{"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":"d1237107-89e8-510d-bfdf-73fc5cbb5494","task_key":"default--v0~2e1~2e0~5fhf--d1237107-89e8-510d-bfdf-73fc5cbb5494","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf d1237107-89e8-510d-bfdf-73fc5cbb5494","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import seaborn as sns\\nimport matplotlib.pyplot as plt\\ndef task_func(df, target_values=[1, 3, 4]):\\n\",\"complete_prompt\":\"import seaborn as sns\\nimport matplotlib.pyplot as plt\\n\\n\\ndef task_func(df, target_values=[1, 3, 4]):\\n    \\\"\\\"\\\"\\n    Replace all elements in DataFrame columns that do not exist in the target_values array with zeros, and then output the distribution of each column after replacing.\\n    - label each plot as the name of the column it corresponds to.\\n\\n    Parameters:\\n    - df (DataFrame): The input pandas DataFrame.\\n    - target_values (list) : Array of values not to replace by zero.\\n\\n    Returns:\\n    - matplotlib.axes.Axes: The Axes object of the plotted data.\\n\\n    Requirements:\\n    - seaborn\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> import pandas as pd\\n    >>> import numpy as np\\n    >>> np.random.seed(42)\\n    >>> df = pd.DataFrame(np.random.randint(0,10,size=(100, 5)), columns=list('ABCDE'))\\n    >>> print(df.head(2))\\n       A  B  C  D  E\\n    0  6  3  7  4  6\\n    1  9  2  6  7  4\\n    >>> df1, ax = task_func(df)\\n    >>> print(ax)\\n    Axes(0.125,0.11;0.775x0.77)\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Replace all elements in DataFrame columns that do not exist in the target_values array with zeros, and then output the distribution of each column after replacing. - label each plot as the name of the column it corresponds to.\\nThe function should output with:\\n    matplotlib.axes.Axes: The Axes object of the plotted data.\\nYou should write self-contained code starting with:\\n```\\nimport seaborn as sns\\nimport matplotlib.pyplot as plt\\ndef task_func(df, target_values=[1, 3, 4]):\\n```\",\"libs\":\"['matplotlib', 'seaborn']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}