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BigCodeBench / BigCodeBench v0.1.0_hf e51b1e96-dc77-5f65-abab-6b8f436be635

Problem

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

complete prompt

import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
from itertools import chain


def task_func(L):
    '''
    Convert a list of lists 'L' into a flattened list of integers, then fit a normal distribution to the data 
    and plot a histogram with the fitted normal distribution overlay.

    Requirements:
    - numpy
    - itertools.chain
    - scipy.stats.norm
    - matplotlib.pyplot

    Parameters:
    L (list of lists): A nested list where each inner list contains integers.

    Returns:
    matplotlib.axes._axes.Axes: Axes object with the plotted histogram and normal distribution overlay.

    Example:
    >>> ax = task_func([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
    '''

instruct prompt

Convert a list of lists 'L' into a flattened list of integers, then fit a normal distribution to the data and plot a histogram with the fitted normal distribution overlay.
The function should output with:
    matplotlib.axes._axes.Axes: Axes object with the plotted histogram and normal distribution overlay.
You should write self-contained code starting with:

Code

import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
from itertools import chain
def task_func(L):

code prompt

Code

import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
from itertools import chain
def task_func(L):

entry point

task_func

libs

  • matplotlib
  • numpy
  • itertools
  • scipy

Discussion

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Source and history

task_id
e51b1e96-dc77-5f65-abab-6b8f436be635
task_key
default--v0~2e1~2e0~5fhf--e51b1e96-dc77-5f65-abab-6b8f436be635
task_revision_id
1
config / split
default / v0.1.0_hf

Official source

initial import