To apply if else iterations on each row

[Logziii]

Hi,

I want to use if else statement on each row with loops on given data frame.

ab = data.frame(x = c("P1","P2","P3","P4","P5"),
A = c("100","100","100","100","100"),
B= c("a","b","c","d","e"),
C= c("PR","PR","SR","SR","TR"),
D= c("75","125","NA","NA","NA"),
stringsAsFactors = FALSE)

Some conditions need to apply.I have used loop function but not working..

for(i in 1:nrow(ab)){
if((ab$D != NULL ) & (ab$C == PR) & (ab$D > ab$A))
{
ab$New <- "0"

}
else if((ab$D == NA) & (ab$C == SR))
{
ab$New <- "0"

}
else if((ab$D == NA)&(ab$C == TR))
{
ab$New <- "1"

}
else
{
ab$New<- "No"
}
}
Result should reflect in same data set with new column.
my conditions are:
1)If column d is not null and value of D is greater than column A and value of column c is PR then in new result column there should be print "0".
2)if column d is Null and value of column C is SR then in result column there should be "0".
3)if column d is null and value of column C is TR then in result column there must be "1"
4)Else print "NO"

Need advise.

Desired Output is :

x A B C D NEW
P2 100 b PR 125 0
P3 100 c SR 120 0
P4 100 d SR NA 0
P5. 100 e TR 50 1

[FJCC]

Does the following code do what you want? Note that there is a difference between a variable having the value "NA" (which is a character string), it having an NA value (which will test TRUE with is.na()), and a variable being NULL.

library(dplyr)
ab = data.frame(x = c("P1","P2","P3","P4","P5"),
                A = c("100","100","100","100","100"),
                B= c("a","b","c","d","e"),
                C= c("PR","PR","SR","SR","TR"),
                D= c("75","125","NA","NA","NA"),
                stringsAsFactors = FALSE)
ab
#>    x   A B  C   D
#> 1 P1 100 a PR  75
#> 2 P2 100 b PR 125
#> 3 P3 100 c SR  NA
#> 4 P4 100 d SR  NA
#> 5 P5 100 e TR  NA
ab <- ab %>% mutate(New = case_when(
  D != "NA" & D > A & C == "PR" ~ "0",
  D == "NA" & C == "SR" ~ "0",
  D == "NA" & C == "TR" ~ "1",
  TRUE ~ "NO"
))
ab
#>    x   A B  C   D New
#> 1 P1 100 a PR  75   0
#> 2 P2 100 b PR 125   0
#> 3 P3 100 c SR  NA   0
#> 4 P4 100 d SR  NA   0
#> 5 P5 100 e TR  NA   1

^{Created on 2020-02-05 by the reprex package (v0.3.0)}

[jpiaskowski]

The function ifelse() is automatically vectorised:

Agreed with above comment on NA versus "NA" - so the command b$D != NULL will always evaluate to TRUE in this example. Also, this argument will go wonky when using characters and not numbers: ab$D > ab$A. The argument is.na() seems to be betters at detecting true NA values.

ab = data.frame(
     x = c("P1","P2","P3","P4","P5"),
     A = c("100","100","100","100","100"),
     B= c("a","b","c","d","e"),
     C= c("PR","PR","SR","SR","TR"),
     D= c("75","125", NA, NA, NA),
     stringsAsFactors = FALSE)

ab$New <- ifelse(!is.na(ab$D)  & ab$C == "PR" & ab$D > ab$A, "0",
                       ifelse(is.na(ab$D) & ab$C == "SR", "0", 
                           ifelse(is.na(ab$D) & ab$C == "TR", "1", "No")))

[Logziii]

Hi,

Thanks...its working and it is a very simple solution.