week3_assigment_3_carol.ipynb

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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Assigment of week 3.\n",
    "## Segmenting and Clustering Neighborhoods in Toronto\n",
    "### Part 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, I'll explore and cluster the neighborhoods in Toronto."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting package metadata (current_repodata.json): done\n",
      "Solving environment: done\n",
      "\n",
      "## Package Plan ##\n",
      "\n",
      "  environment location: /home/jupyterlab/conda/envs/python\n",
      "\n",
      "  added / updated specs:\n",
      "    - geopy\n",
      "\n",
      "\n",
      "The following packages will be downloaded:\n",
      "\n",
      "    package                    |            build\n",
      "    ---------------------------|-----------------\n",
      "    geographiclib-1.50         |             py_0          34 KB  conda-forge\n",
      "    geopy-1.22.0               |     pyh9f0ad1d_0          63 KB  conda-forge\n",
      "    ------------------------------------------------------------\n",
      "                                           Total:          97 KB\n",
      "\n",
      "The following NEW packages will be INSTALLED:\n",
      "\n",
      "  geographiclib      conda-forge/noarch::geographiclib-1.50-py_0\n",
      "  geopy              conda-forge/noarch::geopy-1.22.0-pyh9f0ad1d_0\n",
      "\n",
      "\n",
      "\n",
      "Downloading and Extracting Packages\n",
      "geopy-1.22.0         | 63 KB     | ##################################### | 100% \n",
      "geographiclib-1.50   | 34 KB     | ##################################### | 100% \n",
      "Preparing transaction: done\n",
      "Verifying transaction: done\n",
      "Executing transaction: done\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.colors as colors\n",
    "\n",
    "!conda install -c conda-forge geopy --yes # uncomment this line if you haven't completed the Foursquare API lab\n",
    "from geopy.geocoders import Nominatim # convert an address into latitude and longitude values\n",
    "\n",
    "# import k-means from clustering stage\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "#!conda install -c conda-forge folium=0.5.0 --yes # uncomment this line if you haven't completed the Foursquare API lab\n",
    "import folium # map rendering library"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Download and Explore Dataset\n",
    "\n",
    "In previews notebook I worked preparing the dataframe with the information of Postal code of Toronto, with names of Borough, neigborhoods and latitude and longitude data.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>M1B</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Malvern, Rouge</td>\n",
       "      <td>43.806686</td>\n",
       "      <td>-79.194353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Rouge Hill, Port Union, Highland Creek</td>\n",
       "      <td>43.784535</td>\n",
       "      <td>-79.160497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Guildwood, Morningside, West Hill</td>\n",
       "      <td>43.763573</td>\n",
       "      <td>-79.188711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>M1G</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Woburn</td>\n",
       "      <td>43.770992</td>\n",
       "      <td>-79.216917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>M1H</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cedarbrae</td>\n",
       "      <td>43.773136</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "   Unnamed: 0 Postal Code      Borough  \\\n",
       "0           0         M1B  Scarborough   \n",
       "1           1         M1C  Scarborough   \n",
       "2           2         M1E  Scarborough   \n",
       "3           3         M1G  Scarborough   \n",
       "4           4         M1H  Scarborough   \n",
       "\n",
       "                             Neighborhood   Latitude  Longitude  \n",
       "0                          Malvern, Rouge  43.806686 -79.194353  \n",
       "1  Rouge Hill, Port Union, Highland Creek  43.784535 -79.160497  \n",
       "2       Guildwood, Morningside, West Hill  43.763573 -79.188711  \n",
       "3                                  Woburn  43.770992 -79.216917  \n",
       "4                               Cedarbrae  43.773136 -79.239476  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read the file with the whole data\n",
    "neighborhoods=pd.read_csv('toronto_data.csv')\n",
    "neighborhoods.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Toronto are 43.6534817, -79.3839347.\n"
     ]
    }
   ],
   "source": [
    "address = 'Toronto, CA'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"ny_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "print('The geograpical coordinate of Toronto are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Create a map of Toronto with borough superimposed on top."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f1db7fa5d30>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Toronto using latitude and longitude values\n",
    "map_toronto = folium.Map(location=[latitude, longitude], zoom_start=10)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, borough, neighborhood in zip(neighborhoods['Latitude'], neighborhoods['Longitude'], neighborhoods['Borough'], neighborhoods['Neighborhood']):\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,\n",
    "        parse_html=False).add_to(map_toronto)  \n",
    "    \n",
    "map_toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's segment and cluster only the neighborhoods in Central Toronto. So let's slice the original dataframe and create a new dataframe of the Central Toronto data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>44</td>\n",
       "      <td>M4N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45</td>\n",
       "      <td>M4P</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>46</td>\n",
       "      <td>M4R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>43.715383</td>\n",
       "      <td>-79.405678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>47</td>\n",
       "      <td>M4S</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville</td>\n",
       "      <td>43.704324</td>\n",
       "      <td>-79.388790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48</td>\n",
       "      <td>M4T</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>43.689574</td>\n",
       "      <td>-79.383160</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 Postal Code          Borough                       Neighborhood  \\\n",
       "0          44         M4N  Central Toronto                      Lawrence Park   \n",
       "1          45         M4P  Central Toronto                   Davisville North   \n",
       "2          46         M4R  Central Toronto  North Toronto West, Lawrence Park   \n",
       "3          47         M4S  Central Toronto                         Davisville   \n",
       "4          48         M4T  Central Toronto        Moore Park, Summerhill East   \n",
       "\n",
       "    Latitude  Longitude  \n",
       "0  43.728020 -79.388790  \n",
       "1  43.712751 -79.390197  \n",
       "2  43.715383 -79.405678  \n",
       "3  43.704324 -79.388790  \n",
       "4  43.689574 -79.383160  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralT_data = neighborhoods[neighborhoods['Borough'] == 'Central Toronto'].reset_index(drop=True)\n",
    "centralT_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's get the geographical coordinates of Central Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The geograpical coordinate of Central Toronto are 43.6534817, -79.3839347.\n"
     ]
    }
   ],
   "source": [
    "address = 'Central Toronto, Toronto'\n",
    "\n",
    "geolocator = Nominatim(user_agent=\"ny_explorer\")\n",
    "location = geolocator.geocode(address)\n",
    "latitude = location.latitude\n",
    "longitude = location.longitude\n",
    "print('The geograpical coordinate of Central Toronto are {}, {}.'.format(latitude, longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we did with all of Toronto City, let's visualizate Central Toronto the neighborhoods in it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
