Distribution of outcomes in dice experiments

Question

So I wrote a short Python function to plot distribution outcome of dice experiments. It\'s working fine but when I run for example dice(1,5000) or dice(10

Answer 1

According to a sample of your code, the issue is a plotting problem, not a computational one, which is why you are seeing the correct mean. As you can see, the following image shows five bars, the last one being twice the size of the others:

Notice also that the bars are labeled on the left, and there is therefore no "6" bar. This has to do with what plt.hist means by bins:

If bins is a sequence, it defines the bin edges, including the left edge of the first bin and the right edge of the last bin; in this case, bins may be unequally spaced. All but the last (righthand-most) bin is half-open.

So to specify bin edges, you probably want something more like

plt.hist(np.ravel(result), bins=np.arange(0.5, 7.5, 1))

And the result:

Unasked Questions

If you want to simulate N * n data points, you can use numpy directly. Replace your original initialization of result and the for loop with any of the following lines:

result = (np.random.uniform(size=(n, N)) * 6 + 1).astype(int)
result = np.random.uniform(1.0. 7.0, size=(n, N)).astype(int)
result = np.random.randint(1, 7, size=(n, N))

The last line is preferable in terms of efficiency and accuracy.

Another possible improvement is in how you compute the histogram. Right now, you are using plt.hist, which calls np.histogram and plt.bar. For small integers like you have, np.bincount is arguably a much better binning technique:

count = np.bincount(result.ravel())[1:]
plt.bar(np.arange(1, 7), count)

Notice that this also simplifies the plotting since you specify the centers of the bars directly, instead of having plt.hist guess it for you.