{"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":"aca8ff4e-44db-5ba5-829a-f82a801dee13","task_key":"default--v0~2e1~2e0~5fhf--aca8ff4e-44db-5ba5-829a-f82a801dee13","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf aca8ff4e-44db-5ba5-829a-f82a801dee13","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from scipy.stats import linregress\\nimport matplotlib.pyplot as plt\\ndef task_func(data, column1, column2):\\n\",\"complete_prompt\":\"from scipy.stats import linregress\\nimport matplotlib.pyplot as plt\\n\\ndef task_func(data, column1, column2):\\n    \\\"\\\"\\\"\\n    Perform a linear regression on two columns of a dataset and record the result.\\n    Additionally, generates a plot representing the original data and the fitted line.\\n\\n    Parameters:\\n    data (DataFrame): The dataset.\\n    column1 (str): The name of the first column.\\n    column2 (str): The name of the second column.\\n\\n    Returns:\\n    tuple: The slope, intercept, r-value, p-value, and standard error of the regression.\\n    Axes: The matplotlib Axes object containing the plot.\\n\\n    Raises:\\n    ValueError: If the specified columns do not exist in the DataFrame.\\n\\n    Requirements:\\n    - scipy.stats\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> data = pd.DataFrame([[14, 25], [1, 22], [7, 8]], columns=['Column1', 'Column2'])\\n    >>> result, ax = task_func(data, 'Column1', 'Column2')\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Perform a linear regression on two columns of a dataset and record the result. Additionally, generates a plot representing the original data and the fitted line.\\nThe function should raise the exception for: ValueError: If the specified columns do not exist in the DataFrame.\\nThe function should output with:\\n    tuple: The slope, intercept, r-value, p-value, and standard error of the regression.\\n    Axes: The matplotlib Axes object containing the plot.\\nYou should write self-contained code starting with:\\n```\\nfrom scipy.stats import linregress\\nimport matplotlib.pyplot as plt\\ndef task_func(data, column1, column2):\\n```\",\"libs\":\"['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":[]}