great_expectations.expectations.core.expect_column_median_to_be_between

Module Contents

Classes

ExpectColumnMedianToBeBetween(configuration: Optional[ExpectationConfiguration] = None)

Expect the column median to be between a minimum value and a maximum value.

class great_expectations.expectations.core.expect_column_median_to_be_between.ExpectColumnMedianToBeBetween(configuration: Optional[ExpectationConfiguration] = None)

Bases: great_expectations.expectations.expectation.ColumnExpectation

Expect the column median to be between a minimum value and a maximum value.

expect_column_median_to_be_between is a [Column Aggregate Expectation](https://docs.greatexpectations.io/docs/guides/expectations/creating_custom_expectations/how_to_create_custom_column_aggregate_expectations).

Parameters
  • column (str) – The column name.

  • min_value (int or None) – The minimum value for the column median.

  • max_value (int or None) – The maximum value for the column median.

  • strict_min (boolean) – If True, the column median must be strictly larger than min_value, default=False

  • strict_max (boolean) – If True, the column median must be strictly smaller than max_value, default=False

Other Parameters
Returns

//docs.greatexpectations.io/docs/terms/validation_result)

Exact fields vary depending on the values passed to result_format, include_config, catch_exceptions, and meta.

Return type

An [ExpectationSuiteValidationResult](https

Notes

  • min_value and max_value are both inclusive unless strict_min or strict_max are set to True.

  • If min_value is None, then max_value is treated as an upper bound

  • If max_value is None, then min_value is treated as a lower bound

  • observed_value field in the result object is customized for this expectation to be a float representing the true median for the column

library_metadata
metric_dependencies = ['column.median']
success_keys = ['min_value', 'strict_min', 'max_value', 'strict_max', 'auto', 'profiler_config']
median_range_estimator_parameter_builder_config
validation_parameter_builder_configs :List[ParameterBuilderConfig]
default_profiler_config
default_kwarg_values
args_keys = ['column', 'min_value', 'max_value', 'strict_min', 'strict_max']
validate_configuration(self, configuration: Optional[ExpectationConfiguration])

Validates that a configuration has been set, and sets a configuration if it has yet to be set. Ensures that necessary configuration arguments have been provided for the validation of the expectation.

Parameters

configuration (OPTIONAL[ExpectationConfiguration]) – An optional Expectation Configuration entry that will be used to configure the expectation

Returns

None. Raises InvalidExpectationConfigurationError if the config is not validated successfully

classmethod _atomic_prescriptive_template(cls, configuration: Optional[ExpectationConfiguration] = None, result: Optional[ExpectationValidationResult] = None, runtime_configuration: Optional[dict] = None, **kwargs)

Template function that contains the logic that is shared by AtomicPrescriptiveRendererType.SUMMARY and LegacyRendererType.PRESCRIPTIVE.

classmethod _prescriptive_renderer(cls, configuration: Optional[ExpectationConfiguration] = None, result: Optional[ExpectationValidationResult] = None, runtime_configuration: Optional[dict] = None, **kwargs)
_validate(self, configuration: ExpectationConfiguration, metrics: Dict, runtime_configuration: Optional[dict] = None, execution_engine: Optional[ExecutionEngine] = None)