Here comes the sun: Music features of popular songs reflect prevailing weather conditions

Data and analysis code supporting the paper:

Anglada-Tort, M., Lee, H., Krause, A. E., & North, A. C. (2023). Here comes the sun: music features of popular songs reflect prevailing weather conditions. Royal Society Open Science, 10(5), 221443. https://doi.org/10.1098/rsos.221443

Data and code have been archived within the Zenodo repository: https://zenodo.org/badge/latestdoi/562985935

Analysis

1. analyze-weather/analysis.R: main analysis code
2. analyze-weather/functions.R: supporting methods
3. analyze-weather/prepare-data.R: code to prepare the raw data to the monthly aggregated data used in the main analysis

Data

1. data/spotify_monthly_aggregate.csv: aggregated music featrures data from Spotify (month level)
2. data/spotify_top10_bottom10_aggregate.csv: aggregated music featrures data from Spotify (month level) of the top, middle, and bottom 10 songs
3. data/UK-spotify-unique.csv: song-level data with music features and metadata
4. weather/...: raw weather datasets from the Meteorological Office of the United Kingdom
5. *data/weather_data.csv:"" aggregated raw weather data
6. "data/weather-music-1953-2019.csv:"" aggregated data with weather and music features (generated with prepare-data.R) -> main dataset