Add deprecation to all subclasses of map for signature consistency

Author: datapythonista

pandas/core/arrays/arrow/array.py

@@ -1477,11 +1477,18 @@ def to_numpy(
             result[~mask] = data[~mask]._pa_array.to_numpy()
         return result
 
-    def map(self, mapper, skipna: bool = False):
+    def map(
+        self,
+        mapper,
+        na_action: Literal["ignore"] | None | lib.NoDefault = lib.no_default,
+        skipna: bool = False,
+    ):
         if is_numeric_dtype(self.dtype):
-            return map_array(self.to_numpy(), mapper, skipna=skipna)
+            return map_array(
+                self.to_numpy(), mapper, na_action=na_action, skipna=skipna
+            )
         else:
-            return super().map(mapper, skipna=skipna)
+            return super().map(mapper, na_action=na_action, skipna=skipna)
 
     @doc(ExtensionArray.duplicated)
     def duplicated(

pandas/core/arrays/categorical.py

@@ -10,6 +10,7 @@
     cast,
     overload,
 )
+import warnings
 
 import numpy as np
 
@@ -22,6 +23,7 @@
 )
 from pandas._libs.arrays import NDArrayBacked
 from pandas.compat.numpy import function as nv
+from pandas.util._exceptions import find_stack_level
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import (
@@ -1497,6 +1499,7 @@ def remove_unused_categories(self) -> Self:
     def map(
         self,
         mapper,
+        na_action: Literal["ignore"] | None | lib.NoDefault = lib.no_default,
         skipna: bool = False,
     ):
         """
@@ -1515,6 +1518,11 @@ def map(
         ----------
         mapper : function, dict, or Series
             Mapping correspondence.
+        na_action : {None, 'ignore'}, default None
+            If 'ignore', propagate NaN values, without passing them to func.
+
+            .. deprecated:: 3.0.0
+                Use ``skipna`` instead.
         skipna : bool, default False
             If ``True``, propagate NA values, without passing them to the
             mapping correspondence.
@@ -1572,6 +1580,21 @@ def map(
         """
         assert callable(mapper) or is_dict_like(mapper)
 
+        if na_action != lib.no_default:
+            warnings.warn(
+                "The ``na_action`` parameter has been deprecated and it will be "
+                "removed in a future version of pandas. Use ``skipna`` instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+            if na_action == "ignore":
+                skipna = True
+            elif na_action not in (None, "ignore"):
+                raise ValueError(
+                    "na_action must either be 'ignore' or None, "
+                    f"{na_action!r} was passed"
+                )
+
         new_categories = self.categories.map(mapper)
 
         has_nans = np.any(self._codes == -1)

pandas/core/arrays/datetimelike.py

@@ -743,10 +743,15 @@ def _unbox(self, other) -> np.int64 | np.datetime64 | np.timedelta64 | np.ndarra
     #  pandas assumes they're there.
 
     @ravel_compat
-    def map(self, mapper, skipna: bool = False):
+    def map(
+        self,
+        mapper,
+        na_action: Literal["ignore"] | None | lib.NoDefault = lib.no_default,
+        skipna: bool = False,
+    ):
         from pandas import Index
 
-        result = map_array(self, mapper, skipna=skipna)
+        result = map_array(self, mapper, na_action=na_action, skipna=skipna)
         result = Index(result)
 
         if isinstance(result, ABCMultiIndex):

pandas/core/arrays/masked.py

@@ -1324,8 +1324,13 @@ def max(self, *, skipna: bool = True, axis: AxisInt | None = 0, **kwargs):
         )
         return self._wrap_reduction_result("max", result, skipna=skipna, axis=axis)
 
-    def map(self, mapper, skipna: bool = False):
-        return map_array(self.to_numpy(), mapper, skipna=skipna)
+    def map(
+        self,
+        mapper,
+        na_action: Literal["ignore"] | None | lib.NoDefault = lib.no_default,
+        skipna: bool = False,
+    ):
+        return map_array(self.to_numpy(), mapper, na_action=na_action, skipna=skipna)
 
     @overload
     def any(

pandas/core/arrays/sparse/array.py

@@ -1309,14 +1309,24 @@ def astype(self, dtype: AstypeArg | None = None, copy: bool = True):
 
         return self._simple_new(sp_values, self.sp_index, dtype)
 
-    def map(self, mapper, skipna: bool = False) -> Self:
+    def map(
+        self,
+        mapper,
+        na_action: Literal["ignore"] | None | lib.NoDefault = lib.no_default,
+        skipna: bool = False,
+    ) -> Self:
         """
         Map categories using an input mapping or function.
 
         Parameters
         ----------
         mapper : dict, Series, callable
             The correspondence from old values to new.
+        na_action : {None, 'ignore'}, default None
+            If 'ignore', propagate NaN values, without passing them to func.
+
+            .. deprecated:: 3.0.0
+                Use ``skipna`` instead.
         skipna : bool, default False
             If ``True``, propagate NA values, without passing them to the
             mapping correspondence.
@@ -1349,6 +1359,21 @@ def map(self, mapper, skipna: bool = False) -> Self:
         IntIndex
         Indices: array([1, 2], dtype=int32)
         """
+        if na_action != lib.no_default:
+            warnings.warn(
+                "The ``na_action`` parameter has been deprecated and it will be "
+                "removed in a future version of pandas. Use ``skipna`` instead.",
+                FutureWarning,
+                stacklevel=find_stack_level(),
+            )
+            if na_action == "ignore":
+                skipna = True
+            elif na_action not in (None, "ignore"):
+                raise ValueError(
+                    "na_action must either be 'ignore' or None, "
+                    f"{na_action!r} was passed"
+                )
+
         is_map = isinstance(mapper, (abc.Mapping, ABCSeries))
 
         fill_val = self.fill_value