added dtype check for series apply and map

Author: Gnot727

pandas/core/algorithms.py

@@ -17,6 +17,7 @@
 
 import numpy as np
 
+import pandas as pd
 from pandas._libs import (
     algos,
     hashtable as htable,
@@ -1648,9 +1649,15 @@ def map_array(
         a MultiIndex will be returned.
     """
     if na_action not in (None, "ignore"):
-        msg = f"na_action must either be 'ignore' or None, {na_action} was passed"
+        msg = f"na_acti(on must either be 'ignore' or None, {na_action} was passed"
         raise ValueError(msg)
 
+    check = pd.isna(arr)
+    
+    def apply_map(x):
+        if na_action == "ignore" and pd.isna(x):
+            return x
+        
     # we can fastpath dict/Series to an efficient map
     # as we know that we are not going to have to yield
     # python types

pandas/core/apply.py

@@ -14,6 +14,7 @@
 )
 
 import numpy as np
+from pandas.core.dtypes.missing import isna
 
 from pandas._libs.internals import BlockValuesRefs
 from pandas._typing import (
@@ -1389,7 +1390,8 @@ def __init__(
 
     def apply(self) -> DataFrame | Series:
         obj = self.obj
-
+        
+        
         if len(obj) == 0:
             return self.apply_empty_result()
 

pandas/core/series.py

@@ -4404,12 +4404,22 @@ def map(
         3  I am a rabbit
         dtype: object
         """
-        if callable(arg):
-            arg = functools.partial(arg, **kwargs)
-        new_values = self._map_values(arg, na_action=na_action)
-        return self._constructor(new_values, index=self.index, copy=False).__finalize__(
-            self, method="map"
-        )
+        #Check if the dtype is an integer
+        if pd.api.types.is_integer_dtype(self) and pd.api.types.is_nullable(self.dtype):
+            #if dtype is nullable int type, ensure NaN values replaced with pd.NA
+            def map_check(val):
+                if val is None:
+                    return pd.NA
+                return val
+            arg = map_check(arg)
+
+        else:
+            if callable(arg):
+                arg = functools.partial(arg, **kwargs)
+            new_values = self._map_values(arg, na_action=na_action)
+            return self._constructor(new_values, index=self.index, copy=False).__finalize__(
+                self, method="map"
+                )
 
     def _gotitem(self, key, ndim, subset=None) -> Self:
         """
@@ -4609,6 +4619,16 @@ def apply(
         Helsinki    2.484907
         dtype: float64
         """
+        # check if dtype is nullable integer 
+        if pd.api.types.is_integer_dtype(self) and pd.api.types.is_nullable(self.dtype):
+        # def functon to handle NaN as pd.NA
+        def apply_check(val):
+            if val is None:
+                return pd.NA
+            return val
+        func = functools.partial(apply_check,func)
+
+        #proceed with usual apply method 
         return SeriesApply(
             self,
             func,