Source code for pm4py.statistics.end_activities.pandas.get

from pm4py.util.constants import CASE_CONCEPT_NAME
from pm4py.util.xes_constants import DEFAULT_NAME_KEY
from pm4py.util.constants import GROUPED_DATAFRAME
from pm4py.util import exec_utils
from pm4py.util import constants
from enum import Enum
from typing import Optional, Dict, Any, Union
from collections import Counter
import pandas as pd




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"





def get_end_activities(
    df: pd.DataFrame,
    parameters: Optional[Dict[Union[str, Parameters], Any]] = None,
) -> Dict[str, int]:
    """
    Get end activities count

    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

    Returns
    -----------
    endact_dict
        Dictionary of end 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
    )
    grouped_df = (
        parameters[GROUPED_DATAFRAME]
        if GROUPED_DATAFRAME in parameters
        else None
    )

    if grouped_df is None:
        grouped_df = df.groupby(case_id_glue, sort=False)

    endact_dict = dict(
        Counter(grouped_df[activity_key].last().to_numpy().tolist())
    )
    return endact_dict