PCA Plot

A PCA (Principal Component Analysis) Plot is a fundamental visualization for exploring high-dimensional data. PCA is a dimensionality reduction technique that transforms complex datasets into a smaller number of "principal components," which capture the most variance in the data. The resulting 2D or 3D plot allows you to visualize the main patterns, clusters, and outliers in your data that would be hidden in a high-dimensional space. It is widely used in fields like bioinformatics, finance, and machine learning to simplify data, identify underlying structures, and prepare data for further modeling. Use a PCA plot to gain a clear, interpretable overview of complex data relationships.