Week 3(3): Clustering Neighborhood in Toronto.ipynb

{
    "nbformat_minor": 1, 
    "cells": [
        {
            "source": "import pandas as pd\nimport numpy as np\nfrom bs4 import BeautifulSoup\nimport requests", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 9
        }, 
        {
            "source": "wikipedia_link='https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M'\nraw_wikipedia_page= requests.get(wikipedia_link).text\n\nsoup = BeautifulSoup(raw_wikipedia_page,'xml')\n\n#print(soup.prettify())\n#The prettify() method will turn a Beautiful Soup parse tree into a nicely formatted Unicode string, with a separate line for each HTML/XML tag and string", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 10
        }, 
        {
            "source": "table = soup.find('table')\n\nPostcode      = []\nBorough       = []\nNeighbourhood = []\n\n# print(table)\nfor tr_cell in table.find_all('tr'):\n    \n    counter = 1\n    Postcode_var      = -1\n    Borough_var       = -1\n    Neighbourhood_var = -1\n    \n    for td_cell in tr_cell.find_all('td'):\n        if counter == 1: \n            Postcode_var = td_cell.text\n        if counter == 2: \n            Borough_var = td_cell.text\n            tag_a_Borough = td_cell.find('a')\n            \n        if counter == 3: \n            Neighbourhood_var = str(td_cell.text).strip()\n            tag_a_Neighbourhood = td_cell.find('a')\n            \n        counter +=1\n        \n    if (Postcode_var == 'Not assigned' or Borough_var == 'Not assigned' or Neighbourhood_var == 'Not assigned'): \n        continue\n    try:\n        if ((tag_a_Borough is None) or (tag_a_Neighbourhood is None)):\n            continue\n    except:\n        pass\n    if(Postcode_var == -1 or Borough_var == -1 or Neighbourhood_var == -1):\n        continue\n        \n    Postcode.append(Postcode_var)\n    Borough.append(Borough_var)\n    Neighbourhood.append(Neighbourhood_var)\nunique_p = set(Postcode)\nprint('num of unique Postal codes:', len(unique_p))\nPostcode_u      = []\nBorough_u       = []\nNeighbourhood_u = []\nfor postcode_unique_element in unique_p:\n    p_var = ''; b_var = ''; n_var = ''; \n    for postcode_idx, postcode_element in enumerate(Postcode):\n        if postcode_unique_element == postcode_element:\n            p_var = postcode_element;\n            b_var = Borough[postcode_idx]\n            if n_var == '': \n                n_var = Neighbourhood[postcode_idx]\n            else:\n                n_var = n_var + ', ' + Neighbourhood[postcode_idx]\n    Postcode_u.append(p_var)\n    Borough_u.append(b_var)\n    Neighbourhood_u.append(n_var)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "stream", 
                    "name": "stdout", 
                    "text": "num of unique Postal codes: 77\n"
                }
            ], 
            "execution_count": 11
        }, 
        {
            "source": "toronto_dict = {'Postcode':Postcode_u, 'Borough':Borough_u, 'Neighbourhood':Neighbourhood_u}\ndf_toronto = pd.DataFrame.from_dict(toronto_dict)\ndf_toronto.to_csv('toronto_part1.csv')\ndf_toronto.head(14)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>Borough</th>\n      <th>Neighbourhood</th>\n      <th>Postcode</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Downtown Toronto</td>\n      <td>Berczy Park</td>\n      <td>M5E</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>North York</td>\n      <td>Humber Summit</td>\n      <td>M9L</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Central Toronto</td>\n      <td>The Annex, Yorkville</td>\n      <td>M5R</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Downtown Toronto</td>\n      <td>Design Exchange, Toronto Dominion Centre</td>\n      <td>M5K</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Downtown Toronto</td>\n      <td>University of Toronto</td>\n      <td>M5S</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Central Toronto</td>\n      <td>Moore Park</td>\n      <td>M4T</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>East Toronto</td>\n      <td>The Beaches</td>\n      <td>M4E</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Downtown Toronto</td>\n      <td>CN Tower, King and Spadina, Railway Lands, Sou...</td>\n      <td>M5V</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>North York</td>\n      <td>Bayview Village</td>\n      <td>M2K</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Etobicoke</td>\n      <td>New Toronto</td>\n      <td>M8V</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Scarborough</td>\n      <td>Birch Cliff</td>\n      <td>M1N</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Scarborough</td>\n      <td>Upper Rouge</td>\n      <td>M1X</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>North York</td>\n      <td>Victoria Village</td>\n      <td>M4A</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>North York</td>\n      <td>Henry Farm</td>\n      <td>M2J</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "             Borough                                      Neighbourhood  \\\n0   Downtown Toronto                                        Berczy Park   \n1         North York                                      Humber Summit   \n2    Central Toronto                               The Annex, Yorkville   \n3   Downtown Toronto           Design Exchange, Toronto Dominion Centre   \n4   Downtown Toronto                              University of Toronto   \n5    Central Toronto                                         Moore Park   \n6       East Toronto                                        The Beaches   \n7   Downtown Toronto  CN Tower, King and Spadina, Railway Lands, Sou...   \n8         North York                                    Bayview Village   \n9          Etobicoke                                        New Toronto   \n10       Scarborough                                        Birch Cliff   \n11       Scarborough                                        Upper Rouge   \n12        North York                                   Victoria Village   \n13        North York                                         Henry Farm   \n\n   Postcode  \n0       M5E  \n1       M9L  \n2       M5R  \n3       M5K  \n4       M5S  \n5       M4T  \n6       M4E  \n7       M5V  \n8       M2K  \n9       M8V  \n10      M1N  \n11      M1X  \n12      M4A  \n13      M2J  "
                    }, 
                    "execution_count": 12, 
                    "metadata": {}
                }
            ], 
            "execution_count": 12
        }, 
        {
            "source": "df = pd.read_csv('http://cocl.us/Geospatial_data')\ndf.columns = ['Postcode','Latitude','Longitude']", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 13
        }, 
        {
            "source": "final_df = df_toronto.merge(df, how='left', on='Postcode')\nfinal_df", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>Borough</th>\n      <th>Neighbourhood</th>\n      <th>Postcode</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Downtown Toronto</td>\n      <td>Berczy Park</td>\n      <td>M5E</td>\n      <td>43.644771</td>\n      <td>-79.373306</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>North York</td>\n      <td>Humber Summit</td>\n      <td>M9L</td>\n      <td>43.756303</td>\n      <td>-79.565963</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Central Toronto</td>\n      <td>The Annex, Yorkville</td>\n      <td>M5R</td>\n      <td>43.672710</td>\n      <td>-79.405678</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Downtown Toronto</td>\n      <td>Design Exchange, Toronto Dominion Centre</td>\n      <td>M5K</td>\n      <td>43.647177</td>\n      <td>-79.381576</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Downtown Toronto</td>\n      <td>University of Toronto</td>\n      <td>M5S</td>\n      <td>43.662696</td>\n      <td>-79.400049</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Central Toronto</td>\n      <td>Moore Park</td>\n      <td>M4T</td>\n      <td>43.689574</td>\n      <td>-79.383160</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>East Toronto</td>\n      <td>The Beaches</td>\n      <td>M4E</td>\n      <td>43.676357</td>\n      <td>-79.293031</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Downtown Toronto</td>\n      <td>CN Tower, King and Spadina, Railway Lands, Sou...</td>\n      <td>M5V</td>\n      <td>43.628947</td>\n      <td>-79.394420</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>North York</td>\n      <td>Bayview Village</td>\n      <td>M2K</td>\n      <td>43.786947</td>\n      <td>-79.385975</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Etobicoke</td>\n      <td>New Toronto</td>\n      <td>M8V</td>\n      <td>43.605647</td>\n      <td>-79.501321</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Scarborough</td>\n      <td>Birch Cliff</td>\n      <td>M1N</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Scarborough</td>\n      <td>Upper Rouge</td>\n      <td>M1X</td>\n      <td>43.836125</td>\n      <td>-79.205636</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>North York</td>\n      <td>Victoria Village</td>\n      <td>M4A</td>\n      <td>43.725882</td>\n      <td>-79.315572</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>North York</td>\n      <td>Henry Farm</td>\n      <td>M2J</td>\n      <td>43.778517</td>\n      <td>-79.346556</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>North York</td>\n      <td>Northwood Park, York University</td>\n      <td>M3J</td>\n      <td>43.767980</td>\n      <td>-79.487262</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>West Toronto</td>\n      <td>Runnymede, Swansea</td>\n      <td>M6S</td>\n      <td>43.651571</td>\n      <td>-79.484450</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>Downtown Toronto</td>\n      <td>Toronto Islands, Union Station</td>\n      <td>M5J</td>\n      <td>43.640816</td>\n      <td>-79.381752</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>Downtown Toronto</td>\n      <td>St. James Town</td>\n      <td>M5C</td>\n      <td>43.651494</td>\n      <td>-79.375418</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>North York</td>\n      <td>Hillcrest Village</td>\n      <td>M2H</td>\n      <td>43.803762</td>\n      <td>-79.363452</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>East York</td>\n      <td>Woodbine Gardens, Parkview Hill</td>\n      <td>M4B</td>\n      <td>43.706397</td>\n      <td>-79.309937</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>Scarborough</td>\n      <td>Rouge, Malvern</td>\n      <td>M1B</td>\n      <td>43.806686</td>\n      <td>-79.194353</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>Scarborough</td>\n      <td>Morningside, West Hill</td>\n      <td>M1E</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>North York</td>\n      <td>Downsview West</td>\n      <td>M3L</td>\n      <td>43.739015</td>\n      <td>-79.506944</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>East Toronto</td>\n      <td>India Bazaar</td>\n      <td>M4L</td>\n      <td>43.668999</td>\n      <td>-79.315572</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>Central Toronto</td>\n      <td>Forest Hill North</td>\n      <td>M5P</td>\n      <td>43.696948</td>\n      <td>-79.411307</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>Central Toronto</td>\n      <td>Lawrence Park</td>\n      <td>M4N</td>\n      <td>43.728020</td>\n      <td>-79.388790</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>West Toronto</td>\n      <td>Parkdale, Roncesvalles</td>\n      <td>M6R</td>\n      <td>43.648960</td>\n      <td>-79.456325</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>North York</td>\n      <td>Bathurst Manor, Wilson Heights</td>\n      <td>M3H</td>\n      <td>43.754328</td>\n      <td>-79.442259</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>Central Toronto</td>\n      <td>Deer Park, Rathnelly, South Hill</td>\n      <td>M4V</td>\n      <td>43.686412</td>\n      <td>-79.400049</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>Etobicoke</td>\n      <td>Alderwood, Long Branch</td>\n      <td>M8W</td>\n      <td>43.602414</td>\n      <td>-79.543484</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>North York</td>\n      <td>Flemingdon Park</td>\n      <td>M3C</td>\n      <td>43.725900</td>\n      <td>-79.340923</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>East York</td>\n      <td>Thorncliffe Park</td>\n      <td>M4H</td>\n      <td>43.705369</td>\n      <td>-79.349372</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>North York</td>\n      <td>Downsview</td>\n      <td>M6L</td>\n      <td>43.713756</td>\n      <td>-79.490074</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>Scarborough</td>\n      <td>Maryvale, Wexford</td>\n      <td>M1R</td>\n      <td>43.750072</td>\n      <td>-79.295849</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>Scarborough</td>\n      <td>Agincourt</td>\n      <td>M1S</td>\n      <td>43.794200</td>\n      <td>-79.262029</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>Downtown Toronto</td>\n      <td>Harbourfront, Regent Park</td>\n      <td>M5A</td>\n      <td>43.654260</td>\n      <td>-79.360636</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td>Scarborough</td>\n      <td>Scarborough Village</td>\n      <td>M1J</td>\n      <td>43.744734</td>\n      <td>-79.239476</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>West Toronto</td>\n      <td>High Park</td>\n      <td>M6P</td>\n      <td>43.661608</td>\n      <td>-79.464763</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>Downtown Toronto</td>\n      <td>Church and Wellesley</td>\n      <td>M4Y</td>\n      <td>43.665860</td>\n      <td>-79.383160</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>Etobicoke</td>\n      <td>Mimico NW, The Queensway West</td>\n      <td>M8Z</td>\n      <td>43.628841</td>\n      <td>-79.520999</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>Scarborough</td>\n      <td>Highland Creek, Rouge Hill, Port Union</td>\n      <td>M1C</td>\n      <td>43.784535</td>\n      <td>-79.160497</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>West Toronto</td>\n      <td>Little Portugal, Trinity</td>\n      <td>M6J</td>\n      <td>43.647927</td>\n      <td>-79.419750</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>Scarborough</td>\n      <td>Ionview, Kennedy Park</td>\n      <td>M1K</td>\n      <td>43.727929</td>\n      <td>-79.262029</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>Scarborough</td>\n      <td>Woburn</td>\n      <td>M1G</td>\n      <td>43.770992</td>\n      <td>-79.216917</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>Etobicoke</td>\n      <td>Beaumond Heights, Jamestown, Mount Olive, Silv...</td>\n      <td>M9V</td>\n      <td>43.739416</td>\n      <td>-79.588437</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>York</td>\n      <td>Weston</td>\n      <td>M9N</td>\n      <td>43.706876</td>\n      <td>-79.518188</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>North York</td>\n      <td>Emery, Humberlea</td>\n      <td>M9M</td>\n      <td>43.724766</td>\n      <td>-79.532242</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>North York</td>\n      <td>Parkwoods</td>\n      <td>M3A</td>\n      <td>43.753259</td>\n      <td>-79.329656</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>East York</td>\n      <td>East Toronto</td>\n      <td>M4J</td>\n      <td>43.685347</td>\n      <td>-79.338106</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>East York</td>\n      <td>Woodbine Heights</td>\n      <td>M4C</td>\n      <td>43.695344</td>\n      <td>-79.318389</td>\n    </tr>\n    <tr>\n      <th>50</th>\n      <td>Scarborough</td>\n      <td>Clairlea, Golden Mile, Oakridge</td>\n      <td>M1L</td>\n      <td>43.711112</td>\n      <td>-79.284577</td>\n    </tr>\n    <tr>\n      <th>51</th>\n      <td>Scarborough</td>\n      <td>Dorset Park, Scarborough Town Centre, Wexford ...</td>\n      <td>M1P</td>\n      <td>43.757410</td>\n      <td>-79.273304</td>\n    </tr>\n    <tr>\n      <th>52</th>\n      <td>Etobicoke</td>\n      <td>Humber Bay, Mimico NE, Old Mill South, The Que...