| # |
| # 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 numpy as np |
| import pandas as pd |
| |
| from pyspark import pandas as ps |
| from pyspark.testing.pandasutils import PandasOnSparkTestCase |
| from pyspark.testing.sqlutils import SQLTestUtils |
| |
| |
| class SeriesAsOfMixin: |
| def test_asof(self): |
| pser = pd.Series([1, 2, np.nan, 4], index=[10, 20, 30, 40], name="Koalas") |
| psser = ps.from_pandas(pser) |
| |
| self.assert_eq(psser.asof(20), pser.asof(20)) |
| self.assert_eq(psser.asof([5, 20]).sort_index(), pser.asof([5, 20]).sort_index()) |
| self.assert_eq(psser.asof(100), pser.asof(100)) |
| self.assert_eq(str(psser.asof(-100)), str(pser.asof(-100))) |
| self.assert_eq(psser.asof([-100, 100]).sort_index(), pser.asof([-100, 100]).sort_index()) |
| |
| # where cannot be an Index, Series or a DataFrame |
| self.assertRaises(ValueError, lambda: psser.asof(ps.Index([-100, 100]))) |
| self.assertRaises(ValueError, lambda: psser.asof(ps.Series([-100, 100]))) |
| self.assertRaises(ValueError, lambda: psser.asof(ps.DataFrame({"A": [1, 2, 3]}))) |
| # asof is not supported for a MultiIndex |
| pser.index = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b"), ("y", "c"), ("y", "d")]) |
| psser = ps.from_pandas(pser) |
| self.assertRaises(ValueError, lambda: psser.asof(20)) |
| # asof requires a sorted index (More precisely, should be a monotonic increasing) |
| psser = ps.Series([1, 2, np.nan, 4], index=[10, 30, 20, 40], name="Koalas") |
| self.assertRaises(ValueError, lambda: psser.asof(20)) |
| psser = ps.Series([1, 2, np.nan, 4], index=[40, 30, 20, 10], name="Koalas") |
| self.assertRaises(ValueError, lambda: psser.asof(20)) |
| |
| pidx = pd.DatetimeIndex(["2013-12-31", "2014-01-02", "2014-01-03"]) |
| pser = pd.Series([1, 2, np.nan], index=pidx) |
| psser = ps.from_pandas(pser) |
| |
| self.assert_eq(psser.asof("2014-01-01"), pser.asof("2014-01-01")) |
| self.assert_eq(psser.asof("2014-01-02"), pser.asof("2014-01-02")) |
| self.assert_eq(str(psser.asof("1999-01-02")), str(pser.asof("1999-01-02"))) |
| |
| # SPARK-37482: Skip check monotonic increasing for Series.asof with 'compute.eager_check' |
| pser = pd.Series([1, 2, np.nan, 4], index=[10, 30, 20, 40]) |
| psser = ps.from_pandas(pser) |
| |
| with ps.option_context("compute.eager_check", False): |
| self.assert_eq(psser.asof(20), 1.0) |
| |
| pser = pd.Series([1, 2, np.nan, 4], index=[40, 30, 20, 10]) |
| psser = ps.from_pandas(pser) |
| |
| with ps.option_context("compute.eager_check", False): |
| self.assert_eq(psser.asof(20), 4.0) |
| |
| pser = pd.Series([2, 1, np.nan, 4], index=[10, 20, 30, 40], name="Koalas") |
| psser = ps.from_pandas(pser) |
| self.assert_eq(psser.asof([5, 20]), pser.asof([5, 20])) |
| |
| pser = pd.Series([4, np.nan, np.nan, 2], index=[10, 20, 30, 40], name="Koalas") |
| psser = ps.from_pandas(pser) |
| self.assert_eq(psser.asof([5, 100]), pser.asof([5, 100])) |
| |
| pser = pd.Series([np.nan, 4, 1, 2], index=[10, 20, 30, 40], name="Koalas") |
| psser = ps.from_pandas(pser) |
| self.assert_eq(psser.asof([5, 35]), pser.asof([5, 35])) |
| |
| pser = pd.Series([2, 1, np.nan, 4], index=[10, 20, 30, 40], name="Koalas") |
| psser = ps.from_pandas(pser) |
| self.assert_eq(psser.asof([25, 25]), pser.asof([25, 25])) |
| |
| pser = pd.Series([2, 1, np.nan, 4], index=["a", "b", "c", "d"], name="Koalas") |
| psser = ps.from_pandas(pser) |
| self.assert_eq(psser.asof(["a", "d"]), pser.asof(["a", "d"])) |
| |
| pser = pd.Series( |
| [2, 1, np.nan, 4], |
| index=[ |
| pd.Timestamp(2020, 1, 1), |
| pd.Timestamp(2020, 2, 2), |
| pd.Timestamp(2020, 3, 3), |
| pd.Timestamp(2020, 4, 4), |
| ], |
| name="Koalas", |
| ) |
| psser = ps.from_pandas(pser) |
| self.assert_eq( |
| psser.asof([pd.Timestamp(2020, 1, 1)]), |
| pser.asof([pd.Timestamp(2020, 1, 1)]), |
| ) |
| |
| pser = pd.Series([2, np.nan, 1, 4], index=[10, 20, 30, 40], name="Koalas") |
| psser = ps.from_pandas(pser) |
| self.assert_eq(psser.asof(np.nan), pser.asof(np.nan)) |
| self.assert_eq(psser.asof([np.nan, np.nan]), pser.asof([np.nan, np.nan])) |
| self.assert_eq(psser.asof([10, np.nan]), pser.asof([10, np.nan])) |
| |
| |
| class SeriesAsOfTests( |
| SeriesAsOfMixin, |
| PandasOnSparkTestCase, |
| SQLTestUtils, |
| ): |
| pass |
| |
| |
| if __name__ == "__main__": |
| from pyspark.pandas.tests.series.test_as_of 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) |