ueshin commented on a change in pull request #33714:
URL: https://github.com/apache/spark/pull/33714#discussion_r697782465
##########
File path: python/pyspark/pandas/tests/test_ops_on_diff_frames.py
##########
@@ -654,30 +654,35 @@ def test_combine_first(self):
psser1.combine_first(psser2).sort_index(),
pser1.combine_first(pser2).sort_index()
)
- # Series come from same DataFrame
- pdf = pd.DataFrame(
- {
- "A": {"falcon": 330.0, "eagle": 160.0},
- "B": {"falcon": 345.0, "eagle": 200.0, "duck": 30.0},
- }
- )
- pser1 = pdf.A
- pser2 = pdf.B
- psser1 = ps.from_pandas(pser1)
- psser2 = ps.from_pandas(pser2)
+ # DataFrame
+ pdf1 = pd.DataFrame({"A": [None, 0], "B": [4, None]})
+ psdf1 = ps.from_pandas(pdf1)
+ pdf2 = pd.DataFrame({"C": [3, 3], "B": [1, 1]})
+ psdf2 = ps.from_pandas(pdf2)
- self.assert_eq(
- psser1.combine_first(psser2).sort_index(),
pser1.combine_first(pser2).sort_index()
- )
+ if LooseVersion(pd.__version__) >= LooseVersion("1.2.0"):
+ self.assert_eq(pdf1.combine_first(pdf2),
psdf1.combine_first(psdf2))
+ else:
+ # pandas < 1.2.0 returns unexpected dtypes,
+ # please refer to
https://github.com/pandas-dev/pandas/issues/28481 for details
+ expected_pdf = pd.DataFrame({"A": [None, 0], "B": [4.0, 1.0], "C":
[3, 3]})
+ self.assert_eq(expected_pdf, psdf1.combine_first(psdf2))
- psser1.name = ("X", "A")
- psser2.name = ("Y", "B")
- pser1.name = ("X", "A")
- pser2.name = ("Y", "B")
+ pdf1.columns = pd.MultiIndex.from_tuples([("A", "willow"), ("B",
"pine")])
+ psdf1 = ps.from_pandas(pdf1)
+ pdf2.columns = pd.MultiIndex.from_tuples([("C", "oak"), ("B", "pine")])
+ psdf2 = ps.from_pandas(pdf2)
- self.assert_eq(
- psser1.combine_first(psser2).sort_index(),
pser1.combine_first(pser2).sort_index()
- )
+ if LooseVersion(pd.__version__) >= LooseVersion("1.2.0"):
+ self.assert_eq(pdf1.combine_first(pdf2),
psdf1.combine_first(psdf2))
Review comment:
ditto.
##########
File path: python/pyspark/pandas/tests/test_ops_on_diff_frames.py
##########
@@ -654,30 +654,35 @@ def test_combine_first(self):
psser1.combine_first(psser2).sort_index(),
pser1.combine_first(pser2).sort_index()
)
- # Series come from same DataFrame
- pdf = pd.DataFrame(
- {
- "A": {"falcon": 330.0, "eagle": 160.0},
- "B": {"falcon": 345.0, "eagle": 200.0, "duck": 30.0},
- }
- )
- pser1 = pdf.A
- pser2 = pdf.B
- psser1 = ps.from_pandas(pser1)
- psser2 = ps.from_pandas(pser2)
+ # DataFrame
+ pdf1 = pd.DataFrame({"A": [None, 0], "B": [4, None]})
+ psdf1 = ps.from_pandas(pdf1)
+ pdf2 = pd.DataFrame({"C": [3, 3], "B": [1, 1]})
+ psdf2 = ps.from_pandas(pdf2)
- self.assert_eq(
- psser1.combine_first(psser2).sort_index(),
pser1.combine_first(pser2).sort_index()
- )
+ if LooseVersion(pd.__version__) >= LooseVersion("1.2.0"):
+ self.assert_eq(pdf1.combine_first(pdf2),
psdf1.combine_first(psdf2))
Review comment:
I guess this case needs `sort_index()`?
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