A cool feature for the standardscaler (And other preprocessors) would be a partial_fit option. This would work well with existing out-of-core learning tools (i.e. SGDClassifer's partial_fit). If I can't load the data into memory, I can't use the standardscaler, and I end up calculating the mean and std in batches. That works fine, but it isn't very elegant.