using its notation 'u'\n",
    "        col='Use_Code'  # column to get unique values from\n",
    "       )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize temporal and spatial trends"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Your data shows permits, but what do these permits say about when and where growth is happening in the county? Your data also contains temporal attribute fields, such as Added_Date, which indicates when a permit was first added to the system. The field has several values that break down the data by year, month, and even hour."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Split the **Added_date** to get year, month, week_of_day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "i=0\n",
    "lst = []\n",
    "for value in sdf.Added_Date:\n",
    "    myval = str(value)[:-3]\n",
    "    dt = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(int(myval)))\n",
    "    lst.append(dt)\n",
    "sdf['date_modified'] = lst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Added_Date', 'Address', 'Building_Area', 'City', 'Declare_Value',\n",
       "       'DeclValNu2', 'Description', 'FID', 'Final_Date', 'Issue_Date',\n",
       "       'Location', 'Permit_Num', 'Post_direc', 'Pre_direct', 'State', 'Status',\n",
       "       'Street_Nam', 'Street_Num', 'Street_Suf', 'Use_Code', 'Work_Type',\n",
       "       'ZIP_code', 'SHAPE', 'date_modified'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "sdf['datetime'] = pd.to_datetime(sdf['date_modified'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdf['year'],sdf['month'],sdf['day_of_week'] = sdf.datetime.dt.year, sdf.datetime.dt.month, sdf.datetime.dt.dayofweek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2010, 2016, 2011, 2012, 2013, 2014, 2015, 2017], dtype=int64)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sdf.year.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To visualize patterns in permit activity over time, use groupby() to find out which year had most number of permits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_by_year = sdf.groupby(sdf['year']).count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Building_Area</th>\n",
       "      <th>City</th>\n",
       "      <th>Declare_Value</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Description</th>\n",
       "      <th>FID</th>\n",
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       "      <th>Issue_Date</th>\n",
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       "      <th>SHAPE</th>\n",
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       "    </tr>\n",
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       "  <tbody>\n",
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       "      <th>2010</th>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
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       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>842</td>\n",
       "      <td>1249</td>\n",
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       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "      <td>1279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>870</td>\n",
       "      <td>1503</td>\n",
       "      <td>...</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "      <td>1547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>790</td>\n",
       "      <td>1504</td>\n",
       "      <td>...</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "      <td>1552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>848</td>\n",
       "      <td>1443</td>\n",
       "      <td>...</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "      <td>1493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>898</td>\n",
       "      <td>1601</td>\n",
       "      <td>...</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "      <td>1671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>664</td>\n",
       "      <td>1439</td>\n",
       "      <td>...</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "      <td>1566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>476</td>\n",
       "      <td>1530</td>\n",
       "      <td>...</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "      <td>1660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>8</td>\n",
       "      <td>193</td>\n",
       "      <td>...</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "      <td>456</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Added_Date  Address  Building_Area  City  Declare_Value  DeclValNu2  \\\n",
       "year                                                                        \n",
       "2010        1279     1279           1279  1279           1279        1279   \n",
       "2011        1547     1547           1547  1547           1547        1547   \n",
       "2012        1552     1552           1552  1552           1552        1552   \n",
       "2013        1493     1493           1493  1493           1493        1493   \n",
       "2014        1671     1671           1671  1671           1671        1671   \n",
       "2015        1566     1566           1566  1566           1566        1566   \n",
       "2016        1660     1660           1660  1660           1660        1660   \n",
       "2017         456      456            456   456            456         456   \n",
       "\n",
       "      Description   FID  Final_Date  Issue_Date     ...       Street_Num  \\\n",
       "year                                                ...                    \n",
       "2010         1279  1279         842        1249     ...             1279   \n",
       "2011         1547  1547         870        1503     ...             1547   \n",
       "2012         1552  1552         790        1504     ...             1552   \n",
       "2013         1493  1493         848        1443     ...             1493   \n",
       "2014         1671  1671         898        1601     ...             1671   \n",
       "2015         1566  1566         664        1439     ...             1566   \n",
       "2016         1660  1660         476        1530     ...             1660   \n",
       "2017          456   456           8         193     ...              456   \n",
       "\n",
       "      Street_Suf  Use_Code  Work_Type  ZIP_code  SHAPE  date_modified  \\\n",
       "year                                                                    \n",
       "2010        1279      1279       1279      1279   1279           1279   \n",
       "2011        1547      1547       1547      1547   1547           1547   \n",
       "2012        1552      1552       1552      1552   1552           1552   \n",
       "2013        1493      1493       1493      1493   1493           1493   \n",
       "2014        1671      1671       1671      1671   1671           1671   \n",
