Mutate several columns based on one condition-CodePudding

I'd like to assign different values to several columns, based on the value in another column, i.e. do a multiple mutate based on a single condition.

For example, I would have a dataframe like this:

df <- tibble(cfr = c("IRL000I12572", "ESP000023522", "ESP000023194"), 
             vessel_name = c("RACHEL JAY", "ALAKRANTXU", "DONIENE"), 
             length = c(NA, NA, 109.30),
             tonnage = c(NA, NA, 3507.00), 
             power = c(NA, NA, 7149.05))

I'd like to manually assign a set of values to length, tonnage, and power when cfr == IRL000I12572, another set of values when cfr == ESP000023522, and keep the given values when cfr == ESP000023194.

Right know, I'm doing it using either an ifelse or case_when statement in my mutate, but I end up with three rows per cfr (and I have many)... For example:

df <- df %>%
mutate(length = ifelse(cfr == "IRL000I12572", 22.5, length),
tonnage = ifelse(cfr == "IRL000I12572", 153.00, tonnage),
power = ifelse(cfr == "IRL000I12572", 370, power))

Is there a way to 'condense' the statement and have only one per cfr value, to assign the three different length, tonnage, and power values in one row?

Thanks!

CodePudding user response：

In base R you could do:

df[df$cfr == "IRL000I12572", -c(1:2)] <- list(22.5, 153.00, 370)

So that

df
#> # A tibble: 3 x 5
#>   cfr          vessel_name length tonnage power
#>   <chr>        <chr>        <dbl>   <dbl> <dbl>
#> 1 IRL000I12572 RACHEL JAY    22.5     153  370 
#> 2 ESP000023522 ALAKRANTXU    NA        NA   NA 
#> 3 ESP000023194 DONIENE      109.     3507 7149.

CodePudding user response：

You can use rows_update() from dplyr. Note that this is marked as an experimental function, so use at your own risk!

library(dplyr)

df <- tibble(cfr = c("IRL000I12572", "ESP000023522", "ESP000023194"), 
             vessel_name = c("RACHEL JAY", "ALAKRANTXU", "DONIENE"), 
             length = c(NA, NA, 109.30),
             tonnage = c(NA, NA, 3507.00), 
             power = c(NA, NA, 7149.05))

df_update <- tibble(cfr = "IRL000I12572",
                    length = 22.5,
                    tonnage = 153.00,
                    power = 370)

df %>% 
  rows_update(df_update, by = "cfr")

# A tibble: 3 x 5
  cfr          vessel_name length tonnage power
  <chr>        <chr>        <dbl>   <dbl> <dbl>
1 IRL000I12572 RACHEL JAY    22.5     153  370 
2 ESP000023522 ALAKRANTXU    NA        NA   NA 
3 ESP000023194 DONIENE      109.     3507 7149.

You can also make use of across to pull from a reference list (or vector). But this would require a different reference table or some other code feature per lookup ID.

x <- list(length = 22.5,
          tonnage = 153.00,
          power = 370)

df %>% 
  mutate(across(names(x), ~ ifelse(cfr == "IRL000I12572", x[[cur_column()]], .)))