def test_invalid1(): testing_df = df.copy() result = clean.invalidValuesInDataFrame(testing_df) assert (result['col1']['hasInvalidValues'] == True) assert (result['col1']['invalidIndices'] == [2]) assert (result['col2']['hasInvalidValues'] == True) assert (result['col2']['invalidIndices'] == [3]) assert (result['col3']['hasInvalidValues'] == False)
def test_invalid3(): testing_df = df.copy() testing_df['col4'] = pd.Series([1., 2], index = [0, 4]) result = clean.invalidValuesInDataFrame(testing_df) assert (result['col4']['hasInvalidValues'] == True) assert (result['col4']['invalidIndices'] == [1, 2, 3])
def test_invalid2(): testing_df = df.copy() result =clean.invalidValuesInDataFrame(testing_df.dropna()) assert (result['col1']['hasInvalidValues'] == False) assert (result['col2']['hasInvalidValues'] == False) assert (result['col3']['hasInvalidValues'] == False)