</td>\n      <td>M8Y</td>\n      <td>43.636258</td>\n      <td>-79.498509</td>\n    </tr>\n    <tr>\n      <th>53</th>\n      <td>North York</td>\n      <td>CFB Toronto</td>\n      <td>M3K</td>\n      <td>43.737473</td>\n      <td>-79.464763</td>\n    </tr>\n    <tr>\n      <th>54</th>\n      <td>Downtown Toronto</td>\n      <td>First Canadian Place, Underground city</td>\n      <td>M5X</td>\n      <td>43.648429</td>\n      <td>-79.382280</td>\n    </tr>\n    <tr>\n      <th>55</th>\n      <td>North York</td>\n      <td>Bedford Park</td>\n      <td>M5M</td>\n      <td>43.733283</td>\n      <td>-79.419750</td>\n    </tr>\n    <tr>\n      <th>56</th>\n      <td>North York</td>\n      <td>Willowdale West</td>\n      <td>M2R</td>\n      <td>43.782736</td>\n      <td>-79.442259</td>\n    </tr>\n    <tr>\n      <th>57</th>\n      <td>Scarborough</td>\n      <td>Tam O'Shanter</td>\n      <td>M1T</td>\n      <td>43.781638</td>\n      <td>-79.304302</td>\n    </tr>\n    <tr>\n      <th>58</th>\n      <td>Scarborough</td>\n      <td>Cliffcrest, Cliffside</td>\n      <td>M1M</td>\n      <td>43.716316</td>\n      <td>-79.239476</td>\n    </tr>\n    <tr>\n      <th>59</th>\n      <td>North York</td>\n      <td>Lawrence Heights, Lawrence Manor</td>\n      <td>M6A</td>\n      <td>43.718518</td>\n      <td>-79.464763</td>\n    </tr>\n    <tr>\n      <th>60</th>\n      <td>Etobicoke</td>\n      <td>Islington Avenue</td>\n      <td>M9A</td>\n      <td>43.667856</td>\n      <td>-79.532242</td>\n    </tr>\n    <tr>\n      <th>61</th>\n      <td>Etobicoke</td>\n      <td>Kingsview Village</td>\n      <td>M9R</td>\n      <td>43.688905</td>\n      <td>-79.554724</td>\n    </tr>\n    <tr>\n      <th>62</th>\n      <td>Etobicoke</td>\n      <td>Markland Wood</td>\n      <td>M9C</td>\n      <td>43.643515</td>\n      <td>-79.577201</td>\n    </tr>\n    <tr>\n      <th>63</th>\n      <td>Downtown Toronto</td>\n      <td>Chinatown, Grange Park, Kensington Market</td>\n      <td>M5T</td>\n      <td>43.653206</td>\n      <td>-79.400049</td>\n    </tr>\n    <tr>\n      <th>64</th>\n      <td>East Toronto</td>\n      <td>Riverdale</td>\n      <td>M4K</td>\n      <td>43.679557</td>\n      <td>-79.352188</td>\n    </tr>\n    <tr>\n      <th>65</th>\n      <td>North York</td>\n      <td>Newtonbrook, Willowdale</td>\n      <td>M2M</td>\n      <td>43.789053</td>\n      <td>-79.408493</td>\n    </tr>\n    <tr>\n      <th>66</th>\n      <td>East York</td>\n      <td>Leaside</td>\n      <td>M4G</td>\n      <td>43.709060</td>\n      <td>-79.363452</td>\n    </tr>\n    <tr>\n      <th>67</th>\n      <td>York</td>\n      <td>Keelesdale, Mount Dennis, Silverthorn</td>\n      <td>M6M</td>\n      <td>43.691116</td>\n      <td>-79.476013</td>\n    </tr>\n    <tr>\n      <th>68</th>\n      <td>Downtown Toronto</td>\n      <td>Commerce Court</td>\n      <td>M5L</td>\n      <td>43.648198</td>\n      <td>-79.379817</td>\n    </tr>\n    <tr>\n      <th>69</th>\n      <td>West Toronto</td>\n      <td>Dovercourt Village</td>\n      <td>M6H</td>\n      <td>43.669005</td>\n      <td>-79.442259</td>\n    </tr>\n    <tr>\n      <th>70</th>\n      <td>Downtown Toronto</td>\n      <td>Rosedale</td>\n      <td>M4W</td>\n      <td>43.679563</td>\n      <td>-79.377529</td>\n    </tr>\n    <tr>\n      <th>71</th>\n      <td>Etobicoke</td>\n      <td>Islington, Princess Gardens, West Deane Park</td>\n      <td>M9B</td>\n      <td>43.650943</td>\n      <td>-79.554724</td>\n    </tr>\n    <tr>\n      <th>72</th>\n      <td>Scarborough</td>\n      <td>Agincourt North, Milliken</td>\n      <td>M1V</td>\n      <td>43.815252</td>\n      <td>-79.284577</td>\n    </tr>\n    <tr>\n      <th>73</th>\n      <td>Downtown Toronto</td>\n      <td>Cabbagetown, St. James Town</td>\n      <td>M4X</td>\n      <td>43.667967</td>\n      <td>-79.367675</td>\n    </tr>\n    <tr>\n      <th>74</th>\n      <td>North York</td>\n      <td>York Mills</td>\n      <td>M2L</td>\n      <td>43.757490</td>\n      <td>-79.374714</td>\n    </tr>\n    <tr>\n      <th>75</th>\n      <td>Etobicoke</td>\n      <td>The Kingsway</td>\n      <td>M8X</td>\n      <td>43.653654</td>\n      <td>-79.506944</td>\n    </tr>\n    <tr>\n      <th>76</th>\n      <td>West Toronto</td>\n      <td>Exhibition Place, Parkdale Village</td>\n      <td>M6K</td>\n      <td>43.636847</td>\n      <td>-79.428191</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "             Borough                                      Neighbourhood  \\\n0   Downtown Toronto                                        Berczy Park   \n1         North York                                      Humber Summit   \n2    Central Toronto                               The Annex, Yorkville   \n3   Downtown Toronto           Design Exchange, Toronto Dominion Centre   \n4   Downtown Toronto                              University of Toronto   \n5    Central Toronto                                         Moore Park   \n6       East Toronto                                        The Beaches   \n7   Downtown Toronto  CN Tower, King and Spadina, Railway Lands, Sou...   \n8         North York                                    Bayview Village   \n9          Etobicoke                                        New Toronto   \n10       Scarborough                                        Birch Cliff   \n11       Scarborough                                        Upper Rouge   \n12        North York                                   Victoria Village   \n13        North York                                         Henry Farm   \n14        North York                    Northwood Park, York University   \n15      West Toronto                                 Runnymede, Swansea   \n16  Downtown Toronto                     Toronto Islands, Union Station   \n17  Downtown Toronto                                     St. James Town   \n18        North York                                  Hillcrest Village   \n19         East York                    Woodbine Gardens, Parkview Hill   \n20       Scarborough                                     Rouge, Malvern   \n21       Scarborough                             Morningside, West Hill   \n22        North York                                     Downsview West   \n23      East Toronto                                       India Bazaar   \n24   Central Toronto                                  Forest Hill North   \n25   Central Toronto                                      Lawrence Park   \n26      West Toronto                             Parkdale, Roncesvalles   \n27        North York                     Bathurst Manor, Wilson Heights   \n28   Central Toronto                   Deer Park, Rathnelly, South Hill   \n29         Etobicoke                             Alderwood, Long Branch   \n30        North York                                    Flemingdon Park   \n31         East York                                   Thorncliffe Park   \n32        North York                                          Downsview   \n33       Scarborough                                  Maryvale, Wexford   \n34       Scarborough                                          Agincourt   \n35  Downtown Toronto                          Harbourfront, Regent Park   \n36       Scarborough                                Scarborough Village   \n37      West Toronto                                          High Park   \n38  Downtown Toronto                               Church and Wellesley   \n39         Etobicoke                      Mimico NW, The Queensway West   \n40       Scarborough             Highland Creek, Rouge Hill, Port Union   \n41      West Toronto                           Little Portugal, Trinity   \n42       Scarborough                              Ionview, Kennedy Park   \n43       Scarborough                                             Woburn   \n44         Etobicoke  Beaumond Heights, Jamestown, Mount Olive, Silv...   \n45              York                                             Weston   \n46        North York                                   Emery, Humberlea   \n47        North York                                          Parkwoods   \n48         East York                                       East Toronto   \n49         East York                                   Woodbine Heights   \n50       Scarborough                    Clairlea, Golden Mile, Oakridge   \n51       Scarborough  Dorset Park, Scarborough Town Centre, Wexford ...   \n52         Etobicoke  Humber Bay, Mimico NE, Old Mill South, The Que...   \n53        North York                                        CFB Toronto   \n54  Downtown Toronto             First Canadian Place, Underground city   \n55        North York                                       Bedford Park   \n56        North York                                    Willowdale West   \n57       Scarborough                                      Tam O'Shanter   \n58       Scarborough                              Cliffcrest, Cliffside   \n59        North York                   Lawrence Heights, Lawrence Manor   \n60         Etobicoke                                   Islington Avenue   \n61         Etobicoke                                  Kingsview Village   \n62         Etobicoke                                      Markland Wood   \n63  Downtown Toronto          Chinatown, Grange Park, Kensington Market   \n64      East Toronto                                          Riverdale   \n65        North York                            Newtonbrook, Willowdale   \n66         East York                                            Leaside   \n67              York              Keelesdale, Mount Dennis, Silverthorn   \n68  Downtown Toronto                                     Commerce Court   \n69      West Toronto                                 Dovercourt Village   \n70  Downtown Toronto                                           Rosedale   \n71         Etobicoke       Islington, Princess Gardens, West Deane Park   \n72       Scarborough                          Agincourt North, Milliken   \n73  Downtown Toronto                        Cabbagetown, St. James Town   \n74        North York                                         York Mills   \n75         Etobicoke                                       The Kingsway   \n76      West Toronto                 Exhibition Place, Parkdale Village   \n\n   Postcode   Latitude  Longitude  \n0       M5E  43.644771 -79.373306  \n1       M9L  43.756303 -79.565963  \n2       M5R  43.672710 -79.405678  \n3       M5K  43.647177 -79.381576  \n4       M5S  43.662696 -79.400049  \n5       M4T  43.689574 -79.383160  \n6       M4E  43.676357 -79.293031  \n7       M5V  43.628947 -79.394420  \n8       M2K  43.786947 -79.385975  \n9       M8V  43.605647 -79.501321  \n10      M1N  43.692657 -79.264848  \n11      M1X  43.836125 -79.205636  \n12      M4A  43.725882 -79.315572  \n13      M2J  43.778517 -79.346556  \n14      M3J  43.767980 -79.487262  \n15      M6S  43.651571 -79.484450  \n16      M5J  43.640816 -79.381752  \n17      M5C  43.651494 -79.375418  \n18      M2H  43.803762 -79.363452  \n19      M4B  43.706397 -79.309937  \n20      M1B  43.806686 -79.194353  \n21      M1E  43.763573 -79.188711  \n22      M3L  43.739015 -79.506944  \n23      M4L  43.668999 -79.315572  \n24      M5P  43.696948 -79.411307  \n25      M4N  43.728020 -79.388790  \n26      M6R  43.648960 -79.456325  \n27      M3H  43.754328 -79.442259  \n28      M4V  43.686412 -79.400049  \n29      M8W  43.602414 -79.543484  \n30      M3C  43.725900 -79.340923  \n31      M4H  43.705369 -79.349372  \n32      M6L  43.713756 -79.490074  \n33      M1R  43.750072 -79.295849  \n34      M1S  43.794200 -79.262029  \n35      M5A  43.654260 -79.360636  \n36      M1J  43.744734 -79.239476  \n37      M6P  43.661608 -79.464763  \n38      M4Y  43.665860 -79.383160  \n39      M8Z  43.628841 -79.520999  \n40      M1C  43.784535 -79.160497  \n41      M6J  43.647927 -79.419750  \n42      M1K  43.727929 -79.262029  \n43      M1G  43.770992 -79.216917  \n44      M9V  43.739416 -79.588437  \n45      M9N  43.706876 -79.518188  \n46      M9M  43.724766 -79.532242  \n47      M3A  43.753259 -79.329656  \n48      M4J  43.685347 -79.338106  \n49      M4C  43.695344 -79.318389  \n50      M1L  43.711112 -79.284577  \n51      M1P  43.757410 -79.273304  \n52      M8Y  43.636258 -79.498509  \n53      M3K  43.737473 -79.464763  \n54      M5X  43.648429 -79.382280  \n55      M5M  43.733283 -79.419750  \n56      M2R  43.782736 -79.442259  \n57      M1T  43.781638 -79.304302  \n58      M1M  43.716316 -79.239476  \n59      M6A  43.718518 -79.464763  \n60      M9A  43.667856 -79.532242  \n61      M9R  43.688905 -79.554724  \n62      M9C  43.643515 -79.577201  \n63      M5T  43.653206 -79.400049  \n64      M4K  43.679557 -79.352188  \n65      M2M  43.789053 -79.408493  \n66      M4G  43.709060 -79.363452  \n67      M6M  43.691116 -79.476013  \n68      M5L  43.648198 -79.379817  \n69      M6H  43.669005 -79.442259  \n70      M4W  43.679563 -79.377529  \n71      M9B  43.650943 -79.554724  \n72      M1V  43.815252 -79.284577  \n73      M4X  43.667967 -79.367675  \n74      M2L  43.757490 -79.374714  \n75      M8X  43.653654 -79.506944  \n76      M6K  43.636847 -79.428191  "
                    }, 
                    "execution_count": 14, 
                    "metadata": {}
                }
            ], 
            "execution_count": 14
        }, 
        {
            "source": "df_toronto = final_df\ndf_toronto.he", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>Borough</th>\n      <th>Neighbourhood</th>\n      <th>Postcode</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Downtown Toronto</td>\n      <td>Berczy Park</td>\n      <td>M5E</td>\n      <td>43.644771</td>\n      <td>-79.373306</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>North York</td>\n      <td>Humber Summit</td>\n      <td>M9L</td>\n      <td>43.756303</td>\n      <td>-79.565963</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Central Toronto</td>\n      <td>The Annex, Yorkville</td>\n      <td>M5R</td>\n      <td>43.672710</td>\n      <td>-79.405678</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Downtown Toronto</td>\n      <td>Design Exchange, Toronto Dominion Centre</td>\n      <td>M5K</td>\n      <td>43.647177</td>\n      <td>-79.381576</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Downtown Toronto</td>\n      <td>University of Toronto</td>\n      <td>M5S</td>\n      <td>43.662696</td>\n      <td>-79.400049</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Central Toronto</td>\n      <td>Moore Park</td>\n      <td>M4T</td>\n      <td>43.689574</td>\n      <td>-79.383160</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>East Toronto</td>\n      <td>The Beaches</td>\n      <td>M4E</td>\n      <td>43.676357</td>\n      <td>-79.293031</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "            Borough                             Neighbourhood Postcode  \\\n0  Downtown Toronto                               Berczy Park      M5E   \n1        North York                             Humber Summit      M9L   \n2   Central Toronto                      The Annex, Yorkville      M5R   \n3  Downtown Toronto  Design Exchange, Toronto Dominion Centre      M5K   \n4  Downtown Toronto                     University of Toronto      M5S   \n5   Central Toronto                                Moore Park      M4T   \n6      East Toronto                               The Beaches      M4E   \n\n    Latitude  Longitude  \n0  43.644771 -79.373306  \n1  43.756303 -79.565963  \n2  43.672710 -79.405678  \n3  43.647177 -79.381576  \n4  43.662696 -79.400049  \n5  43.689574 -79.383160  \n6  43.676357 -79.293031  "
                    }, 
                    "execution_count": 16, 
                    "metadata": {}
                }
            ], 
            "execution_count": 16
        }, 
        {
            "source": "pd.set_option('display.max_columns', None)\npd.set_option('display.max_rows', None)\n\n# !conda install -c conda-forge geopy --yes # uncomment this line if you haven't completed the Foursquare API lab\nfrom geopy.geocoders import Nominatim # convert an address into latitude and longitude values\n\nimport requests # library to handle requests\n\n# !conda install -c conda-forge folium=0.5.0 --yes # uncomment this line if you haven't completed the Foursquare API lab\nimport folium # map rendering library\n\nprint('Libraries imported.')", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "stream", 
                    "name": "stdout", 
                    "text": "Libraries imported.\n"
                }
            ], 
            "execution_count": 17
        }, 
        {
            "source": "# for the city Toronto, latitude and longtitude are manually extracted via google search\ntoronto_latitude = 43.6532; toronto_longitude = -79.3832\nmap_toronto = folium.Map(location = [toronto_latitude, toronto_longitude], zoom_start = 10.7)\n\n# add markers to map\nfor lat, lng, borough, neighborhood in zip(df_toronto['Latitude'], df_toronto['Longitude'], df_toronto['Borough'], df_toronto['Neighbourhood']):\n    label = '{}, {}'.format(neighborhood, borough)\n    label = folium.Popup(label, parse_html=True)\n    folium.CircleMarker(\n        [lat, lng],\n        radius=5,\n        popup=label,\n        color='blue',\n        fill=True,\n        fill_color='#3186cc',\n        fill_opacity=0.7).add_to(map_toronto)  \n    \n\nmap_toronto", 
            "cell_type": "code", 
            "metadata": {
                "scrolled": true
            }, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "data": {
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            var circle_marker_1b61963da45e4473af05900ee095b23a = L.circleMarker(
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                {
  "bubblingMouseEvents": true,
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            var popup_710853d785f644fb844b70b40bf7cb25 = L.popup({maxWidth: '300'});

