{"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":"4e02abf4-d93f-5b4f-a436-4fc5b8d71d0b","task_key":"default--v0~2e1~2e0~5fhf--4e02abf4-d93f-5b4f-a436-4fc5b8d71d0b","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 4e02abf4-d93f-5b4f-a436-4fc5b8d71d0b","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import seaborn as sns\\nimport numpy as np\\ndef task_func(df):\\n\",\"complete_prompt\":\"import seaborn as sns\\nimport numpy as np\\n\\n\\ndef task_func(df):\\n    \\\"\\\"\\\"\\n    Generates a pair plot from a numeric DataFrame and calculates its covariance matrix.\\n\\n    Parameters:\\n    - df (pandas.DataFrame): A pandas DataFrame with only numeric columns.\\n\\n    Returns:\\n    - tuple:\\n        - covariance_df (pandas.DataFrame): The covariance matrix of the input DataFrame.\\n        - pair_plot (sns.axisgrid.PairGrid): Pair plot of the input DataFrame.\\n\\n    Raises:\\n    - ValueError: If the DataFrame is empty.\\n    - TypeError: If the DataFrame contains non-numeric data types.\\n\\n    Requirements:\\n    - numpy\\n    - seaborn\\n\\n    Examples:\\n    >>> import pandas as pd\\n    >>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9]})\\n    >>> covariance_df, ax = task_func(df)\\n    >>> type(ax)\\n    <class 'seaborn.axisgrid.PairGrid'>\\n    >>> covariance_df\\n         A    B    C\\n    A  1.0  1.0  1.0\\n    B  1.0  1.0  1.0\\n    C  1.0  1.0  1.0\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generates a pair plot from a numeric DataFrame and calculates its covariance matrix.\\nThe function should raise the exception for: ValueError: If the DataFrame is empty. TypeError: If the DataFrame contains non-numeric data types.\\nThe function should output with:\\n    tuple:\\n    covariance_df (pandas.DataFrame): The covariance matrix of the input DataFrame.\\n    pair_plot (sns.axisgrid.PairGrid): Pair plot of the input DataFrame.\\nYou should write self-contained code starting with:\\n```\\nimport seaborn as sns\\nimport numpy as np\\ndef task_func(df):\\n```\",\"libs\":\"['numpy', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}