code: def nan_type(x):
      if x is np.nan:
          return "numpy.nan"
      elif x is pd.NA:
          return "pandas.NA"
      elif x is pd.NaT:
          return "pandas.NaT"
      elif isinstance(x, float) and math.isnan(x):
          return "math.nan"
      return str(x)
  
imports: import math
  from typing import Dict, Iterable, List, Optional, Union
  import numpy
  import pandas
  from pandas.api.types import is_categorical_dtype
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.core.reduce_classes import ReduceFeatureMixin
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.tabular._shared_docs import docstrings
  from deepchecks.tabular.utils.feature_importance import N_TOP_MESSAGE
  from deepchecks.tabular.utils.messages import get_condition_passed_message
  from deepchecks.utils.dataframes import select_from_dataframe
  from deepchecks.utils.strings import format_percent, string_baseform
  from deepchecks.utils.typing import Hashable
label_desc: Use image node_id 1 for calling a global function with example usage: nan_type(x) and returns: str, str, str, str, str