[R] DPLYR Multiple Mutate Statements On Same DataFrame

Hadley Wickham h@w|ckh@m @end|ng |rom gm@||@com
Sat Oct 19 19:41:24 CEST 2024


Out of interest, I asked chatGPT to take the original code, convert it to
tidyverse style, use the base pipe, and collapse to a single mutate
(interestingly I didn't need to explicitly ask to use across() and
case_when), and I got code pretty similar to yours:

df3 <- df0 |>
  mutate(
    across(starts_with('P'), ~ case_when(
      .x == 0 ~ 0,
      .x == 1 ~ 25,
      .x == 2 ~ 75,
      .x == 3 ~ 150,
      .x == 4 ~ 350,
      .x == 5 ~ 750,
      .x == 6 ~ 3000,
      .x == 7 ~ 7500,
      .x == 8 ~ 15000,
      .x == 9 ~ 30000,
      TRUE ~ -99
    )),
    across(MRELGE:MSKC, ~ case_when(
      .x == 0 ~ 0,
      .x == 1 ~ 5,
      TRUE ~ -99
    )),
    MGODRK = case_when(
      MGODRK == 0 ~ 0,
      MGODRK == 1 ~ 5,
      TRUE ~ -99
    )
  )

Hadley



On Fri, Oct 18, 2024 at 2:56 AM Rui Barradas <ruipbarradas using sapo.pt> wrote:

