Andrew Graham - 1 year ago 154
R Question

# Can I use separate() or extract() from tidyr to split a numeric value of variable length into its component digits?

I have a data frame with ~300 observations, each associated with a numeric code that I want to split into its component digits. The code variable is either a 3 or 4 digit integer, aligned by its last digit, & so my desired output would look something like this:

``````code    d4 d3 d2 d1
403  <NA>  4  0  3
5123     5  1  2  3
105  <NA>  1  0  5
``````

While I can see lots of ways to divide the code using
`strsplit`
(base R) or
`stringr::str_split`
, I am having difficulty applying any of these operations to my data frame.

``````library(stringr)
as.integer(unlist(str_split(5123, ""))[1]) # returns 5, the first digit - correct
as.integer(rev(unlist(str_split(5123, "")))[1]) # returns 3, the last digit - correct
``````

But the plausible (to me) operation

``````libray(dplyr)
df <- data.frame(code = c(403, 5123, 105))
df <- df %>%
mutate(
last = as.integer(rev(unlist(str_split(df\$code,"")))[4])
)
``````

returns

``````> df
code last
1  403    3
2 5123    3
3  105    3
``````

Clearly my understanding of how operations on lists and atomic vectors are handled within data frames is lacking...

I then felt sure that either the
`separate()`
or
`extract()`
functions from the
`tidyr`
package would help. Certainly,
`tidyr::separate()`
produces the desired result if the codes are supplied as strings with a leading space before each digit:

``````library(tidyr)
dfsep <- data.frame(code = c(" 4 0 3", "5 1 2 3", " 1 0 5"))
dfsep <- dfsep %>%
separate(
code, c("d4", "d3", "d2", "d1"), fill =  "right", remove = FALSE
)

dfsep
code d4 d3 d2 d1
1   4 0 3     4  0  3
2 5 1 2 3  5  1  2  3
3   1 0 5     1  0  5
``````

But a continuous string of digits cannot be split in this way; and empty search patterns are not supported by
`tidyr::separate()`

``````df <- data.frame(code = c(403, 5123, 105))
df <- df %>%
separate(
code, c("d4", "d3", "d2", "d1"), fill =  "right", remove = FALSE
)

df
code   d4   d3   d2   d1
1  403  403 <NA> <NA> <NA>
2 5123 5123 <NA> <NA> <NA>
3  105  105 <NA> <NA> <NA>
``````

While the problem with
`tidyr::extract()`
is that although it extracts the digits beautifully I have not been able to find a set of arguments that handles both 3 & 4 digit integers:

``````dfext <- data.frame(code = c(403, 5123, 105))
dfext <- dfext %>%
extract(
code, c("d4", "d3", "d2", "d1"), "(.)(.)(.)(.)", remove = FALSE
)

dfext
code   d4   d3   d2   d1
1  403 <NA> <NA> <NA> <NA>
2 5123    5    1    2    3
3  105 <NA> <NA> <NA> <NA>
``````

Perhaps I have not understood how to construct the correct regex code for my purpose...

I have looked at related questions on StackOverflow including this one about separate() and this one about extract(), but I could not see how to apply the answers to my own problem. The question here gives a solution for a variable with values of fixed length, not variable.

Any help, tips or observations would be much appreciated!

P.S. To give context, this is a data frame of dives in a diving competition. Every row represents one dive, a single observation with multiple grouping variables: name, age, sex, dive number (e.g. 1 of 5), board height, dive code, dive position, tariff, J1 award, J2 award, ... J5 award, total award (dropping highest & lowest awards), & score (total award multiplied by tariff). The codes are determined by FINA

We can use `stri_list2matrix` from `stringi` after splitting with `strsplit`

``````n <- max(nchar(df\$code)) #get the maximum number of characters
fmt <- paste0('%', n, 'd') #create a format for the `sprintf`
library(stringi)
#the list output from `strsplit` can be coerced to `matrix` using
#stri_list2matrix.
d1 <- stri_list2matrix(strsplit(sprintf( fmt, df\$code), ''), byrow=TRUE)
#But, the output is character class, which we can convert to 'numeric'
m1 <- matrix(as.numeric(d1), ncol=ncol(d1), nrow=nrow(d1))
m1
#     [,1] [,2] [,3] [,4]
#[1,]   NA    4    0    3
#[2,]    5    1    2    3
#[3,]   NA    1    0    5
``````

For the 'dfsep' dataset

``````v1 <- gsub('\\s+', '', dfsep\$code)
n <- max(nchar(v1))
fmt <- paste0('%', n, 's')
d1  <- stri_list2matrix(strsplit(sprintf(fmt, v1), ''), byrow=TRUE)
m1 <- matrix(as.numeric(d1), ncol=ncol(d1), nrow=nrow(d1))
m1
#     [,1] [,2] [,3] [,4]
#[1,]   NA    4    0    3
#[2,]    5    1    2    3
#[3,]   NA    1    0    5
``````

We can `cbind` with the original dataset

``````cbind(dfsep, m1)
``````

This can be made into a function for applying to different datasets.

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