The Netflix EDA Project uncovers insights from streaming data to enhance content strategy. Analyzing genres, user behavior, and regional variations, it informs decision-making, improves user experiences, and ensures global relevance. An exciting exploration into Netflix's data-driven success.
๐ Step 1: Data Collection ๐ฅ Obtained the Netflix dataset from Kaggle, ensuring a rich source of information for analysis.
๐งน Step 2: Data Cleaning ๐งผ Employed the versatile pandas library to clean the dataset, handling missing values, removing duplicates, and ensuring data consistency.
๐ Step 3: Visualization ๐ Leveraged the power of Plotly libraries to create captivating visualizations, allowing for the exploration of Netflix data through interactive charts and graphs.
๐ Step 4: Deployment ๐ Deployed the Netflix EDA project using Streamlit, creating a user-friendly interface for seamless exploration and sharing of insights.
๐ Key Takeaways ๐ This project showcases the utilization of Kaggle data, data cleaning with pandas, visualizations with Plotly, and deployment using Streamlit. It offers a captivating journey into the world of Netflix, unraveling patterns and trends for data enthusiasts and streaming enthusiasts alike
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