pm4py.stats.get_service_time#

pm4py.stats.get_service_time(log: EventLog | DataFrame, aggregation_measure: str = 'mean', activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', start_timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') → Dict[str, float][source]#

Computes the service time for each activity in the event log using the specified aggregation measure.

Service time refers to the duration an activity takes within a case.

Parameters:

log – Event log (EventLog or pandas DataFrame).
aggregation_measure (str) – Aggregation function to apply (e.g., “mean”, “median”, “min”, “max”, “sum”).
activity_key (str) – Attribute to be used for the activity.
timestamp_key (str) – Attribute to be used for the timestamp.
start_timestamp_key (str) – Attribute to be used for the start timestamp.
case_id_key (str) – Attribute to be used as the case identifier.

Returns:

A dictionary mapping each activity to its aggregated service time.

import pm4py

log = pm4py.read_xes('tests/input_data/interval_event_log.xes')
mean_serv_time = pm4py.get_service_time(
    log,
    start_timestamp_key='start_timestamp',
    aggregation_measure='mean'
)
print(mean_serv_time)

median_serv_time = pm4py.get_service_time(
    log,
    start_timestamp_key='start_timestamp',
    aggregation_measure='median'
)
print(median_serv_time)