ENH: infer_objects copy kwd (#50096)

* ENH: infer_objects copy kwd

* GH ref

Author: jbrockmendel

doc/source/whatsnew/v2.0.0.rst

@@ -84,6 +84,7 @@ Other enhancements
 - :meth:`DataFrame.to_json` now supports a ``mode`` keyword with supported inputs 'w' and 'a'. Defaulting to 'w', 'a' can be used when lines=True and orient='records' to append record oriented json lines to an existing json file. (:issue:`35849`)
 - Added ``name`` parameter to :meth:`IntervalIndex.from_breaks`, :meth:`IntervalIndex.from_arrays` and :meth:`IntervalIndex.from_tuples` (:issue:`48911`)
 - Added :meth:`Index.infer_objects` analogous to :meth:`Series.infer_objects` (:issue:`50034`)
+- Added ``copy`` parameter to :meth:`Series.infer_objects` and :meth:`DataFrame.infer_objects`, passing ``False`` will avoid making copies for series or columns that are already non-object or where no better dtype can be inferred (:issue:`50096`)
 - :meth:`DataFrame.plot.hist` now recognizes ``xlabel`` and ``ylabel`` arguments (:issue:`49793`)
 -
 

pandas/core/generic.py

@@ -6316,7 +6316,7 @@ def __deepcopy__(self: NDFrameT, memo=None) -> NDFrameT:
         return self.copy(deep=True)
 
     @final
-    def infer_objects(self: NDFrameT) -> NDFrameT:
+    def infer_objects(self: NDFrameT, copy: bool_t = True) -> NDFrameT:
         """
         Attempt to infer better dtypes for object columns.
 
@@ -6325,6 +6325,12 @@ def infer_objects(self: NDFrameT) -> NDFrameT:
         columns unchanged. The inference rules are the
         same as during normal Series/DataFrame construction.
 
+        Parameters
+        ----------
+        copy : bool, default True
+            Whether to make a copy for non-object or non-inferrable columns
+            or Series.
+
         Returns
         -------
         converted : same type as input object
@@ -6354,7 +6360,7 @@ def infer_objects(self: NDFrameT) -> NDFrameT:
         A    int64
         dtype: object
         """
-        new_mgr = self._mgr.convert()
+        new_mgr = self._mgr.convert(copy=copy)
         return self._constructor(new_mgr).__finalize__(self, method="infer_objects")
 
     @final

pandas/core/internals/array_manager.py

@@ -374,19 +374,22 @@ def fillna(self: T, value, limit, inplace: bool, downcast) -> T:
     def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
         return self.apply(astype_array_safe, dtype=dtype, copy=copy, errors=errors)
 
-    def convert(self: T) -> T:
+    def convert(self: T, copy: bool) -> T:
         def _convert(arr):
             if is_object_dtype(arr.dtype):
                 # extract PandasArray for tests that patch PandasArray._typ
                 arr = np.asarray(arr)
-                return lib.maybe_convert_objects(
+                result = lib.maybe_convert_objects(
                     arr,
                     convert_datetime=True,
                     convert_timedelta=True,
                     convert_period=True,
                 )
+                if result is arr and copy:
+                    return arr.copy()
+                return result
             else:
-                return arr.copy()
+                return arr.copy() if copy else arr
 
         return self.apply(_convert)
 

pandas/core/internals/blocks.py

@@ -1981,6 +1981,8 @@ def convert(
             convert_timedelta=True,
             convert_period=True,
         )
+        if copy and res_values is values:
+            res_values = values.copy()
         res_values = ensure_block_shape(res_values, self.ndim)
         return [self.make_block(res_values)]
 

pandas/core/internals/managers.py

@@ -441,10 +441,10 @@ def fillna(self: T, value, limit, inplace: bool, downcast) -> T:
     def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
         return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
 
-    def convert(self: T) -> T:
+    def convert(self: T, copy: bool) -> T:
         return self.apply(
             "convert",
-            copy=True,
+            copy=copy,
         )
 
     def replace(self: T, to_replace, value, inplace: bool) -> T:

pandas/tests/internals/test_internals.py

@@ -591,15 +591,15 @@ def _compare(old_mgr, new_mgr):
 
         # noops
         mgr = create_mgr("f: i8; g: f8")
-        new_mgr = mgr.convert()
+        new_mgr = mgr.convert(copy=True)
         _compare(mgr, new_mgr)
 
         # convert
         mgr = create_mgr("a,b,foo: object; f: i8; g: f8")
         mgr.iset(0, np.array(["1"] * N, dtype=np.object_))
         mgr.iset(1, np.array(["2."] * N, dtype=np.object_))
         mgr.iset(2, np.array(["foo."] * N, dtype=np.object_))
-        new_mgr = mgr.convert()
+        new_mgr = mgr.convert(copy=True)
         assert new_mgr.iget(0).dtype == np.object_
         assert new_mgr.iget(1).dtype == np.object_
         assert new_mgr.iget(2).dtype == np.object_
@@ -612,7 +612,7 @@ def _compare(old_mgr, new_mgr):
         mgr.iset(0, np.array(["1"] * N, dtype=np.object_))
         mgr.iset(1, np.array(["2."] * N, dtype=np.object_))
         mgr.iset(2, np.array(["foo."] * N, dtype=np.object_))
-        new_mgr = mgr.convert()
+        new_mgr = mgr.convert(copy=True)
         assert new_mgr.iget(0).dtype == np.object_
         assert new_mgr.iget(1).dtype == np.object_
         assert new_mgr.iget(2).dtype == np.object_

pandas/tests/series/methods/test_infer_objects.py

@@ -4,6 +4,19 @@
 
 
 class TestInferObjects:
+    def test_copy(self, index_or_series):
+        # GH#50096
+        # case where we don't need to do inference because it is already non-object
+        obj = index_or_series(np.array([1, 2, 3], dtype="int64"))
+
+        result = obj.infer_objects(copy=False)
+        assert tm.shares_memory(result, obj)
+
+        # case where we try to do inference but can't do better than object
+        obj2 = index_or_series(np.array(["foo", 2], dtype=object))
+        result2 = obj2.infer_objects(copy=False)
+        assert tm.shares_memory(result2, obj2)
+
     def test_infer_objects_series(self, index_or_series):
         # GH#11221
         actual = index_or_series(np.array([1, 2, 3], dtype="O")).infer_objects()