IsSingleValue

class IsSingleValue

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

Parameters

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.

__init__(columns: Optional[Union[Hashable, List[Hashable]]] = None, ignore_columns: Optional[Union[Hashable, List[Hashable]]] = None, ignore_nan: bool = True, **kwargs)

__new__(*args, **kwargs)

Methods

IsSingleValue.add_condition(name, ...)	Add new condition function to the check.
IsSingleValue.add_condition_not_single_value()	Add condition - no column contains only a single value.
IsSingleValue.clean_conditions()	Remove all conditions from this check instance.
IsSingleValue.conditions_decision(result)	Run conditions on given result.
IsSingleValue.config()	Return check configuration (conditions' configuration not yet supported).
IsSingleValue.from_config(conf)	Return check object from a CheckConfig object.
IsSingleValue.metadata([with_doc_link])	Return check metadata.
IsSingleValue.name()	Name of class in split camel case.
IsSingleValue.params([show_defaults])	Return parameters to show when printing the check.
IsSingleValue.remove_condition(index)	Remove given condition by index.
IsSingleValue.run(dataset[, model, ...])	Run check.
IsSingleValue.run_logic(context, dataset_kind)	Run check.

Examples

Is Single Value

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MixedDataTypes.run_logic

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IsSingleValue.add_condition