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BigCodeBench / BigCodeBench v0.1.0_hf 95263400-ebe6-55fc-91a8-4e2a83c89e75

Problem

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

complete prompt

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


def task_func(matrix):
    """
    Calculate the distribution of the maximum values of each row in the matrix, 
    record the histogram and the estimate of the core density of the distribution, 
    and return the skew, kurtosis, and the histogram plot of the distribution.
    
    Parameters:
    matrix (list): A list of lists representing a matrix.
    
    Returns:
    tuple: The skewness, the kurtosis of the distribution, and the histogram plot (matplotlib Axes object).
    
    Requirements:
    - numpy
    - scipy.stats
    - matplotlib.pyplot
    
    Example:
    >>> skew, kurtosis, ax = task_func([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
    >>> type(ax)
    <class 'matplotlib.axes._axes.Axes'>
    >>> round(skew, 2)
    0.0
    >>> round(kurtosis, 2)
    -1.5
    """

instruct prompt

Calculate the distribution of the maximum values of each row in the matrix, record the histogram and the estimate of the core density of the distribution, and return the skew, kurtosis, and the histogram plot of the distribution.
The function should output with:
    tuple: The skewness, the kurtosis of the distribution, and the histogram plot (matplotlib Axes object).
You should write self-contained code starting with:

Code

import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
def task_func(matrix):

code prompt

Code

import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
def task_func(matrix):

entry point

task_func

libs

  • numpy
  • matplotlib
  • scipy

Discussion

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Source and history

task_id
95263400-ebe6-55fc-91a8-4e2a83c89e75
task_key
default--v0~2e1~2e0~5fhf--95263400-ebe6-55fc-91a8-4e2a83c89e75
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import