       "2015        1566      1566       1566      1566   1566           1566   \n",
       "2016        1660      1660       1660      1660   1660           1660   \n",
       "2017         456       456        456       456    456            456   \n",
       "\n",
       "      datetime  month  day_of_week  \n",
       "year                                \n",
       "2010      1279   1279         1279  \n",
       "2011      1547   1547         1547  \n",
       "2012      1552   1552         1552  \n",
       "2013      1493   1493         1493  \n",
       "2014      1671   1671         1671  \n",
       "2015      1566   1566         1566  \n",
       "2016      1660   1660         1660  \n",
       "2017       456    456          456  \n",
       "\n",
       "[8 rows x 27 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_by_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_by_year.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x256512ed358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"City\", hue=\"year\", data=grouped_by_year);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, you can directly use countplot over the column to get the plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x256512ed470>"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2565142e390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"year\", data=sdf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly you can visualize it by month as well as day_of_week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25651491d30>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x256514a1128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"month\", data=sdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2565142e518>"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x25651491be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x=\"day_of_week\", data=sdf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "lst = ['2010-02-01T05:30:00.000000000', '2011-02-01T05:30:00.000000000', '2012-02-01T05:30:00.000000000',\n",
    "         '2013-02-01T05:30:00.000000000', '2014-02-01T05:30:00.000000000']\n",
    "gp_date = sdf.loc[sdf['datetime'].isin(lst)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "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>Added_Date</th>\n",
       "      <th>Address</th>\n",
       "      <th>Building_Area</th>\n",
       "      <th>City</th>\n",
       "      <th>Declare_Value</th>\n",
       "      <th>DeclValNu2</th>\n",
       "      <th>Description</th>\n",
       "      <th>FID</th>\n",
       "      <th>Final_Date</th>\n",
       "      <th>Issue_Date</th>\n",
       "      <th>...</th>\n",
       "      <th>Street_Suf</th>\n",
       "      <th>Use_Code</th>\n",
       "      <th>Work_Type</th>\n",
       "      <th>ZIP_code</th>\n",
       "      <th>SHAPE</th>\n",
       "      <th>date_modified</th>\n",
       "      <th>datetime</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>1264982400000</td>\n",
       "      <td>15010 BROSCHART RD</td>\n",
       "      <td>11214.0</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>210000.0</td>\n",
       "      <td>210000.0</td>\n",
       "      <td>Interior Alterations\\n1St Floor</td>\n",
       "      <td>51</td>\n",
       "      <td>1.27138e+12</td>\n",
       "      <td>1.269216e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>RD</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20850</td>\n",
       "      <td>{'x': -8593876.2647, 'y': 4736450.687200002, '...</td>\n",
       "      <td>2010-02-01 05:30:00</td>\n",
       "      <td>2010-02-01 05:30:00</td>\n",
       "      <td>2010</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>943</th>\n",
       "      <td>1296518400000</td>\n",
       "      <td>6251 EXECUTIVE BLVD</td>\n",
       "      <td>1885.0</td>\n",
       "      <td>ROCKVILLE</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>DENTAL OFFICE\\nREVISION - 3/15/11 - ELECTRICAL...</td>\n",
       "      <td>944</td>\n",
       "      <td>1.30507e+12</td>\n",
       "      <td>1.297210e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20852</td>\n",
       "      <td>{'x': -8585600.3765, 'y': 4728700.415600002, '...</td>\n",
       "      <td>2011-02-01 05:30:00</td>\n",
       "      <td>2011-02-01 05:30:00</td>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>949</th>\n",
       "      <td>1296518400000</td>\n",
       "      <td>9025 SHADY GROVE CT</td>\n",
       "      <td>900.0</td>\n",
       "      <td>GAITHERSBURG</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>Medical Office - 1st floor *INTERMEDIATE FAST ...</td>\n",
       "      <td>950</td>\n",
       "      <td>1.30861e+12</td>\n",
       "      <td>1.300666e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>CT</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20877</td>\n",
       "      <td>{'x': -8592008.3716, 'y': 4738734.382299997, '...</td>\n",
       "      <td>2011-02-01 05:30:00</td>\n",
       "      <td>2011-02-01 05:30:00</td>\n",
       "      <td>2011</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2201</th>\n",
       "      <td>1328054400000</td>\n",
       "      <td>5530 WISCONSIN AVE</td>\n",
       "      <td>3626.0</td>\n",
       "      <td>CHEVY CHASE</td>\n",
       "      <td>20800.0</td>\n",
       "      <td>20800.0</td>\n",
       "      <td>Interior Alterations\\n14th floor</td>\n",
       "      <td>2202</td>\n",
       "      <td>1344902400000</td>\n",
       "      <td>1.329782e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>AVE</td>\n",
       "      <td>BUSINESS BUILDING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20815</td>\n",
       "      <td>{'x': -8581385.817, 'y': 4716655.9186, 'spatia...</td>\n",
       "      <td>2012-02-01 05:30:00</td>\n",
       "      <td>2012-02-01 05:30:00</td>\n",
       "      <td>2012</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2206</th>\n",
       "      <td>1328054400000</td>\n",
       "      <td>7101 DEMOCRACY BLVD</td>\n",
       "      <td>10571.0</td>\n",
       "      <td>BETHESDA</td>\n",
       "      <td>775000.0</td>\n",
       "      <td>775000.0</td>\n",
       "      <td>Interior demolition and tenant fit out</td>\n",
       "      <td>2207</td>\n",
       "      <td>1351814400000</td>\n",
       "      <td>1.342742e+12</td>\n",
       "      <td>...</td>\n",
       "      <td>BLVD</td>\n",
       "      <td>MERCANTILE BUILDING</td>\n",
       "      <td>ALTER</td>\n",
       "      <td>20817</td>\n",
       "      <td>{'x': -8587952.034, 'y': 4724840.1963, 'spatia...</td>\n",
       "      <td>2012-02-01 05:30:00</td>\n",
       "      <td>2012-02-01 05:30:00</td>\n",
       "      <td>2012</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Added_Date              Address  Building_Area          City  \\\n",
