[R] DPLYR Multiple Mutate Statements On Same DataFrame

[CALUM POLWART]

Why can't you do:

df0 |> mutate( ... ) |>
  mutate( ... ) |>
  mutate( ... )

I've simplified the code to show passing the result of the first line to
the next rather than focussing on the detail. This would work with %>% as
well as |> but I am anticipating that the more modern native pipe ( |> )
will become the norm in the future.

BTW - mutate_at is depreciated as far as I know, so you'd be more future
proof to use mutate( across( ... ) )

You can use mutate more than one thing in a single mutate

df |> mutate (
  surname = to.upper(surname),
  initial = substring(first name, 1, 1)
  )

is the same as:

df |> mutate (
    surname = to.upper(surname)) |>
  mutate (
  initial = substring(first name, 1, 1)
  )

Or

df |> mutate (
  surname = to.upper(surname)
  ) -> df2

df2 |>
  mutate (
  initial = substring(first name, 1, 1)
  )

On Thu, 17 Oct 2024, 22:51 Sparks, John, <jspark4 using uic.edu> wrote:

> 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)))
>
>
>
>
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>
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