Exploring Spotify Audio Features

This is a beginner-friendly data analysis project that explores the relationship between danceability, valence (musical happiness), and energy in songs using a real-world Spotify dataset.

We visualized key audio features to identify patterns in music, using color to represent energy and scatter plots to show feature relationships.

Tools & Libraries

• Python (Google Colab)
• pandas
• matplotlib

What’s Inside

• Summary statistics for danceability, valence, and energy
• Histograms showing the distribution of each feature
• A scatter plot with color-coded energy to compare danceability vs valence
• Interpretations and observations on emotional + rhythmic content in music

Here are some example visualizations from the analysis:

What I Learned

• High danceability doesn't always mean high happiness
• Energy level adds an extra dimension to understanding music mood
• Scatter plots and histograms can reveal hidden musical trends

File Info

• SpotifyDataSet.ipynb: Google Colab notebook containing the analysis

How to Run

1. Click on SpotifyDataSet.ipynb link above.
2. Click Open in Colab (top bar).
3. Run all cells in order — no external API keys needed.