One option is ifelse
which is vectorized version of if/else
. If we are doing this for each row, the if/else
as showed in the OP’s pandas post can be done in either a for
loop or lapply/sapply
, but that would be inefficient in R
.
df <- transform(df, c= ifelse(a==b, a+b, b-a))
df
# a b c
#1 1 1 2
#2 2 20 18
#3 3 3 6
#4 4 4 8
#5 5 50 45
This can be otherwise written as
df$c <- with(df, ifelse(a==b, a+b, b-a))
to create the ‘c’ column in the original dataset
As the OP wants a similar option in R
using if/else
df$c <- apply(df, 1, FUN = function(x) if(x[1]==x[2]) x[1]+x[2] else x[2]-x[1])