class_docstr: An ExtensionDtype to hold a single size of floating dtype.
  
  These specific implementations are subclasses of the non-public
  FloatingDtype. For example we have Float32Dtype to represent float32.
  
  The attributes name & type are set when these subclasses are created.
class_docstr_tok: ["An","ExtensionDtype","to","hold","a","single","size","of","floating","dtype",".","These","specific","implementations","are","subclasses","of","the","non-public","FloatingDtype",".","For","example","we","have","Float32Dtype","to","represent","float32",".","The","attributes","name","&","type","are","set","when","these","subclasses","are","created","."]
docstr: Return the array type associated with this dtype.
  
  Returns
  -------
  type
docstr_tok: ["Return","the","array","type","associated","with","this","dtype",".","Returns","--","--","--","-","type"]
code: def construct_array_type(cls) -> type[FloatingArray]:
      """
      Return the array type associated with this dtype.
  
      Returns
      -------
      type
      """
      return FloatingArray
  
file_path: pandas/pandas/core/arrays/floating.py
imports: from __future__ import annotations
  from typing import ClassVar
  import numpy
  from pandas.core.dtypes.base import register_extension_dtype
  from pandas.core.dtypes.common import is_float_dtype
  from pandas.core.arrays.numeric import NumericArray, NumericDtype
label_desc: Use image node_id 1 for calling the FloatingDtype obj's underlying member method code with example usage: obj.construct_array_type(cls) and returns: FloatingArray