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Then by using geocoder library I find the Longitudes and Latitudes of the Location and add a columns of each in my dataframe.I used python folium library to visualize geographic details of London and its boroughs and I created a map of London with boroughs superimposed on top.his article was written as part of final capstone project for IBM Data Science Professional Certification in Coursera.
I used latitude and longitude values to get the visual as below: I utilized the Foursquare API to explore the boroughs and segment them.
I designed the limit as 100 venue and the radius 1400 meter for each borough from their given latitude and longitude information.
Bexley, Croydon, and Sutton Boroughs have very low house prices but have good venues to visit nearby.
As people are turning to big cities to start a business or work.
Keeping above things in mind it is very difficult for an individual to find such place in such big city and gather this much information.
When we consider all these problems, we can create a map and information chart where the real estate index is placed on London and each district is clustered according to the venue density.
In general, capstone courses are designed to give students practical experience and skill sets they can transfer to their careers.
While the format of capstone courses varies greatly among colleges and universities, the purpose is the same.
Here is a head of the list Venues name, category, latitude and longitude information from Foursquare API. In this reason I used unsupervised learning K-means algorithm to cluster the boroughs.
K-Means algorithm is one of the most common cluster method of unsupervised learning.