pm4py.statistics.service_time.log.get module#

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class pm4py.statistics.service_time.log.get.Parameters(*values)[source]#

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'#

START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'#

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#

AGGREGATION_MEASURE = 'aggregationMeasure'#

BUSINESS_HOURS = 'business_hours'#

BUSINESS_HOUR_SLOTS = 'business_hour_slots'#

WORKCALENDAR = 'workcalendar'#

pm4py.statistics.service_time.log.get.apply(log: EventLog, parameters: Dict[str | Parameters, Any] | None = None) → Dict[str, float][source]#

Gets the service time per activity on an event log object.

Parameters:

dataframe – Pandas dataframe
parameters – Parameters of the algorithm, including:
- Parameters.ACTIVITY_KEY => activity key
- Parameters.START_TIMESTAMP_KEY => start timestamp key
- Parameters.TIMESTAMP_KEY => timestamp key
- Parameters.AGGREGATION_MEASURE => performance aggregation measure (sum, min, max, mean, median)
- Parameters.BUSINESS_HOURS => calculates the difference of time based on the business hours, not the total time. Default: False
- Parameters.BUSINESS_HOURS_SLOTS => work schedule of the company. The following list defines that business hours are Mondays 07:00 - 17:00 and Tuesdays 07:00 - 12:00 and 13:00 - 17:00:
```
[
    (7 * 60 * 60, 17 * 60 * 60),
    ((24 + 7) * 60 * 60, (24 + 12) * 60 * 60),
    ((24 + 13) * 60 * 60, (24 + 17) * 60 * 60),
]
```

Returns:

Service time dictionary

Return type:

soj_time_dict

pm4py.statistics.service_time.log.get module#

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