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BigCodeBench / BigCodeBench v0.1.0_hf 6f90de17-3879-567f-bd75-104991833985

Problem

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

complete prompt

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats


def task_func(mean=123456.908, std_dev=1.2, save_plots=False):
    """
    Generate a random sample from a normal distribution, analyze its skewness and kurtosis,
    and create a histogram and a QQ plot to visualize the distribution.

    Parameters:
    - mean (float, optional): Mean of the normal distribution. Defaults to 123456.908.
    - std_dev (float, optional): Standard deviation of the normal distribution. Defaults to 1.2.
    - save_plots (bool, optional): If True, saves the plots to files. Defaults to False.

    Returns:
    - float: Skewness of the sample.
    - float: Kurtosis of the sample.
    - list: Paths to the saved plot files, empty if save_plots is False.

    Requirements:
    - numpy
    - matplotlib.pyplot
    - scipy.stats

    Example:
    >>> np.random.seed(0)
    >>> skewness, kurtosis, plot_paths = task_func(123456.908, 1.2, True)
    >>> print(f'Skewness: {skewness}, Kurtosis: {kurtosis}, Plots: {plot_paths}')
    Skewness: 0.03385895323538189, Kurtosis: -0.04676632447765128, Plots: ['histogram_plot.png', 'qq_plot.png']

    """

instruct prompt

Generate a random sample from a normal distribution, analyze its skewness and kurtosis, and create a histogram and a QQ plot to visualize the distribution.
The function should output with:
    float: Skewness of the sample.
    float: Kurtosis of the sample.
    list: Paths to the saved plot files, empty if save_plots is False.
You should write self-contained code starting with:

Code

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
def task_func(mean=123456.908, std_dev=1.2, save_plots=False):

code prompt

Code

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
def task_func(mean=123456.908, std_dev=1.2, save_plots=False):

entry point

task_func

libs

  • numpy
  • matplotlib
  • scipy

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Source and history

task_id
6f90de17-3879-567f-bd75-104991833985
task_key
default--v0~2e1~2e0~5fhf--6f90de17-3879-567f-bd75-104991833985
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import