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