{"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":"9ae89a10-c1f7-5f71-81c6-5f0031d8c956","task_key":"default--v0~2e1~2e0~5fhf--9ae89a10-c1f7-5f71-81c6-5f0031d8c956","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 9ae89a10-c1f7-5f71-81c6-5f0031d8c956","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport random\\nfrom scipy import stats\\ndef task_func(n_data_points=5000, min_value=0.0, max_value=10.0):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport random\\nfrom scipy import stats\\n\\ndef task_func(n_data_points=5000, min_value=0.0, max_value=10.0):\\n    \\\"\\\"\\\"\\n    Generate a random dataset of floating-point numbers within a specified range, \\n    truncate each value to 3 decimal places, and calculate statistical measures (mean, median, mode) of the data.\\n    \\n    Parameters:\\n    n_data_points (int): Number of data points to generate. Default is 5000.\\n    min_value (float): Minimum value range for data points. Default is 0.0.\\n    max_value (float): Maximum value range for data points. Default is 10.0.\\n\\n    Returns:\\n    dict: A dictionary with keys 'mean', 'median', 'mode' and their corresponding calculated values.\\n    \\n    Requirements:\\n    - pandas\\n    - random\\n    - scipy.stats\\n\\n    Example:\\n    >>> random.seed(0)\\n    >>> stats = task_func(1000, 5.0, 5.0)\\n    >>> print(stats)\\n    {'mean': 5.0, 'median': 5.0, 'mode': 5.0}\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate a random dataset of floating-point numbers within a specified range, truncate each value to 3 decimal places, and calculate statistical measures (mean, median, mode) of the data.\\nThe function should output with:\\n    dict: A dictionary with keys 'mean', 'median', 'mode' and their corresponding calculated values.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport random\\nfrom scipy import stats\\ndef task_func(n_data_points=5000, min_value=0.0, max_value=10.0):\\n```\",\"libs\":\"['pandas', 'random', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}