{"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":"2777af49-b29e-50ed-b142-7569c3edb8ac","task_key":"default--v0~2e1~2e0~5fhf--2777af49-b29e-50ed-b142-7569c3edb8ac","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 2777af49-b29e-50ed-b142-7569c3edb8ac","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport itertools\\nimport random\\ndef task_func(colors, states):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport itertools\\nimport random\\n\\n\\ndef task_func(colors, states):\\n    \\\"\\\"\\\"\\n    Generates a pandas DataFrame containing shuffled combinations of provided colors and states.\\n    The DataFrame is formatted so that each column represents a series of unique combinations,\\n    with each combination displayed as \\\"Color:State\\\".\\n\\n    Parameters:\\n    - colors (list): A list of strings representing color names.\\n    - states (list): A list of strings representing state descriptions.\\n\\n    Returns:\\n    - df (pandas.DataFrame): A DataFrame where each cell contains a string of the format \\\"Color:State\\\".\\n      The combinations are distributed across columns, with the number of columns being the lesser\\n      of the lengths of 'colors' and 'states'.\\n\\n    Requirements:\\n    - pandas\\n    - itertools\\n    - random\\n\\n    Note:\\n    - Cartesian product of 'colors' and 'states',\\n    - The number of columns in the resulting DataFrame is determined by the smaller number of elements\\n      in either the 'colors' or 'states' list, ensuring an even distribution without excess empty cells.\\n    - If the number of combinations is not evenly divisible by the number of columns, some columns\\n      will have fewer entries.\\n\\n    Example:\\n    >>> colors = ['Red', 'Blue', 'Green']\\n    >>> states = ['Solid', 'Liquid']\\n    >>> color_state_table = task_func(colors, states)\\n    >>> print(color_state_table)\\n      Color:State 1 Color:State 2\\n    0   Blue:Liquid    Red:Liquid\\n    1    Blue:Solid   Green:Solid\\n    2     Red:Solid  Green:Liquid\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generates a pandas DataFrame containing shuffled combinations of provided colors and states. The DataFrame is formatted so that each column represents a series of unique combinations, with each combination displayed as \\\"Color:State\\\".\\nNote that: Cartesian product of 'colors' and 'states', The number of columns in the resulting DataFrame is determined by the smaller number of elements in either the 'colors' or 'states' list, ensuring an even distribution without excess empty cells. If the number of combinations is not evenly divisible by the number of columns, some columns will have fewer entries.\\nThe function should output with:\\n    df (pandas.DataFrame): A DataFrame where each cell contains a string of the format \\\"Color:State\\\".\\n    The combinations are distributed across columns, with the number of columns being the lesser\\n    of the lengths of 'colors' and 'states'.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport itertools\\nimport random\\ndef task_func(colors, states):\\n```\",\"libs\":\"['pandas', 'random', 'itertools']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}