{"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":"7ec69a5e-51b7-52c4-8676-d9b9ad2deaf1","task_key":"default--v0~2e1~2e0~5fhf--7ec69a5e-51b7-52c4-8676-d9b9ad2deaf1","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 7ec69a5e-51b7-52c4-8676-d9b9ad2deaf1","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from sklearn.decomposition import PCA\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\n# Constants\\nN_COMPONENTS = 2\\ndef task_func(L):\\n\",\"complete_prompt\":\"from sklearn.decomposition import PCA\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\n\\n# Constants\\nN_COMPONENTS = 2\\n\\n\\ndef task_func(L):\\n    \\\"\\\"\\\"\\n    Convert a list of lists 'L' into a 2D numeric array, apply PCA to it and return the PCA result and scatter plot.\\n    \\n    Requirements:\\n    - numpy\\n    - sklearn.decomposition\\n    - matplotlib.pyplot\\n\\n    Parameters:\\n    L (list of lists): A list of lists where each sublist contains integers.\\n    \\n    Returns:\\n    tuple: A tuple containing the PCA result (numpy array) and the scatter plot (matplotlib Axes object).\\n\\n    Example:\\n    >>> pca_result, plot = task_func([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\\n    >>> type(pca_result)\\n    <class 'numpy.ndarray'>\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Convert a list of lists 'L' into a 2D numeric array, apply PCA to it and return the PCA result and scatter plot.\\nThe function should output with:\\n    tuple: A tuple containing the PCA result (numpy array) and the scatter plot (matplotlib Axes object).\\nYou should write self-contained code starting with:\\n```\\nfrom sklearn.decomposition import PCA\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\n# Constants\\nN_COMPONENTS = 2\\ndef task_func(L):\\n```\",\"libs\":\"['numpy', 'matplotlib', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}