REF: de-duplicate piece of DataFrame._reduce (pandas-dev#29830)

Author: jbrockmendel

pandas/core/frame.py

@@ -7606,6 +7606,23 @@ def _reduce(
         def f(x):
             return op(x, axis=axis, skipna=skipna, **kwds)
 
+        def _get_data(axis_matters):
+            if filter_type is None or filter_type == "numeric":
+                data = self._get_numeric_data()
+            elif filter_type == "bool":
+                if axis_matters:
+                    # GH#25101, GH#24434
+                    data = self._get_bool_data() if axis == 0 else self
+                else:
+                    data = self._get_bool_data()
+            else:  # pragma: no cover
+                msg = (
+                    "Generating numeric_only data with filter_type {f}"
+                    "not supported.".format(f=filter_type)
+                )
+                raise NotImplementedError(msg)
+            return data
+
         if numeric_only is None:
             values = self.values
             try:
@@ -7616,7 +7633,7 @@ def f(x):
                     # TODO: combine with hasattr(result, 'dtype') further down
                     # hard since we don't have `values` down there.
                     result = np.bool_(result)
-            except TypeError as err:
+            except TypeError:
                 # e.g. in nanops trying to convert strs to float
 
                 # try by-column first
@@ -7639,31 +7656,15 @@ def f(x):
                         result = result.iloc[0]
                     return result
 
-                if filter_type is None or filter_type == "numeric":
-                    data = self._get_numeric_data()
-                elif filter_type == "bool":
-                    data = self._get_bool_data()
-                else:  # pragma: no cover
-                    raise NotImplementedError(
-                        "Handling exception with filter_type {f} not"
-                        "implemented.".format(f=filter_type)
-                    ) from err
+                # TODO: why doesnt axis matter here?
+                data = _get_data(axis_matters=False)
                 with np.errstate(all="ignore"):
                     result = f(data.values)
                 labels = data._get_agg_axis(axis)
         else:
             if numeric_only:
-                if filter_type is None or filter_type == "numeric":
-                    data = self._get_numeric_data()
-                elif filter_type == "bool":
-                    # GH 25101, # GH 24434
-                    data = self._get_bool_data() if axis == 0 else self
-                else:  # pragma: no cover
-                    msg = (
-                        "Generating numeric_only data with filter_type {f}"
-                        "not supported.".format(f=filter_type)
-                    )
-                    raise NotImplementedError(msg)
+                data = _get_data(axis_matters=True)
+
                 values = data.values
                 labels = data._get_agg_axis(axis)
             else: