pm4py.algo.filtering.pandas.ends_with 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.ends_with.ends_with_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.ends_with.ends_with_filter.Parameters(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum
- CASE_ID_KEY = 'pm4py:param:case_id_key'#
- ACTIVITY_KEY = 'pm4py:param:activity_key'#
- DECREASING_FACTOR = 'decreasingFactor'#
- POSITIVE = 'positive'#
- pm4py.algo.filtering.pandas.ends_with.ends_with_filter.apply(df: DataFrame, admitted_suffixes: List[str], parameters: Dict[str | Parameters, Any] | None = None) DataFrame [source]#
Apply a filter on variants
Parameters#
- df
Dataframe
- admitted_suffixes
List of admitted suffixes (to include/exclude)
- parameters
- Parameters of the algorithm, including:
Parameters.CASE_ID_KEY -> Column that contains the Case ID Parameters.ACTIVITY_KEY -> Column that contains the activity Parameters.POSITIVE -> Specifies if the filter should be applied including traces (positive=True) or excluding traces (positive=False) variants_df -> If provided, avoid recalculation of the variants dataframe
Returns#
- df
Filtered dataframe