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</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f1db7d56e48>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create map of Central Toronto using latitude and longitude values\n",
    "map_centralt = folium.Map(location=[latitude, longitude], zoom_start=11)\n",
    "\n",
    "# add markers to map\n",
    "for lat, lng, label in zip(centralT_data['Latitude'], centralT_data['Longitude'], centralT_data['Neighborhood']):\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,\n",
    "        parse_html=False).add_to(map_centralt)  \n",
    "    \n",
    "map_centralt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we are going to start utilizing the Foursquare API to explore the borough and segment them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your credentails:\n",
      "CLIENT_ID: SDB14ASDOOCN0HI0UDVMFPWSZOEKG5M1LOI5FNDTBKXNOIIB\n",
      "CLIENT_SECRET:RYALKSQNP4PAX1U2LV31JMYJOQ2K2HG4YXHR5SUR0WCLWAHA\n"
     ]
    }
   ],
   "source": [
    "#define Foursquare credentials\n",
    "CLIENT_ID = 'SDB14ASDOOCN0HI0UDVMFPWSZOEKG5M1LOI5FNDTBKXNOIIB' # your Foursquare ID\n",
    "CLIENT_SECRET = 'RYALKSQNP4PAX1U2LV31JMYJOQ2K2HG4YXHR5SUR0WCLWAHA' # your Foursquare Secret\n",
    "VERSION = '20200603' # Foursquare API version\n",
    "\n",
    "print('Your credentails:')\n",
    "print('CLIENT_ID: ' + CLIENT_ID)\n",
    "print('CLIENT_SECRET:' + CLIENT_SECRET)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's explore the first borough in our dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Central Toronto'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Get the borough's name.\n",
    "centralT_data.loc[0, 'Borough']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get the borough's latitude and longitude values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Latitude and longitude values of Central Toronto are 43.7280205, -79.3887901.\n"
     ]
    }
   ],
   "source": [
    "borough_latitude = centralT_data.loc[0, 'Latitude'] # neighborhood latitude value\n",
    "borough_longitude = centralT_data.loc[0, 'Longitude'] # neighborhood longitude value\n",
    "\n",
    "borough_name = centralT_data.loc[0, 'Borough'] # neighborhood name\n",
    "\n",
    "print('Latitude and longitude values of {} are {}, {}.'.format(borough_name, \n",
    "                                                               borough_latitude, \n",
    "                                                               borough_longitude))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Now, let's get the top 100 venues that are in Central Toronto within a radius of 500 meters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.foursquare.com/v2/venues/explore?&client_id=SDB14ASDOOCN0HI0UDVMFPWSZOEKG5M1LOI5FNDTBKXNOIIB&client_secret=RYALKSQNP4PAX1U2LV31JMYJOQ2K2HG4YXHR5SUR0WCLWAHA&v=20200603&ll=43.7280205,-79.3887901&radius=500&limit=100'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#First, let's create the GET request URL. Name your URL **url**.\n",
    "# type your answer here\n",
    "\n",
    "LIMIT = 100 # limit of number of venues returned by Foursquare API\n",
    "\n",
    "radius = 500 # define radius\n",
    "\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",
    "    borough_latitude, \n",
    "    borough_longitude, \n",
    "    radius, \n",
    "    LIMIT)\n",
    "url # display URL\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Send the GET request and examine the resutls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'meta': {'code': 200, 'requestId': '5ed7f47cf7706a001ba313ba'},\n",
       " 'response': {'warning': {'text': \"There aren't a lot of results near you. Try something more general, reset your filters, or expand the search area.\"},\n",
       "  'headerLocation': 'Toronto',\n",
       "  'headerFullLocation': 'Toronto',\n",
       "  'headerLocationGranularity': 'city',\n",
       "  'totalResults': 3,\n",
       "  'suggestedBounds': {'ne': {'lat': 43.7325205045, 'lng': -79.3825744605273},\n",
       "   'sw': {'lat': 43.7235204955, 'lng': -79.3950057394727}},\n",
       "  'groups': [{'type': 'Recommended Places',\n",
       "    'name': 'recommended',\n",
       "    'items': [{'reasons': {'count': 0,\n",
       "       'items': [{'summary': 'This spot is popular',\n",
       "         'type': 'general',\n",
       "         'reasonName': 'globalInteractionReason'}]},\n",
       "      'venue': {'id': '50e6da19e4b0d8a78a0e9794',\n",
       "       'name': 'Lawrence Park Ravine',\n",
       "       'location': {'address': '3055 Yonge Street',\n",
       "        'crossStreet': 'Lawrence Avenue East',\n",
       "        'lat': 43.72696303913755,\n",
       "        'lng': -79.39438246708775,\n",
       "        'labeledLatLngs': [{'label': 'display',\n",
       "          'lat': 43.72696303913755,\n",
       "          'lng': -79.39438246708775}],\n",
       "        'distance': 465,\n",
       "        'cc': 'CA',\n",
       "        'city': 'Toronto',\n",
       "        'state': 'ON',\n",
       "        'country': 'Canada',\n",
       "        'formattedAddress': ['3055 Yonge Street (Lawrence Avenue East)',\n",
       "         'Toronto ON',\n",
       "         'Canada']},\n",
       "       'categories': [{'id': '4bf58dd8d48988d163941735',\n",
       "         'name': 'Park',\n",
       "         'pluralName': 'Parks',\n",
       "         'shortName': 'Park',\n",
       "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/parks_outdoors/park_',\n",
       "          'suffix': '.png'},\n",
       "         'primary': True}],\n",
       "       'photos': {'count': 0, 'groups': []}},\n",
       "      'referralId': 'e-0-50e6da19e4b0d8a78a0e9794-0'},\n",
       "     {'reasons': {'count': 0,\n",
       "       'items': [{'summary': 'This spot is popular',\n",
       "         'type': 'general',\n",
       "         'reasonName': 'globalInteractionReason'}]},\n",
       "      'venue': {'id': '5082ef77e4b0a7491cf7b022',\n",
       "       'name': 'Zodiac Swim School',\n",
       "       'location': {'lat': 43.72853205765438,\n",
       "        'lng': -79.3828602612317,\n",
       "        'labeledLatLngs': [{'label': 'display',\n",
       "          'lat': 43.72853205765438,\n",
       "          'lng': -79.3828602612317}],\n",
       "        'distance': 480,\n",
       "        'cc': 'CA',\n",
       "        'country': 'Canada',\n",
       "        'formattedAddress': ['Canada']},\n",
       "       'categories': [{'id': '52e81612bcbc57f1066b7a44',\n",
       "         'name': 'Swim School',\n",
       "         'pluralName': 'Swim Schools',\n",
       "         'shortName': 'Swim School',\n",
       "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/parks_outdoors/pool_',\n",
       "          'suffix': '.png'},\n",
       "         'primary': True}],\n",
       "       'photos': {'count': 0, 'groups': []}},\n",
       "      'referralId': 'e-0-5082ef77e4b0a7491cf7b022-1'},\n",
       "     {'reasons': {'count': 0,\n",
       "       'items': [{'summary': 'This spot is popular',\n",
       "         'type': 'general',\n",
       "         'reasonName': 'globalInteractionReason'}]},\n",
       "      'venue': {'id': '50ed9da8e4b081eabee12672',\n",
       "       'name': 'TTC Bus #162 - Lawrence-Donway',\n",
       "       'location': {'lat': 43.72802605799448,\n",
       "        'lng': -79.38280527753858,\n",
       "        'labeledLatLngs': [{'label': 'display',\n",
       "          'lat': 43.72802605799448,\n",
       "          'lng': -79.38280527753858}],\n",
       "        'distance': 481,\n",
       "        'cc': 'CA',\n",
       "        'city': 'Toronto',\n",
       "        'state': 'ON',\n",
       "        'country': 'Canada',\n",
       "        'formattedAddress': ['Toronto ON', 'Canada']},\n",
       "       'categories': [{'id': '4bf58dd8d48988d12b951735',\n",
       "         'name': 'Bus Line',\n",
       "         'pluralName': 'Bus Lines',\n",
       "         'shortName': 'Bus',\n",
       "         'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/travel/busstation_',\n",
       "          'suffix': '.png'},\n",
       "         'primary': True}],\n",
       "       'photos': {'count': 0, 'groups': []}},\n",
