pm4py.filtering.filter_variants_by_coverage_percentage#

pm4py.filtering.filter_variants_by_coverage_percentage(log: EventLog | DataFrame, min_coverage_percentage: float, activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') → EventLog | DataFrame[source]#

Filters the variants of the log based on a coverage percentage. For example, if min_coverage_percentage=0.4 and the log has 1000 cases with: - 500 cases of variant 1, - 400 cases of variant 2, - 100 cases of variant 3, the filter keeps only the traces of variant 1 and variant 2.

Parameters:

log – Event log or Pandas DataFrame.
min_coverage_percentage (float) – Minimum allowed percentage of coverage.
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 case identifier.

Returns:

Filtered event log or Pandas DataFrame.

import pm4py

filtered_dataframe = pm4py.filter_variants_by_coverage_percentage(
    dataframe,
    0.1,
    activity_key='concept:name',
    timestamp_key='time:timestamp',
    case_id_key='case:concept:name'
)