In this repository I will make a EDA about the of the most subscribed YouTube channels.

A collection of YouTube giants, this dataset offers a perfect avenue to analyze and gain valuable insights from the luminaries of the platform. With comprehensive details on top creators' subscriber counts, video views, upload frequency, country of origin, earnings, and more, this treasure trove of information is a must-explore for aspiring content creators, data enthusiasts, and anyone intrigued by the ever-evolving online content landscape. Immerse yourself in the world of YouTube success and unlock a wealth of knowledge with this extraordinary dataset.

rank: Position of the YouTube channel based on the number of subscribers Youtuber: Name of the YouTube channel subscribers: Number of subscribers to the channel video views: Total views across all videos on the channel category: Category or niche of the channel Title: Title of the YouTube channel uploads: Total number of videos uploaded on the channel Country: Country where the YouTube channel originates Abbreviation: Abbreviation of the country channel_type: Type of the YouTube channel (e.g., individual, brand) video_views_rank: Ranking of the channel based on total video views country_rank: Ranking of the channel based on the number of subscribers within its country channel_type_rank: Ranking of the channel based on its type (individual or brand) video_views_for_the_last_30_days: Total video views in the last 30 days lowest_monthly_earnings: Lowest estimated monthly earnings from the channel highest_monthly_earnings: Highest estimated monthly earnings from the channel lowest_yearly_earnings: Lowest estimated yearly earnings from the channel highest_yearly_earnings: Highest estimated yearly earnings from the channel subscribers_for_last_30_days: Number of new subscribers gained in the last 30 days created_year: Year when the YouTube channel was created created_month: Month when the YouTube channel was created created_date: Exact date of the YouTube channel's creation Gross tertiary education enrollment (%): Percentage of the population enrolled in tertiary education in the country Population: Total population of the country Unemployment rate: Unemployment rate in the country Urban_population: Percentage of the population living in urban areas Latitude: Latitude coordinate of the country's location Longitude: Longitude coordinate of the country's location

YouTube Analytics: Gain valuable insights into the success factors of top YouTube channels and understand what sets them apart from the rest. Content Strategy: Discover the most popular categories and upload frequencies that resonate with audiences. Regional Influencers: Identify influential YouTube creators from different countries and analyze their impact on a global scale. Earnings Analysis: Explore the correlation between channel performance and estimated earnings. Geospatial Visualization: Visualize the distribution of successful YouTube channels on a world map and uncover geographical trends. Trending Topics: Investigate how certain categories gain popularity over time and correlate with world events.

This project was published in Kaggle: https://www.kaggle.com/datasets/nelgiriyewithana/global-youtube-statistics-2023?datasetId=3566603&sortBy=voteCount