Use python:Use the convenience function from the screenshot to create a plot for clip_threshold = 2. This should require only one line of code import matplotlib.pyplot as pltimport randomimport numpy as npdef clipped_hist(df, clip_threshold =1):newData =[x for x in df if x > clip_threshold]return newDatanp.random.:.seed(42)data = [random.gauss(0, 1) for i in range(1000)]data_len1clip_threshold = -1len(data)%3Ddata =clipped_hist(data, clip_threshold)data len2 =len(data)title ="The values clipped+ str(data_len1data_len2) +The value clipping threshold" + str(clip_threshold)plt.hist(data)plt.title(title)plt.show()

import matplotlib.pyplot as plt import random import numpy as np def clipped_hist(df,…

Answered: Use python: Use the convenience…

Use python: Use the convenience function from the screenshot to create a plot for clip_threshold = 2. This should require only one line of code

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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Question

Use python:

Use the convenience function from the screenshot to create a plot for clip_threshold = 2. This should require only one line of code

import matplotlib.pyplot as plt
import random
import numpy as np
def clipped_hist(df, clip_threshold =
1):
newData =
[x for x in df if x > clip_threshold]
return newData
np.random.:
.seed(42)
data = [random.gauss(0, 1) for i in range(1000)]
data_len1
clip_threshold = -1
len(data)
%3D
data =
clipped_hist(data, clip_threshold)
data len2 =
len(data)
title =
"The values clipped
+ str(data_len1
data_len2) +
The value clipping threshold
" + str(clip_threshold)
plt.hist(data)
plt.title(title)
plt.show()

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