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amlanmohanty1/customer-trends-data-analysis-SQL-Python-PowerBI

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Data Analytics Portfolio Project with end-to-end industry standard Data Analysis of Customer Shopping Trends from Retail Data using SQL, Python and Power BI.

Jupyter Notebook · active 2025-10-152026-07-17 (UTC)

Complete coverage26,558 / 26,558 hourly files (100%) · 2 absent upstream2023-08-152026-08-25 (UTC)
Events
95
Pushes
4
Pull requests
2
Issues
0
Stars
58
Forks
30

Activity over time

Daily event counts in the loaded window

Line chart, 276 days from 2025-10-15 to 2026-07-17. Pushes: 4 total, peak 4 in a day. Pull requests: 2 total, peak 1 in a day. Issues: 0 total, peak 0 in a day. Comments: 1 total, peak 1 in a day. Stars: 58 total, peak 2 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
amlanmohanty14400
udaykakinada1010
adijain1231010
shailychouhan1001

Recent activity

Latest issues, pull requests and releases

  • Pull request#4udaykakinada2026-04-11 04:30
  • Pull request#1adijain1232025-11-14 13:45

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 58 stars here means stars gained during the window, not the repo's star count.