fix comments

Author: topper-123

pandas/core/indexes/base.py

@@ -2416,12 +2416,13 @@ def _is_multi(self) -> bool:
         """
         return isinstance(self, ABCMultiIndex)
 
+    @final
     @classmethod
     def _is_num_index(cls) -> bool:
         """
-        Whether self is a NumIndex, but not *not* Int64Index, UInt64Index, FloatIndex.
+        Check if this is a NumericIndex, but *not* Int64Index, UInt64Index, FloatIndex.
 
-        Typically used to check if an operation should return NumIndex or plain Index.
+        Used to check if an operation should return NumericIndex or plain Index.
         """
         from pandas.core.indexes.numeric import (
             Float64Index,

pandas/core/indexes/category.py

@@ -293,21 +293,21 @@ def astype(self, dtype, copy: bool = True) -> Index:
 
         dtype = pandas_dtype(dtype)
 
-        cat = self.categories
+        categories = self.categories
         # the super method always returns Int64Index, UInt64Index and Float64Index
         # but if e.g. the categories are a NumIndex with dtype float32, we want to
         # return an index with the same dtype as self.categories.
-        if cat._is_num_index():
-            assert isinstance(cat, NumericIndex)  # mypy complaint fix
+        if categories._is_num_index():
+            assert isinstance(categories, NumericIndex)  # mypy complaint fix
             try:
-                cat._validate_dtype(dtype)
+                categories._validate_dtype(dtype)
             except ValueError:
                 pass
             else:
                 new_values = self._data.astype(dtype, copy=copy)
                 # pass copy=False because any copying has been done in the
                 #  _data.astype call above
-                return type(cat)(new_values, name=self.name, copy=False)
+                return type(categories)(new_values, name=self.name, copy=False)
 
         return super().astype(dtype, copy=copy)
 

pandas/core/indexes/numeric.py

@@ -15,6 +15,7 @@
 from pandas._typing import (
     Dtype,
     DtypeObj,
+    final,
 )
 from pandas.util._decorators import (
     cache_readonly,
@@ -268,6 +269,15 @@ def _assert_safe_casting(cls, data, subarr):
         """
         pass
 
+    @final
+    @cache_readonly
+    def _can_hold_na(self) -> bool:
+        if is_integer_dtype(self.dtype):
+            return False
+        else:
+            return True
+
+    @final
     @property
     def _is_all_dates(self) -> bool:
         """