Source code for pm4py.statistics.start_activities.polars.get

'''
    PM4Py – A Process Mining Library for Python
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'''
from pm4py.util.constants import CASE_CONCEPT_NAME
from pm4py.util.xes_constants import DEFAULT_NAME_KEY
from pm4py.util import exec_utils
from pm4py.util import constants
from enum import Enum
from typing import Optional, Dict, Any, Union
import polars as pl


[docs] class Parameters(Enum): ATTRIBUTE_KEY = constants.PARAMETER_CONSTANT_ATTRIBUTE_KEY ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY START_TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY CASE_ID_KEY = constants.PARAMETER_CONSTANT_CASEID_KEY MAX_NO_POINTS_SAMPLE = "max_no_of_points_to_sample" KEEP_ONCE_PER_CASE = "keep_once_per_case"
[docs] def get_start_activities( lf: pl.LazyFrame, parameters: Optional[Dict[Union[str, Parameters], Any]] = None, ) -> Dict[str, int]: """ Get start activities count Parameters ----------- lf Polars LazyFrame parameters Parameters of the algorithm, including: Parameters.CASE_ID_KEY -> Case ID column in the dataframe Parameters.ACTIVITY_KEY -> Column that represents the activity Returns ----------- startact_dict Dictionary of start activities along with their count """ if parameters is None: parameters = {} case_id_glue = exec_utils.get_param_value( Parameters.CASE_ID_KEY, parameters, CASE_CONCEPT_NAME ) activity_key = exec_utils.get_param_value( Parameters.ACTIVITY_KEY, parameters, DEFAULT_NAME_KEY ) # Get the first activity for each case start_activities_df = ( lf.group_by(case_id_glue) .agg(pl.col(activity_key).first().alias("start_activity")) .select("start_activity") .group_by("start_activity") .count() .collect() ) # Convert to dictionary startact_dict = dict( zip( start_activities_df["start_activity"].to_list(), start_activities_df["count"].to_list() ) ) return startact_dict