code: def data_for_grouping(dtype):
      if dtype.kind == "f":
          b = 0.1
          a = 0.0
          c = 0.2
      elif dtype.kind == "b":
          b = True
          a = False
          c = b
      else:
          b = 1
          a = 0
          c = 2
  
      na = pd.NA
      return pd.array([b, b, na, na, a, a, b, c], dtype=dtype)
  
imports: import warnings
  import numpy
  import pytest
  from pandas.compat import IS64, is_platform_windows
  from pandas.compat.numpy import np_version_gt2
  from pandas.core.dtypes.common import is_float_dtype, is_signed_integer_dtype, is_unsigned_integer_dtype
  import pandas
  import pandas._testing
  from pandas.core.arrays.boolean import BooleanDtype
  from pandas.core.arrays.floating import Float32Dtype, Float64Dtype
  from pandas.core.arrays.integer import Int8Dtype, Int16Dtype, Int32Dtype, Int64Dtype, UInt8Dtype, UInt16Dtype, UInt32Dtype, UInt64Dtype
  from pandas.tests.extension import base
label_desc: Use image node_id 11 for calling a global function with example usage: data_for_grouping(dtype) and returns: pd