Extract

Nice! -- Let read.table do the work of handling the NA's.
However, even simpler is to use the 'colnames' argument of
read.table() for the column names no?

      string <- read.table(text = dat$string, fill = TRUE, header =
FALSE, na.strings = "",
col.names = paste0("s", 1:5))
      dat <- cbind(dat, string)

-- Bert

On Sun, Jul 21, 2024 at 10:16?AM Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:

We can use read.table for a base R solution

string <- read.table(text = dat$string, fill = TRUE, header = FALSE,
na.strings = "")
names(string) <- paste0("S", seq_along(string))
cbind(dat[-3], string)

On Fri, Jul 19, 2024 at 12:52?PM Val <valkremk at gmail.com> wrote:

Hi All,

I want to extract new variables from a string and add it to the dataframe.
Sample data is csv file.

dat<-read.csv(text="Year, Sex,string
2002,F,15 xc Ab
2003,F,14
2004,M,18 xb 25 35 21
2005,M,13 25
2006,M,14 ac 256 AV 35
2007,F,11",header=TRUE)

The string column has  a maximum of five variables. Some rows have all
and others may not have all the five variables. If missing then  fill
it with NA,
Desired result is shown below,


Year,Sex,string, S1, S2, S3 S4,S5
2002,F,15 xc Ab, 15,xc,Ab, NA, NA
2003,F,14, 14,NA,NA,NA,NA
2004,M,18 xb 25 35 21,18, xb, 25, 35, 21
2005,M,13 25,13, 25,NA,NA,NA
2006,M,14 ac 256 AV 35, 14, ac, 256, AV, 35
2007,F,11, 11,NA,NA,NA,NA

Any help?
Thank you in advance.

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