pm4py.filtering.filter_time_range

pm4py.filtering.filter_time_range(log: EventLog | DataFrame, dt1: str, dt2: str, mode='events', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') → EventLog | DataFrame

Filter a log on a time interval

Parameters:

• log – event log / Pandas dataframe

• dt1 (str) – left extreme of the interval

• dt2 (str) – right extreme of the interval

• mode (str) – modality of filtering (events, traces_contained, traces_intersecting). events: any event that fits the time frame is retained; traces_contained: any trace completely contained in the timeframe is retained; traces_intersecting: any trace intersecting with the time-frame is retained.

• timestamp_key (str) – attribute to be used for the timestamp

• case_id_key (str) – attribute to be used as case identifier

Return type:

Union[EventLog, pd.DataFrame]

import pm4py

filtered_dataframe1 = pm4py.filter_time_range(dataframe, '2010-01-01 00:00:00', '2011-01-01 00:00:00', mode='traces_contained', case_id_key='case:concept:name', timestamp_key='time:timestamp')
filtered_dataframe1 = pm4py.filter_time_range(dataframe, '2010-01-01 00:00:00', '2011-01-01 00:00:00', mode='traces_intersecting', case_id_key='case:concept:name', timestamp_key='time:timestamp')
filtered_dataframe1 = pm4py.filter_time_range(dataframe, '2010-01-01 00:00:00', '2011-01-01 00:00:00', mode='events', case_id_key='case:concept:name', timestamp_key='time:timestamp')