BUG: Bug in .resample() and .groupby() when aggregating on integers

closes #16361

Author: jreback

doc/source/whatsnew/v0.20.2.txt

@@ -88,6 +88,7 @@ Groupby/Resample/Rolling
 
 - Bug creating datetime rolling window on an empty DataFrame (:issue:`15819`)
 - Bug in ``rolling.cov()`` with offset window (:issue:`16058`)
+- Bug in ``.resample()`` and ``.groupby()`` when aggregating on integers (:issue:`16361`)
 
 
 Sparse

pandas/core/groupby.py

@@ -3337,13 +3337,15 @@ def _cython_agg_blocks(self, how, alt=None, numeric_only=True):
                 obj = self.obj[data.items[locs]]
                 s = groupby(obj, self.grouper)
                 result = s.aggregate(lambda x: alt(x, axis=self.axis))
-                result = result._data.blocks[0]
+                newb = result._data.blocks[0]
 
-            # see if we can cast the block back to the original dtype
-            result = block._try_coerce_and_cast_result(result)
+            finally:
+
+                # see if we can cast the block back to the original dtype
+                result = block._try_coerce_and_cast_result(result)
+                newb = block.make_block(result)
 
             new_items.append(locs)
-            newb = block.make_block_same_class(result)
             new_blocks.append(newb)
 
         if len(new_blocks) == 0:

pandas/tests/test_resample.py

@@ -1672,6 +1672,28 @@ def test_resample_dtype_preservation(self):
         result = df.groupby('group').resample('1D').ffill()
         assert result.val.dtype == np.int32
 
+    def test_resample_dtype_coerceion(self):
+
+        pytest.importorskip('scipy')
+
+        # GH 16361
+        df = {"a": [1, 3, 1, 4]}
+        df = pd.DataFrame(
+            df, index=pd.date_range("2017-01-01", "2017-01-04"))
+
+        expected = (df.astype("float64")
+                    .resample("H")
+                    .mean()
+                    ["a"]
+                    .interpolate("cubic")
+                    )
+
+        result = df.resample("H")["a"].mean().interpolate("cubic")
+        tm.assert_series_equal(result, expected)
+
+        result = df.resample("H").mean()["a"].interpolate("cubic")
+        tm.assert_series_equal(result, expected)
+
     def test_weekly_resample_buglet(self):
         # #1327
         rng = date_range('1/1/2000', freq='B', periods=20)