{"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":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"f23fe38e-665d-52a9-ace5-66a649a3215b","task_key":"default--v0~2e1~2e0~5fhf--f23fe38e-665d-52a9-ace5-66a649a3215b","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf f23fe38e-665d-52a9-ace5-66a649a3215b","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom sklearn.linear_model import LinearRegression\\ndef task_func(d, target='z'):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom sklearn.linear_model import LinearRegression\\n\\ndef task_func(d, target='z'):\\n    \\\"\\\"\\\"\\n    Perform linear regression to \\\"x,\\\" \\\"y,\\\" against \\\"z\\\" from a list of dictionaries \\\"d.\\\"\\n\\n    Parameters:\\n    d (list): A list of dictionaries.\\n    target (str): The target variable for the regression.\\n\\n    Returns:\\n    LinearRegression: A LinearRegression model.\\n\\n    Requirements:\\n    - pandas\\n    - sklearn.linear_model.LinearRegression\\n\\n    Examples:\\n    >>> data = [{'x': 1, 'y': 10, 'z': 5}, {'x': 3, 'y': 15, 'z': 6}, {'x': 2, 'y': 1, 'z': 7}]\\n    >>> model = task_func(data)\\n    >>> isinstance(model, LinearRegression)\\n    True\\n\\n    >>> data = [{'x': 4, 'y': 20, 'z': 10}, {'x': 5, 'y': 25, 'z': 15}, {'x': 6, 'y': 5, 'z': 20}]\\n    >>> model = task_func(data, target='y')\\n    >>> isinstance(model, LinearRegression)\\n    True\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Perform linear regression to \\\"x,\\\" \\\"y,\\\" against \\\"z\\\" from a list of dictionaries \\\"d.\\\" >>> data = [{'x': 4, 'y': 20, 'z': 10}, {'x': 5, 'y': 25, 'z': 15}, {'x': 6, 'y': 5, 'z': 20}] >>> model = task_func(data, target='y') >>> isinstance(model, LinearRegression) True\\nThe function should output with:\\n    LinearRegression: A LinearRegression model.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom sklearn.linear_model import LinearRegression\\ndef task_func(d, target='z'):\\n```\",\"libs\":\"['pandas', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}