def test_dummy_encoder_8():
tr_df = pd.DataFrame({'A': ['a', 'b', 'd']})
denc = DummyEncoder(ifq_thrshld=1).fit(tr_df)
te_df = pd.DataFrame({'A': ['f', 'h', 'y']})
encoded = denc.transform(te_df).todense()
expected = np.array([[1, 1, 1]]).T
assert np.array_equal(expected, encoded)
def test_dummy_encoder_6():
df = pd.DataFrame({
'A': ['a', 'b', 'd'],
'B': ['d', 'd', 'f'],
'C': [1, 2, np.nan]
})
denc = DummyEncoder(ifq_thrshld=1, ifq_str_rpl='unk').fit(df)
assert denc.var_names == ['A_unk', 'B_d', 'B_unk', 'C']
def test_dummy_encoder_4():
df = pd.DataFrame({
'A': ['a', 'b', np.nan],
'B': ['d', 'd', 'f'],
'C': [1, 2, np.nan]
})
denc = DummyEncoder(nan_str_rpl='NaN').fit(df)
assert denc.var_names == ['A_NaN', 'A_a', 'A_b', 'B_d', 'B_f', 'C']
def test_dummy_encoder_3():
df = pd.DataFrame({
'A': ['a', 'b', np.nan],
'B': ['d', 'd', 'f'],
'C': [1, 2, np.nan]
})
encoded = DummyEncoder().fit_transform(df)
assert encoded.shape == (3, 3 + 2 + 1)
def test_dummy_encoder_5():
df = pd.DataFrame({
'A': ['a', 'b', np.nan],
'B': ['d', 'd', 'f'],
'C': [1, 2, np.nan]
})
encoded = DummyEncoder().fit_transform(df).todense().view(np.ndarray)
expected = np.array([[0, 0, 1], [1, 0, 0], [0, 1, 0], [1, 1, 0], [0, 0, 1],
[1, 2, np.nan]]).T
assert nan_equal(expected, encoded)
def test_dummy_encoder_1():
denc = DummyEncoder()
assert denc is not None
def test_dummy_encoder_9():
_test_immutability(encoder=DummyEncoder())