Stratified Sampling in Pandas

Question

I\'ve looked at the Sklearn stratified sampling docs as well as the pandas docs and also Stratified samples from Pandas and sklearn stratified sampling based on a column but

Answer 1

the following sample a total of N row where each group appear in its original proportion to the nearest integer, then shuffle and reset the index using:

df = pd.DataFrame(dict(
    A=[1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 4, 4, 4, 4, 4],
    B=range(20)
))

Short and sweet:

df.sample(n=N, weights='A', random_state=1).reset_index(drop=True)

Long version

df.groupby('A', group_keys=False).apply(lambda x: x.sample(int(np.rint(N*len(x)/len(df))))).sample(frac=1).reset_index(drop=True)