This project performs an exploratory data analysis (EDA) on Spotify music data to uncover insights and correlations related to song features, popularity, and genre. Using Python and popular data science libraries like Pandas, Seaborn, and Matplotlib, the project provides data cleaning, manipulation, and visualization to help identify patterns and trends in music data.
The main objectives of this analysis are:
- Identifying popular songs and genres.
- Understanding correlations between different song attributes.
- Analyzing trends over time, including song duration and release years.
To run this project, you'll need:
- Python 3.x
- Libraries:
numpy,pandas,matplotlib,seaborn
To install the required libraries, use:
pip install numpy pandas matplotlib seaborn