pm4py.algo.filtering.pandas.end_activities package

Submodules

pm4py.algo.filtering.pandas.end_activities.end_activities_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.end_activities.end_activities_filter.Parameters[source]

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'
CASE_ID_KEY = 'pm4py:param:case_id_key'
DECREASING_FACTOR = 'decreasingFactor'
GROUP_DATAFRAME = 'grouped_dataframe'
POSITIVE = 'positive'
RETURN_EA_COUNT = 'return_ea_count_dict_autofilter'
pm4py.algo.filtering.pandas.end_activities.end_activities_filter.apply(df: pandas.core.frame.DataFrame, values: List[str], parameters: Optional[Dict[Union[str, pm4py.algo.filtering.pandas.end_activities.end_activities_filter.Parameters], Any]] = None) → pandas.core.frame.DataFrame[source]

Filter dataframe on end activities

Parameters:

  • df – Dataframe

  • values – Values to filter on

  • parameters –

    Possible parameters of the algorithm, including:

    Parameters.CASE_ID_KEY -> Case ID column in the dataframe Parameters.ACTIVITY_KEY -> Column that represents the activity Parameters.POSITIVE -> Specifies if the filtered should be applied including traces (positive=True) or excluding traces (positive=False)
Returns:

Filtered dataframe
Return type:

df
pm4py.algo.filtering.pandas.end_activities.end_activities_filter.apply_auto_filter(df, parameters=None)[source]

Apply auto filter on end activities

Parameters:

  • df – Pandas dataframe

  • parameters –

    Parameters of the algorithm, including:

    Parameters.CASE_ID_KEY -> Case ID column in the dataframe Parameters.ACTIVITY_KEY -> Column that represents the activity Parameters.DECREASING_FACTOR -> Decreasing factor that should be passed to the algorithm
Returns:

Filtered dataframe
Return type:

df

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

pm4py.algo.filtering.pandas.end_activities.end_activities_filter.filter_df_on_end_activities(df, values, case_id_glue='case:concept:name', activity_key='concept:name', grouped_df=None, positive=True)[source]

Filter dataframe on end activities

Parameters:
  • df – Dataframe
  • values – Values to filter on
  • case_id_glue – Case ID column in the dataframe
  • activity_key – Column that represent the activity
  • positive – Specifies if the filtered should be applied including traces (positive=True) or excluding traces (positive=False)
Returns:

Filtered dataframe
Return type:

df
pm4py.algo.filtering.pandas.end_activities.end_activities_filter.filter_df_on_end_activities_nocc(df, nocc, ea_count0=None, case_id_glue='case:concept:name', grouped_df=None, activity_key='concept:name', return_dict=False, most_common_variant=None)[source]

Filter dataframe on end activities number of occurrences

Parameters:
  • df – Dataframe
  • nocc – Minimum number of occurrences of the end activity
  • ea_count0 – (if provided) Dictionary that associates each end activity with its count
  • case_id_glue – Column that contains the Case ID
  • activity_key – Column that contains the activity
  • grouped_df – Grouped dataframe
  • return_dict – Return dict

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/>.