Suppose we have the following data.table:
x_dt <- data.table(sexn = c(1,0,0,1,NA,1,NA), country = c("CHN", "JPN", "BGR", "AUT", " ", "TWN", " "), age=c(35,NA,40,NA,70,18,36))
I am trying to create a variable asia_region, which has a value of 1 when country %chin% c("CHN", "JPN", "KOR", "SGP", "TWN"), a value of 0 when country is not missing and NA when country is missing.
The following code populates 0's when country is missing.
result<-x_dt[ ,asia_region:=ifelse(country %chin% c("CHN", "JPN", "KOR", "SGP", "TWN"),1,0)]
CodePudding user response:
We can directly coerce the logical to binary with as.integer
or
, then change the values to NA
where the 'country' is blank (""
) by specifying a logical condition in i
and assignment (:=
) for those corresponding elements in 'asia_region' to NA
x_dt[, asia_region := (country %chin% c("CHN", "JPN", "KOR", "SGP", "TWN"))]
x_dt[trimws(country) == "", asia_region := NA_integer_]
-output
> x_dt
sexn country age asia_region
1: 1 CHN 35 1
2: 0 JPN NA 1
3: 0 BGR 40 0
4: 1 AUT NA 0
5: NA 70 NA
6: 1 TWN 18 1
7: NA 36 NA
Or if we need a ifelse/fifelse
(if/else
wouldn't work as it is not vectorized i.e. it expects input expression with length 1 and not more than that)
x_dt[, asia_region := fifelse(trimws(country) == "", NA_integer_,
fifelse(country %chin% c("CHN", "JPN", "KOR", "SGP", "TWN"), 1, 0))]
CodePudding user response:
How about a dplyr()
solution? I'd make a vector of the countries, for easier referencing:
asia_countries <- c("CHN", "JPN", "KOR", "SGP", "TWN")
x_dt |>
dplyr::mutate(asia_region = ifelse(country %in% asia_countries, 1, 0)) |>
dplyr::mutate(asia_region = ifelse(country == " ", NA, asia_region))