zhengruifeng commented on code in PR #38016:
URL: https://github.com/apache/spark/pull/38016#discussion_r980911416
##########
python/pyspark/pandas/tests/indexes/test_base.py:
##########
@@ -203,9 +203,35 @@ def test_to_frame(self):
# non-string names
self.assert_eq(psidx.to_frame(name=[10, 20]), pidx.to_frame(name=[10,
20]))
self.assert_eq(psidx.to_frame(name=("x", 10)),
pidx.to_frame(name=("x", 10)))
- self.assert_eq(
- psidx.to_frame(name=[("x", 10), ("y", 20)]),
pidx.to_frame(name=[("x", 10), ("y", 20)])
- )
+ if LooseVersion(pd.__version__) < LooseVersion("1.5.0"):
+ self.assert_eq(
+ psidx.to_frame(name=[("x", 10), ("y", 20)]),
+ pidx.to_frame(name=[("x", 10), ("y", 20)]),
+ )
+ else:
+ # Since pandas 1.5.0, the result is changed as below:
+ # (x, 10) (y, 20)
+ # b
+ # 0 4 0 4
+ # 1 5 1 5
+ # 3 6 3 6
+ # 5 3 5 3
+ # 6 2 6 2
+ # 8 1 8 1
+ # 9 0 9 0
+ # 0 9 0
+ # 0 9 0
+ #
+ # pandas API on Spark doesn't support mixed type for Index,
Review Comment:
`mixed type` means a `MultiIndex` with different atomic Index type on each
level?
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