Welcome to the repository for my analysis of the Top 1000 YouTuber Challenge by Onyx! This project dives into comprehensive insights across four key categories: Popularity, Last 30 Days data, Earnings, and Rankings.
- Popularity: Subscriber count, population, and video views.
- Last 30 Days Data: Subscribers and video views.
- Earnings: Highest/lowest monthly and yearly earnings.
- Rankings: Overall, country, channel type, and video view ranks.
In the initial phase, I thoroughly examined the metadata within the dataset and established relationships among key elements. This laid the foundation for a robust analysis.
Utilizing DAX (Data Analysis Expressions) and Power BI, I crafted visually insightful charts to represent the data trends. The README provides a guide on how to interpret these visualizations.
One significant challenge was implementing charts based on a four-category filter. Particularly, retrieving the top 10 rankings for three categories while allowing for 1 to 10 rankings for countries, YouTubers, and channel types. This was successfully addressed using DAX subdivision functions and rank calculations with a switch case.
Feel free to explore the dataset, analyses, and visualizations provided. The README file serves as a comprehensive guide to understanding the project's objectives, methodologies, and insights.
Your feedback and contributions are highly valued. Let's foster collaboration and discussions around this intriguing data analysis challenge!
Feel free to modify this to better suit the specifics of your project and any additional details you'd like to include in your README file.