{"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":"ecf539c6-fddd-50ad-95e0-4a070c1a2f2d","task_key":"default--v0~2e1~2e0~5fhf--ecf539c6-fddd-50ad-95e0-4a070c1a2f2d","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf ecf539c6-fddd-50ad-95e0-4a070c1a2f2d","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport random\\ndef task_func(data, columns=['Name', 'Age', 'Occupation'], fill_missing=False, num_range=(0, 100), seed=None):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport random\\n\\ndef task_func(data, columns=['Name', 'Age', 'Occupation'], fill_missing=False, num_range=(0, 100), seed=None):\\n    \\\"\\\"\\\"\\n    Create a Pandas DataFrame from a list of tuples, each representing a row.\\n    Tuples of unequal lengths are allowed, and missing elements are filled with None.\\n    Optionally, missing numeric values can be filled with random data.\\n\\n    Parameters:\\n    data (list of tuples): Each tuple contains the data for each row.\\n                           Elements in tuples represent values corresponding to the columns parameter.\\n    columns (list of str): List of column names for the DataFrame.\\n                           Defaults to ['Name', 'Age', 'Occupation'].\\n    fill_missing (bool): If True, fill missing numeric values with random data.\\n                         Defaults to False.\\n    num_range (tuple): Range (min, max) of random numbers for filling missing values.\\n                       Defaults to (0, 100).\\n    seed (int): Optional seed for random number generator for reproducibility.\\n                Defaults to None.\\n\\n    Returns:\\n    DataFrame: A pandas DataFrame with specified columns.\\n               Missing elements are represented as None or filled with random data.\\n\\n    Requirements:\\n    - pandas\\n    - random\\n\\n    Example:\\n    >>> data = [('John', 25, 'Engineer'), ('Alice', ), ('Bob', )]\\n    >>> df = task_func(data, fill_missing=True, num_range=(0, 10), seed=42)\\n    >>> print(df)\\n        Name   Age Occupation\\n    0   John  25.0   Engineer\\n    1  Alice  10.0       None\\n    2    Bob   1.0       None\\n\\n    >>> data = [('Mango', 20), ('Apple', ), ('Banana', )]\\n    >>> df = task_func(data, columns=['Fruit', 'Quantity'], fill_missing=False, seed=42)\\n    >>> print(df)\\n        Fruit  Quantity\\n    0   Mango      20.0\\n    1   Apple       NaN\\n    2  Banana       NaN\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Create a Pandas DataFrame from a list of tuples, each representing a row. Tuples of unequal lengths are allowed, and missing elements are filled with None. Optionally, missing numeric values can be filled with random data. >>> data = [('Mango', 20), ('Apple', ), ('Banana', )] >>> df = task_func(data, columns=['Fruit', 'Quantity'], fill_missing=False, seed=42) >>> print(df) Fruit  Quantity 0   Mango      20.0 1   Apple       NaN 2  Banana       NaN\\nThe function should output with:\\n    DataFrame: A pandas DataFrame with specified columns.\\n    Missing elements are represented as None or filled with random data.\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport random\\ndef task_func(data, columns=['Name', 'Age', 'Occupation'], fill_missing=False, num_range=(0, 100), seed=None):\\n```\",\"libs\":\"['pandas', 'random']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}