Prompt: In python, modify the function below to plot a Gaussian distribution. Code: import matplotlib.pyplot as plt import random import numpy as np from scipy.stats import norm import seaborn as sns def clipped_hist(df, clip_threshold): newData = [x for x in df if x < clip_threshold] return newData np.random.seed(30) data = [random.gauss(0, 1) for i in range(24)] data_len1 = len(data) clip_threshold = 1.0 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()
Prompt: In python, modify the function below to plot a Gaussian distribution. Code: import matplotlib.pyplot as plt import random import numpy as np from scipy.stats import norm import seaborn as sns def clipped_hist(df, clip_threshold): newData = [x for x in df if x < clip_threshold] return newData np.random.seed(30) data = [random.gauss(0, 1) for i in range(24)] data_len1 = len(data) clip_threshold = 1.0 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()
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
Prompt: In python, modify the function below to plot a Gaussian distribution.
Code:
import matplotlib.pyplot as plt
import random
import numpy as np
from scipy.stats import norm
import seaborn as sns
def clipped_hist(df, clip_threshold):
newData = [x for x in df if x < clip_threshold]
return newData
np.random.seed(30)
data = [random.gauss(0, 1) for i in range(24)]
data_len1 = len(data)
clip_threshold = 1.0
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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