{"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":"e1b903ba-9041-56d5-b70f-7a7375880e4a","task_key":"default--v0~2e1~2e0~5fhf--e1b903ba-9041-56d5-b70f-7a7375880e4a","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf e1b903ba-9041-56d5-b70f-7a7375880e4a","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom random import uniform\\ndef task_func(n_data_points=1000, min_value=0.0, max_value=10.0, column_name='Value'):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom random import uniform\\n\\n\\ndef task_func(n_data_points=1000, min_value=0.0, max_value=10.0, column_name='Value'):\\n    \\\"\\\"\\\"\\n    Generate a random dataset of floating-point numbers, truncate each value to 3 decimal places, then return the generated DataFrame with\\n    the specified column name.\\n\\n    Parameters:\\n    n_data_points (int, optional): The number of data points to generate. Default is 1000.\\n    min_value (float, optional): The minimum value for the generated data. Default is 0.0.\\n    max_value (float, optional): The maximum value for the generated data. Default is 10.0.\\n    column_name (str, optional): The column name in generated DataFrame. Default is 'Value'.\\n\\n\\n    Returns:\\n    DataFrame: A pandas DataFrame with the generated data.\\n    \\n    Requirements:\\n    - pandas\\n    - random.uniform\\n\\n    Example:\\n    >>> random.seed(0)\\n    >>> data = task_func()\\n    >>> data.shape[0]\\n    1000\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate a random dataset of floating-point numbers, truncate each value to 3 decimal places, then return the generated DataFrame with the specified column name.\\nThe function should output with:\\n    DataFrame: A pandas DataFrame with the generated data.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom random import uniform\\ndef task_func(n_data_points=1000, min_value=0.0, max_value=10.0, column_name='Value'):\\n```\",\"libs\":\"['pandas', 'random']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}