val - 8 months ago 45

R Question

I'm learning to update column data using this previous post. However, is there a trick for specifying which column should provide the final updated value in case of a conflict. For example, I can combine columns of data as long as only one value exists per row:

`data <- data.frame('a' = c('A','B','C','D','E'),`

'x' = c(NA,NA,3,NA,NA),

'y' = c(1,2,NA,NA,NA),

'z' = c(NA,NA,NA,4,5))

cbind.data.frame(data3[1], mycol=c(na.omit(c(t(data3[, -1])))))

How would I force the value to come from

`newVal`

`data <- data.frame('a' = c('A','B','C','D','E','F'),`

'x' = c(NA,NA,NA,3,NA,NA),

'y' = c(1,2,8,NA,NA,NA),

'z' = c(99,NA,4,NA,4,5))

Answer Source

Use `max.col`

and some matrix indexing (specifying which row/col combination to take):

```
cbind(1:nrow(data), max.col(!is.na(data[-1]), "last"))
# [,1] [,2]
#[1,] 1 3
#[2,] 2 2
#[3,] 3 3
#[4,] 4 1
#[5,] 5 3
#[6,] 6 3
data[-1][cbind(1:nrow(data), max.col(!is.na(data[-1]), "last"))]
#[1] 99 2 4 3 4 5
cbind(data[1], result=data[-1][cbind(1:nrow(data), max.col(!is.na(data[-1]), "last"))])
# a result
#1 A 99
#2 B 2
#3 C 4
#4 D 3
#5 E 4
#6 F 5
```

If you need a particular column to always be given precedence, make a temporary object with the columns in a particular order, and then process it:

```
tmp <- data[-1][c("z", setdiff(names(data[-1]), "z"))]
tmp[cbind(1:nrow(tmp), max.col(!is.na(tmp), "first"))]
#[1] 99 2 4 3 4 5
```