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markgamall/Song-Popularity-Data-Science-Project

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The objective of our project is to develop a predictive model that can forecast the popularity of songs on Spotify. To achieve this, we will leverage a comprehensive dataset containing various features related to each song. These features encompass details such as song attributes, information, and specific metrics from the Hot 100 chart.

active 2024-04-302024-05-25 (UTC)

Complete coverage26,626 / 26,626 hourly files (100%) · 2 absent upstream2023-08-152026-08-28 (UTC)
Events
36
Pushes
32
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 26 days from 2024-04-30 to 2024-05-25. Pushes: 32 total, peak 28 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

ContributorContributionsPushesPRsComments
markgamall323200

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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.