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In python: Modifydef clipped_hist(df, clip_threshold = 1) to plot a Gaussian distribution on top of a normalized histogram.

In python: Modifydef clipped_hist(df, clip_threshold = 1) to plot a Gaussian distribution on top of a normalized histogram.

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

Modifydef clipped_hist(df, clip_threshold = 1) to plot a Gaussian distribution on top of a normalized histogram.
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()
Transcribed Image Text: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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