This project presents a systematic approach to analyze social media data, aiming to extract insights and trends from a simulated dataset. By leveraging Python libraries such as pandas, numpy, Matplotlib, seaborn, and random, the project guides users through tasks such as data generation, exploration, cleaning, visualization, and analysis
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This project presents a systematic approach to analyze social media data, aiming to extract insights and trends from a simulated dataset. By leveraging Python libraries such as pandas, numpy, Matplotlib, seaborn, and random, the project guides users through tasks such as data generation, exploration, cleaning, visualization, and analysis
MoSbeaa/Clean-and-analyze-social-media-usage-data-with-Python
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This project presents a systematic approach to analyze social media data, aiming to extract insights and trends from a simulated dataset. By leveraging Python libraries such as pandas, numpy, Matplotlib, seaborn, and random, the project guides users through tasks such as data generation, exploration, cleaning, visualization, and analysis
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