# Tabular Constraints¶

## CustomConstraint¶

 CustomConstraint([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. Return a dict representation of this Constraint.

## UniqueCombinations¶

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

## Positive¶

 Positive(high[, strict, handling_strategy, …]) Ensure that the high column is 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. Return a dict representation of this Constraint.

## Negative¶

 Negative(low[, strict, handling_strategy, …]) Ensure that the low column is 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. 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) Transform the table data. 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. 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) Transform the table data. 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. 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. 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. Return a dict representation of this Constraint.