class IsSingleValue[source]#

Check if there are columns which have only a single unique value in all rows.

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

Columns to check, if none are given checks all columns except ignored ones.

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

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

ignore_nanbool, default True

Whether to ignore NaN values in a column when counting the number of unique values.

n_samplesint , default: 10_000_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, ignore_nan: bool = True, n_samples: int = 10000000, random_state: int = 42, **kwargs)[source]#
__new__(*args, **kwargs)#


IsSingleValue.add_condition(name, ...)

Add new condition function to the check.


Add condition - no column contains only a single value.


Remove all conditions from this check instance.


Run conditions on given result.

IsSingleValue.config([include_version, ...])

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

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

Return check object from a CheckConfig object.

IsSingleValue.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.


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

Run check.

IsSingleValue.run_logic(context, dataset_kind)

Run check.

IsSingleValue.to_json([indent, ...])

Serialize check instance to JSON string.