Hi,

I have a data set which is like this I write as the CSV I import:

Sample;Hole;Feature;Value
1;5;x;4,2334
1;5;y;3,3434
1;5;r;0,1080
1;10;x;5,2526
1;10;y;4,3434
1;10;r;0,1080
....

with 98 sample and 10 different holes. These are measured values.

Now I also have a list of nominel values:

Hole;Feature;Nominel;LSL;USL
5;x;4,25,4,20;4,30
5;y;3,35;3,30;3,40
5;r;0,10;0,07;0,13
10;x;5,25;5,20;5,30
...

If I want to "normalize" the measured values. The results are to be used in
a Sweave file that I plan to reuse for several similar data sets in the
furture.

I have been looking at different approache:
1. do it in a script out side R
2. do it the long and hard way by filtering out all the single holes and
Feature, the on this list subtract the nominel values, and then combine it
back.
3. ?

Any help and guidence apriciated
-- 
Klaus F. Østergaard, <farremosen(at)gmail dot com>

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