def test_fillna_numerical():
df_test = InsolverDataFrame(pd.DataFrame(data={'col1': [1, 2, np.nan]}))
df_transformed = InsolverTransform(df_test, [
AutoFillNATransforms(),
])
df_transformed.ins_transform()
assert df_transformed['col1'][2] == 1.5
def test_fillna_categorical():
df_test = InsolverDataFrame(
pd.DataFrame(data={'col1': ['A', 'B', 'C', 'A', None]}))
df_transformed = InsolverTransform(df_test, [
AutoFillNATransforms(),
])
df_transformed.ins_transform()
assert df_transformed['col1'][4] == 'A'
def test_fillna_categorical_all_na():
df_test = InsolverDataFrame(
pd.DataFrame(data={'col1': [None, None, None]}))
df_transformed = InsolverTransform(df_test, [
AutoFillNATransforms(),
])
df_transformed.ins_transform()
assert df_transformed['col1'][0] == 1
assert df_transformed['col1'][1] == 1
assert df_transformed['col1'][2] == 1
def test_EncoderTransforms():
df_test = InsolverDataFrame(
pd.DataFrame(data={'col1': ['A', 'B', 'C', 'A']}))
df_transformed = InsolverTransform(df_test, [
EncoderTransforms(['col1']),
])
df_transformed.ins_transform()
assert df_transformed['col1'][0] == 0
assert df_transformed['col1'][1] == 1
assert df_transformed['col1'][2] == 2
assert df_transformed['col1'][3] == 0
def test_OneHotEncoderTransforms():
df_test = InsolverDataFrame(
pd.DataFrame(data={'col1': ['A', 'B', 'C', 'A']}))
df_transformed = InsolverTransform(df_test, [
OneHotEncoderTransforms(['col1']),
])
df_transformed.ins_transform()
assert 'col1_A' in df_transformed.columns
assert 'col1_B' in df_transformed.columns
assert 'col1_C' in df_transformed.columns
assert df_transformed['col1_A'][0] == 1
assert df_transformed['col1_B'][1] == 1
assert df_transformed['col1_C'][2] == 1
assert df_transformed['col1_A'][3] == 1
def get_claims(self):
if self._df_claims_result:
return InsolverDataFrame(self._df_claims_result)
else:
return None
def get_policies(self):
if self._df_policies_result:
return InsolverDataFrame(self._df_policies_result)
else:
return None