def test_reverse_transform_all_none(self):
dt = pd.to_datetime(['2020-01-01'])
dtt = DatetimeTransformer(strip_constant=True)
dtt.fit(dt)
output = dtt.reverse_transform(np.array([None]))
expected = pd.to_datetime(['NaT'])
pd.testing.assert_series_equal(output.to_series(), expected.to_series())
def test_reverse_transform_2d_ndarray(self):
dt = pd.to_datetime(['2020-01-01', '2020-02-01', '2020-03-01'])
dtt = DatetimeTransformer(strip_constant=True)
dtt.fit(dt)
transformed = np.array([[18262.], [18293.], [18322.]])
output = dtt.reverse_transform(transformed)
expected = pd.to_datetime(['2020-01-01', '2020-02-01', '2020-03-01'])
pd.testing.assert_series_equal(output.to_series(), expected.to_series())
def test_fit_nan_mode_series(self):
"""Test fit nan mode with pandas.Series"""
# Setup
data = np.array([None, '1996-10-17', '1965-05-23'])
data = pd.to_datetime(data)
# Run
transformer = DatetimeTransformer(nan='mode')
transformer.fit(data)
# Asserts
expect_nan = 'mode'
expect_fill_value = -145497600000000000
self.assertEqual(transformer.nan, expect_nan, 'Unexpected nan')
self.assertEqual(transformer.null_transformer.fill_value,
expect_fill_value, "Data mean is wrong")
def test_fit_nan_mean_array(self):
"""Test fit nan mean with numpy.array"""
# Setup
data = np.array([None, '1996-10-17', '1965-05-23'])
data = pd.to_datetime(data).to_numpy()
# Run
transformer = DatetimeTransformer(nan='mean')
transformer.fit(data)
# Asserts
expect_nan = 'mean'
expect_fill_value = 350006400000000000
self.assertEqual(transformer.nan, expect_nan, 'Unexpected nan')
self.assertEqual(transformer.null_transformer.fill_value,
expect_fill_value, "Data mean is wrong")