class_docstr: Transforms features into isnull flags.
  
  Parameters
  ----------
  null_map : dict, default {'object': ''}
      Map which dictates the values to consider as NaN.
      Keys are the raw types of the features as in self.feature_metadata_in.type_map_raw.
      If a feature's raw type is not present in null_map, np.nan is treated as NaN.
      If a value other than np.nan is specified, np.nan is not considered NaN.
  **kwargs :
      Refer to :class:`AbstractFeatureGenerator` documentation for details on valid key word arguments.
code: def _transform(self, X: DataFrame) -> DataFrame:
      is_nan_features = dict()
      for feature in self.features_in:
          if feature in self._null_feature_map:
              null_val = self._null_feature_map[feature]
              is_nan_features["__nan__." + feature] = (
                  X[feature] == null_val
              ).astype(np.uint8)
          else:
              is_nan_features["__nan__." + feature] = (
                  X[feature].isnull().astype(np.uint8)
              )
      return pd.DataFrame(is_nan_features, index=X.index)
  
file_path: autogluon/features/src/autogluon/features/generators/isnan.py
imports: import logging
  import numpy
  import pandas
  from pandas import DataFrame
  from autogluon.common.features.types import R_OBJECT, S_BOOL
  from .abstract import AbstractFeatureGenerator
label_desc: Use image node_id 3 for calling the IsNanFeatureGenerator obj's underlying member method code with example usage: obj._transform(X) and returns: pd