BUG: Agg in non-unique col

Author: luke

pandas/core/apply.py

@@ -416,16 +416,23 @@ def agg_dict_like(self) -> DataFrame | Series:
                 results = {key: colg.agg(how) for key, how in arg.items()}
             else:
                 # key used for column selection and output
-                results = {
-                    key: obj._gotitem(key, ndim=1).agg(how) for key, how in arg.items()
-                }
+                results = {}
+                for key, how in arg.items():
+                    indices = [i for i, col in enumerate(obj.columns) if col == key]
+                    if len(indices) == 1:  # for unique columns
+                        results[key] = obj._gotitem(key, ndim=1).agg(how)
+                    else:  # for non-unique columns
+                        col_results = [obj.iloc[:, i].agg(how) for i in indices]
+                        results[key] = col_results
 
         # set the final keys
         keys = list(arg.keys())
 
         # Avoid making two isinstance calls in all and any below
         is_ndframe = [isinstance(r, ABCNDFrame) for r in results.values()]
 
+        is_list = [isinstance(v, list) for v in results.values()]
+
         # combine results
         if all(is_ndframe):
             keys_to_use: Iterable[Hashable]
@@ -451,6 +458,14 @@ def agg_dict_like(self) -> DataFrame | Series:
                 "and transformation operations "
                 "simultaneously"
             )
+        elif any(is_list):
+            # GH#51099
+            # convert list-like values in results to Series with corresponding keys
+            from pandas import Series
+
+            values = [val for sublist in results.values() for val in sublist]
+            keys = [key for key, sublist in results.items() for _ in sublist]
+            result = Series(values, index=keys)
         else:
             from pandas import Series
 

pandas/tests/apply/test_frame_apply.py

@@ -1642,3 +1642,15 @@ def foo2(x, b=2, c=0):
         columns=MultiIndex.from_tuples([("x", "foo1"), ("x", "foo2")]),
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_agg_dist_like_and_nonunique_columns():
+    # GH#51099
+    df = DataFrame(
+        {"A": [None, 2, 3], "B": [1.0, np.nan, 3.0], "C": ["foo", None, "bar"]}
+    )
+    df.columns = ["A", "A", "C"]
+
+    result = df.agg({"A": "count"})  # same with 'apply' instead of 'agg'
+    expected = df["A"].count()
+    tm.assert_series_equal(result, expected)