{"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":"55eedb03-d3cc-5c03-8ad7-3e3ea85faafb","task_key":"default--v0~2e1~2e0~5fhf--55eedb03-d3cc-5c03-8ad7-3e3ea85faafb","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 55eedb03-d3cc-5c03-8ad7-3e3ea85faafb","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(df, features):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\nfrom sklearn.preprocessing import StandardScaler\\n\\ndef task_func(df, features):\\n    \\\"\\\"\\\"\\n    Standardize the functions in a DataFrame.\\n    The function applies standard scaling to the features.\\n    \\n    Parameters:\\n    - df (pandas.DataFrame): The input DataFrame.\\n    - features (list): The list of features to standardize. May be empty.\\n    \\n    Returns:\\n    - df (pandas.DataFrame): The DataFrame with the standardized features.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n    - scikit-learn\\n\\n    Example:\\n    >>> np.random.seed(42)\\n    >>> df = pd.DataFrame(np.random.randn(20, 3), columns=['a', 'b', 'c'])\\n    >>> df = task_func(df, ['a', 'b'])\\n    >>> df.head(2)\\n              a         b         c\\n    0  0.608932  0.127900  0.647689\\n    1  2.025355  0.031682 -0.234137\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Standardize the functions in a DataFrame. The function applies standard scaling to the features.\\nThe function should output with:\\n    df (pandas.DataFrame): The DataFrame with the standardized features.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(df, features):\\n```\",\"libs\":\"['pandas', 'numpy', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}