       "50    1264982400000   15010 BROSCHART RD        11214.0     ROCKVILLE   \n",
       "943   1296518400000  6251 EXECUTIVE BLVD         1885.0     ROCKVILLE   \n",
       "949   1296518400000  9025 SHADY GROVE CT          900.0  GAITHERSBURG   \n",
       "2201  1328054400000   5530 WISCONSIN AVE         3626.0   CHEVY CHASE   \n",
       "2206  1328054400000  7101 DEMOCRACY BLVD        10571.0      BETHESDA   \n",
       "\n",
       "      Declare_Value  DeclValNu2  \\\n",
       "50         210000.0    210000.0   \n",
       "943         10000.0     10000.0   \n",
       "949         20000.0     20000.0   \n",
       "2201        20800.0     20800.0   \n",
       "2206       775000.0    775000.0   \n",
       "\n",
       "                                            Description   FID     Final_Date  \\\n",
       "50                      Interior Alterations\\n1St Floor    51    1.27138e+12   \n",
       "943   DENTAL OFFICE\\nREVISION - 3/15/11 - ELECTRICAL...   944    1.30507e+12   \n",
       "949   Medical Office - 1st floor *INTERMEDIATE FAST ...   950    1.30861e+12   \n",
       "2201                   Interior Alterations\\n14th floor  2202  1344902400000   \n",
       "2206             Interior demolition and tenant fit out  2207  1351814400000   \n",
       "\n",
       "        Issue_Date     ...     Street_Suf             Use_Code Work_Type  \\\n",
       "50    1.269216e+12     ...             RD    BUSINESS BUILDING     ALTER   \n",
       "943   1.297210e+12     ...           BLVD    BUSINESS BUILDING     ALTER   \n",
       "949   1.300666e+12     ...             CT    BUSINESS BUILDING     ALTER   \n",
       "2201  1.329782e+12     ...            AVE    BUSINESS BUILDING     ALTER   \n",
       "2206  1.342742e+12     ...           BLVD  MERCANTILE BUILDING     ALTER   \n",
       "\n",
       "     ZIP_code                                              SHAPE  \\\n",
       "50      20850  {'x': -8593876.2647, 'y': 4736450.687200002, '...   \n",
       "943     20852  {'x': -8585600.3765, 'y': 4728700.415600002, '...   \n",
       "949     20877  {'x': -8592008.3716, 'y': 4738734.382299997, '...   \n",
       "2201    20815  {'x': -8581385.817, 'y': 4716655.9186, 'spatia...   \n",
       "2206    20817  {'x': -8587952.034, 'y': 4724840.1963, 'spatia...   \n",
       "\n",
       "            date_modified            datetime  year month day_of_week  \n",
       "50    2010-02-01 05:30:00 2010-02-01 05:30:00  2010     2           0  \n",
       "943   2011-02-01 05:30:00 2011-02-01 05:30:00  2011     2           1  \n",
       "949   2011-02-01 05:30:00 2011-02-01 05:30:00  2011     2           1  \n",
       "2201  2012-02-01 05:30:00 2012-02-01 05:30:00  2012     2           2  \n",
       "2206  2012-02-01 05:30:00 2012-02-01 05:30:00  2012     2           2  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp_date.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0,0,'2010-02-01T05:30:00.000000000'),\n",
       " Text(0,0,'2011-02-01T05:30:00.000000000'),\n",
       " Text(0,0,'2012-02-01T05:30:00.000000000'),\n",
       " Text(0,0,'2013-02-01T05:30:00.000000000')]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2564dc05cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.countplot(x=\"date_modified\", data=gp_date)\n",
    "g.set_xticklabels(labels=['2010-02-01T05:30:00.000000000', '2011-02-01T05:30:00.000000000', '2012-02-01T05:30:00.000000000',\n",
    "         '2013-02-01T05:30:00.000000000', '2014-02-01T05:30:00.000000000'],rotation=90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdf[\"time\"] = sdf['year'].map(str) + \"-\" + sdf['month'].map(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "xf = sdf[['time', 'City']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\priyanka\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "xf['time'] = pd.to_datetime(xf['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x256513383c8>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x256513d79e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.dates as dates\n",
    "\n",
    "gp = xf.groupby(\"time\").count()\n",
    "gp.plot(x_compat=True, title='Count of Commercial Permits over time', legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A huge spike in permit activity occurred in mid-2011. What caused this spike? Is it an increase in overall permit activity, or is it mostly an increase in a certain type of permit? You'll group the time series card by use code to answer these questions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\priyanka\\Anaconda3\\lib\\site-packages\\IPython\\html.py:14: ShimWarning: The `IPython.html` package has been deprecated since IPython 4.0. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.\n",
      "  \"`IPython.html.widgets` has moved to `ipywidgets`.\", ShimWarning)\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67453f75182a47ec9119a5c8ddd387ae",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Dropdown</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "Dropdown(options=('Added_Date', 'Address', 'Building_Area', 'City', 'Declare_Value', 'DeclValNu2', 'Description', 'FID', 'Final_Date', 'Issue_Date', 'Location', 'Permit_Num', 'Post_direc', 'Pre_direct', 'State', 'Status', 'Street_Nam', 'Street_Num', 'Street_Suf', 'Use_Code', 'Work_Type', 'ZIP_code', 'SHAPE', 'date_modified', 'datetime', 'year', 'month', 'day_of_week', 'time'), value='Added_Date')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "from IPython.html.widgets import interactive\n",
    "\n",
    "items = list(sdf.columns)\n",
    "v = widgets.Dropdown(options=items)\n",
    "display(v)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](insights_images/imageA.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Use_Code'"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v.value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x256514dc940>"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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StAlO3Sx3K1KkaI3U0KdI0SbSYGyKlYLU0KdI0SZYSt2kWCFIDX2KFG2CpZmxKVYIUkOfIkWbsBlD6tCnWAlIDX2KFG3CTuWVKVYIUkOfIkWbkMlSdmrsU2iO1NCnSNEmpH1PefoUuiM19ClStAlp4FOJZQrdkRr6FCnahOPRp6WKU2iO1NCnSNEmHI4+9ehTaI7U0KdI0SZS6ibFSkFq6FOkaBMudZMa+hR6IzX0KVK0CcejTw19Cs0RytAT0SEieoyIHiaiPWLbWiK6mYj2if/DYjsR0ceJaD8RPUpEFyZ5AilSLBeYI69c3nakSNEKUTz6/8EYeyFj7CLx/l0AbmWM7QZwq3gPAK8FsFv8XQng03E1NkUKnWCnwdgUKwSdUDeXAbhWvL4WwOXK9usYx70Ahohocwe/kyKFlkipmxQrBWENPQPwQyJ6gIiuFNs2MsaOA4D4v0Fs3wrgiPLdUbEtRYqugtTPpx59Ct0R1tC/jDF2ITgt8zYienmTfSlgW92TQERXEtEeItozPj4eshkpVivGZkt4wd//F544NrPcTXHg1rpZ5oakSNECoQw9Y+yY+D8G4D8BvATASUnJiP9jYvdRAKcpX98G4FjAMT/DGLuIMXbRyMhI+2eQYlXgxGwJ8+UajkwuLndTHEjGJtXRp9AdLQ09EfUR0YB8DeDnATwO4CYAV4jdrgBwo3h9E4C3CPXNJQBmJMWTIkW7cIyqRt5zytGnWCkI49FvBHA3ET0C4H4A32WM/QDA+wH8HBHtA/Bz4j0AfA/AQQD7AXwWwB/H3uoUiaFUtfDP39+LxUptuZvigY5ZqNK+M43alCJFEDKtdmCMHQRwQcD2UwBeFbCdAXhbLK1LseR4dHQG/3bnQfz3M9fjZ3frQ6nJ7FOdslCZhoNPihRBSDNjU3ggaYiaRgYVUKkbfdqVUjcpVgpSQ5/CA8dLtfQyXnpTN8vbjpWCp0/M4aZH6nQZKZYAqaFP4YGloUEFlCxUjbxnnTz6x0ZncMfTY613XEZ85b7n8H9vfHy5m7Eq0ZKjT7G6oCNFArhadZ0GINkUHdp09V0H8PSJOVx61obWOy8TajZDTbOZ4mpB6tGn8EB6qfpx9Pp69DqobmqWjUpNI+1pAGwG1NLssmVBauhTeKCjugXQiyaRcNu0zA2BMKI6NKQJbJtpdf9WE1JDn8ID+Rzq6tHrNPPXieaybYaKThcnADZLDf1yITX0KTxwvVS9vEOngJhGhkKnNWNtxrSnRSzGYDO97uFqQWroU3hga6uj108N5CwlqEGbLAZUNefodQperzakhj6FB7qug6o3R7/8bWKMoapBO5pBXicdrtdqQ2roU3igr+pG/NekXYwxZSnB5W+TZTP9g7Ga9q3VgNTQp/BAJy9VhW7UjdoMHahxW/Dfut03Fc491Dxo3I1IDX0KD3Q19LI9unj0qhevw+AjL0tVY69eDoi6B427EamhT+GB+zAuv/FSoVsgz/Z49MvfJl2D6Cp0La+xGpAa+hQeWJp69DolJwE6evS8DTorb5imfWs1IDX0KTzQ9WF0qBsNjCrg4+g1aJKkvasa0yJOMl7K0S85UkO/wlCqWphaqCR2fOkx62boHepGk3YxZb17HagbOUBXNTaiqbxy+ZAa+hWGT96+H2+6+p7Ejq+rBE63ILHaDB3a5CwYowu3FQBd+9ZqQGroVxgm5suYTNCjd6kbvQyG5MF1oW7UdujQJld1s/xtaQTdBuvVhNTQrzDUrGQLQ7nT68R+oi3oVEAMAJhyfXQw9C51o9mNU5DKK5cPqaFfYbBslmjwzzWoej2MOhUQA3yqGw0ulUvd6HF9guDMyjS4XqsNqaFfYbASLvWqK4+qWyBPP+qGt6Giw6jTAMzpW/q2sVuRGvoVhprNEjUstmaes4Q701jedkh4EqY0uFaudFGTCxQA3Qbr1YTU0K8wWFbShp7/140C0I26YR7qZvnbpOtMTIWui9qsBqSGfoWhlvBybLoqI3Rrl67yypVA3ehwvVYbUkO/DDgyuYiTs6W2viurFCYFmfyjQ1q/CieRS5N2qTMLHZrENJ2JqbBWwKyjWxHa0BORSUQPEdF3xPsziOg+ItpHRNcTUU5sz4v3+8XnO5Jp+srFO7/+MP7xO0+29V35kCSVjanr9NqJHWjSLm1r3Wjs0dtO1rW+bexWRPHo3wFgr/L+AwA+whjbDWAKwFvF9rcCmGKMnQngI2K/FArmSjXMl2ptfVc+JEkZF11rhus27WeaUjdaG3rNCtOtJoQy9ES0DcDrAXxOvCcArwRwg9jlWgCXi9eXifcQn79K7L9kmFyo4FN37PcEzHRCJws5J13cS9dyt9I46BKM9VI3y98mXYPoKnRdeH41IKxH/1EAfwVA3qF1AKYZY9ItHQWwVbzeCuAIAIjPZ8T+HhDRlUS0h4j2jI+Pt9n8YNy69yQ++IOncWSyGOtx4wJf9q29B9JdgCPOFrnQacFrFXoHY5evHRIrgbqxNHUiVgNaGnoiegOAMcbYA+rmgF1ZiM/cDYx9hjF2EWPsopGRkVCNDQu3Q+nZ6TtZ8q2WcLBUV5meQ91o0ixtOXrN7psK3SqQriZkQuzzMgC/RESvA1AAMAju4Q8RUUZ47dsAHBP7jwI4DcAoEWUArAEwGXvLm0DXxTMkLJu1bUjthKkbS9PptaVZMFala3Ro00qoXumobnQZrVcRWnr0jLG/YYxtY4ztAPCrAG5jjP0GgNsBvEnsdgWAG8Xrm8R7iM9vY0tMYurKM0vYHZQxSFp1o6vXpVtRM90yY2UTdKZudKPfVhM60dH/NYB3EtF+cA7+GrH9GgDrxPZ3AnhXZ02MDt2Mgh+2zdp+IJNOI7cTPn67cIyEBkYV0Ji60dhb1nU94tWAMNSNA8bYHQDuEK8PAnhJwD4lAG+OoW1tQ/egTyeFyRyPPqFT0zWpxU54JhMVKrOlQ5tWlrxS3zZ2K7oyM1b3KaJlt9+2pDl6eVgdjJcKZ5amgfcM+KtXLmNDBFZCZqzuz2U3oysNve5V8riOvkPVTWKZsZp69NoFY93XOvQzOQDqvDi4lVI3y4buNPSa173mOno9E6Z0HSR1q8Gjaz36am3529IIumU3ryZ0paHXNaAo0YlHv1QJU7p5XfrVo1eCsct8rRhjLnWjqXMD6Bv/WQ3oSkOv+xTR7qDUcNIJU0wzikRCN+rGK69cvnb4f1/rYKzmDlg3ozsNvaaFuSSsjjx6UdQsoYdFV8WSbvJKnRKm1NmF1vJKTWeLqwFdaeiZ5lNEuwPVjfxeUjlouuYgSEZiuY2qhKfWzTIPPuq90jkzNpVXLh+60tDrGlCUsFgMCVNJlynW7Nrp5tHrFIxVf15nj959Lpe5IasQkRKmVgpWguqm3brNq1deyf/rMgDZGlE3loe60bPPA2p5DX3b2K3oSo9e56CPWoenHfpFGpiknEhb04dRt2CsR0e/7MHYlWHodXUiVgO60tA764tq2KE6zahM3KPXdJBMqZvGUAc/nY2o7lVluxldaeh15ZmBzqbZtu3qpVcfR8//6+KweuSVy666cV/r6tF7tf569a3VgK409LpKBAFvolNUY6qeT3KqGz2vXdI1fqJCp4Qp9fd1DcZ6VEqatrGb0ZWGXlevFPB64lGNqde4xNYkD3SlvXS7p0wj6kZti67ySruDfp+ic3S1odexQ6mGqhOPPimDxzTjwiV0C8Z6yhQvezDWfa2rR6/21+UeGFcjutLQu3pd/bwbb+AsWvvUKW/S1A1j+hhVQJlpaGIk5HXKGLTss4yVIK9Ub5uODli3o0sNPf+vY4fyUDcRvS/1u0kZPEvTB1K3yoeyGRmTlt1DXQmqG0/f1dAB63Z0paF3+FwNp7GdBPHUGUDS1A2g1xTboW60aRNvR9Ywlr1N6u9XanoaUbsDBydF5+hKQ79SVDdR26ca9+QSpvT0DqVt0M2jN83lp27kz+czhrbZ4PYSxJdSNEZ3GnrNpvkqOpnCdhLIbes3NPK8nPLJLLn4RBS4HL2R2NoAYSHvWT5jaOstq91VJwditaArDb2uyhHA69lEVUh4jHDC1SuT/I12oNsarbINWZOW/TrJ/p7LmKhoGozVKe9gNaIrDb3O1SvjklcmpYjxaLKX21VVsBSzmSiQ18k0NAjGqtSNrh59B2qzFJ2jSw09/69jp+8kYcqrRY6tSQ1/QweDKuEpOaDBTEO2IWsayy5DdaibrKGtvNJbMmL52rFa0ZWGXucFDrxBqQ44+iWgbnQaKJlmU3956zLG8lM3sr/nM2bbVVGThqXpTHG1oCsNvdaqmw4MqbXE1I0OnrPEUgxyUWCr1E1EuzW1UIlVBukaev44a9nvNZ0prha0NPREVCCi+4noESJ6goj+QWw/g4juI6J9RHQ9EeXE9rx4v198viPZU6iHbnVRVHiWfeuEo08sYUpPeaVO1SIBV97aTsLUaz/2I1x7z6HY2qJy9ICe2bG6ynZXC8J49GUAr2SMXQDghQBeQ0SXAPgAgI8wxnYDmALwVrH/WwFMMcbOBPARsd+SQm+PPh6OPrl69MG/t9zQjrpR5JVR2sMYw8m5Esbny7G1xeXoTQB61rvxqLk0uH+rDS0NPeOYF2+z4o8BeCWAG8T2awFcLl5fJt5DfP4qImp35by2sHJUN+1z9El59LrK4HSTfaryyij3whJrCsQZ/3Dklaa+Hn0nM9kUnSMUR09EJhE9DGAMwM0ADgCYZozVxC6jALaK11sBHAEA8fkMgHUBx7ySiPYQ0Z7x8fHOzsIHnRc46KTWjRrESurUbMaQNfm4rJOh98YnlrEhsg0eeWX470lvO06hgEPdZAVHr6FHr8pRdepXqwWhDD1jzGKMvRDANgAvAXBO0G7if5D3XndnGWOfYYxdxBi7aGRkJGx7Q8HNjNXAIvjQSQGqpaBVbMYlg4BeA6VnpqGBRy8NV9aMRt3IhKY4r62aGQvo6dF7Esw06lerBZFUN4yxaQB3ALgEwBARZcRH2wAcE69HAZwGAOLzNQAm42hsWKwU6iZ6MFb16JOjbqSh1+n6qaerQzDWqV4Z0UOVRjjOa8sc1Y3k6PUz9PJ8ow6MKeJBGNXNCBENidc9AF4NYC+A2wG8Sex2BYAbxeubxHuIz29jSyzs1Vl14w1KdcDRJxaM1dPQW5rFDlzqxoikW68m4dGvBHmlEkdIdfRLj0zrXbAZwLVEZIIPDF9njH2HiJ4E8DUiugrAQwCuEftfA+CLRLQf3JP/1QTa3RQrRnUTmaNX6YvYmuSBzYCc4Oh1eiB1o27arXVTrfF94xyo/Ry9jh69mkmsU79aLWhp6BljjwJ4UcD2g+B8vX97CcCbY2ldm1gp1E3U9tlL4NFbNkM2o59HzxhgEDdqOlA30ovPmEak9XuT4Ojl9XCpm+W/Pn7I081lDJRK1vI2ZhWiKzNjnTVjNezwnmXfNEyYYppy9JZKKWnh0QsP1aC2qJs4r21dZqyGHr3L0ZNW5a9XC7rU0PP/OhkqCU8qeMQHcqlq3eho6HULEssmmBFr3bgcfQLySmHodSxVrJZS1pFS7XZ0p6F3OHr9OnwnqpulCMZajCkcvT4PJGO83ACgl44+E1FFkoRH75dXajmTtWUwdvmLwK1GdKWh13mFqU4yT5eiTLFK3ejAhUtYNkPG0Ie6kU3ImhTpOkn+PM5B1C+v1NHBcYPXqbxyOdCdhl5r1Y37upOiZqsxYSqnUcauNO7RM2MT8OiloReqm0pt+a+PH6rqhpeB0K+N3YyuNPTyIWznYWKM4Wv3H8ZipdZ65zbgoW6ilileghLCuqpubMZpEv56+dvl8VCXPRjL/7s6eh09esnR69e3VgO60tB3Qt0cnFjAu/7jMdy6dyzuZgHwUzcRg7FKkC05j545xbF0ehhtxhyOXod2udUro1E30ttOVl6po6Hn/3WcLa4GdKeht+X/6J2pWOEa3zgXhlARXz362JrkAWNALtOeQWWM4S++8Qh+eij+ihfqAKRD7IAxBqLoa8YuhbxSSx29DMa22bdSdIauNPSOjr6NzlSuxS9/U9FJwtRSlClW9epRr1+xauGGB0Zxz/5TsbfLthWPXhPqxiACEefow3LOSZRAcDNjdfbAF/fyAAAgAElEQVTopeom9eiXA11t6NvxGso17tEn1RFVAx3V87KcgFZyFQC9evVoBkPOhpIYJG0GV3WjgZGwGYNBgCmWWgjbJNejj1FH75NXVhOajXYCtaiZ+j7F0qArDb2ruone4SVlk5QWuaOiZpb7sCSXGdv+w7hYSW6Q9FA3mnj0RATRpNBtqjj16ONsCz9mIasxdSM5+jQYuyzoSkPfierGpW6So0Yk2uXos6ahZcJUqSoMfQLUgTcYG/vhI4MJj14unha2r0lvO06P3q1eyakbHTNj/dRNauiXFl1p6K04OPqEHha7A/pF0gWZiGn3UX+jXY++WE3Qo7ddeaUORoLfC4JpkPM+DJLl6KWOXmNDr7EEtJvRlYZe9qF2iidVlsijz5pG5Cl2zWYwDTcAGDcY4+uZOtPriIOJQ90kQB2oCVO6UDcGkcPRh/bok1Dd2FLqaSBjkJbBWLWomfo+xdKgKw19Zx59csYK8NYlaWfhEdPgvHAS1I1f6xx1oEzUo2dMu2AsESCXvQ/bJMnRx9m/5MBnkHQg9DP0cmzOmbJMw/Lfw9WE7jT0HXD0lQQ4VBXqFLadomYZw4BJyahu1NK7QBvyykqSHL1S1EwDj55Jj15SNyGvVS3BzFjDIOQy0WeKSwGnb6U6+mVB1xl6Vc/cDo8tOfqoteLDQtrAXCZ6cScrYerG8QwNipwIBLiGPu6H2Em2aYOjv/nJk/iNz90be20VR15pRNP2J8LR29KjJ2RNQ8tgrOW7hzpW2OxmdJ2hlx3KFIs2R33Ay9X4PS4V3rUzo3L0tqBuohvhUG0T9sE0OPfcTsIUEP8g6ZYEju4NPvDcFH68/1TsXq4MxhoUNRjLIu0fti0Ap25yJmmpo3erfeojkV1N6D5D36GMq2IJY5WU6sZJBTcjUxwuR58sdSM91ciqG8ejj/fayWa0U9RsocyL08Wt8pA6esfQhzy8s5RgjP3LYopHn9GTo3eT/cJlxk4vVpx4WYrO0XWGXj5w2Ta14El79FbHHD2BKBmPyFYMRsagyNNrx6NPwHsG1ME7/HddQx9vm+QatjJhKjR1U4u/f8mfltSNzhy9W72y+U1846fuwaduP5B4u1YLus7QW3UdKqpHn6y80uWbo3vMNZs5kr4kqRuDCKYZ/TcWEwrGqpUigWixlwVRbjpuTpj5qZuI8so4+5dKV+rK0cvr4zhgLe7H2FwZY3PlxNu1WtB9ht4f9GnTo08qYcpiLv3SlkdvLhF1QxSZ7iglJK+so24iHH+hnNzgYxDa5uiTqF7pcPQ6GnpxuvmQDljVsrVc5HylousMvcuBt+fRJ13UzLK5Ec0YRtsc/VKpbtrl6OP2njtJtpkX1E38AWJZ6yZam5KYMdq21PSTtjp6f1GzVudfs1mqtY8R3WfoO0y1doNlyaluDKO9YKdlM5iUXMKU5ePoIxc1qyYjr2S+QF4USmnRoW4S8OgNPihGaZNqhOO6hzJLFxAJU5ovJQg07yOMMVg203LAWqnoOkPfKUefuLxSGOusGZ26kSUQTEqm1o0a1DPaoJakR19NTHUT3aOX1E3cAUrGAAK1XaYYiM+rlzQSwMtXaMnRRzD08l7Fbehvf3oMV9+5OgO8LQ09EZ1GRLcT0V4ieoKI3iG2ryWim4lon/