week-3-project-geo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Obtain data from Wiki Page"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting wikipedia\n",
      "  Downloading https://files.pythonhosted.org/packages/67/35/25e68fbc99e672127cc6fbb14b8ec1ba3dfef035bf1e4c90f78f24a80b7d/wikipedia-1.4.0.tar.gz\n",
      "Requirement already satisfied: beautifulsoup4 in /home/jupyterlab/conda/lib/python3.6/site-packages (from wikipedia) (4.6.3)\n",
      "Requirement already satisfied: requests<3.0.0,>=2.0.0 in /home/jupyterlab/conda/lib/python3.6/site-packages (from wikipedia) (2.20.1)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/jupyterlab/conda/lib/python3.6/site-packages (from requests<3.0.0,>=2.0.0->wikipedia) (2018.11.29)\n",
      "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /home/jupyterlab/conda/lib/python3.6/site-packages (from requests<3.0.0,>=2.0.0->wikipedia) (3.0.4)\n",
      "Requirement already satisfied: urllib3<1.25,>=1.21.1 in /home/jupyterlab/conda/lib/python3.6/site-packages (from requests<3.0.0,>=2.0.0->wikipedia) (1.23)\n",
      "Requirement already satisfied: idna<2.8,>=2.5 in /home/jupyterlab/conda/lib/python3.6/site-packages (from requests<3.0.0,>=2.0.0->wikipedia) (2.7)\n",
      "Building wheels for collected packages: wikipedia\n",
      "  Running setup.py bdist_wheel for wikipedia ... \u001b[?25ldone\n",
      "\u001b[?25h  Stored in directory: /home/jupyterlab/.cache/pip/wheels/87/2a/18/4e471fd96d12114d16fe4a446d00c3b38fb9efcb744bd31f4a\n",
      "Successfully built wikipedia\n",
      "Installing collected packages: wikipedia\n",
      "Successfully installed wikipedia-1.4.0\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import wikipedia as wp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>M7A</td>\n",
       "      <td>Queen's Park</td>\n",
       "      <td>Queen's Park</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Postcode       Borough Neighbourhood\n",
       "85      M7A  Queen's Park  Queen's Park"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the table from wiki page\n",
    "html = wp.page(\"List of postal codes of Canada: M\").html().encode(\"UTF-8\")\n",
    "df = pd.read_html(html, header = 0)[0]\n",
    "\n",
    "# Drope the rows with Borough of \"Not assigned\"\n",
    "df_assigned = df[df.Borough != 'Not assigned']\n",
    "df_assigned.reset_index(drop = True, inplace = True)\n",
    "\n",
    "# Merge rows with the same Postcode\n",
    "df_assigned = df_assigned.groupby(['Postcode', 'Borough'], as_index=False).agg(lambda x: ', '.join(set(x)))\n",
    "\n",
    "# Set 'Not assigned' Neigbourhood to be equal to Borough\n",
    "na_nb_idx =df_assigned['Neighbourhood'] == 'Not assigned'\n",
    "df_assigned.loc[na_nb_idx, 'Neighbourhood'] = df_assigned[na_nb_idx].Borough\n",
    "df_assigned[df_assigned['Postcode'] == 'M7A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(103, 3)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Show the shape of the df\n",
    "df_assigned.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add latitude and longitude of each neighborhood"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2019-01-03 07:45:45--  http://cocl.us/Geospatial_data/\n",
      "Resolving cocl.us (cocl.us)... 169.48.113.201\n",
      "Connecting to cocl.us (cocl.us)|169.48.113.201|:80... connected.\n",
