Clustering of São Paulo Subway Stations using Foursquare API

The repository will include code for the project. This includes data, notebooks and reports.

Capstone Project description

At this notebook, Foursquare API was used to cluster subway station (Metro) neighborhoods in Sao Paulo regarding closely venues. The amount of venues per category in each subway station was acquired by a HTTP request to Foursquare API, and then used to group the stations into clusters. For this notebook k-means clustering algorithm was selected to complete this task. Finally, Folium library has been used to visualize the neighborhoods in Sao Paulo and their emerging clusters.

• Report
• Notebook
• Article - Medium Post

Set up

1. Clone the repository

git clone git@github.com:felipetestaaa/ml-sao-paulo-subway-clustering.git

2. Move inside the newly created repository

cd ml-sao-paulo-subway-clustering

3. Create a virtual environment and activate it

virtualenv -p python3 .venv

4. Activate the virtual environment

source .venv/bin/activate

5. Install all libraries

pip install -r requirements.txt

6. Start jupyter

jupyter notebook

7. Deactivate environment (if created and activated before)

deactivate