Splitting strings from integers in R - r

Question

I've recently come across an interesting problem while trying to
create a custom database.
my rows are in form:
183746IGH
105928759UBS
and so on (so basically an integer concatenated with a string, both of relatively random sizes.). What I'm trying to do is somehow separate the whole number in column 1 and everything else(the letters) in column 2. How can this be done? I've been trying with strsplit but it doesn't seem to offer this kind of functionality.
Thank you for any help.

Answer 1

Other options include tstrsplit from the devel version of data.table
library(data.table)#v1.9.5+
setDT(df)[,tstrsplit(V1,'(?<=\\d)(?=\\D)', perl=TRUE, type.convert=TRUE)]
# V1 V2
#1: 131341 adad
#2: 45365 adadar
#3: 425 cavsbsb
#4: 46567567 daadvsv
If there are elements were 'non-numeric' part appears first and 'numeric' last, then, we can use a bit more generalized option as the regex pattern,
setDT(df)[,tstrsplit(V1, "(?<=\\d)(?=\\D)|(?<=\\D)(?=\\d)",
perl = TRUE)]
Or using extract from tidyr
library(tidyr)
extract(df, V1, into=c('V1', 'V2'), '(\\d+)(\\D+)', convert=TRUE)
# V1 V2
#1 131341 adad
#2 45365 adadar
#3 425 cavsbsb
#4 46567567 daadvsv
If you need the original column as well,
extract(df, V1, into=c('V2', 'V3'), '(\\d+)(\\D+)',
convert=TRUE, remove=FALSE)
# V1 V2 V3
#1 131341adad 131341 adad
#2 45365adadar 45365 adadar
#3 425cavsbsb 425 cavsbsb
#4 46567567daadvsv 46567567 daadvsv
For the data.table, we can use := to create the new columns so that the existing columns remain in the output, i.e.
setDT(df)[,paste0('V',2:3):=tstrsplit(V1,'(?<=\\d)(?=\\D)',
perl=TRUE, type.convert=TRUE)]
# V1 V2 V3
#1: 131341adad 131341 adad
#2: 45365adadar 45365 adadar
#3: 425cavsbsb 425 cavsbsb
#4: 46567567daadvsv 46567567 daadvsv
NOTE: Both the solutions have the option to convert the class of the split columns (type.convert/convert).
data
df <- data.frame(V1 = c("131341adad", "45365adadar", "425cavsbsb",
"46567567daadvsv"))

Answer 2

And another way with base-R and regular expressions:
all <- c(' 183746IGH','105928759UBS')
numeric <- sapply(a, function(x) sub('[[:alpha:]]+','', x))
alphabetic <- sapply(a, function(x) sub('[[:digit:]]+','', x))
> data.frame(all,alphabetic,numeric)
all alphabetic numeric
183746IGH 183746IGH IGH 183746
105928759UBS 105928759UBS UBS 105928759
Or as per #rawr's comment below:
> read.table(text = gsub('(\\d)(\\D)', '\\1 \\2', all))
V1 V2
1 183746 IGH
2 105928759 UBS
Or a vectorised version of the above with a function:
get_alphanum <- function(x, type) {
type <- switch(type,
alpha = '[[:digit:]]+',
digit = '[[:alpha:]]+')
sub(type,'', x)
}
get_alphanum <- Vectorize(get_alphanum)
Which gives a result applied directly on a vector!
> get_alphanum(all, type='alpha')
183746IGH 105928759UBS
" IGH" "UBS"
> get_alphanum(all, type='digit')
183746IGH 105928759UBS
" 183746" "105928759"
which can also be used to create a data.frame:
> data.frame(all,
alpha=get_alphanum(all, type='alpha') ,
numeric=get_alphanum(all, type='digit'))
all alpha numeric
183746IGH 183746IGH IGH 183746
105928759UBS 105928759UBS UBS 105928759

Answer 3

You could do:
df <- data.frame(V1 = c("adad131341", "adadar45365", "cavsbsb425", "daadvsv46567567"))
library(dplyr)
library(stringr)
df %>% mutate(V2 = str_extract(V1, "[0-9]+"),
V3 = str_extract(V1, "[aA-zZ]+"))
Which gives:
# V1 V2 V3
#1 adad131341 131341 adad
#2 adadar45365 45365 adadar
#3 cavsbsb425 425 cavsbsb
#4 daadvsv46567567 46567567 daadvsv

Answer 4

strsplit does work if you provide the correct regex to split on.
In this case, you would want something like:
strsplit(String, split = "(?<=[a-zA-Z])(?=[0-9])", perl = TRUE)
Here it is applied to #Steven's sample data:
strsplit(as.character(df$V1), split = "(?<=[a-zA-Z])(?=[0-9])", perl = TRUE)
# [[1]]
# [1] "adad" "131341"
#
# [[2]]
# [1] "adadar" "45365"
#
# [[3]]
# [1] "cavsbsb" "425"
#
# [[4]]
# [1] "daadvsv" "46567567"
Some time in the past I've written a function to do this since my mind honestly doesn't think in regex very often. The function looks like:
SplitMe <- function(string, alphaFirst = TRUE, bind = FALSE) {
if (!is.character(string)) string <- as.character(string)
Pattern <- ifelse(isTRUE(alphaFirst),
"(?<=[a-zA-Z])(?=[0-9])",
"(?<=[0-9])(?=[a-zA-Z])")
out <- strsplit(string, split = Pattern, perl = TRUE)
if (isTRUE(bind)) {
require(data.table)
as.data.table(do.call(rbind, out))
} else {
out
}
}
The intended usage was something like:
library(data.table)
as.data.table(df)[, c("char", "num") := SplitMe(V1, bind = TRUE)][]
# V1 char num
# 1: adad131341 adad 131341
# 2: adadar45365 adadar 45365
# 3: cavsbsb425 cavsbsb 425
# 4: daadvsv46567567 daadvsv 46567567
Once you know that pattern, you can use it in other places that make use of strsplit, like separate from "tidyr", which conveniently separates values into columns:
library(dplyr)
library(tidyr)
df %>%
separate(V1, into = c("char", "num"),
sep = "(?<=[a-zA-Z])(?=[0-9])", perl = TRUE)
# char num
# 1 adad 131341
# 2 adadar 45365
# 3 cavsbsb 425
# 4 daadvsv 46567567

Answer 5

read.pattern in the gsubfn package can do that. Each parenthesized part of the regular expression given in the pattern argument will be read into a separate column:
x <- c("183746IGH", "105928759UBS")
library(gsubfn)
read.pattern(text = x, pattern = "(\\d+)(\\D+)")
giving:
V1 V2
1 183746 IGH
2 105928759 UBS