rohanjain101 opened a new issue, #38833:
URL: https://github.com/apache/arrow/issues/38833
### Describe the bug, including details regarding any error messages,
version, and platform.
```
>>> df = pd.DataFrame({"A": pd.Series([True, True, True],
dtype="bool[pyarrow]"), "B": pd.Series([9223372036854775805,
9223372036854775806, 9223372036854775807], dtype="int64[pyarrow]")})
>>> pa_table = pa.Table.from_pandas(df)
>>> pa.TableGroupBy(pa_table, ["A"]).aggregate([("B", "mean")])
pyarrow.Table
A: bool
B_mean: double
----
A: [[true]]
B_mean: [[3.0744573456182584e+18]]
>>>
```
I would expect B_mean to be 9.223372036854776e+18. Looks similar to
https://github.com/apache/arrow/issues/34909
The scalar aggregate works as expected:
```
>>> compute.mean(pa_table["B"])
<pyarrow.DoubleScalar: 9.223372036854776e+18>
```
So I would expect the vector aggregate with a single group to produce the
same result.
```
>>> pa.__version__
'14.0.0'
>>>
```
### Component(s)
C++, Python
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