code: def un_numpy(val):
      """Convert numpy value to native value.
  
      Parameters
      ----------
      val :
          The value to convert.
  
      Returns
      -------
          returns the numpy value in a native type.
      """
      if isinstance(val, np.str_):
          # NOTE:
          # 'np.str_' is instance of the 'np.generic' but
          # 'np.isnan(np.str_())' raises an error with a next message:
          # >> TypeError: ufunc 'isnan' not supported for the input types...)
          #
          # therefore this 'if' statement is needed
          return val.item()
      if isinstance(val, np.generic):
          if np.isnan(val):
              return None
          return val.item()
      if isinstance(val, np.ndarray):
          return val.tolist()
      return val
  
file_path: deepchecks/deepchecks/utils/dataframes.py
imports: import typing
  import numpy
  import pandas
  from pandas.core.dtypes.common import is_float_dtype, is_integer_dtype, is_numeric_dtype
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.utils.type_inference import infer_categorical_features
  from deepchecks.utils.typing import Hashable
  from deepchecks.utils.validation import ensure_hashable_or_mutable_sequence
label_desc: Use image node_id 5 for calling a global function with example usage: un_numpy(val) and returns: val, val, val, val, None