lattitude_and_longitude.ipynb

{
    "nbformat_minor": 1, 
    "cells": [
        {
            "source": "# Latitude & Longitude (Using csv file)", 
            "cell_type": "markdown", 
            "metadata": {
                "collapsed": true
            }
        }, 
        {
            "source": "### Scrap data from wikipedia page & Create dataframe", 
            "cell_type": "markdown", 
            "metadata": {}
        }, 
        {
            "execution_count": 1, 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "source": "import requests\nfrom bs4 import BeautifulSoup\nimport pandas as pd"
        }, 
        {
            "execution_count": 2, 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "source": "page = requests.get(\"https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M\")\nsoup = BeautifulSoup(page.content, 'html.parser')"
        }, 
        {
            "execution_count": 3, 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "source": "table = soup.find('tbody')\nrows = table.select('tr')\nrow = [r.get_text() for r in rows]"
        }, 
        {
            "execution_count": 4, 
            "cell_type": "code", 
            "metadata": {
                "scrolled": true
            }, 
            "outputs": [
                {
                    "execution_count": 4, 
                    "metadata": {}, 
                    "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>0</th>\n      <td>M3A</td>\n      <td>North York</td>\n      <td>Parkwoods</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>M4A</td>\n      <td>North York</td>\n      <td>Victoria Village</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>M5A</td>\n      <td>Downtown Toronto</td>\n      <td>Harbourfront,Regent Park</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>M6A</td>\n      <td>North York</td>\n      <td>Lawrence Heights,Lawrence Manor</td>\n    </tr>\n    <tr>\n      <th>4</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\n0      M3A        North York                        Parkwoods\n1      M4A        North York                 Victoria Village\n2      M5A  Downtown Toronto         Harbourfront,Regent Park\n3      M6A        North York  Lawrence Heights,Lawrence Manor\n4      M7A      Queen's Park                     Queen's Park"
                    }, 
                    "output_type": "execute_result"
                }
            ], 
            "source": "df = pd.DataFrame(row)\ndf1 = df[0].str.split('\\n', expand=True)\ndf2 = df1.rename(columns=df1.iloc[0])\ndf3 = df2.drop(df2.index[0])\ndf4 = df3[df3.Borough != 'Not assigned']\ndf5 = df4.groupby(['Postcode', 'Borough'], sort = False).agg(','.join)\ndf5.reset_index(inplace = True) \ndf6 = df5.replace(\"Not assigned\", \"Queen's Park\")\ndf6.head()"
        }, 
        {
            "source": "## Read csv file", 
            "cell_type": "markdown", 
            "metadata": {}
        }, 
        {
            "execution_count": 5, 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "execution_count": 5, 
                    "metadata": {}, 
                    "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>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\n0         M1B  43.806686 -79.194353\n1         M1C  43.784535 -79.160497\n2         M1E  43.763573 -79.188711\n3         M1G  43.770992 -79.216917\n4         M1H  43.773136 -79.239476"
                    }, 
                    "output_type": "execute_result"
                }
            ], 
            "source": "url = \"http://cocl.us/Geospatial_data\"\ndf7 = pd.read_csv(url)\ndf7.head()"
        }, 
        {
            "source": "## chane the first column's name to be as the first dataframe", 
            "cell_type": "markdown", 
            "metadata": {}
        }, 
        {
            "execution_count": 6, 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "execution_count": 6, 
                    "metadata": {}, 
                    "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>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": "  Postcode   Latitude  Longitude\n0      M1B  43.806686 -79.194353\n1      M1C  43.784535 -79.160497\n2      M1E  43.763573 -79.188711\n3      M1G  43.770992 -79.216917\n4      M1H  43.773136 -79.239476"
                    }, 
                    "output_type": "execute_result"
                }
            ], 
            "source": "df7.rename(columns={'Postal Code': 'Postcode'}, inplace=True)\ndf7.head()"
        }, 
        {
            "source": "## Create a new dataframe to merge first & second dataframe", 
            "cell_type": "markdown", 
            "metadata": {}
        }, 
        {
            "execution_count": 7, 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [
                {
                    "execution_count": 7, 
                    "metadata": {}, 
                    "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      <th>Latitude</th>\n      <th>Longitude</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>M3A</td>\n      <td>North York</td>\n      <td>Parkwoods</td>\n      <td>43.753259</td>\n      <td>-79.329656</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>M4A</td>\n      <td>North York</td>\n      <td>Victoria Village</td>\n      <td>43.725882</td>\n      <td>-79.315572</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>M5A</td>\n      <td>Downtown Toronto</td>\n      <td>Harbourfront,Regent Park</td>\n      <td>43.654260</td>\n      <td>-79.360636</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>M6A</td>\n      <td>North York</td>\n      <td>Lawrence Heights,Lawrence Manor</td>\n      <td>43.718518</td>\n      <td>-79.464763</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>M7A</td>\n      <td>Queen's Park</td>\n      <td>Queen's Park</td>\n      <td>43.662301</td>\n      <td>-79.389494</td>\n    </tr>\n  </tbody>\n</table>\n</div>", 
                        "text/plain": "  Postcode           Borough                    Neighbourhood   Latitude  \\\n0      M3A        North York                        Parkwoods  43.753259   \n1      M4A        North York                 Victoria Village  43.725882   \n2      M5A  Downtown Toronto         Harbourfront,Regent Park  43.654260   \n3      M6A        North York  Lawrence Heights,Lawrence Manor  43.718518   \n4      M7A      Queen's Park                     Queen's Park  43.662301   \n\n   Longitude  \n0 -79.329656  \n1 -79.315572  \n2 -79.360636  \n3 -79.464763  \n4 -79.389494  "
                    }, 
                    "output_type": "execute_result"
                }
            ], 
            "source": "df8 = pd.merge(df6, df7, on='Postcode')\ndf8.head()"
        }, 
        {
            "execution_count": null, 
            "cell_type": "code", 
            "metadata": {}, 
            "outputs": [], 
            "source": ""
        }
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