This fix allows a DataFrame to retain key order from a dictionary with only one column instead of sorting them alphabetically.

Author: paulreece

doc/source/whatsnew/v2.2.0.rst

@@ -327,7 +327,7 @@ Datetimelike
 - Bug in addition or subtraction of :class:`BusinessDay` offset with ``offset`` attribute to non-nanosecond :class:`Index`, :class:`Series`, or :class:`DataFrame` column giving incorrect results (:issue:`55608`)
 - Bug in addition or subtraction of :class:`DateOffset` objects with microsecond components to ``datetime64`` :class:`Index`, :class:`Series`, or :class:`DataFrame` columns with non-nanosecond resolution (:issue:`55595`)
 - Bug in addition or subtraction of very large :class:`Tick` objects with :class:`Timestamp` or :class:`Timedelta` objects raising ``OverflowError`` instead of ``OutOfBoundsTimedelta`` (:issue:`55503`)
--
+- Bug in creating a Dataframe using the from_dict method which would alphabetize the rows of the created DataFrame.  (:issue:`55683`)
 
 Timedelta
 ^^^^^^^^^

pandas/core/indexes/api.py

@@ -220,7 +220,10 @@ def union_indexes(indexes, sort: bool | None = True) -> Index:
     if len(indexes) == 1:
         result = indexes[0]
         if isinstance(result, list):
-            result = Index(sorted(result))
+            if not sort:
+                result = Index(result)
+            else:
+                result = Index(sorted(result))
         return result
 
     indexes, kind = _sanitize_and_check(indexes)

pandas/tests/frame/constructors/test_from_dict.py

@@ -200,3 +200,24 @@ def test_from_dict_orient_invalid(self):
         )
         with pytest.raises(ValueError, match=msg):
             DataFrame.from_dict({"foo": 1, "baz": 3, "bar": 2}, orient="abc")
+
+    def test_from_dict_order_with_single_column(self):
+        data = {
+            "alpha": {
+                "value2": 123,
+                "value1": 532,
+                "animal": 222,
+                "plant": False,
+                "name": "test",
+            }
+        }
+        result = DataFrame.from_dict(
+            data,
+            orient="columns",
+        )
+        expected = DataFrame(
+            [[123], [532], [222], [False], ["test"]],
+            index=["value2", "value1", "animal", "plant", "name"],
+            columns=["alpha"],
+        )
+        tm.assert_frame_equal(result, expected)

pandas/tests/frame/methods/test_rename.py

@@ -53,10 +53,10 @@ def test_rename(self, float_frame):
         # gets sorted alphabetical
         df = DataFrame(data)
         renamed = df.rename(index={"foo": "bar", "bar": "foo"})
-        tm.assert_index_equal(renamed.index, Index(["foo", "bar"]))
+        tm.assert_index_equal(renamed.index, Index(["bar", "foo"]))
 
         renamed = df.rename(index=str.upper)
-        tm.assert_index_equal(renamed.index, Index(["BAR", "FOO"]))
+        tm.assert_index_equal(renamed.index, Index(["FOO", "BAR"]))
 
         # have to pass something
         with pytest.raises(TypeError, match="must pass an index to rename"):

pandas/tests/indexing/multiindex/test_setitem.py

@@ -175,7 +175,7 @@ def test_multiindex_setitem2(self):
         )
 
         expected = df_orig.copy()
-        expected.iloc[[0, 2, 3]] *= 2
+        expected.iloc[[0, 1, 3]] *= 2
 
         idx = pd.IndexSlice
         df = df_orig.copy()