Shift missing values to facilitate missing data exploration/visualisation
shadow_shift
transforms missing values to facilitate visualisation, and has
different behaviour for different types of variables. For numeric
variables, the values are shifted to 10% below the minimum value for a given
variable plus some jittered noise, to separate repeated values, so that
missing values can be visualised along with the rest of the data.
shadow_shift(x, ...)
x |
a variable of interest to shift |
... |
extra arguments to pass |
airquality$Ozone shadow_shift(airquality$Ozone) ## Not run: library(dplyr) airquality %>% mutate(Ozone_shift = shadow_shift(Ozone)) ## End(Not run)
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