As an alternative to bind_shadow()
, you can add specific individual shadow
columns to a dataset. These also respect the dplyr verbs
starts_with
, contains
, ends_with
, etc.
add_shadow(data, ...)
data | data.frame |
---|---|
... | One or more unquoted variable names, separated by commas. These also
respect the dplyr verbs |
data.frame
bind_shadow()
add_any_miss()
add_label_missings()
add_label_shadow()
add_miss_cluster()
add_n_miss()
add_prop_miss()
add_shadow_shift()
cast_shadow()
airquality %>% add_shadow(Ozone)#> # A tibble: 153 x 7 #> Ozone Solar.R Wind Temp Month Day Ozone_NA #> <int> <int> <dbl> <int> <int> <int> <fct> #> 1 41 190 7.4 67 5 1 !NA #> 2 36 118 8 72 5 2 !NA #> 3 12 149 12.6 74 5 3 !NA #> 4 18 313 11.5 62 5 4 !NA #> 5 NA NA 14.3 56 5 5 NA #> 6 28 NA 14.9 66 5 6 !NA #> 7 23 299 8.6 65 5 7 !NA #> 8 19 99 13.8 59 5 8 !NA #> 9 8 19 20.1 61 5 9 !NA #> 10 NA 194 8.6 69 5 10 NA #> # … with 143 more rowsairquality %>% add_shadow(Ozone, Solar.R)#> # A tibble: 153 x 8 #> Ozone Solar.R Wind Temp Month Day Ozone_NA Solar.R_NA #> <int> <int> <dbl> <int> <int> <int> <fct> <fct> #> 1 41 190 7.4 67 5 1 !NA !NA #> 2 36 118 8 72 5 2 !NA !NA #> 3 12 149 12.6 74 5 3 !NA !NA #> 4 18 313 11.5 62 5 4 !NA !NA #> 5 NA NA 14.3 56 5 5 NA NA #> 6 28 NA 14.9 66 5 6 !NA NA #> 7 23 299 8.6 65 5 7 !NA !NA #> 8 19 99 13.8 59 5 8 !NA !NA #> 9 8 19 20.1 61 5 9 !NA !NA #> 10 NA 194 8.6 69 5 10 NA !NA #> # … with 143 more rows