ueshin opened a new pull request, #54146:
URL: https://github.com/apache/spark/pull/54146
### What changes were proposed in this pull request?
Makes ops tests with "decimal_nan" columns ignore `NaN` vs. `None`.
### Why are the changes needed?
pandas 3 made `assert_frame_equal` strictly check `NaN` vs. `None`.
```py
>>> pdf = pd.DataFrame([decimal.Decimal(np.nan)])
>>> psdf = ps.from_pandas(pdf)
>>>
>>> pdf
0
0 NaN
>>> psdf
0
0 None
```
- pandas < 3
```py
>>> assert_frame_equal(pdf, psdf.to_pandas())
<stdin>:1: FutureWarning: Mismatched null-like values NaN and None found. In
a future version, pandas equality-testing functions (e.g. assert_frame_equal)
will consider these not-matching and raise.
```
- pandas == 3
```py
>>> pd.__version__
'3.0.0'
>>> assert_frame_equal(pdf, psdf.to_pandas())
Traceback (most recent call last):
...
AssertionError: DataFrame.iloc[:, 0] (column name="0") are different
DataFrame.iloc[:, 0] (column name="0") values are different (100.0 %)
[index]: [0]
[left]: [NaN]
[right]: [None]
At positional index 0, first diff: NaN != None
```
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Updated the related tests.
### Was this patch authored or co-authored using generative AI tooling?
No.
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