{"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":"c2202bff-ca83-5e7f-b459-553b9642577e","task_key":"default--v0~2e1~2e0~5fhf--c2202bff-ca83-5e7f-b459-553b9642577e","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf c2202bff-ca83-5e7f-b459-553b9642577e","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport seaborn as sns\\ndef task_func(data, column=\\\"c\\\"):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport seaborn as sns\\n\\n\\ndef task_func(data, column=\\\"c\\\"):\\n    \\\"\\\"\\\"\\n    Removes a column from a given data dictionary and creates a heatmap\\n    of the correlation matrix of the remaining data. Non-numeric columns are\\n    excluded from the heatmap. If the data is empty or has no numeric columns,\\n    the function returns None.\\n\\n    Parameters:\\n    - data: The input data dictionary.\\n    - column (str): Name of column to remove. Defaults to \\\"c\\\".\\n\\n    Returns:\\n    - matplotlib.axes._axes.Axes or None: The Axes object of the heatmap\\n      or None if the heatmap is not generated.\\n\\n    Requirements:\\n    - pandas\\n    - seaborn\\n\\n    Example:\\n    >>> task_func({'a': [1, 2, 3], 'b': [4, 5, 6], 'c': [7, 8, 9]})\\n    <Axes: >\\n    >>> task_func(pd.DataFrame({'a': [\\\"foo\\\", \\\"bar\\\"]}))\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Removes a column from a given data dictionary and creates a heatmap of the correlation matrix of the remaining data. Non-numeric columns are excluded from the heatmap. If the data is empty or has no numeric columns, the function returns None.\\nThe function should output with:\\n    matplotlib.axes._axes.Axes or None: The Axes object of the heatmap\\n    or None if the heatmap is not generated.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport seaborn as sns\\ndef task_func(data, column=\\\"c\\\"):\\n```\",\"libs\":\"['pandas', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}