Closed njtierney closed 7 years ago
ggplot2::scale_y_reverse()
seems to take care of this for both vis_dat()
and vis_miss()
.
# i.e.
airquality %>%
vis_miss() +
ggplot2::scale_y_reverse()
Thanks for that, I also wanted to flip the axis on to the top so it more closely resembles a dataframe.
Here's the new options
library(visdat)
tibble::as_tibble(airquality)
#> # A tibble: 153 × 6
#> Ozone Solar.R Wind Temp Month Day
#> <int> <int> <dbl> <int> <int> <int>
#> 1 41 190 7.4 67 5 1
#> 2 36 118 8.0 72 5 2
#> 3 12 149 12.6 74 5 3
#> 4 18 313 11.5 62 5 4
#> 5 NA NA 14.3 56 5 5
#> 6 28 NA 14.9 66 5 6
#> 7 23 299 8.6 65 5 7
#> 8 19 99 13.8 59 5 8
#> 9 8 19 20.1 61 5 9
#> 10 NA 194 8.6 69 5 10
#> # ... with 143 more rows
vis_dat(airquality)
vis_dat(airquality,flip = TRUE)
vis_miss(airquality)
vis_miss(airquality,flip = TRUE)
This is so vis_dat and vis_miss etc look more like a dataframe, where the axis labels are on the top, and the row numbers go from 1 - the total number.