pm4py.filtering.filter_eventually_follows_relation#

pm4py.filtering.filter_eventually_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]#

Retains traces that contain any of the specified ‘eventually 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>,<a,d,b>].

Parameters:

log – Event log or Pandas DataFrame.
relations – List of activity name pairs, representing allowed or forbidden paths.
retain (bool) – Boolean indicating whether the paths should be kept (if True) or removed (if False).
activity_key (str) – Attribute to be used for the activity.
timestamp_key (str) – Attribute to be used for the timestamp.
case_id_key (str) – Attribute to be used as case identifier.

Returns:

Filtered event log or Pandas DataFrame.

import pm4py

filtered_dataframe = pm4py.filter_eventually_follows_relation(
    dataframe,
    [('A', 'B'), ('A', 'C')],
    activity_key='concept:name',
    case_id_key='case:concept:name',
    timestamp_key='time:timestamp'
)