      "HTTP request sent, awaiting response... 301 Moved Permanently\n",
      "Location: https://cocl.us/Geospatial_data/ [following]\n",
      "--2019-01-03 07:45:45--  https://cocl.us/Geospatial_data/\n",
      "Connecting to cocl.us (cocl.us)|169.48.113.201|:443... connected.\n",
      "HTTP request sent, awaiting response... 301 Moved Permanently\n",
      "Location: https://ibm.box.com/shared/static/9afzr83pps4pwf2smjjcf1y5mvgb18rr.csv [following]\n",
      "--2019-01-03 07:45:46--  https://ibm.box.com/shared/static/9afzr83pps4pwf2smjjcf1y5mvgb18rr.csv\n",
      "Resolving ibm.box.com (ibm.box.com)... 107.152.25.197, 107.152.24.197\n",
      "Connecting to ibm.box.com (ibm.box.com)|107.152.25.197|:443... connected.\n",
      "HTTP request sent, awaiting response... 301 Moved Permanently\n",
      "Location: https://ibm.ent.box.com/shared/static/9afzr83pps4pwf2smjjcf1y5mvgb18rr.csv [following]\n",
      "--2019-01-03 07:45:47--  https://ibm.ent.box.com/shared/static/9afzr83pps4pwf2smjjcf1y5mvgb18rr.csv\n",
      "Resolving ibm.ent.box.com (ibm.ent.box.com)... 107.152.26.211\n",
      "Connecting to ibm.ent.box.com (ibm.ent.box.com)|107.152.26.211|:443... connected.\n",
      "HTTP request sent, awaiting response... 302 Found\n",
      "Location: https://public.boxcloud.com/d/1/b1!qua8zNTevdJv4NFFL5uSeqP-HdzwjtInjREA-As-1J0_I3eoSts1ya4Oz-347uwkudgnioX9BfXzRmWYTMF_7pvH2JXwwshp1T3kaWOfcBwhdHNXLpnfuVdOgqS4HmaWNsiKze8UuFp90Tt9nKcbxckoL2WLfv-9PJ5d4KHmHoCeehvRzRRas7jod_EvGeWhUGU_hdI2Gn0ZHAg3GheUI_536dijMkUUaqHoVjuX_VGqHHjEDug-03-qY0BvGloY5Y6B3vu6RvKf93JS2pUngJwVcez2AnQL0147DPEWqiWkZjr3DEaBG_tY7lKmC9ZSZyVb45DgZPiRHVj4nTfdCB1C7EXq5-Q6yU2MCFTVJsKPQHP_cTEsE7IP_5V1sf1iEX-FZVknJwduxke0UciZDd3omzbGPAA1yGxQGgkZ66oJYhdihXrb0JVaXvd45OGdXlZFOX1aNOmVob5DxEf4tmPkUYEd0_sPDo4LnnPHXfjMWVtlvxzTWLl4nSWKAzOuGRvWu6cCIj99x37fNxU-BEeB8VKP-_qg7o2lb1B_X_IRmrBqlfyJaCX-GTFN2ZokgKPCtgsCB5_VY_TlUotjzNLiTPb8Eh3a7BTsVgGQCzUnPnRISQqU2kvk1xN0VfuiBCGAhWUR3lV7ExbBHR4kYN00hBaMYBIKtWoKZxQ4SFBPVzuGEstOKPeiLb9LKTHn52XmaTK0QWBfJuPNpOfcFu58n2KQc_1-mWtfNrHg_u--adok8d_DiNtR70i9fRucdbCKXyMxIQkk3d8vUtD4aO4A5oGuKFoQhf-KUxY4QUk7UyGYPLVLQxsa09es7-M3-O_QC_AeAD9-5p3xEJcZGkMlBblYLBXWxMVgS8YxbiRTmxmhUJOt5rCd3mFpdnnAFTYa5pBxuQynbdNPktjA3uV_0VQoDadvG5A5V6csfmPKl3jqckFkrM7MNQnCgvNl5CIJZoywJg_59i_i9LJFMytuG7sOvznQMkNMmSVnIHNJ-PfohIx2IfHYU6vFrD4rbHz-2112juQ_HvXMYqkYn-EMSU-c6SgWtyXqCheU81CDpEbldu4kkw-bg39of_39e1N8EMkSVYCeHYfEhNPpZnbdiBTf90acxp-nLef5TPnOYy9VPtUyFFHr8NQMLAEjSwWWMXCfGPZh-dR5pxAQKYCWNuczuv1usm0ntdqpSs57LvyuxXahAguymMyIoWHU__96GZaEWuVfFrpkz__tetFAQZtotgeGlAE7OAOgGMYRHpc12gud5AK_iaV4If_CpD4ymrGZGv_EvcTcNeiyj9GPLkh54cKc5AH3uHcjR0mttbpVDWhqb_C4cciwKv1YczqGwAKsNOLZTzj1hs-hws7m5pY1TVuIW8WXWL-2nYS4FM9U/download [following]\n",
      "--2019-01-03 07:45:47--  https://public.boxcloud.com/d/1/b1!qua8zNTevdJv4NFFL5uSeqP-HdzwjtInjREA-As-1J0_I3eoSts1ya4Oz-347uwkudgnioX9BfXzRmWYTMF_7pvH2JXwwshp1T3kaWOfcBwhdHNXLpnfuVdOgqS4HmaWNsiKze8UuFp90Tt9nKcbxckoL2WLfv-9PJ5d4KHmHoCeehvRzRRas7jod_EvGeWhUGU_hdI2Gn0ZHAg3GheUI_536dijMkUUaqHoVjuX_VGqHHjEDug-03-qY0BvGloY5Y6B3vu6RvKf93JS2pUngJwVcez2AnQL0147DPEWqiWkZjr3DEaBG_tY7lKmC9ZSZyVb45DgZPiRHVj4nTfdCB1C7EXq5-Q6yU2MCFTVJsKPQHP_cTEsE7IP_5V1sf1iEX-FZVknJwduxke0UciZDd3omzbGPAA1yGxQGgkZ66oJYhdihXrb0JVaXvd45OGdXlZFOX1aNOmVob5DxEf4tmPkUYEd0_sPDo4LnnPHXfjMWVtlvxzTWLl4nSWKAzOuGRvWu6cCIj99x37fNxU-BEeB8VKP-_qg7o2lb1B_X_IRmrBqlfyJaCX-GTFN2ZokgKPCtgsCB5_VY_TlUotjzNLiTPb8Eh3a7BTsVgGQCzUnPnRISQqU2kvk1xN0VfuiBCGAhWUR3lV7ExbBHR4kYN00hBaMYBIKtWoKZxQ4SFBPVzuGEstOKPeiLb9LKTHn52XmaTK0QWBfJuPNpOfcFu58n2KQc_1-mWtfNrHg_u--adok8d_DiNtR70i9fRucdbCKXyMxIQkk3d8vUtD4aO4A5oGuKFoQhf-KUxY4QUk7UyGYPLVLQxsa09es7-M3-O_QC_AeAD9-5p3xEJcZGkMlBblYLBXWxMVgS8YxbiRTmxmhUJOt5rCd3mFpdnnAFTYa5pBxuQynbdNPktjA3uV_0VQoDadvG5A5V6csfmPKl3jqckFkrM7MNQnCgvNl5CIJZoywJg_59i_i9LJFMytuG7sOvznQMkNMmSVnIHNJ-PfohIx2IfHYU6vFrD4rbHz-2112juQ_HvXMYqkYn-EMSU-c6SgWtyXqCheU81CDpEbldu4kkw-bg39of_39e1N8EMkSVYCeHYfEhNPpZnbdiBTf90acxp-nLef5TPnOYy9VPtUyFFHr8NQMLAEjSwWWMXCfGPZh-dR5pxAQKYCWNuczuv1usm0ntdqpSs57LvyuxXahAguymMyIoWHU__96GZaEWuVfFrpkz__tetFAQZtotgeGlAE7OAOgGMYRHpc12gud5AK_iaV4If_CpD4ymrGZGv_EvcTcNeiyj9GPLkh54cKc5AH3uHcjR0mttbpVDWhqb_C4cciwKv1YczqGwAKsNOLZTzj1hs-hws7m5pY1TVuIW8WXWL-2nYS4FM9U/download\n",
      "Resolving public.boxcloud.com (public.boxcloud.com)... 107.152.24.200, 107.152.25.200\n",
      "Connecting to public.boxcloud.com (public.boxcloud.com)|107.152.24.200|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 2891 (2.8K) [text/csv]\n",
      "Saving to: ‘GeoCord.csv’\n",
      "\n",
      "GeoCord.csv         100%[=====================>]   2.82K  --.-KB/s   in 0s     \n",
      "\n",
      "2019-01-03 07:45:48 (49.5 MB/s) - ‘GeoCord.csv’ saved [2891/2891]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Since it is not able to obtain coordinates from using geocoder.google, the given csv file is used\n",
    "!wget -O GeoCord.csv http://cocl.us/Geospatial_data/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postal Code</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>M1B</td>\n",
       "      <td>43.806686</td>\n",
       "      <td>-79.194353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>M1C</td>\n",
       "      <td>43.784535</td>\n",
       "      <td>-79.160497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M1E</td>\n",
       "      <td>43.763573</td>\n",
       "      <td>-79.188711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>M1G</td>\n",
       "      <td>43.770992</td>\n",
       "      <td>-79.216917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M1H</td>\n",
       "      <td>43.773136</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Postal Code   Latitude  Longitude\n",
       "0         M1B  43.806686 -79.194353\n",
       "1         M1C  43.784535 -79.160497\n",
       "2         M1E  43.763573 -79.188711\n",
       "3         M1G  43.770992 -79.216917\n",
       "4         M1H  43.773136 -79.239476"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cord = pd.read_csv('GeoCord.csv') # Read the csv data\n",
    "df_cord.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Borough</th>\n",
       "      <th>Neighbourhood</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\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>M1C</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Highland Creek, Rouge Hill, Port Union</td>\n",
       "      <td>43.784535</td>\n",
       "      <td>-79.160497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>M1E</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Morningside, Guildwood, West Hill</td>\n",
       "      <td>43.763573</td>\n",
       "      <td>-79.188711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\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>M1H</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cedarbrae</td>\n",
