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BigCodeBench / BigCodeBench v0.1.0_hf 20049650-6774-5bfc-adf3-88d1f3729ea8

Problem

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

complete prompt

import random
from collections import Counter

def task_func(values, weights, n_samples):
    """
    Sample random numbers based on a given weighted distribution and return a histogram of the samples.

    Parameters:
    - values (list): List of values to be sampled from.
    - weights (list): List of weights corresponding to the values.
    - n_samples (int): Number of samples to be drawn.

    Returns:
    - histogram (dict): A histogram as a dictionary with the values as keys and counts as values.

    Requirements:
    - collections.Counter
    - random

    Example:
    >>> random.seed(42)
    >>> task_func([1, 2, 3], [3, 2, 1], 1000)
    {2: 342, 1: 480, 3: 178}
    """

instruct prompt

Sample random numbers based on a given weighted distribution and return a histogram of the samples.
The function should output with:
    histogram (dict): A histogram as a dictionary with the values as keys and counts as values.
You should write self-contained code starting with:

Code

import random
from collections import Counter
def task_func(values, weights, n_samples):

code prompt

Code

import random
from collections import Counter
def task_func(values, weights, n_samples):

entry point

task_func

libs

  • collections
  • random

Discussion

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Source and history

task_id
20049650-6774-5bfc-adf3-88d1f3729ea8
task_key
default--v0~2e1~2e0~5fhf--20049650-6774-5bfc-adf3-88d1f3729ea8
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import