{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"7fb4f839-585d-5078-88ba-b1ca7ae738b5","task_key":"default--v0~2e1~2e0~5fhf--7fb4f839-585d-5078-88ba-b1ca7ae738b5","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 7fb4f839-585d-5078-88ba-b1ca7ae738b5","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from random import randint, seed\\nimport matplotlib.pyplot as plt\\nimport pandas as pd\\n# Constants (they can be overridden with default parameters)\\nTEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']\\nPENALTY_COST = 1000  # in dollars\\ndef task_func(goals, penalties, teams=TEAMS, penalty_cost=PENALTY_COST, rng_seed=None):\\n\",\"complete_prompt\":\"from random import randint, seed\\nimport matplotlib.pyplot as plt\\nimport pandas as pd\\n\\n\\n# Constants (they can be overridden with default parameters)\\nTEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']\\nPENALTY_COST = 1000  # in dollars\\n\\n\\ndef task_func(goals, penalties, teams=TEAMS, penalty_cost=PENALTY_COST, rng_seed=None):\\n    \\\"\\\"\\\"\\n    Generate a Dataframe to show the football match results of teams 'Team' with random goals 'Goals' and\\n    penalties 'Penalty Cost', and create a bar plot of the results. Penalties are converted into fines according to the\\n    penalty costs.\\n\\n    Parameters:\\n    - goals (int): The maximum number of goals a team can score in a match.\\n    - penalties (int): The maximum number of penalties a team can receive in a match.\\n    - teams (list of str, optional): A list of team names. Default is ['Team A', 'Team B', 'Team C', 'Team D', 'Team E'].\\n    - penalty_cost (int, optional): Cost of a penalty in dollars. Default is 1000.\\n    - rng_seed (int, optional): Random seed for reproducibility. Default is None.\\n\\n    Returns:\\n    - DataFrame: A pandas DataFrame containing columns for teams, their goals, and penalty costs.\\n    - Axes: A matplotlib Axes object representing the bar plot of the results.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib.pyplot\\n    - random\\n\\n    Example:\\n    >>> seed(42)  # Setting seed for reproducibility\\n    >>> df, ax = task_func(5, 3, rng_seed=42)\\n    >>> isinstance(df, pd.DataFrame) and 'Team' in df.columns and 'Goals' in df.columns and 'Penalty Cost' in df.columns\\n    True\\n    >>> all(df['Goals'] <= 5) and all(df['Penalty Cost'] <= 3000)  # Goals and penalties are within expected range\\n    True\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate a Dataframe to show the football match results of teams 'Team' with random goals 'Goals' and penalties 'Penalty Cost', and create a bar plot of the results. Penalties are converted into fines according to the penalty costs.\\nThe function should output with:\\n    DataFrame: A pandas DataFrame containing columns for teams, their goals, and penalty costs.\\n    Axes: A matplotlib Axes object representing the bar plot of the results.\\nYou should write self-contained code starting with:\\n```\\nfrom random import randint, seed\\nimport matplotlib.pyplot as plt\\nimport pandas as pd\\n# Constants (they can be overridden with default parameters)\\nTEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']\\nPENALTY_COST = 1000  # in dollars\\ndef task_func(goals, penalties, teams=TEAMS, penalty_cost=PENALTY_COST, rng_seed=None):\\n```\",\"libs\":\"['pandas', 'random', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}