       "      <td>43.773136</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>M1J</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Scarborough Village</td>\n",
       "      <td>43.744734</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>M1K</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Ionview, Kennedy Park, East Birchmount Park</td>\n",
       "      <td>43.727929</td>\n",
       "      <td>-79.262029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>M1L</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Golden Mile, Clairlea, Oakridge</td>\n",
       "      <td>43.711112</td>\n",
       "      <td>-79.284577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>M1M</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cliffside, Scarborough Village West, Cliffcrest</td>\n",
       "      <td>43.716316</td>\n",
       "      <td>-79.239476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>M1N</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Cliffside West, Birch Cliff</td>\n",
       "      <td>43.692657</td>\n",
       "      <td>-79.264848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>M1P</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Scarborough Town Centre, Wexford Heights, Dors...</td>\n",
       "      <td>43.757410</td>\n",
       "      <td>-79.273304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>M1R</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Wexford, Maryvale</td>\n",
       "      <td>43.750072</td>\n",
       "      <td>-79.295849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>M1S</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Agincourt</td>\n",
       "      <td>43.794200</td>\n",
       "      <td>-79.262029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>M1T</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Sullivan, Clarks Corners, Tam O'Shanter</td>\n",
       "      <td>43.781638</td>\n",
       "      <td>-79.304302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>M1V</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Agincourt North, Steeles East, L'Amoreaux East...</td>\n",
       "      <td>43.815252</td>\n",
       "      <td>-79.284577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>M1W</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>L'Amoreaux West, Steeles West</td>\n",
       "      <td>43.799525</td>\n",
       "      <td>-79.318389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>M1X</td>\n",
       "      <td>Scarborough</td>\n",
       "      <td>Upper Rouge</td>\n",
       "      <td>43.836125</td>\n",
       "      <td>-79.205636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>M2H</td>\n",
       "      <td>North York</td>\n",
       "      <td>Hillcrest Village</td>\n",
       "      <td>43.803762</td>\n",
       "      <td>-79.363452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>M2J</td>\n",
       "      <td>North York</td>\n",
       "      <td>Fairview, Oriole, Henry Farm</td>\n",
       "      <td>43.778517</td>\n",
       "      <td>-79.346556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>M2K</td>\n",
       "      <td>North York</td>\n",
       "      <td>Bayview Village</td>\n",
       "      <td>43.786947</td>\n",
       "      <td>-79.385975</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Postcode      Borough                                      Neighbourhood  \\\n",
