Lihan_PlayingF.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# The best neighborhood in Pittsburgh\n",
    "\n",
    "## Supermarkets & Convenience Stores\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "# By Lihan Wang\n",
    "DataSet: https://data.wprdc.org/dataset/allegheny-county-supermarkets-convenience-stores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Let's get start by importing library\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "import os\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### Import information about 90 neighborhoods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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40.4552358338457, -79.905600781874 40.4552199607547))\n"
     ]
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    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>objectid</th>\n",
       "      <th>fid_blockg</th>\n",
       "      <th>statefp10</th>\n",
       "      <th>countyfp10</th>\n",
       "      <th>tractce10</th>\n",
       "      <th>blkgrpce10</th>\n",
       "      <th>geoid10</th>\n",
       "      <th>namelsad10</th>\n",
       "      <th>mtfcc10</th>\n",
       "      <th>funcstat10</th>\n",
       "      <th>...</th>\n",
       "      <th>page_number</th>\n",
       "      <th>plannerassign</th>\n",
       "      <th>globalid</th>\n",
       "      <th>created_user</th>\n",
       "      <th>created_date</th>\n",
       "      <th>last_edited_user</th>\n",
       "      <th>last_edited_date</th>\n",
       "      <th>temp</th>\n",
       "      <th>shape_area</th>\n",
       "      <th>shape_length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>233</td>\n",
       "      <td>42</td>\n",
       "      <td>003</td>\n",
       "      <td>140500</td>\n",
       "      <td>3</td>\n",
       "      <td>420031405003</td>\n",
       "      <td>Block Group 3</td>\n",
       "      <td>G5030</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>Ose Akinlotan</td>\n",
       "      <td>a642a6b6-a2a9-48d5-acf2-3e2ce87d4bc0</td>\n",
       "      <td>SDE</td>\n",
       "      <td>2020-08-14T12:57:28</td>\n",
       "      <td>SDE</td>\n",
       "      <td>2020-08-14T13:02:13</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.153647e+06</td>\n",
       "      <td>14047.065024</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>203</td>\n",
       "      <td>42</td>\n",
       "      <td>003</td>\n",
       "      <td>140100</td>\n",
       "      <td>3</td>\n",
       "      <td>420031401003</td>\n",
       "      <td>Block Group 3</td>\n",
       "      <td>G5030</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>Ose Akinlotan</td>\n",
       "      <td>20d4605b-258e-441a-a57e-a28fdabb6d30</td>\n",
       "      <td>SDE</td>\n",
       "      <td>2020-08-14T12:57:28</td>\n",
       "      <td>SDE</td>\n",
       "      <td>2020-08-14T13:02:41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.407739e+07</td>\n",
       "      <td>30347.886823</td>\n",
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       "<p>2 rows × 39 columns</p>\n",
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       "   objectid  fid_blockg statefp10 countyfp10 tractce10 blkgrpce10  \\\n",
       "0         1         233        42        003    140500          3   \n",
       "1         2         203        42        003    140100          3   \n",
       "\n",
       "        geoid10     namelsad10 mtfcc10 funcstat10  ...  page_number  \\\n",
       "0  420031405003  Block Group 3   G5030          S  ...           15   \n",
       "1  420031401003  Block Group 3   G5030          S  ...           15   \n",
       "\n",
       "   plannerassign                              globalid created_user  \\\n",
       "0  Ose Akinlotan  a642a6b6-a2a9-48d5-acf2-3e2ce87d4bc0          SDE   \n",
       "1  Ose Akinlotan  20d4605b-258e-441a-a57e-a28fdabb6d30          SDE   \n",
       "\n",
       "          created_date  last_edited_user     last_edited_date  temp  \\\n",
       "0  2020-08-14T12:57:28               SDE  2020-08-14T13:02:13   NaN   \n",
       "1  2020-08-14T12:57:28               SDE  2020-08-14T13:02:41   NaN   \n",
       "\n",
       "     shape_area  shape_length  \n",
       "0  8.153647e+06  14047.065024  \n",
       "1  3.407739e+07  30347.886823  \n",
       "\n",
       "[2 rows x 39 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "os.environ['SHAPE_RESTORE_SHX'] = 'YES'\n",
    "neighborhood=gpd.read_file('map.shp')\n",
    "\n",
    "print(neighborhood[\"geometry\"][0])\n",
    "neighborhood.plot()\n",
    "nb = pd.read_csv(\"map.csv\")\n",
    "nb.head(2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### Import information about 104 playing field."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "pf=pd.read_csv(\"playfield.csv\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### Since map.shp doesn't contain names of neighborhood, I get this information from map.csv and combine it with other information in playing field data frame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Neighborhood</th>\n",
       "      <th>Geometry</th>\n",
       "      <th>playfield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>St. Clair</td>\n",
