In this project, I dive into Citibike Ride Activity data from 2019 in order to better understand the behavior of bike riders in NYC. Utilizing the statistical programming language R, I break down factors such as: gender, day of week, month, speed, etc. Lastly, I see which stations gain or lose the most bikes per day, on average.
active 2024-02-19 → 2024-02-19 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-02-19 to 2024-02-19. Pushes: 8 total, peak 8 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 1 total, peak 1 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| martinbauer1 | 9 | 8 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.