Scikit-learn balanced subsampling

Question

I\'m trying to create N balanced random subsamples of my large unbalanced dataset. Is there a way to do this simply with scikit-learn / pandas or do I have to implement it m

Answer 1

A slight modification to the top answer by mikkom.

If you want to preserve ordering of the larger class data, ie. you don't want to shuffle.

Instead of

    if len(this_xs) > use_elems:
        np.random.shuffle(this_xs)

do this

        if len(this_xs) > use_elems:
            ratio = len(this_xs) / use_elems
            this_xs = this_xs[::ratio]