I'm still learning how to translate a SAS code into R and I get warnings. I need to understand where I'm making mistakes. What I want to do is create a variable which summarizes and differentiates 3 status of a population: mainland, overseas, foreigner. I have a database with 2 variables:
idnat (french, foreigner), If idnat is french then:
idbp (mainland, colony, overseas) I want to summarize the info from idnat and idbp into a new variable called idnat2:
All these variables use "character type".
Results expected in column idnat2 :
idnat idbp idnat2
1 french mainland mainland
2 french colony overseas
3 french overseas overseas
4 foreign foreign foreign
Here is my SAS code I want to translate in R:
if idnat = "french" then do;
if idbp in ("overseas","colony") then idnat2 = "overseas";
else idnat2 = "mainland";
end;
else idnat2 = "foreigner";
run;
Here is my attempt in R:
if(idnat=="french"){
idnat2 <- "mainland"
} else if(idbp=="overseas"|idbp=="colony"){
idnat2 <- "overseas"
} else {
idnat2 <- "foreigner"
}
I receive this warning:
Warning message:
In if (idnat=="french") { :
the condition has length > 1 and only the first element will be used
I was advised to use a "nested ifelse" instead for its easiness but get more warnings:
idnat2 <- ifelse (idnat=="french", "mainland",
ifelse (idbp=="overseas"|idbp=="colony", "overseas")
)
else (idnat2 <- "foreigner")
According to the Warning message, the length is greater than 1 so only what's between the first brackets will be taken into account. Sorry but I don't understand what this length has to do with here? Anybody know where I'm wrong?
This question is related to
r
if-statement
nested
sas
With data.table, the solutions is:
DT[, idnat2 := ifelse(idbp %in% "foreign", "foreign",
ifelse(idbp %in% c("colony", "overseas"), "overseas", "mainland" ))]
The ifelse is vectorized. The if-else is not. Here, DT is:
idnat idbp
1 french mainland
2 french colony
3 french overseas
4 foreign foreign
This gives:
idnat idbp idnat2
1: french mainland mainland
2: french colony overseas
3: french overseas overseas
4: foreign foreign foreign
Using the SQL CASE statement with the dplyr and sqldf packages:
Data
df <-structure(list(idnat = structure(c(2L, 2L, 2L, 1L), .Label = c("foreign",
"french"), class = "factor"), idbp = structure(c(3L, 1L, 4L,
2L), .Label = c("colony", "foreign", "mainland", "overseas"), class = "factor")), .Names = c("idnat",
"idbp"), class = "data.frame", row.names = c(NA, -4L))
sqldf
library(sqldf)
sqldf("SELECT idnat, idbp,
CASE
WHEN idbp IN ('colony', 'overseas') THEN 'overseas'
ELSE idbp
END AS idnat2
FROM df")
dplyr
library(dplyr)
df %>%
mutate(idnat2 = case_when(.$idbp == 'mainland' ~ "mainland",
.$idbp %in% c("colony", "overseas") ~ "overseas",
TRUE ~ "foreign"))
Output
idnat idbp idnat2
1 french mainland mainland
2 french colony overseas
3 french overseas overseas
4 foreign foreign foreign
If the data set contains many rows it might be more efficient to join with a lookup table using data.table instead of nested ifelse().
Provided the lookup table below
lookup
idnat idbp idnat2 1: french mainland mainland 2: french colony overseas 3: french overseas overseas 4: foreign foreign foreign
and a sample data set
library(data.table)
n_row <- 10L
set.seed(1L)
DT <- data.table(idnat = "french",
idbp = sample(c("mainland", "colony", "overseas", "foreign"), n_row, replace = TRUE))
DT[idbp == "foreign", idnat := "foreign"][]
idnat idbp 1: french colony 2: french colony 3: french overseas 4: foreign foreign 5: french mainland 6: foreign foreign 7: foreign foreign 8: french overseas 9: french overseas 10: french mainland
then we can do an update while joining:
DT[lookup, on = .(idnat, idbp), idnat2 := i.idnat2][]
idnat idbp idnat2 1: french colony overseas 2: french colony overseas 3: french overseas overseas 4: foreign foreign foreign 5: french mainland mainland 6: foreign foreign foreign 7: foreign foreign foreign 8: french overseas overseas 9: french overseas overseas 10: french mainland mainland
Sorry for joining too late to the party. Here's an easy solution.
