Yikun commented on code in PR #37801:
URL: https://github.com/apache/spark/pull/37801#discussion_r964975991
##########
python/pyspark/pandas/groupby.py:
##########
@@ -895,6 +895,102 @@ def sem(col: Column) -> Column:
bool_to_numeric=True,
)
+ # TODO: 1, 'n' accepts list and slice; 2, implement 'dropna' parameter
+ def nth(self, n: int) -> FrameLike:
+ """
+ Take the nth row from each group.
+
+ .. versionadded:: 3.4.0
+
+ Parameters
+ ----------
+ n : int
+ A single nth value for the row
+
+ Returns
+ -------
+ Series or DataFrame
+
+ Notes
+ -----
+ There is a behavior difference between pandas-on-Spark and pandas:
+
+ * when there is no aggregation column, and `n` not equal to 0 or -1,
+ the returned empty dataframe may have an index with different lenght
`__len__`.
Review Comment:
```suggestion
```
##########
python/pyspark/pandas/groupby.py:
##########
@@ -895,6 +895,102 @@ def sem(col: Column) -> Column:
bool_to_numeric=True,
)
+ # TODO: 1, 'n' accepts list and slice; 2, implement 'dropna' parameter
+ def nth(self, n: int) -> FrameLike:
+ """
+ Take the nth row from each group.
+
Review Comment:
```
.. note:: There is a behavior difference between pandas-on-Spark and
pandas:
when there is no aggregation column, and `n` not equal to 0 or
-1,
the returned empty dataframe may have an index with different
lenght `__len__`.
```
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