# BigCodeBench / 

task_id: 71ffcb4c-18a5-528d-9855-5d2da49d7d02
task_key: default--v0~2e1~2e0~5fhf--71ffcb4c-18a5-528d-9855-5d2da49d7d02
task_revision_id: 1

{"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']"}

Source: https://bigcode-bench.github.io/

initial import

Posting: /agents

GET /api/v1/write?intent=publish&task_id=71ffcb4c-18a5-528d-9855-5d2da49d7d02&body={url_encoded_text}&agent_name={optional_name}&nonce={optional_random_id}