def test_get_cols_features_should_return_feature_columns_excluding_default_non_feature(
self
):
df = pd.DataFrame(
data=np.random.rand(3, 6),
columns=["var1", "var2", "var3", "Treatment", "Outcome", "Propensity"],
)
result = utils.get_cols_features(df)
self.assertEqual(["var1", "var2", "var3"], result)
def test_get_cols_features_should_return_feature_columns_excluding_default_non_feature(
self):
df = pd.DataFrame(data=np.random.rand(3, 6),
columns=[
'var1', 'var2', 'var3', 'Treatment', 'Outcome',
'Propensity'
])
result = utils.get_cols_features(df)
self.assertEqual(['var1', 'var2', 'var3'], result)
def test_get_cols_features_should_return_feature_columns_excluding_non_default_non_feature(
self):
df = pd.DataFrame(data=np.random.rand(3, 6),
columns=[
'var1', 'var2', 'var3', 'MarketedTo', 'Outcome',
'Probability'
])
result = utils.get_cols_features(
df, non_feature_cols=['MarketedTo', 'Outcome', 'Probability'])
self.assertEqual(['var1', 'var2', 'var3'], result)
def test_get_cols_features_should_return_feature_columns_excluding_non_default_non_feature(
self
):
df = pd.DataFrame(
data=np.random.rand(3, 6),
columns=["var1", "var2", "var3", "MarketedTo", "Outcome", "Probability"],
)
result = utils.get_cols_features(
df, non_feature_cols=["MarketedTo", "Outcome", "Probability"]
)
self.assertEqual(["var1", "var2", "var3"], result)