blob: 338214c99e123fe36a70a06a6c3742cac83b2c6d [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 pandas as pd
from pyspark import pandas as ps
from pyspark.pandas.config import set_option, reset_option
from pyspark.testing.pandasutils import PandasOnSparkTestCase
from pyspark.testing.sqlutils import SQLTestUtils
class AssignSeriesMixin:
@property
def pdf1(self):
return pd.DataFrame(
{"a": [1, 2, 3, 4, 5, 6, 7, 8, 9], "b": [4, 5, 6, 3, 2, 1, 0, 0, 0]},
index=[0, 1, 3, 5, 6, 8, 9, 10, 11],
)
@property
def pdf2(self):
return pd.DataFrame(
{"a": [9, 8, 7, 6, 5, 4, 3, 2, 1], "b": [0, 0, 0, 4, 5, 6, 1, 2, 3]},
index=list(range(9)),
)
@property
def pdf3(self):
return pd.DataFrame(
{"b": [1, 1, 1, 1, 1, 1, 1, 1, 1], "c": [1, 1, 1, 1, 1, 1, 1, 1, 1]},
index=list(range(9)),
)
@property
def pdf4(self):
return pd.DataFrame(
{"e": [2, 2, 2, 2, 2, 2, 2, 2, 2], "f": [2, 2, 2, 2, 2, 2, 2, 2, 2]},
index=list(range(9)),
)
@property
def pdf5(self):
return pd.DataFrame(
{
"a": [1, 2, 3, 4, 5, 6, 7, 8, 9],
"b": [4, 5, 6, 3, 2, 1, 0, 0, 0],
"c": [4, 5, 6, 3, 2, 1, 0, 0, 0],
},
index=[0, 1, 3, 5, 6, 8, 9, 10, 11],
).set_index(["a", "b"])
@property
def pdf6(self):
return pd.DataFrame(
{
"a": [9, 8, 7, 6, 5, 4, 3, 2, 1],
"b": [0, 0, 0, 4, 5, 6, 1, 2, 3],
"c": [9, 8, 7, 6, 5, 4, 3, 2, 1],
"e": [4, 5, 6, 3, 2, 1, 0, 0, 0],
},
index=list(range(9)),
).set_index(["a", "b"])
@property
def pser1(self):
midx = pd.MultiIndex(
[["lama", "cow", "falcon", "koala"], ["speed", "weight", "length", "power"]],
[[0, 3, 1, 1, 1, 2, 2, 2], [0, 2, 0, 3, 2, 0, 1, 3]],
)
return pd.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1], index=midx)
@property
def pser2(self):
midx = pd.MultiIndex(
[["lama", "cow", "falcon"], ["speed", "weight", "length"]],
[[0, 0, 0, 1, 1, 1, 2, 2, 2], [0, 1, 2, 0, 1, 2, 0, 1, 2]],
)
return pd.Series([-45, 200, -1.2, 30, -250, 1.5, 320, 1, -0.3], index=midx)
@property
def pser3(self):
midx = pd.MultiIndex(
[["koalas", "cow", "falcon"], ["speed", "weight", "length"]],
[[0, 0, 0, 1, 1, 1, 2, 2, 2], [1, 1, 2, 0, 0, 2, 2, 2, 1]],
)
return pd.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3], index=midx)
@property
def psdf1(self):
return ps.from_pandas(self.pdf1)
@property
def psdf2(self):
return ps.from_pandas(self.pdf2)
@property
def psdf3(self):
return ps.from_pandas(self.pdf3)
@property
def psdf4(self):
return ps.from_pandas(self.pdf4)
@property
def psdf5(self):
return ps.from_pandas(self.pdf5)
@property
def psdf6(self):
return ps.from_pandas(self.pdf6)
@classmethod
def setUpClass(cls):
super().setUpClass()
set_option("compute.ops_on_diff_frames", True)
@classmethod
def tearDownClass(cls):
reset_option("compute.ops_on_diff_frames")
super().tearDownClass()
def test_assignment_series(self):
psdf = ps.from_pandas(self.pdf1)
pdf = self.pdf1
psser = psdf.a
pser = pdf.a
psdf["a"] = self.psdf2.a
pdf["a"] = self.pdf2.a
self.assert_eq(psdf.sort_index(), pdf.sort_index())
self.assert_eq(psser, pser)
psdf = ps.from_pandas(self.pdf1)
pdf = self.pdf1
psser = psdf.a
pser = pdf.a
psdf["a"] = self.psdf2.b
pdf["a"] = self.pdf2.b
self.assert_eq(psdf.sort_index(), pdf.sort_index())
self.assert_eq(psser, pser)
psdf = ps.from_pandas(self.pdf1)
pdf = self.pdf1
psdf["c"] = self.psdf2.a
pdf["c"] = self.pdf2.a
self.assert_eq(psdf.sort_index(), pdf.sort_index())
# Multi-index columns
psdf = ps.from_pandas(self.pdf1)
pdf = self.pdf1
columns = pd.MultiIndex.from_tuples([("x", "a"), ("x", "b")])
psdf.columns = columns
pdf.columns = columns
psdf[("y", "c")] = self.psdf2.a
pdf[("y", "c")] = self.pdf2.a
self.assert_eq(psdf.sort_index(), pdf.sort_index())
pdf = pd.DataFrame({"a": [1, 2, 3], "Koalas": [0, 1, 2]}).set_index("Koalas", drop=False)
psdf = ps.from_pandas(pdf)
psdf.index.name = None
psdf["NEW"] = ps.Series([100, 200, 300])
pdf.index.name = None
pdf["NEW"] = pd.Series([100, 200, 300])
self.assert_eq(psdf.sort_index(), pdf.sort_index())
def test_assignment_series_chain(self):
psdf = ps.from_pandas(self.pdf1)
pdf = self.pdf1
psdf["a"] = self.psdf1.a
pdf["a"] = self.pdf1.a
psdf["a"] = self.psdf2.b
pdf["a"] = self.pdf2.b
psdf["d"] = self.psdf3.c
pdf["d"] = self.pdf3.c
self.assert_eq(psdf.sort_index(), pdf.sort_index())
def test_multi_index_assignment_series(self):
psdf = ps.from_pandas(self.pdf5)
pdf = self.pdf5
psdf["x"] = self.psdf6.e
pdf["x"] = self.pdf6.e
self.assert_eq(psdf.sort_index(), pdf.sort_index())
psdf = ps.from_pandas(self.pdf5)
pdf = self.pdf5
psdf["e"] = self.psdf6.e
pdf["e"] = self.pdf6.e
self.assert_eq(psdf.sort_index(), pdf.sort_index())
psdf = ps.from_pandas(self.pdf5)
pdf = self.pdf5
psdf["c"] = self.psdf6.e
pdf["c"] = self.pdf6.e
self.assert_eq(psdf.sort_index(), pdf.sort_index())
class AssignSeriesTests(
AssignSeriesMixin,
PandasOnSparkTestCase,
SQLTestUtils,
):
pass
if __name__ == "__main__":
import unittest
from pyspark.pandas.tests.diff_frames_ops.test_assign_series 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)