sdv.constraints.ScalarRange

class sdv.constraints.ScalarRange(column_name, low_value, high_value, strict_boundaries=True)[source]

Ensure that the column_name is between the range of low and high.

The transformation strategy works by replacing the 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
  • column_name (str) – Name of the column that has to be between the lower bound and upper bound.

  • low_value (int or float) – Lower bound on the values of the column_name.

  • high_value (int or float) – Higher bound on the values of the column_name.

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

__init__(column_name, low_value, high_value, strict_boundaries=True)

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

Methods

__init__(column_name, low_value, high_value)

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 column_name is between the low and high values.

reverse_transform(table_data)

Handle logic around reverse transforming constraints.

to_dict()

Return a dict representation of this Constraint.

transform(table_data)

Perform necessary transformations needed by constraint.

Attributes

constraint_columns