[SOLVED] collapse: Modifying Columns by row along with combine values from multiple columns

collapse: Modifying Columns by row along with combine values from multiple columns

I want to translate the following R code using tidytable into collapse: Advanced and Fast Data Transformation.

tidytable Code

library(tidytable)
library(collapse)
Out1 <- 
  wlddev %>% 
  mutate_rowwise.(New1 = sum(c_across.(PCGDP:GINI), na.rm = TRUE))
Out1 %>% 
  select.(New1)
# A tidytable: 13,176 x 1
    New1
   <dbl>
 1  32.4
 2  33.0
 3  33.5
 4  34.0
 5  34.5
 6  34.9
 7  35.4
 8  35.9
 9  36.4
10  36.9
# ... with 13,166 more rows

collapse Code

library(collapse)
Out2 <- 
  wlddev %>% 
  ftransform(New1 = fsum(across(PCGDP:GINI), na.rm = TRUE))

  Error in `context_peek()`:
  ! `across()` must only be used inside dplyr verbs.
  Run `rlang::last_error()` to see where the error occurred.

Any hint please.

Solution

I wonder why you need to come up with something so complex. You have functions like rowSums in base R, and you have parallel statistical functions in kit:

library(collapse)
library(magrittr)
library(kit, include.only = "psum")  
library(microbenchmark)
  
microbenchmark(
A = wlddev %>%
  ftransform(New1 = rowSums(qM(slt(., PCGDP:GINI)), na.rm = TRUE)),
B = wlddev %>%
  ftransform(New1 = psum(slt(., PCGDP:GINI), na.rm = TRUE)), 
C = wlddev %>%
  ftransform(New1 = psum(PCGDP, LIFEEX, GINI, na.rm = TRUE))
)

#> Unit: microseconds
#>  expr   min      lq      mean   median       uq      max neval
#>     A 68.88 97.8875 194.24037 102.2335 113.8775 4646.366   100
#>     B 25.83 30.1350  35.43548  34.9115  38.6630   56.416   100
#>     C 22.55 25.8095  29.99396  30.5860  32.9025   53.792   100

^{Created on 2022-02-05 by the reprex package (v2.0.1)}