pm4py.filtering.filter_directly_follows_relation#
- pm4py.filtering.filter_directly_follows_relation(log: EventLog | DataFrame, relations: List[str], retain: bool = True, activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') EventLog | DataFrame[source]#
Retain traces that contain any of the specified ‘directly follows’ relations. For example, if relations == [(‘a’,’b’),(‘a’,’c’)] and log [<a,b,c>,<a,c,b>,<a,d,b>] the resulting log will contain traces describing [<a,b,c>,<a,c,b>].
- Parameters:
log – event log / Pandas dataframe
relations – list of activity name pairs, which are allowed/forbidden paths
retain (
bool) – parameter that says whether the paths should be kept/removedactivity_key (
str) – attribute to be used for the activitytimestamp_key (
str) – attribute to be used for the timestampcase_id_key (
str) – attribute to be used as case identifier
- Return type:
Union[EventLog, pd.DataFrame]
import pm4py filtered_dataframe = pm4py.filter_directly_follows_relation(dataframe, [('A','B'),('A','C')], activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')