Now you are read).r to Poissonize! Suppose you roll N dice where N has the Poisson (12) distribution. For 1 5 i 3 I5, let N,- be the number of times the face with i spots appears. Complete the code cell to simulate the following process independently 100,000 times. - Generate a value of N. - Roll a die that many limes. - Collect the values of N.- for l g i g 6. Your simulation should result in a table counts that has 100,000 rows. But please don't start with 100,000 repetitions; just test out the code for 2 repetitions until you're sure it's working. Then you can change the number of repetitions. The full simulation might take some time to mn. In [23]: # Arr-oy- or' List of the probabilities of the six faces fair'_die_pr'obs = [1;'6, NS, 116, ifs, 116, 1.16] 1? Optional Line in case you wont to generate oLL the vetoes of N at once; deLete if not used counts = Tab1e(['N', 'Ni', 'N2', 'N3', 'N4', 'N5', 'N5']) for x in counts: n = 2 poissoni = stats.poisson.rvs(1f6, size=n) # Use as many Lines as you need or" none counts.append(np.append(poisson) counts .show