pm4py.statistics.traces.generic.pandas.case_arrival module#

PM4Py – A Process Mining Library for Python

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class pm4py.statistics.traces.generic.pandas.case_arrival.Parameters(*values)[source]#

Bases: Enum

ATTRIBUTE_KEY = 'pm4py:param:attribute_key'#
ACTIVITY_KEY = 'pm4py:param:activity_key'#
START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'#
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
CASE_ID_KEY = 'pm4py:param:case_id_key'#
MAX_NO_POINTS_SAMPLE = 'max_no_of_points_to_sample'#
KEEP_ONCE_PER_CASE = 'keep_once_per_case'#
pm4py.statistics.traces.generic.pandas.case_arrival.get_case_arrival_avg(df: DataFrame, parameters: Dict[str | Parameters, Any] | None = None) → float[source]#

Gets the average time interlapsed between case starts

Parameters:

  • df – Pandas dataframe

  • parameters –

    Parameters of the algorithm, including:

    Parameters.TIMESTAMP_KEY -> attribute of the log to be used as timestamp

Returns:

Average time interlapsed between case starts

Return type:

case_arrival_avg

pm4py.statistics.traces.generic.pandas.case_arrival.get_case_dispersion_avg(df, parameters=None)[source]#

Gets the average time interlapsed between case ends

Parameters:

  • df – Pandas dataframe

  • parameters –

    Parameters of the algorithm, including:

    Parameters.TIMESTAMP_KEY -> attribute of the log to be used as timestamp

Returns:

Average time interlapsed between the completion of cases

Return type:

case_dispersion_avg