Welcome to SpotifyStreamlit! This tool is designed to provide in-depth analysis of Spotify's dataset, featuring data on 15,000 songs. It's built with Python and Streamlit, offering a user-friendly interface for data visualization and analysis.
Visualize key metrics of the Spotify dataset, including acousticness, danceability, energy, and more. Understand the distribution and trends within the entire dataset.
A curated table displaying the top 50 songs based on popularity.
Select an artist from a drop-down menu and view detailed visualizations of their song features.
Insights into album data.
- Clustering & Recommendation: Advanced song clustering and personalized recommendations.
- Python 3.x
- Streamlit
- Clone the repository:
git clone https://github.com/rohankumawat/spotifyStreamlit.git
- Navigate to the cloned directory:
cd spotifyStreamlit
- Install dependencies:
pip install -r requirements.txt
- Running the Application
streamlit run spotify.py
We welcome contributions to the spotifyStreamlit project! If you're interested in helping out, please take a moment to read through our CONTRIBUTING.md file. It contains important information about how to contribute to the project, including how to submit issues, pull requests, and coding standards to follow.
Your contributions play a significant role in the continuous development of spotifyStreamlit, and we greatly appreciate any effort you make to help improve this project.
For support, questions, or feedback, please open an issue in the repository.