{"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":"3dafa5d3-aca6-5ffc-84c3-eeba1fbe1a33","task_key":"default--v0~2e1~2e0~5fhf--3dafa5d3-aca6-5ffc-84c3-eeba1fbe1a33","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 3dafa5d3-aca6-5ffc-84c3-eeba1fbe1a33","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nimport pandas as pd\\ndef task_func(n_rows, remove_cols, columns=['A', 'B', 'C', 'D', 'E'], random_seed=None):\\n\",\"complete_prompt\":\"import numpy as np\\nimport pandas as pd\\n\\n\\ndef task_func(n_rows, remove_cols, columns=['A', 'B', 'C', 'D', 'E'], random_seed=None):\\n    \\\"\\\"\\\"\\n    Generate a DataFrame with columns 'columns' and fill them with random \\n    integer values between 0 and 100. Remove some columns based on the provided indexes.\\n    \\n    Parameters:\\n    n_rows (int): The number of rows in the DataFrame.\\n    remove_cols (list of int): The indices of columns to be removed.\\n    columns (list of str, optional): The columns to be included in the DataFrame. Defaults to ['A', 'B', 'C', 'D', 'E'].\\n    random_seed (int): Seed for the rng. Default is None.\\n\\n    Returns:\\n    DataFrame: The resulting DataFrame after removal of columns.\\n    \\n    Requirements:\\n    - numpy\\n    - pandas\\n    \\n    Example:\\n    >>> df = task_func(10, [1, 3], random_seed=1)\\n    >>> print(df)\\n        A   C   E\\n    0  37  72  75\\n    1   5  64   1\\n    2  76   6  50\\n    3  20  84  28\\n    4  29  50  87\\n    5  87  96  13\\n    6   9  63  22\\n    7  57   0  81\\n    8   8  13  72\\n    9  30   3  21\\n\\n    >>> df = task_func(3, [1, 3], columns=['test', 'rem1', 'apple', 'remove'], random_seed=12)\\n    >>> print(df)\\n       test  apple\\n    0    75      6\\n    1     3     76\\n    2    22     52\\n\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate a DataFrame with columns 'columns' and fill them with random integer values between 0 and 100. Remove some columns based on the provided indexes. >>> df = task_func(3, [1, 3], columns=['test', 'rem1', 'apple', 'remove'], random_seed=12) >>> print(df) test  apple 0    75      6 1     3     76 2    22     52\\nThe function should output with:\\n    DataFrame: The resulting DataFrame after removal of columns.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nimport pandas as pd\\ndef task_func(n_rows, remove_cols, columns=['A', 'B', 'C', 'D', 'E'], random_seed=None):\\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":[]}