great_expectations.expectations.core.expect_column_distinct_values_to_be_in_set
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Module Contents¶
Classes¶
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Expect the set of distinct column values to be contained by a given set. |
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class
great_expectations.expectations.core.expect_column_distinct_values_to_be_in_set.
ExpectColumnDistinctValuesToBeInSet
(configuration: Optional[ExpectationConfiguration] = None)¶ Bases:
great_expectations.expectations.expectation.ColumnExpectation
Expect the set of distinct column values to be contained by a given set.
The success value for this expectation will match that of expect_column_values_to_be_in_set. However, expect_column_distinct_values_to_be_in_set is a
column_aggregate_expectation
.For example:
# my_df.my_col = [1,2,2,3,3,3] >>> my_df.expect_column_distinct_values_to_be_in_set( "my_col", [2, 3, 4] ) { "success": false "result": { "observed_value": [1,2,3], "details": { "value_counts": [ { "value": 1, "count": 1 }, { "value": 2, "count": 1 }, { "value": 3, "count": 1 } ] } } }
- Parameters
column (str) – The column name.
value_set (set-like) – A set of objects used for comparison.
- Keyword Arguments
parse_strings_as_datetimes (boolean or None) – If True values provided in value_set will be parsed as datetimes before making comparisons.
- Other Parameters
result_format (str or None) – Which output mode to use: BOOLEAN_ONLY, BASIC, COMPLETE, or SUMMARY. For more detail, see result_format.
include_config (boolean) – If True, then include the expectation config as part of the result object. For more detail, see include_config.
catch_exceptions (boolean or None) – If True, then catch exceptions and include them as part of the result object. For more detail, see catch_exceptions.
meta (dict or None) – A JSON-serializable dictionary (nesting allowed) that will be included in the output without modification. For more detail, see meta.
- Returns
An ExpectationSuiteValidationResult
Exact fields vary depending on the values passed to result_format and include_config, catch_exceptions, and meta.
See also
expect_column_distinct_values_to_contain_set
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metric_dependencies
= ['column.value_counts']¶
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success_keys
= ['value_set', 'parse_strings_as_datetimes']¶
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default_kwarg_values
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classmethod
_prescriptive_renderer
(cls, configuration=None, result=None, language=None, runtime_configuration=None, **kwargs)¶
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classmethod
_descriptive_value_counts_bar_chart_renderer
(cls, configuration=None, result=None, language=None, runtime_configuration=None, **kwargs)¶
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validate_configuration
(self, configuration: Optional[ExpectationConfiguration])¶ Validating that user has inputted a value set and that configuration has been initialized
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_validate
(self, configuration: ExpectationConfiguration, metrics: Dict, runtime_configuration: dict = None, execution_engine: ExecutionEngine = None)¶