Is a Dataframe Just a Table? (2019) [pdf]
> What should we make of it?<p>People are idiots! (I am sorry to say that, I don't really mean it, I empathize, everyone sometimes is.)<p>Yes, dataframe is pretty much just a table. (And yes, GraphQL is a poor reinvention of SQL.) However, to be fair, there are different considerations. Database needs to know things like storage constraints and foreign keys (so you have many different column types), when you're doing just analytics (i.e. pandas), you pretty much only need two types - number and (trimmed) string (and sometimes a datetime, but that's just conveniently formatted number). (I think SAS got that right.)<p>Anyway, I think the way out of this mess is to have a functional, Haskell-like language for processing tables (not necessarily Turing complete) that would subsume declarativness of SQL, and that could be compiled into different targets. The language would basically specify some (limited, so recursion in that language would not be allowed) processing of tables (of known types), and you could then compose these processing pieces, or integrate them with custom processing in other language.<p>I understand why people hate SQL, it is on some level hard to write and compose. I think a correctly designed functional language would help here. Or maybe just tear LINQ out of the .NET ecosystem.