R/cast-shadows.R
cast_shadow_shift_label.Rd
Shift the values, add shadow, add missing label
cast_shadow_shift_label(data, ...)
data | data.frame |
---|---|
... | One or more unquoted expressions separated by commas. These also respect the dplyr verbs "starts_with", "contains", "ends_with", etc. |
data.frame with the shadow and shadow_shift vars, and missing labels
cast_shadow_shift()
, cast_shadow_shift_label()
bind_shadow()
add_any_miss()
add_label_missings()
add_label_shadow()
add_miss_cluster()
add_prop_miss()
add_shadow_shift()
airquality %>% cast_shadow_shift_label(Ozone, Solar.R)#> # A tibble: 153 x 7 #> Ozone Solar.R Ozone_NA Solar.R_NA Ozone_shift Solar.R_shift any_missing #> <int> <int> <fct> <fct> <dbl> <dbl> <chr> #> 1 41 190 !NA !NA 41 190 Not Missing #> 2 36 118 !NA !NA 36 118 Not Missing #> 3 12 149 !NA !NA 12 149 Not Missing #> 4 18 313 !NA !NA 18 313 Not Missing #> 5 NA NA NA NA -19.7 -33.6 Missing #> 6 28 NA !NA NA 28 -33.1 Missing #> 7 23 299 !NA !NA 23 299 Not Missing #> 8 19 99 !NA !NA 19 99 Not Missing #> 9 8 19 !NA !NA 8 19 Not Missing #> 10 NA 194 NA !NA -18.5 194 Missing #> # … with 143 more rows# replicate the plot generated by geom_miss_point() if (FALSE) { library(ggplot2) airquality %>% cast_shadow_shift_label(Ozone,Solar.R) %>% ggplot(aes(x = Ozone_shift, y = Solar.R_shift, colour = any_missing)) + geom_point() }