pm4py.statistics.traces.generic.pandas package¶

Submodules¶

pm4py.statistics.traces.generic.pandas.case_arrival 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.statistics.traces.generic.pandas.case_arrival.Parameters[source]¶

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'¶

ATTRIBUTE_KEY = 'pm4py:param:attribute_key'¶

CASE_ID_KEY = 'pm4py:param:case_id_key'¶

KEEP_ONCE_PER_CASE = 'keep_once_per_case'¶

MAX_NO_POINTS_SAMPLE = 'max_no_of_points_to_sample'¶

START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'¶

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'¶

pm4py.statistics.traces.generic.pandas.case_arrival.get_case_arrival_avg(df: pandas.core.frame.DataFrame, parameters: Optional[Dict[Union[str, pm4py.statistics.traces.generic.pandas.case_arrival.Parameters], Any]] = None) → float[source]¶

Gets the average time interlapsed between case starts

Parameters:	df – Pandas dataframe parameters – Parameters of the algorithm, including: Parameters.TIMESTAMP_KEY -> attribute of the log to be used as timestamp
Returns:	Average time interlapsed between case starts
Return type:	case_arrival_avg

pm4py.statistics.traces.generic.pandas.case_arrival.get_case_dispersion_avg(df, parameters=None)[source]¶

Gets the average time interlapsed between case ends

Parameters:	df – Pandas dataframe parameters – Parameters of the algorithm, including: Parameters.TIMESTAMP_KEY -> attribute of the log to be used as timestamp
Returns:	Average time interlapsed between the completion of cases
Return type:	case_dispersion_avg

pm4py.statistics.traces.generic.pandas.case_statistics 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.statistics.traces.generic.pandas.case_statistics.Parameters[source]¶

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'¶

ATTRIBUTE_KEY = 'pm4py:param:attribute_key'¶

BUSINESS_HOURS = 'business_hours'¶

CASE_ID_KEY = 'pm4py:param:case_id_key'¶

ENABLE_SORT = 'enable_sort'¶

MAX_RET_CASES = 'max_ret_cases'¶

MAX_VARIANTS_TO_RETURN = 'max_variants_to_return'¶

SORT_ASCENDING = 'sort_ascending'¶

SORT_BY_COLUMN = 'sort_by_column'¶

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'¶

VARIANTS_DF = 'variants_df'¶

WEEKENDS = 'weekends'¶

WORKCALENDAR = 'workcalendar'¶

WORKTIMING = 'worktiming'¶

pm4py.statistics.traces.generic.pandas.case_statistics.get_all_case_durations(df, parameters=None)[source]¶

Gets all the case durations out of the log

Parameters:	df – Pandas dataframe parameters – Possible parameters of the algorithm
Returns:	List of all duration values
Return type:	duration_values

pm4py.statistics.traces.generic.pandas.case_statistics.get_cases_description(df: pandas.core.frame.DataFrame, parameters: Optional[Dict[Union[str, pm4py.statistics.traces.generic.pandas.case_statistics.Parameters], Any]] = None) → Dict[str, Dict[str, Any]][source]¶

Get a description of traces present in the Pandas dataframe

Parameters:	df – Pandas dataframe parameters – Parameters of the algorithm, including: Parameters.CASE_ID_KEY -> Column that identifies the case ID Parameters.TIMESTAMP_KEY -> Column that identifies the timestamp enable_sort -> Enable sorting of traces Parameters.SORT_BY_COLUMN -> Sort traces inside the dataframe using the specified column. Admitted values: startTime, endTime, caseDuration Parameters.SORT_ASCENDING -> Set sort direction (boolean; it true then the sort direction is ascending, otherwise descending) Parameters.MAX_RET_CASES -> Set the maximum number of returned traces
Returns:	Dictionary of traces associated to their start timestamp, their end timestamp and their duration
Return type:	ret

pm4py.statistics.traces.generic.pandas.case_statistics.get_events(df: pandas.core.frame.DataFrame, case_id: str, parameters: Optional[Dict[Union[str, pm4py.statistics.traces.generic.pandas.case_statistics.Parameters], Any]] = None) → List[Dict[str, Any]][source]¶

