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BigCodeBench / BigCodeBench v0.1.0_hf 42748ac8-0870-5b0e-ae55-6782acacf9ec

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

from random import choice
import numpy as np
import pandas as pd


# Constants
TEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']
PENALTIES_COSTS = [100, 200, 300, 400, 500]


def task_func(goals, penalties, teams=TEAMS, penalties_costs=PENALTIES_COSTS):
    """
    Generates a performance report DataFrame for teams, detailing goals and penalties. For each team, the function fetches
    goal and penalty counts, calculates 'Penalties Cost' using a random multiplier from a predefined list, and computes
    a 'Performance Score' as the non-negative difference between goals and penalties. Return a Dataframe with colomns 'Team',
    'Goals', 'Penalties', 'Penalties Cost' and 'Performance Score'.

    Parameters:
    - goals (dict): Team names as keys, numbers of goals scored as values.
    - penalties (dict): Team names as keys, numbers of penalties incurred as values.
    - teams (list, optioanl): input teams. Default value is ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']
    - penalties_costs (list, optional): input penalties_costs. Default value is [100, 200, 300, 400, 500].

    Returns:
    - pd.DataFrame: DataFrame with Team, Goals, Penalties, Penalties Cost, Performance Score.

    Requirements:
    - pandas
    - numpy
    - random.choice

    Example:
    >>> goals = {'Team A': 3, 'Team B': 2}
    >>> penalties = {'Team A': 1, 'Team B': 0}
    >>> report = task_func(goals, penalties)
    """

instruct prompt

Generates a performance report DataFrame for teams, detailing goals and penalties. For each team, the function fetches goal and penalty counts, calculates 'Penalties Cost' using a random multiplier from a predefined list, and computes a 'Performance Score' as the non-negative difference between goals and penalties. Return a Dataframe with colomns 'Team', 'Goals', 'Penalties', 'Penalties Cost' and 'Performance Score'.
The function should output with:
    pd.DataFrame: DataFrame with Team, Goals, Penalties, Penalties Cost, Performance Score.
You should write self-contained code starting with:

Code

from random import choice
import numpy as np
import pandas as pd
# Constants
TEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']
PENALTIES_COSTS = [100, 200, 300, 400, 500]
def task_func(goals, penalties, teams=TEAMS, penalties_costs=PENALTIES_COSTS):

code prompt

Code

from random import choice
import numpy as np
import pandas as pd
# Constants
TEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']
PENALTIES_COSTS = [100, 200, 300, 400, 500]
def task_func(goals, penalties, teams=TEAMS, penalties_costs=PENALTIES_COSTS):

entry point

task_func

libs

  • pandas
  • numpy
  • random

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Source and history

task_id
42748ac8-0870-5b0e-ae55-6782acacf9ec
task_key
default--v0~2e1~2e0~5fhf--42748ac8-0870-5b0e-ae55-6782acacf9ec
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import