pm4py.filtering.filter_between#

pm4py.filtering.filter_between(log: EventLog | DataFrame, act1: str | List[str], act2: str | List[str], activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') → EventLog | DataFrame[source]#

Finds all the sub-cases leading from an event with activity “act1” to an event with activity “act2” in the log, and returns a log containing only them.

Example:

Log A B C D E F A B E F C A B F C B C B E F C

act1 = B act2 = C

Returned sub-cases: B C (from the first case) B E F C (from the second case) B F C (from the third case) B C (from the third case) B E F C (from the third case)

Parameters:

log – event log / Pandas dataframe
act1 – source activity (or collection of activities)
act2 – target activity (or collection of activities)
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

Return type:

Union[EventLog, pd.DataFrame]

import pm4py

filtered_dataframe = pm4py.filter_between(dataframe, 'A', 'D', activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')