Welcome to this exploratory data analysis (EDA) of YouTube video statistics focusing on Canada's YouTube dataset. In this notebook, we delve into the rich landscape of YouTube content, examining various facets such as views, likes, dislikes, comments, and more to uncover insights and trends within the Canadian YouTube community.
The primary objective of this analysis is to gain a deeper understanding of the dynamics and patterns present in the YouTube landscape specifically within Canada. By leveraging data exploration techniques and data visualization, we aim to extract valuable insights that shed light on user behavior, content popularity, and engagement metrics.
Our analysis begins with thorough data exploration, where we dive into the dataset to understand its structure, features, and distributions. Leveraging popular data science libraries such as pandas, matplotlib, and seaborn, we perform descriptive statistics and visualize key metrics to uncover initial trends.
Throughout this notebook, we'll explore various aspects of the Canadian YouTube dataset, including:
- Distribution of views, likes, dislikes, and comments across different categories.
- Trends in video length and their correlation with engagement metrics.
- Analysis of top-performing channels and videos within the Canadian YouTube community.
- Temporal patterns and seasonality in video uploads and viewership.
By the end of this analysis, we aim to provide valuable insights into the behavior of YouTube users in Canada, as well as offer actionable recommendations for content creators, marketers, and other stakeholders in the YouTube ecosystem.