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##
## Function to do rbind of data frames quickly, even if the columns don't match
##
smartbind <- function(..., list, fill=NA, sep=':', verbose=FALSE)
{
data <- base::list(...)
if(!missing(list))
{
data <- modifyList(list, data)
}
data <- data[!sapply(data, function(l) is.null(l) | (ncol(l)==0) | (nrow(l)==0) )]
defaultNames <- seq.int(length(data))
if(is.null(names(data)))
names(data) <- defaultNames
emptyNames <- names(data)==""
if (any(emptyNames) )
names(data)[emptyNames] <- defaultNames[emptyNames]
data <- lapply(data,
function(x)
if(is.matrix(x) || is.data.frame(x))
x
else
data.frame(as.list(x), check.names=FALSE)
)
#retval <- new.env()
retval <- base::list()
rowLens <- unlist(lapply(data, nrow))
nrows <- sum(rowLens)
rowNameList <- unlist(lapply( names(data),
function(x)
if(rowLens[x]<=1) x
else paste(x, seq(1,rowLens[x]),sep=sep))
)
colClassList <- vector(mode="list", length=length(data))
factorColumnList <- vector(mode="list", length=length(data))
factorLevelList <- vector(mode="list", length=length(data))
start <- 1
blockIndex <- 1
for(block in data)
{
colClassList [[blockIndex]] <- base::list()
factorColumnList[[blockIndex]] <- character(length=0)
factorLevelList [[blockIndex]] <- base::list()
if(verbose) print(head(block))
end <- start+nrow(block)-1
for(col in colnames(block))
{
classVec <- class(block[,col])
## store class and factor level information for later use
colClassList[[blockIndex]][[col]] <- classVec
if("factor" %in% classVec)
{
factorColumnList[[blockIndex]] <-
c(factorColumnList[[blockIndex]], col)
factorLevelList[[blockIndex]][[col]] <-
levels(block[,col])
}
if(verbose) cat("Start:", start,
" End:", end,
" Column:", col,
"\n", sep="")
if ("factor" %in% classVec)
{
newclass <- "character"
}
else
newclass <- classVec[1]
## Coerce everything that isn't a native type to character
if(! (newclass %in% c("logical", "integer", "numeric",
"complex", "character", "raw") ))
{
newclass <- "character"
warning("Converting non-atomic type column '", col,
"' to type character.")
}
if(! (col %in% names(retval) ) )
retval[[col]] <- as.vector(rep(fill,nrows), mode=newclass)
## Handle case when current and previous native types differ
oldclass <- class(retval[[col]])
if(oldclass != newclass)
{
# handle conversions in case of conflicts
# numeric vs integer --> numeric
# complex vs numeric or integer --> complex
# anything else: --> character
if(oldclass %in% c("integer", "numeric") && newclass %in% c("integer", "numeric") )
class(retval[[col]]) <- mode <- "numeric"
else if(oldclass=="complex" && newclass %in% c("integer", "numeric") )
class(retval[[col]]) <- mode <- "complex"
else if(oldclass %in% c("integer", "numeric") && newclass=="complex")
class(retval[[col]]) <- mode <- "complex"
else
{
class(retval[[col]]) <- mode <- "character"
warning("Column class mismatch for '", col, "'. ",
"Converting column to class 'character'.")
}
}
else
mode <- oldclass
if(mode=="character")
vals <- as.character(block[,col])
else
vals <- block[,col]
retval[[col]][start:end] <- as.vector(vals, mode=mode)
}
start <- end+1
blockIndex <- blockIndex+1
}
all.equal.or.null <- function(x,y)
{
if(is.null(x) || is.null(y) )
return(TRUE)
else
return(all.equal(x,y))
}
## Handle factors, merging levels
for( col in unique(unlist(factorColumnList)) )
{
## Ensure column classes match across blocks
colClasses <- lapply(colClassList, function(x) x[[col]])
firstNotNull <- which(!sapply(colClasses, is.null))[1]
allSameOrNull <- all(sapply(colClasses[-firstNotNull],
function(x) isTRUE(all.equal.or.null(colClasses[[firstNotNull]], x))
)
)
if(allSameOrNull)
{
# grab the first *non-NULL* class information
colClass <- colClasses[[firstNotNull]]
}
else
{
warning("Column class mismatch for '", col, "'. ",
"Converting column to class 'character'.")
next()
}
## check if factor levels are all the same
colLevels <- lapply(factorLevelList, function(x) x[[col]])
firstNotNull <- which(!sapply(colLevels, is.null))[1]
allSameOrNull <- all(sapply(colLevels[-firstNotNull],
function(x) isTRUE(all.equal.or.null(colLevels[[firstNotNull]], x))
)
)
if(allSameOrNull)
{
if("ordered" %in% colClass)
retval[[col]] <- ordered(retval[[col]], levels=colLevels[[firstNotNull]] )
else
retval[[col]] <- factor(retval[[col]], levels=colLevels[[firstNotNull]] )
}
else
{
## Check if longest set of levels is a superset of all others,
## and use that one
longestIndex <- which.max( sapply(colLevels, length) )
longestLevels <- colLevels[[longestIndex]]
allSubset <- all(sapply(colLevels[-longestIndex],
function(l) all(l %in% longestLevels)
))
if(allSubset)
{
if("ordered" %in% colClass)
retval[[col]] <- ordered(retval[[col]], levels=longestLevels )
else
retval[[col]] <- factor(retval[[col]], levels=longestLevels )
}
else
{
# form superset by appending to longest level set
levelSuperSet <- unique(c(longestLevels, unlist(colLevels)))
retval[[col]] <- factor(retval[[col]], levels=levelSuperSet )
if(length(colClass)>1) # not just plain factor
{
warning( "column '", col, "' of class ",
paste("'", colClass, "'", collapse=":",
sep="'"),
" converted to class 'factor'. Check level ordering." )
}
}
}
}
attr(retval,"row.names") <- rowNameList
class(retval) <- "data.frame"
return(retval)
}
|
