pm4py.objects.ocel.importer.csv 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
Subpackages#
Submodules#
pm4py.objects.ocel.importer.csv.importer 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.objects.ocel.importer.csv.importer.Variants(value, names=<not given>, *values, module=None, qualname=None, type=None, start=1, boundary=None)[source]#
Bases:
Enum- PANDAS = <module 'pm4py.objects.ocel.importer.csv.variants.pandas' from 'C:\\Users\\berti\\pm4py-core\\pm4py\\objects\\ocel\\importer\\csv\\variants\\pandas.py'>#
- pm4py.objects.ocel.importer.csv.importer.apply(file_path: str, objects_path: str = None, variant=Variants.PANDAS, parameters: Dict[Any, Any] | None = None) OCEL[source]#
Imports an object-centric event log from a CSV file
Parameters#
- file_path
Path to the object-centric event log
- objects_path
Optional path to a CSV file containing the objects dataframe
- variant
Variant of the algorithm that should be used, possible values: - Variants.PANDAS
- parameters
Parameters of the algorithm
Returns#
- ocel
Object-centric event log