pm4py.stats.get_activity_position_summary(log: Union[EventLog, DataFrame], activity: str, activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') Dict[int, int][source]#

Given an event log, returns a dictionary which summarize the positions of the activities in the different cases of the event log. E.g., if an activity happens 1000 times in the position 1 (the second event of a case), and 500 times in the position 2 (the third event of a case), then the returned dictionary would be: {1: 1000, 2: 500}

  • log – Event log object / Pandas dataframe

  • activity (str) – Activity to consider

  • 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:

Dict[int, int]

import pm4py

act_pos = pm4py.get_activity_position_summary(dataframe, 'Act. A', activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')