Hello,

Sorry if this process is too simple for this list.  I know I can do it, but
I always read online about how when using R one should always try to avoid
loops and use vectors.  I am wondering if there exists a more "R friendly"
way to do this than to use for loops.

I have a dataset that has a list of "ID"s.  Let's call this dataset "Master"

Each of these "ID"s has an associated DBF file.  The DBF files each have
the same title, and they are each located in a directory path that
includes, as one of the folder names, the "ID".

These DBF files have 2 columns of interest.  One is the "run number" the
other is the "statistic."  I'm interested in the median and 90th percentile
of the "statistic" as well as their corresponding run numbers.  Ultimately,
I want a table that consists of

ID Run_50th Stat_50 Run_90 Stat_90
1AB      5    102010     3         144376
1AC      3    999999     6         999999999

etc.

Where I currently have a dataset that has

ID
1AB
1AC

etc.

And there are several DBF files that are in folders i.e.
"folder1/1AC/folder2/blah.dbf"

This dbf looks like

run   Stat

1      10
2      10
3      999999
4      100000000000
5      100000000
6       9999999999
7      100000000
8     10
9     10
10    10
11     1000000


I know i could do this with a loop, but I can't see the efficient, R way.
 I was hoping that you experienced R programmers could give me some
pointers on the most efficient way to achieve this result.

Sam

	[[alternative HTML version deleted]]

