This Python project was designed to showcase students relatively simple & straightforward data analysis by using Python & Python Libraries. The data is of automobile insurance company. The aim of the assignment is to clean the data and look for correlations or any indicators regarding insurance risk
active 2025-01-04 → 2025-01-04 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2025-01-04 to 2025-01-04. 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.
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Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| Alesyte | 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.