{"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":"26c9e1a9-03cc-5d8e-ad8e-39fe41016f5b","task_key":"default--v0~2e1~2e0~5fhf--26c9e1a9-03cc-5d8e-ad8e-39fe41016f5b","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 26c9e1a9-03cc-5d8e-ad8e-39fe41016f5b","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom scipy.stats import skew\\ndef task_func(data_matrix):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom scipy.stats import skew\\n\\n\\ndef task_func(data_matrix):\\n    \\\"\\\"\\\"\\n    Calculate the skew of each row in a 2D data matrix and plot the distribution.\\n\\n    Parameters:\\n    - data_matrix (numpy.array): The 2D data matrix.\\n\\n    Returns:\\n    pandas.DataFrame: A DataFrame containing the skewness of each row. The skweness is stored in a new column which name is 'Skewness'.\\n    matplotlib.axes.Axes: The Axes object of the plotted distribution.\\n\\n    Requirements:\\n    - pandas\\n    - matplotlib.pyplot\\n    - scipy.stats.skew\\n\\n    Example:\\n    >>> import numpy as np\\n    >>> data = np.array([[6, 8, 1, 3, 4], [-1, 0, 3, 5, 1]])\\n    >>> df, ax = task_func(data)\\n    >>> print(df)\\n       Skewness\\n    0  0.122440\\n    1  0.403407\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Calculate the skew of each row in a 2D data matrix and plot the distribution.\\nThe function should output with:\\n    pandas.DataFrame: A DataFrame containing the skewness of each row. The skweness is stored in a new column which name is 'Skewness'.\\n    matplotlib.axes.Axes: The Axes object of the plotted distribution.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport matplotlib.pyplot as plt\\nfrom scipy.stats import skew\\ndef task_func(data_matrix):\\n```\",\"libs\":\"['pandas', 'matplotlib', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}