random-draw | Random live giveaway drawing app | Runtime Evironment library

what additional functionality is provided by scipy library that is not there in numpy?

You can see the additional functionality if you look at the documentation for one of the individual distributions (e.g., beta). The numpy functions only allow drawing random values. The scipy distributions have lots of extra methods for other things, like percentiles, cumulative distribution function, and statistics like the mean and standard deviation.

Some of the information that scipy gives you is not computable directly from the numpy functions. The numpy functions only give you individual randomly-drawn values, but scipy represents the distribution mathematically and can compute some things without actually drawing any values. For instance, many of the stats that the scipy distributions return are computed with exact mathematical formulas. You can see in the source you linked to that, e.g., binom_gen._stats computes the mean, stdev, etc. directly. To find the mean using numpy you'd have to draw a bunch of values (theoretically an infinite number) and compute their mean; scipy does it abstractly without drawing any values. The scipy distributions expose mathematical details of the distributions that aren't available through numpy.