[R] Extract

Gabor Grothendieck ggrothend|eck @end|ng |rom gm@||@com
Mon Jul 22 16:45:23 CEST 2024 

I had missed that one can pass fix.empty.names = TRUE to transform and
if we do that then we can
put an unnamed data.frame in transform like we can with mutate so
making that change we have the following
base R solution where there is an inner nested pipeline within the
outer pipeline as with the dplyr example.

  transform(dat,
    read.table(text = string, header = FALSE, na.strings = "", fill =
TRUE), fix.empty.names = TRUE) |>
      list(x = _) |>
      with( setNames(x, sub("V", "S", names(x)) )
    )


On Mon, Jul 22, 2024 at 7:49 AM Gabor Grothendieck
<ggrothendieck using gmail.com> wrote:
>
> Base R. Regarding code improvements:
>
> 1. Personally I find (\(...) ...)() notation hard to read (although by
> placing (\(x), the body and )() on 3 separate lines it can be improved
> somewhat). Instead let us use a named function. The name of the
> function can also serve to self document the code.
>
> 2. The use of dat both at the start of the pipeline and then again
> within a later step of the pipeline goes against a strict left to
> right flow. In general if this occurs it is either a sign that we need
> to break the pipeline into two or that we need to find another
> approach which is what we do here.
>
> We can use the base R code below. Note that the column names produced
> by transform(S = read.table(...)) are S.V1, S.V2, etc. so to fix the
> column names remove .V from all column names as in the fix_colnames
> function shown. It does no harm to apply that to all column names
> since the remaining column names will not match.
>
>   fix_colnames <- function(x) {
>     setNames(x, sub("\\.V", "", names(x)))
>   }
>
>   dat |>
>      transform(S = read.table(text = string,
>        header = FALSE, fill = TRUE, na.strings = "")) |>
>        fix_colnames()
>
> Another way to write this which does not use a separate defined
> function nor the anonymous function notation is to box the output of
> transform:
>
>   dat |>
>      transform(S = read.table(text = string,
>        header = FALSE, fill = TRUE, na.strings = "")) |>
>        list(x = _) |>
>        with( setNames(x, sub("\\.V", "", names(x))) )
>
> dplyr. Alternately use dplyr in which case we can make use of
> rename_with . In this case read.table(...) creates column names V1,
> V2, etc. and mutate does not change them so simply replacing V with S
> at the start of each column name in the output of read.table will do.
> Also we can pipe the read.table output directly to rename_with using a
> nested pipeline, i.e. the second pipe is entirely within mutate rather
> than after it) since mutate won't change the column names. The win
> here is because, unlike transform, mutate does not require the S= that
> is needed with transform (although it allows it had we wanted it).
>
>   library(dplyr)
>
>   dat |>
>      mutate(read.table(text = string,
>        header = FALSE, fill = TRUE, na.strings = "")  |>
>       rename_with(~ sub("^V", "S", .x))
>     )
>
>
> On Sun, Jul 21, 2024 at 3:08 PM Bert Gunter <bgunter.4567 using gmail.com> wrote:
> >
> > As always, good point.
> > Here's a piped version of your code for those who are pipe
> > afficianados. As I'm not very skilled with pipes, it might certainly
> > be improved.
> > dat <-
> >       dat$string |>
> >          read.table( text = _, fill = TRUE, header = FALSE, na.strings = "")  |>
> >          (\(x)'names<-'(x,paste0("s", seq_along(x))))() |>
> >          (\(x)cbind(dat, x))()
> >
> > -- Bert
> >
> >
> > On Sun, Jul 21, 2024 at 11:30 AM Gabor Grothendieck
> > <ggrothendieck using gmail.com> wrote:
> > >
> > > Fixing col.names=paste0("S", 1:5) assumes that there will be 5 columns and
> > > we may not want to do that.  If there are only 3 fields in string, at the most,
> > > we may wish to generate only 3 columns.
> > >
> > > On Sun, Jul 21, 2024 at 2:20 PM Bert Gunter <bgunter.4567 using gmail.com> wrote:
> > > >
> > > > 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$string, fill = TRUE, header =
> > > > FALSE, na.strings = "",
> > > > col.names = paste0("s", 1:5))
> > > >       dat <- cbind(dat, string)
> > > >
> > > > -- Bert
> > > >
> > > > On Sun, Jul 21, 2024 at 10:16 AM Gabor Grothendieck
> > > > <ggrothendieck using gmail.com> wrote:
> > > > >
> > > > > We can use read.table for a base R solution
> > > > >
> > > > > string <- read.table(text = dat$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 using 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.
> > > > > >
> > > > > > ______________________________________________
> > > > > > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > > > > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > > > > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > > > > > and provide commented, minimal, self-contained, reproducible code.
> > > > >
> > > > >
> > > > >
> > > > > --
> > > > > Statistics & Software Consulting
> > > > > GKX Group, GKX Associates Inc.
> > > > > tel: 1-877-GKX-GROUP
> > > > > email: ggrothendieck at gmail.com
> > > > >
> > > > > ______________________________________________
> > > > > R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > > > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > > > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > > > > and provide commented, minimal, self-contained, reproducible code.
> > >
> > >
> > >
> > > --
> > > Statistics & Software Consulting
> > > GKX Group, GKX Associates Inc.
> > > tel: 1-877-GKX-GROUP
> > > email: ggrothendieck at gmail.com
>
>
>
> --
> Statistics & Software Consulting
> GKX Group, GKX Associates Inc.
> tel: 1-877-GKX-GROUP
> email: ggrothendieck at gmail.com



-- 
Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com

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