pm4py.algo.filtering.pandas.timestamp_case_grouping.timestamp_case_grouping_filter module#

class pm4py.algo.filtering.pandas.timestamp_case_grouping.timestamp_case_grouping_filter.Parameters(*values)[source]#

Bases: Enum

CASE_ID_KEY = 'pm4py:param:case_id_key'#
ACTIVITY_KEY = 'pm4py:param:activity_key'#
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
FILTER_TYPE = 'filter_type'#
pm4py.algo.filtering.pandas.timestamp_case_grouping.timestamp_case_grouping_filter.apply(log_obj: EventLog | EventStream | DataFrame, parameters: Dict[Any, Any] | None = None) → DataFrame[source]#

Groups the events of the same case happening at the same timestamp, providing option to keep the first event of each group, keep the last event of each group, create an event having as activity the concatenation of the activities happening in the group

Parameters:

  • log_obj – Log object (EventLog, EventStream, Pandas dataframe)

  • parameters – Parameters of the algorithm, including: - Parameters.CASE_ID_KEY => the case identifier to be used - Parameters.ACTIVITY_KEY => the attribute to be used as activity - Parameters.TIMESTAMP_KEY => the attribute to be used as timestamp - Parameters.FILTER_TYPE => the type of filter to be applied:

    first => keeps the first event of each group last => keeps the last event of each group concat => creates an event having as activity the concatenation of the activities happening in the group

Returns:

Filtered dataframe object

Return type:

filtered_dataframe