{"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":"22fed0da-fed1-5db8-8cad-5602792c6226","task_key":"default--v0~2e1~2e0~5fhf--22fed0da-fed1-5db8-8cad-5602792c6226","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 22fed0da-fed1-5db8-8cad-5602792c6226","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\ndef task_func(df):\\n\",\"complete_prompt\":\"import pandas as pd\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\n\\ndef task_func(df):\\n    \\\"\\\"\\\"\\n    Perform a linear regression between \\\"age\\\" and \\\"score\\\" in the DataFrame, excluding rows with duplicate names.\\n    Plot the regression line and the scatter plot of the data.\\n\\n    Parameters:\\n    df (DataFrame): The pandas DataFrame containing the data.\\n\\n    Returns:\\n    tuple: A tuple containing the matplotlib.pyplot object and the axes object.\\n\\n    Raises:\\n    - The function will raise a ValueError is input df is not a DataFrame.\\n\\n    Note:\\n    - The function use \\\"Linear Regression\\\" for the plot title.\\n    - The function use \\\"Age\\\" and \\\"Score\\\" as the xlabel and ylabel respectively.\\n\\n    Requirements:\\n    - pandas\\n    - scipy.stats\\n    - matplotlib.pyplot\\n\\n    Example:\\n    >>> data = pd.DataFrame([{'Name': 'Alice', 'Age': 20, 'Score': 70}, {'Name': 'Bob', 'Age': 25, 'Score': 75}, {'Name': 'Eve', 'Age': 30, 'Score': 80}])\\n    >>> plt, ax = task_func(data)\\n    >>> ax.lines[0].get_xdata()[0]\\n    20\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Perform a linear regression between \\\"age\\\" and \\\"score\\\" in the DataFrame, excluding rows with duplicate names. Plot the regression line and the scatter plot of the data.\\nNote that: The function use \\\"Linear Regression\\\" for the plot title. The function use \\\"Age\\\" and \\\"Score\\\" as the xlabel and ylabel respectively.\\nThe function should raise the exception for: The function will raise a ValueError is input df is not a DataFrame.\\nThe function should output with:\\n    tuple: A tuple containing the matplotlib.pyplot object and the axes object.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nfrom scipy import stats\\nimport matplotlib.pyplot as plt\\ndef task_func(df):\\n```\",\"libs\":\"['pandas', '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":[]}