| # stratified sampling | |
| from sklearn.model_selection import StratifiedShuffleSplit | |
| split = StratifiedShuffleSplit(n_splits=1, test_size=0.2, random_state=42) | |
| for train_index, test_index in split.split(housing, housing["income_cat"]): | |
| strat_train_set = housing.loc[train_index] | |
| strat_test_set = housing.loc[test_index] | |
| for set_ in (strat_train_set, strat_test_set): | |
| set_.drop('income_cat', axis=1, inplace=True) |
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