## Problem

You want to replace `NA`’s in a vector or factor with the last non-NA value.

## Solution

This code shows how to fill gaps in a vector. If you need to do this repeatedly, see the function below. The function also can fill in leading `NA`’s with the first good value and handle factors properly.

``````# Sample data
x <- c(NA,NA, "A","A", "B","B","B", NA,NA, "C", NA,NA,NA, "A","A","B", NA,NA)

goodIdx <- !is.na(x)
goodIdx
#>   FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE  TRUE
#>   TRUE  TRUE FALSE FALSE

# These are the non-NA values from x only
# Add a leading NA for later use when we index into this vector
goodVals <- c(NA, x[goodIdx])
goodVals
#>   NA  "A" "A" "B" "B" "B" "C" "A" "A" "B"

# Fill the indices of the output vector with the indices pulled from
# these offsets of goodVals. Add 1 to avoid indexing to zero.
fillIdx <- cumsum(goodIdx)+1
fillIdx
#>    1  1  2  3  4  5  6  6  6  7  7  7  7  8  9 10 10 10

# The original vector with gaps filled
goodVals[fillIdx]
#>   NA  NA  "A" "A" "B" "B" "B" "B" "B" "C" "C" "C" "C" "A" "A" "B" "B" "B"
``````

### A function for filling gaps

This function does the same as the code above. It can also fill leading `NA`’s with the first good value, and handle factors properly.

``````fillNAgaps <- function(x, firstBack=FALSE) {
## NA's in a vector or factor are replaced with last non-NA values
## If firstBack is TRUE, it will fill in leading NA's with the first
## non-NA value. If FALSE, it will not change leading NA's.

# If it's a factor, store the level labels and convert to integer
lvls <- NULL
if (is.factor(x)) {
lvls <- levels(x)
x    <- as.integer(x)
}

goodIdx <- !is.na(x)

# These are the non-NA values from x only
# Add a leading NA or take the first good value, depending on firstBack
if (firstBack)   goodVals <- c(x[goodIdx], x[goodIdx])
else             goodVals <- c(NA,            x[goodIdx])

# Fill the indices of the output vector with the indices pulled from
# these offsets of goodVals. Add 1 to avoid indexing to zero.
fillIdx <- cumsum(goodIdx)+1

x <- goodVals[fillIdx]

# If it was originally a factor, convert it back
if (!is.null(lvls)) {
x <- factor(x, levels=seq_along(lvls), labels=lvls)
}

x
}

# Sample data
x <- c(NA,NA, "A","A", "B","B","B", NA,NA, "C", NA,NA,NA, "A","A","B", NA,NA)
x
#>   NA  NA  "A" "A" "B" "B" "B" NA  NA  "C" NA  NA  NA  "A" "A" "B" NA  NA

fillNAgaps(x)
#>   NA  NA  "A" "A" "B" "B" "B" "B" "B" "C" "C" "C" "C" "A" "A" "B" "B" "B"

# Fill the leading NA's with the first good value
fillNAgaps(x, firstBack=TRUE)
#>   "A" "A" "A" "A" "B" "B" "B" "B" "B" "C" "C" "C" "C" "A" "A" "B" "B" "B"

# It also works on factors
y <- factor(x)
y
#>   <NA> <NA> A    A    B    B    B    <NA> <NA> C    <NA> <NA> <NA> A    A    B    <NA>
#>  <NA>
#> Levels: A B C

fillNAgaps(y)
#>   <NA> <NA> A    A    B    B    B    B    B    C    C    C    C    A    A    B    B
#>  B
#> Levels: A B C
``````

This is adapted from `na.locf()` in the zoo library.