To numeric

doc/source/whatsnew/v1.1.0.rst

@@ -88,6 +88,7 @@ Other enhancements
 - :class:`Series.str` now has a `fullmatch` method that matches a regular expression against the entire string in each row of the series, similar to `re.fullmatch` (:issue:`32806`).
 - :meth:`DataFrame.sample` will now also allow array-like and BitGenerator objects to be passed to ``random_state`` as seeds (:issue:`32503`)
 - :meth:`MultiIndex.union` will now raise `RuntimeWarning` if the object inside are unsortable, pass `sort=False` to suppress this warning (:issue:`33015`)
+- :func:`to_numeric` will now support downcasting of nullable dtypes.
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/dtypes/cast.py

@@ -143,9 +143,7 @@ def maybe_downcast_to_dtype(result, dtype):
 
             else:
                 dtype = "object"
-
         dtype = np.dtype(dtype)
-
     converted = maybe_downcast_numeric(result, dtype, do_round)
     if converted is not result:
         return converted
@@ -180,7 +178,8 @@ def maybe_downcast_to_dtype(result, dtype):
 
 def maybe_downcast_numeric(result, dtype, do_round: bool = False):
     """
-    Subset of maybe_downcast_to_dtype restricted to numeric dtypes.
+    Subset of maybe_downcast_to_dtype restricted to numeric and
+    nullable dtypes.
 
     Parameters
     ----------
@@ -210,9 +209,7 @@ def trans(x):
         # don't allow upcasts here (except if empty)
         if result.dtype.itemsize <= dtype.itemsize and result.size:
             return result
-
     if is_bool_dtype(dtype) or is_integer_dtype(dtype):
-
         if not result.size:
             # if we don't have any elements, just astype it
             return trans(result).astype(dtype)
@@ -239,7 +236,9 @@ def trans(x):
                 if (new_result == result).all():
                     return new_result
             else:
-                if np.allclose(new_result, result, rtol=0):
+                # np.allclose raises TypeError on extension arrays
+                nd_result = np.array(result).astype(result[0].dtype)
+                if np.allclose(new_result, nd_result, rtol=0):
                     return new_result
 
     elif (

pandas/core/tools/numeric.py

@@ -159,7 +159,6 @@ def to_numeric(arg, errors="raise", downcast=None):
     # to a numerical dtype and if a downcast method has been specified
     if downcast is not None and is_numeric_dtype(values):
         typecodes = None
-
         if downcast in ("integer", "signed"):
             typecodes = np.typecodes["Integer"]
         elif downcast == "unsigned" and (not len(values) or np.min(values) >= 0):

pandas/tests/tools/test_to_numeric.py

@@ -649,3 +649,14 @@ def test_failure_to_convert_uint64_string_to_NaN():
     ser = Series([32, 64, np.nan])
     result = to_numeric(pd.Series(["32", "64", "uint64"]), errors="coerce")
     tm.assert_series_equal(result, ser)
+
+
+def test_support_downcast_of_nullable_dtypes():
+    # GH 33013
+    try:
+        pd.to_numeric(pd.Series([1, 2, 3], dtype="Int32"), downcast="integer")
+        pd.to_numeric(pd.Series([1, 2, 3], dtype="Int64"), downcast="integer")
+        pd.to_numeric(pd.Series([1, 2], dtype="Int32"), downcast="signed")
+        pd.to_numeric(pd.Series([1, 2, 3], dtype="Int32"), downcast="float")
+    except TypeError:
+        pytest.fail("TypeError raised.")