Suppose I have a dataset with a header row.
ds = Dataset[AssociationThread[{"x", "y", "z"}, #] & /@ RandomReal[{0, 1}, {10, 3}]]; I want to construct the following dataset of means and variances. Note the header row and the stub column.)
Dataset[<|"mean" -> Normal@ds[Mean], "var" -> Normal@ds[Variance]|>] How can I construct that with a single query on ds (an no use of Normal)?
The query ds[<|"mean" -> Mean[#], "var" -> Variance[#]|> &] should give you the dataset you need, though the output doesn't format nicely for some reason. The formatting can be fixed by throwing an extra Dataset at it:
Dataset @ ds[<|"mean" -> Mean[#], "var" -> Variance[#]|> &] 
Dataset @ ds[<|"mean" -> Mean, "var" -> Variance|>] $\endgroup$ Dataset to get what I want, and I confess that I do not understand why this changes anything. (I.e., the underlying association structure seems to be identical, but for some reason the type system information is different and forces the different display. What is the underlying principle?) $\endgroup$ Dataset at it" could help. Why does this matter? (I.e., what is the underlying principle?) $\endgroup$ Dataset, the final type is determined by type inferencing. With it, the type is determined by type deduction. Both use heuristics but, empirically, type deduction tends to yield better results. These issues are discussed at more length in (143551) and (87479). $\endgroup$