https://github.com/jacksonpf1/spotify-user-analysis

ETL process and EDA of user top artists & tracks data in Spotify using Spotipy, Pandas, Airflow and Seaborn
https://github.com/jacksonpf1/spotify-user-analysis

airflow airflow-dags data-science data-visualization eda eda-analyses etl etl-pipeline etl-process pipeline-examples seaborn seaborn-plots spotify spotify-api spotipy

Last synced: about 4 hours ago
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ETL process and EDA of user top artists & tracks data in Spotify using Spotipy, Pandas, Airflow and Seaborn

• Host: GitHub
• URL: https://github.com/jacksonpf1/spotify-user-analysis
• Owner: jacksonpf1
• Created: 2023-05-23T03:01:31.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2023-06-22T22:34:19.000Z (over 1 year ago)
• Last Synced: 2024-11-17T05:16:25.647Z (about 4 hours ago)
• Topics: airflow, airflow-dags, data-science, data-visualization, eda, eda-analyses, etl, etl-pipeline, etl-process, pipeline-examples, seaborn, seaborn-plots, spotify, spotify-api, spotipy
• Language: Jupyter Notebook
• Homepage:
• Size: 466 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Spotify User Data ETL & Analysis

ETL process and EDA of user top artists & tracks data in Spotify using Spotipy, Pandas, Airflow and Seaborn.

## Inspired on:

- https://www.youtube.com/playlist?list=PLNkCniHtd0PNM4NZ5etgYMw4ojid0Aa6i

- https://www.youtube.com/watch?v=eg8t2-E69ew

- https://www.spotilyze.com/

# Requirements

See requirements.txt file