{"id":32747842,"url":"https://github.com/sahilmaurya28/youtube-data-analysis","last_synced_at":"2026-04-13T13:04:06.117Z","repository":{"id":321087213,"uuid":"1084425310","full_name":"SahilMaurya28/Youtube-Data-Analysis","owner":"SahilMaurya28","description":"YouTube Data Analysis using Python — uncovering trends, engagement patterns, and correlations between likes, comments, views, and categories to understand what drives content success.","archived":false,"fork":false,"pushed_at":"2025-10-27T17:33:08.000Z","size":22230,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-10-27T19:08:19.433Z","etag":null,"topics":["analysis","data-analysis","data-visualization","matplotlib-pyplot","numpy","pandas","portfolio-project","python","seaborn","youtube"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🎥 YouTube Data Analysis using Python  \n\n## 📊 Project Overview  \nThis project explores and analyzes YouTube video data to uncover key insights into audience engagement, content performance, and viewing trends.  \nBy examining relationships between **likes, comments, views, dislikes**, and **categories**, this analysis aims to understand what factors contribute most to audience engagement.  \n\n---\n\n## 🎯 Objectives  \n- Measure and compare audience **engagement rates** across videos and categories.  \n- Analyze the **correlation** between likes, views, comments, and dislikes.  \n- Identify **top-performing categories** and channels based on engagement.  \n- Visualize audience patterns and relationships through clear, data-driven charts.  \n\n---\n\n## 🧠 Key Insights  \n- Engagement rate does **not always increase with view count** — smaller channels can have highly active audiences.  \n- Strong **correlation** between likes and views suggests that quality engagement drives visibility.  \n- Categories like *Education*, *Pets \u0026 Animals*, and *Science \u0026 Technology* often have **higher engagement rates** despite fewer overall views.  \n- Most videos maintain a **high like-to-dislike ratio**, showing overall positive viewer sentiment.  \n\n---\n\n## 🧰 Tools and Libraries  \n- **Python** 🐍  \n- **Pandas** — Data cleaning \u0026 analysis  \n- **Matplotlib** — Data visualization  \n- **Seaborn** — Advanced charts \u0026 correlation heatmaps  \n- **WordCloud** *(optional)* — Keyword visualization from video titles  \n\n---\n\n## 📈 Visualizations Included  \n- Correlation Heatmap between key engagement metrics  \n- Likes vs Views Scatterplot  \n- Views vs Engagement Rate (Bubble Chart)  \n- Average Engagement per Category  \n- Top Channels by Engagement  \n- *(Optional)* Word Cloud of Trending Video Titles  \n\n---\n\n## 📂 Dataset  \nThe dataset used contains YouTube video statistics such as:  \n- `video_id`, `title`, `channel_title`, `category_title`,  \n- `views`, `likes`, `dislikes`, `comment_count`,  \n- and additional metadata like publish date and trending date.  \n\n\n---\n\n## 🚀 How to Run  \n1. Clone this repository  \n   ```bash\n   git clone https://github.com/\u003cyour-username\u003e/YouTube-Data-Analysis.git\n   cd YouTube-Data-Analysis\n\n📚 Learning Outcomes\n\n-Practiced data cleaning and manipulation with Pandas\n\n-Applied correlation analysis to real-world data\n\n-Improved data visualization and storytelling using Python\n\n-Learned how engagement metrics interact in digital content analytics\n\n\n🏁 Conclusion\n\nThis analysis reveals that audience interaction and content category play crucial roles in YouTube success — not just raw view counts.\nThe project emphasizes how data storytelling can help creators and analysts make data-driven decisions for content strategy.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsahilmaurya28%2Fyoutube-data-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsahilmaurya28%2Fyoutube-data-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsahilmaurya28%2Fyoutube-data-analysis/lists"}