{"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":"070d0f5f-16c9-5d83-ad2f-bdc1ea275b81","task_key":"default--v0~2e1~2e0~5fhf--070d0f5f-16c9-5d83-ad2f-bdc1ea275b81","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 070d0f5f-16c9-5d83-ad2f-bdc1ea275b81","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(file_path=\\\"data.csv\\\", columns=[\\\"A\\\", \\\"B\\\", \\\"C\\\"]):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\n\\ndef task_func(file_path=\\\"data.csv\\\", columns=[\\\"A\\\", \\\"B\\\", \\\"C\\\"]):\\n    \\\"\\\"\\\"\\n    Read a CSV file into a Pandas DataFrame, convert numeric values into floats,and draw a line chart of data in the specified columns.\\n    In addition, compute the cube-root of the data.\\n\\n    Parameters:\\n    - file_path (str): Path to the CSV file. Default is 'data.csv'.\\n    - columns (list of str): List of column names from the data to plot.\\n                             Default is ['A', 'B', 'C'].\\n\\n    Returns:\\n    tuple: A tuple containing:\\n        - DataFrame: A pandas DataFrame of the data in the CSV file.\\n        - Axes: A matplotlib Axes object showing the plotted data.\\n        - Series: A pandas Series containing the cube-root of the data.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n\\n    Example:\\n    >>> df, ax, croot = task_func('path_to_csv.csv', ['Column1', 'Column2', 'Column3'])\\n    >>> df\\n       Column1  Column2  Column3\\n    0      1.0      2.0      3.0\\n    1      4.0      5.0      6.0\\n    >>> ax\\n    <matplotlib.axes._axes.Axes object at 0x7f24b00f4a90>\\n    >>> croot\\n    0    1.0\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Read a CSV file into a Pandas DataFrame, convert numeric values into floats,and draw a line chart of data in the specified columns. In addition, compute the cube-root of the data.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    DataFrame: A pandas DataFrame of the data in the CSV file.\\n    Axes: A matplotlib Axes object showing the plotted data.\\n    Series: A pandas Series containing the cube-root of the data.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(file_path=\\\"data.csv\\\", columns=[\\\"A\\\", \\\"B\\\", \\\"C\\\"]):\\n```\",\"libs\":\"['pandas', 'numpy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}