R Split strings into two columns based on TWO regular expressions - r

Question

I have some data that is structured something like this:
ID Region Value
1 Europe 8
2 Europe: Class 1 6
3 Asia: System 2 6
4 North America 7
5 Europe: System 1 5
6 Africa 7
7 Africa: Class 2 5
8 South America 9
9 Europe: System 1 3
10 Europe 7
What I want to do is create a new column called Class which adds instances of where "Class" AND "System" are mentioned in the Region column - if it's not clear what I mean, take a look at my expected output below. I know this can be done with the separate function but I think you can only specify one value for the separator part of the code. E.g. sep = ": Class" will only split instances that mention "class" but I also want to split any instances where "system" is mentioned too. Can this be done in one line of code, or do I need to do something a bit more complicated here? Here's how my final data should look:
ID Region Class Value
1 Europe 8
2 Europe 1 6
3 Asia 2 6
4 North America 7
5 Europe 1 5
6 Africa 7
7 Africa 2 5
8 South America 9
9 Europe 1 3
10 Europe 7
Please note, I want to remove any reference to "class" or "system" (including colons) from the Region column, and simply add the numerical value to a new Class column.

Answer 1

You can do it with base functions by just using strsplit with a regular expression that takes either ": System" or ": Class" as symbol:
splitted = strsplit(df$Region,"(: Class)|(: System)")
df$Region = lapply(splitted,FUN=function(x){x[1]})
df$Class = lapply(splitted,FUN=function(x){x[2]})
The result is:
> df
ID Region Value Class
1 1 Europe 8 NA
2 2 Europe 6 1
3 3 Asia 6 2
4 4 North America 7 NA
5 5 Europe 5 1
6 6 Africa 7 NA
7 7 Africa 5 2
8 8 South America 9 NA
9 9 Europe 3 1
10 10 Europe 7 NA

Answer 2

You can use str_extract to extract the number and str_remove to drop the text that you don't want.
library(dplyr)
library(stringr)
df %>%
mutate(Class = str_extract(Region, '(?<=(Class|System)\\s)\\d+'),
Region = str_remove(Region, ':\\s*(Class|System)\\s*\\d+'))
# ID Region Value Class
#1 1 Europe 8 <NA>
#2 2 Europe 6 1
#3 3 Asia 6 2
#4 4 North America 7 <NA>
#5 5 Europe 5 1
#6 6 Africa 7 <NA>
#7 7 Africa 5 2
#8 8 South America 9 <NA>
#9 9 Europe 3 1
#10 10 Europe 7 <NA>
str_extract extracts the number which comes after 'Class'
or 'System'. If these words are not present then it returns NA.
str_remove removes colon followed by zero or more whitespace (\\s*) followed by either 'Class' or 'System' and a number (\\d+).
data
It is easier to help if you provide data in a reproducible format which is easier to copy.
df <- structure(list(ID = 1:10, Region = c("Europe", "Europe: Class 1",
"Asia: System 2", "North America", "Europe: System 1", "Africa",
"Africa: Class 2", "South America", "Europe: System 1", "Europe"
), Value = c(8L, 6L, 6L, 7L, 5L, 7L, 5L, 9L, 3L, 7L)),
class = "data.frame", row.names = c(NA, -10L))