class_docstr: Check if identifiers (Index/Date) can be used to predict the label.
  
  Parameters
  ----------
  ppscore_params : any , default: None
      dictionary containing params to pass to ppscore predictor
  n_samples : int , default: 1_000_000
      number of samples to use for this check.
  random_state : int, default: 42
      random seed for all check internals.
docstr: Add condition - require columns' pps to be less or equal to threshold.
  
  Parameters
  ----------
  max_pps : float , default: 0
      Maximum allowed string length outliers ratio.
docstr_tok: ["Add","condition","-","require","columns","'","pps","to","be","less","or","equal","to","threshold",".","Parameters","--","--","--","--","--","max_pps",":","float",",","default",":","0","Maximum","allowed","string","length","outliers","ratio","."]
code: def add_condition_pps_less_or_equal(self, max_pps: float = 0):
      """Add condition - require columns' pps to be less or equal to threshold.
  
      Parameters
      ----------
      max_pps : float , default: 0
          Maximum allowed string length outliers ratio.
      """
  
      def compare_pps(result: Dict):
          not_passing_columns = {
              k: format_number(score)
              for k, score in result.items()
              if score > max_pps
          }
          if not_passing_columns:
              return ConditionResult(
                  ConditionCategory.FAIL,
                  f"Found {len(not_passing_columns)} out of {len(result)} columns with PPS above"
                  f" threshold: {not_passing_columns}",
              )
          else:
              return ConditionResult(
                  ConditionCategory.PASS,
                  get_condition_passed_message(result),
              )
  
      return self.add_condition(
          f"Identifier columns PPS is less or equal to {format_number(max_pps)}",
          compare_pps,
      )
  
file_path: deepchecks/deepchecks/tabular/checks/data_integrity/identifier_label_correlation.py
imports: from typing import Dict
  import pandas
  import plotly.express
  import deepchecks.ppscore
  from deepchecks.core import CheckResult, ConditionCategory, ConditionResult
  from deepchecks.core.errors import DatasetValidationError
  from deepchecks.tabular import Context, SingleDatasetCheck
  from deepchecks.tabular.dataset import _get_dataset_docs_tag
  from deepchecks.tabular.utils.messages import get_condition_passed_message
  from deepchecks.tabular.utils.task_type import TaskType
  from deepchecks.utils.strings import format_number
label_desc: Use image node_id 3 for calling the IdentifierLabelCorrelation obj's underlying member method code with example usage: obj.add_condition_pps_less_or_equal(max_pps) and returns: self, ConditionResult, ConditionResult