Deserialize a bytes string to a PM4Py object

format_dataframe(df[, case_id, ...])

Give the appropriate format on the dataframe, for process mining purposes

get_properties(log[, activity_key, ...])

Gets the properties from a log object

parse_event_log_string(traces[, sep, ...])

Parse a collection of traces expressed as strings (e.g., ["A,B,C,D", "A,C,B,D", "A,D"]) to a log object (Pandas dataframe)


Parse a POWL model from a string representation of the process model (with the same format as the __repr__ and __str__ methods of the POWL model)


Parse a process tree from a string

project_on_event_attribute(log[, ...])

Project the event log on a specified event attribute.

rebase(log_obj[, case_id, activity_key, ...])

Re-base the log object, changing the case ID, activity and timestamp attributes.

sample_cases(log, num_cases[, case_id_key])

(Random) Sample a given number of cases from the event log.

sample_events(log, num_events)

(Random) Sample a given number of events from the event log.


Serialize a PM4Py object into a bytes string

set_classifier(log, classifier[, ...])

Methods to set the specified classifier on an existing event log