null#

Warning

This issue manager isn’t set up for direct Datalab use yet.

Classes:

NullIssueManager(datalab, **_)

Manages issues related to null/missing values in the rows of features.

class cleanlab.datalab.internal.issue_manager.null.NullIssueManager(datalab, **_)[source]#

Manages issues related to null/missing values in the rows of features.

Parameters:: datalab (Datalab) – The Datalab instance that this issue manager searches for issues in.

Attributes:

`description`	Short text that summarizes the type of issues handled by this IssueManager.
`issue_name`	Returns a key that is used to store issue summary results about the assigned Lab.
`verbosity_levels`	A dictionary of verbosity levels and their corresponding dictionaries of report items to print.
`issue_score_key`	Returns a key that is used to store issue score results about the assigned Lab.
`info`
`issues`
`summary`

Methods:

`find_issues`([features])	Finds occurrences of this particular issue in the dataset.
`collect_info`(null_tracker)	Collects data for the info attribute of the Datalab.
`report`(args, *kwargs)	Return a report of issues found by the NullIssueManager.
`make_summary`(score)	Construct a summary dataframe.

description: ClassVar[str]#

Short text that summarizes the type of issues handled by this IssueManager.

issue_name: ClassVar[str] = 'null'#: Returns a key that is used to store issue summary results about the assigned Lab.

verbosity_levels: ClassVar[Dict[int, List[str]]]#

A dictionary of verbosity levels and their corresponding dictionaries of report items to print.

Example

>>> verbosity_levels = {
...     0: [],
...     1: ["some_info_key"],
...     2: ["additional_info_key"],
... }

find_issues(features=None, **kwargs)[source]#

Finds occurrences of this particular issue in the dataset.

Computes the issues and summary dataframes. Calls collect_info to compute the info dict.

collect_info(null_tracker)[source]#: Collects data for the info attribute of the Datalab. :rtype: dict

Note

This method is called by find_issues() after find_issues() has set the issues and summary dataframes as instance attributes.

classmethod report(*args, **kwargs)[source]#

Return a report of issues found by the NullIssueManager.

This method extends the superclass method by identifying and reporting specific issues related to null values in the dataset.

Parameters:

Return type:

str

Returns:

report_str – A string containing the report.