            
                var html_682a18bfc1be411e81dd55d7da445694 = $('<div id="html_682a18bfc1be411e81dd55d7da445694" style="width: 100.0%; height: 100.0%;">Islington, Princess Gardens, West Deane Park, Etobicoke</div>')[0];
                popup_710853d785f644fb844b70b40bf7cb25.setContent(html_682a18bfc1be411e81dd55d7da445694);
            

            circle_marker_8a6ca0297b2048dd9d19fbe4f9fb5109.bindPopup(popup_710853d785f644fb844b70b40bf7cb25);

            
        
    
            var circle_marker_77ff547f9fc14f9cbbd8e55c418b0ee4 = L.circleMarker(
                [43.8152522,-79.2845772],
                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_e96d9ee4dd244548894dcec3cc42bb26);
            
    
            var popup_dee89b4f21f944f1a88d34ef8519b414 = L.popup({maxWidth: '300'});

            
                var html_04663619d92441359f4554c754335bcf = $('<div id="html_04663619d92441359f4554c754335bcf" style="width: 100.0%; height: 100.0%;">Agincourt North, Milliken, Scarborough</div>')[0];
                popup_dee89b4f21f944f1a88d34ef8519b414.setContent(html_04663619d92441359f4554c754335bcf);
            

            circle_marker_77ff547f9fc14f9cbbd8e55c418b0ee4.bindPopup(popup_dee89b4f21f944f1a88d34ef8519b414);

            
        
    
            var circle_marker_707e560b850a435cbfb787a01c725fd3 = L.circleMarker(
                [43.667967,-79.3676753],
                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_e96d9ee4dd244548894dcec3cc42bb26);
            
    
            var popup_13d00146eacc4d34bdccdc1845ba34d1 = L.popup({maxWidth: '300'});

            
                var html_e7e4f2a811f64327885f2b5417f81e25 = $('<div id="html_e7e4f2a811f64327885f2b5417f81e25" style="width: 100.0%; height: 100.0%;">Cabbagetown, St. James Town, Downtown Toronto</div>')[0];
                popup_13d00146eacc4d34bdccdc1845ba34d1.setContent(html_e7e4f2a811f64327885f2b5417f81e25);
            

            circle_marker_707e560b850a435cbfb787a01c725fd3.bindPopup(popup_13d00146eacc4d34bdccdc1845ba34d1);

            
        
    
            var circle_marker_61698f8934b9419599919ae902aa266c = L.circleMarker(
                [43.7574902,-79.37471409999999],
                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_e96d9ee4dd244548894dcec3cc42bb26);
            
    
            var popup_89366dfdb4174de3ae2a7473e1dde27e = L.popup({maxWidth: '300'});

            
                var html_b21c6515b80044a48a5c9f89099b02c5 = $('<div id="html_b21c6515b80044a48a5c9f89099b02c5" style="width: 100.0%; height: 100.0%;">York Mills, North York</div>')[0];
                popup_89366dfdb4174de3ae2a7473e1dde27e.setContent(html_b21c6515b80044a48a5c9f89099b02c5);
            

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            var circle_marker_e6d26d7326214b50819522967596fc0d = L.circleMarker(
                [43.653653600000005,-79.5069436],
                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_e96d9ee4dd244548894dcec3cc42bb26);
            
    
            var popup_53012645f48941caa4adcde91ce45277 = L.popup({maxWidth: '300'});

            
                var html_79106715e7c44df2a5ab781fd9969cb2 = $('<div id="html_79106715e7c44df2a5ab781fd9969cb2" style="width: 100.0%; height: 100.0%;">The Kingsway, Etobicoke</div>')[0];
                popup_53012645f48941caa4adcde91ce45277.setContent(html_79106715e7c44df2a5ab781fd9969cb2);
            

            circle_marker_e6d26d7326214b50819522967596fc0d.bindPopup(popup_53012645f48941caa4adcde91ce45277);

            
        
    
            var circle_marker_2b2c9f5504c14f6ebda19aae93c9dcbb = L.circleMarker(
                [43.6368472,-79.42819140000002],
                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_e96d9ee4dd244548894dcec3cc42bb26);
            
    
            var popup_451abccf2d3d4a2587e135c46ebc9aef = L.popup({maxWidth: '300'});

            
                var html_219aca28ddf94d969224e7e21a71778f = $('<div id="html_219aca28ddf94d969224e7e21a71778f" style="width: 100.0%; height: 100.0%;">Exhibition Place, Parkdale Village, West Toronto</div>')[0];
                popup_451abccf2d3d4a2587e135c46ebc9aef.setContent(html_219aca28ddf94d969224e7e21a71778f);
            

            circle_marker_2b2c9f5504c14f6ebda19aae93c9dcbb.bindPopup(popup_451abccf2d3d4a2587e135c46ebc9aef);

            
        
</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>", 
                        "text/plain": "<folium.folium.Map at 0x7f026b8feb38>"
                    }, 
                    "execution_count": 18, 
                    "metadata": {}
                }
            ], 
            "execution_count": 18
        }, 
        {
            "source": "CLIENT_ID = 'Y42EA5EWMGOYGUGGQ3KPHG1OTRCP544JNCR0AQL5H5CNNWQS' \nCLIENT_SECRET = 'WHFEMCWXKHHUP1EWJCWHZFSJX5QC5BE42YTYTX5AT4DRXF0S' \nVERSION = '20180605'", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 58
        }, 
        {
            "source": "scarborough_data = df_toronto[df_toronto['Borough'] == 'Scarborough'].reset_index(drop=True)\nscarborough_data.head(7)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>Borough</th>\n      <th>Neighbourhood</th>\n      <th>Postcode</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Scarborough</td>\n      <td>Birch Cliff</td>\n      <td>M1N</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Scarborough</td>\n      <td>Upper Rouge</td>\n      <td>M1X</td>\n      <td>43.836125</td>\n      <td>-79.205636</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Scarborough</td>\n      <td>Rouge, Malvern</td>\n      <td>M1B</td>\n      <td>43.806686</td>\n      <td>-79.194353</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Scarborough</td>\n      <td>Morningside, West Hill</td>\n      <td>M1E</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Scarborough</td>\n      <td>Maryvale, Wexford</td>\n      <td>M1R</td>\n      <td>43.750072</td>\n      <td>-79.295849</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Scarborough</td>\n      <td>Agincourt</td>\n      <td>M1S</td>\n      <td>43.794200</td>\n      <td>-79.262029</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Scarborough</td>\n      <td>Scarborough Village</td>\n      <td>M1J</td>\n      <td>43.744734</td>\n      <td>-79.239476</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "       Borough           Neighbourhood Postcode   Latitude  Longitude\n0  Scarborough             Birch Cliff      M1N  43.692657 -79.264848\n1  Scarborough             Upper Rouge      M1X  43.836125 -79.205636\n2  Scarborough          Rouge, Malvern      M1B  43.806686 -79.194353\n3  Scarborough  Morningside, West Hill      M1E  43.763573 -79.188711\n4  Scarborough       Maryvale, Wexford      M1R  43.750072 -79.295849\n5  Scarborough               Agincourt      M1S  43.794200 -79.262029\n6  Scarborough     Scarborough Village      M1J  43.744734 -79.239476"
                    }, 
                    "execution_count": 28, 
                    "metadata": {}
                }
            ], 
            "execution_count": 28
        }, 
        {
            "source": "address_scar = 'Scarborough,Toronto'\nlatitude_scar = 43.773077\nlongitude_scar = -79.257774\nprint('The geograpical coordinate of Scarborough are {}, {}.'.format(latitude_scar, longitude_scar))", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "stream", 
                    "name": "stdout", 
                    "text": "The geograpical coordinate of Scarborough are 43.773077, -79.257774.\n"
                }
            ], 
            "execution_count": 29
        }, 
        {
            "source": "map_scarb = folium.Map(location=[latitude_scar, longitude_scar], zoom_start=12)\n\n# add markers to map\nfor lat, lng, label in zip(scarborough_data['Latitude'], scarborough_data['Longitude'], scarborough_data['Neighbourhood']):\n    label = folium.Popup(label, parse_html=True)\n    folium.CircleMarker(\n        [lat, lng],\n        radius=5,\n        popup=label,\n        color='blue',\n        fill=True,\n        fill_color='#3186cc',\n        fill_opacity=0.7).add_to(map_scarb)  \n    \nmap_scarb", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "data": {
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    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS = false; L_NO_TOUCH = false; L_DISABLE_3D = false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.js"></script>
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.2.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
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    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
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                width : 100.0%;
                height: 100.0%;
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<body>    
    
