I have to apply PCA on a dataset, which contains both numerical and categorical values. In the preprocessing phase, I converted all the categorical values in numerical, so that the software can deal with them (basically I created dummy variables). Now, in order to apply PCA I have to scale the data matrix such that I have mean equal to 0. My question is: does it make sense to normalize also the categorical values (which now are numbers, but they are actually categorical values)? I think it doesn't, but in that case how do I proceed? I do the PCA without scaling these variables?