{"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":"afe43bf9-da05-5c1e-acd0-0d16ab3ee8e0","task_key":"default--v0~2e1~2e0~5fhf--afe43bf9-da05-5c1e-acd0-0d16ab3ee8e0","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf afe43bf9-da05-5c1e-acd0-0d16ab3ee8e0","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport seaborn as sns\\ndef task_func(goals, penalties):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport seaborn as sns\\n\\n\\ndef task_func(goals, penalties):\\n    \\\"\\\"\\\"\\n    Visualize the distribution of goals and penalties for a number of teams and return the data as a\\n    DataFrame with colomns 'Team', 'Goals' and 'Penalties'.\\n\\n    Parameters:\\n    - goals (dict): A dictionary where keys are team names and values are numbers of goals scored.\\n    - penalties (dict): A dictionary where keys are team names and values are numbers of penalties incurred.\\n\\n    Returns:\\n    tuple: A tuple containing:\\n        - DataFrame: A pandas DataFrame with the goals and penalties for the teams.\\n        - Axes: A seaborn pairplot visualization of goals and penalties distribution for the teams.\\n\\n    Requirements:\\n    - pandas\\n    - seaborn\\n\\n    Example:\\n    >>> goals = {'Team A': 3, 'Team B': 2, 'Team C': 1, 'Team D': 0, 'Team E': 2}\\n    >>> penalties = {'Team A': 1, 'Team B': 0, 'Team C': 2, 'Team D': 3, 'Team E': 1}\\n    >>> df, plot = task_func(goals, penalties)\\n    >>> print(df)\\n         Team  Goals  Penalties\\n    0  Team A      3          1\\n    1  Team B      2          0\\n    2  Team C      1          2\\n    3  Team D      0          3\\n    4  Team E      2          1\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Visualize the distribution of goals and penalties for a number of teams and return the data as a DataFrame with colomns 'Team', 'Goals' and 'Penalties'.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    DataFrame: A pandas DataFrame with the goals and penalties for the teams.\\n    Axes: A seaborn pairplot visualization of goals and penalties distribution for the teams.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport seaborn as sns\\ndef task_func(goals, penalties):\\n```\",\"libs\":\"['pandas', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}