       "      'referralId': 'e-0-50ed9da8e4b081eabee12672-2'}]}]}}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import requests # library to handle requests\n",
    "from pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe\n",
    "\n",
    "results = requests.get(url).json()\n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function that extracts the category of the venue\n",
    "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": "markdown",
   "metadata": {},
   "source": [
    "Now we are ready to clean the json and structure it into a *pandas* dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jupyterlab/conda/envs/python/lib/python3.6/site-packages/ipykernel_launcher.py:3: FutureWarning: pandas.io.json.json_normalize is deprecated, use pandas.json_normalize instead\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>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>Lawrence Park Ravine</td>\n",
       "      <td>Park</td>\n",
       "      <td>43.726963</td>\n",
       "      <td>-79.394382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Zodiac Swim School</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>43.728532</td>\n",
       "      <td>-79.382860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TTC Bus #162 - Lawrence-Donway</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>43.728026</td>\n",
       "      <td>-79.382805</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             name   categories        lat        lng\n",
       "0            Lawrence Park Ravine         Park  43.726963 -79.394382\n",
       "1              Zodiac Swim School  Swim School  43.728532 -79.382860\n",
       "2  TTC Bus #162 - Lawrence-Donway     Bus Line  43.728026 -79.382805"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "venues = results['response']['groups'][0]['items']\n",
    "    \n",
    "nearby_venues = json_normalize(venues) # flatten JSON\n",
    "\n",
    "# filter columns\n",
    "filtered_columns = ['venue.name', 'venue.categories', 'venue.location.lat', 'venue.location.lng']\n",
    "nearby_venues =nearby_venues.loc[:, filtered_columns]\n",
    "\n",
    "# filter the category for each row\n",
    "nearby_venues['venue.categories'] = nearby_venues.apply(get_category_type, axis=1)\n",
    "\n",
    "# clean columns\n",
    "nearby_venues.columns = [col.split(\".\")[-1] for col in nearby_venues.columns]\n",
    "\n",
    "nearby_venues.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And how many venues were returned by Foursquare?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 venues were returned by Foursquare.\n"
     ]
    }
   ],
   "source": [
    "print('{} venues were returned by Foursquare.'.format(nearby_venues.shape[0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Explore Neighborhoods in Central Toronto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's create a function to repeat the same process to all the borough in Central Toronto"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "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": "markdown",
   "metadata": {},
   "source": [
    "#### Now write the code to run the above function on each borough and create a new dataframe called *centralT_venues*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lawrence Park\n",
      "Davisville North\n",
      "North Toronto West, Lawrence Park\n",
      "Davisville\n",
      "Moore Park, Summerhill East\n",
      "Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park\n",
      "Roselawn\n",
      "Forest Hill Road Park, Forest Hill North & West\n",
      "The Annex, North Midtown, Yorkville\n"
     ]
    }
   ],
   "source": [
    "# type your answer here\n",
    "\n",
    "centralT_venues = getNearbyVenues(names=centralT_data['Neighborhood'],\n",
    "                                   latitudes=centralT_data['Latitude'],\n",
    "                                   longitudes=centralT_data['Longitude']\n",
    "                                  )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's check the size of the resulting dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(114, 7)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>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>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>Lawrence Park Ravine</td>\n",
       "      <td>43.726963</td>\n",
       "      <td>-79.394382</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>Zodiac Swim School</td>\n",
       "      <td>43.728532</td>\n",
       "      <td>-79.382860</td>\n",
       "      <td>Swim School</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>TTC Bus #162 - Lawrence-Donway</td>\n",
       "      <td>43.728026</td>\n",
       "      <td>-79.382805</td>\n",
       "      <td>Bus Line</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "      <td>Homeway Restaurant &amp; Brunch</td>\n",
       "      <td>43.712641</td>\n",
       "      <td>-79.391557</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "      <td>Sherwood Park</td>\n",
       "      <td>43.716551</td>\n",
       "      <td>-79.387776</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Neighborhood  Neighborhood Latitude  Neighborhood Longitude  \\\n",
       "0     Lawrence Park              43.728020              -79.388790   \n",
       "1     Lawrence Park              43.728020              -79.388790   \n",
       "2     Lawrence Park              43.728020              -79.388790   \n",
       "3  Davisville North              43.712751              -79.390197   \n",
       "4  Davisville North              43.712751              -79.390197   \n",
       "\n",
       "                            Venue  Venue Latitude  Venue Longitude  \\\n",
       "0            Lawrence Park Ravine       43.726963       -79.394382   \n",
       "1              Zodiac Swim School       43.728532       -79.382860   \n",
       "2  TTC Bus #162 - Lawrence-Donway       43.728026       -79.382805   \n",
       "3     Homeway Restaurant & Brunch       43.712641       -79.391557   \n",
       "4                   Sherwood Park       43.716551       -79.387776   \n",
       "\n",
       "   Venue Category  \n",
       "0            Park  \n",
       "1     Swim School  \n",
       "2        Bus Line  \n",
       "3  Breakfast Spot  \n",
       "4            Park  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(centralT_venues.shape)\n",
    "centralT_venues.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>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>109</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>43.67271</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>Tim Hortons</td>\n",
       "      <td>43.675800</td>\n",
       "      <td>-79.403532</td>\n",
       "      <td>Coffee Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>43.67271</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>Subway</td>\n",
       "      <td>43.675650</td>\n",
       "      <td>-79.410255</td>\n",
       "      <td>Sandwich Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>43.67271</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>Nick's Shoe Repair</td>\n",
       "      <td>43.675457</td>\n",
       "      <td>-79.403675</td>\n",
       "      <td>Shoe Repair</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>43.67271</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>The Kitchen Table</td>\n",
       "      <td>43.675770</td>\n",
       "      <td>-79.402746</td>\n",
       "      <td>Grocery Store</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>43.67271</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>Davenport Garden Centre</td>\n",
       "      <td>43.675851</td>\n",
       "      <td>-79.401894</td>\n",
       "      <td>Flower Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Neighborhood  Neighborhood Latitude  \\\n",
       "109  The Annex, North Midtown, Yorkville               43.67271   \n",
       "110  The Annex, North Midtown, Yorkville               43.67271   \n",
       "111  The Annex, North Midtown, Yorkville               43.67271   \n",
       "112  The Annex, North Midtown, Yorkville               43.67271   \n",
       "113  The Annex, North Midtown, Yorkville               43.67271   \n",
       "\n",
