This is a generic function to replace NA values in data. It takes most data types as input and is extendible by other packages.
na_replace(x, ...)
# Default S3 method
na_replace(x, replacement = "", ...)
# S3 method for class 'data.frame'
na_replace(x, ..., replacement = NULL)
# S3 method for class 'matrix'
na_replace(x, replacement = 0, ...)
# S3 method for class 'list'
na_replace(x, replacement = NULL, ...)
# S3 method for class 'numeric'
na_replace(x, replacement = 0, ...)
# S3 method for class 'Date'
na_replace(x, replacement = Sys.Date(), ...)
# S3 method for class 'logical'
na_replace(x, replacement = FALSE, ...)any vector, data.frame, matrix or list with values of which NA must be replaced
When x is a data.frame: columns of x to affect. This supports tidy evaluation without the need to quote the columns, see Examples.
value to replace NA with. This is at default: 0 for numeric values and class matrix, FALSE for class logical, today for class Date, and "" otherwise. Can also be a vector with the length of the number of NAs of x (sum(is.na(x))). When x is a data.frame, this can be a vector with the length of the number of columns to be affected, see Examples.
All functions preserve attributes. Within a list or data.frame, all attributes per index/item/column are also preserved.
mtrx <- matrix(c(1, 2, NA, 3), nrow = 2)
mtrx
#> [,1] [,2]
#> [1,] 1 NA
#> [2,] 2 3
na_replace(mtrx)
#> [,1] [,2]
#> [1,] 1 0
#> [2,] 2 3
na_replace(c(1, 2, NA, NA))
#> [1] 1 2 0 0
na_replace(c(1, 2, NA, NA), replacement = -1)
#> [1] 1 2 -1 -1
na_replace(c(1, 2, NA, NA), replacement = c(0, -1))
#> [1] 1 2 0 -1
na_replace(c(Sys.Date(), NA)) # replacement defaults to 'today'
#> [1] "2024-11-19" "2024-11-19"
na_replace(c(TRUE, FALSE, NA))
#> [1] TRUE FALSE FALSE
na_replace(c(TRUE, FALSE, NA), replacement = TRUE)
#> [1] TRUE FALSE TRUE
# we're flexible, the class only remains the same if
# the replacement value allows it
na_replace(c(1, 2, 3, NA), replacement = "-")
#> [1] "1" "2" "3" "-"
# data.frame is a special case
mtcars[1:6, c("mpg", "hp")] <- NA
head(mtcars)
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 NA 6 160 NA 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag NA 6 160 NA 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 NA 4 108 NA 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive NA 6 258 NA 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout NA 8 360 NA 3.15 3.440 17.02 0 0 3 2
#> Valiant NA 6 225 NA 2.76 3.460 20.22 1 0 3 1
head(na_replace(mtcars, mpg, hp)) # no need to quote columns (but you can)
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 0 6 160 0 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 0 6 160 0 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 0 4 108 0 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 0 6 258 0 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 0 8 360 0 3.15 3.440 17.02 0 0 3 2
#> Valiant 0 6 225 0 2.76 3.460 20.22 1 0 3 1
head(na_replace(mtcars, mpg, hp, replacement = c(999, 123)))
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> Mazda RX4 999 6 160 123 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 999 6 160 123 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 999 4 108 123 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 999 6 258 123 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 999 8 360 123 3.15 3.440 17.02 0 0 3 2
#> Valiant 999 6 225 123 2.76 3.460 20.22 1 0 3 1
if (FALSE) { # \dontrun{
# practical way using tidyverse
library(dplyr)
starwars %>%
na_replace()
# even maintains groups
starwars %>%
group_by(hair_color) %>%
na_replace(hair_color, replacement = "TEST!") %>%
summarise(n = n())
} # }