don't create a separate method

Author: arw2019

pandas/core/dtypes/common.py

@@ -1231,44 +1231,6 @@ def needs_i8_conversion(arr_or_dtype) -> bool:
     )
 
 
-def np_issubclass_compat(unique_dtype, dtypes_set) -> bool:
-    """
-    Check whether the provided dtype is a subclass of, or has an attribute
-    (e.g. _is_numeric) indiciating it is a subclass of any of the dtypes in
-    dtypes_set.
-
-    Parameters
-    ----------
-    unique_dtype : dtype
-        The dtype to check.
-    dtypes_set : array-like
-        The dtypes to check unique_dtype is a sublass of.
-
-    Returns
-    -------
-    boolean
-        Whether or not the unique_dtype is a subclass of dtype_set.
-
-    Examples
-    --------
-    >>> np_issubclass_compat(pd.Int16Dtype(), [np.bool_, np.float])
-    False
-    >>> np_issubclass_compat(pd.Int16Dtype(), [np.integer])
-    True
-    >>> np_issubclass_compat(pd.BooleanDtype(), [np.bool_])
-    True
-    >>> np_issubclass_compat(pd.Float64Dtype(), [np.float])
-    True
-    >>> np_issubclass_compat(pd.Float64Dtype(), [np.number])
-    True
-    """
-    return issubclass(unique_dtype.type, tuple(dtypes_set)) or (
-        np.number in dtypes_set
-        and hasattr(unique_dtype, "_is_numeric")  # is an extensionarray
-        and unique_dtype._is_numeric
-    )
-
-
 def is_numeric_dtype(arr_or_dtype) -> bool:
     """
     Check whether the provided array or dtype is of a numeric dtype.

pandas/core/frame.py

@@ -114,7 +114,6 @@
     is_object_dtype,
     is_scalar,
     is_sequence,
-    np_issubclass_compat,
     pandas_dtype,
 )
 from pandas.core.dtypes.missing import isna, notna
@@ -3713,7 +3712,14 @@ def extract_unique_dtypes_from_dtypes_set(
             extracted_dtypes = [
                 unique_dtype
                 for unique_dtype in unique_dtypes
-                if np_issubclass_compat(unique_dtype, dtypes_set)
+                if (
+                    issubclass(unique_dtype.type, tuple(dtypes_set))
+                    or (
+                        np.number in dtypes_set
+                        and hasattr(unique_dtype, "_is_numeric")
+                        and unique_dtype._is_numeric
+                    )
+                )
             ]
             return extracted_dtypes