FAQ

Is this what you want:


x <- read.table(text = "X1 X2 X3 Y1 Y2 Y3
+ 1232 357 23 0 9871 72
+ 0 71 9 811 795 743
+ 43 919 1111 0 76 14", header = TRUE)
x
     X1 X2 X3 Y1 Y2 Y3
1 1232 357 23 0 9871 72
2 0 71 9 811 795 743
3 43 919 1111 0 76 14
# create indices of columns that start with the same character
indx <- split(seq(ncol(x)), substring(colnames(x), 1, 1))
names(indx) <- NULL # remove names so output not messed up

result <- lapply(indx, function(a){
+ row_sum <- rowSums(x[, a])
+ x[row_sum < 100, a] <- 0
+ x[, a]
+ })
# combine back together
do.call(cbind, result)
     X1 X2 X3 Y1 Y2 Y3
1 1232 357 23 0 9871 72
2 0 0 0 811 795 743
3 43 919 1111 0 0 0




Jim Holtman
Data Munger Guru


What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.


On Fri, Nov 6, 2015 at 5:40 AM, Assa Yeroslaviz wrote:

Hi,

I have a data frame with multiple columns, which are belong to several
groups
like that:
X1 X2 X3 Y1 Y2 Y3
1232 357 23 0 9871 72
0 71 9 811 795 743
43 919 1111 0 76 14

I would like to filter such rows out, where the sums in one group is lower
than a specifc value. For example, I would like to set all the values in a
group of cloums to zero, if the sum in one group is less than 100
In my example table I would like to set the values in the second row for
the three X-columns to 0, so that the table looks like that:

X1 X2 X3 Y1 Y2 Y3
1232 357 23 0 9871 72
0 0 0 811 795 743
43 919 1111 0 0 0

the same apply also for the Y-values in the last column.
Is there a more efficient way of doing it than going row by row and use the
apply function on each of the subgroups I have in the columns?

thanks
Assa

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