Welcome to my Projects repository! This is a collection of diverse data-focused and coding projects I’ve created, each designed to explore, analyze, and solve interesting problems using various tools and techniques.
Explore Spotify data to uncover insights about song popularity, genres, and more.
- Techniques: EDA, correlations, clustering, and predictive modeling.
- Dataset: Sourced from Kaggle.
- Notebooks: Read the project details here.
Showcase SQL skills by analyzing Spotify songs using relational databases.
- Highlights: Data preparation, normalized database schema, advanced SQL queries, and trend analysis.
- Tools: Python (data preparation), SQL (analysis).
- Dataset: Sourced from Kaggle.
- Notebooks: Read the project details here
Analyze the emotional tone of lyrics from various artists and genres using sentiment analysis techniques.
- Techniques:
- Sentiment analysis using TextBlob (lexicon-based) and VADER (rule-based).
- Comparison of sentiment scores across methods to uncover patterns in lyrical content.
- Highlights:
- Scraped lyrics from Genius API.
- Analyzed songs by artists like Linkin Park, Ed Sheeran, The Weeknd, and more.
- Insights into how sentiment varies by artist and genre.
- Tools: Python (
lyricsgenius,textblob,vaderSentiment,pandas). - Data: Lyrics collected via Genius API.
- Notebooks: Read the project details here
I plan to continually expand this repository with new and exciting projects, including but not limited to:
- Machine Learning applications.
- Data visualizations and storytelling.
- Web scraping and API usage.
- Explorations of real-world datasets.
This repository is a showcase of my journey as a data enthusiast and developer. It’s my space to practice, learn, and share insights that might inspire others in their learning path.
More projects are on the way! Feel free to explore the existing ones, and check back regularly for updates.