       "     Neighborhood Longitude                    Venue  Venue Latitude  \\\n",
       "109              -79.405678              Tim Hortons       43.675800   \n",
       "110              -79.405678                   Subway       43.675650   \n",
       "111              -79.405678       Nick's Shoe Repair       43.675457   \n",
       "112              -79.405678        The Kitchen Table       43.675770   \n",
       "113              -79.405678  Davenport Garden Centre       43.675851   \n",
       "\n",
       "     Venue Longitude  Venue Category  \n",
       "109       -79.403532     Coffee Shop  \n",
       "110       -79.410255  Sandwich Place  \n",
       "111       -79.403675     Shoe Repair  \n",
       "112       -79.402746   Grocery Store  \n",
       "113       -79.401894     Flower Shop  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralT_venues.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's check how many venues were returned for each neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood 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>Davisville</th>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Davisville North</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Forest Hill Road Park, Forest Hill North &amp; West</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>Lawrence Park</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>Moore Park, Summerhill East</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>North Toronto West, Lawrence Park</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Roselawn</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>Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Annex, North Midtown, Yorkville</th>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    Neighborhood Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Davisville                                                             32   \n",
       "Davisville North                                                        9   \n",
       "Forest Hill Road Park, Forest Hill North & West                         4   \n",
       "Lawrence Park                                                           3   \n",
       "Moore Park, Summerhill East                                             4   \n",
       "North Toronto West, Lawrence Park                                      20   \n",
       "Roselawn                                                                3   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...                     16   \n",
       "The Annex, North Midtown, Yorkville                                    23   \n",
       "\n",
       "                                                    Neighborhood Longitude  \\\n",
       "Neighborhood                                                                 \n",
       "Davisville                                                              32   \n",
       "Davisville North                                                         9   \n",
       "Forest Hill Road Park, Forest Hill North & West                          4   \n",
       "Lawrence Park                                                            3   \n",
       "Moore Park, Summerhill East                                              4   \n",
       "North Toronto West, Lawrence Park                                       20   \n",
       "Roselawn                                                                 3   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...                      16   \n",
       "The Annex, North Midtown, Yorkville                                     23   \n",
       "\n",
       "                                                    Venue  Venue Latitude  \\\n",
       "Neighborhood                                                                \n",
       "Davisville                                             32              32   \n",
       "Davisville North                                        9               9   \n",
       "Forest Hill Road Park, Forest Hill North & West         4               4   \n",
       "Lawrence Park                                           3               3   \n",
       "Moore Park, Summerhill East                             4               4   \n",
       "North Toronto West, Lawrence Park                      20              20   \n",
       "Roselawn                                                3               3   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...     16              16   \n",
       "The Annex, North Midtown, Yorkville                    23              23   \n",
       "\n",
       "                                                    Venue Longitude  \\\n",
       "Neighborhood                                                          \n",
       "Davisville                                                       32   \n",
       "Davisville North                                                  9   \n",
       "Forest Hill Road Park, Forest Hill North & West                   4   \n",
       "Lawrence Park                                                     3   \n",
       "Moore Park, Summerhill East                                       4   \n",
       "North Toronto West, Lawrence Park                                20   \n",
       "Roselawn                                                          3   \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...               16   \n",
       "The Annex, North Midtown, Yorkville                              23   \n",
       "\n",
       "                                                    Venue Category  \n",
       "Neighborhood                                                        \n",
       "Davisville                                                      32  \n",
       "Davisville North                                                 9  \n",
       "Forest Hill Road Park, Forest Hill North & West                  4  \n",
       "Lawrence Park                                                    3  \n",
       "Moore Park, Summerhill East                                      4  \n",
       "North Toronto West, Lawrence Park                               20  \n",
       "Roselawn                                                         3  \n",
       "Summerhill West, Rathnelly, South Hill, Forest ...              16  \n",
       "The Annex, North Midtown, Yorkville                             23  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralT_venues.groupby('Neighborhood').count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's find out how many unique categories can be curated from all the returned venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 66 uniques categories.\n"
     ]
    }
   ],
   "source": [
    "print('There are {} uniques categories.'.format(len(centralT_venues['Venue Category'].unique())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Analyze Each Neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Bus Line</th>\n",
       "      <th>Café</th>\n",
       "      <th>...</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Swim School</th>\n",
       "      <th>Tennis Court</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Toy / Game Store</th>\n",
       "      <th>Trail</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Lawrence Park</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>...</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>Lawrence Park</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>...</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Lawrence Park</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>...</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>3</th>\n",
       "      <td>Davisville North</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>...</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>Davisville North</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>...</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",
       "<p>5 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Neighborhood  American Restaurant  BBQ Joint  Bagel Shop  Bank  \\\n",
       "0     Lawrence Park                    0          0           0     0   \n",
       "1     Lawrence Park                    0          0           0     0   \n",
       "2     Lawrence Park                    0          0           0     0   \n",
