great_expectations.expectations.metrics.column_aggregate_metrics.column_median

Module Contents

Classes

ColumnMedian()

MetricProvider Class for Aggregate Mean MetricProvider

class great_expectations.expectations.metrics.column_aggregate_metrics.column_median.ColumnMedian

Bases: great_expectations.expectations.metrics.column_aggregate_metric_provider.ColumnAggregateMetricProvider

MetricProvider Class for Aggregate Mean MetricProvider

metric_name = column.median
_pandas(cls, column, **kwargs)

Pandas Median Implementation

_sqlalchemy(cls, execution_engine: SqlAlchemyExecutionEngine, metric_domain_kwargs: Dict, metric_value_kwargs: Dict, metrics: Dict[Tuple, Any], runtime_configuration: Dict)
_spark(cls, execution_engine: SqlAlchemyExecutionEngine, metric_domain_kwargs: Dict, metric_value_kwargs: Dict, metrics: Dict[Tuple, Any], runtime_configuration: Dict)
classmethod _get_evaluation_dependencies(cls, metric: MetricConfiguration, configuration: Optional[ExpectationConfiguration] = None, execution_engine: Optional[ExecutionEngine] = None, runtime_configuration: Optional[dict] = None)

This should return a dictionary: {

“dependency_name”: MetricConfiguration, …

}