{"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":"a30f1971-b990-5349-9038-27d34cd223b3","task_key":"default--v0~2e1~2e0~5fhf--a30f1971-b990-5349-9038-27d34cd223b3","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf a30f1971-b990-5349-9038-27d34cd223b3","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import matplotlib.pyplot as plt\\nimport numpy as np\\nimport pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(a, b, columns=['A', 'B']):\\n\",\"complete_prompt\":\"import matplotlib.pyplot as plt\\nimport numpy as np\\nimport pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\n\\n\\ndef task_func(a, b, columns=['A', 'B']):\\n    \\\"\\\"\\\"\\n    Standardize two lists of numbers using the StandardScaler from sklearn and visualize the standardized values using a bar plot.\\n\\n    Parameters:\\n        a (list): A list of numbers.\\n        b (list): Another list of numbers.\\n        columns (list, optional): Column names for the resulting DataFrame. Defaults to ['A', 'B'].\\n\\n    Returns:\\n        pd.DataFrame: A DataFrame containing the standardized values.\\n        matplotlib.axes.Axes: Axes object of the displayed bar plot.\\n\\n    Requirements:\\n        - numpy\\n        - pandas\\n        - sklearn.preprocessing\\n        - matplotlib.pyplot\\n\\n    Example:\\n        >>> df, ax = task_func([1, 2, 3, 4, 5], [2, 4, 6, 8, 10])\\n        >>> isinstance(df, pd.DataFrame) and isinstance(ax, matplotlib.axes.Axes)\\n        True\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Standardize two lists of numbers using the StandardScaler from sklearn and visualize the standardized values using a bar plot.\\nThe function should output with:\\n    pd.DataFrame: A DataFrame containing the standardized values.\\n    matplotlib.axes.Axes: Axes object of the displayed bar plot.\\nYou should write self-contained code starting with:\\n```\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\nimport pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(a, b, columns=['A', 'B']):\\n```\",\"libs\":\"['pandas', '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":[]}