Add new column if range of columns contains string in R - r

Question

I have a dataframe like below. I would like to add 2 columns:
ContainsANZ: Indicates if any of the columns from F0 to F3 contain 'Australia' or 'New Zealand' ignoring NA values
AllANZ: Indicates if all non NA columns contain 'Australia' or 'New Zealand'
Starting dataframe would be:
dfContainsANZ
Col.A Col.B Col.C F0 F1 F2 F3
1 data 0 xxx Australia Singapore <NA> <NA>
2 data 1 yyy United States United States United States <NA>
3 data 0 zzz Australia Australia Australia Australia
4 data 0 ooo Hong Kong London Australia <NA>
5 data 1 xxx New Zealand <NA> <NA> <NA>
The end result should look like this:
df
Col.A Col.B Col.C F0 F1 F2 F3 ContainsANZ AllANZ
1 data 0 xxx Australia Singapore <NA> <NA> Australia undefined
2 data 1 yyy United States United States United States <NA> undefined undefined
3 data 0 zzz Australia Australia Australia Australia Australia Australia
4 data 0 ooo Hong Kong London Australia <NA> Australia undefined
5 data 1 xxx New Zealand <NA> <NA> <NA> New Zealand New Zealand
I'm using dplyr (preferred solution) and have come up with a code like this which doesn't work and is very repetitive. Is there a better way to write this so that I am not having to copy F0|F1|F2... rules over again? My real data set has more. Is NAs interfering with the code?
df <- df %>%
mutate(ANZFlag =
ifelse(
F0 == 'Australia' |
F1 == 'Australia' |
F2 == 'Australia' |
F3 == 'Australia',
'Australia',
ifelse(
F0 == 'New Zealand' |
F1 == 'New Zealand' |
F2 == 'New Zealand' |
F3 == 'New Zealand',
'New Zealand', 'undefined'
)
)
)

Answer 1

Still some typing, but I think this gets at the essence you're looking for:
library(dplyr)
df <- read.table(text='Col.A,Col.B,Col.C,F0,F1,F2,F3
data,0,xxx,Australia,Singapore,NA,NA
data,1,yyy,"United States","United States","United States",NA
data,0,zzz,Australia,Australia,Australia,Australia
data,0,ooo,"Hong Kong",London,Australia,NA
data,1,xxx,"New Zealand",NA,NA,NA', header=TRUE, sep=",", stringsAsFactors=FALSE)
down_under <- function(x) {
mtch <- c("Australia", "New Zealand")
cols <- unlist(x)[c("F0", "F1", "F2", "F3")]
bind_cols(x, data_frame(ContainsANZ=any(mtch %in% cols, na.rm=TRUE),
AllANZ=all(as.vector(na.omit(cols)) %in% cols)))
}
rowwise(df) %>% do(down_under(.))
## Source: local data frame [5 x 9]
## Groups: <by row>
##
## Col.A Col.B Col.C F0 F1 F2 F3 ContainsANZ AllANZ
## (chr) (int) (chr) (chr) (chr) (chr) (chr) (lgl) (lgl)
## 1 data 0 xxx Australia Singapore NA NA TRUE TRUE
## 2 data 1 yyy United States United States United States NA FALSE TRUE
## 3 data 0 zzz Australia Australia Australia Australia TRUE TRUE
## 4 data 0 ooo Hong Kong London Australia NA TRUE TRUE
## 5 data 1 xxx New Zealand NA NA NA TRUE TRUE