BUG: Series[object].unstack preserve object dtype

Author: jbrockmendel

pandas/core/reshape/reshape.py

@@ -213,7 +213,9 @@ def get_result(self, values, value_columns, fill_value):
         columns = self.get_new_columns(value_columns)
         index = self.new_index
 
-        return self.constructor(values, index=index, columns=columns)
+        return self.constructor(
+            values, index=index, columns=columns, dtype=values.dtype
+        )
 
     def get_new_values(self, values, fill_value=None):
 

pandas/tests/extension/base/reshaping.py

@@ -3,12 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas.core.dtypes.common import (
-    is_datetime64tz_dtype,
-    is_interval_dtype,
-    is_period_dtype,
-)
-
 import pandas as pd
 from pandas.api.extensions import ExtensionArray
 from pandas.core.internals import ExtensionBlock
@@ -327,17 +321,11 @@ def test_unstack(self, data, index, obj):
             expected = ser.astype(object).unstack(
                 level=level, fill_value=data.dtype.na_value
             )
-            if obj == "series":
-                # TODO: special cases belong in dtype-specific tests
-                if is_datetime64tz_dtype(data.dtype):
-                    assert expected.dtypes.apply(is_datetime64tz_dtype).all()
-                    expected = expected.astype(object)
-                if is_period_dtype(data.dtype):
-                    assert expected.dtypes.apply(is_period_dtype).all()
-                    expected = expected.astype(object)
-                if is_interval_dtype(data.dtype):
-                    assert expected.dtypes.apply(is_interval_dtype).all()
-                    expected = expected.astype(object)
+            if obj == "series" and not isinstance(ser.dtype, pd.SparseDtype):
+                # GH#34457 SparseArray.astype(object) gives Sparse[object]
+                #  instead of np.dtype(object)
+                assert (expected.dtypes == object).all()
+
             result = result.astype(object)
 
             self.assert_frame_equal(result, expected)

pandas/tests/series/methods/test_unstack.py

@@ -10,6 +10,18 @@
 import pandas._testing as tm
 
 
+def test_unstack_preserves_object():
+    mi = MultiIndex.from_product([["bar", "foo"], ["one", "two"]])
+
+    ser = Series(np.arange(4.0), index=mi, dtype=object)
+
+    res1 = ser.unstack()
+    assert (res1.dtypes == object).all()
+
+    res2 = ser.unstack(level=0)
+    assert (res2.dtypes == object).all()
+
+
 def test_unstack():
     index = MultiIndex(
         levels=[["bar", "foo"], ["one", "three", "two"]],