https://github.com/hilalguleryuz/python_spotify_youtube_eda_project

https://github.com/hilalguleryuz/python_spotify_youtube_eda_project

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• Host: GitHub
• URL: https://github.com/hilalguleryuz/python_spotify_youtube_eda_project
• Owner: hilalguleryuz
• Created: 2024-10-23T12:04:09.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-10-24T10:01:15.000Z (3 months ago)
• Last Synced: 2024-10-25T04:54:00.643Z (3 months ago)
• Language: Jupyter Notebook
• Size: 858 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## 🎧📊 Spotify & YouTube Exploratory Data Analysis (EDA) Project

In this project, I applied Exploratory Data Analysis (EDA) using Spotify & Youtube data. 

### 📋 Project Overview

#### Engagement Metrics Analysis: 

- I analyzed the correlation between engagement metrics: views, likes, and comments.

- **Findings**: As the number of views increases, the number of likes and comments also increases. Likewise, as the number of likes increases, comments also increases as expected.

  

#### Audio Metrics Analysis: 

- I explored the relationships between audio metrics like danceability, energy, loudness, valance, and instrumentalness.

- **Findings**:

- Strong positive correlation:

There is a strong positive correlation between Energy and Loudness meaning that songs with higher energy tend to be louder or vice versa.

There is also a strong positive correlation between Danceability and Valence which means that songs that are suitable for dancing express more positive emotions.

- Strong negative correlation:

There is a strong negative correlation between Acousticness and Energy meaning that acoustic songs tend to be less energetic.

There is also a strong negative correlation between Acousticness and Loudness meaning that acoustic songs tend to be less loud.r.

  

#### Song Distribution Analysis: 

- I examined the distribution of songs by album type (album, single, compilation).

- **Findings**: 72% of songs were released as albums, 24% as singles.

#### Top 10 Songs on YouTube vs. Spotify:

- Most viewed song on YouTube: "Despacito" (1.5e10 views)

- Most streamed song on Spotify: "Closer" (5e9 streams)

### 🎯 Summary

This analysis provides valuable insights for artists, music producers, and marketing teams. The relationships between engagement and audio features can help guide strategic decisions.