Get events belonging to the specified case

Parameters:	df – Pandas dataframe case_id – Required case ID parameters – Possible parameters of the algorithm, including: Parameters.CASE_ID_KEY -> Column in which the case ID is contained
Returns:	List of events belonging to the case
Return type:	list_eve

pm4py.statistics.traces.generic.pandas.case_statistics.get_first_quartile_case_duration(df, parameters=None)[source]¶

Gets the first quartile out of the log

Parameters:	df – Pandas dataframe parameters – Possible parameters of the algorithm
Returns:	First quartile value
Return type:	value

pm4py.statistics.traces.generic.pandas.case_statistics.get_kde_caseduration(df, parameters=None)[source]¶

Gets the estimation of KDE density for the case durations calculated on the dataframe

Parameters:

df – Pandas dataframe
parameters –

Possible parameters of the algorithm, including:

Parameters.GRAPH_POINTS -> number of points to include in the graph Parameters.CASE_ID_KEY -> Column hosting the Case ID

Returns:

x – X-axis values to represent
y – Y-axis values to represent

pm4py.statistics.traces.generic.pandas.case_statistics.get_kde_caseduration_json(df, parameters=None)[source]¶

Gets the estimation of KDE density for the case durations calculated on the log/dataframe (expressed as JSON)

Parameters:	df – Pandas dataframe parameters – Possible parameters of the algorithm, including: Parameters.GRAPH_POINTS -> number of points to include in the graph Parameters.CASE_ID_KEY -> Column hosting the Case ID
Returns:	JSON representing the graph points
Return type:	json

pm4py.statistics.traces.generic.pandas.case_statistics.get_median_case_duration(df, parameters=None)[source]¶

Gets the median case duration out of the log

Parameters:	df – Pandas dataframe parameters – Possible parameters of the algorithm
Returns:	Median duration value
Return type:	value

pm4py.statistics.traces.generic.pandas.case_statistics.get_variant_statistics(df: pandas.core.frame.DataFrame, parameters: Optional[Dict[Union[str, pm4py.statistics.traces.generic.pandas.case_statistics.Parameters], Any]] = None) → Union[List[Dict[str, int]], List[Dict[List[str], int]]][source]¶

Get variants from a Pandas dataframe

Parameters:	df – Dataframe 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.MAX_VARIANTS_TO_RETURN -> Maximum number of variants to return variants_df -> If provided, avoid recalculation of the variants dataframe
Returns:	List of variants inside the Pandas dataframe
Return type:	variants_list

pm4py.statistics.traces.generic.pandas.case_statistics.get_variants_df(df, parameters=None)[source]¶

Get variants dataframe from a Pandas dataframe

Parameters:	df – Dataframe parameters – Parameters of the algorithm, including: Parameters.CASE_ID_KEY -> Column that contains the Case ID Parameters.ACTIVITY_KEY -> Column that contains the activity
Returns:	Variants dataframe
Return type:	variants_df

pm4py.statistics.traces.generic.pandas.case_statistics.get_variants_df_and_list(df: pandas.core.frame.DataFrame, parameters: Optional[Dict[Union[str, pm4py.statistics.traces.generic.pandas.case_statistics.Parameters], Any]] = None) → Tuple[pandas.core.frame.DataFrame, Union[List[Dict[str, int]], List[Dict[List[str], int]]]][source]¶

(Technical method) Provides variants_df and variants_list out of the box

Parameters:

df – Dataframe
parameters –

Parameters of the algorithm, including:

Parameters.CASE_ID_KEY -> Column that contains the Case ID Parameters.ACTIVITY_KEY -> Column that contains the activity

Returns:

variants_df – Variants dataframe
variants_list – List of variants sorted by their count

pm4py.statistics.traces.generic.pandas.case_statistics.get_variants_df_with_case_duration(df, parameters=None)[source]¶

Get variants dataframe from a Pandas dataframe, with case duration that is included

Parameters:	df – Dataframe 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.TIMESTAMP_KEY -> Column that contains the timestamp
Returns:	Variants dataframe
Return type:	variants_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/>.