Andrew Luyt
Last updated: Friday August 13, 2021
This case study explores a real-world public dataset from Divvy, a bike-sharing company run cooperatively between the City of Chicago and Motivate International Inc. The system provides bicycles in a city-wide network of docking stations which can be accessed by annual members or casual users who purchase a single-ride or day pass. Over four million rides were taken between June 2020 and July 2021.
This case study will explore the differences between members & casual users, along with patterns of overall system use, particularly traffic volume and flow. The R programming language has been used for the entire analysis.
- Introduction: Some more detail on this project
- Data Preparation: Summary examination and sanity checks on the data
- Data Cleaning: processing the raw data into convenient form
- Analysis: Animations, maps, graphs - the fun
part
