I'm thrilled to share my latest project, where I delved into linear regression analysis to uncover insights from customer data. 📊 Using Python libraries like pandas, NumPy, and seaborn, I explored relationships between variables and developed a predictive model to understand factors influencing yearly customer spending.
active 2025-01-04 → 2025-01-07 (UTC)
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Line chart, 4 days from 2025-01-04 to 2025-01-07. Pushes: 3 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 |
|---|---|---|---|---|
| MonirulIslamm08 | 3 | 3 | 0 | 0 |
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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.