class_docstr: Class that generates a report about the issues stored in a :py:class:`DataIssues` object.
  
  Parameters
  ----------
  data_issues :
      The :py:class:`DataIssues` object containing the issues to report on. This is usually
      generated by the :py:class:`Datalab` class, stored in the :py:attr:`data_issues` attribute,
      and then passed to the :py:class:`Reporter` class to generate a report.
  
  task :
      Specific machine learning task like classification or regression.
  
  verbosity :
      The default verbosity of the report to generate. Each :py:class`IssueManager`
      specifies the available verbosity levels and what additional information
      is included at each level.
  
  include_description :
      Whether to include the description of each issue type in the report. The description
      is included by default, but can be excluded by setting this parameter to ``False``.
  
  Note
  ----
  This class is not intended to be used directly. Instead, use the
  `Datalab.find_issues` method which internally utilizes an IssueFinder instance.
code: def _write_summary(self, summary: pd.DataFrame) -> str:
      statistics = self.data_issues.get_info("statistics")
      num_examples = statistics["num_examples"]
      num_classes = statistics.get(
          "num_classes"
      )  # This may not be required for all types of datasets  in the future (e.g. unlabeled/regression)
  
      dataset_information = (
          f"Dataset Information: num_examples: {num_examples}"
      )
      if num_classes is not None:
          dataset_information += f", num_classes: {num_classes}"
  
      if self.show_summary_score:
          return (
              "Here is a summary of the different kinds of issues found in the data:\n\n"
              + summary.to_string(index=False)
              + "\n\n"
              + "(Note: A lower score indicates a more severe issue across all examples in the dataset.)\n\n"
              + f"{dataset_information}\n\n\n"
          )
  
      return (
          "Here is a summary of the different kinds of issues found in the data:\n\n"
          + summary.drop(columns=["score"]).to_string(index=False)
          + "\n\n"
          + f"{dataset_information}\n\n\n"
      )
  
file_path: cleanlab/cleanlab/datalab/internal/report.py
imports: from typing import TYPE_CHECKING, List
  import pandas
  from cleanlab.datalab.internal.adapter.constants import DEFAULT_CLEANVISION_ISSUES
  from cleanlab.datalab.internal.issue_manager_factory import _IssueManagerFactory
label_desc: Use image node_id 4 for calling the Reporter obj's underlying member method code with example usage: obj._write_summary(summary) and returns: unknown, unknown