Conditional merging in R & if then statement

1) just because you don't use sqldf doesn't make it better. merge only does the join, not the conditions, so you have to apply them after merge. Untested (you should provide a complete example):

result <- merge ( detail, pdetail, by=TDATE, suffixes=c(".a",".b") )
result <- subset ( result, STIM.a >= STIM.b and STIM.a <=MAXTIM.b ) 

You can add a select argument to subset to remove the pdetail columns.

2) if is different than ifelse ... read the Introduction to R document, and/or read the help pages on if and ifelse.
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1)I am wandering how the following SQL statement can be written in R
language
w/o using sqldf:
create table  detail2 as
select a.*
from   detail a,
      pdetail b
where a.TDATE=b.TDATE
and    (a.STIM >= b.STIM and a.STIM <=b.MAXTIM)

2) when try if then in R it only applies to the 1st row & not to whole
dataset like in SAS. How do you get round that?
in SAS:

data summary;
 set all1;
 if entry='a:prop' then pctexec=stkful/stocks*100;
run;



Thanks in advance for your help.



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1)I am wandering how the following SQL statement can be written in R language
w/o using sqldf:
create table  detail2 as
select a.*
from   detail a,
      pdetail b
where a.TDATE=b.TDATE
and    (a.STIM >= b.STIM and a.STIM <=b.MAXTIM)

2) when try if then in R

You need to provide code that shows what you did. If you had the output of 

dat <- merge(a, b, by=TDATE)

You could then limit your data depending on the names of the columns and whether MATIM was a duplicate name in "a" and "b" with something along the lines of

subset(dat, STIM.x >= STIM.y & STIM.s <=MAXTIM.y)

it only applies to the 1st row

Yes, that is how "if" is used in R. You need to educate yourself about R rather than assuming the similar words are necessarily the same function. read:

?"if"
?ifelse

& not to whole
dataset like in SAS. How do you get round that?
in SAS:

data summary;
 set all1;
 if entry='a:prop' then pctexec=stkful/stocks*100;
run;

David Winsemius, MD
Alameda, CA, USA