{"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":"2b8a7115-8848-5a00-a7f3-5ffb0d4e0d97","task_key":"default--v0~2e1~2e0~5fhf--2b8a7115-8848-5a00-a7f3-5ffb0d4e0d97","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 2b8a7115-8848-5a00-a7f3-5ffb0d4e0d97","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom matplotlib import pyplot as plt\\n# Constants\\nTEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']\\nGOALS_RANGE = (-10, 10)\\ndef task_func(goals, penalties):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom matplotlib import pyplot as plt\\n\\n# Constants\\nTEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']\\nGOALS_RANGE = (-10, 10)\\n\\n\\ndef task_func(goals, penalties):\\n    \\\"\\\"\\\"\\n    Calculates net scores for teams ('Team A' to 'Team E') by subtracting penalties from goals and clips scores to stay\\n    within -10 to 10. Visualizes results with a bar chart showing each team's adjusted scores 'Team' on the x-axis and\\n    score values 'Score' on the y-axis.\\n\\n\\n    Parameters:\\n    - goals (dict): A dictionary where keys are team names and values are the number of goals scored.\\n    - penalties (dict): A dictionary where keys are team names and values are the number of penalties incurred.\\n\\n    Returns:\\n    - DataFrame: A pandas DataFrame with columns 'Team' and 'Score', representing each team's net score.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib\\n\\n    Example:\\n    >>> goals = {'Team A': 5, 'Team B': 3, 'Team C': 1, 'Team D': 0, 'Team E': 4}\\n    >>> penalties = {'Team A': 1, 'Team B': 1, 'Team C': 1, 'Team D': 0, 'Team E': 2}\\n    >>> df = task_func(goals, penalties)\\n    >>> print(df)\\n         Team  Score\\n    0  Team A      4\\n    1  Team B      2\\n    2  Team C      0\\n    3  Team D      0\\n    4  Team E      2\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Calculates net scores for teams ('Team A' to 'Team E') by subtracting penalties from goals and clips scores to stay within -10 to 10. Visualizes results with a bar chart showing each team's adjusted scores 'Team' on the x-axis and score values 'Score' on the y-axis.\\nThe function should output with:\\n    DataFrame: A pandas DataFrame with columns 'Team' and 'Score', representing each team's net score.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom matplotlib import pyplot as plt\\n# Constants\\nTEAMS = ['Team A', 'Team B', 'Team C', 'Team D', 'Team E']\\nGOALS_RANGE = (-10, 10)\\ndef task_func(goals, penalties):\\n```\",\"libs\":\"['pandas', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}