BUG: Fix to GH34422 SeriesGroupBy works only with 'func' now (#34435)

Author: gurukiran07

doc/source/whatsnew/v1.1.0.rst

@@ -975,6 +975,7 @@ Groupby/resample/rolling
   to the input DataFrame is inconsistent. An internal heuristic to detect index mutation would behave differently for equal but not identical
   indices. In particular, the result index shape might change if a copy of the input would be returned.
   The behaviour now is consistent, independent of internal heuristics. (:issue:`31612`, :issue:`14927`, :issue:`13056`)
+- Bug in :meth:`SeriesGroupBy.agg` where any column name was accepted in the named aggregation of ``SeriesGroupBy`` previously. The behaviour now allows only ``str`` and callables else would raise ``TypeError``. (:issue:`34422`)
 
 Reshaping
 ^^^^^^^^^

pandas/core/aggregation.py

@@ -5,7 +5,7 @@
 
 from collections import defaultdict
 from functools import partial
-from typing import Any, DefaultDict, List, Sequence, Tuple
+from typing import Any, Callable, DefaultDict, List, Sequence, Tuple, Union
 
 from pandas.core.dtypes.common import is_dict_like, is_list_like
 
@@ -196,3 +196,39 @@ def maybe_mangle_lambdas(agg_spec: Any) -> Any:
         mangled_aggspec = _managle_lambda_list(agg_spec)
 
     return mangled_aggspec
+
+
+def validate_func_kwargs(
+    kwargs: dict,
+) -> Tuple[List[str], List[Union[str, Callable[..., Any]]]]:
+    """
+    Validates types of user-provided "named aggregation" kwargs.
+    `TypeError` is raised if aggfunc is not `str` or callable.
+
+    Parameters
+    ----------
+    kwargs : dict
+
+    Returns
+    -------
+    columns : List[str]
+        List of user-provied keys.
+    func : List[Union[str, callable[...,Any]]]
+        List of user-provided aggfuncs
+
+    Examples
+    --------
+    >>> validate_func_kwargs({'one': 'min', 'two': 'max'})
+    (['one', 'two'], ['min', 'max'])
+    """
+    no_arg_message = "Must provide 'func' or named aggregation **kwargs."
+    tuple_given_message = "func is expected but recieved {} in **kwargs."
+    columns = list(kwargs)
+    func = []
+    for col_func in kwargs.values():
+        if not (isinstance(col_func, str) or callable(col_func)):
+            raise TypeError(tuple_given_message.format(type(col_func).__name__))
+        func.append(col_func)
+    if not columns:
+        raise TypeError(no_arg_message)
+    return columns, func

pandas/core/groupby/generic.py

@@ -57,6 +57,7 @@
     is_multi_agg_with_relabel,
     maybe_mangle_lambdas,
     normalize_keyword_aggregation,
+    validate_func_kwargs,
 )
 import pandas.core.algorithms as algorithms
 from pandas.core.base import DataError, SpecificationError
@@ -233,13 +234,9 @@ def aggregate(
 
         relabeling = func is None
         columns = None
-        no_arg_message = "Must provide 'func' or named aggregation **kwargs."
         if relabeling:
-            columns = list(kwargs)
-            func = [kwargs[col] for col in columns]
+            columns, func = validate_func_kwargs(kwargs)
             kwargs = {}
-            if not columns:
-                raise TypeError(no_arg_message)
 
         if isinstance(func, str):
             return getattr(self, func)(*args, **kwargs)

pandas/tests/groupby/aggregate/test_aggregate.py

@@ -511,6 +511,21 @@ def test_mangled(self):
         expected = pd.DataFrame({"a": [0, 0], "b": [1, 1]})
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize(
+        "inp",
+        [
+            pd.NamedAgg(column="anything", aggfunc="min"),
+            ("anything", "min"),
+            ["anything", "min"],
+        ],
+    )
+    def test_named_agg_nametuple(self, inp):
+        # GH34422
+        s = pd.Series([1, 1, 2, 2, 3, 3, 4, 5])
+        msg = f"func is expected but recieved {type(inp).__name__}"
+        with pytest.raises(TypeError, match=msg):
+            s.groupby(s.values).agg(a=inp)
+
 
 class TestNamedAggregationDataFrame:
     def test_agg_relabel(self):