pm4py.algo.filtering.pandas.paths package

Submodules

pm4py.algo.filtering.pandas.paths.paths_filter module

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/>.

class pm4py.algo.filtering.pandas.paths.paths_filter.Parameters

Bases: enum.Enum

An enumeration.

ATTRIBUTE_KEY = 'pm4py:param:attribute_key'

CASE_ID_KEY = 'pm4py:param:case_id_key'

DECREASING_FACTOR = 'decreasingFactor'

MAX_PERFORMANCE = 'max_performance'

MIN_PERFORMANCE = 'min_performance'

POSITIVE = 'positive'

TARGET_ATTRIBUTE_KEY = 'target_attribute_key'

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'

pm4py.algo.filtering.pandas.paths.paths_filter.apply(df: pandas.core.frame.DataFrame, paths: List[Tuple[str, str]], parameters: Optional[Dict[Union[str, pm4py.algo.filtering.pandas.paths.paths_filter.Parameters], Any]] = None) → pandas.core.frame.DataFrame

Apply a filter on traces containing / not containing a path

Parameters:

• df – Dataframe

• paths – Paths to filter on

• parameters –

  Possible parameters of the algorithm, including:

  Parameters.CASE_ID_KEY -> Case ID column in the dataframe Parameters.ATTRIBUTE_KEY -> Attribute we want to filter Parameters.POSITIVE -> Specifies if the filter should be applied including traces (positive=True) or excluding traces (positive=False)

Returns:

Filtered dataframe

Return type:

df

pm4py.algo.filtering.pandas.paths.paths_filter.apply_auto_filter(df, parameters=None)

Deprecated since version 2.2.11: This will be removed in 3.0.0. Removed

pm4py.algo.filtering.pandas.paths.paths_filter.apply_performance(df: pandas.core.frame.DataFrame, provided_path: Tuple[str, str], parameters: Optional[Dict[Union[str, pm4py.algo.filtering.pandas.paths.paths_filter.Parameters], Any]] = None) → pandas.core.frame.DataFrame

Filters the cases of a dataframe where there is at least one occurrence of the provided path occurring in the defined timedelta range.

Parameters:

• df – Dataframe

• paths – Paths to filter on

• parameters –

  Possible parameters of the algorithm, including:

  Parameters.CASE_ID_KEY -> Case ID column in the dataframe Parameters.ATTRIBUTE_KEY -> Attribute we want to filter Parameters.TIMESTAMP_KEY -> Attribute identifying the timestamp in the log Parameters.POSITIVE -> Specifies if the filter should be applied including traces (positive=True) or excluding traces (positive=False) Parameters.MIN_PERFORMANCE -> Minimal allowed performance of the provided path Parameters.MAX_PERFORMANCE -> Maximal allowed performance of the provided path

Returns:

Filtered dataframe

Return type:

df

Module contents

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/>.