class_docstr: Estimator of the error from DP pipeline from DatasetHistograms.
  
  The recommended way to create this object is to use create_error_estimator.
  It works only for COUNT and PRIVACY_ID_COUNT.
  
  Partition selection error is not implemented yet. Now only contribution
  bounding and noise error are taken into consideration.
docstr: Computes ratio
docstr_tok: ["Computes","ratio"]
code: def get_ratio_dropped_l0(self, l0_bound: int) -> float:
      """Computes ratio"""
      return self._get_ratio_dropped(self._l0_ratios_dropped, l0_bound)
  
file_path: pipelinedp/pipeline_dp/dataset_histograms/histogram_error_estimator.py
imports: import pipeline_dp
  from pipeline_dp.dataset_histograms import histograms
  from typing import Optional, Sequence, Tuple
  import math
  import bisect
label_desc: Use image node_id 3 for calling the CountErrorEstimator obj's underlying member method code with example usage: obj.get_ratio_dropped_l0(l0_bound) and returns: self