Simplify PintArray.map; CI and CHANGES updates

Simplify PintArray.map to let `pandas.core.algorithms.map_array` do the mapping and we just clean up the PintArray details if necessary.

Pandas 2.1.0rc0 added to CI

Updated CHANGES

Signed-off-by: Michael Tiemann <[email protected]>

Author: MichaelTiemannOSC

.github/workflows/ci.yml

@@ -8,7 +8,7 @@ jobs:
       matrix:
         python-version: [3.9, "3.10", "3.11"]
         numpy: ["numpy>=1.20.3,<2.0.0"]
-        pandas: ["pandas==2.0.2", ]
+        pandas: ["pandas==2.0.2", "pandas==2.1.0rc0" ]
         pint: ["pint>=0.21.1", "pint==0.22"]
 
     runs-on: ubuntu-latest

CHANGES

@@ -5,6 +5,7 @@ pint-pandas Changelog
 ----------------
 
 <<<<<<< HEAD
+- Support for Pandas version 2.1.0 (including dtype-preserving `PintArray.map`) #196
 - Support for <NA> values in columns with integer magnitudes
 - Support for magnitudes of any type, such as complex128 or tuples #146
 - Support for pandas 2.0, allowing `.cumsum, .cummax, .cummin` methods for `Series` and `DataFrame`. #186

pint_pandas/pint_array.py

@@ -844,28 +844,17 @@ def map(self, mapper, na_action=None):
         If mapper is a function, operate on the magnitudes of the array and
 
         """
-        if callable(mapper) and len(self):
-            from pandas._libs import lib
-
-            # This converts PintArray into array of Quantities
-            values = self.astype(object, copy=False)
-            # Using _from_sequence allows for possibility that mapper changes units
-            if na_action is None:
-                arr = lib.map_infer(values, mapper, convert=True)
-            else:
-                arr = lib.map_infer_mask(
-                    values, mapper, mask=pd.isna(values).view(np.uint8), convert=True
-                )
-            master_scalar = None
-            try:
-                master_scalar = next(i for i in arr if hasattr(i, "units"))
-            except StopIteration:
-                # JSON mapper formatting Qs as str don't create PintArrays
-                # ...and that's OK.  Caller will get array of values
-                return arr
-            return PintArray._from_sequence(arr, PintType(master_scalar.units))
-        else:
-            return super().map(mapper, na_action=na_action)
+        from pandas.core.algorithms import map_array
+
+        arr = map_array(self, mapper, na_action)
+        master_scalar = None
+        try:
+            master_scalar = next(i for i in arr if hasattr(i, "units"))
+        except StopIteration:
+            # JSON mapper formatting Qs as str don't create PintArrays
+            # ...and that's OK.  Caller will get array of values
+            return arr
+        return PintArray._from_sequence(arr, PintType(master_scalar.units))
 
     def _reduce(self, name, *, skipna: bool = True, keepdims: bool = False, **kwds):
         """