pm4py.algo.filtering.pandas.rework package#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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.algo.filtering.pandas.rework.rework_filter module#
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
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
- class pm4py.algo.filtering.pandas.rework.rework_filter.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum
- ACTIVITY_KEY = 'pm4py:param:activity_key'#
- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- MIN_OCCURRENCES = 'min_occurrences'#
- POSITIVE = 'positive'#
- pm4py.algo.filtering.pandas.rework.rework_filter.apply(df0: DataFrame, activity: str, parameters: Dict[Any, Any] | None = None) DataFrame [source]#
Applies the rework filter on the provided dataframe and activity. This filter the cases of the log having at least Parameters.MIN_OCCURRENCES (default: 2) occurrences of the given activity.
It is also possible (setting Parameters.POSITIVE to False) to retrieve the cases of the log not having the given activity or having the activity occurred less than Parameters.MIN_OCCURRENCES times.
Parameters#
- df0
Dataframe
- activity
Activity of which the rework shall be filtered
- parameters
Parameters of the filter, including: - Parameters.ACTIVITY_KEY => the attribute to use as activity - Parameters.CASE_ID_KEY => the attribute to use as case ID - Parameters.MIN_OCCURRENCES => the minimum number of occurrences for the activity - Parameters.POSITIVE => if True, filters the cases of the log having at least MIN_OCCURRENCES occurrences.
if False, filters the cases of the log where such behavior does not occur.
Returns#
- filtered_df
Filtered dataframe