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SpotifyData

Analysis of Spotify chart data across European countries, combining chart rankings with audio features to explore music trends.

Data Sources

Folder Dataset
data/kaggle1/ Spotify Charts — daily/weekly top-200 and viral-50 charts by country
data/kaggle2/ Spotify Dataset 1921-2020 (600k+ Tracks) — track audio features and artist metadata
data/european_countries.csv List of European countries used to filter the charts

Note: To run this notebook you must first download charts.csv from the Spotify Charts dataset on Kaggle and place it in data/kaggle1/. The file is ~3.2 GB, which exceeds GitHub's file-size limit, so it is not included in this repository.

Note: To run this notebook you must first download tracks.csv and artists.csv from the Spotify Dataset 1921-2020 (600k+ Tracks) dataset on Kaggle and place it in data/kaggle2/. The files exceed GitHub's file-size limit, so it is not included in this repository.

🚀 Setup & Installation

  1. Clone the repository.
  2. Create a virtual environment (recommended).
  3. Install the required Python packages using the requirements.txt file:
pip install -r requirements.txt

About

This Spotify study (1920–2020) reveals how shorter, louder tracks and minor keys dominate Europe. While North and South differ in BPM, hits now favor high danceability and rapid virality over long-term cultural retention.

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