DataOp

class skrub.DataOp(impl)

Representation of a computation that can be used to build DataOps plans and learners.

A complete machine learning pipeline – from data loading and wrangling to the final prediction – in a single object that can be fitted, tuned, cross-validated, and saved like any scikit-learn estimator.

This class is usually not instantiated manually, but through one of the functions var(), as_data_op(), X() or y(), by applying a deferred() function, or by calling a method or applying an operator to an existing DataOp.

Refer to the Building complete pipelines with DataOps page for more information.