Calculating subtotals in R

OK. Assuming your data are in a data frame named foo:

> head(foo)
             date mcode      mname ycode yname   yissue bsent breturn tsent
417572 2010/07/28 45740 ENDPOINT A  5772  XMAG 20100800     7       0     7
417573 2010/07/31 45740 ENDPOINT A  5772  XMAG 20100800     0       0     0
417574 2010/08/04 45740 ENDPOINT A  5772  XMAG 20100800     0       0     0
417575 2010/08/14 45740 ENDPOINT A  5772  XMAG 20100800     0       0     0
417576 2010/08/26 45740 ENDPOINT A  5772  XMAG 20100800     0       4     0
417577 2010/07/28 45741 ENDPOINT L  5772  XMAG 20100800     2       0     2
       treturn csales
417572       0      0
417573       0      1
417574       0      1
417575       0      1
417576       0      0
417577       0      0

Then this will do the aggregation of the numeric columns in your data:

> aggregate(cbind(bsent, breturn, tsent, treturn, csales) ~ yname, data = foo, 
+           FUN = sum)
  yname bsent breturn tsent treturn csales
1  XMAG    14       8    14       0      6
2  YMAG    11       6    11       6      5

That was using the snippet of data you included in your Q. I used the formula interface to aggregate(), which is a bit nicer in this instance because you don't need all the foo$ bits on the variable names you wish the aggregate. If you have missing data (NA)in your full data set, then you'll need add an extra argument na.rm = TRUE which will get passed to sum(), like so:

> aggregate(cbind(bsent, breturn, tsent, treturn, csales) ~ yname, data = foo, 
+           FUN = sum, na.rm = TRUE)

Or the plyr library, which is easily extensible to other data classes:

> library(plyr)
> result.2 <- ddply(df$a, .(df$b), sum)
> result.2
  df.b V1
1 down 30
2   up 25