BUG: preserve EA dtype in transpose

doc/source/whatsnew/v1.0.0.rst

@@ -775,6 +775,7 @@ Reshaping
 - Bug where :meth:`DataFrame.equals` returned True incorrectly in some cases when two DataFrames had the same columns in different orders (:issue:`28839`)
 - Bug in :meth:`DataFrame.replace` that caused non-numeric replacer's dtype not respected (:issue:`26632`)
 - Bug in :func:`melt` where supplying mixed strings and numeric values for ``id_vars`` or ``value_vars`` would incorrectly raise a ``ValueError`` (:issue:`29718`)
+- Dtypes are now preserved when transposing a ``DataFrame`` where each column is the same extension dtyep (:issue:``)
 - Bug in :func:`merge_asof` merging on a tz-aware ``left_index`` and ``right_on`` a tz-aware column (:issue:`29864`)
 -
 

pandas/core/generic.py

@@ -721,12 +721,37 @@ def transpose(self, *args, **kwargs):
         new_axes = self._construct_axes_dict_from(
             self, [self._get_axis(x) for x in axes_names]
         )
-        new_values = self.values.transpose(axes_numbers)
-        if kwargs.pop("copy", None) or (len(args) and args[-1]):
-            new_values = new_values.copy()
+
+        if (
+            self._is_homogeneous_type
+            and len(self._data.blocks)
+            and is_extension_array_dtype(self._data.blocks[0].dtype)
+        ):
+            kwargs.pop("copy", None)  # by definition, we're copying
+            dtype = self._data.blocks[0].dtype
+            arr_type = dtype.construct_array_type()
+
+            # Slow, but unavoidable with 1D EAs.
+            new_values = []
+            for i in range(len(self)):
+                new_values.append(
+                    arr_type._from_sequence(
+                        [block.values[i] for block in self._data.blocks], dtype=dtype
+                    )
+                )
+            columns = new_axes.pop("columns")
+            new_values = dict(zip(columns, new_values))
+            result = self._constructor(new_values, **new_axes)
+
+        else:
+            new_values = self.values.transpose(axes_numbers)
+            if kwargs.pop("copy", None) or (len(args) and args[-1]):
+                new_values = new_values.copy()
+
+            result = self._constructor(new_values, **new_axes)
 
         nv.validate_transpose(tuple(), kwargs)
-        return self._constructor(new_values, **new_axes).__finalize__(self)
+        return result.__finalize__(self)
 
     def swapaxes(self, axis1, axis2, copy=True):
         """

pandas/tests/extension/base/reshaping.py

@@ -295,3 +295,17 @@ def test_ravel(self, data):
         # Check that we have a view, not a copy
         result[0] = result[1]
         assert data[0] == data[1]
+
+    def test_transpose(self, data):
+        df = pd.DataFrame({"A": data[:4], "B": data[:4]}, index=["a", "b", "c", "d"])
+        result = df.T
+        expected = pd.DataFrame(
+            {
+                "a": type(data)._from_sequence([data[0]] * 2, dtype=data.dtype),
+                "b": type(data)._from_sequence([data[1]] * 2, dtype=data.dtype),
+                "c": type(data)._from_sequence([data[2]] * 2, dtype=data.dtype),
+                "d": type(data)._from_sequence([data[3]] * 2, dtype=data.dtype),
+            },
+            index=["A", "B"],
+        )
+        self.assert_frame_equal(result, expected)

pandas/tests/extension/test_numpy.py

@@ -330,6 +330,10 @@ def test_merge_on_extension_array_duplicates(self, data):
         # Fails creating expected
         super().test_merge_on_extension_array_duplicates(data)
 
+    @skip_nested
+    def test_transpose(self, data):
+        super().test_transpose(data)
+
 
 class TestSetitem(BaseNumPyTests, base.BaseSetitemTests):
     @skip_nested