def random_split(df, first_portion=<NUM_LIT>):
mask = np.random.binomial(<NUM_LIT:1>, first_portion, size=len(df)).astype(bool)<EOL>return df[mask].copy(), df[~mask].copy()<EOL>
Randomly sample Dataframe rows. Typically for testset/training set cross-valication

    random_split(pd.DataFrame())