https://github.com/sumaiyyaf/spotify-data-analysis

This project explores Spotify music data, using Python to clean, analyze, and visualize the dataset. It examines the relationship between audio features and sentiment in song lyrics, uncovering patterns and trends to provide valuable insights into music preferences.
https://github.com/sumaiyyaf/spotify-data-analysis

eda numpy pandas python

Last synced: about 2 months ago
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This project explores Spotify music data, using Python to clean, analyze, and visualize the dataset. It examines the relationship between audio features and sentiment in song lyrics, uncovering patterns and trends to provide valuable insights into music preferences.

• Host: GitHub
• URL: https://github.com/sumaiyyaf/spotify-data-analysis
• Owner: SumaiyyaF
• Created: 2024-10-24T01:15:48.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-10-24T14:43:02.000Z (over 1 year ago)
• Last Synced: 2025-02-07T01:24:43.004Z (over 1 year ago)
• Topics: eda, numpy, pandas, python
• Language: Jupyter Notebook
• Homepage:
• Size: 603 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: Change in Duration of songs wrt Years.png

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README

          
# Spotify-Data-Analysis

This project focuses on exploring and analyzing music data from Spotify to gain valuable insights. The data used in this analysis is from Kaggle.

The analysis involved cleaning the dataset and performing exploratory data analysis (EDA) using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn. By examining relationships between audio features and conducting sentiment analysis on song lyrics, the project uncovers patterns and trends in music preferences. This project highlights the use of secondary data from Spotify, helping to identify correlations between different musical characteristics while developing strong skills in dataset interpretation and analysis.