{"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":"4190e38b-eac2-506d-bfb2-2b55c7b4e8f0","task_key":"default--v0~2e1~2e0~5fhf--4190e38b-eac2-506d-bfb2-2b55c7b4e8f0","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 4190e38b-eac2-506d-bfb2-2b55c7b4e8f0","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\ndef task_func(df):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\n\\ndef task_func(df):\\n    \\\"\\\"\\\"\\n    Standardize the 'age' and 'income' columns for each group by 'id' in a Pandas DataFrame, and return the standardized DataFrame.\\n\\n    Parameters:\\n    df (DataFrame): A pandas DataFrame with columns ['id', 'age', 'income'].\\n\\n    Returns:\\n    DataFrame: The pandas DataFrame after standardizing 'age' and 'income' columns.\\n\\n    Raises:\\n    - This function will raise ValueError if the DataFrame does not have the 'id', 'age', and 'income' columns.\\n\\n    Requirements:\\n    - pandas\\n    - sklearn.preprocessing.StandardScaler\\n\\n    Example:\\n    >>> df = pd.DataFrame({ 'id': [1, 1, 2, 2, 3, 3], 'age': [25, 26, 35, 36, 28, 29], 'income': [50000, 60000, 70000, 80000, 90000, 100000]})\\n    >>> df_standardized = task_func(df)\\n    >>> print(df_standardized.iloc[0]['age'] == 25)\\n    False\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Standardize the 'age' and 'income' columns for each group by 'id' in a Pandas DataFrame, and return the standardized DataFrame.\\nThe function should raise the exception for: This function will raise ValueError if the DataFrame does not have the 'id', 'age', and 'income' columns.\\nThe function should output with:\\n    DataFrame: The pandas DataFrame after standardizing 'age' and 'income' columns.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom sklearn.preprocessing import StandardScaler\\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":[]}