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#' Replace Cells in a Matrix or Data Frame
#'
#' Replace elements of a dataframe, matrix or vector with least restrictive
#' class.
#'
#' @param dat Data; either a dataframe, matrix or vector.
#' @param replace Element to replace.
#' @param with Replacement element.
#' @return Returns a dataframe, matrix or vector with the element replaced.
#' @keywords replace
#' @export
#' @examples
#' \dontrun{
#' replacer(mtcars[1:10, ], 0, "REP")
#' replacer(mtcars[1:10, ], 4, NA)
#' replacer(c("a", "b"), "a", "foo")
#' #replace missing values (NA)
#' dat <- data.frame(matrix(sample(c(1:3, NA), 25, TRUE), ncol=5))
#' replacer(dat, NA, "FOO")
#' }
replacer <-
function(dat, replace=0, with="-"){
h <- is.vector(dat)
i <- is.matrix(dat)
j <- is.data.frame(dat)
CLS <- sapply(dat, class)
if (is.numeric(replace)){
NAMES <- colnames(dat)
if (h) {
dat <- data.frame(dat)
}
not.num <- Negate(is.numeric)
dat1 <- dat[, sapply(dat, not.num), drop = FALSE]
inds <- which(sapply(dat, is.numeric))
subdf <- function(df, ii) {
do.call("data.frame", c(as.list(df)[ii, drop=FALSE],
check.names=FALSE))
}
dat2 <- subdf(dat, inds)
} else {
dat2 <- dat
}
y <- as.matrix(dat2)
if (is.na(replace)) {
y[is.na(y)] <- with
} else {
y[y==replace] <- with
}
if (is.numeric(replace)){
y <- data.frame(dat1, y, check.names = FALSE)
m <- NAMES[!NAMES%in%names(y)]
if(length(m) == 1) names(y)[1] <- m
y <- subdf(y, NAMES)
}
if(h) y <- as.vector(y)
if(i) y <- as.matrix(y)
if(j) {
y <- as.data.frame(y, check.names = FALSE)
for (i in 1:ncol(y)) {
FUN <- match.fun(paste0("as.", CLS[i]))
FUN2 <- match.fun(paste0("is.", CLS[i]))
if (CLS[i] %in% c("numeric", "integer")) {
numTest <- function(x) {
v <- sum(is.na(x))
w <- sum(is.na(suppressWarnings(as.numeric(as.character(x)))))
v == w
}
if (!numTest(y[, i])){
y[, i] <- as.character(y[, i])
} else {
y[, i] <- FUN(as.character(y[, i]))
}
} else {
y[, i] <- FUN(as.character(y[, i]))
}
}
}
return(y)
}
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