I need to manipulate my array.
I have an array call res which contain all my results.
See just below the input.
RT Max blk24 blk23 mat23 sm23 sm24
1 1.6 261 13 19 19 27 20
2 1.6 284 NA 53 5 99 91
3 1.7 304 NA NA NA 81 NA
4 1.8 305 32 28 28 39 33
5 1.9 322 8 NA NA 36 39
6 1.9 349 NA NA NA 24 17
7 2 389 1 3 NA 50 NA
8 2.1 393 80 70 7 12 71
9 2.1 622 NA NA 15 97 96
10 2.2 705 NA NA NA NA 32
I want to extract my data according to the column name which are here blk, and sm and a criteria of the value by itself.
For blk I propose to do like that:
whereblk<- grep("^Blk", colnames(res))
for (i in 1:length(res)){
tmp.res<-res[which(res[whereblk]>0),]
}
I get an output which give me all the RT and Max value when blk>0.
then I would like to extract the values from sm columns. I want to extract sm values when blk=NA and mat=NA.
do you have any clues?
My desired output is:
RT Max sm23 sm24
1
2
3 1.7 304 81 NA
4
5
6 1.9 349 24 17
7
8
9
10 2.2 705 NA 32
To do it using excel, it is possible to use the followed formula, =IF(COUNTIF(blk:blk,">0"),"-",sm). The problem with excel is, I cannot use it automatically if for example the number of blk column changes.
The difficulty here is to use formula which localizes the column position according to its name. And extract the value according to two criteria which is something I still have not mastered.
If you have any suggestion, you are very welcome.
Here is a dplyr solution.
I am fairly sure @thelatemail provided a solution that will work using just base R in the comments section.
library(dplyr)
df <- read.table(text = "RT Max blk24 blk23 mat23 sm23 sm24
1 1.6 261 13 19 19 27 20
2 1.6 284 NA 53 5 99 91
3 1.7 304 NA NA NA 81 NA
4 1.8 305 32 28 28 39 33
5 1.9 322 8 NA NA 36 39
6 1.9 349 NA NA NA 24 17
7 2 389 1 3 NA 50 NA
8 2.1 393 80 70 7 12 71
9 2.1 622 NA NA 15 97 96
10 2.2 705 NA NA NA NA 32", header = T)
nams <- df %>% select(matches('blk|mat'))
df <- df[apply(nams, 1, function(i) all(is.na(i)))==TRUE,]
df
RT Max blk24 blk23 mat23 sm23 sm24
3 1.7 304 NA NA NA 81 NA
6 1.9 349 NA NA NA 24 17
10 2.2 705 NA NA NA NA 32