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","."]
docstr: Calculate and return the impact of null values per column, represented as the proportion
  of rows having null values in each column.
  
  Parameters
  ----------
  null_tracker : np.ndarray
      A boolean array of the same shape as features, where True indicates null/missing entries.
  
  Returns
  -------
  Dict[str, List[float]]
      A dictionary containing the impact per column, with values being a list
      where each element is the percentage of rows having null values in the corresponding column.
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code: def _column_impact(
      null_tracker: np.ndarray,
  ) -> Dict[str, List[float]]:
      """
      Calculate and return the impact of null values per column, represented as the proportion
      of rows having null values in each column.
  
      Parameters
      ----------
      null_tracker : np.ndarray
          A boolean array of the same shape as features, where True indicates null/missing entries.
  
      Returns
      -------
      Dict[str, List[float]]
          A dictionary containing the impact per column, with values being a list
          where each element is the percentage of rows having null values in the corresponding column.
      """
      # Calculate proportion of nulls in each column
      proportion_of_nulls_per_column = null_tracker.mean(axis=0)
  
      # Return result as a dictionary containing a list of proportions
      return {"column_impact": proportion_of_nulls_per_column.tolist()}
  
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 4 for calling the NullIssueManager obj's underlying member method code with example usage: obj._column_impact(null_tracker) and returns: dict