       "3  Davisville North                    0          0           0     0   \n",
       "4  Davisville North                    0          0           0     0   \n",
       "\n",
       "   Breakfast Spot  Brewery  Burger Joint  Bus Line  Café  ...  Supermarket  \\\n",
       "0               0        0             0         0     0  ...            0   \n",
       "1               0        0             0         0     0  ...            0   \n",
       "2               0        0             0         1     0  ...            0   \n",
       "3               1        0             0         0     0  ...            0   \n",
       "4               0        0             0         0     0  ...            0   \n",
       "\n",
       "   Sushi Restaurant  Swim School  Tennis Court  Thai Restaurant  \\\n",
       "0                 0            0             0                0   \n",
       "1                 0            1             0                0   \n",
       "2                 0            0             0                0   \n",
       "3                 0            0             0                0   \n",
       "4                 0            0             0                0   \n",
       "\n",
       "   Toy / Game Store  Trail  Vegetarian / Vegan Restaurant  \\\n",
       "0                 0      0                              0   \n",
       "1                 0      0                              0   \n",
       "2                 0      0                              0   \n",
       "3                 0      0                              0   \n",
       "4                 0      0                              0   \n",
       "\n",
       "   Vietnamese Restaurant  Yoga Studio  \n",
       "0                      0            0  \n",
       "1                      0            0  \n",
       "2                      0            0  \n",
       "3                      0            0  \n",
       "4                      0            0  \n",
       "\n",
       "[5 rows x 67 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# one hot encoding\n",
    "centralT_onehot = pd.get_dummies(centralT_venues[['Venue Category']], prefix=\"\", prefix_sep=\"\")\n",
    "\n",
    "# add neighborhood column back to dataframe\n",
    "centralT_onehot['Neighborhood'] = centralT_venues['Neighborhood'] \n",
    "\n",
    "# move neighborhood column to the first column\n",
    "fixed_columns = [centralT_onehot.columns[-1]] + list(centralT_onehot.columns[:-1])\n",
    "centralT_onehot = centralT_onehot[fixed_columns]\n",
    "\n",
    "centralT_onehot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(114, 67)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#And let's examine the new dataframe size.\n",
    "centralT_onehot.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>American Restaurant</th>\n",
       "      <th>BBQ Joint</th>\n",
       "      <th>Bagel Shop</th>\n",
       "      <th>Bank</th>\n",
       "      <th>Breakfast Spot</th>\n",
       "      <th>Brewery</th>\n",
       "      <th>Burger Joint</th>\n",
       "      <th>Bus Line</th>\n",
       "      <th>Café</th>\n",
       "      <th>...</th>\n",
       "      <th>Supermarket</th>\n",
       "      <th>Sushi Restaurant</th>\n",
       "      <th>Swim School</th>\n",
       "      <th>Tennis Court</th>\n",
       "      <th>Thai Restaurant</th>\n",
       "      <th>Toy / Game Store</th>\n",
       "      <th>Trail</th>\n",
       "      <th>Vegetarian / Vegan Restaurant</th>\n",
       "      <th>Vietnamese Restaurant</th>\n",
       "      <th>Yoga Studio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Davisville</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.03125</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.03125</td>\n",
       "      <td>0.03125</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Davisville North</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Forest Hill Road Park, Forest Hill North &amp; West</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.2500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.333333</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.25</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.050000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Roselawn</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Summerhill West, Rathnelly, South Hill, Forest...</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0625</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.043478</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.043478</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.130435</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.043478</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood  American Restaurant  \\\n",
       "0                                         Davisville               0.0000   \n",
       "1                                   Davisville North               0.0000   \n",
       "2    Forest Hill Road Park, Forest Hill North & West               0.0000   \n",
       "3                                      Lawrence Park               0.0000   \n",
       "4                        Moore Park, Summerhill East               0.0000   \n",
       "5                  North Toronto West, Lawrence Park               0.0000   \n",
       "6                                           Roselawn               0.0000   \n",
       "7  Summerhill West, Rathnelly, South Hill, Forest...               0.0625   \n",
       "8                The Annex, North Midtown, Yorkville               0.0000   \n",
       "\n",
       "   BBQ Joint  Bagel Shop    Bank  Breakfast Spot  Brewery  Burger Joint  \\\n",
       "0   0.000000      0.0000  0.0000        0.000000  0.03125      0.000000   \n",
       "1   0.000000      0.0000  0.0000        0.111111  0.00000      0.000000   \n",
       "2   0.000000      0.0000  0.0000        0.000000  0.00000      0.000000   \n",
       "3   0.000000      0.0000  0.0000        0.000000  0.00000      0.000000   \n",
       "4   0.000000      0.0000  0.0000        0.000000  0.00000      0.000000   \n",
       "5   0.000000      0.0500  0.0000        0.000000  0.00000      0.000000   \n",
       "6   0.000000      0.0000  0.0000        0.000000  0.00000      0.000000   \n",
       "7   0.000000      0.0625  0.0625        0.000000  0.00000      0.000000   \n",
       "8   0.043478      0.0000  0.0000        0.000000  0.00000      0.043478   \n",
       "\n",
       "   Bus Line      Café  ...  Supermarket  Sushi Restaurant  Swim School  \\\n",
       "0  0.000000  0.062500  ...       0.0000            0.0625     0.000000   \n",
       "1  0.000000  0.000000  ...       0.0000            0.0000     0.000000   \n",
       "2  0.000000  0.000000  ...       0.0000            0.2500     0.000000   \n",
       "3  0.333333  0.000000  ...       0.0000            0.0000     0.333333   \n",
       "4  0.000000  0.000000  ...       0.0000            0.0000     0.000000   \n",
       "5  0.000000  0.050000  ...       0.0000            0.0000     0.000000   \n",
       "6  0.000000  0.000000  ...       0.0000            0.0000     0.000000   \n",
       "7  0.000000  0.000000  ...       0.0625            0.0625     0.000000   \n",
       "8  0.000000  0.130435  ...       0.0000            0.0000     0.000000   \n",
       "\n",
       "   Tennis Court  Thai Restaurant  Toy / Game Store  Trail  \\\n",
       "0          0.00          0.03125           0.03125   0.00   \n",
       "1          0.00          0.00000           0.00000   0.00   \n",
       "2          0.00          0.00000           0.00000   0.25   \n",
       "3          0.00          0.00000           0.00000   0.00   \n",
       "4          0.25          0.00000           0.00000   0.00   \n",
       "5          0.00          0.00000           0.00000   0.00   \n",
       "6          0.00          0.00000           0.00000   0.00   \n",
       "7          0.00          0.00000           0.00000   0.00   \n",
       "8          0.00          0.00000           0.00000   0.00   \n",
       "\n",
       "   Vegetarian / Vegan Restaurant  Vietnamese Restaurant  Yoga Studio  \n",
       "0                       0.000000                 0.0000         0.00  \n",
       "1                       0.000000                 0.0000         0.00  \n",
