Expect the set of distinct column values to be contained by a given set.

expect_column_distinct_values_to_be_in_set is a Column Aggregate Expectation.

The success value for this expectation will match that of expect_column_values_to_be_in_set.

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
                }
            ]
        }
    }
}

Args:

• column (str): The column name.
• value_set (set-like): A set of objects used for comparison.

Keyword Args:

• 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.
• 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, include_config, catch_exceptions, and meta.

See Also:

• expect_column_distinct_values_to_contain_set
• expect_column_distinct_values_to_equal_set