pm4py.discovery.discover_dfg(log: Union[EventLog, DataFrame], activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') Tuple[dict, dict, dict][source]#

Discovers a Directly-Follows Graph (DFG) from a log.

This method returns a dictionary with the couples of directly-following activities (in the log) as keys and the frequency of relation as value.

  • log – event log / Pandas dataframe

  • 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:

Tuple[dict, dict, dict]

import pm4py

dfg, start_activities, end_activities = pm4py.discover_dfg(dataframe, case_id_key='case:concept:name', activity_key='concept:name', timestamp_key='time:timestamp')