pm4py.filtering.filter_case_performance#

pm4py.filtering.filter_case_performance(log: EventLog | DataFrame, min_performance: float, max_performance: float, timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') → EventLog | DataFrame[source]#

Filters the event log, keeping cases that have a duration (the timestamp of the last event minus the timestamp of the first event) between min_performance and max_performance.

Parameters:

log – Event log or Pandas DataFrame.
min_performance (float) – Minimum allowed case duration.
max_performance (float) – Maximum allowed case duration.
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_case_performance(
    dataframe,
    3600.0,
    86400.0,
    timestamp_key='time:timestamp',
    case_id_key='case:concept:name'
)