Processors

These processors are used to process data before and after avatarization.

Table of contents

avatars.processors.DatetimeProcessor()	Process datetime for avatarization.
avatars.processors.ExpectedMeanProcessor(...)	Processor to force values to have similar mean to original data.
avatars.processors.GeolocationNormalizationProcessor(*, ...)	Processor to normalize longitude values for different latitude.
avatars.processors.GroupModalitiesProcessor(*)	Processor to group modalities in order to reduce the dataframe dimension.
avatars.processors.InterRecordBoundedCumulatedDifferenceProcessor(...)	Processor to express the value of a variable as the difference from the previous value.
avatars.processors.InterRecordBoundedRangeDifferenceProcessor(*, ...)	Processor to express two related bounded variables relative to previous records.
avatars.processors.InterRecordCumulatedDifferenceProcessor(*, ...)	Processor to express the value of a variable as the difference from the previous value.
avatars.processors.InterRecordRangeDifferenceProcessor(*, ...)	Processor to express the values of two related variables relative to previous records.
avatars.processors.PerturbationProcessor([...])	Processor to reduce the difference between originals and avatars.
avatars.processors.ProportionProcessor(...)	Processor to express numeric variables as a proportion of another variable.
avatars.processors.RelativeDifferenceProcessor(...)	Express numeric variables as a difference relative to the sum of other variables.
avatars.processors.ToCategoricalProcessor(...)	Processor to model selected numeric variables as categorical variables.