Tabular Constraints

CustomConstraint

CustomConstraint([columns, transform, …])	Custom Constraint Class.
CustomConstraint.fit(table_data)	Fit Constraint class to data.
CustomConstraint.transform(table_data)	Perform necessary transformations needed by constraint.
CustomConstraint.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
CustomConstraint.reverse_transform(table_data)	Identity method for completion.
CustomConstraint.is_valid(table_data)	Say whether the given table rows are valid.
CustomConstraint.filter_valid(table_data)	Get only the rows that are valid.
CustomConstraint.from_dict(constraint_dict)	Build a Constraint object from a dict.
CustomConstraint.to_dict()	Return a dict representation of this Constraint.

FixedCombinations

FixedCombinations(column_names[, …])	Ensure that the combinations across multiple colums are fixed.
FixedCombinations.fit(table_data)	Fit Constraint class to data.
FixedCombinations.transform(table_data)	Perform necessary transformations needed by constraint.
FixedCombinations.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
FixedCombinations.reverse_transform(table_data)	Reverse transform the table data.
FixedCombinations.is_valid(table_data)	Say whether the column values are within the original combinations.
FixedCombinations.filter_valid(table_data)	Get only the rows that are valid.
FixedCombinations.from_dict(constraint_dict)	Build a Constraint object from a dict.
FixedCombinations.to_dict()	Return a dict representation of this Constraint.

GreaterThan

GreaterThan(low, high[, strict, …])	Ensure that the high column is always greater than the low one.
GreaterThan.fit(table_data)	Fit Constraint class to data.
GreaterThan.transform(table_data)	Perform necessary transformations needed by constraint.
GreaterThan.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
GreaterThan.reverse_transform(table_data)	Reverse transform the table data.
GreaterThan.is_valid(table_data)	Say whether high is greater than low in each row.
GreaterThan.filter_valid(table_data)	Get only the rows that are valid.
GreaterThan.from_dict(constraint_dict)	Build a Constraint object from a dict.
GreaterThan.to_dict()	Return a dict representation of this Constraint.

Positive

Positive(columns[, strict, …])	Ensure that the given column(s) are always positive.
Positive.fit(table_data)	Fit Constraint class to data.
Positive.transform(table_data)	Perform necessary transformations needed by constraint.
Positive.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
Positive.reverse_transform(table_data)	Reverse transform the table data.
Positive.is_valid(table_data)	Say whether high is greater than low in each row.
Positive.filter_valid(table_data)	Get only the rows that are valid.
Positive.from_dict(constraint_dict)	Build a Constraint object from a dict.
Positive.to_dict()	Return a dict representation of this Constraint.

Negative

Negative(columns[, strict, …])	Ensure that the given columns are always negative.
Negative.fit(table_data)	Fit Constraint class to data.
Negative.transform(table_data)	Perform necessary transformations needed by constraint.
Negative.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
Negative.reverse_transform(table_data)	Reverse transform the table data.
Negative.is_valid(table_data)	Say whether high is greater than low in each row.
Negative.filter_valid(table_data)	Get only the rows that are valid.
Negative.from_dict(constraint_dict)	Build a Constraint object from a dict.
Negative.to_dict()	Return a dict representation of this Constraint.

ColumnFormula

ColumnFormula(column, formula[, …])	Compute a column based on applying a formula on the others.
ColumnFormula.fit(table_data)	Fit Constraint class to data.
ColumnFormula.transform(table_data)	Perform necessary transformations needed by constraint.
ColumnFormula.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
ColumnFormula.reverse_transform(table_data)	Reverse transform the table data.
ColumnFormula.is_valid(table_data)	Say whether the data fulfills the formula.
ColumnFormula.filter_valid(table_data)	Get only the rows that are valid.
ColumnFormula.from_dict(constraint_dict)	Build a Constraint object from a dict.
ColumnFormula.to_dict()	Return a dict representation of this Constraint.

Between

Between(column, low, high[, strict, …])	Ensure that the constraint_column is always between high and low.
Between.fit(table_data)	Fit Constraint class to data.
Between.transform(table_data)	Perform necessary transformations needed by constraint.
Between.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
Between.reverse_transform(table_data)	Reverse transform the table data.
Between.is_valid(table_data)	Say whether the constraint_column is between the low and high values.
Between.filter_valid(table_data)	Get only the rows that are valid.
Between.from_dict(constraint_dict)	Build a Constraint object from a dict.
Between.to_dict()	Return a dict representation of this Constraint.

Rounding

Rounding(columns, digits[, …])	Round a column based on the specified number of digits.
Rounding.fit(table_data)	Fit Constraint class to data.
Rounding.transform(table_data)	Perform necessary transformations needed by constraint.
Rounding.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
Rounding.reverse_transform(table_data)	Reverse transform the table data.
Rounding.is_valid(table_data)	Determine if the data satisfies the rounding constraint.
Rounding.filter_valid(table_data)	Get only the rows that are valid.
Rounding.from_dict(constraint_dict)	Build a Constraint object from a dict.
Rounding.to_dict()	Return a dict representation of this Constraint.

OneHotEncoding

OneHotEncoding(columns[, handling_strategy])	Ensure the appropriate columns are one hot encoded.
OneHotEncoding.fit(table_data)	Fit Constraint class to data.
OneHotEncoding.transform(table_data)	Perform necessary transformations needed by constraint.
OneHotEncoding.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
OneHotEncoding.reverse_transform(table_data)	Reverse transform the table data.
OneHotEncoding.is_valid(table_data)	Check whether the data satisfies the one-hot constraint.
OneHotEncoding.filter_valid(table_data)	Get only the rows that are valid.
OneHotEncoding.from_dict(constraint_dict)	Build a Constraint object from a dict.
OneHotEncoding.to_dict()	Return a dict representation of this Constraint.

Unique

Unique(columns)	Ensure that each value for a specified column/group of columns is unique.
Unique.fit(table_data)	Fit Constraint class to data.
Unique.transform(table_data)	Perform necessary transformations needed by constraint.
Unique.fit_transform(table_data)	Fit this Constraint to the data and then transform it.
Unique.reverse_transform(table_data)	Identity method for completion.
Unique.is_valid(table_data)	Get indices of first instance of unique rows.
Unique.filter_valid(table_data)	Get only the rows that are valid.
Unique.from_dict(constraint_dict)	Build a Constraint object from a dict.
Unique.to_dict()	Return a dict representation of this Constraint.

sdv.constraints.Constraint.to_dict sdv.constraints.CustomConstraint