{"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":"25cf441e-f764-5132-93ad-4729265adc14","task_key":"default--v0~2e1~2e0~5fhf--25cf441e-f764-5132-93ad-4729265adc14","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 25cf441e-f764-5132-93ad-4729265adc14","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(column, data):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\n\\ndef task_func(column, data):\\n    \\\"\\\"\\\"\\n    Analyze a list of sales data, calculate the sum, the mean, the minimum, the maximum of a given column,\\n    and return the bar chart plot for the given column without displaying it.\\n\\n    Parameters:\\n    column (str): The column to analyze. Expected values are ['Product', 'Quantity Sold', 'Total Sales'].\\n    data (list): The sales data. Expected format: [['Product Name', Quantity Sold (int), Total Sales (int)], ...]\\n                 The function checks for data validity in the quantity columns (must not be negative).\\n\\n    Returns:\\n    tuple: A tuple containing:\\n        - dict: A dictionary with the sum, mean, min, max of the column.\\n        - matplotlib.axes.Axes: The Axes object of the plotted bar chart. The bar chart will have Product in its\\n                                x-axis and the title Bar Chart of (column).\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n\\n    Raises:\\n    - ValueError: If the quantity sold or total sales is negative.\\n    \\n    Example:\\n    >>> data = [['Product A', 100, 10000], ['Product B', 150, 15000], ['Product C', 200, 20000]]\\n    >>> stats, plot = task_func('Total Sales', data)\\n    >>> stats\\n    {'sum': 45000, 'mean': 15000.0, 'min': 10000, 'max': 20000}\\n    >>> plot\\n    <Axes: title={'center': 'Bar Chart of Total Sales'}, xlabel='Product'>\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Analyze a list of sales data, calculate the sum, the mean, the minimum, the maximum of a given column, and return the bar chart plot for the given column without displaying it.\\nThe function should raise the exception for: ValueError: If the quantity sold or total sales is negative.\\nThe function should output with:\\n    tuple: A tuple containing:\\n    dict: A dictionary with the sum, mean, min, max of the column.\\n    matplotlib.axes.Axes: The Axes object of the plotted bar chart. The bar chart will have Product in its\\n    x-axis and the title Bar Chart of (column).\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(column, data):\\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":[]}