Replace logical values (TRUE / FALSE) with numeric (1 / 0)
Solution 1
For a data.frame, you could convert all logical columns to numeric with:
# The data
set.seed(144)
dat <- data.frame(V1=1:100,V2=rnorm(100)>0)
dat$V3 <- dat$V2 == 1
head(dat)
# V1 V2 V3
# 1 1 FALSE FALSE
# 2 2 TRUE TRUE
# 3 3 FALSE FALSE
# 4 4 FALSE FALSE
# 5 5 FALSE FALSE
# 6 6 TRUE TRUE
# Convert all to numeric
cols <- sapply(dat, is.logical)
dat[,cols] <- lapply(dat[,cols], as.numeric)
head(dat)
# V1 V2 V3
# 1 1 0 0
# 2 2 1 1
# 3 3 0 0
# 4 4 0 0
# 5 5 0 0
# 6 6 1 1
In data.table
syntax:
# Data
set.seed(144)
DT = data.table(cbind(1:100,rnorm(100)>0))
DT[,V3 := V2 == 1]
DT[,V4 := FALSE]
head(DT)
# V1 V2 V3 V4
# 1: 1 0 FALSE FALSE
# 2: 2 1 TRUE FALSE
# 3: 3 0 FALSE FALSE
# 4: 4 0 FALSE FALSE
# 5: 5 0 FALSE FALSE
# 6: 6 1 TRUE FALSE
# Converting
(to.replace <- names(which(sapply(DT, is.logical))))
# [1] "V3" "V4"
for (var in to.replace) DT[, (var):= as.numeric(get(var))]
head(DT)
# V1 V2 V3 V4
# 1: 1 0 0 0
# 2: 2 1 1 0
# 3: 3 0 0 0
# 4: 4 0 0 0
# 5: 5 0 0 0
# 6: 6 1 1 0
Solution 2
Simplest way of doing this!
Multiply your matrix by 1
For example:
A <- matrix(c(TRUE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,TRUE),ncol=4)
A
# [,1] [,2] [,3] [,4]
# [1,] TRUE TRUE TRUE FALSE
# [2,] FALSE TRUE FALSE TRUE
B <- 1*A
B
# [,1] [,2] [,3] [,4]
# [1,] 1 1 1 0
# [2,] 0 1 0 1
(You could also add zero: B <- 0 + A
)
Solution 3
What about just a:
dat <- data.frame(le = letters[1:10], lo = rep(c(TRUE, FALSE), 5))
dat
le lo
1 a TRUE
2 b FALSE
3 c TRUE
4 d FALSE
5 e TRUE
6 f FALSE
7 g TRUE
8 h FALSE
9 i TRUE
10 j FALSE
dat$lo <- as.numeric(dat$lo)
dat
le lo
1 a 1
2 b 0
3 c 1
4 d 0
5 e 1
6 f 0
7 g 1
8 h 0
9 i 1
10 j 0
or another approach could be with dplyr
in order to retain the previous column if the case (no one knows) your data will be imported in R.
library(dplyr)
dat <- dat %>% mutate(lon = as.numeric(lo))
dat
Source: local data frame [10 x 3]
le lo lon
1 a TRUE 1
2 b FALSE 0
3 c TRUE 1
4 d FALSE 0
5 e TRUE 1
6 f FALSE 0
7 g TRUE 1
8 h FALSE 0
9 i TRUE 1
10 j FALSE 0
Edit: Loop
I do not know if my code here is performing but it checks all column and change to numerical only those that are logical. Of course if your TRUE
and FALSE
are not logical but character strings (which might be remotely) my code won't work.
for(i in 1:ncol(dat)){
if(is.logical(dat[, i]) == TRUE) dat[, i] <- as.numeric(dat[, i])
}
Solution 4
If there are multiple columns, you could use set
(using @josilber's example)
library(data.table)
Cols <- which(sapply(dat, is.logical))
setDT(dat)
for(j in Cols){
set(dat, i=NULL, j=j, value= as.numeric(dat[[j]]))
}
Solution 5
As Ted Harding pointed out in the R-help mailing list, one easy way to convert logical objects to numeric is to perform an arithmetic operation on them. Convenient ones would be * 1
and + 0
, which will keep the TRUE/FALSE == 1/0 paradigm.
For your mock data (I've changed the code a bit to use regular R packages and to reduce size):
df <- data.frame(cbind(1:10, rnorm(10) > 0))
df$X3 <- df$X2 == 1
df$X4 <- df$X2 != 1
The dataset you get has a mixture of numeric and boolean variables:
X1 X2 X3 X4
1 1 0 FALSE TRUE
2 2 0 FALSE TRUE
3 3 1 TRUE FALSE
4 4 1 TRUE FALSE
5 5 1 TRUE FALSE
6 6 0 FALSE TRUE
7 7 0 FALSE TRUE
8 8 1 TRUE FALSE
9 9 0 FALSE TRUE
10 10 1 TRUE FALSE
Now let
df2 <- 1 * df
(If your dataset contains character or factor variables, you will need to apply this operation to a subset of df
filtering out those variables)
df2
is equal to
X1 X2 X3 X4
1 1 0 0 1
2 2 0 0 1
3 3 1 1 0
4 4 1 1 0
5 5 1 1 0
6 6 0 0 1
7 7 0 0 1
8 8 1 1 0
9 9 0 0 1
10 10 1 1 0
Which is 100% numeric, as str(df2)
will show you.
Now you can safely export df2
to your other program.
johneric
Updated on May 02, 2021Comments
-
johneric about 3 years
I am exporting data from R with the command:
write.table(output,file = "data.raw", na "-9999", sep = "\t", row.names = FALSE, col.names = FALSE)
It exports my data correctly, but it exports all of the logical variables as
TRUE
andFALSE
.I need to read the data into another program that can only process numeric values. Is there an efficient way to convert
logical
columns to numeric 1s and 0s during the export? I have a large number of numeric variables, so I was hoping to automatically loop through all the variables in the data.tableAlternatively, my output object is a
data.table
. Is there an efficient way to convert all the logical variables in adata.table
into numeric variables?In case it is helpful, here is some code to generate a
data.table
with a logical variable in it (it is not a large number of logical variables, but enough to use on example code):DT = data.table(cbind(1:100, rnorm(100) > 0) DT[ , V3:= V2 == 1 ] DT[ , V4:= V2 != 1 ]