# sdv.constraints.Range¶

class sdv.constraints.Range(low_column_name, middle_column_name, high_column_name, strict_boundaries=True)[source]

Ensure that the middle_column_name is between low and high columns.

The transformation strategy works by replacing the middle_column_name with a scaled version and then applying a logit function. The reverse transform applies a sigmoid to the data and then scales it back to the original space.

Parameters
• low_column_name (str) – Name of the column which will be the lower bound.

• middle_column_name (str) – Name of the column that has to be between the lower bound and upper bound.

• high_column_name (str) – Name of the column which will be the higher bound.

• strict_boundaries (bool) – Whether the comparison of the values should be strict >= or not > when comparing them.

__init__(low_column_name, middle_column_name, high_column_name, strict_boundaries=True)

Initialize self. See help(type(self)) for accurate signature.

Methods

 __init__(low_column_name, …[, …]) Initialize self. filter_valid(table_data) Get only the rows that are valid. fit(table_data) Fit Constraint class to data. fit_transform(table_data) Fit this Constraint to the data and then transform it. from_dict(constraint_dict) Build a Constraint object from a dict. is_valid(table_data) Say whether the constraint_column is between the low and high values. reverse_transform(table_data) Handle logic around reverse transforming constraints. Return a dict representation of this Constraint. transform(table_data) Perform necessary transformations needed by constraint.

Attributes

 constraint_columns