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</body>
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                                  'map_afffd1021cdf4b9aa8c3c406a0911792',
                                  {center: [43.773077,-79.257774],
                                  zoom: 12,
                                  maxBounds: bounds,
                                  layers: [],
                                  worldCopyJump: false,
                                  crs: L.CRS.EPSG3857
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            var tile_layer_b438b37086fa4fe1808f7186a0fe4ff8 = L.tileLayer(
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  "attribution": null,
  "detectRetina": false,
  "maxZoom": 18,
  "minZoom": 1,
  "noWrap": false,
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}
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                [43.692657000000004,-79.2648481],
                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_afffd1021cdf4b9aa8c3c406a0911792);
            
    
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                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
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                var html_8d371a07714e430c9331834ce53bbb14 = $('<div id="html_8d371a07714e430c9331834ce53bbb14" style="width: 100.0%; height: 100.0%;">Upper Rouge</div>')[0];
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                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
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  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
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                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_afffd1021cdf4b9aa8c3c406a0911792);
            
    
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                {
  "bubblingMouseEvents": true,
  "color": "blue",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "#3186cc",
  "fillOpacity": 0.7,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                ).addTo(map_afffd1021cdf4b9aa8c3c406a0911792);
            
    
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  "bubblingMouseEvents": true,
  "color": "blue",
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  "dashOffset": null,
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                var html_74b0d95cc24e4a9b87ccebbc708cc7e6 = $('<div id="html_74b0d95cc24e4a9b87ccebbc708cc7e6" style="width: 100.0%; height: 100.0%;">Agincourt North, Milliken</div>')[0];
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</script>\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>", 
                        "text/plain": "<folium.folium.Map at 0x7f0269f1fac8>"
                    }, 
                    "execution_count": 30, 
                    "metadata": {}
                }
            ], 
            "execution_count": 30
        }, 
        {
            "source": "neighborhood_latitude = scarborough_data.loc[0, 'Latitude'] # neighbourhood latitude value\nneighborhood_longitude = scarborough_data.loc[0, 'Longitude'] # neighbourhood longitude value\n\nneighborhood_name = scarborough_data.loc[0, 'Neighbourhood'] # neighbourhood name\n\nprint('Latitude and longitude values of \"{}\" are {}, {}.'.format(neighborhood_name, \n                                                               neighborhood_latitude, \n                                                               neighborhood_longitude))", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "stream", 
                    "name": "stdout", 
                    "text": "Latitude and longitude values of \"Birch Cliff\" are 43.692657000000004, -79.2648481.\n"
                }
            ], 
            "execution_count": 31
        }, 
        {
            "source": "LIMIT = 100\nradius = 500\nurl = 'https://api.foursquare.com/v2/venues/explore?client_id={}&client_secret={}&ll={},{}&v={}&radius={}&limit={}'.format(CLIENT_ID, CLIENT_SECRET, latitude_scar, longitude_scar, VERSION, radius, LIMIT)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 32
        }, 
        {
            "source": "results = requests.get(url).json()\nresults", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "data": {
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 {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4e62b5f1aeb73603150d8e06-39',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/candystore_',\n          'suffix': '.png'},\n         'id': '52f2ab2ebcbc57f1066b8b31',\n         'name': 'Chocolate Shop',\n         'pluralName': 'Chocolate Shops',\n         'primary': True,\n         'shortName': 'Chocolate Shop'}],\n       'id': '4e62b5f1aeb73603150d8e06',\n       'location': {'address': '300 Borough Drive',\n        'cc': 'CA',\n        'city': 'Scarborough',\n        'country': 'Canada',\n        'distance': 226,\n        'formattedAddress': ['300 Borough Drive',\n         'Scarborough ON M1P 4P5',\n         'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.7751112,\n          'lng': -79.2577682}],\n        'lat': 43.7751112,\n        'lng': -79.2577682,\n        'postalCode': 'M1P 4P5',\n        'state': 'ON'},\n       'name': 'Godiva Chocolatier',\n       'photos': {'count': 0, 'groups': []}}},\n     {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4c54a4d7728920a10a381683-40',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/beauty_cosmetic_',\n          'suffix': '.png'},\n         'id': '4bf58dd8d48988d10c951735',\n         'name': 'Cosmetics Shop',\n         'pluralName': 'Cosmetics Shops',\n         'primary': True,\n         'shortName': 'Cosmetics'}],\n       'id': '4c54a4d7728920a10a381683',\n       'location': {'address': '300 Borough Dr',\n        'cc': 'CA',\n        'city': 'Toronto',\n        'country': 'Canada',\n        'distance': 241,\n        'formattedAddress': ['300 Borough Dr', 'Toronto ON', 'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.775246,\n          'lng': -79.25771}],\n        'lat': 43.775246,\n        'lng': -79.25771,\n        'state': 'ON'},\n       'name': 'MAC Cosmetics',\n       'photos': {'count': 0, 'groups': []}}},\n     {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4b58e618f964a520a37128e3-41',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/beauty_cosmetic_',\n          'suffix': '.png'},\n         'id': '4bf58dd8d48988d10c951735',\n         'name': 'Cosmetics Shop',\n         'pluralName': 'Cosmetics Shops',\n         'primary': True,\n         'shortName': 'Cosmetics'}],\n       'id': '4b58e618f964a520a37128e3',\n       'location': {'address': '300 Borough Drive Unit 227',\n        'cc': 'CA',\n        'city': 'Scarborough',\n        'country': 'Canada',\n        'crossStreet': 'in Scarborough Town Centre',\n        'distance': 254,\n        'formattedAddress': ['300 Borough Drive Unit 227 (in Scarborough Town Centre)',\n         'Scarborough ON M1P 4P5',\n         'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.77535787123638,\n          'lng': -79.25752421502017}],\n        'lat': 43.77535787123638,\n        'lng': -79.25752421502017,\n        'postalCode': 'M1P 4P5',\n        'state': 'ON'},\n       'name': 'The Body Shop',\n       'photos': {'count': 0, 'groups': []}}},\n     {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4ddd22dfbd410c18fca8b159-42',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/travel/default_',\n          'suffix': '.png'},\n         'id': '52f2ab2ebcbc57f1066b8b29',\n         'name': 'Luggage Store',\n         'pluralName': 'Luggage Stores',\n         'primary': True,\n         'shortName': 'Luggage Store'}],\n       'id': '4ddd22dfbd410c18fca8b159',\n       'location': {'address': '300 Borough Drive',\n        'cc': 'CA',\n        'city': 'Scarborough',\n        'country': 'Canada',\n        'distance': 328,\n        'formattedAddress': ['300 Borough Drive',\n         'Scarborough ON M1P 4P5',\n         'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.775910528917485,\n          'lng': -79.25891044671643}],\n        'lat': 43.775910528917485,\n        'lng': -79.25891044671643,\n        'postalCode': 'M1P 4P5',\n        'state': 'ON'},\n       'name': 'Bentley',\n       'photos': {'count': 0, 'groups': []}}},\n     {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4c1a62d7c09ed13af34b828e-43',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/apparel_',\n          'suffix': '.png'},\n         'id': '4bf58dd8d48988d103951735',\n         'name': 'Clothing Store',\n         'pluralName': 'Clothing Stores',\n         'primary': True,\n         'shortName': 'Apparel'}],\n       'id': '4c1a62d7c09ed13af34b828e',\n       'location': {'address': '300 Borough Drive, Unit 270',\n        'cc': 'CA',\n        'city': 'Scarborough',\n        'country': 'Canada',\n        'distance': 358,\n        'formattedAddress': ['300 Borough Drive, Unit 270',\n         'Scarborough ON M1P 4P5',\n         'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.776301126641116,\n          'lng': -79.25775155092617}],\n        'lat': 43.776301126641116,\n        'lng': -79.25775155092617,\n        'postalCode': 'M1P 4P5',\n        'state': 'ON'},\n       'name': 'GUESS',\n       'photos': {'count': 0, 'groups': []}}},\n     {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4e19f23bc65b6bfb591d34a0-44',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/apparel_shoestore_',\n          'suffix': '.png'},\n         'id': '4bf58dd8d48988d107951735',\n         'name': 'Shoe Store',\n         'pluralName': 'Shoe Stores',\n         'primary': True,\n         'shortName': 'Shoes'}],\n       'id': '4e19f23bc65b6bfb591d34a0',\n       'location': {'address': '300 Borough Dr',\n        'cc': 'CA',\n        'city': 'Toronto',\n        'country': 'Canada',\n        'distance': 369,\n        'formattedAddress': ['300 Borough Dr', 'Toronto ON', 'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.77637808681919,\n          'lng': -79.25731378384347}],\n        'lat': 43.77637808681919,\n        'lng': -79.25731378384347,\n        'state': 'ON'},\n       'name': \"Brown's Shoes\",\n       'photos': {'count': 0, 'groups': []}}},\n     {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4e7e5c0ef790985203539652-45',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/pet_store_',\n          'suffix': '.png'},\n         'id': '4bf58dd8d48988d100951735',\n         'name': 'Pet Store',\n         'pluralName': 'Pet Stores',\n         'primary': True,\n         'shortName': 'Pet Store'}],\n       'id': '4e7e5c0ef790985203539652',\n       'location': {'cc': 'CA',\n        'city': 'Toronto',\n        'country': 'Canada',\n        'distance': 440,\n        'formattedAddress': ['Toronto ON', 'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.77159778313037,\n          'lng': -79.25269061743035}],\n        'lat': 43.77159778313037,\n        'lng': -79.25269061743035,\n        'state': 'ON'},\n       'name': 'Global Pet Foods',\n       'photos': {'count': 0, 'groups': []}}},\n     {'reasons': {'count': 0,\n       'items': [{'reasonName': 'globalInteractionReason',\n         'summary': 'This spot is popular',\n         'type': 'general'}]},\n      'referralId': 'e-0-4d921a708e5a1456ced399c0-46',\n      'venue': {'categories': [{'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/storage_',\n          'suffix': '.png'},\n         'id': '4f04b1572fb6e1c99f3db0bf',\n         'name': 'Storage Facility',\n         'pluralName': 'Storage Facilities',\n         'primary': True,\n         'shortName': 'Storage'}],\n       'id': '4d921a708e5a1456ced399c0',\n       'location': {'address': '1340 Ellesmere Rd',\n        'cc': 'CA',\n        'city': 'Scarborough',\n        'country': 'Canada',\n        'distance': 496,\n        'formattedAddress': ['1340 Ellesmere Rd',\n         'Scarborough ON M1P 2X9',\n         'Canada'],\n        'labeledLatLngs': [{'label': 'display',\n          'lat': 43.77046,\n          'lng': -79.26277}],\n        'lat': 43.77046,\n        'lng': -79.26277,\n        'postalCode': 'M1P 2X9',\n        'state': 'ON'},\n       'name': 'Access Storage - Scarborough Town Centre',\n       'photos': {'count': 0, 'groups': []},\n       'venuePage': {'id': '478361942'}}}],\n    'name': 'recommended',\n    'type': 'Recommended Places'}],\n  'headerFullLocation': 'Scarborough City Centre, Toronto',\n  'headerLocation': 'Scarborough City Centre',\n  'headerLocationGranularity': 'neighborhood',\n  'suggestedBounds': {'ne': {'lat': 43.7775770045, 'lng': -79.25155367954714},\n   'sw': {'lat': 43.7685769955, 'lng': -79.26399432045285}},\n  'suggestedFilters': {'filters': [{'key': 'openNow', 'name': 'Open now'}],\n   'header': 'Tap to show:'},\n  'totalResults': 47}}"
                    }, 
                    "execution_count": 33, 
                    "metadata": {}
                }
            ], 
            "execution_count": 33
        }, 
        {
            "source": "def get_category_type(row):\n    try:\n        categories_list = row['categories']\n    except:\n        categories_list = row['venue.categories']\n        \n    if len(categories_list) == 0:\n        return None\n    else:\n        return categories_list[0]['name']", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 36
        }, 
        {
            "source": "import json # library to handle JSON files\nfrom pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe\n\nvenues = results['response']['groups'][0]['items']  \nnearby_venues = json_normalize(venues) # flatten JSON\n\n# filter columns\nfiltered_columns = ['venue.name', 'venue.categories', 'venue.location.lat', 'venue.location.lng']\nnearby_venues =nearby_venues.loc[:, filtered_columns]\n\n# filter the category for each row\nnearby_venues['venue.categories'] = nearby_venues.apply(get_category_type, axis=1)\n\n# clean columns\nnearby_venues.columns = [col.split(\".\")[-1] for col in nearby_venues.columns]\n\nnearby_venues.head(10)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>name</th>\n      <th>categories</th>\n      <th>lat</th>\n      <th>lng</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Disney Store</td>\n      <td>Toy / Game Store</td>\n      <td>43.775537</td>\n      <td>-79.256833</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>SEPHORA</td>\n      <td>Cosmetics Shop</td>\n      <td>43.775017</td>\n      <td>-79.258109</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>American Eagle Outfitters</td>\n      <td>Clothing Store</td>\n      <td>43.775908</td>\n      <td>-79.258352</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>DAVIDsTEA</td>\n      <td>Tea Room</td>\n      <td>43.776613</td>\n      <td>-79.258516</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Tommy Hilfiger Company Store</td>\n      <td>Clothing Store</td>\n      <td>43.776015</td>\n      <td>-79.257369</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Chipotle Mexican Grill</td>\n      <td>Mexican Restaurant</td>\n      <td>43.776410</td>\n      <td>-79.258069</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Scarborough Town Centre</td>\n      <td>Shopping Mall</td>\n      <td>43.775237</td>\n      <td>-79.257363</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>St. Andrews Fish &amp; Chips</td>\n      <td>Fish &amp; Chips Shop</td>\n      <td>43.771865</td>\n      <td>-79.252645</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Coliseum Scarborough Cinemas</td>\n      <td>Movie Theater</td>\n      <td>43.775995</td>\n      <td>-79.255649</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Jimmy The Greek</td>\n      <td>Greek Restaurant</td>\n      <td>43.775112</td>\n      <td>-79.257119</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "                           name          categories        lat        lng\n0                  Disney Store    Toy / Game Store  43.775537 -79.256833\n1                       SEPHORA      Cosmetics Shop  43.775017 -79.258109\n2     American Eagle Outfitters      Clothing Store  43.775908 -79.258352\n3                     DAVIDsTEA            Tea Room  43.776613 -79.258516\n4  Tommy Hilfiger Company Store      Clothing Store  43.776015 -79.257369\n5        Chipotle Mexican Grill  Mexican Restaurant  43.776410 -79.258069\n6       Scarborough Town Centre       Shopping Mall  43.775237 -79.257363\n7      St. Andrews Fish & Chips   Fish & Chips Shop  43.771865 -79.252645\n8  Coliseum Scarborough Cinemas       Movie Theater  43.775995 -79.255649\n9               Jimmy The Greek    Greek Restaurant  43.775112 -79.257119"
