what is wrong with my code

[Marwah Soliman]

I'm generating a random numbers x,y between -10 and 10
then I create an if statement to classify each pair(x,y) in 4 quadrant in the following if statement
but the column quad give me all 4

so why?

x <- runif(n=400, min = -10, max = +10)
y <- runif(n=400, min = -10, max = +10)
mydata=cbind(x,y)
mydata=as.data.frame(mydata)
plot(x,y)

for(i in 1:400){
  
if((0< mydata$x[i] & mydata$x[i] <10) & (0< mydata$y[i] & mydata$y[i] <10)){
  mydata$quad=1
}else
  if((0<mydata$x[i] & mydata$x[i]<10) & (-10<mydata$y[i] & mydata$y[i]<0)){
    mydata$quad=2
  }else
    if((-10<mydata$x[i] & mydata$x[i]<0) & (-10<mydata$y[i] & mydata$y[i]<0)){
      mydata$quad=3
    }else
      if((-10<mydata$x[i] &mydata$x[i]<0) & (0<mydata$y[i] & mydata$y[i]<10)){
        mydata$quad=4
      }}

 

[GretaGarbo]

I think you forgot to insert the "" in "mydata$quad=1"

set.seed(2103) #if you repeat the code you will get the same numbers

x <- runif(n=400, min = -10, max = +10)
y <- runif(n=400, min = -10, max = +10)
mydata=cbind(x,y)
mydata=as.data.frame(mydata)
plot(x,y)

# initialize the variable
mydata$quad <- numeric(length = 400)

for(i in 1:400){
  
  if((0< mydata$x[i] & mydata$x[i] <10) & (0< mydata$y[i] & mydata$y[i] <10)){
    mydata$quad[i]=1
  }else
    if((0<mydata$x[i] & mydata$x[i]<10) & (-10<mydata$y[i] & mydata$y[i]<0)){
      mydata$quad[i]=2
    }else
      if((-10<mydata$x[i] & mydata$x[i]<0) & (-10<mydata$y[i] & mydata$y[i]<0)){
        mydata$quad[i]=3
      }else
        if((-10<mydata$x[i] &mydata$x[i]<0) & (0<mydata$y[i] & mydata$y[i]<10)){
          mydata$quad[i]=4
        }}

table(mydata$quad)

Maybe this help text that I copied somewhere some time ago can be helpful:

Spoiler

# Your confusion comes from how SAS and R handle if-else constructions. 
# In R, if and else are not vectorized, meaning they check whether a single 
# condition is true (i.e., if("french"=="french") works) and cannot 
# handle multiple logicals (i.e., if(c("french","foreigner")=="french") doesn't work) 
# and R gives you the warning you're receiving.

# By contrast, ifelse is vectorized, so it can take your vectors (aka input variables) 
# and test the logical condition on each of their elements, like you're used to in SAS.
# An alternative way to wrap your head around this would be to build a loop using 
# if and else statements (as you've started to do here) but the vectorized ifelse 
# approach will be more efficient and involve generally less code.


x<-c(3,6,9,12,15,21,25,32,36,39, 45, 70)

group <- ifelse ((x >=   0 & x <= 10), 1 , 
                 ifelse((x >= 11 & x <= 20 ), 2 , 
                        ifelse((x >= 21 & x <= 30), 3 , 
                               ifelse((x >= 31 & x <= 40), 4 , 
                                      ifelse((x >= 41 & x <= 50 ), 5 , 9 )  ))))

An alternative (vectorized) method is:

mydata$quad <- 
  ifelse(((0< mydata$x & mydata$x <10) & (0< mydata$y & mydata$y <10)), 1, 
      ifelse(((0<mydata$x & mydata$x<10) & (-10<mydata$y & mydata$y<0)),  2,
        ifelse(((-10<mydata$x & mydata$x<0) & (-10<mydata$y & mydata$y<0)), 3,  
          ifelse(((-10<mydata$x &mydata$x<0) & (0<mydata$y & mydata$y<10)),  4, 9)))) 

table(mydata$quad)

Here there was no loop.