dataframely.testing.mask module

dataframely.testing.mask.validation_mask(df: DataFrame | LazyFrame, failure: FailureInfo) → Series

Build a validation mask for the left data frame based on the failure info.

Args:

df: The data frame for whose rows to generate the validation mask. failure: The failure object whose information should be used to determine

which rows of the input data frame are invalid.

Returns:

A series where with the same length as the input data frame where a value of True indicates validity and False the opposite.

Raises:

ValueError: If columns with a dtype of struct or nested list is contained in

the input. In polars v1.1.0, both of these do not work reliably.