       "      <td>POLYGON ((-79.96995 40.41188, -79.96932 40.411...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Point Breeze</td>\n",
       "      <td>POLYGON ((-79.89319 40.44649, -79.89391 40.443...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Duquesne Heights</td>\n",
       "      <td>POLYGON ((-80.01774 40.43972, -80.01783 40.439...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>East Hills</td>\n",
       "      <td>POLYGON ((-79.87523 40.45979, -79.87448 40.459...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Esplen</td>\n",
       "      <td>POLYGON ((-80.05154 40.46364, -80.05140 40.463...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>Strip District</td>\n",
       "      <td>POLYGON ((-79.97494 40.45629, -79.97484 40.456...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>Banksville</td>\n",
       "      <td>POLYGON ((-80.02969 40.42127, -80.02976 40.419...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>Shadyside</td>\n",
       "      <td>POLYGON ((-79.92238 40.46055, -79.92208 40.460...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>South Oakland</td>\n",
       "      <td>POLYGON ((-79.95899 40.43665, -79.95887 40.436...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Spring Hill-City View</td>\n",
       "      <td>POLYGON ((-79.99761 40.47460, -79.99761 40.474...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Neighborhood                                           Geometry  \\\n",
       "73              St. Clair  POLYGON ((-79.96995 40.41188, -79.96932 40.411...   \n",
       "59           Point Breeze  POLYGON ((-79.89319 40.44649, -79.89391 40.443...   \n",
       "9        Duquesne Heights  POLYGON ((-80.01774 40.43972, -80.01783 40.439...   \n",
       "55             East Hills  POLYGON ((-79.87523 40.45979, -79.87448 40.459...   \n",
       "58                 Esplen  POLYGON ((-80.05154 40.46364, -80.05140 40.463...   \n",
       "81         Strip District  POLYGON ((-79.97494 40.45629, -79.97484 40.456...   \n",
       "53             Banksville  POLYGON ((-80.02969 40.42127, -80.02976 40.419...   \n",
       "75              Shadyside  POLYGON ((-79.92238 40.46055, -79.92208 40.460...   \n",
       "62          South Oakland  POLYGON ((-79.95899 40.43665, -79.95887 40.436...   \n",
       "69  Spring Hill-City View  POLYGON ((-79.99761 40.47460, -79.99761 40.474...   \n",
       "\n",
       "    playfield  \n",
       "73          0  \n",
       "59          0  \n",
       "9           0  \n",
       "55          0  \n",
       "58          0  \n",
       "81          0  \n",
       "53          0  \n",
       "75          0  \n",
       "62          0  \n",
       "69          0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_data = pd.DataFrame()\n",
    "n_data[\"Neighborhood\"]=nb[\"hood\"]\n",
    "n_data[\"Geometry\"] = neighborhood[\"geometry\"]\n",
    "n_data[\"playfield\"]=0\n",
    "n_data.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "#### Now, I need to get the number of supermarkets in each Neighborhood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "90\n"
     ]
    },
    {
     "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>Neighborhood</th>\n",
       "      <th>Geometry</th>\n",
       "      <th>playfield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>South Side Slopes</td>\n",
       "      <td>POLYGON ((-79.99713 40.42920, -79.99547 40.428...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>West End</td>\n",
       "      <td>POLYGON ((-80.02821 40.44427, -80.02821 40.444...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Allentown</td>\n",
       "      <td>POLYGON ((-79.99679 40.42820, -79.99642 40.427...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Friendship</td>\n",
       "      <td>POLYGON ((-79.93068 40.46350, -79.93072 40.463...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>North Shore</td>\n",
       "      <td>POLYGON ((-79.99529 40.44985, -79.99535 40.449...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Allegheny West</td>\n",
       "      <td>POLYGON ((-80.00895 40.44996, -80.00894 40.449...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Chateau</td>\n",
       "      <td>POLYGON ((-80.02999 40.45909, -80.02989 40.458...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Lincoln-Lemington-Belmar</td>\n",
       "      <td>MULTIPOLYGON (((-79.90496 40.48522, -79.90470 ...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Central Lawrenceville</td>\n",
       "      <td>POLYGON ((-79.95393 40.47731, -79.95381 40.477...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>New Homestead</td>\n",
       "      <td>POLYGON ((-79.91621 40.39849, -79.91621 40.398...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Neighborhood  \\\n",
       "48         South Side Slopes   \n",
       "57                  West End   \n",
       "30                 Allentown   \n",
       "41                Friendship   \n",
       "29               North Shore   \n",
       "32            Allegheny West   \n",
       "74                   Chateau   \n",
       "21  Lincoln-Lemington-Belmar   \n",
       "56     Central Lawrenceville   \n",
       "37             New Homestead   \n",
       "\n",
       "                                             Geometry  playfield  \n",
       "48  POLYGON ((-79.99713 40.42920, -79.99547 40.428...          6  \n",
