{"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":"244b2b50-c634-5442-b612-60acb7a145a7","task_key":"default--v0~2e1~2e0~5fhf--244b2b50-c634-5442-b612-60acb7a145a7","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 244b2b50-c634-5442-b612-60acb7a145a7","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import matplotlib.pyplot as plt\\nimport numpy as np\\nimport scipy.stats as stats\\n# Constants\\nTARGET_VALUE = '332'\\nARRAY = np.array([['0', '1', '2'], ['a', 'bb', 'ccc'], ['332', '33', '2'], ['33', '22', '332']])\\ndef task_func(target_value=TARGET_VALUE, array=ARRAY):\\n\",\"complete_prompt\":\"import matplotlib.pyplot as plt\\nimport numpy as np\\nimport scipy.stats as stats\\n\\n# Constants\\nTARGET_VALUE = '332'\\nARRAY = np.array([['0', '1', '2'], ['a', 'bb', 'ccc'], ['332', '33', '2'], ['33', '22', '332']])\\n\\n\\ndef task_func(target_value=TARGET_VALUE, array=ARRAY):\\n    \\\"\\\"\\\"\\n    Finds the row indices in a numpy array where the first cell matches target_value \\\"332\\\"\\n    Performs statistical analysis on these indices and plots their distribution.\\n    Return 'N/A' for all stats if no target value found.\\n\\n    Parameters:\\n    - target_value (str): The target value. Default value is '332'\\n    - array (np.ndarray): The input array\\n\\n    Returns:\\n    tuple: A tuple with mean, variance, skewness, and kurtosis of the indices, or\\n           'N/A' if statistical analysis cannot be performed.\\n\\n    Requirements:\\n    - numpy\\n    - scipy.stats\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> task_func()\\n    (2.0, 'N/A', 'N/A', 'N/A')\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Finds the row indices in a numpy array where the first cell matches target_value \\\"332\\\" Performs statistical analysis on these indices and plots their distribution. Return 'N/A' for all stats if no target value found.\\nThe function should output with:\\n    tuple: A tuple with mean, variance, skewness, and kurtosis of the indices, or\\n    'N/A' if statistical analysis cannot be performed.\\nYou should write self-contained code starting with:\\n```\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\nimport scipy.stats as stats\\n# Constants\\nTARGET_VALUE = '332'\\nARRAY = np.array([['0', '1', '2'], ['a', 'bb', 'ccc'], ['332', '33', '2'], ['33', '22', '332']])\\ndef task_func(target_value=TARGET_VALUE, array=ARRAY):\\n```\",\"libs\":\"['numpy', 'matplotlib', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}