{"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":"9263cd3e-e610-58d2-9762-d762065202f0","task_key":"default--v0~2e1~2e0~5fhf--9263cd3e-e610-58d2-9762-d762065202f0","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 9263cd3e-e610-58d2-9762-d762065202f0","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from datetime import datetime\\nfrom random import randint\\nimport matplotlib.pyplot as plt\\nimport pandas as pd\\nTEMP_CATEGORIES = ['Cold', 'Normal', 'Hot']\\nFILE_PATH = 'custom_data.csv'\\ndef task_func(hours, file_path=FILE_PATH):\\n\",\"complete_prompt\":\"from datetime import datetime\\nfrom random import randint\\nimport matplotlib.pyplot as plt\\nimport pandas as pd\\n\\n\\nTEMP_CATEGORIES = ['Cold', 'Normal', 'Hot']\\nFILE_PATH = 'custom_data.csv'\\n\\n\\ndef task_func(hours, file_path=FILE_PATH):\\n    \\\"\\\"\\\"\\n    Generate temperature data for the specified number of hours, save it in a CSV file, \\n    and plot the data using matplotlib.\\n    \\n    Parameters:\\n    hours (int): The number of hours for which temperature data is to be generated.\\n    file_path (str, optional): Path where the CSV file will be saved. Defaults to 'temp_data.csv'.\\n    \\n    Returns:\\n    tuple: \\n        - str: The path of the generated CSV file.\\n        - Axes: The plot object for further manipulation or saving.\\n    \\n    Requirements:\\n    - pandas\\n    - datetime\\n    - random\\n    - matplotlib.pyplot\\n    \\n    Data Structure:\\n    The function uses a dictionary to manage the generated temperature data with keys: 'Time', 'Temperature', and 'Category'.\\n    \\n    Example:\\n    >>> file_path, ax = task_func(24)\\n    >>> isinstance(file_path, str)\\n    True\\n    >>> 'custom_data.csv' in file_path\\n    True\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate temperature data for the specified number of hours, save it in a CSV file, and plot the data using matplotlib. Data Structure: The function uses a dictionary to manage the generated temperature data with keys: 'Time', 'Temperature', and 'Category'.\\nThe function should output with:\\n    tuple:\\n    str: The path of the generated CSV file.\\n    Axes: The plot object for further manipulation or saving.\\nYou should write self-contained code starting with:\\n```\\nfrom datetime import datetime\\nfrom random import randint\\nimport matplotlib.pyplot as plt\\nimport pandas as pd\\nTEMP_CATEGORIES = ['Cold', 'Normal', 'Hot']\\nFILE_PATH = 'custom_data.csv'\\ndef task_func(hours, file_path=FILE_PATH):\\n```\",\"libs\":\"['pandas', 'datetime', 'random', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}