       "2                       0.000000                 0.0000         0.00  \n",
       "3                       0.000000                 0.0000         0.00  \n",
       "4                       0.000000                 0.0000         0.00  \n",
       "5                       0.000000                 0.0000         0.05  \n",
       "6                       0.000000                 0.0000         0.00  \n",
       "7                       0.000000                 0.0625         0.00  \n",
       "8                       0.043478                 0.0000         0.00  \n",
       "\n",
       "[9 rows x 67 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralT_grouped = centralT_onehot.groupby('Neighborhood').mean().reset_index()\n",
    "centralT_grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(9, 67)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's confirm the new size\n",
    "centralT_grouped.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's print each neighborhood along with the top 5 most common venues"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----Davisville----\n",
      "                venue  freq\n",
      "0      Sandwich Place  0.09\n",
      "1        Dessert Shop  0.09\n",
      "2         Pizza Place  0.06\n",
      "3                Café  0.06\n",
      "4  Italian Restaurant  0.06\n",
      "\n",
      "\n",
      "----Davisville North----\n",
      "               venue  freq\n",
      "0        Pizza Place  0.11\n",
      "1              Hotel  0.11\n",
      "2   Department Store  0.11\n",
      "3       Dance Studio  0.11\n",
      "4  Food & Drink Shop  0.11\n",
      "\n",
      "\n",
      "----Forest Hill Road Park, Forest Hill North & West----\n",
      "                 venue  freq\n",
      "0                 Park  0.25\n",
      "1        Jewelry Store  0.25\n",
      "2                Trail  0.25\n",
      "3     Sushi Restaurant  0.25\n",
      "4  American Restaurant  0.00\n",
      "\n",
      "\n",
      "----Lawrence Park----\n",
      "                 venue  freq\n",
      "0                 Park  0.33\n",
      "1          Swim School  0.33\n",
      "2             Bus Line  0.33\n",
      "3  Rental Car Location  0.00\n",
      "4                  Pub  0.00\n",
      "\n",
      "\n",
      "----Moore Park, Summerhill East----\n",
      "                 venue  freq\n",
      "0           Restaurant  0.25\n",
      "1                 Park  0.25\n",
      "2           Playground  0.25\n",
      "3         Tennis Court  0.25\n",
      "4  Rental Car Location  0.00\n",
      "\n",
      "\n",
      "----North Toronto West, Lawrence Park----\n",
      "            venue  freq\n",
      "0  Clothing Store  0.10\n",
      "1     Coffee Shop  0.10\n",
      "2     Yoga Studio  0.05\n",
      "3           Diner  0.05\n",
      "4            Park  0.05\n",
      "\n",
      "\n",
      "----Roselawn----\n",
      "                 venue  freq\n",
      "0       Ice Cream Shop  0.33\n",
      "1                 Pool  0.33\n",
      "2               Garden  0.33\n",
      "3  American Restaurant  0.00\n",
      "4             Pharmacy  0.00\n",
      "\n",
      "\n",
      "----Summerhill West, Rathnelly, South Hill, Forest Hill SE, Deer Park----\n",
      "                 venue  freq\n",
      "0          Coffee Shop  0.12\n",
      "1                  Pub  0.12\n",
      "2  American Restaurant  0.06\n",
      "3         Liquor Store  0.06\n",
      "4          Pizza Place  0.06\n",
      "\n",
      "\n",
      "----The Annex, North Midtown, Yorkville----\n",
      "            venue  freq\n",
      "0            Café  0.13\n",
      "1  Sandwich Place  0.13\n",
      "2     Coffee Shop  0.09\n",
      "3     Flower Shop  0.04\n",
      "4      Donut Shop  0.04\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "num_top_venues = 5\n",
    "\n",
    "for hood in centralT_grouped['Neighborhood']:\n",
    "    print(\"----\"+hood+\"----\")\n",
    "    temp = centralT_grouped[centralT_grouped['Neighborhood'] == hood].T.reset_index()\n",
    "    temp.columns = ['venue','freq']\n",
    "    temp = temp.iloc[1:]\n",
    "    temp['freq'] = temp['freq'].astype(float)\n",
    "    temp = temp.round({'freq': 2})\n",
    "    print(temp.sort_values('freq', ascending=False).reset_index(drop=True).head(num_top_venues))\n",
    "    print('\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Let's put that into a *pandas* dataframe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let's write a function to sort the venues in descending order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "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": "markdown",
   "metadata": {},
   "source": [
    "Now let's create the new dataframe and display the top 10 venues for each neighborhood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>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>Davisville</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Davisville North</td>\n",
       "      <td>Park</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Forest Hill Road Park, Forest Hill North &amp; West</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Jewelry Store</td>\n",
       "      <td>Park</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Park</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Tennis Court</td>\n",
       "      <td>Park</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Garden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Metro Station</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Rental Car Location</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Roselawn</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Pool</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Summerhill West, Rathnelly, South Hill, Forest...</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Sports Bar</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>The Annex, North Midtown, Yorkville</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Shoe Repair</td>\n",
       "      <td>History Museum</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Neighborhood 1st Most Common Venue  \\\n",
       "0                                         Davisville        Sandwich Place   \n",
       "1                                   Davisville North                  Park   \n",
       "2    Forest Hill Road Park, Forest Hill North & West                 Trail   \n",
       "3                                      Lawrence Park              Bus Line   \n",
       "4                        Moore Park, Summerhill East            Restaurant   \n",
       "5                  North Toronto West, Lawrence Park        Clothing Store   \n",
       "6                                           Roselawn        Ice Cream Shop   \n",
       "7  Summerhill West, Rathnelly, South Hill, Forest...                   Pub   \n",
       "8                The Annex, North Midtown, Yorkville                  Café   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0          Dessert Shop                   Gym    Italian Restaurant   \n",
       "1  Gym / Fitness Center                 Hotel           Pizza Place   \n",
       "2         Jewelry Store                  Park      Sushi Restaurant   \n",
       "3                  Park           Swim School           Gas Station   \n",
       "4            Playground          Tennis Court                  Park   \n",
       "5           Coffee Shop           Yoga Studio        Ice Cream Shop   \n",
       "6                Garden                  Pool        Farmers Market   \n",
       "7           Coffee Shop   American Restaurant           Supermarket   \n",
       "8        Sandwich Place           Coffee Shop     Indian Restaurant   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0           Pizza Place                  Café      Sushi Restaurant   \n",
       "1        Breakfast Spot        Sandwich Place      Department Store   \n",
       "2           Yoga Studio                Garden  Fast Food Restaurant   \n",
       "3  Fast Food Restaurant           Flower Shop     Food & Drink Shop   \n",
       "4   Fried Chicken Joint        Farmers Market  Fast Food Restaurant   \n",
       "5         Metro Station    Mexican Restaurant  Fast Food Restaurant   \n",
