I have a lot of java data analysis code I have written for processing 400MB
per day of compressed packet sniffer data. I have been playing with R
recently and struggling to understand where the dividing line between
languages like java and R is in terms of which sorts of code in makes sense
to write in each.
It struck me the other day, as I was using excel to manually manipulate
large tables of string and numeric data doing things like table lookup
(using excel's vlookup function) and partitioning a table by the unique
values of a text column to perform sums on different numeric columns within
the partitions (you wouldn't believe the tricks I have stumbled upon to make
excel do things like that over the years) that R seemed to be made for
computations like this. Once that occured to me, I opened "An Introduction
to R" again and saw how easy R's index arrays, match(), and tapply()
functions make all of those operations.
I don't know how obvious that must seem to most of the people on this list,
but I thought I'd offer it up in case anyone else found it to be the key to
unlocking R that I have found it to be.
Thank you, R authors and contributers, for such a fantastic tool. I
absolutely recoiled in horror after cracking a book on Visual Basic for
Excel in one of my previous attempts to automate the manual stuff I have
been doing in excel these past few years. It is so nice to have a system
like R to turn to for this.
Chris Marshall
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