{"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":"ba3599ce-ac08-5139-b14d-e5bbdeb17aff","task_key":"default--v0~2e1~2e0~5fhf--ba3599ce-ac08-5139-b14d-e5bbdeb17aff","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf ba3599ce-ac08-5139-b14d-e5bbdeb17aff","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(df, cols):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\n\\ndef task_func(df, cols):\\n    \\\"\\\"\\\"\\n    Standardize specified numeric columns in a dataframe.\\n\\n    Parameters:\\n    df (DataFrame): The dataframe.\\n    cols (list): The columns to standardize.\\n\\n    Returns:\\n    DataFrame: The dataframe with standardized columns.\\n\\n    Raises:\\n    ValueError: If 'df' is not a DataFrame, 'cols' is not a list, or columns in 'cols' don't exist in 'df'.\\n\\n    Requirements:\\n    - pandas\\n    - sklearn.preprocessing.StandardScaler\\n\\n    Example:\\n    >>> np.random.seed(0)\\n    >>> df = pd.DataFrame({'A': np.random.normal(0, 1, 1000), 'B': np.random.exponential(1, 1000)})\\n    >>> df = task_func(df, ['A', 'B'])\\n    >>> print(df.describe())\\n                      A             B\\n    count  1.000000e+03  1.000000e+03\\n    mean  -1.243450e-17 -1.865175e-16\\n    std    1.000500e+00  1.000500e+00\\n    min   -3.040310e+00 -1.024196e+00\\n    25%   -6.617441e-01 -7.183075e-01\\n    50%   -1.293911e-02 -2.894497e-01\\n    75%    6.607755e-01  4.095312e-01\\n    max    2.841457e+00  5.353738e+00\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Standardize specified numeric columns in a dataframe.\\nThe function should raise the exception for: ValueError: If 'df' is not a DataFrame, 'cols' is not a list, or columns in 'cols' don't exist in 'df'.\\nThe function should output with:\\n    DataFrame: The dataframe with standardized columns.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(df, cols):\\n```\",\"libs\":\"['pandas', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}