       "0       M1B  Scarborough                                     Malvern, Rouge   \n",
       "1       M1C  Scarborough             Highland Creek, Rouge Hill, Port Union   \n",
       "2       M1E  Scarborough                  Morningside, Guildwood, West Hill   \n",
       "3       M1G  Scarborough                                             Woburn   \n",
       "4       M1H  Scarborough                                          Cedarbrae   \n",
       "5       M1J  Scarborough                                Scarborough Village   \n",
       "6       M1K  Scarborough        Ionview, Kennedy Park, East Birchmount Park   \n",
       "7       M1L  Scarborough                    Golden Mile, Clairlea, Oakridge   \n",
       "8       M1M  Scarborough    Cliffside, Scarborough Village West, Cliffcrest   \n",
       "9       M1N  Scarborough                        Cliffside West, Birch Cliff   \n",
       "10      M1P  Scarborough  Scarborough Town Centre, Wexford Heights, Dors...   \n",
       "11      M1R  Scarborough                                  Wexford, Maryvale   \n",
       "12      M1S  Scarborough                                          Agincourt   \n",
       "13      M1T  Scarborough            Sullivan, Clarks Corners, Tam O'Shanter   \n",
       "14      M1V  Scarborough  Agincourt North, Steeles East, L'Amoreaux East...   \n",
       "15      M1W  Scarborough                      L'Amoreaux West, Steeles West   \n",
       "16      M1X  Scarborough                                        Upper Rouge   \n",
       "17      M2H   North York                                  Hillcrest Village   \n",
       "18      M2J   North York                       Fairview, Oriole, Henry Farm   \n",
       "19      M2K   North York                                    Bayview Village   \n",
       "\n",
       "     Latitude  Longitude  \n",
       "0   43.806686 -79.194353  \n",
       "1   43.784535 -79.160497  \n",
       "2   43.763573 -79.188711  \n",
       "3   43.770992 -79.216917  \n",
       "4   43.773136 -79.239476  \n",
       "5   43.744734 -79.239476  \n",
       "6   43.727929 -79.262029  \n",
       "7   43.711112 -79.284577  \n",
       "8   43.716316 -79.239476  \n",
       "9   43.692657 -79.264848  \n",
       "10  43.757410 -79.273304  \n",
       "11  43.750072 -79.295849  \n",
       "12  43.794200 -79.262029  \n",
       "13  43.781638 -79.304302  \n",
       "14  43.815252 -79.284577  \n",
       "15  43.799525 -79.318389  \n",
       "16  43.836125 -79.205636  \n",
       "17  43.803762 -79.363452  \n",
       "18  43.778517 -79.346556  \n",
       "19  43.786947 -79.385975  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create Latitude and Longitude columns in df_assigned\n",
    "df_assigned['Latitude'] = np.nan\n",
    "df_assigned['Longitude'] = np.nan\n",
    "\n",
    "# For each postcode in df_assigned, find corresponding coordinates in df_cord and assign it to df_assigned\n",
    "for idx in df_assigned.index:\n",
    "    cord_idx = df_cord['Postal Code'] == df_assigned.loc[idx, 'Postcode']\n",
    "    df_assigned.at[idx, 'Latitude'] = df_cord.loc[cord_idx, 'Latitude'].values\n",
    "    df_assigned.at[idx, 'Longitude'] = df_cord.loc[cord_idx, 'Longitude'].values\n",
    "\n",
    "# Display the results\n",
    "df_assigned.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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