fix: group by no aggregation (#944)

narwhals/_dask/group_by.py

@@ -72,6 +72,7 @@ def agg(
             output_names.extend(expr._output_names)
 
         return agg_dask(
+            self._df,
             self._grouped,
             exprs,
             self._keys,
@@ -88,6 +89,7 @@ def _from_native_frame(self, df: DaskLazyFrame) -> DaskLazyFrame:
 
 
 def agg_dask(
+    df: DaskLazyFrame,
     grouped: Any,
     exprs: list[DaskExpr],
     keys: list[str],
@@ -99,6 +101,10 @@ def agg_dask(
     - https://github.com/rapidsai/cudf/issues/15118
     - https://github.com/rapidsai/cudf/issues/15084
     """
+    if not exprs:
+        # No aggregation provided
+        return df.select(*keys).unique(subset=keys)
+
     all_simple_aggs = True
     for expr in exprs:
         if not is_simple_aggregation(expr):

narwhals/_pandas_like/group_by.py

@@ -80,6 +80,7 @@ def agg(
             dataframe_is_empty=self._df._native_frame.empty,
             implementation=implementation,
             backend_version=self._df._backend_version,
+            native_namespace=self._df.__native_namespace__(),
         )
 
     def _from_native_frame(self, df: PandasLikeDataFrame) -> PandasLikeDataFrame:
@@ -114,6 +115,7 @@ def agg_pandas(  # noqa: PLR0915
     implementation: Any,
     backend_version: tuple[int, ...],
     dataframe_is_empty: bool,
+    native_namespace: Any,
 ) -> PandasLikeDataFrame:
     """
     This should be the fastpath, but cuDF is too far behind to use it.
@@ -204,9 +206,9 @@ def agg_pandas(  # noqa: PLR0915
             result_aggs = result_nunique_aggs
         elif simple_aggs and not nunique_aggs:
             result_aggs = result_simple_aggs
-        else:  # pragma: no cover
-            msg = "Congrats, you entered unreachable code. Please report a bug to https://github.com/narwhals-dev/narwhals/issues."
-            raise RuntimeError(msg)
+        else:
+            # No aggregation provided
+            result_aggs = native_namespace.DataFrame(grouped.groups.keys(), columns=keys)
         return from_dataframe(result_aggs.loc[:, output_names])
 
     if dataframe_is_empty:

tests/test_group_by.py

@@ -246,3 +246,10 @@ def test_key_with_nulls(constructor: Any, request: Any) -> None:
         )
         expected = {"b": [4.0, 5, float("nan")], "len": [1, 1, 1], "a": [1, 2, 3]}
         compare_dicts(result, expected)
+
+
+def test_no_agg(constructor: Any) -> None:
+    result = nw.from_native(constructor(data)).group_by(["a", "b"]).agg().sort("a", "b")
+
+    expected = {"a": [1, 3], "b": [4, 6]}
+    compare_dicts(result, expected)