This project focuses on analyzing and visualizing the top songs of 2023 using data from a Kaggle Dataset and Spotify's API, alongside powerful tools like Deneb, Kaggle, Power BI, and Excel!
- Spotify API: To fetch album covers on the top tracks, artists, and playlists of 2023.
- Kaggle: Provided the main datasets for data comparisons.
- Power BI: For creating the main dashboard with interactive slicers, filters and visuals.
- Deneb & HTML: For powerful, customizable visualizations.
- Excel: Data cleaning, preprocessing, and statistical analysis.
- Sharepoint: To preview the final dashboard.
- Data Collection: Utilized data on the top songs of 2023 using the Kaggle API and added album covers through Spotify's API.
- Data Processing: Cleaned and organized the dataset using Excel and Power BI for optimal analysis.
- Visualizations: Engaging dashboards built with HTML, Deneb and Power BI, showcasing top tracks, artists, and streaming trends of 2023.
- Analysis: Explored music trends and user behavior by analyzing top songs, genres, and artists of 2023.
- Visualizations of the top songs of 2023.
- Insights into streaming trends, genre popularity, and top artists.
- Interactive dashboards with various filtering options.
- Comparative analysis of music attributes through acousticness, danceability, liveness and more!
- Clone the repository.
- Get your Spotify API credentials from Spotify for Developers.
- Alter the file paths in app.py.
- Run the Dashboard_NEW.pbix file!