       "6  Fast Food Restaurant           Flower Shop     Food & Drink Shop   \n",
       "7            Restaurant          Liquor Store    Light Rail Station   \n",
       "8           Shoe Repair        History Museum           Flower Shop   \n",
       "\n",
       "  8th Most Common Venue      9th Most Common Venue 10th Most Common Venue  \n",
       "0           Coffee Shop             Farmers Market             Restaurant  \n",
       "1          Dance Studio          Food & Drink Shop            Yoga Studio  \n",
       "2           Flower Shop          Food & Drink Shop    Fried Chicken Joint  \n",
       "3   Fried Chicken Joint                     Garden            Yoga Studio  \n",
       "4           Flower Shop          Food & Drink Shop                 Garden  \n",
       "5                  Park                      Diner    Rental Car Location  \n",
       "6   Fried Chicken Joint                Yoga Studio             Donut Shop  \n",
       "7   Fried Chicken Joint                 Sports Bar            Pizza Place  \n",
       "8          Liquor Store  Middle Eastern Restaurant                   Park  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_top_venues = 10\n",
    "\n",
    "indicators = ['st', 'nd', 'rd']\n",
    "\n",
    "# create columns according to number of top venues\n",
    "columns = ['Neighborhood']\n",
    "for 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\n",
    "neighborhoods_venues_sorted = pd.DataFrame(columns=columns)\n",
    "neighborhoods_venues_sorted['Neighborhood'] = centralT_grouped['Neighborhood']\n",
    "\n",
    "for ind in np.arange(centralT_grouped.shape[0]):\n",
    "    neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(centralT_grouped.iloc[ind, :], num_top_venues)\n",
    "\n",
    "neighborhoods_venues_sorted"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Cluster Neighborhoods\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run *k*-means to cluster the neighborhood into 3 clusters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 2, 0, 0, 1, 0, 0], dtype=int32)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set number of clusters\n",
    "kclusters = 3\n",
    "\n",
    "centralT_grouped_clustering = centralT_grouped.drop('Neighborhood', 1)\n",
    "\n",
    "# run k-means clustering\n",
    "kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(centralT_grouped_clustering)\n",
    "\n",
    "# check cluster labels generated for each row in the dataframe\n",
    "kmeans.labels_[0:10] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's create a new dataframe that includes the cluster as well as the top 10 venues for each neighborhood."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighborhood</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>44</td>\n",
       "      <td>M4N</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Lawrence Park</td>\n",
       "      <td>43.728020</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>2</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Park</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45</td>\n",
       "      <td>M4P</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville North</td>\n",
       "      <td>43.712751</td>\n",
       "      <td>-79.390197</td>\n",
       "      <td>0</td>\n",
       "      <td>Park</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>46</td>\n",
       "      <td>M4R</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>North Toronto West, Lawrence Park</td>\n",
       "      <td>43.715383</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>0</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Metro Station</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Rental Car Location</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>47</td>\n",
       "      <td>M4S</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Davisville</td>\n",
       "      <td>43.704324</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>0</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48</td>\n",
       "      <td>M4T</td>\n",
       "      <td>Central Toronto</td>\n",
       "      <td>Moore Park, Summerhill East</td>\n",
       "      <td>43.689574</td>\n",
       "      <td>-79.383160</td>\n",
       "      <td>0</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Tennis Court</td>\n",
       "      <td>Park</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Garden</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 Postal Code          Borough                       Neighborhood  \\\n",
       "0          44         M4N  Central Toronto                      Lawrence Park   \n",
       "1          45         M4P  Central Toronto                   Davisville North   \n",
       "2          46         M4R  Central Toronto  North Toronto West, Lawrence Park   \n",
       "3          47         M4S  Central Toronto                         Davisville   \n",
       "4          48         M4T  Central Toronto        Moore Park, Summerhill East   \n",
       "\n",
       "    Latitude  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "0  43.728020 -79.388790               2              Bus Line   \n",
       "1  43.712751 -79.390197               0                  Park   \n",
       "2  43.715383 -79.405678               0        Clothing Store   \n",
       "3  43.704324 -79.388790               0        Sandwich Place   \n",
       "4  43.689574 -79.383160               0            Restaurant   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0                  Park           Swim School           Gas Station   \n",
       "1  Gym / Fitness Center                 Hotel           Pizza Place   \n",
       "2           Coffee Shop           Yoga Studio        Ice Cream Shop   \n",
       "3          Dessert Shop                   Gym    Italian Restaurant   \n",
       "4            Playground          Tennis Court                  Park   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0  Fast Food Restaurant           Flower Shop     Food & Drink Shop   \n",
       "1        Breakfast Spot        Sandwich Place      Department Store   \n",
       "2         Metro Station    Mexican Restaurant  Fast Food Restaurant   \n",
       "3           Pizza Place                  Café      Sushi Restaurant   \n",
       "4   Fried Chicken Joint        Farmers Market  Fast Food Restaurant   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0   Fried Chicken Joint                Garden            Yoga Studio  \n",
       "1          Dance Studio     Food & Drink Shop            Yoga Studio  \n",
       "2                  Park                 Diner    Rental Car Location  \n",
       "3           Coffee Shop        Farmers Market             Restaurant  \n",
       "4           Flower Shop     Food & Drink Shop                 Garden  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# add clustering labels\n",
    "neighborhoods_venues_sorted.insert(0, 'Cluster Labels', kmeans.labels_)\n",
    "\n",
    "centralT_merged = centralT_data\n",
    "\n",
    "# merge toronto_grouped with toronto_data to add latitude/longitude for each neighborhood\n",
    "centralT_merged = centralT_merged.join(neighborhoods_venues_sorted.set_index('Neighborhood'), on='Neighborhood')\n",
    "\n",
    "centralT_merged.head() # check the last columns!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, let's visualize the cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
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   "source": [
    "# create map\n",
    "map_clusters = folium.Map(location=[latitude, longitude], zoom_start=11)\n",
    "\n",
    "# set color scheme for the clusters\n",
    "x = np.arange(kclusters)\n",
    "ys = [i + x + (i*x)**2 for i in range(kclusters)]\n",
    "colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))\n",
    "rainbow = [colors.rgb2hex(i) for i in colors_array]\n",
    "\n",
    "# add markers to the map\n",
    "markers_colors = []\n",
    "for lat, lon, poi, cluster in zip(centralT_merged['Latitude'], centralT_merged['Longitude'], centralT_merged['Neighborhood'], centralT_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",
    "       \n",
