Find the first non-missing element

Given a set of vectors, coalesce() finds the first non-missing value at each position. It's inspired by the SQL COALESCE function which does the same thing for SQL NULLs.

Usage

coalesce(..., .ptype = NULL, .size = NULL)

Arguments

...

<dynamic-dots>

One or more vectors. These will be recycled against each other, and will be cast to their common type.

.ptype

An optional prototype declaring the desired output type. If supplied, this overrides the common type of the vectors in ....

.size

An optional size declaring the desired output size. If supplied, this overrides the common size of the vectors in ....

Value

A vector with the same type and size as the common type and common size of the vectors in ....

See also

• na_if() to replace a specified value with NA.

• replace_values() for making arbitrary replacements by value.

• replace_when() for making arbitrary replacements using logical conditions.

Examples

# Replace missing values with a single value
x <- sample(c(1:5, NA, NA, NA))
coalesce(x, 0L)
#> [1] 1 0 5 0 3 2 4 0

# Or replace missing values with the corresponding non-missing value in
# another vector
x <- c(1, 2, NA, NA, 5, NA)
y <- c(NA, NA, 3, 4, 5, NA)
coalesce(x, y)
#> [1]  1  2  3  4  5 NA

# For cases like these where your replacement is a single value or a single
# vector, `replace_values()` works just as well
replace_values(x, NA ~ 0)
#> [1] 1 2 0 0 5 0
coalesce(x, 0)
#> [1] 1 2 0 0 5 0

replace_values(x, NA ~ y)
#> [1]  1  2  3  4  5 NA
coalesce(x, y)
#> [1]  1  2  3  4  5 NA

# `coalesce()` really shines when you have >2 vectors to coalesce with
z <- c(NA, 2, 3, 4, 5, 6)
coalesce(x, y, z)
#> [1] 1 2 3 4 5 6

# If you're looking to replace values with `NA`, rather than replacing `NA`
# with a value, then use `replace_values()`
x <- c(0, -1, 5, -99, 8)
replace_values(x, c(-1, -99) ~ NA)
#> [1]  0 NA  5 NA  8

# The equivalent to a missing value in a list is `NULL`
coalesce(list(1, 2, NULL, NA), list(0))
#> [[1]]
#> [1] 1
#> 
#> [[2]]
#> [1] 2
#> 
#> [[3]]
#> [1] 0
#> 
#> [[4]]
#> [1] NA
#> 

# Supply lists of vectors by splicing them into dots
vecs <- list(
  c(1, 2, NA, NA, 5),
  c(NA, NA, 3, 4, 5)
)
coalesce(!!!vecs)
#> [1] 1 2 3 4 5