{"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":"988d644d-56f2-5da1-aeab-43e61c69574f","task_key":"default--v0~2e1~2e0~5fhf--988d644d-56f2-5da1-aeab-43e61c69574f","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 988d644d-56f2-5da1-aeab-43e61c69574f","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import numpy as np\\nimport matplotlib.pyplot as plt\\nfrom scipy.stats import norm\\ndef task_func(df, column, bins=30, density=True, alpha=0.6, color=\\\"g\\\", seed=None):\\n\",\"complete_prompt\":\"import numpy as np\\nimport matplotlib.pyplot as plt\\nfrom scipy.stats import norm\\n\\n\\ndef task_func(df, column, bins=30, density=True, alpha=0.6, color=\\\"g\\\", seed=None):\\n    \\\"\\\"\\\"\\n    Plots a histogram for a specified column of a pandas DataFrame and overlays\\n    it with a fitted normal distribution curve.\\n\\n    Parameters:\\n    - df (pandas.DataFrame): The input DataFrame.\\n    - column (str): The column name for which the histogram is plotted.\\n    - bins (int, optional): Number of bins for the histogram. Defaults to 30.\\n    - density (bool, optional): If True, the histogram is normalized to form a\\n                                probability density. Defaults to True.\\n    - alpha (float, optional): Transparency level for the histogram bars.\\n                               Defaults to 0.6.\\n    - color (str, optional): Color of the histogram bars. Defaults to 'g'.\\n    - seed (int, optional): Seed for the random number generator.\\n                            Defaults to None (not set).\\n\\n    Returns:\\n    - matplotlib.axes._axes.Axes: The matplotlib Axes object with the plot.\\n\\n    Requirements:\\n    - numpy\\n    - matplotlib\\n    - scipy\\n\\n    Example:\\n    >>> np.random.seed(0)\\n    >>> df = pd.DataFrame({'A': np.random.normal(0, 1, 1000)})\\n    >>> ax = task_func(df, 'A')\\n    >>> ax.get_title()\\n    \\\"Normal Fit for 'A'\\\"\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Plots a histogram for a specified column of a pandas DataFrame and overlays it with a fitted normal distribution curve.\\nThe function should output with:\\n    matplotlib.axes._axes.Axes: The matplotlib Axes object with the plot.\\nYou should write self-contained code starting with:\\n```\\nimport numpy as np\\nimport matplotlib.pyplot as plt\\nfrom scipy.stats import norm\\ndef task_func(df, column, bins=30, density=True, alpha=0.6, color=\\\"g\\\", seed=None):\\n```\",\"libs\":\"['numpy', 'matplotlib', 'scipy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}