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Documentaries, Comedy dominate top categories  \n- **Type Split**: 69.7% Movies vs 30.3% TV Shows  \n- **Top Ratings**: Most content rated TV-MA, TV-14  \n- **Peak Year**: 2019 had the highest number of new additions\n\n---\n\n## File Structure\n\nNetflix-Data-Analysis/  \n│  \n├── dashboard/  \n│ ├── Dashboard.twb # Tableau workbook  \n│ └── Dashboard.png # Dashboard image  \n│  \n├── data/  \n│ ├── netflix_data.csv # Raw data  \n│ └── netflix_data.xlsx # Cleaned or used in Tableau  \n│  \n├── notebooks/  \n│ └── netflix_data_analysis.ipynb # EDA notebook  \n│  \n└── README.md  \n\n---\n\n## What I Learned\n\n- Conducting deep EDA on media/entertainment datasets\n- Identifying content trends using date-time analysis\n- Visual storytelling using Tableau\n- Structuring professional GitHub repos\n\n---\n\n*This project is part of my Data Analyst Portfolio.*\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FNishuMehta%2FNetflix-Trends-Data-Analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FNishuMehta%2FNetflix-Trends-Data-Analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FNishuMehta%2FNetflix-Trends-Data-Analysis/lists"}