Standardization After PCA for Kmean clustering I want to apply Kmean for clustering after PCA dimensionality reduction. I have standardized data with StandardScaler before the PCA, then I want to train Kmeans for finding clusters. However, the variance among the PCA components could not be of the same order of magnitude. 

It is a good practice to standardize the PCA components before the clustering?
Usually PCA already returns standardized components.

Did you compute the variance of each component? Usually, it will be 1.

The more tricky question is whether to use standardization before doing PCA. I don't think there is a general answer for that.