| # |
| # 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 unittest |
| |
| import pandas as pd |
| |
| from pyspark import pandas as ps |
| from pyspark.testing.pandasutils import PandasOnSparkTestCase |
| from pyspark.testing.sqlutils import SQLTestUtils |
| from pyspark.testing.utils import have_tabulate, tabulate_requirement_message |
| |
| |
| class SeriesConversionMixin: |
| @property |
| def pser(self): |
| return pd.Series([1, 2, 3, 4, 5, 6, 7], name="x") |
| |
| @property |
| def psser(self): |
| return ps.from_pandas(self.pser) |
| |
| def test_to_numpy(self): |
| pser = pd.Series([1, 2, 3, 4, 5, 6, 7], name="x") |
| |
| psser = ps.from_pandas(pser) |
| self.assert_eq(psser.to_numpy(), pser.values) |
| |
| def test_to_datetime(self): |
| pser = pd.Series(["3/11/2000", "3/12/2000", "3/13/2000"] * 100) |
| psser = ps.from_pandas(pser) |
| |
| self.assert_eq( |
| pd.to_datetime(pser, infer_datetime_format=True), |
| ps.to_datetime(psser, infer_datetime_format=True), |
| ) |
| |
| def test_to_list(self): |
| self.assert_eq(self.psser.tolist(), self.pser.tolist()) |
| |
| def test_to_frame(self): |
| pser = pd.Series(["a", "b", "c"]) |
| psser = ps.from_pandas(pser) |
| |
| self.assert_eq(pser.to_frame(name="a"), psser.to_frame(name="a")) |
| |
| # for MultiIndex |
| midx = pd.MultiIndex.from_tuples([("a", "x"), ("b", "y"), ("c", "z")]) |
| pser = pd.Series(["a", "b", "c"], index=midx) |
| psser = ps.from_pandas(pser) |
| |
| self.assert_eq(pser.to_frame(name="a"), psser.to_frame(name="a")) |
| |
| @unittest.skipIf(not have_tabulate, tabulate_requirement_message) |
| def test_to_markdown(self): |
| pser = pd.Series(["elk", "pig", "dog", "quetzal"], name="animal") |
| psser = ps.from_pandas(pser) |
| |
| self.assert_eq(pser.to_markdown(), psser.to_markdown()) |
| |
| |
| class SeriesConversionTests( |
| SeriesConversionMixin, |
| PandasOnSparkTestCase, |
| SQLTestUtils, |
| ): |
| pass |
| |
| |
| if __name__ == "__main__": |
| from pyspark.pandas.tests.series.test_conversion import * # noqa: F401 |
| |
| try: |
| import xmlrunner |
| |
| testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) |
| except ImportError: |
| testRunner = None |
| unittest.main(testRunner=testRunner, verbosity=2) |