       "57  POLYGON ((-80.02821 40.44427, -80.02821 40.444...          1  \n",
       "30  POLYGON ((-79.99679 40.42820, -79.99642 40.427...          1  \n",
       "41  POLYGON ((-79.93068 40.46350, -79.93072 40.463...          0  \n",
       "29  POLYGON ((-79.99529 40.44985, -79.99535 40.449...          0  \n",
       "32  POLYGON ((-80.00895 40.44996, -80.00894 40.449...          0  \n",
       "74  POLYGON ((-80.02999 40.45909, -80.02989 40.458...          0  \n",
       "21  MULTIPOLYGON (((-79.90496 40.48522, -79.90470 ...          2  \n",
       "56  POLYGON ((-79.95393 40.47731, -79.95381 40.477...          2  \n",
       "37  POLYGON ((-79.91621 40.39849, -79.91621 40.398...          0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from shapely.geometry import Point\n",
    "cnt=0\n",
    "for i,cur in pf.iterrows():\n",
    "  \n",
    "    pt=Point(cur[\"longitude\"],cur[\"latitude\"])\n",
    "    found=False\n",
    "    for j,nb in n_data.iterrows():\n",
    "        if(nb[\"Geometry\"].contains(pt)): \n",
    "            cnt+=1\n",
    "            n_data.at[j,\"playfield\"]+=1\n",
    "            \n",
    "# print(neighborhood.head())\n",
    "# neighborhood.plot(column='a',legend=True)\n",
    "print(len(neighborhood))\n",
    "n_data.sample(10)\n",
    "# print(cnt)\n",
    "# cn1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     0\n",
      "1     1\n",
      "2     1\n",
      "3     2\n",
      "4     0\n",
      "     ..\n",
      "85    2\n",
      "86    1\n",
      "87    2\n",
      "88    2\n",
      "89    1\n",
      "Name: playfield, Length: 90, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f143de45f70>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "neighborhood[\"playfield\"]=n_data[\"playfield\"]\n",
    "print(neighborhood[\"playfield\"])\n",
    "neighborhood.plot(column=\"playfield\",legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Geometry</th>\n",
       "      <th>playfield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Brighton Heights</td>\n",
       "      <td>POLYGON ((-80.04078 40.49142, -80.03756 40.490...</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>South Side Slopes</td>\n",
       "      <td>POLYGON ((-79.99713 40.42920, -79.99547 40.428...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Brookline</td>\n",
       "      <td>POLYGON ((-80.00172 40.40193, -80.00171 40.401...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>Carrick</td>\n",
       "      <td>POLYGON ((-79.99194 40.40719, -79.99191 40.407...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Squirrel Hill South</td>\n",
       "      <td>POLYGON ((-79.94475 40.44101, -79.94405 40.440...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Fairywood</td>\n",
       "      <td>POLYGON ((-80.08808 40.45975, -80.08803 40.459...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Upper Hill</td>\n",
       "      <td>POLYGON ((-79.95848 40.44846, -79.95861 40.448...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Ridgemont</td>\n",
       "      <td>POLYGON ((-80.03431 40.43366, -80.03424 40.433...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bluff</td>\n",
       "      <td>POLYGON ((-79.99390 40.43893, -79.99381 40.438...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Point Breeze North</td>\n",
       "      <td>POLYGON ((-79.90560 40.45522, -79.90553 40.455...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>90 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Neighborhood                                           Geometry  \\\n",
       "47     Brighton Heights  POLYGON ((-80.04078 40.49142, -80.03756 40.490...   \n",
       "48    South Side Slopes  POLYGON ((-79.99713 40.42920, -79.99547 40.428...   \n",
       "24            Brookline  POLYGON ((-80.00172 40.40193, -80.00171 40.401...   \n",
       "51              Carrick  POLYGON ((-79.99194 40.40719, -79.99191 40.407...   \n",
       "80  Squirrel Hill South  POLYGON ((-79.94475 40.44101, -79.94405 40.440...   \n",
       "..                  ...                                                ...   \n",
       "23            Fairywood  POLYGON ((-80.08808 40.45975, -80.08803 40.459...   \n",
       "63           Upper Hill  POLYGON ((-79.95848 40.44846, -79.95861 40.448...   \n",
       "64            Ridgemont  POLYGON ((-80.03431 40.43366, -80.03424 40.433...   \n",
       "22                Bluff  POLYGON ((-79.99390 40.43893, -79.99381 40.438...   \n",
       "0    Point Breeze North  POLYGON ((-79.90560 40.45522, -79.90553 40.455...   \n",
       "\n",
       "    playfield  \n",
       "47          7  \n",
       "48          6  \n",
       "24          6  \n",
       "51          5  \n",
       "80          5  \n",
       "..        ...  \n",
       "23          0  \n",
       "63          0  \n",
       "64          0  \n",
       "22          0  \n",
       "0           0  \n",
       "\n",
       "[90 rows x 3 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb_pf=n_data.sort_values(\"playfield\",ascending=False)\n",
    "plt=nb_pf.iloc[:30].plot(kind='bar',x='Neighborhood',y='playfield')\n",
    "ax.set_title(\"PlayingFields in Pittsburgh\")\n",
    "\n",
    "nb_pf"
   ]
  },
  {
   "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}