                    }, 
                    "execution_count": 37, 
                    "metadata": {}
                }
            ], 
            "execution_count": 37
        }, 
        {
            "source": "print('{} venues were returned by Foursquare.'.format(nearby_venues.shape[0]))", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "stream", 
                    "name": "stdout", 
                    "text": "47 venues were returned by Foursquare.\n"
                }
            ], 
            "execution_count": 38
        }, 
        {
            "source": "def getNearbyVenues(names, latitudes, longitudes, radius=500):\n    \n    venues_list=[]\n    for name, lat, lng in zip(names, latitudes, longitudes):\n        print(name)\n            \n        # create the API request URL\n        url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(\n            CLIENT_ID, \n            CLIENT_SECRET, \n            VERSION, \n            lat, \n            lng, \n            radius, \n            LIMIT)\n            \n        # make the GET request\n        results = requests.get(url).json()[\"response\"]['groups'][0]['items']\n        \n        # return only relevant information for each nearby venue\n        venues_list.append([(\n            name, \n            lat, \n            lng, \n            v['venue']['name'], \n            v['venue']['location']['lat'], \n            v['venue']['location']['lng'],  \n            v['venue']['categories'][0]['name']) for v in results])\n\n    nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])\n    nearby_venues.columns = ['Neighborhood', \n                  'Neighborhood Latitude', \n                  'Neighborhood Longitude', \n                  'Venue', \n                  'Venue Latitude', \n                  'Venue Longitude', \n                  'Venue Category']\n        \n    return(nearby_venues)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 40
        }, 
        {
            "source": "scarborough_venues = getNearbyVenues(names=scarborough_data['Neighbourhood'],\n                                   latitudes=scarborough_data['Latitude'],\n                                   longitudes=scarborough_data['Longitude']\n                                  )", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "stream", 
                    "name": "stdout", 
                    "text": "Birch Cliff\nUpper Rouge\nRouge, Malvern\nMorningside, West Hill\nMaryvale, Wexford\nAgincourt\nScarborough Village\nHighland Creek, Rouge Hill, Port Union\nIonview, Kennedy Park\nWoburn\nClairlea, Golden Mile, Oakridge\nDorset Park, Scarborough Town Centre, Wexford Heights\nTam O'Shanter\nCliffcrest, Cliffside\nAgincourt North, Milliken\n"
                }
            ], 
            "execution_count": 41
        }, 
        {
            "source": "scarborough_venues.head(10)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>Neighborhood Latitude</th>\n      <th>Neighborhood Longitude</th>\n      <th>Venue</th>\n      <th>Venue Latitude</th>\n      <th>Venue Longitude</th>\n      <th>Venue Category</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Birch Cliff</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n      <td>The Birchcliff</td>\n      <td>43.691666</td>\n      <td>-79.264532</td>\n      <td>Caf\u00e9</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Birch Cliff</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n      <td>Birchmount Community Centre</td>\n      <td>43.695175</td>\n      <td>-79.262161</td>\n      <td>General Entertainment</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Birch Cliff</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n      <td>Scarborough Gardens</td>\n      <td>43.694647</td>\n      <td>-79.262230</td>\n      <td>Skating Rink</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Birch Cliff</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n      <td>Birchmount Stadium</td>\n      <td>43.695323</td>\n      <td>-79.261293</td>\n      <td>College Stadium</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Rouge, Malvern</td>\n      <td>43.806686</td>\n      <td>-79.194353</td>\n      <td>Wendy's</td>\n      <td>43.807448</td>\n      <td>-79.199056</td>\n      <td>Fast Food Restaurant</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Morningside, West Hill</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n      <td>Swiss Chalet Rotisserie &amp; Grill</td>\n      <td>43.767697</td>\n      <td>-79.189914</td>\n      <td>Pizza Place</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Morningside, West Hill</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n      <td>G &amp; G Electronics</td>\n      <td>43.765309</td>\n      <td>-79.191537</td>\n      <td>Electronics Store</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Morningside, West Hill</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n      <td>Marina Spa</td>\n      <td>43.766000</td>\n      <td>-79.191000</td>\n      <td>Spa</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Morningside, West Hill</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n      <td>Big Bite Burrito</td>\n      <td>43.766299</td>\n      <td>-79.190720</td>\n      <td>Mexican Restaurant</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Morningside, West Hill</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n      <td>Enterprise Rent-A-Car</td>\n      <td>43.764076</td>\n      <td>-79.193406</td>\n      <td>Rental Car Location</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "             Neighborhood  Neighborhood Latitude  Neighborhood Longitude  \\\n0             Birch Cliff              43.692657              -79.264848   \n1             Birch Cliff              43.692657              -79.264848   \n2             Birch Cliff              43.692657              -79.264848   \n3             Birch Cliff              43.692657              -79.264848   \n4          Rouge, Malvern              43.806686              -79.194353   \n5  Morningside, West Hill              43.763573              -79.188711   \n6  Morningside, West Hill              43.763573              -79.188711   \n7  Morningside, West Hill              43.763573              -79.188711   \n8  Morningside, West Hill              43.763573              -79.188711   \n9  Morningside, West Hill              43.763573              -79.188711   \n\n                             Venue  Venue Latitude  Venue Longitude  \\\n0                   The Birchcliff       43.691666       -79.264532   \n1      Birchmount Community Centre       43.695175       -79.262161   \n2              Scarborough Gardens       43.694647       -79.262230   \n3               Birchmount Stadium       43.695323       -79.261293   \n4                          Wendy's       43.807448       -79.199056   \n5  Swiss Chalet Rotisserie & Grill       43.767697       -79.189914   \n6                G & G Electronics       43.765309       -79.191537   \n7                       Marina Spa       43.766000       -79.191000   \n8                 Big Bite Burrito       43.766299       -79.190720   \n9            Enterprise Rent-A-Car       43.764076       -79.193406   \n\n          Venue Category  \n0                   Caf\u00e9  \n1  General Entertainment  \n2           Skating Rink  \n3        College Stadium  \n4   Fast Food Restaurant  \n5            Pizza Place  \n6      Electronics Store  \n7                    Spa  \n8     Mexican Restaurant  \n9    Rental Car Location  "
                    }, 
                    "execution_count": 42, 
                    "metadata": {}
                }
            ], 
            "execution_count": 42
        }, 
        {
            "source": "scarborough_venues.groupby('Neighborhood').count()", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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 Latitude</th>\n      <th>Neighborhood Longitude</th>\n      <th>Venue</th>\n      <th>Venue Latitude</th>\n      <th>Venue Longitude</th>\n      <th>Venue Category</th>\n    </tr>\n    <tr>\n      <th>Neighborhood</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>Agincourt</th>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>Agincourt North, Milliken</th>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>Birch Cliff</th>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>Clairlea, Golden Mile, Oakridge</th>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n    </tr>\n    <tr>\n      <th>Cliffcrest, Cliffside</th>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>Dorset Park, Scarborough Town Centre, Wexford Heights</th>\n      <td>7</td>\n      <td>7</td>\n      <td>7</td>\n      <td>7</td>\n      <td>7</td>\n      <td>7</td>\n    </tr>\n    <tr>\n      <th>Highland Creek, Rouge Hill, Port Union</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    </tr>\n    <tr>\n      <th>Ionview, Kennedy Park</th>\n      <td>6</td>\n      <td>6</td>\n      <td>6</td>\n      <td>6</td>\n      <td>6</td>\n      <td>6</td>\n    </tr>\n    <tr>\n      <th>Maryvale, Wexford</th>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>Morningside, West Hill</th>\n      <td>8</td>\n      <td>8</td>\n      <td>8</td>\n      <td>8</td>\n      <td>8</td>\n      <td>8</td>\n    </tr>\n    <tr>\n      <th>Rouge, Malvern</th>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>Scarborough Village</th>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>Tam O'Shanter</th>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n      <td>10</td>\n    </tr>\n    <tr>\n      <th>Woburn</th>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "                                                    Neighborhood Latitude  \\\nNeighborhood                                                                \nAgincourt                                                               4   \nAgincourt North, Milliken                                               2   \nBirch Cliff                                                             4   \nClairlea, Golden Mile, Oakridge                                        10   \nCliffcrest, Cliffside                                                   2   \nDorset Park, Scarborough Town Centre, Wexford H...                      7   \nHighland Creek, Rouge Hill, Port Union                                  3   \nIonview, Kennedy Park                                                   6   \nMaryvale, Wexford                                                       5   \nMorningside, West Hill                                                  8   \nRouge, Malvern                                                          1   \nScarborough Village                                                     2   \nTam O'Shanter                                                          10   \nWoburn                                                                  4   \n\n                                                    Neighborhood Longitude  \\\nNeighborhood                                                                 \nAgincourt                                                                4   \nAgincourt North, Milliken                                                2   \nBirch Cliff                                                              4   \nClairlea, Golden Mile, Oakridge                                         10   \nCliffcrest, Cliffside                                                    2   \nDorset Park, Scarborough Town Centre, Wexford H...                       7   \nHighland Creek, Rouge Hill, Port Union                                   3   \nIonview, Kennedy Park                                                    6   \nMaryvale, Wexford                                                        5   \nMorningside, West Hill                                                   8   \nRouge, Malvern                                                           1   \nScarborough Village                                                      2   \nTam O'Shanter                                                           10   \nWoburn                                                                   4   \n\n                                                    Venue  Venue Latitude  \\\nNeighborhood                                                                \nAgincourt                                               4               4   \nAgincourt North, Milliken                               2               2   \nBirch Cliff                                             4               4   \nClairlea, Golden Mile, Oakridge                        10              10   \nCliffcrest, Cliffside                                   2               2   \nDorset Park, Scarborough Town Centre, Wexford H...      7               7   \nHighland Creek, Rouge Hill, Port Union                  3               3   \nIonview, Kennedy Park                                   6               6   \nMaryvale, Wexford                                       5               5   \nMorningside, West Hill                                  8               8   \nRouge, Malvern                                          1               1   \nScarborough Village                                     2               2   \nTam O'Shanter                                          10              10   \nWoburn                                                  4               4   \n\n                                                    Venue Longitude  \\\nNeighborhood                                                          \nAgincourt                                                         4   \nAgincourt North, Milliken                                         2   \nBirch Cliff                                                       4   \nClairlea, Golden Mile, Oakridge                                  10   \nCliffcrest, Cliffside                                             2   \nDorset Park, Scarborough Town Centre, Wexford H...                7   \nHighland Creek, Rouge Hill, Port Union                            3   \nIonview, Kennedy Park                                             6   \nMaryvale, Wexford                                                 5   \nMorningside, West Hill                                            8   \nRouge, Malvern                                                    1   \nScarborough Village                                               2   \nTam O'Shanter                                                    10   \nWoburn                                                            4   \n\n                                                    Venue Category  \nNeighborhood                                                        \nAgincourt                                                        4  \nAgincourt North, Milliken                                        2  \nBirch Cliff                                                      4  \nClairlea, Golden Mile, Oakridge                                 10  \nCliffcrest, Cliffside                                            2  \nDorset Park, Scarborough Town Centre, Wexford H...               7  \nHighland Creek, Rouge Hill, Port Union                           3  \nIonview, Kennedy Park                                            6  \nMaryvale, Wexford                                                5  \nMorningside, West Hill                                           8  \nRouge, Malvern                                                   1  \nScarborough Village                                              2  \nTam O'Shanter                                                   10  \nWoburn                                                           4  "
