vis_miss() column %s NA when % = 0.1

[jenniferthompson]

I have a column with 0.1% missing, and the column percentage is NA instead of 0.1%. I think the issue is that the case_when() call in label_col_missing_pct doesn't account for the case when x == 0.1; guessing it should be fixed by changing line 80 to >= instead of >. My attempts at a reprex were failing, but happy to try again or submit a PR if either would help!

visdat/R/internals.R

Lines 78 to 82 in de3186b

	dplyr::case_when(
	x == 0 ~ "0%",
	x > 0.1 ~ paste0(x,"%"),
	x < 0.1 ~ "<0.1%"
	)

[njtierney]

@jenniferthompson !

Sorry I have overlooked this. This is indeed the case, thank you so much for linking to this line of code, this has made this much easier to debug!

OK, so here is pre the change:

library(visdat)
library(tibble)

temp <- rnorm(n = 10000,
              mean = 25,
              sd = 2.5)

temp[1:10] <- NA

wind <- rnorm(n = 10000,
              mean = 15,
              sd = 7.5)

wind[1:12] <- NA

ozone <- rnorm(n = 10000,
               mean = 43,
               sd = 30)

ozone[1:8] <- NA

dat <- tibble(temp,
              wind,
              ozone)

dat
#> # A tibble: 10,000 x 3
#>     temp  wind ozone
#>    <dbl> <dbl> <dbl>
#>  1    NA    NA NA   
#>  2    NA    NA NA   
#>  3    NA    NA NA   
#>  4    NA    NA NA   
#>  5    NA    NA NA   
#>  6    NA    NA NA   
#>  7    NA    NA NA   
#>  8    NA    NA NA   
#>  9    NA    NA 16.3 
#> 10    NA    NA  4.26
#> # ... with 9,990 more rows

vis_miss(dat)

Created on 2018-03-20 by the reprex package (v0.2.0).

This once I made a change to lines 76 and 80

library(visdat)
library(tibble)

temp <- rnorm(n = 10000,
              mean = 25,
              sd = 2.5)

temp[1:10] <- NA

wind <- rnorm(n = 10000,
              mean = 15,
              sd = 7.5)

wind[1:12] <- NA

ozone <- rnorm(n = 10000,
               mean = 43,
               sd = 30)

ozone[1:8] <- NA

dat <- tibble(temp,
              wind,
              ozone)

dat
#> # A tibble: 10,000 x 3
#>     temp  wind ozone
#>    <dbl> <dbl> <dbl>
#>  1    NA    NA  NA  
#>  2    NA    NA  NA  
#>  3    NA    NA  NA  
#>  4    NA    NA  NA  
#>  5    NA    NA  NA  
#>  6    NA    NA  NA  
#>  7    NA    NA  NA  
#>  8    NA    NA  NA  
#>  9    NA    NA  47.1
#> 10    NA    NA  17.3
#> # ... with 9,990 more rows

vis_miss(dat)

Created on 2018-03-20 by the reprex package (v0.2.0).

I think that is it - but please feel free to open this if it doesn't work :)