class PercentOfNulls[source]#

Percent of ‘Null’ values in each column.

columnsUnion[Hashable, List[Hashable]] , default: None

List of columns to check, if none given checks all columns Except ignored ones.

ignore_columnsUnion[Hashable, List[Hashable]] , default: None

List of columns to ignore, if none given checks based on columns variable.

max_features_to_showint , default: 5

maximum features with to show, showing top features based on percent of nulls.

aggregation_method: str, default: ‘max’

argument for the reduce_output functionality, decides how to aggregate the drift scores for a collective score. The collective score value is between 0 and 1 for all methods other than l2_combination. Possible values are: ‘l2_weighted’: L2 norm over the combination of drift scores and feature importance, minus the L2 norm of feature importance alone, specifically, ||FI + DRIFT|| - ||FI||. This method returns a value between 0 and sqrt(n_features). ‘weighted’: Weighted mean based on feature importance, provides a robust estimation on how much the drift will affect the model’s performance. ‘mean’: Mean of all drift scores. ‘max’: Maximum of all the features drift scores. ‘none’: No averaging. Return a dict with a drift score for each feature. ‘top_5’ No averaging. Return a dict with a drift score for top 5 features based on feature importance.

n_samplesint , default: 100_000

number of samples to use for this check.

random_stateint, default: 42

random seed for all check internals.

__init__(columns: Optional[Union[Hashable, List[Hashable]]] = None, ignore_columns: Optional[Union[Hashable, List[Hashable]]] = None, max_features_to_show: int = 5, aggregation_method='max', n_samples: int = 100000, random_state: int = 42, **kwargs)[source]#
__new__(*args, **kwargs)#


PercentOfNulls.add_condition(name, ...)

Add new condition function to the check.


Add condition - percent of null values in each column is not greater than the threshold.


Remove all conditions from this check instance.


Run conditions on given result.


Return check configuration (conditions' configuration not yet supported).


Return an aggregated drift score based on aggregation method defined.

PercentOfNulls.from_config(conf[, ...])

Return check object from a CheckConfig object.

PercentOfNulls.from_json(conf[, version_unmatch])

Deserialize check instance from JSON string.


Return check metadata.

Name of class in split camel case.


Return parameters to show when printing the check.


Return an aggregated drift score based on aggregation method defined.


Remove given condition by index.[, model, ...])

Run check.

PercentOfNulls.run_logic(context, dataset_kind)

Run check logic.


Serialize check instance to JSON string.