https://github.com/akku-1206/spotify_data_analysis

https://github.com/akku-1206/spotify_data_analysis

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• Host: GitHub
• URL: https://github.com/akku-1206/spotify_data_analysis
• Owner: Akku-1206
• Created: 2024-11-08T08:32:05.000Z (11 days ago)
• Default Branch: main
• Last Pushed: 2024-11-08T08:46:27.000Z (11 days ago)
• Last Synced: 2024-11-08T09:31:26.746Z (11 days ago)
• Language: Python
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Spotify Tracks Analysis

This project performs an exploratory data analysis (EDA) on Spotify music data to uncover insights and correlations related to song features, popularity, and genre. Using Python and popular data science libraries like Pandas, Seaborn, and Matplotlib, the project provides data cleaning, manipulation, and visualization to help identify patterns and trends in music data.

## Objectives

The main objectives of this analysis are:

- Identifying popular songs and genres.

- Understanding correlations between different song attributes.

- Analyzing trends over time, including song duration and release years.

## Requirements

To run this project, you'll need:

- **Python** 3.x

- Libraries: `numpy`, `pandas`, `matplotlib`, `seaborn`

To install the required libraries, use:

```bash

pip install numpy pandas matplotlib seaborn