                    }, 
                    "execution_count": 43, 
                    "metadata": {}
                }
            ], 
            "execution_count": 43
        }, 
        {
            "source": "print('There are {} uniques categories.'.format(len(scarborough_venues['Venue Category'].unique())))", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "stream", 
                    "name": "stdout", 
                    "text": "There are 47 uniques categories.\n"
                }
            ], 
            "execution_count": 44
        }, 
        {
            "source": "# one hot encoding\nscarb_onehot = pd.get_dummies(scarborough_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n\n# add neighborhood column back to dataframe\nscarb_onehot['Neighborhood'] = scarborough_venues['Neighborhood'] \n\n# move neighborhood column to the first column\nfixed_columns = [scarb_onehot.columns[-1]] + list(scarb_onehot.columns[:-1])\nscarb_onehot = scarb_onehot[fixed_columns]\n\nscarb_onehot.head()", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>American Restaurant</th>\n      <th>Auto Garage</th>\n      <th>Bakery</th>\n      <th>Bar</th>\n      <th>Breakfast Spot</th>\n      <th>Bus Line</th>\n      <th>Bus Station</th>\n      <th>Caf\u00e9</th>\n      <th>Chinese Restaurant</th>\n      <th>Clothing Store</th>\n      <th>Coffee Shop</th>\n      <th>College Stadium</th>\n      <th>Convenience Store</th>\n      <th>Department Store</th>\n      <th>Discount Store</th>\n      <th>Electronics Store</th>\n      <th>Fast Food Restaurant</th>\n      <th>Fried Chicken Joint</th>\n      <th>Furniture / Home Store</th>\n      <th>General Entertainment</th>\n      <th>History Museum</th>\n      <th>Indian Restaurant</th>\n      <th>Insurance Office</th>\n      <th>Intersection</th>\n      <th>Italian Restaurant</th>\n      <th>Korean Restaurant</th>\n      <th>Latin American Restaurant</th>\n      <th>Lounge</th>\n      <th>Medical Center</th>\n      <th>Metro Station</th>\n      <th>Mexican Restaurant</th>\n      <th>Middle Eastern Restaurant</th>\n      <th>Motel</th>\n      <th>Moving Target</th>\n      <th>Noodle House</th>\n      <th>Park</th>\n      <th>Pet Store</th>\n      <th>Pharmacy</th>\n      <th>Pizza Place</th>\n      <th>Playground</th>\n      <th>Rental Car Location</th>\n      <th>Sandwich Place</th>\n      <th>Skating Rink</th>\n      <th>Soccer Field</th>\n      <th>Spa</th>\n      <th>Thai Restaurant</th>\n      <th>Vietnamese Restaurant</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Birch Cliff</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Birch Cliff</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Birch Cliff</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Birch Cliff</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Rouge, Malvern</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "     Neighborhood  American Restaurant  Auto Garage  Bakery  Bar  \\\n0     Birch Cliff                    0            0       0    0   \n1     Birch Cliff                    0            0       0    0   \n2     Birch Cliff                    0            0       0    0   \n3     Birch Cliff                    0            0       0    0   \n4  Rouge, Malvern                    0            0       0    0   \n\n   Breakfast Spot  Bus Line  Bus Station  Caf\u00e9  Chinese Restaurant  \\\n0               0         0            0     1                   0   \n1               0         0            0     0                   0   \n2               0         0            0     0                   0   \n3               0         0            0     0                   0   \n4               0         0            0     0                   0   \n\n   Clothing Store  Coffee Shop  College Stadium  Convenience Store  \\\n0               0            0                0                  0   \n1               0            0                0                  0   \n2               0            0                0                  0   \n3               0            0                1                  0   \n4               0            0                0                  0   \n\n   Department Store  Discount Store  Electronics Store  Fast Food Restaurant  \\\n0                 0               0                  0                     0   \n1                 0               0                  0                     0   \n2                 0               0                  0                     0   \n3                 0               0                  0                     0   \n4                 0               0                  0                     1   \n\n   Fried Chicken Joint  Furniture / Home Store  General Entertainment  \\\n0                    0                       0                      0   \n1                    0                       0                      1   \n2                    0                       0                      0   \n3                    0                       0                      0   \n4                    0                       0                      0   \n\n   History Museum  Indian Restaurant  Insurance Office  Intersection  \\\n0               0                  0                 0             0   \n1               0                  0                 0             0   \n2               0                  0                 0             0   \n3               0                  0                 0             0   \n4               0                  0                 0             0   \n\n   Italian Restaurant  Korean Restaurant  Latin American Restaurant  Lounge  \\\n0                   0                  0                          0       0   \n1                   0                  0                          0       0   \n2                   0                  0                          0       0   \n3                   0                  0                          0       0   \n4                   0                  0                          0       0   \n\n   Medical Center  Metro Station  Mexican Restaurant  \\\n0               0              0                   0   \n1               0              0                   0   \n2               0              0                   0   \n3               0              0                   0   \n4               0              0                   0   \n\n   Middle Eastern Restaurant  Motel  Moving Target  Noodle House  Park  \\\n0                          0      0              0             0     0   \n1                          0      0              0             0     0   \n2                          0      0              0             0     0   \n3                          0      0              0             0     0   \n4                          0      0              0             0     0   \n\n   Pet Store  Pharmacy  Pizza Place  Playground  Rental Car Location  \\\n0          0         0            0           0                    0   \n1          0         0            0           0                    0   \n2          0         0            0           0                    0   \n3          0         0            0           0                    0   \n4          0         0            0           0                    0   \n\n   Sandwich Place  Skating Rink  Soccer Field  Spa  Thai Restaurant  \\\n0               0             0             0    0                0   \n1               0             0             0    0                0   \n2               0             1             0    0                0   \n3               0             0             0    0                0   \n4               0             0             0    0                0   \n\n   Vietnamese Restaurant  \n0                      0  \n1                      0  \n2                      0  \n3                      0  \n4                      0  "
                    }, 
                    "execution_count": 45, 
                    "metadata": {}
                }
            ], 
            "execution_count": 45
        }, 
        {
            "source": "scarb_onehot.shape", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "data": {
                        "text/plain": "(68, 48)"
                    }, 
                    "execution_count": 46, 
                    "metadata": {}
                }
            ], 
            "execution_count": 46
        }, 
        {
            "source": "\nscarb_grouped = scarb_onehot.groupby('Neighborhood').mean().reset_index()\nscarb_grouped.head(7)", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>American Restaurant</th>\n      <th>Auto Garage</th>\n      <th>Bakery</th>\n      <th>Bar</th>\n      <th>Breakfast Spot</th>\n      <th>Bus Line</th>\n      <th>Bus Station</th>\n      <th>Caf\u00e9</th>\n      <th>Chinese Restaurant</th>\n      <th>Clothing Store</th>\n      <th>Coffee Shop</th>\n      <th>College Stadium</th>\n      <th>Convenience Store</th>\n      <th>Department Store</th>\n      <th>Discount Store</th>\n      <th>Electronics Store</th>\n      <th>Fast Food Restaurant</th>\n      <th>Fried Chicken Joint</th>\n      <th>Furniture / Home Store</th>\n      <th>General Entertainment</th>\n      <th>History Museum</th>\n      <th>Indian Restaurant</th>\n      <th>Insurance Office</th>\n      <th>Intersection</th>\n      <th>Italian Restaurant</th>\n      <th>Korean Restaurant</th>\n      <th>Latin American Restaurant</th>\n      <th>Lounge</th>\n      <th>Medical Center</th>\n      <th>Metro Station</th>\n      <th>Mexican Restaurant</th>\n      <th>Middle Eastern Restaurant</th>\n      <th>Motel</th>\n      <th>Moving Target</th>\n      <th>Noodle House</th>\n      <th>Park</th>\n      <th>Pet Store</th>\n      <th>Pharmacy</th>\n      <th>Pizza Place</th>\n      <th>Playground</th>\n      <th>Rental Car Location</th>\n      <th>Sandwich Place</th>\n      <th>Skating Rink</th>\n      <th>Soccer Field</th>\n      <th>Spa</th>\n      <th>Thai Restaurant</th>\n      <th>Vietnamese Restaurant</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Agincourt</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.25</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.25</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.25</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.25</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Agincourt North, Milliken</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.5</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.5</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Birch Cliff</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.25</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.25</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.25</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.25</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Clairlea, Golden Mile, Oakridge</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.2</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.2</td>\n      <td>0.1</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.1</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.1</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.1</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.1</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.1</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Cliffcrest, Cliffside</td>\n      <td>0.5</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.5</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Dorset Park, Scarborough Town Centre, Wexford ...</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.142857</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.142857</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.285714</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.142857</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.142857</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.142857</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Highland Creek, Rouge Hill, Port Union</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.333333</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.333333</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.333333</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.00</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.0</td>\n      <td>0.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "                                        Neighborhood  American Restaurant  \\\n0                                          Agincourt                  0.0   \n1                          Agincourt North, Milliken                  0.0   \n2                                        Birch Cliff                  0.0   \n3                    Clairlea, Golden Mile, Oakridge                  0.0   \n4                              Cliffcrest, Cliffside                  0.5   \n5  Dorset Park, Scarborough Town Centre, Wexford ...                  