{"version":"1.0","type":"rich","title":"Students_Dataset_Viz","description":"This example demonstrates Principal Component Analysis (PCA) on a student dataset, reducing high-dimensional data to two components for a scatter plot visualization. It loads CSV data from a GitHub repository, processes the numeric values, and applies a custom PCA implementation using the numeric library to compute eigenvalues and eigenvectors. D3 v6 renders the resulting projections as blue circles with x and y axes, using d3.scaleLinear and d3.axisBottom/axisLeft for the chart layout. The visualization shows how PCA reduces complex data into a clear 2D representation.","provider_name":"VizHub AI Studio","provider_url":"https://vizhub.com","html":"<iframe src=\"https://vizhub.com/viz/dd8848e0f524483b95d4b42800329958?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"0\"></iframe>","width":960,"height":500,"cache_age":3600}