pm4py.statistics.traces.cycle_time.pandas package#

PM4Py – A Process Mining Library for Python

This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

Submodules#

pm4py.statistics.traces.cycle_time.pandas.get module#

PM4Py – A Process Mining Library for Python

You should have received a copy of the GNU Affero General Public License along with this program. If not, see this software project’s root or visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions Contact: info@processintelligence.solutions

class pm4py.statistics.traces.cycle_time.pandas.get.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#

Bases: Enum

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#

START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'#

CASE_ID_KEY = 'pm4py:param:case_id_key'#

pm4py.statistics.traces.cycle_time.pandas.get.apply(df: DataFrame, parameters: Dict[str | Parameters, Any] | None = None) → float[source]#

Computes the cycle time starting from a Pandas dataframe

The definition that has been followed is the one proposed in: https://www.presentationeze.com/presentations/lean-manufacturing-just-in-time/lean-manufacturing-just-in-time-full-details/process-cycle-time-analysis/calculate-cycle-time/#:~:text=Cycle%20time%20%3D%20Average%20time%20between,is%2024%20minutes%20on%20average.

So: Cycle time = Average time between completion of units.

Example taken from the website: Consider a manufacturing facility, which is producing 100 units of product per 40 hour week. The average throughput rate is 1 unit per 0.4 hours, which is one unit every 24 minutes. Therefore the cycle time is 24 minutes on average.

Parameters#

df: Dataframe
parameters: Parameters of the algorithm, including: - Parameters.START_TIMESTAMP_KEY => the attribute acting as start timestamp - Parameters.TIMESTAMP_KEY => the attribute acting as timestamp - Parameters.CASE_ID_KEY => the attribute acting as case identifier

Returns#

cycle_time: Cycle time