This project analyzes a dataset from "Rate Your Music," obtained from Kaggle. The primary goal is to explore the influence of album ratings and music genres on their chart positions.
The dataset includes ratings and genre classifications for the top 5000 albums as rated by users on "Rate Your Music." Users can rate any music release, from singles to albums.
- Does the average rating of an album affect its position on the chart?
- Does the genre of music influence chart position?
- Rating Influence: There's a clear correlation between higher album ratings and better chart positions. Albums in the top 10 consistently scored above 4.0 out of 5.0.
- Genre Influence: Certain genres do appear to have different impacts on chart positions. Despite higher ratings, some popular genres did not correlate with higher chart positions, suggesting that popularity might play a role.
- Figures 1 and 2 compare ratings of albums in top and bottom chart positions.
- Figure 3 examines the relationship between music genre and chart positions.
- Python for data manipulation and analysis.
- Libraries: Pandas for data handling, Matplotlib and Seaborn for visualizations.
The analysis confirms that both the average rating and the genre of an album can significantly influence its chart position. Higher-rated albums and certain genres are more likely to achieve higher positions.
Future research could explore other factors like sales volume and artist popularity, which could also impact album chart positions.
- Clone this repository.
- Install required Python libraries:
pip install pandas matplotlib seaborn - Run the Jupyter notebooks provided in the
notebooksfolder.
- Data source: Kaggle
- Additional resources and code examples from Stack Overflow and Medium.
Additional supporting materials and code snippets are included in the appendix folder of this project repository.