westonpace commented on code in PR #14482:
URL: https://github.com/apache/arrow/pull/14482#discussion_r1003583810
##########
python/pyarrow/table.pxi:
##########
@@ -5282,6 +5282,7 @@ class TableGroupBy:
list[tuple(str, str, FunctionOptions)]
List of tuples made of aggregation column names followed
by function names and optionally aggregation function options.
+ Pass empty list to imitate drop_duplicates pandas function.
Review Comment:
It's not quite the same though. Pandas `drop_duplicates` will keep columns
that are not key columns. By default it will keep the first value in each
group, though this is configurable. For example:
```
>>> tab = pa.Table.from_pydict({"x": [1, 1, 1, 2, 2], "y": ["a", "b", "c",
"d", "e"]})
>>> pa.TableGroupBy(tab, "x").aggregate([])
pyarrow.Table
x: int64
----
x: [[1,2]]
```
With `drop_duplicates` you would also get `y: [["a", "d"]]`. You can kind
of imitate this by using the `one` function which just picks some arbitrary
value from a non-key column ("first" and "last" are difficult concepts within
datasets at the moment).
```
>>> pa.TableGroupBy(tab, "x").aggregate([("y", "one")])
pyarrow.Table
y_one: string
x: int64
----
y_one: [["a","d"]]
x: [[1,2]]
```
Either way, maybe this should be:
```suggestion
Pass empty list to get a single row for each group.
```
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