https://github.com/reyhaneh-saffar/spotify-music-trends-analysis

Exploring the top 10,000 Spotify songs from 1960 to the present, analyzing music trends and characteristics.
https://github.com/reyhaneh-saffar/spotify-music-trends-analysis

Last synced: 16 days ago
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Exploring the top 10,000 Spotify songs from 1960 to the present, analyzing music trends and characteristics.

• Host: GitHub
• URL: https://github.com/reyhaneh-saffar/spotify-music-trends-analysis
• Owner: reyhaneh-saffar
• Created: 2025-01-09T20:03:54.000Z (21 days ago)
• Default Branch: main
• Last Pushed: 2025-01-09T20:15:24.000Z (21 days ago)
• Last Synced: 2025-01-09T21:26:00.692Z (21 days ago)
• Language: Jupyter Notebook
• Size: 801 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Spotify Music Trends Analysis

## Overview

This project explores the top 10,000 Spotify songs from 1960 to the present, analyzing music trends and characteristics. The dataset includes track names, artists, albums, release dates, genres, and audio features like danceability, energy, and popularity. It serves as a valuable resource for music trend analysis and recommendations.

## Key Insights

### Data Exploration

- **Dataset Coverage**: Contains detailed information about tracks, including popularity, genres, and various audio features.

- **Research Utility**: Useful for understanding music trends across decades and predicting song characteristics.

### Statistical Tests 

#### Shapiro-Wilk Test

- Tested features such as "Danceability," "Popularity," and "Energy" for normality.

#### Correlation Analysis

- **Danceability vs. Energy**.

#### ANOVA Test

- Analyzed song popularity differences across decades.

#### T-Test

- Compare the popularity of songs across five genres (pop, rock, hip hop, country, jazz).

#### Mann-Whitney U Test

- Examined popularity differences based on energy levels (high vs. low).

#### Kruskal-Wallis Test

- Investigated popularity differences based on acousticness scores (high vs. low).