Apply if else statements across columns in data frame based on condition of value in other column

Question

I want to apply an if else statement to each column (a-d) in a data frame where if each value satisfies a condition based on another column (m), the value stays the same, otherwise the value is changed to zero.

Here is a reproducible example:

a <- c(10, 11, 12, 15,7,8)
b <- c(15,11,16,17,1.5,9)
c <- c(18,14,6,14,1,17)
d <- c(12,11,13,19,2,4)
p <- c(2,1,3,2.5,1.3,2.1)
m <- c(12,13,8,9,14,11)

df<- data.frame(a,b,c,d,p,m)

print(df)

   a    b  c  d   p  m
1 10 15.0 18 12 2.0 12
2 11 11.0 14 11 1.0 13
3 12 16.0  6 13 3.0  8
4 15 17.0 14 19 2.5  9
5  7  1.5  1  2 1.3 14
6  8  9.0 17  4 2.1 11

This is the 'long' version of what I want to do which works but is very repetitive:

df$a<- ifelse((df$a-df$p)>df$m, df$a, 0)
df$b<- ifelse((df$b-df$p)>df$m, df$b, 0)
df$c<- ifelse((df$c-df$p)>df$m, df$c, 0)
df$d<- ifelse((df$d-df$p)>df$m, df$d, 0)

print(df)

This is the output I want:

   a  b  c  d   p  m
1  0 15 18  0 2.0 12
2 11 11 14 11 1.0  7
3 12 16  0 13 3.0  8
4 15 17 14 19 2.5  9
5  0  0  0  0 1.3 14
6  0  0 17  0 2.1 11

Answer 1

We can use an lapply

df[1:4] <- lapply(df[1:4], function(x) ifelse((x - df$p) > df$m, x, 0))
df
#   a  b  c  d   p  m
#1  0 15 18  0 2.0 12
#2  0  0  0  0 1.0 13
#3 12 16  0 13 3.0  8
#4 15 17 14 19 2.5  9
#5  0  0  0  0 1.3 14
#6  0  0 17  0 2.1 11

---

Or without using ifelse

df[1:4] <- ((df[1:4]-df$p) > df$m)*df[1:4]