Interactive YouTube Analytics with PCA and Clustering
Автор: Ankita Sethi
Загружено: 2026-02-02
Просмотров: 5
Описание:
This video demonstrates an interactive data visualization project built to analyze global YouTube channel statistics.
The project applies Principal Component Analysis (PCA) to reduce dimensionality, visualizes eigenvalues using a scree plot, and explores data relationships through PCA biplots and scatterplot matrices. K-means clustering is used to identify patterns in channel popularity, growth, and earnings.
The interface is built using D3.js for interactive visualizations, with Python used on the backend for data processing, PCA computation, and clustering.
Dataset: Global YouTube Statistics 2023 (Kaggle)
This project highlights practical visual analytics techniques for exploring high-dimensional real-world data.
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