Should rand, count, etc. use DataFrames directly?

[mykelk]

We have changed some of the code to use Table, which wraps DataFrame. It has the field potential. Should tables be interpreted solely as representations of potentials (in this case probability distributions)? Or should we have one Table type that holds all kinds of tables, e.g., samples, counts, weighted samples, conditional probability tables, etc.? And, if so, should we rename potential to something else (perhaps, df)?

I'd especially like to know what @tawheeler and @hamzaelsaawy think. Let me know and I'll implement it over the next few days.