This project aims to create a web interface that allows users to predict doctor consultation fees based on their input. The machine learning model was trained on a dataset obtained by scraping data from the Practo website using Selenium. With the use of Python Pandas, the scraped data was thoroughly cleaned & preprocessed for accurate predictions.
active 2025-08-14 → 2025-09-05 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 23 days from 2025-08-14 to 2025-09-05. Pushes: 41 total, peak 16 in a day. Pull requests: 15 total, peak 7 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 2 total, peak 1 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
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 2 stars here means stars gained during the window, not the repo's star count.