Yikun commented on a change in pull request #32821: URL: https://github.com/apache/spark/pull/32821#discussion_r649663634
########## File path: python/pyspark/pandas/tests/data_type_ops/test_decimal_ops.py ########## @@ -0,0 +1,65 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +import decimal as d + +import numpy as np +import pandas as pd + +from pyspark.pandas.data_type_ops.num_ops import DecimalOps +from pyspark import pandas as ps +from pyspark.pandas.tests.data_type_ops.testing_utils import TestCasesUtils +from pyspark.testing.pandasutils import PandasOnSparkTestCase + + +class DecimalOpsTest(PandasOnSparkTestCase, TestCasesUtils): + @property + def decimal_pser(self): + return pd.Series([d.Decimal(1.0), d.Decimal(2.0), d.Decimal(np.nan)]) + + @property + def decimal_psser(self): + return ps.from_pandas(self.decimal_pser) + + @property + def float_pser(self): + return pd.Series([1, 2, np.nan], dtype=float) + + @property + def float_psser(self): + return ps.from_pandas(self.float_pser) + + def test_datatype_ops(self): + psser = self.decimal_psser + self.assertIsInstance(psser._dtype_op, DecimalOps) + self.assertEqual(psser._dtype_op.pretty_name, "decimal") + + def test_isnull(self): Review comment: Yep ########## File path: python/pyspark/pandas/tests/data_type_ops/test_decimal_ops.py ########## @@ -0,0 +1,65 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +import decimal as d + +import numpy as np +import pandas as pd + +from pyspark.pandas.data_type_ops.num_ops import DecimalOps +from pyspark import pandas as ps +from pyspark.pandas.tests.data_type_ops.testing_utils import TestCasesUtils +from pyspark.testing.pandasutils import PandasOnSparkTestCase + + +class DecimalOpsTest(PandasOnSparkTestCase, TestCasesUtils): + @property + def decimal_pser(self): + return pd.Series([d.Decimal(1.0), d.Decimal(2.0), d.Decimal(np.nan)]) + + @property + def decimal_psser(self): + return ps.from_pandas(self.decimal_pser) + + @property + def float_pser(self): + return pd.Series([1, 2, np.nan], dtype=float) + + @property + def float_psser(self): + return ps.from_pandas(self.float_pser) + + def test_datatype_ops(self): + psser = self.decimal_psser + self.assertIsInstance(psser._dtype_op, DecimalOps) + self.assertEqual(psser._dtype_op.pretty_name, "decimal") + + def test_isnull(self): + deci_psser = self.decimal_psser + float_psser = self.float_psser + + self.assertEqual(deci_psser._dtype_op.pretty_name, "decimal") + self.assertEqual(float_psser._dtype_op.pretty_name, "fractions") + + self.assert_eq( + pd.Series([False, False, False], index=[0, 1, 2]), + deci_psser._dtype_op.isnull(deci_psser), Review comment: Good suggestion. ########## File path: python/pyspark/pandas/data_type_ops/base.py ########## @@ -206,3 +209,10 @@ def restore(self, col: pd.Series) -> pd.Series: def prepare(self, col: pd.Series) -> pd.Series: """Prepare column when from_pandas.""" return col.replace({np.nan: None}) + + def isnull(self, element): Review comment: Sure, it would be: `def isnull(self, series) -> Union["Series", "Index"]:` ########## File path: python/pyspark/pandas/tests/data_type_ops/test_decimal_ops.py ########## @@ -0,0 +1,65 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +import decimal as d + +import numpy as np +import pandas as pd + +from pyspark.pandas.data_type_ops.num_ops import DecimalOps +from pyspark import pandas as ps +from pyspark.pandas.tests.data_type_ops.testing_utils import TestCasesUtils +from pyspark.testing.pandasutils import PandasOnSparkTestCase + + +class DecimalOpsTest(PandasOnSparkTestCase, TestCasesUtils): + @property + def decimal_pser(self): + return pd.Series([d.Decimal(1.0), d.Decimal(2.0), d.Decimal(np.nan)]) + + @property + def decimal_psser(self): + return ps.from_pandas(self.decimal_pser) + + @property + def float_pser(self): + return pd.Series([1, 2, np.nan], dtype=float) + + @property + def float_psser(self): + return ps.from_pandas(self.float_pser) + + def test_datatype_ops(self): + psser = self.decimal_psser + self.assertIsInstance(psser._dtype_op, DecimalOps) + self.assertEqual(psser._dtype_op.pretty_name, "decimal") + + def test_isnull(self): + deci_psser = self.decimal_psser + float_psser = self.float_psser + + self.assertEqual(deci_psser._dtype_op.pretty_name, "decimal") + self.assertEqual(float_psser._dtype_op.pretty_name, "fractions") + + self.assert_eq( + pd.Series([False, False, False], index=[0, 1, 2]), + deci_psser._dtype_op.isnull(deci_psser), + ) + self.assert_eq( + pd.Series([False, False, True], index=[0, 1, 2]), + float_psser._dtype_op.isnull(float_psser), Review comment: It just because I didn't realize we can use pandas.isnull result directly. : ), will fix in next patch -- This is an automated message from the Apache Git Service. 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