This program analyzes the relationship between temperature and revenue for an ice cream stand using linear regression. It employs Pandas, Seaborn, Matplotlib, and Scikit-learn for data handling, visualization, and modeling. Features include data exploration, model training/testing, plotting results, and predicting revenue.
active 2024-12-27 → 2024-12-27 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-12-27 to 2024-12-27. Pushes: 1 total, peak 1 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 |
|---|---|---|---|---|
| Jonathan-Gonzalez0 | 1 | 1 | 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.