Yeah row names are another good example. I've never used them, so I would be inclined to leave them out. But I'm not sure what other people use them for. May

Yeah row names are another good example. I've never used them, so I would be inclined to leave them out. But I'm not sure what other people use them for. Maybe they are used for fast lookup? In other words, its like an index? If you want to retrieve a particular row, it's usually an O(n) scan. But maybe row names are like a limited kind of index and you can retrieve by name in O(1) time. I tend to follow Hadley Wickham's model -- column labels are essential, but I'm pretty sure he would say row names are not in the model? I haven't seen it addressed actually. If I'm understanding correctly the transition matrix example, I think data frames and matrices are vastly different. And it makes sense to have labels for every dimension on matrices, but not data frames. What language are you implementing your data frame library in? I'm curious about both the API and the algorithms. I looked at Hadley's newer dplyr code, and it's mostly in C++., as opposed to plyr which was mostly in R. Are you a R user? If I were doing this (which I may but not for like a year), I would probably use Hadley's API and model the code after his. I'm curious if you have any criticisms of the way he does things. FWIW the summary of using indices is that it changes the computational complexity of an algorithm -- and O(n + m) algorithm can be turned into O(m log n), and this makes an orders of magnitude difference in running time. It's not small difference. I've used this to good effect in real programs. It's more like data preparation than analysis, but that is a big part of what people use data frames for.