def test_raises_error_when_transform_df_with_different_n_variables(
df_datetime):
transformer = DatetimeFeatures()
transformer.fit(df_datetime)
# different number of columns than the df used to fit
with pytest.raises(ValueError):
transformer.transform(df_datetime[vars_dt])
def test_raises_error_when_nan_in_transform_df(df_datetime):
transformer = DatetimeFeatures()
transformer.fit(df_datetime)
# dataset containing nans
with pytest.raises(ValueError):
transformer.transform(dates_nan)
transformer = DatetimeFeatures(variables="index")
transformer.fit(dates_idx_dt)
with pytest.raises(ValueError):
transformer.transform(dates_idx_nan)
def test_extract_features_from_localized_tz_variables():
tz_df = pd.DataFrame({
"date_var": [
"2018-10-28 01:30:00",
"2018-10-28 02:00:00",
"2018-10-28 02:30:00",
"2018-10-28 02:00:00",
"2018-10-28 02:30:00",
"2018-10-28 03:00:00",
"2018-10-28 03:30:00",
]
})
tz_df["date_var"] = pd.to_datetime(
tz_df["date_var"]).dt.tz_localize(tz="US/Eastern")
# when utc is None
transformer = DatetimeFeatures(features_to_extract=["hour"]).fit(tz_df)
# init params
assert transformer.variables is None
assert transformer.utc is None
assert transformer.features_to_extract == ["hour"]
# fit attr
assert transformer.variables_ == ["date_var"]
assert transformer.features_to_extract_ == ["hour"]
assert transformer.n_features_in_ == 1
# transform
X = transformer.transform(tz_df)
df_expected = pd.DataFrame({"date_var_hour": [1, 2, 2, 2, 2, 3, 3]})
pd.testing.assert_frame_equal(X, df_expected)
# when utc is True
transformer = DatetimeFeatures(features_to_extract=["hour"],
utc=True).fit(tz_df)
# init params
assert transformer.variables is None
assert transformer.utc is True
assert transformer.features_to_extract == ["hour"]
# fit attr
assert transformer.variables_ == ["date_var"]
assert transformer.features_to_extract_ == ["hour"]
assert transformer.n_features_in_ == 1
# transform
X = transformer.transform(tz_df)
df_expected = pd.DataFrame({"date_var_hour": [5, 6, 6, 6, 6, 7, 7]})
pd.testing.assert_frame_equal(X, df_expected)
def test_raises_error_when_transforming_not_a_df(_not_a_df, df_datetime):
transformer = DatetimeFeatures()
transformer.fit(df_datetime)
# trying to transform not a df
with pytest.raises(TypeError):
transformer.transform(_not_a_df)