2. In this problem, you will perform K-means clustering manually, with K = 2, on a smallexample with n = 6 observations and p = 2 features. The observations are as follows.(a) Plot the observations.(b) Randomly assign a cluster label to each observation. You can use the np.random.choice()function to do this. Report the cluster labels for each observation. Obs.X1X2114232130344515602064(c) Compute the centroid for each cluster.(d) Assign each observation to the centroid to which it is closest, in terms of Euclidean distance.Report the cluster labels for each observation.(e) Repeat (c) and (d) until the answers obtained stop changing.(f) In your plot from (a), color the observations or mark them by different markers accordingto the cluster labels obtained.

Plotting the Observations: We’ll start by plotting the given observations. The data points are…

Answered: (a) Plot the observations. (b) Randomly…

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(a) Plot the observations. (b) Randomly assign a cluster label to each observation. You can use the np.random.choice() function to do this. Report the cluster labels for each observation.