PDF with music. Spotify analysis.
In a comprehensive data analysis project, I processed an extensive dataset encompassing all tracks from Spotify's Top 200 list in 36 countries worldwide between 2017 and 2020, consisting of 9,807,001 raw data records and 170,633 detailed song records (https://www.kaggle.com/datasets/pepepython/spotify-huge-database-daily-charts-over-3-years).
The project's primary focus was to identify rising trends in song popularity in Poland, developing an algorithm that could later be adapted for any other country. After filtering both databases for Poland exclusively and ranking songs by their highest positions during the study period, I searched for tracks that reached the Top 50 at least once and remained on the list for a minimum of 10 days.
The analysis included examining initial and final chart positions, emphasizing songs that showed an increasing popularity trend. Each qualifying song was then visually represented through a custom-designed chart for further visual analysis.
The culmination of this project is a uniquely interactive PDF featuring these variability charts, with an added functionality allowing the listener to directly stream each track. This innovative approach not only provides insightful data analysis but also offers an engaging and interactive experience for the audience.