Write a function clipped_hist(df, clip_threshold) that plots a histogram of the data after applying a filter that removes all the data above a maximum value, clip_threshold.The default threshold should be 1.0. The title of the plot should indicate the the number of values clipped and the value of the clipping threshold. Use a list comprehension when manipulating the data. [2] import matplotlib.pyplot as plt import random import numpy as np # For reproducibility np.random.seed (42) # Generate some data with a random normal distribution data = [random.gauss(0, 1) for i in range(1000)] # Plot a histogram of the data plt.hist(data);

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