ENH: support na_action in SparseArray.map

doc/source/whatsnew/v2.1.0.rst

@@ -36,6 +36,7 @@ Other enhancements
 - :class:`api.extensions.ExtensionArray` now has a :meth:`~api.extensions.ExtensionArray.map` method (:issue:`51809`)
 - Improve error message when having incompatible columns using :meth:`DataFrame.merge` (:issue:`51861`)
 - Improved error message when creating a DataFrame with empty data (0 rows), no index and an incorrect number of columns. (:issue:`52084`)
+- :meth:`arrays.SparseArray.map` now supports ``na_action`` (:issue:`52096`).
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_210.notable_bug_fixes:
@@ -233,7 +234,7 @@ Reshaping
 
 Sparse
 ^^^^^^
--
+- Bug in :meth:`arrays.SparseArray.map` allowed the fill value to be included in the sparse values (:issue:`52095`)
 -
 
 ExtensionArray

pandas/core/arrays/sparse/array.py

@@ -1305,23 +1305,24 @@ def map(self, mapper, na_action=None) -> Self:
         IntIndex
         Indices: array([1, 2], dtype=int32)
         """
-        if na_action is not None:
-            raise NotImplementedError
+        is_map = isinstance(mapper, (abc.Mapping, ABCSeries))
 
-        # this is used in apply.
-        # We get hit since we're an "is_extension_array_dtype" but regular extension
-        # types are not hit. This may be worth adding to the interface.
-        if isinstance(mapper, ABCSeries):
-            mapper = mapper.to_dict()
+        fill_val = self.fill_value
 
-        if isinstance(mapper, abc.Mapping):
-            fill_value = mapper.get(self.fill_value, self.fill_value)
-            sp_values = [mapper.get(x, None) for x in self.sp_values]
-        else:
-            fill_value = mapper(self.fill_value)
-            sp_values = [mapper(x) for x in self.sp_values]
+        if na_action is None or notna(fill_val):
+            fill_val = mapper.get(fill_val, fill_val) if is_map else mapper(fill_val)
+
+        def func(sp_val):
+            new_sp_val = mapper.get(sp_val, None) if is_map else mapper(sp_val)
+            # check identity and equality because nans are not equal to each other
+            if new_sp_val is fill_val or new_sp_val == fill_val:
+                msg = "fill value in the sparse values not supported"
+                raise ValueError(msg)
+            return new_sp_val
+
+        sp_values = [func(x) for x in self.sp_values]
 
-        return type(self)(sp_values, sparse_index=self.sp_index, fill_value=fill_value)
+        return type(self)(sp_values, sparse_index=self.sp_index, fill_value=fill_val)
 
     def to_dense(self) -> np.ndarray:
         """

pandas/tests/extension/test_sparse.py

@@ -351,14 +351,27 @@ def test_equals(self, data, na_value, as_series, box):
         self._check_unsupported(data)
         super().test_equals(data, na_value, as_series, box)
 
+    @pytest.mark.parametrize(
+        "func, na_action, expected",
+        [
+            (lambda x: x, None, SparseArray([1.0, np.nan])),
+            (lambda x: x, "ignore", SparseArray([1.0, np.nan])),
+            (str, None, SparseArray(["1.0", "nan"], fill_value="nan")),
+            (str, "ignore", SparseArray(["1.0", np.nan])),
+        ],
+    )
+    def test_map(self, func, na_action, expected):
+        # GH52096
+        data = SparseArray([1, np.nan])
+        result = data.map(func, na_action=na_action)
+        self.assert_extension_array_equal(result, expected)
+
     @pytest.mark.parametrize("na_action", [None, "ignore"])
-    def test_map(self, data, na_action):
-        if na_action is not None:
-            with pytest.raises(NotImplementedError, match=""):
-                data.map(lambda x: x, na_action=na_action)
-        else:
-            result = data.map(lambda x: x, na_action=na_action)
-            self.assert_extension_array_equal(result, data)
+    def test_map_raises(self, data, na_action):
+        # GH52096
+        msg = "fill value in the sparse values not supported"
+        with pytest.raises(ValueError, match=msg):
+            data.map(lambda x: np.nan, na_action=na_action)
 
 
 class TestCasting(BaseSparseTests, base.BaseCastingTests):