BUG: Preserve column metadata with DataFrame.astype

doc/source/whatsnew/v0.23.0.txt

@@ -954,6 +954,7 @@ Reshaping
 - Bug in :func:`qcut` where datetime and timedelta data with ``NaT`` present raised a ``ValueError`` (:issue:`19768`)
 - Bug in :func:`DataFrame.iterrows`, which would infers strings not compliant to `ISO8601 <https://en.wikipedia.org/wiki/ISO_8601>`_ to datetimes (:issue:`19671`)
 - Bug in :class:`Series` constructor with ``Categorical`` where a ```ValueError`` is not raised when an index of different length is given (:issue:`19342`)
+- Bug in :meth:`DataFrame.astype` where column metadata is lost when converting to categorical or a dictionary of dtypes (:issue:`19920`)
 
 Other
 ^^^^^

pandas/core/generic.py

@@ -4436,17 +4436,21 @@ def astype(self, dtype, copy=True, errors='raise', **kwargs):
                     results.append(col.astype(dtype[col_name], copy=copy))
                 else:
                     results.append(results.append(col.copy() if copy else col))
-            return pd.concat(results, axis=1, copy=False)
 
         elif is_categorical_dtype(dtype) and self.ndim > 1:
             # GH 18099: columnwise conversion to categorical
             results = (self[col].astype(dtype, copy=copy) for col in self)
-            return pd.concat(results, axis=1, copy=False)
 
-        # else, only a single dtype is given
-        new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
-                                     **kwargs)
-        return self._constructor(new_data).__finalize__(self)
+        else:
+            # else, only a single dtype is given
+            new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
+                                         **kwargs)
+            return self._constructor(new_data).__finalize__(self)
+
+        # GH 19920: retain column metadata after concat
+        result = pd.concat(results, axis=1, copy=False)
+        result.columns = self.columns
+        return result
 
     def copy(self, deep=True):
         """

pandas/tests/frame/test_dtypes.py

@@ -649,6 +649,15 @@ def test_astype_categoricaldtype_class_raises(self, cls):
         with tm.assert_raises_regex(TypeError, xpr):
             df['A'].astype(cls)
 
+    @pytest.mark.parametrize('dtype', [
+        {100: 'float64', 200: 'uint64'}, 'category', 'float64'])
+    def test_astype_column_metadata(self, dtype):
+        # GH 19920
+        columns = pd.UInt64Index([100, 200, 300], name='foo')
+        df = DataFrame(np.arange(15).reshape(5, 3), columns=columns)
+        df = df.astype(dtype)
+        tm.assert_index_equal(df.columns, columns)
+
     @pytest.mark.parametrize("dtype", ["M8", "m8"])
     @pytest.mark.parametrize("unit", ['ns', 'us', 'ms', 's', 'h', 'm', 'D'])
     def test_astype_from_datetimelike_to_objectt(self, dtype, unit):