Hello i have been spending time to convert my R tools into Mathematica Packages mainly because i like the functional programming style in Mathematica. In doing so it seems that i run into one conundrum. On one had functional programming suggests to avoid intermediate variables on the other side, a simple example like below clearly shows the potentially significant performance difference when avoiding intermediate (pre-calculated) steps.

do i miss any better solution, or is this really a case where functional style, just looses out ?

dfm is simply a List of Lists with some syntactic sugar dfm["SER"] is a vector of 25k real numbers dfm["serial"] is a vector of 25k string factors

(* check out the add variation as function of model *) uSerial = DeleteDuplicates[dfm["serial"]]; tt = Transpose@{dfm["SER"], dfm["serial"]}; foo[z_] := Select[tt, (Last[#] == z) &][[All, 1]]; serMhdd = Mean /@ Map[foo[#] &, dfm["serial"]] // N; // AbsoluteTiming

uSerial = DeleteDuplicates[dfm["serial"]]; foo[z_] := Select[Transpose@{dfm["detSER"], dfm["serial"]}, (Last[#] == z) &][[All, 1]]; serMhdd = Mean /@ Map[foo[#] &, dfm["serial"]] // N; // AbsoluteTiming

happy holidays, Bernd