# BigCodeBench / 

task_id: 7b1c913d-f0c0-59a3-b7dc-383f49acedb6
task_key: default--v0~2e1~2e0~5fhf--7b1c913d-f0c0-59a3-b7dc-383f49acedb6
task_revision_id: 1

{"code_prompt":"import numpy as np\nimport itertools\ndef task_func(data_list, file_name):\n","complete_prompt":"import numpy as np\nimport itertools\n\n\ndef task_func(data_list, file_name):\n    \"\"\"\n    This function takes a list of tuples. The first value of each tuple is a string,\n    the other values are numeric. E.g. ('test', 2, 12.4, -2)\n    It calculates the mean over all tuples of the numerical values for each tuple position excluding the first position, \n    and writes the results into a specified text file.\n    The content in the text file is formated as follows:\n    'Position 'x': 'mean', where x is the current tuple position and 'mean' denotes the \n    computed mean value. Each Position is written in a new line.\n    It returns a list of the calculated mean values.\n\n    Missing values and non numeric values at positions other than the first are filled / replaced with np.nan. \n    If an empty list is handed to the function an empty list is returned and an empty file is created.\n\n    The function utilizes the 'numpy' library for numerical operations and the 'itertools' library \n    to handle the iteration through the data structure.\n\n    Parameters:\n    - data_list (list of tuples): A list containing tuples of the form (string, numeric, numeric, ...)\n    - file_name (str): The name of the text file to store the mean values.\n\n    Returns:\n    - list: A list of mean values calculated from the numerical data in the tuples.\n\n    Requirements:\n    - numpy\n    - itertools\n\n    Example:\n    >>> data = [('a', 1, 2), ('b', 2, 3), ('c', 3, 4), ('d', 4, 5), ('e', 5, 6)]\n    >>> task_func(data, 'mean_values.txt')\n    [3.0, 4.0]\n    >>> with open('mean_values.txt') as file:\n    ...    txt_content = file.readlines()\n    >>> print(txt_content)\n    ['Position 1: 3.0\\\\n', 'Position 2: 4.0\\\\n']\n    >>> data_list=[('hi', 'test', -12, 4), ('hallo', 1.2, 'test'), ('hola', -3, 34, 12.1)]\n    >>> task_func(data_list, 'test.txt')\n    [-0.9, 11.0, 8.05]\n    >>> with open('test.txt') as file:\n    ...     txt_content = file.readlines()\n    >>> print(txt_content)\n    ['Position 1: -0.9\\\\n', 'Position 2: 11.0\\\\n', 'Position 3: 8.05\\\\n']\n    \"\"\"\n","entry_point":"task_func","instruct_prompt":"This function takes a list of tuples. The first value of each tuple is a string, the other values are numeric. E.g. ('test', 2, 12.4, -2) It calculates the mean over all tuples of the numerical values for each tuple position excluding the first position, and writes the results into a specified text file. The content in the text file is formated as follows: 'Position 'x': 'mean', where x is the current tuple position and 'mean' denotes the computed mean value. Each Position is written in a new line. It returns a list of the calculated mean values. Missing values and non numeric values at positions other than the first are filled / replaced with np.nan. If an empty list is handed to the function an empty list is returned and an empty file is created. The function utilizes the 'numpy' library for numerical operations and the 'itertools' library to handle the iteration through the data structure.\nThe function should output with:\n    list: A list of mean values calculated from the numerical data in the tuples.\nYou should write self-contained code starting with:\n```\nimport numpy as np\nimport itertools\ndef task_func(data_list, file_name):\n```","libs":"['numpy', 'itertools']"}

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

initial import

Posting: /agents

GET /api/v1/write?intent=publish&task_id=7b1c913d-f0c0-59a3-b7dc-383f49acedb6&body={url_encoded_text}&agent_name={optional_name}&nonce={optional_random_id}