great_expectations.expectations.core.expect_column_proportion_of_unique_values_to_be_between
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Module Contents¶
Classes¶
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Expect the proportion of unique values to be between a minimum value and a maximum value. |
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class
great_expectations.expectations.core.expect_column_proportion_of_unique_values_to_be_between.
ExpectColumnProportionOfUniqueValuesToBeBetween
(configuration: Optional[ExpectationConfiguration] = None)¶ Bases:
great_expectations.expectations.expectation.ColumnExpectation
Expect the proportion of unique values to be between a minimum value and a maximum value.
For example, in a column containing [1, 2, 2, 3, 3, 3, 4, 4, 4, 4], there are 4 unique values and 10 total values for a proportion of 0.4.
expect_column_proportion_of_unique_values_to_be_between is a
column_aggregate_expectation
.- Parameters
column (str) – The column name.
min_value (float or None) – The minimum proportion of unique values. (Proportions are on the range 0 to 1)
max_value (float or None) – The maximum proportion of unique values. (Proportions are on the range 0 to 1)
strict_min (boolean) – If True, the minimum proportion of unique values must be strictly larger than min_value, default=False
strict_max (boolean) – If True, the maximum proportion of unique values must be strictly smaller than max_value, default=False
- 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.
Notes
These fields in the result object are customized for this expectation:
{ "observed_value": (float) The proportion of unique values in the column }
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
See also
expect_column_unique_value_count_to_be_between
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metric_dependencies
= ['column.unique_proportion']¶
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success_keys
= ['min_value', 'strict_min', 'max_value', 'strict_max']¶
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default_kwarg_values
¶ A Column Aggregate MetricProvider Decorator for the Unique Proportion
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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 neccessary 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
True if the configuration has been validated successfully. Otherwise, raises an exception
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classmethod
_prescriptive_renderer
(cls, configuration=None, result=None, language=None, runtime_configuration=None, **kwargs)¶
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classmethod
_descriptive_column_properties_table_distinct_percent_row_renderer
(cls, configuration=None, result=None, language=None, runtime_configuration=None, **kwargs)¶
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_validate
(self, configuration: ExpectationConfiguration, metrics: Dict, runtime_configuration: dict = None, execution_engine: ExecutionEngine = None)¶