Suggestion: move DataFrames, plotting into standard distribution

This specific feedback is actually very useful.

Concerning verbosity, I’ve translated the same hflights tutorial to JuliaDB here and I find the syntax reasonably concise. Can you pinpoint specific cases that could be improved/specific suggestions on how to do so? As a caveat, you need a very recent version of JuliaDB and IndexedTables to run the tutorial as most syntax improvements are recent.

Concerning dplyr ggplot2 integration via pipeline (I’m not sure how that’d work exactly as I’m not a R user) the closest I can think of is the @df macro from StatPlots which is fully integrated with the Query/IterableTables framework (though I have some idea to simplify the syntax even further when plotting from a @map statement, but I haven’t quite decided how, I’m curious what @davidanthoff has in mind). There is also GroupedErrors to make plots from data tables if you’re working with grouped data.

See this announcement, though I haven’t focused on Query integration (as ShiftedArrays and Query have different missing data representation): will think about it once there is convergence.

I’d be curious to see how to add rownumber: what does it do exactly? You can use it inside a groupby and it will give you the row numbers of the group as computed inside the larger dataset?

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