g/LLYTEX2ciPYT0aNEdGHSJ6FC2ph2EzPkQ5KUN2Ex1jY1IhffoIQyY92gHtry6EsJefTOtF+WQIgwyM0nJq+UHL23ja2gettxXSdLBIYB/Tl6d6bdzNAnM6v+9sPH8IUfPxvrMVcKwnj0NQB/zhg7B8AlAN5GRM8H8C4AtzLGdgO4VbwHgNcC2C3+rgTw6dhb3QR+jz6qcmQpPHpDcvRtefQGTIOQgEPvXCvJPUevRy/48AQULoDL0UehPBYTUt1IusRok6MH4ht8ZDkGQN9aN1HKFMt7FXdcpWqzVZuR29LQM8aOM8YeFK/nAOwFsBXAZQCuFbtdC+By8foyANcxjnsBDBHR5thb3gCujKtN1U0tmexOCY/qpp1grFDEJDEQqdRNxoheoqHoDJLJJkyFvWzlmpUYDSCLmknqJuzAq7YjNo9eUHoA7/dalin2iSSaDXKS+os7rlKt2VrSWkuBSBw9Ee0A8CIA9wHYyBg7DvDBAMAGsdtWAEeUr42Kbf5jXUlEe4hoz/j4ePSWN4BaHVJ9HxblhIuaWbaSkNRGCYSMYYAomXVTVeqmPY4+Ge9ZnmtUHb3k54EkEqaEjj5iwpR6beLk6GUVTX0Tpvj/MMqpWgIVPgH+/Og421kKhDb0RNQP4JsA/jdjbLbZrgHb6u4YY+wzjLGLGGMXjYyMhG1GS9SlWkfl6GVRs6RUNzbjHHg7C4/YcGYDcRfpAuozY3VZeMQp2mUQDApP3cisWCABj14M2JIyiVqPnh8jJkOvePS5DGnptUaRV8prFHdQv2IxLQfBpUAoQ09EWXAj/2XG2H+IzSclJSP+j4ntowBOU76+DcCxeJrbGp3r6JMvgcAlkp0VNUsmYYr/b5ejT6pMsRzTTNmusB59xTX08XP0grqJKK+sJKK60Z+jZ+J6hVFOyesS93nULBuWzVZlieQwqhsCcA2AvYyxDysf3QTgCvH6CgA3KtvfItQ3lwCYkRTPUsCJ7pvt6eiXYilBw5C1ZNpLmDKIkIRjIo2V2a6hT8ijd/T9Bjdo7Xj0SRQ1a7cEQtyrLHnklaahZfVKqQwKk2BWS0h1U01YUaczMiH2eRmA3wLwGBE9LLb9LYD3A/g6Eb0VwGEAbxaffQ/A6wDsB7AI4HdibXELWB169JWEM2PlNLutEgiMFzWzWfTyy6Ha5qteGcU4Vi3bmRbHXwLBpZSiDEDzCkefhBJIDjxAlHr0DIWsiapVi1lHL6kbfTl6mREOLI+OPqn+uRLQ0tAzxu5GMO8OAK8K2J8BeFuH7Wob9ZmxulE3sspgG0XNLFECgSXTPmnXqY3qldKbB5KgbhRDHyFZbLGcLHXjXWEq3PeqNRuFnIm5Ui22gL+MFwBwippxqqTRY7v0kGUa5PVqZsSTKPymHrdas4F8rIfWHt2XGduBR88Yc1eYSrAePfeY2ytT7FA3iXD0UnVDkT36kuDne7JmYkXNpG49LE0ynzB1Q6IcBX8fnqPvyca7bqqU7AJwFlDXzWu1RRulGq7chF6q2clQN7WEZgorAd1n6H2JGVE6vDrlTcyjF8a6HVWLfKANSjZhildBNJo+jH5Ij36gkImfo7fddkUKxnpUN0l49HC85ihLCTqGPqY2+eWV8nd0goxp5DMGDHID90GQ9ypu9ZC8JjqqkpJG1xl6//qiUSRs6oo2SfGcalAq6lKHcuGRKMYuClTPub+Q8RjKVpC16AcKmcTq0RvObCbc9xYqSdJJLpUEhOtnls1gM6CQjXc5PVVe6Rh6zQqbWbY7MPbmMk5/CYKro4/Z0NvJSqd1RtcZekev2wZHr2YUJlrUTHj0QLT21Syu2IlCX0SB4zkbhP58xkN9tILr0Wdhs3ira6oZu1Eqd3o8+gQCxJ7FwUMcX3qUhZipG4+8UvR73bxWJtRmANCTM1GsNu5b1YSoGzn46TbbWQp0naH3yyujBLwkVZGJyE9HgeQqMyFqfvghPXojoaUEmULd9BcymCuFN/QlxaMHkllBSS6I0g51k8Qsg4gcyiTM6Urj25Pjhj4JeaXk6NsxZo+OTmNsrhRLm/xQC6/15sxQHn3cCVM1O9n4m87oQkPfvupGGvreXPwBRQmpumnHo+ccvZFYmWKVuhnIZ1Cu2aHrpiz6DH0iKyhFnM0sVCwMyoEnkaJm0RKmpL69kImfo1dVN0B7xuyt1+7BZ+48GEub/FBnHT3ZVobe69Ffc/ezuOuZzsukJJ31rjO6ztB3orqRHaEvn0lu4RHbO+WP4mlaonwCN3bxt831nDl1AyA0T+9QN/ksgHi9MXUAihqMXdMbf3sAt9aN5OjD9DM5qMfu0fvklUB7hn6+VIs0i4sC2e8B7kg1Dcbart6dMYbP3HUA//nQ0Y7bkFTG7UpA9xl6YQSkjCuKwZbBWO7RJ1XUTFI37XD0vKjZ0lA33ECG5emLfo8+xoHSv5Zt+ISpGoZ6cgCSL1Mc5n5IR8Ll6OPpY5bCf0tDX2kjGFuxkqvuKClLgA90i5UmHL0yi6xaLNLMshk8OvpVhq4z9P4yxbp59FFSwf2wmatxT7LWjQzGAgjt4anBWCBmj140zJQ6+rAJUxULgz2SukmmTLF0KErVxh6qhDQ0Ul4Z12DNVI4+0x5HL2vAqMqzOGHZKnXTQnWj9J2azY18p+1ijCUm21wJ6DpD71A3bejoJUffl8s408a4IVU3crWkSB69bYtgbHhjFwXqmrHSMw/t0VeT5Oj5f5KZsRFUN325DLImJbI4uEGEwR4+sM0WW18naWh6cu1VVm0Efz16ILoxk05OUrXsZckIQFA3TQZGlUOvWkwY+s7apT5nKUffBfAHY6Opblzqhh8r5sbBu/AIEI3isGymaMmT8OgV6sbx6Kuhvis9NPm9OGdEarsMI7yOfr5cQ18+w1fzSqAsg0FAfy4Dg4DZENfJ79HHp7pxE7dcHX17hr5Tg9oI0VQ3bhsqNRs1m3Vu6NV1AFKPfuXDkVd2oKPvFcYqiaCN9AQlRx+F4lATppIYhOQMxjR4whQQ3qMvVS3kMwaymfhT8FXVjWmEpzwWKxb68iYyJiWUGcuppMGeLGaKrQ19JTEdPV95DGjfoy9b3PAmZehlUTNA6OibUjfudZH7ddou9Xqk1E0XwL/AQRSvyaVu4vW4VKjVK6P8hi2yKmUJhGQSpvh/Ka8EwnP05aqFQtZ0qhPG6TV5VDcRg7F9+QyyphF/rRvb9aIHC1nMhjD0VV8wNl4dvax1I1U30Y6dNHWjlmnoFcHYRtSo2nbpaJRDxECaQe2PKXXTBbB9qpt2DH1vLhnttWyPQVAMYrjfkPy5STxhKhkdPT8miYQpILxHX67ZyGeMtvIDWrZLSZgKG4ytWTyI15vNRK7EGapNSgB0TUiP3uHo4/boVXllm8FY2bbEPHoljtCby8BmjX9LNcpSndPpAOTl/VOPfsXDr6NvKxibj1f+pkJ6X5mIHr2znqspqZvk5JWmQejJmjANwnxYj75mI581nIzfZDj68B59qSazUPngE389ete4DvZkQhp6r0cf16zMUgKd7eroXY8+GdWNOuuQA10j+kYNnC/ERN1UPR6991hHp4u45cmTHR1fd3SvoW+HuqnKYGz8afwSUiEha5KUQj5Y8jwyTnZo7E3zUDdE0erdlGsW8hlT8ejjp25Mce5h7qm8l/mMiUwS1I1iXNf0ZDEbYkB0SyC0t1ZCI7AA6iaqB5x4MFahuqTYYbEBHaMaYrmmQJyG3n9tvnTvc/jjLz+YiMpOF3SdoZfeXzsJSfJB7M/HO7VWIZNbtg33AACeO7UY6nuyLaZImEqSupGURH8+fL2biqRuEqiHLg07iYSpMLMZaRhkm5JZM9bl6Nvx6ONaeESVV8qZbGSOXgRjk5RXytr9MjO42CBpSqVuXI++Q45e6Y/+vrlYrqFidS7h1BldZ+hlH3FrvkeQV1alx5VMkg3Ap/wmEU5f24uMQTg4Ph/qew51E8HYRYVKkQBcEz9fDievlBy9W9ohvvZ5VpgK69FLQ581kDXiXzBbpW7W9IQMxiZYvbJOXhlVdROjR88Clrr0yiv589VIYqkOUnFx9Or3/dJTec5JlX/QAd1n6H0LXEf16HOm4SzenCh1Yxo4fV0vDo4vhP4eAJimAcPgC4/EPdX0G/pI1E3VRj5jOoYmUeomxGlLD5BTN9HX523dJjcYO9iTRblmt8yO9Qdj41LdMI+8sr1gbJyqm/d9by/e8vn7PdvUomYOddPA0Kt9Z16hbjrp796EKe85yvsWZf2FlYauM/SO9yc9+ii1bqo2chkjsiImCrjqhnf4nev7cSCkRy87vxmxkFYUyOfLMfQRShWXaxbyWcWjT0JHT3xGEyaIKWdnnLqJ36NXDZeTHdsiacqfMBXnUoL+ombtZsbGUQLh2YkFHDrldWDUomYuddPA0KsevbLAeyf6dw9H73uupUcfZf2FlYauM/QuxcG9v2iqG8vHMyeluuGvd4304blTi6EoImm4CllDKaQVb9ucEgiiV/TnM9FUNxnDLe2QgOqG2qFuMiayCcgrGVxduCyF3Iq+qTpKoPirV9Znxkbl6HnbbNY5ZVmq2nVGXC1q1sqjV6mbBYXH74RWaqa6SQ39CoS6SlLUdVkrNenRx88zq+2THX7XSD8qlo3RqWLL70l1Tk/WdLy3uHl6FsDRz0XS0ZtKIlic1I2aQxA2GCuom6wIxiaQMKVy9AAw06LejTRgSSRMyUCnTMZrl7oBOufpi1Ur0NA7qpus5OgbBGOVe6XSKZ3QStUmJRBS6mYFwjEKBsE0jMg6ejnVB5Lh6G2lpOzOkT4AwMGJ1vSNfHAKWdN5qGOnbpQMVCCiRy9LIDgccZwJU2678i0WrXDb41I3WdNIQEfvTZgCWnv00mvOt5Hj0QyqRh3gPH1YQ39wfB7z5ZrHiHbK05eqFopVy8Op27a3BAKAhoXNah6P3t2nkwGollI33QVHdSOSkqIuDq569EmUQLBs5nT4nSP9ABAqICsfikKCHr07G+Lv+/NZFKtWOGpJJEy1U365ZbuUjN3ThntwbLrY0pCp1E0SS0O2w9FLA5ozDUFBxSevlM4DwOmbsHz2L3/qHnz+7md9HHbnht5m3uOoeQetqJuKZTsOw6JifDspg9CMupEefWroVxDUNP6oqpti1UZPLtPW6k/h2+euLrW2L4fh3myogKzsjD05xdDH3Dw/dSPLICyUQ3jQNa/qJs7gp5qxu2N9H2o2w9EWdJeruuEztCR19C5109zQy8JvhhFdEdYMqtQT4ANJmOtftWzMFKs4NV/2eMtyNtQuSuL7pYp7HDVgLIPRDVU3lu3QWwuxBWMbq24cj341yyuJ6PNENEZEjyvb1hLRzUS0T/wfFtuJiD5ORPuJ6FEiujDJxgfBCcaKVZyieE3FSg29WTNReaVte6fZ29f14fBk66Qp+fDI0gRA/ElTfurGKWwWQksvZ0NJePRqu85Yz+muZ081nwXJh7cg7mcSqhs3GBuOulmsWI43G1UR1rwtrrwSEB59CJpDOg/FquWr7tiZ8kY9rttGt18ZBqGQNRonTNnMGQw8wdgOBiB5/4MGwZSj5/h3AK/xbXsXgFsZY7sB3CreA8BrAewWf1cC+HQ8zQwPNXDXn89gajFcwg/AH8SenAnTiF8LLmEpgTNAJiW1frBcjt5wuOG4qSVVsQSEL2xm2Xz1HlWxFOdCH+5atsCOddzQH5poYeirikcfMVYTBt5VnQz0ZM2WHn2xajkGLE6P3vJz9JlwtX1knypWvUv1lTr26AMMvSKvBHjSVGPVjR1I73TG0YschpxZt8yiy9EnU+dHB7Q09IyxuwBM+jZfBuBa8fpaAJcr269jHPcCGCKizXE1NgycSocG9/7CBDolilVu6JNW3agPJV8oubUnIR+anqzp8LFJJUyRIq8EWk9pKx4+XNQYSoC6MQzC+v4c+nJma0OvZMb6SyD81Q2P4DuPHuuoTf4A6GBPpuUqU0XhSADco48rxqLKK4HwHL3sU8WK5Q3GdnDvGGOe4zptVOSVAO/HzXT0Mjs9LtWNPKe+gPWgXY4+vFO40tAuR7+RMXYcAMT/DWL7VgBHlP1GxbY6ENGVRLSHiPaMj4+32Yx6WMwrXxydKoZazxPgHbM3ayZSr0VCVd0A3LNptqyahDyHQs50E6Zil1fy/36PvlXSlGvok6l1o1I3RJynP9SiRlBZCXz6SyDc+PAx/OiZiY7bpBr6MKWKpSMBILIirHlbvLPEnGmEWmFKesulqtfQN6JIZkLMjqsWc+6X2q8tm3kGo2arTFVthp6s4Wkj0Fkyl4y39eTMhhx9mFjUSkXcwVgK2BbYmxljn2GMXcQYu2hkZCS2BliKjGvnSB8YC184zPXok5NXqqobgHPIzVbbkXAMfcYNxsZO3QSUQAC8PGkQPJr1BDJjVeoGgDD0rTx6CxmDkDENTwkEuf5omKX/mkFdSAMQi4+0OCZ3JPg1NY1oy0i2aovh8+jDxCSKDTn6+u/e/+wkLrzqZhxpEU9SjbvqYMkaTxK9ObNh9cqaZTsDYnwJU0z8bsaTTGbbzBnkwuaMrES0a+hPSkpG/B8T20cBnKbstw1AZ3PkiFBlXLuEfDFsmQHJ0WcSUt0wxr0dr0cfThderFqiRg4p1E2szfMolmTbAG8aehDKAdRNvCtMuZmxAHDGuj6MTjWXWPLaO7wtquGT8YZODb1f6RLGo1+sWig41E18Hr1lwyevDMfRlyrB1E2QjPHQxAIsm+HIVIuZlPJdtV+rNfMBuZxgo+qVbjBW7eOdePRyyc6enNlwUFvtwdgg3ATgCvH6CgA3KtvfItQ3lwCYkRTPUkHlwKVCI0yFSEuM7D0JUjd+agQQHL0vuSQIpSpvGy8D4LbZPTbreCELp33CaPTlInr0AStMJdGuHev7uNFp4l1yXb/Lh0uOXi523opPbwW1lAWAUOvGlgQ1CCBWHT3ztSUsR9+Iugn67nSxAqA1faMGcr2qG39sqnkwVt47FY04+jD9S3rxvT7qRqWpVru88qsAfgLgLCIaJaK3Ang/gJ8jon0Afk68B4DvATgIYD+AzwL440Ra3QQqNdKXz2DzmkKkhKRelbqJORjrVNZUrnoha4Kx1tPSYtVCQfCWRgBHf/1Pj+BlH7itI6PqUiQiVT3fXO8sUVKyUA2DL3Uor923Hz2On3nvLR15Yy6lxN/vWNcLAE3pG1m3CIBn4REZb4iDulENV38+09IjXKzWPMHYeBcHV3T0mejUTdmynUE6iKOfFgZ+OkQcQqJU8VI36vVqtkB41baRFbNXeT5A8DPy9Ik5nP3uH7QMztdsGwZx6lO9NurCP92cMJVptQNj7NcafPSqgH0ZgLd12qhO4A927hzpC0XdyLobqkcfZ70WfjxXPSKhysgKAV6MREn5XD4w6ixg39g8js+UsFCpYUDouqPCv/BIzuQeeisD5ipc6mmJZ07M4dRCBafmK9gy1NNhu3jDNg4WAADjc+WmbXKpG05lMMZcQx+ifnzzNnmVLv2F1iWdixU3ESjO5SD9gc6wCVOqoa/WbPQXMpherAZ69HK2MrVYaXpMlZf3B2NV1U1vk1IWNYvx2IphoGpZGMhncKpWCRyA9o3NoWLZODgxjx1iBh8Enm1rIJvxJs/JYw7kMy1nrisZXZkZq3aonev7cXB8oTU1UpEcXiaRgKJsG4A6eSXQuO6H076aV4MNuOUeAPdBDLPSUeP2cX5eGg0iChVDUKkbAELOaHva08pANIO8dU7JATGQNVMDyfr4gLsQu81cr22uVOtInuqnS/rzGVQt1nTmUqzUnPttRqyoOVOs4v/852OBhcD83nLWNEJVryyqHL1lO8H3II5eevKtqZtgQ+8PXvN+FXz/qhZD1nQVXANC/RU0AE0tCEqpRb+viWNmTfIcR3r06/pzmO+wT+iMrjP0lu3t9LtG+jBXrmF8vrH3B/BpNSCoG98C19fc/Sx+7TP3xtA2b0IS4FYybKWlL3o8eu/xANdD7YR79mftApz+Cu3RC0OvJgOFNRDN4FfdhJF9yvr4gLusZNWyHY6+ZrNQstZG8MsrW+UcSH15j4ejD29U7n92El++7zAePjxd95k/CS8bkbqRi6bImWCgR78YbsBWr6lHR+/rW335DBYqwbGpms1r3chyGn35DIiCByCZEDndon9VRf0cv9RWevRr+3Ko2axrlxPsOkNv295Ov3WY87knZkpNvyc7ZU/WrPPoHzkyjQeem+p4tHeqMPp09EBrHlw1EkFFzSTn3An37A8w8vaF8Ogdjp63L6tw4tPCMETJUA5qF+Cet2kQ+nJmC0PvpW4Afj9VeqWjQdF3rfryzesClWs2bIZAjv6e/RN45YfuaOjhAm4yT9Ai5EHVK8MYLPW+zhRrTsmLQI5eBGNbGVQ1GFvyePReB2eoNwvLZoGSxprFkDHcwH4uYyBnGoHnJAeeVh59VdBB/qxh16PPA+henr7rDL3lC0wNhEz6cQx9gLxyarGCimV7Sqa22zYAnrokDnUTIuBZyHmpG4+hF0arU+rG79H3h+AuVR29bJ+cDcVB3TgJU4Z6X7OOdx7cpnrqpmbZnn4QdlAcnyt74gF8TVQfR59vXi7CKUoX4NE/PDqNgxMLTfM9ZLuDztn2ySvD3DO1TQCfEfbmTRA1UN2EDMaq1JWHo/fJK4d7c/x4C/XHc7xv4bHlTAP5TANDvxBuAKo6y4R6k8nkoLa+n7enWyWWXWfobV/JVpfPbV1wCvAWDZMe16ToTLJTtd02pQqjhPTwGiWPSJSqFgoZn+pGmfrPONRNpx6919D35jIRdPTCg1apm8UYYgd2/UxjoMUyh6rqRq2R7zH0Idv0Z9c/jL+84RHnvT9mALQ29LJ/9Xp09HLWw9txcrbxrNM19I08evf9YIEvVt5qBlr0ePRVx6AGyRhnHIqkBXUjjmmQ9/jM17fW9nHDOhlwvJrNkDG9qpt81mzg0Yfr9zXLRsYk5HzSUznYretLPfoVBX+BJ+nRB015VajySrlknf9BnOzU0Aeobnqy4Tx6NX0+aClBl7ppfJ6PH53BZZ+4u2FnDjKofXkzhEfvpW5MJRjrUDchrt3tT4/hp4f8ZZWCB6CBFiqXctVWOHq3SJ064If16PePzXvKIvvVSQC/TkBjj9CpVZSr9+hlv2rX0PtnsYM9GdgMLWegKnUzX641pEhqlu1QLK2pG37Mod5cnepGvYfDwtD7+4VtM1i2oG7Efcs77QoIEov+1WqmUXWCsd5ENXmu64RH361a+u4z9ISLOacAACAASURBVD4Z12DI1X/UFZwAL4cqH8RODb2/xAAQhbpRAnk+jt5WuOdm5/ng4Sk8MjqD504tYKFcw+d+dNCju/dn7fL2NU5skXAW1HA8ev4wqRxsGI7+/d97Ch+/dV/d9qB29UeibtwidfPlmqP+CMPRV2o2Ts6VPNRTMJUkSzo3MPQVL3XDS2jzA005hr6xYMDl6L3nHEQjDYQsm+yvAZUzgz1n6Tz0ZE1MLzafKZTEd4d7s/UcvXK9JHXjp/RkBmvWJOe+5TMm8tlg6mYyNEfP8wSypgFL9E1A8egFR9+tEsuuM/Rcaua+l1Pqlhx91T+15jyzXBYNiMHQB6huwlI3HtWNLzOWSwX5tmYdXnpjUwtV3LL3JK767l48fmzG+TzIc+7LmyFUN155peTo50pVp12tpvwAD/jJa7xQrjm/65cyAlGpG3cxlPlSDRsHuA6/FZ0HAMdnimCMD1RyUPSXigDUYGw4j94gxdCLa3MilEfvN/T8vxlIV4br8xK5Bp6zvHfb1/WiYtlN1UpyQBvqzXkcBL+8cq0w9P5nSsZ2pPct25XPmIGUkuT4W/WvqiXWg1YUWIDr0a8XM4xW12ylousMvd+jNw1el77VNN3lUPkDmxEjv+pxdBJQBIJVNz0h5ZWlql2XMCUNzmxIOkIOApOLFUzM83M5Na96qkGqm9Yevbo+KyAzUZlnmt9qag3wgUh+5x1fexh/dv3DAOqn/QAwWMg0palU1Y1a0mKuVMOWIW7oW9F5AJyF2y3b5febcvQNjlms4+jdGaOc7Yw1MfTzDagbf9YwwKkboDU1tVipOTw4ILnweo5e3ju5FkAz+qYkFqCRpT0kbLteJGEaVPdMSUOfUXT0jYKxVYVSarUwe81myBico5ffBVwnxfHou7SCZfcZ+gCvdLCF9we4htYxDgZflUj1OOKiblT5pxxYipV6b8X5ns1Qsey6hCk5cKhefDM6YloJqE0ucJpgQskv8A+SAK/fvVBpnkhSrnFvSdIHco1WaSB6c2aojMpyzXb2Ozgxj2dOzvHz9EnzAE5PNKsfzjl6r+pGGoZ1/XnkM0aoYOyoUsRLti2Qo8+FC8YWAlQ3sl+F8+hrmFyo4IrP34+Ts6W6gm9A+BWvilXbCYoC3KAGcfQyELt9PZcqN7uXZVGTyV9v3k+/GQZhqCdbR+mp1I3q0ecyRp2OXrZjIJ/BTLHStI9WaraTMAW41SylHNTh6JeoJn3NskOXT48DXWfo7QBjNSBUCM0gdeqyM0oOdUqRf3Xq0ftryQD8gc9lDCdhKwhOieIGtW6k52Ya1PQ8Z4purCEo7uBP6weA3nwGjDVfdUilSQD32rlT/r6WQTz5+WLFQqlq4dR8BcdnSqLip3faD/CHu1S1AxODGGOBqhtJJw3kMxjsaV5W+NN3HMAX733OE4SdrDP0XsPVlzNbyivdGSP36GuWWzK5GUc/V3apm0eOTOPOZ8Zx37OTzmAfGJdqWTa55nDlgKRIgjx6ft5nCI++WfIbpxgN9ORMjyELcsCG+3J1wVjHozcMr+omwKOXfWbH+j5UreYJcDWbOSUQgHqPfrg3h7V9Odzx9PiSZMd+6IfP4E1X35P470h0naFXFx6RGOxp7dHLEsUSvM6GS91kTerYo1cXuVbRbLUdIIjf5dslZyyN+5ahQtOH2+XoKw5lc0o5pyAuvC+gLrgfauATcGdDM86UvxfTi5WmBdekMQG4bn2mWBUefrWufhHQPD+iZvNy0CqVxLfbmC/X0F/IcOqnyezn63uO4Oo7DuCIYuilUZKn4R8Um2URL/qCsabBqcGZIo9jDPVmMTFfbpjRqiZMySzvY9PFwNnFoFSatVrxqmp5PXrBhfs5esejF4a+WWC9VOOxpJ6sl7oJ6ltre3N1z5Q8/4xJzkysEUcvvytr3DRzJvzafPk7pSrX15sG4e2vPBP3HDiFO56ObyGkRth3cg7PnJhfspIL3WfoA/jcgUK25QLXauYpAGdh8SnFK50KSO6I1DZlPVsVvU0q+QGqRx+cMCUf6NOGe5t69NNO8lLVeUhUjt6/KApvm8jcbcJdqrXfAT5ISiMG8AfRZs0XdlC9RLUInTRmQdQNEBxQ9cs9s4ZXRz9QyPBZXpNBcWKujKPTRdx78BS2rOGcvrxmLMC4Arw0Q0PVjW+wzgjqRvavszcNgDEvlaZCDcbK5K1j08VAJVdY1U2xYtcZ+lygRy8Nfa9439jhKVb4cyQX1Dk2XcSjo9OBz+VQb7bOOMu4RVbV0ZuGUN0EB4nPkO1qaui5R+9y9Px31FIZv37xdpyxvg/v+97exA3wxHwZFcsOFSeKAyva0N/0yDG8+ep7PIlDQQHFVt4b4F3PE3DrtciH+4z1fYHJHa1wz/4JnPf3/4WphYrTTr8n2NNktR2g3tD7E6akwdo23BNOdbPoUjenFlzDEkTdOPrwph69+7AAfJCsWm4wdofzIDa+fmqwdv+Ya+hPzJQC29Ws3k3ZR3VJj36uVINlM/Tns5y6aXCtSlXLMdjHZ0o4b9saACpHz/cLzCJuKK90JYryu9zQ8zacvWkQgEvfPH1iDken+WyCMeYEY2dLNWcwODZdBJMBfl+Z4kLWaLliUrFSq+PoG1EkA4WMs2/zYCyPjXDqxsYHfvAUfu/aPYES2bV9ubpnSuZf8BIIikcfEDuYUqgboLnirCqrVwZ49NIhyGUM/PpLTse+sfmOEvzCQIohmlVgjRMr2tAvlGv46aEpHJtWklnsemqkVbo8wD2uXsXQZw1eznRqoYLBQgYbBvJtZcY+MjqDuXIN+8fnA/lUIAR1IytrNlDdzBSrIAK2DPVgoWIFru7EGHMM2+RCxTEWqkfPAmgvtxZPNOrGEqqb/nwG64WiodmUv5FHf3ym2DAzFgg29CWfRy/VG9JQS+qmEZ3n96rP2jiAnGlgUszogugSgAdkm8krMyIeA7gBazngPn8zN/SyJtMffekBXPWdJ/n5VG3UbIb+fAaVmu3096PTbjC2jq5sEZeSRdYGC1lvTZkAj36mWMVQbxaFrIlC1mg6YPN8DwM9Wb6S01PH5zAmjJn/eg335TC96A2iyqzVrEnOfcs3UAPJaycppZkmM42aoG7kMeWxyjV3nQcA2DrMS2kfb1EbqxMwxhwHKzX0IbBTjOSqYQhU3fRwKV6z6dhixUvdSI9+arGKtX08UDPVgmcOgsx2PDpVDFTdACGom1p9nRTA9Sxni1UMFrIY6mmsn1bXBR2fKztTRpUjtYI4eifjswl1U/NRN6Ie+nSxgjU9WQzJuiZNPXr3M9WjPz5Tqis9DTQvbSE9ejnLyArPUA7Ug4XmwVg5+K0THuy24V4M92UVjj54ZtbfZPCo619OsF9QN5sHAABjcyXULBuHJxedBXMk7ShloXK7l7rx/l6rYHPFcousyXY19ugrGOrh12K4N9fco6+6HD0A7FeeTT/9NtybRdXyFppTdfQ5n44+qF2FrIFNglqTXvg/fPsJvP2rD3n2lUXN6uSVPtpRHqtVEcROsFCxHHFDq6q6cWFFG/pdG/iasOoKUo1UN1aLsrR+6iZrco9rarGCod4chntzsFn06pCywxydLgaqbgBeA78ZdeMWXJMJSXy7S93UMNiTcdQWQdNO+XAO5DOOh9WbMzExX3YGwKCiZqE8+qpPdSM8+lnhCQ71Zj1tCML0YtUxVvuEoR8oZIShr29XM4/eX3vH9ej57/fnM8Lj5YP/ydkS/vn7e52HX3r0bzh/MwBg29oeDPe6NEOQjl4etxHFVar6g/2uIwHw9Y0zBuHETAknZkuo2QyHJxc9i6XIhVtk8bOZYtX5zD/otKIr1UxwWSyvmUe/RvStNT3ZpuozXpPJPaZKq/qpGyc7Vol9ybIjfh19LlPP0U8tVrG2N+e0Tfavnxw4hbv2eQOq9dSNy9GrC/5sFobe79FXajYePzqDOHBKMe4TqUffGuv6chgsZOo8+sbeX5OO76NupM55cqHiePRAay39c6cWPF6m1EaPThWbqG6MpglTcoCSVAT5qBvp0Tv66YDBSD4EZ4y4q/Ds3tCPcs12FCFB6hZn3Vjh0V995wH8wRf3ePZR12cFvAlTQ73ZhununvYV+cypL8fT7DMG4XkbBxzqpk5eGSUYKw29uHcDhSwGezKoWDbKNRvffuQY/u3Og3h0lNd6l4b+t192Bj74pvNx8Rnr+IzO59HXBWPzmaYJU/4YkCVUXYWsgb58BhsHCzg6XXSStIpVC+PzZeeYm9dwQ1+xbMe4SZ1/vdKsuUevZoI7Hr1Ut/iov4n5ilObZutQD45ON/Z2S1XbM0tQ4R8Y5TOl9gtpgLMGubVusu5MQ52VTy1wJ6xPVJydEYXcDk8uYloRHPDj2p4Ab83D0btmcKQ/D4OAEzMuHQwA33xwFL/0ibtx3Le9HajUYOrRhwARYdeG/jqPvpH314yzVEsMAFJeaWN6sYrh3pxbhKmJsWKM4fJP/hj/8sNnnG0OdaN49EHKlmazjZJPseGvdSM9rjW9Um1Rb2wcLbSy3NrujZwukFRFEBfurhvLj3nzkydx694xjwyw4qdulISpoR7ucRE19+jlOcjrvK4/hy1DPQ51E8mjdwZGyYcL6kZy9PmMM/iMz5UdqujJ4zxBSwbKNq8p4FcuOg2mQRhWAoeNgrFcXmlhvlxzAqkSfupGevSTCxWnLbs39mPfyXnPoueHTy0657hVUDcAcL4IEMtBoV6A0JyjV2vvqNSNPzGpatk4Ol3E9rU8oH7a2l4cPtV4xTa5trF6rvI++NsoKT01IKtmxkq1VM40kc8YYMy76tvkYgXDfVkQEdb0ZDFdrGJivuI4LqoD6KwwJdpSsVSO3uukjAzk65LX9h6fhc14kDwIP3j8BH6kzCJKVQsfvvmZwLyKCSUulnL0IbFzfT8OTrTw6J0EkvAevUz64Q9iVqnNUUXNsvErV/8ENz950nOM4zMlTC1W8dAR7hlaNnNokqNTiy6f6vfoQ8orGy0lOFvyevSSuvm9a3+Kr+85wrc5ChjX0D9vI6e+ZGAosNaN9OgrFmyb4ekTc6jZzFM7vS5hStS6mV6sYk1vlhvK3pxzLYIws1h1KDKAl43dvKaA4zMlWKzeY82aXFkS9CC5a9j6qRvp0Wdw1iY+yD15fNbJwH3y2CwA/vD15zMeA7C2V/HoHfWU93cHCnyW8N7v7sUv/evdHtqiWPV79AYsxpPK5DmftXEA+8fnPdf28OSio6FX19x94WlDAOAMCkFxqWYz2MUG1E0+4y3jOzrFHRQprdy+rhcLFQunFir45+/txfu+t9dz3FLVQj5jOs/SQD6Dc7cMinNu4NGrnrdD3bgevZxpAO69ZYzh4PiCE4hd05vFTLGKw8ogeVAx9BWlTDGgUjdeJwUANq3pqaNupDOpxo8kGGP4+5sex4cUB+/WvWP4+K37cPOTJ+r2l47VyEA+NfRhsXOkDydny84Uni8l6N3HLVXc2MNZrNTqgrFzpRqKVQvDfTkM93EjOrVQwf7xedx/aBLffuSY5xiyEzx1fBY1y8bEfBmWzdCXM3F0uujWuvF79E0WSgbqK2vKr7sJU5Kjd8/zxEwJt+wdw/cfOw7AlS829egDuPBC1gARsCi8VGlY1Q5fp7ox+YLi04sVZ4B83sZ+7D3uGlL/wOYGbvl1Xtefw+Y1BVRqNk7Nl+uMKgD057M4NlPC5Z/8Me5/1i1vXE/d8G5+asE19OdsGoRBwBNHZ5yYwJOifacWKs5CFBLDfTlMF6uwbNaQo5fJZbc/NYZTCxXnfAF+D73UIDzUIL9GA6jUbPxo/wTW9+dAxPl4P0cPAOduGYRpkOLRB2SDlxpXmix5qBt3gY9chicKyr51aIIbONlvThee/eHJRXzr4aO44YFRz2+UBXUj++rOkT5H/uiPI6x1KD2Fo3eoG4WjF7EDfnze7hOzJcwUqzhHDNhDPTxYfnjSnd2rM/2azfhi9+KYjxyZxn88OOoMTCo2DxbqgrFy0FBnCRLHZko4OVvG/pNzznWT5bYfPzpbt7+kbs7eNNAwbyJurHhDv2uEe6XPig4ZRN3ITMGx2RI+96ODdTUmbJsJbjHjbMuahpP+PtKfx/r+PLIm4cD4PB4d5UGZBw9PeY4jjV+5ZuPA+ILTWV54+hBKVdu5qX7VTY8oANXwoax55ZX+hCmHulFKMsu27RV0hJq8BPDBcNd6fu0mFU/V8LWNiLhssGLhKWXaqnZ4WetGImMYmC3VULMZLtzOPc8XbFmDvcdnUbVsXP7JH+NPvvKg53emF6sY6sk6Rm99f94JjB2dLtbdU4Df1x8+cQIPH5nG9T89orTHT93w7z47sYD1/Xms6cmiJ2di10g/bnt6DHOlGvrzGTx9YhaWzTAxV3YkoRJre7NgjF9Hh6P3Xat+MaOS0/57D55yPvMn5MnM2MkFl/9+nhh4HzkyjZ3r+7F5sIAjk4qhX+Ma+g2DBWwaLDTm6Atc0dKodIWTqZsznYC76jlLr14+V7LfSM/+4cPTODlbxuRCBYfEDETWZCpkTGf2smukH9vX8u+aAQ7Y2r6c5zlydPSK9y3VQGq7nhL9+mwhS929YQBPHJvFoYlFEPHcDdlH1Rr3ctD/xO378Zc3PIrJhapHXglw5Y1q6BcrNRwT7w+MLcCPB5/j7V+oWA5lt+c5buifOFYfwD01X8ZgIYMta3pSjz4sdongohy9m0nxrr3nOVz13b34zF0HPZ9L+aI/GDtXrsE0CJeePYJC1sQF24Zw77OTeEwY+tGpIsbm3A5xYHze8TyfODbjPPAvPn0YAJxpZb3qxnRK4e49PuvhaAHXo3fKACu1bmZLVRSrFoZ6c+jJci5zdKrodL4TsyWcmi9jepGvICQlesO9Oawf4AZmogl1I6/LYqWGp4SHOtyb9Xr0PtWNvP4Zg/CSM9YBAM7dOohyzcYPHj+Bo9NF3PrUGO7eN+F8Z0bQPC51k8OZQlV1eHKxLq4BcEMhvfc7nh5zqBL/GraSAmAMuHjnWsezfMHWNY7H9QvnbkKpauPZiQVMzNcb+mElGC+H43rVjdczvPegO8vgwVjXkZCDz7GZEkbEb525od/pP9vW9uD0db14bnLRmUVtXOO2aaQ/jy1DBYfm8V8edXZXrlm44vP345797vUuVgM4eo/nzK/hoVMLGMhnPFJTAPjBEy4lIfuaWpOpx+PR8+/4KUvDIPzSBVtw85MnHWrRo6NXEqZ6RXVQqdCRToccHC/euRYzxSr+64kT2DRYwDmbBx2b4BRKy7iDB8AHpon5cp1Hv2lNAXPlmsMSyOMM92Y9clHn/JWB6pmTc5gv1/DksVmYBuGJo7N1kuyJhQrWD+QxMpDHKSWRMkmseEN/+rpeGORebCuwLgo39HJqfvWdB5ySsB+7ZR/+8ds8MUX1uGR0/uW712ODqF9+yc51ePzoDO49eMrxnh98btr5zv6xeZy/bQiFrIHHj846gdgLt3sNfV1Skvjd3/nC/Xjtx36En/3g7fjWQ0edz0vCkMrzclQ3NsM9+7nXeNH2YRAR/sdZG/C9x47jp4cmHeO79/gcZooVjyFd25dDby6D3pyJySbUDeAGGZ86MYfT1/biBVvX1FM3ilckr90LTxtyyve+YAsPHspBdn1/Hld990lYorDXXLmGoR6Fo+/PY9dIP87c0C8W1qhrlnNfd4704dRCBY8I1Yyfo1dL8V5yxlrnteSOAeCyF24R12qWG/oBL3UjZxrHZ4oNdfSyJj0AvPqcjfjpoUnsH5vDDx4/ITz6+sGQALzlpdsB8AHfCXoO9+L0tb2CuuFeZz5jOgt4r+/P46U71zl0VP0s1p3d3f/sJO58ZhyfvvOA87ka4C8ohl46OzJAeujUInas73POtZA1sWmwgD2CmshnDOfZU4+5eaiAnSN9eNmZ6x0e3X+9AOCNF25FpWbjO49xGlTV0asJUy8SMYmfiFnSUydmsXWox3kOL965TmznfXTnSB8OTy6iatmKksf16F+8fdgZbP0evZxJyuf3oJjVvPqcjZ6CgBIPHp7GOWJm8fTJOTx0eAo2A15z7ibMlWs4MuV13Cbmyljfxw29vxR6Uljxhj6fMXH5C7fiup88hxsfPlpX9xrgN1I+7K86ewOqlo2//uaj+Mp9h/GRW57B18S03x8sA4D/+eJtzraLd66FZTPsG5vHL79oK3KmgYeU0fzA+DzO2tiPczYP4vFjMzgxU0LGIJy/rXngTP7uI6MzeOOFW3H+tjX45+/vdTx5vwZbTZi6a984+vMZZzD5ny/eJozeDH7xAtd4SWokaxqedPa1fTmHUgoqHwEoHv2JWZy9aQC7RvpxYHwets1EpUgvRy+v3X87c72zbedIPwpZA48dncH2db149xvOwVMn5nDnM2NOkHyoN+vEQtb150BE+MXztwReM8CNvbz38vNgGoTb9o4BCKJu3G4uDQIAnCsGn+HeLC7euRZZk/Do6DSmFqvOGqIS528dwnBvFh+5+RklH8LbHjmonba2B68/fxNmilW8/uN34w+/9ABOzpbqVDcA8I5X73ZoEcD1ULcN92D7uj5MzJcxNld2BrWBQgb9+Qx6ciZ+86XbHQ+1sQChilvFdfnx/gmcmClhsVLzFFmT+Rk508DLdvF79kPhsR+aWPC0D+DOlc2ATYMF/MyOtXjwMB9g5SyhkDExWMjitj+/FC86fRi7N/Rj50gfzhQ0q4rztq7B7g39+MYezvWrOnq1euVpwnjf9QxXtjx9Ys4JqANc9nnaWk5tbV/Xi10j/U4uQk2ZJWwczOOPLt2FD735Aqe0Rd4nBd00KJOm+HNxUMzUX3XORgDANx8YxZXX7cHYbAmlqoUnj83gFc8bwZY1BTxzYg4/PTQFg4DfvIQP4E8c8/L0pxYqWNefw8gA72NLwdMnYuiJ6DVE9DQR7SeidyXxGyre98bzcPEZa/EX33gE43Pluk5PRM6D8tsv24G/fd05uGvfBP72Px/DhacPOeoT9UHsz5tY05PFq8XNBbxewIu3D+PcrYOONzMtFvM4c0M/zt0yiL3HZnF8poSNgwUM92bRmzMdVUedjl6Z0v/RK3bh3W94Pk7OlvFvd3EPbGKhgoJiSOX0+sjkIu58ehwv3bXO8VQuPWvEmWa/+pwN2DiYx5PS0ItA56bBguO1nLVxAD988iQeHZ1uSN305TIYnyvj2YkFnL15EGdu6MdixcKP9k84qh6VupEP6Mt2uUbVNMjxel525nq87rzNGBnI48v3HnYyZlXNvQyGvuGCzYHXDODUy0vOWItLdq7Fi7cP49qfHMKbPn0PfiQoIb+Ofm1fDrs3uMbm+VtcfjefMXHe1jX45oN8JrV+wGvo1/Rm8e43PB8PHp7GtfccAhCcMAUAF2wbwiU718EgLkfcIQyjep9fefYGXPnynfj9n93pOYY0Xvx73MDed3DS8eQHClnn2mwYKDgzkaD6TgAP1N/61EmcvWkANgPefePjePE/3YIP/uApAPU6+tPX9eKCbWvw7UePoVKzMTq16BQNk5AB2XM2D+DC04fw9IlZzJdrTjwg7/OQ+/IZ3Pbnl+KlSn+QICL81ku34+Ej0/irGx51jpE1FOpG9O2X7x7Bfc+ewlypiv1j8zhbMfTA/2/v3qOrqO4Fjn9/J2/ygLyBYAJ5EWIBIeEVFLSKeq1eCxda2sK1PuBSqaJd7e31Vm2xVVy2dq1WK9JFFbuWCvUW0BZqVESLSIXwFAIYQJT3IxAwJEjI+d0/Zs7hnLzISRMa4++zVhacmT177znJ+c2e3+yZAyPcNGFmUjfy0px1K3cc9aeDwsOc70z48Y0F9EuJ9ZePDm84ovc9BsHJt+8+doY+iTH+M8BHl2/njfIjzFq4iaUbD1BXr04c6RlP+aHTvLHtMIW9Exia1YNwjzS60arSTQ36Av2lyNO3e6AXkTDgd8C/AYXAt0SksL3bCRQdEcbcKUXER0dw5lx9sxfuYiPDGN4vidtH92PJ3SV8o7gPT397KI//xyASosODph7ef10+r8wYFTTFrltkuH/+8qA+3SnOSmTTvireqzjuv/CTmxbHyOxkPvv8PMu2HCI9IQoRoSgrERG4vjA9qB24kLop6BlPXno8w/omcfOgXvxmRQWzFm5k2ZZDXFOQ5i8fFxXOrVf05vn393KgqpYx+an+dRFhHm69IgMRGJqZSGGvBMoPnqaqto7u7m3sz04t4oGbBgAwZ8JAErtFcseCdXx6oqZR2gucufSb95/CqzAyO8l/Afy259by4z9/CFwYXYMzQyMruRtD3GsTPr4PyuicFCLCPHyjuA8rdx71p9S6x0RQ0DOehOhw/wc1JzWOr2QkNDq9Bph5TS5/+q9RiAgzr8mlOCuRg1W1vL3DGcH6Doi+L3sf0S8pKH3QPSaCYX0TKcl1PvD3XZfvPy1PbTDrBmD8kAzG5Kfy4gefOvU2WO+bFz40M5Fe3WNYOnM0i+8uYc6EQcCFvDk4M57+96YB/gO0T0lOCkmxkeSnx/PVgjQyk7px+PRZ//vrzEa6cFF2+phsusdEkNEjOBj7RvRr9lSy70QtU0dlUZyVyJvlR0hLiPLPwopukKMHuGVwb7YeOM2qimN49cKzZHx86aXC3gkU9U3CqzDv3d3Mc1NDvjx+a00dmcWsa/N4Zf1+flm6E3BH9OEXcvQAY/NTOVvn5fnVeznvVf+FWJ+R7tlaZnIsl/dO4Or+qTxRupN1HzuDscgG7/WIbCeN13BEn5bgBOBF6/Yxf9UeNu07SXZKHBk9YoiOcB6jMO2qfqzZU8n/LP6QgRndGZ2bQv/0eD46Us2Ow5/xvbG5RIWHkZcez1vbj1C29wSl2w6zYvsR54wxLtJ/HehSBPrwixcJ2XBgl6ruARCRhcCtQHkHtOWXFBvJQzcP4P5FmxvNagHnlHhEv2T/0kgOHQAACJpJREFUKG9Qnx48MdFJqfTuEcOmh68PCnJpCdGkJUQ3qufGr/Sk8sw5MpO6MW1MNqsqjnP7grX+6Wc5qXFkJnVj9fDjvLx2n//ZGX+8Y7jzfbZNBFJfWsZ3yz3AryYNpq7ey6ubDjI6N5nZ/3550DYP3VzIux8do6qmjrF5qUHrfnB9PuMK00lzL0qt3HkMj8DAjAR/HwP38493Due7z69l34laMgKm8Pn0T49n19FqHh0/kJKcFE65z/8pyUlmxtgc9p+sYXRAmmbC0D6MH5LRKCd7VV4qf9l8iBJ3ZDd5WCbPvLOb2e41ku4xEeSlx7PlZzcEbffMt4sa3a3Z0Nj8VMbmp7L7WDW3PPUedfXeoLOA743NYWz/1EbbvTKjxP//MW4d7350rNHFWHAOGE9NHsLEZ9+n4mh1o/1LjY/ipWkjGOoe4Hwpu1E5ySyaPtL/hMqWjMpJZsND4/yvHxs/kCl/+MD/tM7Hxg8MKp+XHs+mh8c16ktafBQxEWH+ayJfLUgjLy2eZVsO8t83FrB613He311JVLjnwjx694PztUG9+MWy7Tyw2DmIN5W6ARjQK4Erc1OYMCSDp97eBcCsa/Moygo+wF+MiHD/uHyyU2N5+NVthHmEqHAPY/JSuG1UFunu53BEdhKRYR5+/eZHREd4GJrZI6iecYXpTCzqw5W5KXg8wpOTBnPTb1cx053hFR0ZHNCH9U0iJS4qaMoxOAe//xyVxbIth/jFMuc+gUlFl+HxCDOvziUrJZZbBvUiNiqciDAP08dkExHm8U9Xvm5AGjcN7AnAtKv68eDSrUx8dk1QG8nuiH54vyR/tqFDOd8i334/wERgfsDrqcDTTZSbDpQBZZmZmdoevF6vPrasXN8qP9zkuvp6b7u04fVeqOdU7Tm9f9FGnTh3td63cKO/jbrz9frTV7dq6dZDF62zquac3vvyBj1yujZo+fl6r76+9ZBWn61rcrsV2w/rT1/d2mLd5QdP6Z0L1ukTr2/XTyvPNFuu+mydPv637fp/Zfsu2l9VDXoPQtFwu1+V7tCJc1frnQvWNrufoXpz22F95C/b2rTtnmPVes9LG/TM58335cDJGv3+Sxv0wMmatnYxJE+/XdHq30ugQ1W1+vjftuuc5dtbLFd+8JQ+vPTDoM/HY8vLdeLc1TrthXVae+58UPnjn53Ve1/eoFVnzqmq8zt9+u0KfbJ0R5v/LnyOnKrVf+w+3uz6362s0NmvbdNPjjf/txzok+Nn9IX3P9aXP/ikyd9pS/31er16ovpzPVH9eav26+jpszrzxfV6sCr476Kq5pwu2bBfy/ZW6l83H9S7X1zf4mcxFECZtiIui7bzA/ZFZBJwg6re5b6eCgxX1Xua26a4uFjLysqaW22MMaYJIrJeVYsvVq4jLsbuBy4LeN0HONhMWWOMMR2sIwL9OiBPRPqJSCQwGXitA9oxxhjTCu1+MVZVz4vI94FSIAx4TlW3tXc7xhhjWqcjZt2gqsuB5R1RtzHGmNB84e+MNcYY0zIL9MYY08VZoDfGmC7OAr0xxnRx7X7DVJs6IXIM+KSNm6cAxy9a6tKzfoXG+hW6zto361do/pl+Zalq42d7NNApAv0/Q0TKWnNn2KVm/QqN9St0nbVv1q/QXIp+WerGGGO6OAv0xhjTxXWFQP/7f3UHmmH9Co31K3SdtW/Wr9B0eL++8Dl6Y4wxLesKI3pjjDEtsEBvjDFdnAV6Y4zp4izQG2NMF2eB3hhjujgL9MYY08VZoDfGmC7OAr350hGRd0SkOOB1XxHZ2o71x4nIPBHZLSLbROTvIjIihO1/JiI/bK/+GNMhXyVoTGciImGqWn8Jm5wPfAzkqapXRLKBAZewfWOC2IjedCoi8nMRmRXw+lERuVdEfiQi60Rki4jMDli/VETWuyPn6QHLq0XkERH5ABgVQvuXi8haEdnktpXnLp8SsHyeiIQ1s30OMAJ4UFW9AKq6R1WXuet/ICJb3Z/7Arb7iYjsFJG3gP6B9YnI6+4+rhKRgtbuizE+FuhNZ/MH4DYAEfEAk4EjQB4wHLgCKBKRMW75O1S1CCgG7hWRZHd5LLBVVUeo6nshtD8D+I2qXuHWuV9EBgDfBEa7y+uB7zSz/eXApqbOIESkCLgd50AwEpgmIkPc5ZOBIcAEYFjAZr8H7nH38YfAMyHsizGApW5MJ6Oqe0WkUkSGAOnARpzAd737f4A4nMD/d5zgPt5dfpm7vBInGP+5uWZaWLYG+ImI9AEWq2qFiFwLFAHrRAQgBjjaht27EliiqmcARGQxcBXOgGuJqta4y19z/40DSoBX3HYBotrQrvmSs0BvOqP5wHeBnsBzwLXAHFWdF1hIRK4GrgNGqWqNiLwDRLurz7aQl68EEgNeJ+F+w4+qvuSme74GlIrIXYAAL6jqA63o+zZgsIh4fKmbwC63sF1TBx8PUOWeRRjTZpa6MZ3REuBGnJF8qftzhzvCRUQyRCQN6A6cdIN8AU46pEkiMidg5P8OMEUuDJNvA1a65bKBPar6W+A1YBCwApjotomIJIlIVlPtqOpuoAyY7atfRPJE5FacM5Cvi0g3EYkFxgOr3OXjRSRGROKBW9y6TgMfi8gktx4RkcGtfxuNcdiI3nQ6qnpORFbijGbrgTfcPPkaN3ZWA1OA14EZIrIF2An8o4VqB+IEbnDy3gXAZhFRnMDsG61/E+cgUAccBh5R1RMi8qDbDw9QB8yk+e85vgt4EtglIjU4ZxA/UtUNIrIAWOuWm6+qGwFEZBGwya1zVUBd3wHmuu1HAAuBzS3spzGN2PPoTafjBtMNwCRVrWinOktV9Yb2qMuYLxpL3ZhORUQKgV3AivYK8gAW5M2XmY3ojWkj96Jtw1kwU1X1w39Ff4xpjgV6Y4zp4ix1Y4wxXZwFemOM6eIs0BtjTBdngd4YY7q4/wdxi+0ZdFq7gwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x256513381d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gp_by_yr_m_code = sdf.groupby(['year', v.value]).count()\n",
    "#gp_by_yr_m_code.reset_index(inplace=True)\n",
    "grp_code = gp_by_yr_m_code['City'] #city column contains count for each column grouped\n",
    "grp_code.plot(x_compat=True, title='Count of Commercial Permits over time by permit type')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "aa7b8061867e448ea3b3ae429125342f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>interactive</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "interactive(children=(Dropdown(description='x', options=('-', 'ASSEMBLY BUILDING', 'BANK', 'BIOSCIENCE', 'BOARDING HOUSE', 'BUSINESS BUILDING', 'COMMERCIAL MISCELLANEOUS STRUC', 'EDUCATIONAL BUILDING', 'FACTORY', 'FENCE', 'GARAGE', 'HOSPITAL', 'HOTEL', 'INDUSTRIAL BUILDING', 'INSTITUTIONAL BUILDING', 'MERCANTILE BUILDING', 'MISCELLANEOUS STRUCTURE', 'MULTI-FAMILY DWELLING', 'MULTI-FAMILY SENIOR CITIZEN BL', 'MULTIFAMILY DWELLING HIGH RISE', 'MULTIFAMILY DWELLING LOW RISE', 'OWNERSHIP UNIT', 'PLACE OF WORSHIP', 'RESTAURANT', 'RETAINING WALL', 'SHED', 'STORAGE BUILDING', 'SWIMMING POOL', 'SWIMMING POOL & FENCE', 'THEATER', 'TOWER', 'TOWNHOUSE', 'TRAILER', 'UTILITY, MISCELLANEOUS'), value='-'), Output()), _dom_classes=('widget-interact',))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "from IPython.html.widgets import interactive\n",
    "\n",
    "items = ['-']+sorted(sdf['Use_Code'].unique().tolist())\n",
    "def view(x=''):\n",
    "    if x=='-':\n",
    "        return df\n",
    "    return sdf[sdf['Use_Code']==x]\n",
    "w = widgets.Dropdown(options=items)\n",
    "interactive(view, x=w)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](insights_images/imageB.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "EDUCATIONAL BUILDING\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25650d97550>"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x25650d97be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(w.value)\n",
    "cf = sdf.groupby(['year','month', 'Use_Code']).count()\n",
    "cf.reset_index(inplace=True)\n",
    "cf.rename(columns={\"City\":\"count\"}, inplace=True)\n",
    "cf[\"time\"] = cf['year'].map(str) + cf['month'].map(str)\n",
    "cf = cf[cf['Use_Code'] ==w.value]\n",
    "cf.plot(x=\"time\", y=\"count\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 609,
   "metadata": {},
   "outputs": [],
   "source": [
    "map2 = gis.map('Maryland', zoomlevel=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 610,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ab8b6f39096849bea2bd920cac74876e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>MapView</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "MapView(basemaps=['dark-gray', 'dark-gray-vector', 'gray', 'gray-vector', 'hybrid', 'national-geographic', 'oceans', 'osm', 'satellite', 'streets', 'streets-navigation-vector', 'streets-night-vector', 'streets-relief-vector', 'streets-vector', 'terrain', 'topo', 'topo-vector'], center=[38.81819928400006, -76.15872999999993], zoom=12)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "map2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](insights_images/image16.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](insights_images/image17.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 611,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\priyanka\\Anaconda3\\lib\\site-packages\\arcgis\\features\\_data\\geodataset\\geodataframe.py:351: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self['OBJECTID'] = list(range(1, self.shape[0] + 1))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 611,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vdf.plot(kind='map', map_widget = map2,\n",
    "        renderer_type='h', # specify the unique value renderer using its notation 'u'\n",
    "        col='Status'  # column to get unique values from\n",
    "       )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The bright yellow areas are where there is a high concentration of permits. The highest concentration areas are in the southeast and northwest corners of the county, which correspond to the major population centers of Germantown and the suburban communities near Washington, D.C"
   ]
  },
  {
   "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}