pm4py.stats

The pm4py.stats module contains the statistical functionalities offered in pm4py.

Functions

get_activity_position_summary(log, activity)	Summarizes the positions of a specific activity across all cases in the event log.
get_all_case_durations(log[, ...])	Retrieves the durations of all cases in the event log.
get_case_arrival_average(log[, ...])	Calculates the average time difference between the start times of two consecutive cases.
get_case_duration(log, case_id[, ...])	Retrieves the duration of a specific case.
get_case_overlap(log[, activity_key, ...])	Associates each case in the log with the number of cases that are concurrently open.
get_cycle_time(log[, activity_key, ...])	Calculates the cycle time of the event log.
get_end_activities(log[, activity_key, ...])	Returns the end activities and their frequencies from a log object.
get_event_attribute_values(log, attribute[, ...])	Returns the values and their frequencies for a specified event attribute.
get_event_attributes(log)	Returns the list of event-level attributes in the log.
get_frequent_trace_segments(log, min_occ[, ...])	Retrieves frequent trace segments (sub-sequences of activities) from an event log.
get_minimum_self_distance_witnesses(log[, ...])	Derives the minimum self-distance witnesses for each activity.
get_minimum_self_distances(log[, ...])	Computes the minimum self-distance for each activity observed in an event log.
get_rework_cases_per_activity(log[, ...])	Identifies activities that have rework occurrences, i.e., activities that occur more than once within the same case.
get_service_time(log[, aggregation_measure, ...])	Computes the service time for each activity in the event log using the specified aggregation measure.
get_start_activities(log[, activity_key, ...])	Returns the start activities and their frequencies from a log object.
get_stochastic_language(*args, **kwargs)	Retrieves the stochastic language from the provided object.
get_trace_attribute_values(log, attribute[, ...])	Returns the values and their frequencies for a specified trace attribute.
get_trace_attributes(log)	Returns the list of trace-level attributes in the log.
get_variants(log[, activity_key, ...])	Retrieves the variants from the log.
get_variants_as_tuples(log[, activity_key, ...])	Retrieves the variants from the log, where the variant keys are tuples.
get_variants_paths_duration(log[, ...])	Associates a pandas DataFrame aggregated by variants and their positions within each variant.
split_by_process_variant(log[, ...])	Splits an event log into sub-dataframes for each process variant.