{"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":"1032b5eb-3502-56ac-b505-a14cfc30590c","task_key":"default--v0~2e1~2e0~5fhf--1032b5eb-3502-56ac-b505-a14cfc30590c","task_revision_id":"2","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 1032b5eb-3502-56ac-b505-a14cfc30590c","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(my_list, seed=42):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\ndef task_func(my_list, seed=42):\\n    \\\"\\\"\\\"\\n    Adds an item \\\"12\\\" to a list 'my_list', simulates sales data for different categories with an optional seed for reproducibility, and returns the data along with a bar plot.\\n    \\n    The sales data is a DataFrame with random sales figures for predefined categories.\\n    The categories are 'Electronics', 'Fashion', 'Home & Kitchen', 'Automotive', 'Sports'.\\n    \\n    Parameters:\\n    my_list (list): The input list.\\n    seed (int, optional): Seed for the random number generator (default is None, which means no seed).\\n    \\n    Returns:\\n    tuple: A tuple containing a pandas DataFrame of simulated sales data and the corresponding matplotlib Axes object.\\n    \\n    Raises:\\n    TypeError: If 'my_list' is not a list.\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n    \\n    Example:\\n    >>> my_list = [1, 2, 3]\\n    >>> data, ax = task_func(my_list, seed=123)\\n    >>> print(data)\\n             Category  Sales\\n    0     Electronics   1395\\n    1         Fashion   1266\\n    2  Home & Kitchen    198\\n    3      Automotive    351\\n    4          Sports   2472\\n    >>> ax.get_title()  # Returns 'Category-wise Sales Data'\\n    'Category-wise Sales Data'\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Adds an item \\\"12\\\" to a list 'my_list', simulates sales data for different categories with an optional seed for reproducibility, and returns the data along with a bar plot. The sales data is a DataFrame with random sales figures for predefined categories. The categories are 'Electronics', 'Fashion', 'Home & Kitchen', 'Automotive', 'Sports'.\\nThe function should raise the exception for: TypeError: If 'my_list' is not a list.\\nThe function should output with:\\n    tuple: A tuple containing a pandas DataFrame of simulated sales data and the corresponding matplotlib Axes object.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(my_list, seed=42):\\n```\",\"libs\":\"['pandas', 'numpy']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}