How does PCA behave with missing values?

Standard PCA cannot handle missing values directly and requires imputation or specialized algorithms.

PCA requires complete numeric matrices. Missing values break covariance and SVD computation. Common approaches include mean imputation, iterative PCA, or probabilistic PCA methods.