class_docstr: Find new categories in the test set.
  
  Parameters
  ----------
  columns : Union[Hashable, List[Hashable]] , default: None
      Columns to check, if none are given checks all columns except ignored ones.
  ignore_columns : Union[Hashable, List[Hashable]] , default: None
      Columns to ignore, if none given checks based on columns variable.
  max_features_to_show : int , default: 5
      maximum features with new categories to show
  max_new_categories_to_show : int , default: 5
      maximum new categories to show in feature
  aggregation_method: Optional[str], default: 'max'
      {feature_aggregation_method_argument:2*indent}
  n_samples : int , default: 10_000_000
      number of samples to use for this check.
  random_state : int, default: 42
      random seed for all check internals.
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code: def __init__(
      self,
      columns: Union[Hashable, List[Hashable], None] = None,
      ignore_columns: Union[Hashable, List[Hashable], None] = None,
      max_features_to_show: int = 5,
      max_new_categories_to_show: int = 5,
      aggregation_method: Optional[str] = "max",
      n_samples: int = 10_000_000,
      random_state: int = 42,
      **kwargs,
  ):
      super().__init__(**kwargs)
      self.columns = columns
      self.ignore_columns = ignore_columns
      self.max_features_to_show = max_features_to_show
      self.max_new_categories_to_show = max_new_categories_to_show
      self.aggregation_method = aggregation_method
      self.n_samples = n_samples
      self.random_state = random_state
  
file_path: deepchecks/deepchecks/tabular/checks/train_test_validation/new_category_train_test.py
imports: from typing import Dict, List, Optional, Union
  import pandas
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.core.reduce_classes import ReduceFeatureMixin
  from deepchecks.tabular import Context, TrainTestCheck
  from deepchecks.tabular._shared_docs import docstrings
  from deepchecks.tabular.utils.messages import get_condition_passed_message
  from deepchecks.utils.dataframes import select_from_dataframe
  from deepchecks.utils.strings import format_number, format_percent
  from deepchecks.utils.typing import Hashable
label_desc: Use image node_id 1 to create a new NewCategoryTrainTest object from inherited base classes: TrainTestCheck, ReduceFeatureMixin with example: obj = NewCategoryTrainTest(columns, ignore_columns, max_features_to_show, max_new_categories_to_show, aggregation_method, n_samples, random_state)