Repository files navigation Music Trends Dashboard Project
Ensure you have sqlite3 installed.
The database is pre-populated as music_trends.db
2. Run Calculations and Generate Output Files
Execute main.py to run all completed calculations and write the results to text files.
Ex:
This will generate the following output files in the project directory:
spotify_lastfm_comparison.txt
release_year_distribution.txt
genius_coverage_rate.txt
avg_spotify_popularity.txt
3. Generate Visualizations
Run visualizations.py to create all required and extra credit visualizations.
Ex:
This will generate PNG image files in the project directory:
avg_spotify_popularity.png
spotify_lastfm_comparison.png
itunes_year_distribution.png
genius_coverage_pie_top100.png
main.py : Runs all calculations and writes results to text files.
visualizations.py : Generates all visualizations as PNG images.
calculations.py : Contains all calculation functions used in the project.
database.py : Sets up the SQLite database and tables.
spotify_api.py, itunes_api.py, lastfm/lastfm_api.py, genius/genius_api.py : Scripts to collect data from APIs/websites.
music_trends.db : The main SQLite database file (auto-generated).
calculation_outputs : Results of calculations (see above).
visualization_outputs : Visualizations generated by visualizations.py.
.env : contains the four API keys
Make sure to install any required Python packages (ex: matplotlib) before running visualization scripts:
pip install matplotlib or conda install matplotlib
All scripts should be run from the project root directory.
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