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This repositary is created to demonstrate youtube streamers analysis using python.

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YOUTUBE STREAMERS ANALYSIS

Dataset : Top 1000 Youtubers statistics

Description: This dataset contains valuableinformation about the top YouTube streamers,including their ranking, categories, subscribers,country, visits, likes, comments, and more.Your task is to perform a comprehensiveanalysis of the dataset to extract insightsabout the top YouTube content creators.

  1. Data Exploration: - Start by exploring the dataset to understand its structure and identify key variables. - Check for missing data and outliers.
  2. Trend Analysis: - Identify trends among the top YouTube streamers. Which categories are the most popular? - Is there a correlation between the number of subscribers and the number of likes or comments?
  3. Audience Study: - Analyze the distribution of streamers' audiences by country. Are there regional preferences for specific content categories?
  4. Performance Metrics: - Calculate and visualize the average number of subscribers, visits, likes, and comments. - Are there patterns or anomalies in these metrics?
  5. Content Categories: - Explore the distribution of content categories. Which categories have the highest number of streamers? - Are there specific categories with exceptional performance metrics?
  6. Brands and Collaborations: - Analyze whether streamers with high performance metrics receive more brand collaborations and marketing campaigns.
  7. Benchmarking: - Identify streamers with above-average performance in terms of subscribers, visits, likes, and comments. - Who are the top-performing content creators?
  8. Content Recommendations: - Propose a system for enhancing content recommendations to YouTube users based on streamers categories and performance metrics.

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This repositary is created to demonstrate youtube streamers analysis using python.

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