{"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":"610ce96b-e0f0-5eef-85b0-2335b378a0d4","task_key":"default--v0~2e1~2e0~5fhf--610ce96b-e0f0-5eef-85b0-2335b378a0d4","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 610ce96b-e0f0-5eef-85b0-2335b378a0d4","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import collections\\nimport matplotlib.pyplot as plt\\ndef task_func(data):\\n\",\"complete_prompt\":\"import collections\\nimport matplotlib.pyplot as plt\\n\\n\\ndef task_func(data):\\n    \\\"\\\"\\\"\\n    Combine a list of dictionaries with possibly differing keys (student names) into a single dictionary,\\n    calculate the average score for each student, and return a bar chart of average student scores with\\n    student on the x-axis and average score on the y-axis.\\n\\n    This function handles data with varying dictionary lengths and missing keys by averaging available scores,\\n    ignoring None. If there is any negative score, the function raises ValueError.\\n    Bar colors can be: 'red', 'yellow', 'green', 'blue', 'purple'.\\n\\n    Parameters:\\n    data (list): A list of dictionaries. The keys are student names and the values are scores.\\n\\n    Returns:\\n    ax (matplotlib.axes._axes.Axes or None): A bar chart showing the 'Average Student Scores', with\\n                                             'Student' on the x-axis and 'Average Score' on the y-axis.\\n                                             If data is empty, return None.\\n\\n    Requirements:\\n    - collections\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> data = [{'John': 5, 'Jane': 10, 'Joe': 7},\\\\\\n                {'John': 6, 'Jane': 8, 'Joe': 10},\\\\\\n                {'John': 5, 'Jane': 9, 'Joe': 8},\\\\\\n                {'John': 7, 'Jane': 10, 'Joe': 9}]\\n    >>> ax = task_func(data)\\n    >>> type(ax)\\n    <class 'matplotlib.axes._axes.Axes'>\\n    >>> ax.get_xticklabels()\\n    [Text(0, 0, 'Jane'), Text(1, 0, 'Joe'), Text(2, 0, 'John')]\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Combine a list of dictionaries with possibly differing keys (student names) into a single dictionary, calculate the average score for each student, and return a bar chart of average student scores with student on the x-axis and average score on the y-axis. This function handles data with varying dictionary lengths and missing keys by averaging available scores, ignoring None. If there is any negative score, the function raises ValueError. Bar colors can be: 'red', 'yellow', 'green', 'blue', 'purple'.\\nThe function should output with:\\n    ax (matplotlib.axes._axes.Axes or None): A bar chart showing the 'Average Student Scores', with\\n    'Student' on the x-axis and 'Average Score' on the y-axis.\\n    If data is empty, return None.\\nYou should write self-contained code starting with:\\n```\\nimport collections\\nimport matplotlib.pyplot as plt\\ndef task_func(data):\\n```\",\"libs\":\"['collections', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}