0.0   \n6             Highland Creek, Rouge Hill, Port Union                  0.0   \n\n   Auto Garage  Bakery       Bar  Breakfast Spot  Bus Line  Bus Station  Caf\u00e9  \\\n0          0.0     0.0  0.000000            0.25       0.0          0.0  0.00   \n1          0.0     0.0  0.000000            0.00       0.0          0.0  0.00   \n2          0.0     0.0  0.000000            0.00       0.0          0.0  0.25   \n3          0.0     0.2  0.000000            0.00       0.2          0.1  0.00   \n4          0.0     0.0  0.000000            0.00       0.0          0.0  0.00   \n5          0.0     0.0  0.000000            0.00       0.0          0.0  0.00   \n6          0.0     0.0  0.333333            0.00       0.0          0.0  0.00   \n\n   Chinese Restaurant  Clothing Store  Coffee Shop  College Stadium  \\\n0            0.000000            0.25          0.0             0.00   \n1            0.000000            0.00          0.0             0.00   \n2            0.000000            0.00          0.0             0.25   \n3            0.000000            0.00          0.0             0.00   \n4            0.000000            0.00          0.0             0.00   \n5            0.142857            0.00          0.0             0.00   \n6            0.000000            0.00          0.0             0.00   \n\n   Convenience Store  Department Store  Discount Store  Electronics Store  \\\n0                0.0               0.0             0.0                0.0   \n1                0.0               0.0             0.0                0.0   \n2                0.0               0.0             0.0                0.0   \n3                0.0               0.0             0.0                0.0   \n4                0.0               0.0             0.0                0.0   \n5                0.0               0.0             0.0                0.0   \n6                0.0               0.0             0.0                0.0   \n\n   Fast Food Restaurant  Fried Chicken Joint  Furniture / Home Store  \\\n0                   0.0                  0.0                0.000000   \n1                   0.0                  0.0                0.000000   \n2                   0.0                  0.0                0.000000   \n3                   0.1                  0.0                0.000000   \n4                   0.0                  0.0                0.000000   \n5                   0.0                  0.0                0.142857   \n6                   0.0                  0.0                0.000000   \n\n   General Entertainment  History Museum  Indian Restaurant  Insurance Office  \\\n0                   0.00        0.000000           0.000000               0.0   \n1                   0.00        0.000000           0.000000               0.0   \n2                   0.25        0.000000           0.000000               0.0   \n3                   0.00        0.000000           0.000000               0.0   \n4                   0.00        0.000000           0.000000               0.0   \n5                   0.00        0.000000           0.285714               0.0   \n6                   0.00        0.333333           0.000000               0.0   \n\n   Intersection  Italian Restaurant  Korean Restaurant  \\\n0           0.0                 0.0                0.0   \n1           0.0                 0.0                0.0   \n2           0.0                 0.0                0.0   \n3           0.1                 0.0                0.0   \n4           0.0                 0.0                0.0   \n5           0.0                 0.0                0.0   \n6           0.0                 0.0                0.0   \n\n   Latin American Restaurant  Lounge  Medical Center  Metro Station  \\\n0                   0.000000    0.25             0.0            0.0   \n1                   0.000000    0.00             0.0            0.0   \n2                   0.000000    0.00             0.0            0.0   \n3                   0.000000    0.00             0.0            0.1   \n4                   0.000000    0.00             0.0            0.0   \n5                   0.142857    0.00             0.0            0.0   \n6                   0.000000    0.00             0.0            0.0   \n\n   Mexican Restaurant  Middle Eastern Restaurant  Motel  Moving Target  \\\n0                 0.0                        0.0    0.0       0.000000   \n1                 0.0                        0.0    0.0       0.000000   \n2                 0.0                        0.0    0.0       0.000000   \n3                 0.0                        0.0    0.0       0.000000   \n4                 0.0                        0.0    0.5       0.000000   \n5                 0.0                        0.0    0.0       0.000000   \n6                 0.0                        0.0    0.0       0.333333   \n\n   Noodle House  Park  Pet Store  Pharmacy  Pizza Place  Playground  \\\n0           0.0   0.0   0.000000       0.0          0.0         0.0   \n1           0.0   0.5   0.000000       0.0          0.0         0.5   \n2           0.0   0.0   0.000000       0.0          0.0         0.0   \n3           0.0   0.1   0.000000       0.0          0.0         0.0   \n4           0.0   0.0   0.000000       0.0          0.0         0.0   \n5           0.0   0.0   0.142857       0.0          0.0         0.0   \n6           0.0   0.0   0.000000       0.0          0.0         0.0   \n\n   Rental Car Location  Sandwich Place  Skating Rink  Soccer Field  Spa  \\\n0                  0.0             0.0          0.25           0.0  0.0   \n1                  0.0             0.0          0.00           0.0  0.0   \n2                  0.0             0.0          0.25           0.0  0.0   \n3                  0.0             0.0          0.00           0.1  0.0   \n4                  0.0             0.0          0.00           0.0  0.0   \n5                  0.0             0.0          0.00           0.0  0.0   \n6                  0.0             0.0          0.00           0.0  0.0   \n\n   Thai Restaurant  Vietnamese Restaurant  \n0              0.0               0.000000  \n1              0.0               0.000000  \n2              0.0               0.000000  \n3              0.0               0.000000  \n4              0.0               0.000000  \n5              0.0               0.142857  \n6              0.0               0.000000  "
                    }, 
                    "execution_count": 47, 
                    "metadata": {}
                }
            ], 
            "execution_count": 47
        }, 
        {
            "source": "def return_most_common_venues(row, num_top_venues):\n    row_categories = row.iloc[1:]\n    row_categories_sorted = row_categories.sort_values(ascending=False)\n    \n    return row_categories_sorted.index.values[0:num_top_venues]", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "execution_count": 48
        }, 
        {
            "source": "num_top_venues = 10\n\nindicators = ['st', 'nd', 'rd']\n\n# create columns according to number of top venues\ncolumns = ['Neighborhood']\nfor ind in np.arange(num_top_venues):\n    try:\n        columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))\n    except:\n        columns.append('{}th Most Common Venue'.format(ind+1))\n\n# create a new dataframe\nneighborhoods_venues_sorted = pd.DataFrame(columns=columns)\nneighborhoods_venues_sorted['Neighborhood'] = scarb_grouped['Neighborhood']\n\nfor ind in np.arange(scarb_grouped.shape[0]):\n    neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(scarb_grouped.iloc[ind, :], num_top_venues)\n\nneighborhoods_venues_sorted", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>1st Most Common Venue</th>\n      <th>2nd Most Common Venue</th>\n      <th>3rd Most Common Venue</th>\n      <th>4th Most Common Venue</th>\n      <th>5th Most Common Venue</th>\n      <th>6th Most Common Venue</th>\n      <th>7th Most Common Venue</th>\n      <th>8th Most Common Venue</th>\n      <th>9th Most Common Venue</th>\n      <th>10th Most Common Venue</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Agincourt</td>\n      <td>Skating Rink</td>\n      <td>Breakfast Spot</td>\n      <td>Lounge</td>\n      <td>Clothing Store</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Agincourt North, Milliken</td>\n      <td>Playground</td>\n      <td>Park</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Coffee Shop</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Birch Cliff</td>\n      <td>College Stadium</td>\n      <td>General Entertainment</td>\n      <td>Skating Rink</td>\n      <td>Caf\u00e9</td>\n      <td>Vietnamese Restaurant</td>\n      <td>History Museum</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Clairlea, Golden Mile, Oakridge</td>\n      <td>Bakery</td>\n      <td>Bus Line</td>\n      <td>Intersection</td>\n      <td>Soccer Field</td>\n      <td>Bus Station</td>\n      <td>Fast Food Restaurant</td>\n      <td>Park</td>\n      <td>Metro Station</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Cliffcrest, Cliffside</td>\n      <td>American Restaurant</td>\n      <td>Motel</td>\n      <td>Insurance Office</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Dorset Park, Scarborough Town Centre, Wexford ...</td>\n      <td>Indian Restaurant</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Furniture / Home Store</td>\n      <td>Latin American Restaurant</td>\n      <td>Chinese Restaurant</td>\n      <td>Pet Store</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Highland Creek, Rouge Hill, Port Union</td>\n      <td>Moving Target</td>\n      <td>History Museum</td>\n      <td>Bar</td>\n      <td>Vietnamese Restaurant</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Ionview, Kennedy Park</td>\n      <td>Coffee Shop</td>\n      <td>Convenience Store</td>\n      <td>Bus Station</td>\n      <td>Chinese Restaurant</td>\n      <td>Discount Store</td>\n      <td>Department Store</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Maryvale, Wexford</td>\n      <td>Auto Garage</td>\n      <td>Bakery</td>\n      <td>Sandwich Place</td>\n      <td>Breakfast Spot</td>\n      <td>Middle Eastern Restaurant</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Morningside, West Hill</td>\n      <td>Intersection</td>\n      <td>Spa</td>\n      <td>Rental Car Location</td>\n      <td>Breakfast Spot</td>\n      <td>Pizza Place</td>\n      <td>Electronics Store</td>\n      <td>Medical Center</td>\n      <td>Mexican Restaurant</td>\n      <td>College Stadium</td>\n      <td>Furniture / Home Store</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Rouge, Malvern</td>\n      <td>Fast Food Restaurant</td>\n      <td>Vietnamese Restaurant</td>\n      <td>College Stadium</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n      <td>Department Store</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Scarborough Village</td>\n      <td>Spa</td>\n      <td>Playground</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Coffee Shop</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>Tam O'Shanter</td>\n      <td>Pizza Place</td>\n      <td>Chinese Restaurant</td>\n      <td>Fried Chicken Joint</td>\n      <td>Thai Restaurant</td>\n      <td>Italian Restaurant</td>\n      <td>Fast Food Restaurant</td>\n      <td>Rental Car Location</td>\n      <td>Pharmacy</td>\n      <td>Noodle House</td>\n      <td>Coffee Shop</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>Woburn</td>\n      <td>Coffee Shop</td>\n      <td>Korean Restaurant</td>\n      <td>Insurance Office</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Convenience Store</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "                                         Neighborhood 1st Most Common Venue  \\\n0                                           Agincourt          Skating Rink   \n1                           Agincourt North, Milliken            Playground   \n2                                         Birch Cliff       College Stadium   \n3                     Clairlea, Golden Mile, Oakridge                Bakery   \n4                               Cliffcrest, Cliffside   American Restaurant   \n5   Dorset Park, Scarborough Town Centre, Wexford ...     Indian Restaurant   \n6              Highland Creek, Rouge Hill, Port Union         Moving Target   \n7                               Ionview, Kennedy Park           Coffee Shop   \n8                                   Maryvale, Wexford           Auto Garage   \n9                              Morningside, West Hill          Intersection   \n10                                     Rouge, Malvern  Fast Food Restaurant   \n11                                Scarborough Village                   Spa   \n12                                      Tam O'Shanter           Pizza Place   \n13                                             Woburn           Coffee Shop   \n\n    2nd Most Common Venue   3rd Most Common Venue      4th Most Common Venue  \\\n0          Breakfast Spot                  Lounge             Clothing Store   \n1                    Park   Vietnamese Restaurant                Coffee Shop   \n2   General Entertainment            Skating Rink                       Caf\u00e9   \n3                Bus Line            Intersection               Soccer Field   \n4                   Motel        Insurance Office             History Museum   \n5   Vietnamese Restaurant  Furniture / Home Store  Latin American Restaurant   \n6          History Museum                     Bar      Vietnamese Restaurant   \n7       Convenience Store             Bus Station         Chinese Restaurant   \n8                  Bakery          Sandwich Place             Breakfast Spot   \n9                     Spa     Rental Car Location             Breakfast Spot   \n10  Vietnamese Restaurant         College Stadium             History Museum   \n11             Playground   Vietnamese Restaurant                Coffee Shop   \n12     Chinese Restaurant     Fried Chicken Joint            Thai Restaurant   \n13      Korean Restaurant        Insurance Office      Vietnamese Restaurant   \n\n        5th Most Common Venue   6th Most Common Venue   7th Most Common Venue  \\\n0       Vietnamese Restaurant       Convenience Store   General Entertainment   \n1       General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n2       Vietnamese Restaurant          History Museum  Furniture / Home Store   \n3                 Bus Station    Fast Food Restaurant                    Park   \n4       General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n5          Chinese Restaurant               Pet Store       Convenience Store   \n6       General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n7              Discount Store        Department Store          History Museum   \n8   Middle Eastern Restaurant   Vietnamese Restaurant       Convenience Store   \n9                 Pizza Place       Electronics Store          Medical Center   \n10      General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n11      General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n12         Italian Restaurant    Fast Food Restaurant     Rental Car Location   \n13          Convenience Store          History Museum   General Entertainment   \n\n     8th Most Common Venue   9th Most Common Venue  10th Most Common Venue  \n0   Furniture / Home Store     Fried Chicken Joint    Fast Food Restaurant  \n1     Fast Food Restaurant       Electronics Store          Discount Store  \n2      Fried Chicken Joint    Fast Food Restaurant       Electronics Store  \n3            Metro Station       Convenience Store   General Entertainment  \n4     Fast Food Restaurant       Electronics Store          Discount Store  \n5    General Entertainment     Fried Chicken Joint    Fast Food Restaurant  \n6     Fast Food Restaurant       Electronics Store          Discount Store  \n7    General Entertainment  Furniture / Home Store     Fried Chicken Joint  \n8    General Entertainment  Furniture / Home Store     Fried Chicken Joint  \n9       Mexican Restaurant         College Stadium  Furniture / Home Store  \n10       Electronics Store          Discount Store        Department Store  \n11    Fast Food Restaurant       Electronics Store          Discount Store  \n12                Pharmacy            Noodle House             Coffee Shop  \n13  Furniture / Home Store     Fried Chicken Joint    Fast Food Restaurant  "
