In this analysis, we explored Spotify data using pandas and seaborn focusing on the following areas:
- Most Popular Song: Identified the song with the highest popularity score, revealing the current favorite among listeners.
- Songs Released per Month: Calculated the number of songs released each month to understand monthly release trends.
- Songs Released per Year: Analyzed the annual release patterns to observe trends over multiple years.
- BPM Distribution in Popular Songs: Examined the tempo characteristics of the top 10% most popular songs by analyzing their BPM distribution.
This analysis provides valuable insights into Spotify's music data, highlighting trends in song popularity, release patterns, and tempo characteristics of popular songs. These findings can help in understanding listener preferences and the music industry's release strategies.
- pandas: Data manipulation and analysis.
- seaborn: Data visualization.
- matplotlib: Plotting graphs and visualizations.