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BigCodeBench / BigCodeBench v0.1.0_hf 7b1c913d-f0c0-59a3-b7dc-383f49acedb6

Problem

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complete prompt

import numpy as np
import itertools


def task_func(data_list, file_name):
    """
    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.

    Parameters:
    - data_list (list of tuples): A list containing tuples of the form (string, numeric, numeric, ...)
    - file_name (str): The name of the text file to store the mean values.

    Returns:
    - list: A list of mean values calculated from the numerical data in the tuples.

    Requirements:
    - numpy
    - itertools

    Example:
    >>> data = [('a', 1, 2), ('b', 2, 3), ('c', 3, 4), ('d', 4, 5), ('e', 5, 6)]
    >>> task_func(data, 'mean_values.txt')
    [3.0, 4.0]
    >>> with open('mean_values.txt') as file:
    ...    txt_content = file.readlines()
    >>> print(txt_content)
    ['Position 1: 3.0\\n', 'Position 2: 4.0\\n']
    >>> data_list=[('hi', 'test', -12, 4), ('hallo', 1.2, 'test'), ('hola', -3, 34, 12.1)]
    >>> task_func(data_list, 'test.txt')
    [-0.9, 11.0, 8.05]
    >>> with open('test.txt') as file:
    ...     txt_content = file.readlines()
    >>> print(txt_content)
    ['Position 1: -0.9\\n', 'Position 2: 11.0\\n', 'Position 3: 8.05\\n']
    """

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.
The function should output with:
    list: A list of mean values calculated from the numerical data in the tuples.
You should write self-contained code starting with:

Code

import numpy as np
import itertools
def task_func(data_list, file_name):

code prompt

Code

import numpy as np
import itertools
def task_func(data_list, file_name):

entry point

task_func

libs

  • numpy
  • itertools

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Official source

initial import