Telco Churn Data Analysis explores customer retention trends using Python. It cleans and visualizes data, identifies churn patterns by demographics, contract types, and services. Key insights include churn percentages across variables like gender, senior status, and service types, aiding in targeted retention strategies.
active 2024-10-26 → 2024-10-26 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-10-26 to 2024-10-26. Pushes: 14 total, peak 14 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 |
|---|---|---|---|---|
| world-null | 14 | 14 | 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.