{"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":"a6ed40ec-70e6-5cbe-8086-9b9d385bd94a","task_key":"default--v0~2e1~2e0~5fhf--a6ed40ec-70e6-5cbe-8086-9b9d385bd94a","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf a6ed40ec-70e6-5cbe-8086-9b9d385bd94a","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(d):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\ndef task_func(d):\\n    \\\"\\\"\\\"\\n    Calculate mean, sum, max, min and standard deviation for the keys \\\"x,\\\" \\\"y\\\" and \\\"z\\\" from a list of dictionaries \\\"d.\\\"\\n    \\n    Parameters:\\n    d (list): A list of dictionaries.\\n\\n    Returns:\\n    dict: A dictionary with keys as 'x', 'y', and 'z' and values as dictionaries of statistics.\\n\\n    Raises:\\n    - ValueError: If input is not a list of dictionaries.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n\\n    Examples:\\n    >>> data = [{'x': 1, 'y': 10, 'z': 5}, {'x': 3, 'y': 15, 'z': 6}, {'x': 2, 'y': 1, 'z': 7}]\\n    >>> task_func(data)\\n    {'x': {'mean': 2.0, 'sum': 6, 'max': 3, 'min': 1, 'std': 0.816496580927726}, 'y': {'mean': 8.666666666666666, 'sum': 26, 'max': 15, 'min': 1, 'std': 5.792715732327589}, 'z': {'mean': 6.0, 'sum': 18, 'max': 7, 'min': 5, 'std': 0.816496580927726}}\\n    >>> task_func([])\\n    {'x': None, 'y': None, 'z': None}\\n    >>> task_func([{'a': 1}])\\n    {'x': None, 'y': None, 'z': None}\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Calculate mean, sum, max, min and standard deviation for the keys \\\"x,\\\" \\\"y\\\" and \\\"z\\\" from a list of dictionaries \\\"d.\\\"\\nThe function should raise the exception for: ValueError: If input is not a list of dictionaries.\\nThe function should output with:\\n    dict: A dictionary with keys as 'x', 'y', and 'z' and values as dictionaries of statistics.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(d):\\n```\",\"libs\":\"['pandas', 'numpy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}