> Às 08:27 de 18/10/2024, Rui Barradas escreveu:
> > Às 22:50 de 17/10/2024, Sparks, John escreveu:
> >> Hi R Helpers,
> >>
> >> I have been looking for an example of how to execute different dplyr
> >> mutate statements on the same dataframe in a single step.  I show how
> >> to do what I want to do by going from df0 to df1 to df2 to df3 by
> >> applying a mutate statement to each dataframe in sequence, but I would
> >> like to know if there is a way to execute this in a single step; so
> >> simply go from df0 to df1 while executing all the transformations.
> >> See example below.
> >>
> >> Guidance would be appreciated.
> >> --John J. Sparks, Ph.D.
> >>
> >> library(dplyr)
> >> df0<-structure(list(SeqNum = c(1L, 2L, 3L, 4L, 5L, 6L, 8L, 9L, 10L,
> >> 11L, 12L, 13L, 14L, 15L, 16L, 18L, 19L, 21L, 22L, 23L), MOSTYP = c(37L,
> >> 41L, 41L, 13L, 3L, 27L, 37L, 37L, 15L, 14L, 13L, 37L, 4L, 27L,
> >> 37L, 26L, 17L, 37L, 37L, 17L), MGEMOM = c(1L, 1L, 1L, 1L, 1L,
> >> 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L),
> >>      MGODRK = c(3L, 2L, 2L, 3L, 4L, 2L, 2L, 2L, 3L, 4L, 3L, 2L,
> >>      3L, 1L, 2L, 3L, 4L, 4L, 3L, 3L), MOSHOO = c(7L, 7L, 7L, 2L,
> >>      9L, 4L, 7L, 7L, 2L, 2L, 2L, 7L, 9L, 4L, 7L, 4L, 2L, 7L, 7L,
> >>      2L), MRELGE = c(0L, 1L, 0L, 2L, 1L, 0L, 0L, 0L, 3L, 1L, 1L,
> >>      1L, 0L, 0L, 0L, 0L, 2L, 0L, 0L, 1L), MSKB2 = c(5L, 4L, 4L,
> >>      3L, 4L, 5L, 7L, 1L, 5L, 4L, 3L, 4L, 5L, 6L, 7L, 5L, 4L, 6L,
> >>      4L, 7L), MFWEKI = c(1L, 1L, 2L, 2L, 1L, 0L, 0L, 3L, 0L, 1L,
> >>      2L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 2L, 0L), MAANTH = c(3L, 4L,
> >>      4L, 4L, 4L, 5L, 2L, 6L, 2L, 4L, 4L, 4L, 4L, 2L, 2L, 4L, 3L,
> >>      3L, 3L, 2L), MHHUUR = c(2L, 2L, 4L, 2L, 2L, 3L, 0L, 3L, 2L,
> >>      2L, 2L, 3L, 1L, 6L, 0L, 2L, 2L, 0L, 2L, 2L), MSKA = c(1L,
> >>      0L, 4L, 2L, 2L, 3L, 0L, 3L, 2L, 0L, 2L, 3L, 1L, 5L, 0L, 0L,
> >>      1L, 0L, 0L, 1L), MAUT2 = c(2L, 4L, 4L, 3L, 4L, 5L, 5L, 3L,
> >>      2L, 3L, 3L, 4L, 4L, 3L, 5L, 2L, 3L, 3L, 2L, 3L), MFALLE = c(1L,
> >>      0L, 0L, 3L, 5L, 0L, 0L, 0L, 0L, 4L, 1L, 1L, 2L, 2L, 0L, 2L,
> >>      5L, 0L, 0L, 3L), MGEMLE = c(1L, 0L, 0L, 0L, 4L, 0L, 0L, 0L,
> >>      0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 3L, 2L, 0L), MAUT1 = c(2L,
> >>      5L, 7L, 3L, 0L, 4L, 2L, 1L, 3L, 9L, 5L, 3L, 2L, 4L, 2L, 1L,
> >>      3L, 0L, 4L, 2L), MINKGE = c(2L, 4L, 2L, 2L, 0L, 2L, 2L, 1L,
> >>      3L, 0L, 1L, 4L, 2L, 2L, 2L, 5L, 1L, 0L, 3L, 1L), MOPLHO = c(1L,
> >>      0L, 0L, 0L, 0L, 2L, 2L, 1L, 2L, 0L, 0L, 1L, 0L, 0L, 2L, 0L,
> >>      0L, 0L, 0L, 0L), MGODPR = c(1L, 2L, 2L, 0L, 1L, 3L, 2L, 3L,
> >>      2L, 1L, 2L, 3L, 0L, 3L, 2L, 2L, 2L, 0L, 2L, 1L), MAUT0 = c(8L,
> >>      6L, 9L, 7L, 5L, 9L, 6L, 7L, 6L, 5L, 4L, 7L, 8L, 5L, 6L, 7L,
> >>      5L, 9L, 9L, 5L), MSKB1 = c(0L, 2L, 4L, 1L, 0L, 5L, 2L, 7L,
> >>      2L, 0L, 3L, 3L, 3L, 4L, 2L, 0L, 2L, 3L, 3L, 1L), MSKC = c(4L,
> >>      5L, 3L, 4L, 6L, 3L, 3L, 2L, 4L, 8L, 3L, 3L, 4L, 3L, 3L, 4L,
> >>      4L, 3L, 3L, 5L), PAANHA = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> >>      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), PWAPAR = c(0L,
> >>      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> >>      0L, 0L, 0L, 0L), PPERSA = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> >>      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), AMOTSC = c(0L,
> >>      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> >>      0L, 0L, 0L, 0L), APERSA = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> >>      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), AWAPAR = c(1L,
> >>      1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 1L,
> >>      1L, 0L, 1L, 1L), Resp = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
> >>      0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(NA,
> >> 20L), class = "data.frame")
> >>
> >>
> >> df1<-df0 %>%
> >>    mutate(across(starts_with('P'),~ifelse(.x==0,   0,
> >>                                    ifelse(.x==1,   25,
> >>   ifelse(.x==2,   75,
> >>   ifelse(.x==3,  150,
> >>   ifelse(.x==4,  350,
