{"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":"9e5bebcd-7f2e-5cc8-8b58-dae4fec42db5","task_key":"default--v0~2e1~2e0~5fhf--9e5bebcd-7f2e-5cc8-8b58-dae4fec42db5","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 9e5bebcd-7f2e-5cc8-8b58-dae4fec42db5","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom scipy.spatial import distance\\nimport matplotlib.pyplot as plt\\ndef task_func(a, b):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom scipy.spatial import distance\\nimport matplotlib.pyplot as plt\\n\\n\\ndef task_func(a, b):\\n    \\\"\\\"\\\"\\n    Calculate the Euclidean distance between two lists, create a Pandas DataFrame from these lists\\n    with indices 'A' and 'B', and then draw the values with a line displaying the Euclidean distance.\\n\\n    Parameters:\\n    a (list): A list of numbers.\\n    b (list): Another list of numbers.\\n\\n    Returns:\\n    float: The computed Euclidean distance between the two lists.\\n    pd.DataFrame: A DataFrame containing the two lists as columns.\\n    matplotlib.axes.Axes: The generated plot's Axes object.\\n\\n    Requirements:\\n    - pandas\\n    - scipy.spatial\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> euclidean_distance, df, ax = task_func([1, 2, 3], [2, 3, 4])\\n    >>> print(euclidean_distance)\\n    1.7320508075688772\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Calculate the Euclidean distance between two lists, create a Pandas DataFrame from these lists with indices 'A' and 'B', and then draw the values with a line displaying the Euclidean distance.\\nThe function should output with:\\n    float: The computed Euclidean distance between the two lists.\\n    pd.DataFrame: A DataFrame containing the two lists as columns.\\n    matplotlib.axes.Axes: The generated plot's Axes object.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom scipy.spatial import distance\\nimport matplotlib.pyplot as plt\\ndef task_func(a, b):\\n```\",\"libs\":\"['pandas', '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":[]}