naniar (version 1.1.0)

impute_mean: Impute the mean value into a vector with missing values

Description

This can be useful if you are imputing specific values, however we would generally recommend to impute using other model based approaches. See the simputation package, for example simputation::impute_lm().

Usage

impute_mean(x)
# S3 method for default
impute_mean(x)
# S3 method for factor
impute_mean(x)

Value

vector with mean values replaced

Arguments

x

vector

Examples

library(dplyr)
vec <- rnorm(10)

vec[sample(1:10, 3)] <- NA

impute_mean(vec)

dat <- tibble(
  num = rnorm(10),
  int = as.integer(rpois(10, 5)),
  fct = factor(LETTERS[1:10])
) %>%
  mutate(
    across(
      everything(),
      \(x) set_prop_miss(x, prop = 0.25)
    )
  )

dat

dat %>%
  nabular() %>%
  mutate(
    num = impute_mean(num),
    int = impute_mean(int),
    fct = impute_mean(fct),
  )

dat %>%
  nabular() %>%
  mutate(
    across(
      where(is.numeric),
      impute_mean
    )
  )

dat %>%
  nabular() %>%
  mutate(
    across(
      c("num", "int"),
      impute_mean
    )
  )