随着电商⾏业近⼏年的迅猛发展,电⼦商务从早些年的粗放式经营,逐步转化为精细化运营。随着 平台数据量的不断积累, 通过数据分析挖掘消费者的潜在需求,消费偏好成为平台运营过程中的重要环节。本项⽬基于某电商平台⽤户⾏为数据,在 MySQL 关系型数据库,探索⽤户⾏为规律,寻找⾼价值⽤户;分析商品特征,寻找⾼贡献商品;分析产品功能,优化产品路径。
active 2024-02-17 → 2024-02-17 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-02-17 to 2024-02-17. Pushes: 0 total, peak 0 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
Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.
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.