pm4py.filtering.filter_event_attribute_values(log: Union[EventLog, DataFrame], attribute_key: str, values: Union[Set[str], List[str]], level: str = 'case', retain: bool = True, case_id_key: str = 'case:concept:name') Union[EventLog, DataFrame][source]#

Filter a log object on the values of some event attribute

  • log – event log / Pandas dataframe

  • attribute_key (str) – attribute to filter

  • values – admitted (or forbidden) values

  • level (str) – specifies how the filter should be applied (‘case’ filters the cases where at least one occurrence happens, ‘event’ filter the events eventually trimming the cases)

  • retain (bool) – specifies if the values should be kept or removed

  • case_id_key (str) – attribute to be used as case identifier

Return type:

Union[EventLog, pd.DataFrame]

import pm4py

filtered_dataframe = pm4py.filter_event_attribute_values(dataframe, 'concept:name', ['Act. A', 'Act. Z'], case_id_key='case:concept:name')