pm4py.ml.extract_outcome_enriched_dataframe#
- pm4py.ml.extract_outcome_enriched_dataframe(log: EventLog | DataFrame, activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name', start_timestamp_key: str = 'time:timestamp') DataFrame [source]#
Enriches a dataframe with additional outcome-related columns computed from the entire case.
This function adds columns that model the outcome of each case by computing metrics such as arrival rates and service waiting times.
- Parameters:
log – The event log or Pandas DataFrame to be enriched.
activity_key (
str
) – Attribute to be used for the activity.timestamp_key (
str
) – Attribute to be used for the timestamp.case_id_key (
str
) – Attribute to be used as the case identifier.start_timestamp_key (
str
) – Attribute to be used as the start timestamp.
- Returns:
An enriched Pandas DataFrame with additional outcome-related columns.
- Return type:
pd.DataFrame
import pm4py enriched_df = pm4py.extract_outcome_enriched_dataframe( log, activity_key='concept:name', timestamp_key='time:timestamp', case_id_key='case:concept:name', start_timestamp_key='time:timestamp' )