Ellie2020 / IBM_Project

IBM Data Science Professional Certificate

IBM_Project

IBM Data Science Professional Certificate programme.

This is the Capstone Project.

Python libraries and APIs

1. Language: Python.
2. Scraping library: Python BeautifulSoup library.
3. Other libraries: Numpy, Pandas, Matplotlib, sklearn (KMeans), Folium, etc.
4. APIs: Foursquare converts postcodes into their equivalent latitude and longitude values.

PART 1.

1. Creating a table for the city of Toronto that consist of three columns: PostalCode, Borough, and Neighbourhoods.
2. In the newly created table 'not assigned' Borough and Neighbourhoods are removed and overwritten with the corresponding Borough values, respectively.
3. The data stored in the table are extracted from the Wikipedia page at https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M using the BeautifulSoup library.

PART 2.

1. Finding the latitude and longitude with Foursquare API.
2. Adding two extra columns for latitude and longitude to the table (from PART 1) for Toronto diffferent neighbourhoods and boroughs.

PART 3.

Segmenting and Clustering Neighborhoods in Toronto

1. Generate maps to visualize the neighborhoods.
2. Visualize how the neighbourhoods cluster together.