{"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":"2502c0cd-764f-5515-b778-7fb568737e21","task_key":"default--v0~2e1~2e0~5fhf--2502c0cd-764f-5515-b778-7fb568737e21","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 2502c0cd-764f-5515-b778-7fb568737e21","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nimport pandas as pd\\nfrom scipy.stats import linregress\\ndef task_func(df):\\n\",\"complete_prompt\":\"import numpy as np\\nimport pandas as pd\\nfrom scipy.stats import linregress\\n\\n\\ndef task_func(df):\\n    \\\"\\\"\\\"\\n    Analyze the relationship between two variables in a DataFrame.\\n    The function performs a linear regression on the two variables and adds a 'predicted' column to the DataFrame.\\n\\n    Parameters:\\n    - df (pandas.DataFrame): The input DataFrame with columns 'var1', 'var2'.\\n    \\n    Returns:\\n    - df (pandas.DataFrame): The DataFrame with the added 'predicted' column.\\n\\n    Requirements:\\n    - numpy\\n    - pandas\\n    - scipy\\n\\n    Example:\\n    >>> df = pd.DataFrame({'var1': np.random.randn(10),\\n    ...                    'var2': np.random.randn(10)})\\n    >>> df = task_func(df)\\n    >>> assert 'predicted' in df.columns\\n    >>> assert len(df) == 10\\n    >>> assert len(df.columns) == 3\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Analyze the relationship between two variables in a DataFrame. The function performs a linear regression on the two variables and adds a 'predicted' column to the DataFrame.\\nThe function should output with:\\n    df (pandas.DataFrame): The DataFrame with the added 'predicted' column.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nimport pandas as pd\\nfrom scipy.stats import linregress\\ndef task_func(df):\\n```\",\"libs\":\"['pandas', 'numpy', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}