- Overview
- Repo content
- Setup
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.
- 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.
- 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.