Splitting strings into components - r

Question

For example, I have a data table with several columns:
column A column B
key_500:station and loc 2
spectra:key_600:type 9
alpha:key_100:number 12
I want to split the rows of column A into components and create new columns, guided by the following rules:
the value between "key_" and ":" will be var1,
the next value after ":" will be var2,
the original column A should retain the part of string that is prior to ":key_". If it is empty (as in the first line), then replace "" with an "effect" word.
My expected final data table should be like this one:
column A column B var1 var2
effect 2 500 station and loc
spectra 9 600 type
alpha 12 100 number

Answer 1

Using tidyr extract you can extract specific part of the string using regex.
tidyr::extract(df, columnA, into = c('var1', 'var2'), 'key_(\\d+):(.*)',
convert = TRUE, remove = FALSE) %>%
dplyr::mutate(columnA = sub(':?key_.*', '', columnA),
columnA = replace(columnA, columnA == '', 'effect'))
# columnA var1 var2 columnB
#1 effect 500 station and loc 2
#2 spectra 600 type 9
#3 alpha 100 number 12
If you want to use data.table you can break this down in steps :
library(data.table)
setDT(df)
df[, c('var1', 'var2') := .(sub('.*key_(\\d+).*', '\\1',columnA),
sub('.*key_\\d+:', '', columnA))]
df[, columnA := sub(':?key_.*', '', columnA)]
df[, columnA := replace(columnA, columnA == '', 'effect')]
data
df <- structure(list(columnA = c("key_500:station and loc",
"spectra:key_600:type", "alpha:key_100:number"),
columnB = c(2L, 9L, 12L)), class = "data.frame", row.names = c(NA, -3L))

Answer 2

You can use separate which uses non-letters and separates the string into columns defined in into
require(tidyr)
require(dplyr)
df=tribble(
~"column A",~"column B",
"key_500:station", 2,
"spectra:key_600:type", 9,
"alpha:key_100:number", 12)
df %>% separate("column A",into=c('column A','key','var1','var2'),fill='left') %>% select(-key) %>% select("column A","column B",var1,var2) %>%
mutate(`column A`=ifelse(is.na(`column A`),"effect",`column A`))
And this is a modified version to work with data.tables
require(tidyr)
require(data.table)
DT=data.table(
"column A"=
c("key_500:station and loc",
"spectra:key_600:type",
"alpha:key_100:number"),
"column B"=c(2,9,12))
DT=separate(sep = "[^[:alnum:] ]+",DT,"column A",into=c('column A','key','var1','var2'),fill='left')
DT$key=NULL
DT$`column A`=ifelse(is.na(DT$`column A`),"effect",DT$`column A`)
DT=DT[,c(1,4,2,3)]