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'''
This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
PM4Py is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
PM4Py 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 General Public License for more details.
You should have received a copy of the GNU General Public License
along with PM4Py. If not, see <https://www.gnu.org/licenses/>.
'''
from pm4py.algo.merging.case_relations.variants import pandas
from enum import Enum
import pandas as pd
from typing import Optional, Dict, Any
from pm4py.util import exec_utils
class Variants(Enum):
PANDAS = pandas
def apply(dataframe1: pd.DataFrame, dataframe2: pd.DataFrame, case_relations: pd.DataFrame, variant=Variants.PANDAS,
parameters: Optional[Dict[Any, Any]] = None) -> pd.DataFrame:
"""
Merges the two dataframes (dataframe1 and dataframe2), inserting the events of the second
dataframe inside the cases of the first dataframe.
This is done using a background knowledge provided in the case_relations dataframe, where the cases of the two dataframes
are put in relations.
E.g., if in dataframe1 and dataframe2 there are two case ID columns (case:concept:name),
they are put in relations by case_relations having two columns case:concept:name_LEFT and case:concept:name_RIGHT
Parameters
-----------------
dataframe1
Reference dataframe (in which the events of the other dataframe are inserted)
dataframe2
Second dataframe (to insert in the cases of the first)
case_relations
Case relations dataframe
variant
Variant of the algorithm to use, available ones:
- Variants.PANDAS
parameters
Variant-specific parameters
Returns
----------------
merged_dataframe
Merged dataframe
"""
return exec_utils.get_variant(variant).apply(dataframe1, dataframe2, case_relations, parameters=parameters)
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