faibarazi / ocean

Toronto Bike Station

• Overview
• Repo content
• Setup

Overview:

Storing information about Toronto bike stations from data acquired from Bike Share Toronto data. The data endpoints are:

• https://tor.publicbikesystem.net/ube/gbfs/v1/en/station_information
• https://tor.publicbikesystem.net/ube/gbfs/v1/en/station_status

The purpose is to acquire the data and load it after merging it to answer the following questions:

• How many bike stations are available in the city?
• What is the average bike availability?
• What are the 3 largest bike stations in the city?
• What are the 3 smallest bike stations in the city?

As well as finding the closest stations given a some coordinates.

Repo content:

• etl_code.ipynb: The implementation in a jupyter notebook.
• etl_code.html: HTML version of the notebook
• data: has the input and output data directories.
  • input: The payload from the 2 endpoints saved as json file.
  • output: The merged information in an sqlite format.
• requirements.txt: Python requirements file.

Setup:

• Clone the repo locally, then make a python virtual environment using $python3 -m venv <venv_name> lets assume the venv_name is ocean_venv moving forward.
• Activate the venv by $source ocean_venv/bin/activate
• Install the python requirements $pip install requirements.txt
• To run the jupyter notebook: $jupyter notebook

NOTE: Running certain cells will overwrite the data inputs and outputs.