Coursera Data Science Capstone
Toronto is similar to New York city in many ways. They are both the largest city in their own countries. Besides, both cities are centers for immigrations. According to Quora (John Smith, 2017):
Both the largest cities in their respective countries. Both the financial and tourist capitals of their countries Both have a high cost of living Both have a network of subways, trains and buses serving their greater areas Both are known for their skyscrapers (albeit, Toronto's are limited to its Financial District; New York's cover all of Manhattan) Both are extremely multi-ethnic, although Toronto is more so (49% of TOs citizens were born somewhere else, compared to 36% of NYC's) Both are theatre capitals of the English-speaking world
We make use of both datasets and foursquare API.
We used the data set from "lab: Segmenting and Clustering Neighborhoods in New York City". The data is presented on https://geo.nyu.edu/catalog/nyu_2451_34572. Besides, we also make use of the Toronto data from "peer assignment: Explore and cluster the neighborhoods in Toronto". The data is produced by merging two datasets from http://cocl.us/Geospatial_data and https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M.
Foursquare is a location technology platform dedicated to improving how people move through the real world. Foursquare API This API provides every specific Venue's information respect to given Latitude and Longitude. Foursquare API return the following information of each venue:
- Neighborhoods
- Neighborhoods Latitude 3. Neighborhoods Longitude 4. Venue
- Name of Venue
- Venue Latitude
- Venue Longitude
- Venue Category
