class_docstr: Verify test dataset size comparing it to the train dataset size.
class_docstr_tok: ["Verify","test","dataset","size","comparing","it","to","the","train","dataset","size","."]
docstr: Add condition verifying that size of the test dataset is greater or equal to threshold.
  
  Parameters
  ----------
  value : int , default: 100
      minimal allowed test dataset size.
  
  Returns
  -------
  Self
      current instance of the DatasetsSizeComparison check.
docstr_tok: ["Add","condition","verifying","that","size","of","the","test","dataset","is","greater","or","equal","to","threshold",".","Parameters","--","--","--","--","--","value",":","int",",","default",":","100","minimal","allowed","test","dataset","size",".","Returns","--","--","--","-","Self","current","instance","of","the","DatasetsSizeComparison","check","."]
code: def add_condition_test_size_greater_or_equal(
      self: T, value: int = 100
  ) -> T:
      """Add condition verifying that size of the test dataset is greater or equal to threshold.
  
      Parameters
      ----------
      value : int , default: 100
          minimal allowed test dataset size.
  
      Returns
      -------
      Self
          current instance of the DatasetsSizeComparison check.
      """
  
      def condition(check_result: dict) -> ConditionResult:
          details = (
              f'Test dataset contains {check_result["Test"]} samples'
          )
          category = (
              ConditionCategory.FAIL
              if check_result["Test"] <= value
              else ConditionCategory.PASS
          )
          return ConditionResult(category, details)
  
      return self.add_condition(
          name=f"Test dataset size is greater or equal to {value}",
          condition_func=condition,
      )
  
file_path: deepchecks/deepchecks/tabular/checks/train_test_validation/datasets_size_comparison.py
imports: import typing
  import pandas
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.tabular import Context, TrainTestCheck
  from deepchecks.utils.strings import format_number
label_desc: Use image node_id 2 for calling the DatasetsSizeComparison obj's underlying member method code with example usage: obj.add_condition_test_size_greater_or_equal(value) and returns: self, ConditionResult