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As a user, it would be useful to be able to update, learn or view transformers for my sequential data.
Add the following methods to the PARSynthesizer
PARSynthesizer
auto_assign_transformers(data)
data
pandas.DataFrame
get_transformers()
update_transformers(column_name_to_transformer)
column_name_to_transformer
>>> synthesizer.assign_transformers(data) >>> synthesizer.get_transformers(table_name='users') { 'patient_id': None 'ssn': None, 'time': None ... } >>> from rdt.transformers as rt >>> paf = rt.PeudoAnonymizedFaker(provider_name='address', function_name='address') >>> pn = rt.AnonymizedGeoExtractor() >>> pn2 = rt.AnonymizedGeoExtractor() >>> model.update_transformers( column_name_to_transformer={ 'patient_id': rt.RegexGenerator(regex_format='[0-9]{4}'), }) Error: Transformers for context columns are not allowed to be updated.
The text was updated successfully, but these errors were encountered:
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Problem Description
As a user, it would be useful to be able to update, learn or view transformers for my sequential data.
Acceptance criteria
Add the following methods to the
PARSynthesizer
auto_assign_transformers(data)
data
is apandas.DataFrame
get_transformers()
update_transformers(column_name_to_transformer)
column_name_to_transformer
is a dict mapping column names to transformer instancesExpected behavior
Additional context
The text was updated successfully, but these errors were encountered: