Data frame is fairly well defined, but it's a common source of confusion. In a data frame, the columns are of heterogeneous types (string, integer, bool, doubl

Data frame is fairly well defined, but it's a common source of confusion. In a data frame, the columns are of heterogeneous types (string, integer, bool, double, factor or "enum", etc.). In a vector/matrix, every cell has the same type. A short way to understand it is that R and Matlab aren't the same thing. They are not substitutes for one another. In R, the core type is the data frame. In Matlab, it is the matrix, of which a 2D array is a special case. (Both Matlab and R have grown some of the others' functionality, but it's not good at all. You can tell which one is primary.) Another way to say it: Julia at its core isn't an R replacement; it's a Matlab replacement. Apparently, the representation of missing values was a problem for DataFrames.jl. Whether or not individual entries in a vector are "nullable" has a large impact on how you write vectorized mathematical operations and how well it performs. And if you notice that data frames sound like SQL tables, well that's exactly why these Apache projects are converging/overlapping :) They are coming from different points of view, but they have the same underlying data model. One of my slogans is that "R is the only language without the ORM problem", because its native data model matches the data model of a relational database. I'm designing a shell which will feature data frames (eventually, probably not for a year or more): https://github.com/oilshell/oil/wiki/Oil-and-the-R-Language https://github.com/oilshell/oil/wiki/Oil-and-the-R-Language SQL is a very limited language, with essentially no capabilities for abstraction. Writing programs using the relational model in a Turing-complete language like R or Python is very powerful.