{"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":"444d45eb-e6dd-5f5d-a0ac-59b205d68454","task_key":"default--v0~2e1~2e0~5fhf--444d45eb-e6dd-5f5d-a0ac-59b205d68454","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 444d45eb-e6dd-5f5d-a0ac-59b205d68454","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"from sklearn.preprocessing import MinMaxScaler\\nimport matplotlib.pyplot as plt\\ndef task_func(df):\\n\",\"complete_prompt\":\"from sklearn.preprocessing import MinMaxScaler\\nimport matplotlib.pyplot as plt\\n\\n\\ndef task_func(df):\\n    \\\"\\\"\\\"\\n    Normalize numeric columns in a DataFrame and draw a box plot for each column. Missing values are replaced by column's average.\\n\\n    Parameters:\\n    df (DataFrame): The pandas DataFrame.\\n\\n    Returns:\\n    DataFrame: A pandas DataFrame after normalization.\\n    Axes: A matplotlib Axes displaying a box plot for each column.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n    - sklearn.preprocessing.MinMaxScaler\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> import pandas as pd\\n    >>> import numpy as np\\n    >>> df = pd.DataFrame([[1,2,3],[4,5,6],[7.0,np.nan,9.0]], columns=[\\\"c1\\\",\\\"c2\\\",\\\"c3\\\"])\\n    >>> df, ax = task_func(df)\\n    >>> print(df)\\n        c1   c2   c3\\n    0  0.0  0.0  0.0\\n    1  0.5  1.0  0.5\\n    2  1.0  0.5  1.0\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Normalize numeric columns in a DataFrame and draw a box plot for each column. Missing values are replaced by column's average.\\nThe function should output with:\\n    DataFrame: A pandas DataFrame after normalization.\\n    Axes: A matplotlib Axes displaying a box plot for each column.\\nYou should write self-contained code starting with:\\n```\\nfrom sklearn.preprocessing import MinMaxScaler\\nimport matplotlib.pyplot as plt\\ndef task_func(df):\\n```\",\"libs\":\"['matplotlib', 'sklearn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}