| # |
| # 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 numpy as np |
| import pandas as pd |
| |
| import pyspark.pandas as ps |
| from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils |
| |
| |
| class FrameInterpolateMixin: |
| def _test_interpolate(self, pobj): |
| psobj = ps.from_pandas(pobj) |
| self.assert_eq( |
| psobj.interpolate().sort_index(), |
| pobj.interpolate().sort_index(), |
| ) |
| for limit, limit_direction, limit_area in [ |
| (1, None, None), |
| (2, "forward", "inside"), |
| (3, "backward", "outside"), |
| (4, "backward", "inside"), |
| (5, "both", "inside"), |
| ]: |
| self.assert_eq( |
| psobj.interpolate( |
| limit=limit, limit_direction=limit_direction, limit_area=limit_area |
| ).sort_index(), |
| pobj.interpolate( |
| limit=limit, limit_direction=limit_direction, limit_area=limit_area |
| ).sort_index(), |
| ) |
| |
| def test_interpolate(self): |
| pdf = pd.DataFrame( |
| [ |
| (1, 0.0, np.nan), |
| (2, np.nan, 2.0), |
| (3, 2.0, 3.0), |
| (4, np.nan, 4.0), |
| (5, np.nan, 1.0), |
| ], |
| columns=list("abc"), |
| ) |
| self._test_interpolate(pdf) |
| |
| pdf = pd.DataFrame( |
| [ |
| (0.0, np.nan, -1.0, False, np.nan), |
| (np.nan, 2.0, np.nan, True, np.nan), |
| (2.0, 3.0, np.nan, True, np.nan), |
| (np.nan, 4.0, -4.0, False, np.nan), |
| (np.nan, 1.0, np.nan, True, np.nan), |
| ], |
| columns=list("abcde"), |
| ) |
| self._test_interpolate(pdf) |
| |
| |
| class FrameInterpolateTests( |
| FrameInterpolateMixin, |
| PandasOnSparkTestCase, |
| TestUtils, |
| ): |
| pass |
| |
| |
| if __name__ == "__main__": |
| import unittest |
| from pyspark.pandas.tests.frame.test_interpolate 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) |