Fixed errors from PR

pandas/core/algorithms.py

@@ -1624,7 +1624,7 @@ def union_with_duplicates(
     repeats = final_count.reindex(unique_vals).values
     return np.repeat(unique_vals, repeats)
 
-
+import pandas as pd
 def map_array(
     arr: ArrayLike,
     mapper,
@@ -1698,7 +1698,7 @@ def map_array(
     # we must convert to python types
     #values = arr.astype(object, copy=False)
 
-    if is_integer_dtype(arr) and is_nullable_dtype(arr.dtype):
+    if is_integer_dtype(arr) and is_nullable(arr.dtype):
         def mapper_check(x):
             if x is None:
                 return pd.NA

pandas/core/apply.py

@@ -1446,7 +1446,7 @@ def apply_compat(self):
         except (ValueError, AttributeError, TypeError):
             result = obj.apply(func, by_row=False)
         return result
-
+import pandas as pd
     def apply_standard(self) -> DataFrame | Series:
         # caller is responsible for ensuring that f is Callable
         func = cast(Callable, self.func)
@@ -1460,7 +1460,8 @@ def apply_standard(self) -> DataFrame | Series:
 
         #Check if type is integer and nullable, return pd.NA for None values and
         #normal func for other values
-        if pd.api.types.is_integer_dtype(obj) and pd.api.types.is_nullable_dtype(obj.dtype):
+        if pd.api.types.is_integer_dtype(obj) and 
+        pd.api.types.is_nullable(obj.dtype):
             def wrapped_func(x):
                 if x is None:
                     return pd.NA

pandas/core/series.py

@@ -4417,7 +4417,8 @@ def map_check(val):
             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__(
+            return self._constructor(new_values, index=self.index, copy=False)
+            .__finalize__(
                 self, method="map"
                 )
 
@@ -4619,16 +4620,16 @@ def apply(
         Helsinki    2.484907
         dtype: float64
         """
-        # check if dtype is nullable integer 
+        # 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
+            def apply_check(val):
+                if val is None:
+                    return pd.NA
+                return val
         self = [apply_check(x) for x in self]
 
-        #proceed with usual apply method 
+        #proceed with usual apply method
         return SeriesApply(
             self,
             func,