BUG: inconsistent behaviour for empty DataFrames

pandas/tests/frame/test_constructors.py

@@ -3177,3 +3177,35 @@ def test_frame_allow_non_nano(self, arr):
     def test_frame_from_dict_allow_non_nano(self, arr):
         df = DataFrame({0: arr})
         assert df.dtypes[0] == arr.dtype
+
+
+def test_dtype_warning_on_empty_list_df():
+    # pd.Series([]) without a specified dtype warns the user
+    expected = pd.DataFrame({"a": pd.Series([]), "b": pd.Series([])})
+
+    with tm.assert_produces_warning(FutureWarning):
+        # Lists does not warn the user
+        result = pd.DataFrame({"a": [], "b": []})
+    tm.assert_frame_equal(result, expected)  # This is true
+
+
+def test_empty_constructs():
+    # There should be a consistency for dtype when it's not supplied by the user
+    result = pd.DataFrame({"a": [], "b": []})
+    expected = pd.DataFrame(columns=["a", "b"])
+
+    tm.assert_frame_equal(result, expected)
+
+
+def test_empty_df_without_column_names():
+    # Given
+    result_with_data = pd.DataFrame([1, 2, 3])
+    expected_with_data = pd.DataFrame(pd.Series([1, 2, 3]))
+    # Then
+    tm.assert_frame_equal(result_with_data, expected_with_data)  # True
+
+    # But when it's empty
+    result_empty = pd.DataFrame([])
+    expected_empty = pd.DataFrame(pd.Series([]))
+
+    tm.assert_frame_equal(result_empty, expected_empty)

pandas/tests/groupby/test_apply.py

@@ -1331,3 +1331,17 @@ def test_result_name_when_one_group(name):
     expected = Series([1, 2], name=name)
 
     tm.assert_series_equal(result, expected)
+
+
+def test_apply_on_empty_groupby_dataframe():
+    df = pd.DataFrame([(date.today(), 2, 3)], columns=["date", "a", "b"])
+    df["date"] = pd.to_datetime(df["date"])
+    df = df[df["b"] == 1]  # An empty dataframe
+    result = df.set_index("date").groupby("a", group_keys=True).apply(lambda x: x)
+
+    df2 = pd.DataFrame([(date.today(), 2, 3)], columns=["date", "a", "b"])
+    df2["date"] = pd.to_datetime(df2["date"])
+    df3 = df2.set_index("date").groupby("a", group_keys=True).apply(lambda x: x)
+    expected = df3.iloc[:0]  # An empty dataframe
+
+    tm.assert_frame_equal(result, expected)