{"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":"670b3a27-c567-5af3-b221-ad2fac34aa83","task_key":"default--v0~2e1~2e0~5fhf--670b3a27-c567-5af3-b221-ad2fac34aa83","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 670b3a27-c567-5af3-b221-ad2fac34aa83","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\n# Constants\\nCOLUMN_NAMES = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']\\ndef task_func(data):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\n\\n# Constants\\nCOLUMN_NAMES = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']\\n\\n\\ndef task_func(data):\\n    \\\"\\\"\\\"\\n    Computes the average of each row in a provided 2D array and appends these averages as a new column.\\n    Additionally, it plots the averages against their respective row indices.\\n\\n    Parameters:\\n    data (numpy.array): A 2D numpy array with exactly eight columns, corresponding to 'A' through 'H'.\\n\\n    Returns:\\n    tuple: A tuple containing:\\n        - DataFrame: A pandas DataFrame which includes the original data and an additional 'Average' column.\\n        - Axes: A matplotlib Axes object with the plot of row averages.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib\\n\\n    Example:\\n    >>> import numpy as np\\n    >>> data = np.array([[1, 2, 3, 4, 4, 3, 7, 1], [6, 2, 3, 4, 3, 4, 4, 1]])\\n    >>> df, ax = task_func(data)\\n    >>> print(df.to_string(index=False))\\n     A  B  C  D  E  F  G  H  Average\\n     1  2  3  4  4  3  7  1    3.125\\n     6  2  3  4  3  4  4  1    3.375\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Computes the average of each row in a provided 2D array and appends these averages as a new column. Additionally, it plots the averages against their respective row indices.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    DataFrame: A pandas DataFrame which includes the original data and an additional 'Average' column.\\n    Axes: A matplotlib Axes object with the plot of row averages.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\n# Constants\\nCOLUMN_NAMES = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']\\ndef task_func(data):\\n```\",\"libs\":\"['pandas', 'matplotlib']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}