{"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":"944302cd-98a9-5740-aeb0-af84cc3cb6c0","task_key":"default--v0~2e1~2e0~5fhf--944302cd-98a9-5740-aeb0-af84cc3cb6c0","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 944302cd-98a9-5740-aeb0-af84cc3cb6c0","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(list_of_lists):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\n\\ndef task_func(list_of_lists):\\n    \\\"\\\"\\\"\\n    Generate a list of pandas Series objects, where each Series is indexed by the elements of a sub-list from `list_of_lists`.\\n    Each Series contains unique integers starting from 1 and going up to the length of the respective sub-list. These integers\\n    are shuffled randomly to create a unique ordering for each Series.\\n\\n    Parameters:\\n    - list_of_lists (list of list): This parameter is expected to be a list where each element is itself a list.\\n      These inner lists are used as indices for the Series objects. Each inner list represents the index of one Series.\\n\\n    Returns:\\n    - series_list (list of pandas.Series): This function returns a list. Each element in this list is a pandas Series object.\\n      The Series objects are indexed by the elements of the sub-lists provided in `list_of_lists`. The values in each Series\\n      are unique integers that are randomly shuffled.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n\\n    Example:\\n    - Here's an example demonstrating how to use this function:\\n      >>> import numpy as np\\n      >>> np.random.seed(0)  # Setting a seed for reproducibility of the example\\n      >>> series = task_func([['x', 'y', 'z'], ['a', 'b', 'c']])\\n      >>> for s in series: print(s)\\n      x    3\\n      y    2\\n      z    1\\n      dtype: int64\\n      a    3\\n      b    1\\n      c    2\\n      dtype: int64\\n\\n    Note:\\n    - The function uses numpy's random shuffle, which modifies the sequence in-place. Therefore, each call to the function\\n      may produce different Series values unless the random seed is set beforehand.\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate a list of pandas Series objects, where each Series is indexed by the elements of a sub-list from `list_of_lists`. Each Series contains unique integers starting from 1 and going up to the length of the respective sub-list. These integers are shuffled randomly to create a unique ordering for each Series.\\nNote that: The function uses numpy's random shuffle, which modifies the sequence in-place. Therefore, each call to the function may produce different Series values unless the random seed is set beforehand.\\nThe function should output with:\\n    series_list (list of pandas.Series): This function returns a list. Each element in this list is a pandas Series object.\\n    The Series objects are indexed by the elements of the sub-lists provided in `list_of_lists`. The values in each Series\\n    are unique integers that are randomly shuffled.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(list_of_lists):\\n```\",\"libs\":\"['pandas', 'numpy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}