{"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":"7c148ef9-f9a5-5cb1-ab3c-ef067b2f7082","task_key":"default--v0~2e1~2e0~5fhf--7c148ef9-f9a5-5cb1-ab3c-ef067b2f7082","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 7c148ef9-f9a5-5cb1-ab3c-ef067b2f7082","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\ndef task_func(num_labels=5, data_range=(0, 1)):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\n\\n\\ndef task_func(num_labels=5, data_range=(0, 1)):\\n    \\\"\\\"\\\"\\n    Generate random numeric data across a specified range for a given number of categories and visualize it with\\n     a stacked bar chart.\\n\\n    Parameters:\\n    num_labels (int): Specifies the number of distinct categories or labels to generate data for. Defaults to 5.\\n    data_range (tuple): Defines the lower and upper bounds for the random data values. Defaults to (0, 1).\\n\\n    Returns:\\n    matplotlib.figure.Figure: A Figure object containing the stacked bar chart of the generated data.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib\\n    - numpy\\n\\n    Example:\\n    >>> fig = task_func()\\n    >>> fig.show()  # This will display the figure with default parameters\\n\\n    >>> fig = task_func(num_labels=3, data_range=(1, 10))\\n    >>> fig.show()  # This will display the figure with three labels and data range from 1 to 10\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generate random numeric data across a specified range for a given number of categories and visualize it with a stacked bar chart. >>> fig = task_func(num_labels=3, data_range=(1, 10)) >>> fig.show()  # This will display the figure with three labels and data range from 1 to 10\\nThe function should output with:\\n    matplotlib.figure.Figure: A Figure object containing the stacked bar chart of the generated data.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\nimport numpy as np\\ndef task_func(num_labels=5, data_range=(0, 1)):\\n```\",\"libs\":\"['pandas', 'numpy', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}