blob: 037ff1fd8687a7b99929cc7fd3f1d1704c522a25 [file] [log] [blame]
#
# 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 PivotTableMixin:
def test_pivot_table(self):
pdf = pd.DataFrame(
{
"a": [4, 2, 3, 4, 8, 6],
"b": [1, 2, 2, 4, 2, 4],
"e": [10, 20, 20, 40, 20, 40],
"c": [1, 2, 9, 4, 7, 4],
"d": [-1, -2, -3, -4, -5, -6],
},
index=np.random.rand(6),
)
psdf = ps.from_pandas(pdf)
self.assert_eq(
psdf.pivot_table(columns="a", values="b").sort_index(),
pdf.pivot_table(columns="a", values="b").sort_index(),
almost=True,
)
self.assert_eq(
psdf.pivot_table(index=["c"], columns="a", values="b").sort_index(),
pdf.pivot_table(index=["c"], columns="a", values="b").sort_index(),
almost=True,
)
self.assert_eq(
psdf.pivot_table(index=["c"], columns="a", values="b", aggfunc="sum").sort_index(),
pdf.pivot_table(index=["c"], columns="a", values="b", aggfunc="sum").sort_index(),
almost=True,
)
self.assert_eq(
psdf.pivot_table(index=["c"], columns="a", values=["b"], aggfunc="sum").sort_index(),
pdf.pivot_table(index=["c"], columns="a", values=["b"], aggfunc="sum").sort_index(),
almost=True,
)
self.assert_eq(
psdf.pivot_table(
index=["c"], columns="a", values=["b", "e"], aggfunc="sum"
).sort_index(),
pdf.pivot_table(
index=["c"], columns="a", values=["b", "e"], aggfunc="sum"
).sort_index(),
almost=True,
)
class PivotTableTests(
PivotTableMixin,
PandasOnSparkTestCase,
SQLTestUtils,
):
pass
if __name__ == "__main__":
from pyspark.pandas.tests.computation.test_pivot_table 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)