Refactor tests and summary_rows()

[olivroy]

Avoid superseded mutate_all() replace this with is.na.data.frame(). (6x speed-up, but uses more memory)

Remove pipes in tests

Refactor some tests for clarity

Bench marks

aa <- naniar::oceanbuoys
library(dplyr)
#> 
#> Attachement du package : 'dplyr'
#> Les objets suivants sont masqués depuis 'package:stats':
#> 
#>     filter, lag
#> Les objets suivants sont masqués depuis 'package:base':
#> 
#>     intersect, setdiff, setequal, union

aa[1, 2] <- NaN
f <- function(x) {
  x[is.na(x)] <- NA
x
}

aa %>% dplyr::mutate_all( .funs = function(x) {
  x[is.nan(x)] <- NA 
  x
}) %>% waldo::compare(f(aa))
#> ✔ No differences

bench::mark(
  f(aa),
  aa |> dplyr::mutate(dplyr::across(dplyr::everything(), function(x) {
    x[is.nan(x)] <- NA 
    x
  })) ,
  aa %>% dplyr::mutate_all( .funs = function(x) {
    x[is.nan(x)] <- NA 
    x
  })
)
#> # A tibble: 3 × 6
#>   expression                           min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>                      <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 f(aa)                            485.7µs  656.3µs     1334.    4.23MB     8.65
#> 2 dplyr::mutate(aa, dplyr::acros…   2.56ms    3.2ms      279.  910.29KB    11.3 
#> 3 aa %>% dplyr::mutate_all(.funs…   2.72ms   3.09ms      302.   56.16KB    10.7

^{Created on 2024-06-25 with reprex v2.1.0}

note that base R doesn’t provide is.nan.data.frame() hence why we need to use is.na

[rich-iannone]

Looks great, thank you!