问题描述:

I've constructed a simple matrix in Excel with some character values and some numeric values (Screenshot of data as set up in Excel). I read it into R using the openxlsx package like so:

`library(openxlsx)`

data <- read.xlsx('~desktop/data.xlsx)

After that I check the class:

`sapply(data, class)`

x1 a b c

"character" "numeric" "numeric" "numeric"

Which is exactly what I want. My problem occurs when I try to transpose the matrix, and then check for class again:

`data <- t(data)`

When i check with sapply now, all values are "character". Why are the classes not preserved when transposing?

First off, I don't get your result when I read in your spreadsheet due to the fact the the cells with comma separated numbers appear as characters.

```
data <- read.xlsx("data.xlsx")
data
# X1 a b c
#1 x 0,1 3 4,5
#2 y 2,4 0 6,5
#3 z 24 0 0
sapply(data,class)
# X1 a b c
#"character" "character" "numeric" "character"
```

But the issue you are really seeing is that by transposing the data frame you are mixing types in the same column so R HAS TO convert the whole column to the broadest common type, which is character in this case.

```
mydata<-data.frame(X1=c("x","y","z"),a=c(1,2,24),b=c(3,0,0),c=c(4,6,0),stringsAsFactors = FALSE)
sapply(mydata,class)
# X1 a b c
#"character" "numeric" "numeric" "numeric"
# what you showed
t(mydata)
# [,1] [,2] [,3]
#X1 "x" "y" "z"
#a " 1" " 2" "24"
#b "3" "0" "0"
#c "4" "6" "0"
mydata_t<-t(mydata)
sapply(mydata_t,class)
# x 1 3 4 y 2 #0 6 z 24
#"character" "character" "character" "character" "character" "character" #"character" "character" "character" "character"
# 0 0
#"character" "character"
```

Do you want to work on the numbers in the transposed matrix and transpose them back after? If so, transpose a sub-matrix that has the character columns temporarily removed, then reassemble later, like so:

```
sub_matrix<-t(mydata[,-1])
sub_matrix
# [,1] [,2] [,3]
#a 1 2 24
#b 3 0 0
#c 4 6 0
sub_matrix2<-sub_matrix*2
sub_matrix2
# [,1] [,2] [,3]
#a 2 4 48
#b 6 0 0
#c 8 12 0
cbind(X1=mydata[,1],as.data.frame(t(sub_matrix2)))
# X1 a b c
#1 x 2 6 8
#2 y 4 0 12
#3 z 48 0 0
```