{"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":"71ffcb4c-18a5-528d-9855-5d2da49d7d02","task_key":"default--v0~2e1~2e0~5fhf--71ffcb4c-18a5-528d-9855-5d2da49d7d02","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf 71ffcb4c-18a5-528d-9855-5d2da49d7d02","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import pandas as pd\\nimport numpy as np\\ndef task_func(days, random_seed=0):\\n\",\"complete_prompt\":\"import pandas as pd\\nimport numpy as np\\n\\n\\ndef task_func(days, random_seed=0):\\n    \\\"\\\"\\\"\\n    Generates a spending report DataFrame for the given number of days.\\n\\n    This function takes a number of days as input and populates a pandas DataFrame\\n    with fake expenditure data indexed by date. Each day on or after '2023-01-01'\\n    has its own row. The DataFrame has five columns: Groceries, Entertainment, Rent,\\n    Utilities, and Miscellaneous, with their integer values independently randomly\\n    sampled from 0 to 100.\\n\\n    Parameters:\\n    - days (int): Number of days for which the report is to be generated.\\n                  This is used to generate dates starting from '2023-01-01'.\\n                  For example, a 'days' of 2 will generate data for '2023-01-01',\\n                  '2023-01-02'.\\n                  If 0, this function will return a DataFrame with the expected\\n                  columns that is otherwise empty.\\n    - random_seed (int): Numpy random seed for reproducibility. Defaults to 0.\\n\\n    Returns:\\n    - pd.DataFrame: A DataFrame containing spending details for specified days,\\n                    with shape (num_days, 5).\\n\\n    Requirements:\\n    - pandas\\n    - numpy\\n\\n    Example:\\n    >>> df = task_func(5, random_seed=42)\\n    >>> type(df)\\n    <class 'pandas.core.frame.DataFrame'>\\n    >>> df.head(2)\\n                Groceries  Entertainment  Rent  Utilities  Miscellaneous\\n    date                                                                \\n    2023-01-01         51             20    87         52              1\\n    2023-01-02         92             82    99          1             63\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Generates a spending report DataFrame for the given number of days. This function takes a number of days as input and populates a pandas DataFrame with fake expenditure data indexed by date. Each day on or after '2023-01-01' has its own row. The DataFrame has five columns: Groceries, Entertainment, Rent, Utilities, and Miscellaneous, with their integer values independently randomly sampled from 0 to 100.\\nThe function should output with:\\n    pd.DataFrame: A DataFrame containing spending details for specified days,\\n    with shape (num_days, 5).\\nYou should write self-contained code starting with:\\n```\\nimport pandas as pd\\nimport numpy as np\\ndef task_func(days, random_seed=0):\\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":[]}