| # |
| # 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 |
| |
| |
| class IntersectionMixin: |
| def test_intersection(self): |
| pidx = pd.Index([1, 2, 3, 4], name="Koalas") |
| psidx = ps.from_pandas(pidx) |
| |
| # other = Index |
| pidx_other = pd.Index([3, 4, 5, 6], name="Koalas") |
| psidx_other = ps.from_pandas(pidx_other) |
| self.assert_eq(pidx.intersection(pidx_other), psidx.intersection(psidx_other).sort_values()) |
| self.assert_eq( |
| (pidx + 1).intersection(pidx_other), (psidx + 1).intersection(psidx_other).sort_values() |
| ) |
| |
| pidx_other_different_name = pd.Index([3, 4, 5, 6], name="Databricks") |
| psidx_other_different_name = ps.from_pandas(pidx_other_different_name) |
| self.assert_eq( |
| pidx.intersection(pidx_other_different_name), |
| psidx.intersection(psidx_other_different_name).sort_values(), |
| ) |
| self.assert_eq( |
| (pidx + 1).intersection(pidx_other_different_name), |
| (psidx + 1).intersection(psidx_other_different_name).sort_values(), |
| ) |
| |
| pidx_other_from_frame = pd.DataFrame({"a": [3, 4, 5, 6]}).set_index("a").index |
| psidx_other_from_frame = ps.from_pandas(pidx_other_from_frame) |
| self.assert_eq( |
| pidx.intersection(pidx_other_from_frame), |
| psidx.intersection(psidx_other_from_frame).sort_values(), |
| ) |
| self.assert_eq( |
| (pidx + 1).intersection(pidx_other_from_frame), |
| (psidx + 1).intersection(psidx_other_from_frame).sort_values(), |
| ) |
| |
| # other = MultiIndex |
| pmidx = pd.MultiIndex.from_tuples([("a", "x"), ("b", "y"), ("c", "z")]) |
| psmidx = ps.from_pandas(pmidx) |
| self.assert_eq( |
| pidx.intersection(pmidx), psidx.intersection(psmidx).sort_values(), almost=True |
| ) |
| self.assert_eq( |
| (pidx + 1).intersection(pmidx), |
| (psidx + 1).intersection(psmidx).sort_values(), |
| almost=True, |
| ) |
| |
| # other = Series |
| pser = pd.Series([3, 4, 5, 6]) |
| psser = ps.from_pandas(pser) |
| self.assert_eq(pidx.intersection(pser), psidx.intersection(psser).sort_values()) |
| self.assert_eq((pidx + 1).intersection(pser), (psidx + 1).intersection(psser).sort_values()) |
| |
| pser_different_name = pd.Series([3, 4, 5, 6], name="Databricks") |
| psser_different_name = ps.from_pandas(pser_different_name) |
| self.assert_eq( |
| pidx.intersection(pser_different_name), |
| psidx.intersection(psser_different_name).sort_values(), |
| ) |
| self.assert_eq( |
| (pidx + 1).intersection(pser_different_name), |
| (psidx + 1).intersection(psser_different_name).sort_values(), |
| ) |
| |
| others = ([3, 4, 5, 6], (3, 4, 5, 6), {3: None, 4: None, 5: None, 6: None}) |
| for other in others: |
| self.assert_eq(pidx.intersection(other), psidx.intersection(other).sort_values()) |
| self.assert_eq( |
| (pidx + 1).intersection(other), (psidx + 1).intersection(other).sort_values() |
| ) |
| |
| # MultiIndex / other = Index |
| self.assert_eq( |
| pmidx.intersection(pidx), psmidx.intersection(psidx).sort_values(), almost=True |
| ) |
| self.assert_eq( |
| pmidx.intersection(pidx_other_from_frame), |
| psmidx.intersection(psidx_other_from_frame).sort_values(), |
| almost=True, |
| ) |
| |
| # MultiIndex / other = MultiIndex |
| pmidx_other = pd.MultiIndex.from_tuples([("c", "z"), ("d", "w")]) |
| psmidx_other = ps.from_pandas(pmidx_other) |
| self.assert_eq( |
| pmidx.intersection(pmidx_other), psmidx.intersection(psmidx_other).sort_values() |
| ) |
| |
| # MultiIndex / other = list |
| other = [("c", "z"), ("d", "w")] |
| self.assert_eq(pmidx.intersection(other), psmidx.intersection(other).sort_values()) |
| |
| # MultiIndex / other = tuple |
| other = (("c", "z"), ("d", "w")) |
| self.assert_eq(pmidx.intersection(other), psmidx.intersection(other).sort_values()) |
| |
| # MultiIndex / other = dict |
| other = {("c", "z"): None, ("d", "w"): None} |
| self.assert_eq(pmidx.intersection(other), psmidx.intersection(other).sort_values()) |
| |
| # MultiIndex with different names. |
| pmidx1 = pd.MultiIndex.from_tuples([("a", "x"), ("b", "y"), ("c", "z")], names=["X", "Y"]) |
| pmidx2 = pd.MultiIndex.from_tuples([("c", "z"), ("d", "w")], names=["A", "B"]) |
| psmidx1 = ps.from_pandas(pmidx1) |
| psmidx2 = ps.from_pandas(pmidx2) |
| self.assert_eq(pmidx1.intersection(pmidx2), psmidx1.intersection(psmidx2).sort_values()) |
| |
| with self.assertRaisesRegex(TypeError, "Input must be Index or array-like"): |
| psidx.intersection(4) |
| with self.assertRaisesRegex(TypeError, "other must be a MultiIndex or a list of tuples"): |
| psmidx.intersection(4) |
| with self.assertRaisesRegex(TypeError, "other must be a MultiIndex or a list of tuples"): |
| psmidx.intersection(ps.Series([3, 4, 5, 6])) |
| with self.assertRaisesRegex(TypeError, "other must be a MultiIndex or a list of tuples"): |
| psmidx.intersection([("c", "z"), ["d", "w"]]) |
| with self.assertRaisesRegex(ValueError, "Index data must be 1-dimensional"): |
| psidx.intersection(ps.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})) |
| with self.assertRaisesRegex(ValueError, "Index data must be 1-dimensional"): |
| psmidx.intersection(ps.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})) |
| # other = list of tuple |
| with self.assertRaisesRegex(ValueError, "Names should be list-like for a MultiIndex"): |
| psidx.intersection([(1, 2), (3, 4)]) |
| |
| |
| class IntersectionTests( |
| IntersectionMixin, |
| PandasOnSparkTestCase, |
| SQLTestUtils, |
| ): |
| pass |
| |
| |
| if __name__ == "__main__": |
| from pyspark.pandas.tests.indexes.test_intersection 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) |