{"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":"2da67224-cd6a-5bb5-b126-ab63597b4976","task_key":"default--v0~2e1~2e0~5fhf--2da67224-cd6a-5bb5-b126-ab63597b4976","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 2da67224-cd6a-5bb5-b126-ab63597b4976","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nfrom collections import Counter\\nimport matplotlib.pyplot as plt\\ndef task_func(L):\\n\",\"complete_prompt\":\"import numpy as np\\nfrom collections import Counter\\nimport matplotlib.pyplot as plt\\n\\ndef task_func(L):\\n    \\\"\\\"\\\"\\n    Analyze an \\\"L\\\" list by calculating the mean, median, mode, and standard deviation.\\n    Visualize the data by returning a histogram plot.\\n    \\n    Parameters:\\n    L (list): Input list.\\n    \\n    Returns:\\n    dict: A dictionary with the 'mean', 'median', 'mode', 'std_dev' of 'L, and the 'plot' Axes object.\\n    \\n    Requirements:\\n    - numpy\\n    - collections.Counter\\n    - matplotlib.pyplot\\n    \\n    Example:\\n    >>> L = [1, 2, 3, 4, 5, 6, 7, 8, 9]\\n    >>> stats = task_func(L)\\n    >>> print(stats[\\\"mean\\\"])\\n    5.0\\n    >>> print(stats[\\\"median\\\"])\\n    5.0\\n    >>> print(stats[\\\"mode\\\"])\\n    1\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Analyze an \\\"L\\\" list by calculating the mean, median, mode, and standard deviation. Visualize the data by returning a histogram plot.\\nThe function should output with:\\n    dict: A dictionary with the 'mean', 'median', 'mode', 'std_dev' of 'L, and the 'plot' Axes object.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nfrom collections import Counter\\nimport matplotlib.pyplot as plt\\ndef task_func(L):\\n```\",\"libs\":\"['collections', 'numpy', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}