                    }, 
                    "execution_count": 49, 
                    "metadata": {}
                }
            ], 
            "execution_count": 49
        }, 
        {
            "source": "# import k-means from clustering stage\nfrom sklearn.cluster import KMeans\n\nscarb_data = scarborough_data.drop()\n# set number of clusters\nkclusters = 5\n\nscarb_grouped_clustering = scarb_grouped.drop('Neighborhood', 1)\n\n\n# run k-means clustering\nkmeans = KMeans(n_clusters=kclusters, random_state=0).fit(scarb_grouped_clustering)\n\n# check cluster labels generated for each row in the dataframe\nkmeans.labels_[0:10] \n#len(kmeans.labels_)#=16\n#scarborough_data.shape", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "data": {
                        "text/plain": "array([1, 3, 1, 1, 4, 1, 1, 1, 1, 1], dtype=int32)"
                    }, 
                    "execution_count": 51, 
                    "metadata": {}
                }
            ], 
            "execution_count": 51
        }, 
        {
            "source": "\nscarb_merged = scarb_data\n\n# add clustering labels\nscarb_merged['Cluster Labels'] = kmeans.labels_\n\n# merge toronto_grouped with toronto_data to add latitude/longitude for each neighborhood\nscarb_merged = scarb_merged.join(neighborhoods_venues_sorted.set_index('Neighborhood'), on='Neighbourhood')\n\nscarb_merged", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "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>Borough</th>\n      <th>Neighbourhood</th>\n      <th>Postcode</th>\n      <th>Latitude</th>\n      <th>Longitude</th>\n      <th>Cluster Labels</th>\n      <th>1st Most Common Venue</th>\n      <th>2nd Most Common Venue</th>\n      <th>3rd Most Common Venue</th>\n      <th>4th Most Common Venue</th>\n      <th>5th Most Common Venue</th>\n      <th>6th Most Common Venue</th>\n      <th>7th Most Common Venue</th>\n      <th>8th Most Common Venue</th>\n      <th>9th Most Common Venue</th>\n      <th>10th Most Common Venue</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>Scarborough</td>\n      <td>Birch Cliff</td>\n      <td>M1N</td>\n      <td>43.692657</td>\n      <td>-79.264848</td>\n      <td>1</td>\n      <td>College Stadium</td>\n      <td>General Entertainment</td>\n      <td>Skating Rink</td>\n      <td>Caf\u00e9</td>\n      <td>Vietnamese Restaurant</td>\n      <td>History Museum</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>Scarborough</td>\n      <td>Upper Rouge</td>\n      <td>M1X</td>\n      <td>43.836125</td>\n      <td>-79.205636</td>\n      <td>3</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>Scarborough</td>\n      <td>Rouge, Malvern</td>\n      <td>M1B</td>\n      <td>43.806686</td>\n      <td>-79.194353</td>\n      <td>1</td>\n      <td>Fast Food Restaurant</td>\n      <td>Vietnamese Restaurant</td>\n      <td>College Stadium</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n      <td>Department Store</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>Scarborough</td>\n      <td>Morningside, West Hill</td>\n      <td>M1E</td>\n      <td>43.763573</td>\n      <td>-79.188711</td>\n      <td>1</td>\n      <td>Intersection</td>\n      <td>Spa</td>\n      <td>Rental Car Location</td>\n      <td>Breakfast Spot</td>\n      <td>Pizza Place</td>\n      <td>Electronics Store</td>\n      <td>Medical Center</td>\n      <td>Mexican Restaurant</td>\n      <td>College Stadium</td>\n      <td>Furniture / Home Store</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>Scarborough</td>\n      <td>Maryvale, Wexford</td>\n      <td>M1R</td>\n      <td>43.750072</td>\n      <td>-79.295849</td>\n      <td>4</td>\n      <td>Auto Garage</td>\n      <td>Bakery</td>\n      <td>Sandwich Place</td>\n      <td>Breakfast Spot</td>\n      <td>Middle Eastern Restaurant</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>Scarborough</td>\n      <td>Agincourt</td>\n      <td>M1S</td>\n      <td>43.794200</td>\n      <td>-79.262029</td>\n      <td>1</td>\n      <td>Skating Rink</td>\n      <td>Breakfast Spot</td>\n      <td>Lounge</td>\n      <td>Clothing Store</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>Scarborough</td>\n      <td>Scarborough Village</td>\n      <td>M1J</td>\n      <td>43.744734</td>\n      <td>-79.239476</td>\n      <td>1</td>\n      <td>Spa</td>\n      <td>Playground</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Coffee Shop</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>Scarborough</td>\n      <td>Highland Creek, Rouge Hill, Port Union</td>\n      <td>M1C</td>\n      <td>43.784535</td>\n      <td>-79.160497</td>\n      <td>1</td>\n      <td>Moving Target</td>\n      <td>History Museum</td>\n      <td>Bar</td>\n      <td>Vietnamese Restaurant</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>Scarborough</td>\n      <td>Ionview, Kennedy Park</td>\n      <td>M1K</td>\n      <td>43.727929</td>\n      <td>-79.262029</td>\n      <td>1</td>\n      <td>Coffee Shop</td>\n      <td>Convenience Store</td>\n      <td>Bus Station</td>\n      <td>Chinese Restaurant</td>\n      <td>Discount Store</td>\n      <td>Department Store</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>Scarborough</td>\n      <td>Woburn</td>\n      <td>M1G</td>\n      <td>43.770992</td>\n      <td>-79.216917</td>\n      <td>1</td>\n      <td>Coffee Shop</td>\n      <td>Korean Restaurant</td>\n      <td>Insurance Office</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Convenience Store</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>Scarborough</td>\n      <td>Clairlea, Golden Mile, Oakridge</td>\n      <td>M1L</td>\n      <td>43.711112</td>\n      <td>-79.284577</td>\n      <td>2</td>\n      <td>Bakery</td>\n      <td>Bus Line</td>\n      <td>Intersection</td>\n      <td>Soccer Field</td>\n      <td>Bus Station</td>\n      <td>Fast Food Restaurant</td>\n      <td>Park</td>\n      <td>Metro Station</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>Scarborough</td>\n      <td>Dorset Park, Scarborough Town Centre, Wexford ...</td>\n      <td>M1P</td>\n      <td>43.757410</td>\n      <td>-79.273304</td>\n      <td>3</td>\n      <td>Indian Restaurant</td>\n      <td>Vietnamese Restaurant</td>\n      <td>Furniture / Home Store</td>\n      <td>Latin American Restaurant</td>\n      <td>Chinese Restaurant</td>\n      <td>Pet Store</td>\n      <td>Convenience Store</td>\n      <td>General Entertainment</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>Scarborough</td>\n      <td>Tam O'Shanter</td>\n      <td>M1T</td>\n      <td>43.781638</td>\n      <td>-79.304302</td>\n      <td>1</td>\n      <td>Pizza Place</td>\n      <td>Chinese Restaurant</td>\n      <td>Fried Chicken Joint</td>\n      <td>Thai Restaurant</td>\n      <td>Italian Restaurant</td>\n      <td>Fast Food Restaurant</td>\n      <td>Rental Car Location</td>\n      <td>Pharmacy</td>\n      <td>Noodle House</td>\n      <td>Coffee Shop</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>Scarborough</td>\n      <td>Cliffcrest, Cliffside</td>\n      <td>M1M</td>\n      <td>43.716316</td>\n      <td>-79.239476</td>\n      <td>0</td>\n      <td>American Restaurant</td>\n      <td>Motel</td>\n      <td>Insurance Office</td>\n      <td>History Museum</td>\n      <td>General Entertainment</td>\n      <td>Furniture / Home Store</td>\n      <td>Fried Chicken Joint</td>\n      <td>Fast Food Restaurant</td>\n      <td>Electronics Store</td>\n      <td>Discount Store</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "        Borough                                      Neighbourhood Postcode  \\\n0   Scarborough                                        Birch Cliff      M1N   \n1   Scarborough                                        Upper Rouge      M1X   \n2   Scarborough                                     Rouge, Malvern      M1B   \n3   Scarborough                             Morningside, West Hill      M1E   \n4   Scarborough                                  Maryvale, Wexford      M1R   \n5   Scarborough                                          Agincourt      M1S   \n6   Scarborough                                Scarborough Village      M1J   \n7   Scarborough             Highland Creek, Rouge Hill, Port Union      M1C   \n8   Scarborough                              Ionview, Kennedy Park      M1K   \n9   Scarborough                                             Woburn      M1G   \n10  Scarborough                    Clairlea, Golden Mile, Oakridge      M1L   \n11  Scarborough  Dorset Park, Scarborough Town Centre, Wexford ...      M1P   \n12  Scarborough                                      Tam O'Shanter      M1T   \n13  Scarborough                              Cliffcrest, Cliffside      M1M   \n\n     Latitude  Longitude  Cluster Labels 1st Most Common Venue  \\\n0   43.692657 -79.264848               1       College Stadium   \n1   43.836125 -79.205636               3                   NaN   \n2   43.806686 -79.194353               1  Fast Food Restaurant   \n3   43.763573 -79.188711               1          Intersection   \n4   43.750072 -79.295849               4           Auto Garage   \n5   43.794200 -79.262029               1          Skating Rink   \n6   43.744734 -79.239476               1                   Spa   \n7   43.784535 -79.160497               1         Moving Target   \n8   43.727929 -79.262029               1           Coffee Shop   \n9   43.770992 -79.216917               1           Coffee Shop   \n10  43.711112 -79.284577               2                Bakery   \n11  43.757410 -79.273304               3     Indian Restaurant   \n12  43.781638 -79.304302               1           Pizza Place   \n13  43.716316 -79.239476               0   American Restaurant   \n\n    2nd Most Common Venue   3rd Most Common Venue      4th Most Common Venue  \\\n0   General Entertainment            Skating Rink                       Caf\u00e9   \n1                     NaN                     NaN                        NaN   \n2   Vietnamese Restaurant         College Stadium             History Museum   \n3                     Spa     Rental Car Location             Breakfast Spot   \n4                  Bakery          Sandwich Place             Breakfast Spot   \n5          Breakfast Spot                  Lounge             Clothing Store   \n6              Playground   Vietnamese Restaurant                Coffee Shop   \n7          History Museum                     Bar      Vietnamese Restaurant   \n8       Convenience Store             Bus Station         Chinese Restaurant   \n9       Korean Restaurant        Insurance Office      Vietnamese Restaurant   \n10               Bus Line            Intersection               Soccer Field   \n11  Vietnamese Restaurant  Furniture / Home Store  Latin American Restaurant   \n12     Chinese Restaurant     Fried Chicken Joint            Thai Restaurant   \n13                  Motel        Insurance Office             History Museum   \n\n        5th Most Common Venue   6th Most Common Venue   7th Most Common Venue  \\\n0       Vietnamese Restaurant          History Museum  Furniture / Home Store   \n1                         NaN                     NaN                     NaN   \n2       General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n3                 Pizza Place       Electronics Store          Medical Center   \n4   Middle Eastern Restaurant   Vietnamese Restaurant       Convenience Store   \n5       Vietnamese Restaurant       Convenience Store   General Entertainment   \n6       General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n7       General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n8              Discount Store        Department Store          History Museum   \n9           Convenience Store          History Museum   General Entertainment   \n10                Bus Station    Fast Food Restaurant                    Park   \n11         Chinese Restaurant               Pet Store       Convenience Store   \n12         Italian Restaurant    Fast Food Restaurant     Rental Car Location   \n13      General Entertainment  Furniture / Home Store     Fried Chicken Joint   \n\n     8th Most Common Venue   9th Most Common Venue  10th Most Common Venue  \n0      Fried Chicken Joint    Fast Food Restaurant       Electronics Store  \n1                      NaN                     NaN                     NaN  \n2        Electronics Store          Discount Store        Department Store  \n3       Mexican Restaurant         College Stadium  Furniture / Home Store  \n4    General Entertainment  Furniture / Home Store     Fried Chicken Joint  \n5   Furniture / Home Store     Fried Chicken Joint    Fast Food Restaurant  \n6     Fast Food Restaurant       Electronics Store          Discount Store  \n7     Fast Food Restaurant       Electronics Store          Discount Store  \n8    General Entertainment  Furniture / Home Store     Fried Chicken Joint  \n9   Furniture / Home Store     Fried Chicken Joint    Fast Food Restaurant  \n10           Metro Station       Convenience Store   General Entertainment  \n11   General Entertainment     Fried Chicken Joint    Fast Food Restaurant  \n12                Pharmacy            Noodle House             Coffee Shop  \n13    Fast Food Restaurant       Electronics Store          Discount Store  "
                    }, 
                    "execution_count": 52, 
                    "metadata": {}
                }
            ], 
            "execution_count": 52
        }, 
        {
            "source": "# Matplotlib and associated plotting modules\nimport matplotlib.cm as cm\nimport matplotlib.colors as colors\n\n# create map\nmap_clusters = folium.Map(location = [latitude_scar, longitude_scar], zoom_start=11)\n\n# set color scheme for the clusters\nx = np.arange(kclusters)\nys = [i+x+(i*x)**2 for i in range(kclusters)]\ncolors_array = cm.rainbow(np.linspace(0, 1, len(ys)))\nrainbow = [colors.rgb2hex(i) for i in colors_array]\n\n# add markers to the map\nmarkers_colors = []\nfor lat, lon, poi, cluster in zip(scarb_merged['Latitude'], scarb_merged['Longitude'], scarb_merged['Neighbourhood'], scarb_merged['Cluster Labels']):\n    label = folium.Popup(str(poi) + ' Cluster ' + str(cluster), parse_html=True)\n    folium.CircleMarker(\n        [lat, lon],\n        radius=5,\n        popup=label,\n        color=rainbow[cluster-1],\n        fill=True,\n        fill_color=rainbow[cluster-1],\n        fill_opacity=0.7).add_to(map_clusters)\n       \nmap_clusters", 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "output_type": "execute_result", 
                    "data": {
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