> >>   ifelse(.x==5,  750,
> >>   ifelse(.x==6, 3000,
> >>   ifelse(.x==7, 7500,
> >>   ifelse(.x==8,15000,
> >>   ifelse(.x==9,30000,
> >>   -99))))))))))))
> >>
> >> df2<-df1 %>%
> >> mutate_at(vars(MRELGE:MSKC),~ifelse(.x==0,  0,
> >>                               ifelse(.x==1,  5,
> >> -99)))
> >> df3<-df2 %>%
> >> mutate_at(vars(MGODRK),~ifelse(.x==0,  0,
> >>                          ifelse(.x==1,  5,
> >> -99)))
> >>
> >>
> >>
> >>
> >>     [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> 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 https://www.R-project.org/posting-
> >> guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> > Hello,
> >
> > Use chained mutate() %>% mutate(). In the 2nd mutate I don't even have
> > to pipe a third time, the final variable is changed in the same
> > instruction.
> >
> > Also use mutate(across(...)), mutate_at is deprecated.
> >
> > And use ?case_when instead of nested ifelse's. It's much cleaner.
> >
> > As you can see, the result is identical to your code's result.
> >
> >
> >
> > library(dplyr)
> >
> > df3b <- df0 %>%
> >    mutate(
> >      across(starts_with('P'), ~case_when(
> >        .x == 0 ~ 0,
> >        .x == 1 ~ 25,
> >        .x == 2 ~ 75,
> >        .x == 3 ~ 150,
> >        .x == 4 ~ 350,
> >        .x == 5 ~ 750,
> >        .x == 6 ~ 3000,
> >        .x == 7 ~ 7500,
> >        .x == 8 ~ 15000,
> >        .x == 9 ~ 30000,
> >        TRUE ~ -99
> >      ))
> >    ) %>%
> >    mutate(
> >      across(MRELGE:MSKC, ~case_when(
> >        .x == 0 ~ 0,
> >        .x == 1 ~ 5,
> >        TRUE ~ -99
> >      )),
> >      MGODRK = case_when(
> >        MGODRK == 0 ~ 0,
> >        MGODRK == 1 ~ 5,
> >        TRUE ~ -99
> >      ))
> >
> > identical(df3, df3b)
> > # [1] TRUE
> >
> >
> > And you can have just one mutate, as long as you respect the order the
> > variables are changed.
> >
> >
> >
> > df3c <- df0 %>%
> >    mutate(
> >      across(starts_with('P'), ~case_when(
> >        .x == 0 ~ 0,
> >        .x == 1 ~ 25,
> >        .x == 2 ~ 75,
> >        .x == 3 ~ 150,
> >        .x == 4 ~ 350,
> >        .x == 5 ~ 750,
> >        .x == 6 ~ 3000,
> >        .x == 7 ~ 7500,
> >        .x == 8 ~ 15000,
> >        .x == 9 ~ 30000,
> >        TRUE ~ -99
> >      )),
> >      across(MRELGE:MSKC, ~case_when(
> >        .x == 0 ~ 0,
> >        .x == 1 ~ 5,
> >        TRUE ~ -99
> >      )),
> >      MGODRK = case_when(
> >        MGODRK == 0 ~ 0,
> >        MGODRK == 1 ~ 5,
> >        TRUE ~ -99
> >      )
> >    )
> >
> > identical(df3, df3c)
> > # [1] TRUE
> >
> >
> > Hope this helps,
> >
> > Rui Barradas
> >
> >
> Hello,
>
> Two other simpler solutions.
> In the pipes above you can put the two last case_when statements together.
>
>
>
> df3d <- df0 %>%
>    mutate(
>      across(starts_with('P'), ~case_when(
>        .x == 0 ~ 0,
>        .x == 1 ~ 25,
>        .x == 2 ~ 75,
>        .x == 3 ~ 150,
>        .x == 4 ~ 350,
>        .x == 5 ~ 750,
>        .x == 6 ~ 3000,
>        .x == 7 ~ 7500,
>        .x == 8 ~ 15000,
>        .x == 9 ~ 30000,
>        TRUE ~ -99
>      )),
>      across(c(MGODRK, MRELGE:MSKC), ~case_when(
>        .x == 0 ~ 0,
>        .x == 1 ~ 5,
>        TRUE ~ -99
>      ))
>    )
>
> identical(df3, df3d)
> # [1] TRUE
>
>
>
> And this one combines ifelse with case_when. But you need to create an
> auxiliary variable of the new values for the 'P' case.
>
>
>
> P_new_vals <- c(0, 25, 75, 150, 350, 750, 3000, 7500, 15000, 30000)
> df3e <- df0 %>% mutate(
>    across(starts_with('P'), ~ifelse(.x %in% 0:9, P_new_vals[.x + 1L],
> -99)),
>    across(c(MGODRK, MRELGE:MSKC), ~case_when(
>      .x == 0 ~ 0,
>      .x == 1 ~ 5,
>      TRUE ~ -99
>    ))
> )
> identical(df3, df3e)
> # [1] TRUE
>
>
> Hope this helps,
>
> Rui Barradas
>
>
> --
> Este e-mail foi analisado pelo software antivírus AVG para verificar a
> presença de vírus.
> www.avg.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
> https://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
http://hadley.nz

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