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BigCodeBench / BigCodeBench v0.1.0_hf 6c2db582-eee7-5904-8f27-891514d1e65b

Problem

Answer published by the source. Consult the official source to check your work against its answer.

complete prompt

import numpy as np
import random
from scipy import stats


def task_func(list_of_lists, size=5, seed=0):
    """
    Calculate the mean, median, and mode of values in a list of lists.
    If a list is empty, fill it with SIZE (default: 5) random integers between 0 and 100, 
    and then calculate the statistics.
    
    Parameters:
    list_of_lists (list): The list of lists.
    size (int, Optional): The number of random integers to generate. Default is 5.
    seed (int, Optional): Seed value for random number generation. Default is 0.
    
    Returns:
    dict: A dictionary with the mean, median, and mode of the values.
    
    Requirements:
    - numpy
    - random
    - scipy.stats
    
    Example:
    >>> task_func([[1, 2, 3], [], [4, 5, 6]])
    {'mean': 23.454545454545453, 'median': 5.0, 'mode': array([5])}
    """

instruct prompt

Calculate the mean, median, and mode of values in a list of lists. If a list is empty, fill it with SIZE (default: 5) random integers between 0 and 100, and then calculate the statistics.
The function should output with:
    dict: A dictionary with the mean, median, and mode of the values.
You should write self-contained code starting with:

Code

import numpy as np
import random
from scipy import stats
def task_func(list_of_lists, size=5, seed=0):

code prompt

Code

import numpy as np
import random
from scipy import stats
def task_func(list_of_lists, size=5, seed=0):

entry point

task_func

libs

  • random
  • numpy
  • scipy

Discussion

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Source and history

task_id
6c2db582-eee7-5904-8f27-891514d1e65b
task_key
default--v0~2e1~2e0~5fhf--6c2db582-eee7-5904-8f27-891514d1e65b
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import