    "map_clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Examine Clusters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cluster 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
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       "      <td>Park</td>\n",
       "      <td>Gym / Fitness Center</td>\n",
       "      <td>Hotel</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Breakfast Spot</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Department Store</td>\n",
       "      <td>Dance Studio</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M4R</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>0</td>\n",
       "      <td>Clothing Store</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Metro Station</td>\n",
       "      <td>Mexican Restaurant</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Park</td>\n",
       "      <td>Diner</td>\n",
       "      <td>Rental Car Location</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M4S</td>\n",
       "      <td>-79.388790</td>\n",
       "      <td>0</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Dessert Shop</td>\n",
       "      <td>Gym</td>\n",
       "      <td>Italian Restaurant</td>\n",
       "      <td>Pizza Place</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Restaurant</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M4T</td>\n",
       "      <td>-79.383160</td>\n",
       "      <td>0</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Playground</td>\n",
       "      <td>Tennis Court</td>\n",
       "      <td>Park</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Garden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M4V</td>\n",
       "      <td>-79.400049</td>\n",
       "      <td>0</td>\n",
       "      <td>Pub</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>American Restaurant</td>\n",
       "      <td>Supermarket</td>\n",
       "      <td>Restaurant</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Light Rail Station</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Sports Bar</td>\n",
       "      <td>Pizza Place</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M5P</td>\n",
       "      <td>-79.411307</td>\n",
       "      <td>0</td>\n",
       "      <td>Trail</td>\n",
       "      <td>Jewelry Store</td>\n",
       "      <td>Park</td>\n",
       "      <td>Sushi Restaurant</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M5R</td>\n",
       "      <td>-79.405678</td>\n",
       "      <td>0</td>\n",
       "      <td>Café</td>\n",
       "      <td>Sandwich Place</td>\n",
       "      <td>Coffee Shop</td>\n",
       "      <td>Indian Restaurant</td>\n",
       "      <td>Shoe Repair</td>\n",
       "      <td>History Museum</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Liquor Store</td>\n",
       "      <td>Middle Eastern Restaurant</td>\n",
       "      <td>Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "1         M4P -79.390197               0                  Park   \n",
       "2         M4R -79.405678               0        Clothing Store   \n",
       "3         M4S -79.388790               0        Sandwich Place   \n",
       "4         M4T -79.383160               0            Restaurant   \n",
       "5         M4V -79.400049               0                   Pub   \n",
       "7         M5P -79.411307               0                 Trail   \n",
       "8         M5R -79.405678               0                  Café   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "1  Gym / Fitness Center                 Hotel           Pizza Place   \n",
       "2           Coffee Shop           Yoga Studio        Ice Cream Shop   \n",
       "3          Dessert Shop                   Gym    Italian Restaurant   \n",
       "4            Playground          Tennis Court                  Park   \n",
       "5           Coffee Shop   American Restaurant           Supermarket   \n",
       "7         Jewelry Store                  Park      Sushi Restaurant   \n",
       "8        Sandwich Place           Coffee Shop     Indian Restaurant   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "1        Breakfast Spot        Sandwich Place      Department Store   \n",
       "2         Metro Station    Mexican Restaurant  Fast Food Restaurant   \n",
       "3           Pizza Place                  Café      Sushi Restaurant   \n",
       "4   Fried Chicken Joint        Farmers Market  Fast Food Restaurant   \n",
       "5            Restaurant          Liquor Store    Light Rail Station   \n",
       "7           Yoga Studio                Garden  Fast Food Restaurant   \n",
       "8           Shoe Repair        History Museum           Flower Shop   \n",
       "\n",
       "  8th Most Common Venue      9th Most Common Venue 10th Most Common Venue  \n",
       "1          Dance Studio          Food & Drink Shop            Yoga Studio  \n",
       "2                  Park                      Diner    Rental Car Location  \n",
       "3           Coffee Shop             Farmers Market             Restaurant  \n",
       "4           Flower Shop          Food & Drink Shop                 Garden  \n",
       "5   Fried Chicken Joint                 Sports Bar            Pizza Place  \n",
       "7           Flower Shop          Food & Drink Shop    Fried Chicken Joint  \n",
       "8          Liquor Store  Middle Eastern Restaurant                   Park  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralT_merged.loc[centralT_merged['Cluster Labels'] == 0, centralT_merged.columns[[1] + list(range(5, centralT_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cluster 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</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>6</th>\n",
       "      <td>M5N</td>\n",
       "      <td>-79.416936</td>\n",
       "      <td>1</td>\n",
       "      <td>Ice Cream Shop</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Pool</td>\n",
       "      <td>Farmers Market</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Yoga Studio</td>\n",
       "      <td>Donut Shop</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "6         M5N -79.416936               1        Ice Cream Shop   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "6                Garden                  Pool        Farmers Market   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "6  Fast Food Restaurant           Flower Shop     Food & Drink Shop   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "6   Fried Chicken Joint           Yoga Studio             Donut Shop  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralT_merged.loc[centralT_merged['Cluster Labels'] == 1, centralT_merged.columns[[1] + list(range(5, centralT_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cluster 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</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>M4N</td>\n",
       "      <td>-79.38879</td>\n",
       "      <td>2</td>\n",
       "      <td>Bus Line</td>\n",
       "      <td>Park</td>\n",
       "      <td>Swim School</td>\n",
       "      <td>Gas Station</td>\n",
       "      <td>Fast Food Restaurant</td>\n",
       "      <td>Flower Shop</td>\n",
       "      <td>Food &amp; Drink Shop</td>\n",
       "      <td>Fried Chicken Joint</td>\n",
       "      <td>Garden</td>\n",
       "      <td>Yoga Studio</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code  Longitude  Cluster Labels 1st Most Common Venue  \\\n",
       "0         M4N  -79.38879               2              Bus Line   \n",
       "\n",
       "  2nd Most Common Venue 3rd Most Common Venue 4th Most Common Venue  \\\n",
       "0                  Park           Swim School           Gas Station   \n",
       "\n",
       "  5th Most Common Venue 6th Most Common Venue 7th Most Common Venue  \\\n",
       "0  Fast Food Restaurant           Flower Shop     Food & Drink Shop   \n",
       "\n",
       "  8th Most Common Venue 9th Most Common Venue 10th Most Common Venue  \n",
       "0   Fried Chicken Joint                Garden            Yoga Studio  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "centralT_merged.loc[centralT_merged['Cluster Labels'] == 2, centralT_merged.columns[[1] + list(range(5, centralT_merged.shape[1]))]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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