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Posted to reviews@spark.apache.org by "itholic (via GitHub)" <gi...@apache.org> on 2023/09/19 12:02:32 UTC
[GitHub] [spark] itholic opened a new pull request, #42994: [SPARK-43433][PS] Match `GroupBy.nth` behavior to the latest Pandas
itholic opened a new pull request, #42994:
URL: https://github.com/apache/spark/pull/42994
### What changes were proposed in this pull request?
This PR proposes to match `GroupBy.nth` behavior to the latest Pandas.
### Why are the changes needed?
To match the behavior of Pandas 2.0.0 and above.
### Does this PR introduce _any_ user-facing change?
**Test DataFrame**
```python
>>> psdf = ps.DataFrame(
... {
... "A": [1, 2, 1, 2],
... "B": [3.1, 4.1, 4.1, 3.1],
... "C": ["a", "b", "b", "a"],
... "D": [True, False, False, True],
... }
... )
>>> psdf
A B C D
0 1 3.1 a True
1 2 4.1 b False
2 1 4.1 b False
3 2 3.1 a True
```
**Before fixing**
```python
>>> psdf.groupby("A").nth(-1)
B C D
A
1 4.1 b False
2 3.1 a True
>>> psdf.groupby("A")[["C"]].nth(-1)
C
A
1 b
2 a
>>> psdf.groupby("A")["B"].nth(-1)
A
1 4.1
2 3.1
Name: B, dtype: float64
```
**After fixing**
```python
>>> psdf.groupby("A").nth(-1)
A B C D
2 1 4.1 b False
3 2 3.1 a True
>>> psdf.groupby("A")[["C"]].nth(-1)
C
2 b
3 a
>>> psdf.groupby("A")["B"].nth(-1)
2 4.1
3 3.1
Name: B, dtype: float64
```
### How was this patch tested?
Enabling the existing tests & updating the doctests.
### Was this patch authored or co-authored using generative AI tooling?
No.
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[GitHub] [spark] HyukjinKwon closed pull request #42994: [SPARK-43433][PS] Match `GroupBy.nth` behavior to the latest Pandas
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon closed pull request #42994: [SPARK-43433][PS] Match `GroupBy.nth` behavior to the latest Pandas
URL: https://github.com/apache/spark/pull/42994
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[GitHub] [spark] itholic commented on pull request #42994: [SPARK-43433][PS] Match `GroupBy.nth` behavior to the latest Pandas
Posted by "itholic (via GitHub)" <gi...@apache.org>.
itholic commented on PR #42994:
URL: https://github.com/apache/spark/pull/42994#issuecomment-1726884937
I don't see any failure on my local testing, but it complains on GitHub CI. Let me take a deeper look why this happens.
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[GitHub] [spark] HyukjinKwon commented on pull request #42994: [SPARK-43433][PS] Match `GroupBy.nth` behavior to the latest Pandas
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on PR #42994:
URL: https://github.com/apache/spark/pull/42994#issuecomment-1730762760
Merged to master.
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[GitHub] [spark] itholic commented on a diff in pull request #42994: [SPARK-43433][PS] Match `GroupBy.nth` behavior to the latest Pandas
Posted by "itholic (via GitHub)" <gi...@apache.org>.
itholic commented on code in PR #42994:
URL: https://github.com/apache/spark/pull/42994#discussion_r1331072003
##########
python/pyspark/pandas/groupby.py:
##########
@@ -1155,14 +1152,32 @@ def nth(self, n: int) -> FrameLike:
else:
sdf = sdf.select(*groupkey_names).distinct()
- internal = internal.copy(
+ agg_columns = []
+ if not self._agg_columns_selected:
Review Comment:
`groupkeys` is going to be a data column instead of index when it's not included by `agg_columns_selected`. And index should be kept without updating from Pandas 2.0.0 for `nth`. Therefore, we should include the `groupkeys` into agg_columns to make it as a data column and create a new `InternalFrame` manually.
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