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 or 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.

Returns:

Filtered event log or Pandas 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'
)