This project was completed for my statistics for engineers class at wayne state university as the final project for the winter 2023 semester. We used predictive analytics to determine what makes up a popular song by analyzing different metrics that the Spotify api allowed us to obtain.
active 2023-09-12 → 2024-06-04 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 267 days from 2023-09-12 to 2024-06-04. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 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 |
|---|---|---|---|---|
| roryslange | 2 | 2 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
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.