impute_below_at: Scoped variants of 'impute_below'

In njtierney/naniar: Data Structures, Summaries, and Visualisations for Missing Data

Scoped variants of impute_below

Description

impute_below imputes missing values to a set percentage below the range of the data. To impute many variables at once, we recommend that you use the across function workflow, shown in the examples for impute_below(). impute_below_all operates on all variables. To only impute variables that satisfy a specific condition, use the scoped variants, impute_below_at, and impute_below_if. To use ⁠_at⁠ effectively, you must know that ⁠_at`` affects variables selected with a character vector, or with ⁠vars()'.

Usage

impute_below_at(.tbl, .vars, prop_below = 0.1, jitter = 0.05, ...)

Arguments

.tbl	a data.frame
.vars	variables to impute
prop_below	the degree to shift the values. default is
jitter	the amount of jitter to add. default is 0.05
...	extra arguments

Details

Value

an dataset with values imputed

Examples

# select variables starting with a particular string.
impute_below_at(airquality,
                .vars = c("Ozone", "Solar.R"))

impute_below_at(airquality, .vars = 1:2)

## Not run: 
library(dplyr)
impute_below_at(airquality,
                .vars = vars(Ozone))

library(ggplot2)
airquality %>%
  bind_shadow() %>%
  impute_below_at(vars(Ozone, Solar.R)) %>%
  add_label_shadow() %>%
  ggplot(aes(x = Ozone,
             y = Solar.R,
             colour = any_missing)) +
         geom_point()

## End(Not run)

njtierney/naniar documentation built on March 19, 2024, 9:48 p.m.