{"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":"noindex","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[]}},"task_id":"9c1f3156-2c6b-5b2a-a42a-ee7d96d72a17","task_key":"default--v0~2e1~2e0~5fhf--9c1f3156-2c6b-5b2a-a42a-ee7d96d72a17","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 9c1f3156-2c6b-5b2a-a42a-ee7d96d72a17","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from datetime import datetime\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\n# Constants\\nDATE_FORMAT = \\\"%Y-%m-%d %H:%M:%S\\\"\\ndef task_func(timestamps):\\n\",\"complete_prompt\":\"from datetime import datetime\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\n\\n# Constants\\nDATE_FORMAT = \\\"%Y-%m-%d %H:%M:%S\\\"\\n\\n\\ndef task_func(timestamps):\\n    \\\"\\\"\\\"\\n    Convert a list of Unix timestamps to date objects, create a Pandas DataFrame, and draw a histogram.\\n    - The date format should be as DATE_FORMAT.\\n    - The DataFrame should have 'Timestamp' and 'Datetime' as column names.\\n    - If the list of timestamps is empty, raise a ValueError with the message \\\"Input list of timestamps is empty\\\".\\n\\n    Parameters:\\n    - timestamps (list): The list of Unix timestamps.\\n\\n    Returns:\\n    - pandas.DataFrame: A pandas DataFrame containing the original Unix timestamps and the converted datetime objects.\\n    - Axes: The Axes object of the histogram plot. The histogram will have 10 bins by default, representing the distribution of the datetime objects.\\n\\n    Raises:\\n    - ValueError(\\\"Input list of timestamps is empty.\\\"): If the list of timestamps is empty.\\n\\n    Requirements:\\n    - datetime\\n    - pandas\\n    - matplotlib.pyplot\\n\\n    Examples:\\n    >>> df, ax = task_func([1347517370, 1475153730, 1602737300])\\n    >>> print(df)\\n        Timestamp             Datetime\\n    0  1347517370  2012-09-13 02:22:50\\n    1  1475153730  2016-09-29 08:55:30\\n    2  1602737300  2020-10-15 00:48:20\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Convert a list of Unix timestamps to date objects, create a Pandas DataFrame, and draw a histogram. - The date format should be as DATE_FORMAT. - The DataFrame should have 'Timestamp' and 'Datetime' as column names. - If the list of timestamps is empty, raise a ValueError with the message \\\"Input list of timestamps is empty\\\".\\nThe function should raise the exception for: ValueError(\\\"Input list of timestamps is empty.\\\"): If the list of timestamps is empty.\\nThe function should output with:\\n    pandas.DataFrame: A pandas DataFrame containing the original Unix timestamps and the converted datetime objects.\\n    Axes: The Axes object of the histogram plot. The histogram will have 10 bins by default, representing the distribution of the datetime objects.\\nYou should write self-contained code starting with:\\n```\\nfrom datetime import datetime\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\n# Constants\\nDATE_FORMAT = \\\"%Y-%m-%d %H:%M:%S\\\"\\ndef task_func(timestamps):\\n```\",\"libs\":\"['pandas', 'datetime', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}