{"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":"fff51c41-5ab0-5669-a93e-f94ebfa102bb","task_key":"default--v0~2e1~2e0~5fhf--fff51c41-5ab0-5669-a93e-f94ebfa102bb","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf fff51c41-5ab0-5669-a93e-f94ebfa102bb","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom sklearn.model_selection import train_test_split\\nfrom sklearn.linear_model import LinearRegression\\n# Constants\\nFEATURES = ['feature '+str(i) for i in range(1, 11)]\\nTARGET = 'target'\\ndef task_func(df):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom sklearn.model_selection import train_test_split\\nfrom sklearn.linear_model import LinearRegression\\n\\n# Constants\\nFEATURES = ['feature '+str(i) for i in range(1, 11)]\\nTARGET = 'target'\\n\\ndef task_func(df):\\n    \\\"\\\"\\\"\\n    Train a linear regression model on a given DataFrame.\\n    \\n    Parameters:\\n    df (DataFrame): The DataFrame with features and target.\\n    \\n    Returns:\\n    LinearRegression: The trained linear regression model.\\n    \\n    Requirements:\\n    - pandas\\n    - sklearn.model_selection.train_test_split\\n    - sklearn.linear_model.LinearRegression\\n    \\n    Raises:\\n    - The function will raise a ValueError is input df is not a DataFrame.\\n\\n    Example:\\n    >>> import numpy as np\\n    >>> np.random.seed(0)\\n    >>> df = pd.DataFrame({'feature ' + str(i): np.random.rand(100) for i in range(1, 11)})\\n    >>> df['target'] = df.apply(lambda row: sum(row), axis=1)\\n    >>> model = task_func(df)\\n    >>> print(len(model.coef_))\\n    10\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Train a linear regression model on a given DataFrame.\\nThe function should raise the exception for: The function will raise a ValueError is input df is not a DataFrame.\\nThe function should output with:\\n    LinearRegression: The trained linear regression model.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom sklearn.model_selection import train_test_split\\nfrom sklearn.linear_model import LinearRegression\\n# Constants\\nFEATURES = ['feature '+str(i) for i in range(1, 11)]\\nTARGET = 'target'\\ndef task_func(df):\\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":[]}