#building up your initial table
idnat <- c(1,1,1,2) #1 is french, 2 is foreign
idbp <- c(1,2,3,4) #1 is mainland, 2 is colony, 3 is overseas, 4 is foreign
t <- cbind(idnat, idbp)
#the last column will be a vector of row length = row length of your matrix
idnat2 <- vector()
#.. and we will populate that vector with a cursor
for(i in 1:length(idnat))
#*check that we selected the cursor to for the length of one of the vectors*
{
if (t[i,1] == 2) #*this says: if idnat = foreign, then it's foreign*
{
idnat2[i] <- 3 #3 is foreign
}
else if (t[i,2] == 1) #*this says: if not foreign and idbp = mainland then it's mainland*
{
idnat2[i] <- 2 # 2 is mainland
}
else #*this says: anything else will be classified as colony or overseas*
{
idnat2[i] <- 1 # 1 is colony or overseas
}
}
cbind(t,idnat2)
# Read in the data.
idnat=c("french","french","french","foreign")
idbp=c("mainland","colony","overseas","foreign")
# Initialize the new variable.
idnat2=as.character(vector())
# Logically evaluate "idnat" and "idbp" for each case, assigning the appropriate level to "idnat2".
for(i in 1:length(idnat)) {
if(idnat[i] == "french" & idbp[i] == "mainland") {
idnat2[i] = "mainland"
} else if (idnat[i] == "french" & (idbp[i] == "colony" | idbp[i] == "overseas")) {
idnat2[i] = "overseas"
} else {
idnat2[i] = "foreign"
}
}
# Create a data frame with the two old variables and the new variable.
data.frame(idnat,idbp,idnat2)
Try something like the following:
# some sample data
idnat <- sample(c("french","foreigner"),100,TRUE)
idbp <- rep(NA,100)
idbp[idnat=="french"] <- sample(c("mainland","overseas","colony"),sum(idnat=="french"),TRUE)
# recoding
out <- ifelse(idnat=="french" & !idbp %in% c("overseas","colony"), "mainland",
ifelse(idbp %in% c("overseas","colony"),"overseas",
"foreigner"))
cbind(idnat,idbp,out) # check result
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.
If you are using any spreadsheet application there is a basic function if() with syntax:
if(<condition>, <yes>, <no>)
Syntax is exactly the same for ifelse() in R:
ifelse(<condition>, <yes>, <no>)
The only difference to if() in spreadsheet application is that R ifelse() is vectorized (takes vectors as input and return vector on output). Consider the following comparison of formulas in spreadsheet application and in R for an example where we would like to compare if a > b and return 1 if yes and 0 if not.
In spreadsheet:
A B C
1 3 1 =if(A1 > B1, 1, 0)
2 2 2 =if(A2 > B2, 1, 0)
3 1 3 =if(A3 > B3, 1, 0)
In R:
> a <- 3:1; b <- 1:3
> ifelse(a > b, 1, 0)
[1] 1 0 0
ifelse() can be nested in many ways:
ifelse(<condition>, <yes>, ifelse(<condition>, <yes>, <no>))
ifelse(<condition>, ifelse(<condition>, <yes>, <no>), <no>)
ifelse(<condition>,
ifelse(<condition>, <yes>, <no>),
ifelse(<condition>, <yes>, <no>)
)
ifelse(<condition>, <yes>,
ifelse(<condition>, <yes>,
ifelse(<condition>, <yes>, <no>)
)
)
To calculate column idnat2 you can:
df <- read.table(header=TRUE, text="
idnat idbp idnat2
french mainland mainland
french colony overseas
french overseas overseas
foreign foreign foreign"
)
with(df,
ifelse(idnat=="french",
ifelse(idbp %in% c("overseas","colony"),"overseas","mainland"),"foreign")
)
What is the condition has length > 1 and only the first element will be used? Let's see:
> # What is first condition really testing?
> with(df, idnat=="french")
[1] TRUE TRUE TRUE FALSE
> # This is result of vectorized function - equality of all elements in idnat and
> # string "french" is tested.
> # Vector of logical values is returned (has the same length as idnat)
> df$idnat2 <- with(df,
+ if(idnat=="french"){
+ idnat2 <- "xxx"
+ }
+ )
Warning message:
In if (idnat == "french") { :
the condition has length > 1 and only the first element will be used
> # Note that the first element of comparison is TRUE and that's whay we get:
> df
idnat idbp idnat2
1 french mainland xxx
2 french colony xxx
3 french overseas xxx
4 foreign foreign xxx
> # There is really logic in it, you have to get used to it
Can I still use if()? Yes, you can, but the syntax is not so cool :)
test <- function(x) {
if(x=="french") {
"french"
} else{
"not really french"
}
}
apply(array(df[["idnat"]]),MARGIN=1, FUN=test)
If you are familiar with SQL, you can also use CASE statement in sqldf package.
The explanation with the examples was key to helping mine, but the issue that i came was when I copied it didn't work so I had to mess with it in several ways to get it to work right. (I'm super new at R, and had some issues with the third ifelse due to lack of knowledge).
so for those who are super new to R running into issues...
ifelse(x < -2,"pretty negative", ifelse(x < 1,"close to zero", ifelse(x < 3,"in [1, 3)","large")##all one line
)#normal tab
)
(i used this in a function so it "ifelse..." was tabbed over one, but the last ")" was completely to the left)
You can create the vector idnat2 without if and ifelse.
The function replace can be used to replace all occurrences of "colony" with "overseas":
idnat2 <- replace(idbp, idbp == "colony", "overseas")
Source: Stackoverflow.com