Predefined Constraint Classes

Predefined constraint classes are available for frequently occurring logic. The logic can be isolated to a single column, incorporate multiple columns in a table or be applied to multiple rows.

Single Column

This logic can be applied to a single column of your data.

Constraint Class	Description	Example
Positive	All the values in the column must be >0	The room_rate must be positive
Negative	All the values in the column must be <0	The credit_balance must be negative
ScalarInequality	All the values in the column have a fixed lower or upper bound	All checkin_date values must occur on or after Jan 1, 2020
ScalarRange	All the values in the column have fixed lower and upper bounds	All values in amenities_fee must be between 0 and 500.00
FixedIncrements	All the numerical values are increments of a whole number	All values in salary must be divisible by 1000

Multi Column

This logic requires multiple columns.

Constraint Class	Description	Example
FixedCombinations	No shuffling is allowed other than what's already observed in the data	The city and country values cannot be shuffled to create new permutations.
OneHotEncoding	The original data columns represent a one hot encoding scheme	Exactly 1 of the following columns has a 1 in each row: not_subscribed, basic_subscriber, premium
Inequality	The value in one column must always be greater than the other	The checkout_date must always be after the checkin_date
Range	The value in one column is bounded by the values in other columns	The parent_age must be in between child_age and grandparent_age
＊ChainedInequality	A chain of 2 or more columns in an inequality	purchase_date < start_date < end_date < expiration_date < termination_date