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()

Python  Write a function named cut_vertices() which returns the list of cut vertices. This output should be given as a set.>>> G={0: set(), 1: {11, 10, 19, 13}, 2: {11, 3, 5}, 3: {9, 2, 12, 17}, 4: {10, 5}, 5: {2, 19, 4, 6}, 6: {12, 5}, 7: {11}, 8: {18}, 9: {10, 3}, 10: {9, 12, 4, 1}, 11: {1, 2, 7}, 12: {10, 3, 6}, 13: {1}, 14: set(), 15: {16}, 16: {15}, 17: {3}, 18: {8}, 19: {1, 5}}>>> >>> cut_vertices(G){11, 1, 3}>>> cut_vertices(C(6))set()>>> cut_vertices(P(6)){2, 3, 4, 5}>>> cut_vertices(S(6)){1}

gcd(5x+7y,2x+3y) = ?

Please answer quickly

In python