{"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":"010aebf5-3bc5-58ec-8400-667dd389afaa","task_key":"default--v0~2e1~2e0~5fhf--010aebf5-3bc5-58ec-8400-667dd389afaa","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 010aebf5-3bc5-58ec-8400-667dd389afaa","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nimport itertools\\ndef task_func(data_list):\\n\",\"complete_prompt\":\"import numpy as np\\nimport itertools\\n\\ndef task_func(data_list):\\n    \\\"\\\"\\\"\\n    Unzips a list of tuples and calculates the mean of the numeric values for \\n    each position.\\n\\n    The function accepts a list of tuples, where each tuple consists of \\n    alphanumeric values. It unzips the tuples, and calculates the mean of \\n    numeric values at each position using numpy, where non numeric values are\\n    ignores. If all values at a position are non numeric, the mean at this\\n    position is set to be np.nan.\\n    If the provided tuples have different number of entries, missing values are \\n    treated as zeros.\\n\\n    Parameters:\\n    - data_list (list of tuples): The data to process, structured as a list of tuples. Each tuple can contain alphanumeric values.\\n\\n    Returns:\\n    - list: A list of mean values for each numeric position across the tuples. Non-numeric positions are ignored.\\n            An empty list is returned if the input list (data_list) is empty.\\n\\n    Requirements:\\n    - numpy\\n    - itertools\\n\\n    Example:\\n    >>> task_func([('a', 1, 2), ('b', 2, 3), ('c', 3, 4), ('d', 4, 5), ('e', 5, 6)])\\n    [nan, 3.0, 4.0]\\n    >>> task_func([(1, 'a', 2), ('a', 3, 5), ('c', 1, -2)])\\n    [1.0, 2.0, 1.6666666666666667]\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Unzips a list of tuples and calculates the mean of the numeric values for each position. The function accepts a list of tuples, where each tuple consists of alphanumeric values. It unzips the tuples, and calculates the mean of numeric values at each position using numpy, where non numeric values are ignores. If all values at a position are non numeric, the mean at this position is set to be np.nan. If the provided tuples have different number of entries, missing values are treated as zeros.\\nThe function should output with:\\n    list: A list of mean values for each numeric position across the tuples. Non-numeric positions are ignored.\\n    An empty list is returned if the input list (data_list) is empty.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nimport itertools\\ndef task_func(data_list):\\n```\",\"libs\":\"['numpy', 'itertools']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}