{"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":"9514f7e2-96d8-5483-8cba-524822cf61ac","task_key":"default--v0~2e1~2e0~5fhf--9514f7e2-96d8-5483-8cba-524822cf61ac","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 9514f7e2-96d8-5483-8cba-524822cf61ac","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import matplotlib.pyplot as plt\\nimport seaborn as sns\\ndef task_func(dataframe, target_value='332'):\\n\",\"complete_prompt\":\"import matplotlib.pyplot as plt\\nimport seaborn as sns\\n\\n\\ndef task_func(dataframe, target_value='332'):\\n    \\\"\\\"\\\"\\n    Searches a given DataFrame for occurrences of a specified target value and visualizes these occurrences using a heatmap.\\n\\n    Parameters:\\n    - dataframe (pd.DataFrame): The input DataFrame to search.\\n    - target_value (str, optional): The value to search for in the DataFrame. Defaults to '332'.\\n\\n    Returns:\\n    - tuple: A tuple containing:\\n        - pd.DataFrame: A DataFrame with Boolean values indicating the presence of the target value in the input DataFrame.\\n        - matplotlib.axes._axes.Axes: The Axes object of the heatmap.\\n\\n    Requirements:\\n    - matplotlib.pyplot\\n    - seaborn\\n\\n    Example:\\n    >>> import pandas as pd\\n    >>> df = pd.DataFrame({\\n    ...     'Column1': ['0', 'a', '332', '33'],\\n    ...     'Column2': ['1', 'bb', '33', '22'],\\n    ...     'Column3': ['2', 'ccc', '2', '332']\\n    ... })\\n    >>> mask, ax = task_func(df, '332')\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Searches a given DataFrame for occurrences of a specified target value and visualizes these occurrences using a heatmap.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    pd.DataFrame: A DataFrame with Boolean values indicating the presence of the target value in the input DataFrame.\\n    matplotlib.axes._axes.Axes: The Axes object of the heatmap.\\nYou should write self-contained code starting with:\\n```\\nimport matplotlib.pyplot as plt\\nimport seaborn as sns\\ndef task_func(dataframe, target_value='332'):\\n```\",\"libs\":\"['matplotlib', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}