class_docstr: Manages issues related to null/missing values in the rows of features.
  
  Parameters
  ----------
  datalab :
      The Datalab instance that this issue manager searches for issues in.
class_docstr_tok: ["Manages","issues","related","to","null\/missing","values","in","the","rows","of","features",".","Parameters","--","--","--","--","--","datalab",":","The","Datalab","instance","that","this","issue","manager","searches","for","issues","in","."]
code: def find_issues(
      self,
      features: Optional[npt.NDArray] = None,
      **kwargs,
  ) -> None:
      if features is None:
          raise ValueError(
              "features must be provided to check for null values."
          )
      is_null_issue, scores, null_tracker = self._calculate_null_issues(
          features=features
      )
  
      self.issues = pd.DataFrame(
          {
              f"is_{self.issue_name}_issue": is_null_issue,
              self.issue_score_key: scores,
          },
      )
  
      self.summary = self.make_summary(score=scores.mean())
      self.info = self.collect_info(null_tracker)
  
file_path: cleanlab/cleanlab/datalab/internal/issue_manager/null.py
imports: from __future__ import annotations
  from collections import Counter
  from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, List
  import numpy
  import pandas
  from numpy import ndarray
  from cleanlab.datalab.internal.issue_manager import IssueManager
label_desc: Use image node_id 2 for calling the NullIssueManager obj's underlying member method code with example usage: obj.find_issues(features) without return types