Merge Two or More zoo Objects
Merge two zoo objects by common indexes (times), or do other versions of database join operations.
## S3 method for class 'zoo': merge(\dots, all = TRUE, fill = NA, suffixes = NULL, check.names = FALSE, retclass = c("zoo", "list", "data.frame"))
- two or more objects, usually of class
- logical vector having the same length as the number of
"zoo"objects to be merged (otherwise expanded).
- an element for filling gaps in merged
"zoo"objects (if any).
- character vector of the same length as the number of
"zoo"objects specifying the suffixes to be used for making the merged column names unique.
- character that specifies the class of the returned result.
It can be
NULL. For details see below.
merge method for
"zoo" objects combines the columns
of several objects along the union of the dates
all = TRUE, the default,
or the intersection of their dates for
all = FALSE
filling up the created gaps (if any) with the
The first argument must be a
zoo object. If any of the remaining
arguments are plain vectors or matrices with the same length or number
of rows as the first argument then such arguments are coerced to
as.zoo. If they are plain but have length 1 then they are
merged after all non-scalars such that their column is filled with the
value of the scalar.
all can be a vector of the same length as the number of
objects to merged (if not, it is expanded): All indexes
(times) of the objects corresponding to
TRUE are included, for those
FALSE only the indexes present in all objects are
included. This allows intersection, union and left and right joins
to be expressed.
"zoo" (the default) a single merged
object is returned. If it is set to
"list" a list of
objects is returned. If
retclass = NULL then instead of returning a value it updates each
argument (if it is a variable rather than an expression) in
place so as to extend or reduce it to use the common index vector.
The indexes of different
"zoo" objects can be of different classes and are coerced to
one class in the resulting object (with a warning).
cbind method is essentially the default
method, but does not support the
method combines the dates of the
"zoo" objects (duplicate dates are
not allowed) and combines the rows of the objects. Furthermore, the
c method is identical to the
- An object of class
retclass="zoo", an object of class
retclass="list"or modified arguments as explained above if
retclass=NULL. If the result is an object of class
"zoo"then its frequency is the common frequency of its zoo arguments, if they have a common frequency.
## simple merging x.date <- as.Date(paste(2003, 02, c(1, 3, 7, 9, 14), sep = "-")) x <- zoo(rnorm(5), x.date) y1 <- zoo(matrix(1:10, ncol = 2), 1:5) y2 <- zoo(matrix(rnorm(10), ncol = 2), 3:7) ## using arguments `fill' and `suffixes' merge(y1, y2, all = FALSE) merge(y1, y2, all = FALSE, suffixes = c("a", "b")) merge(y1, y2, all = TRUE) merge(y1, y2, all = TRUE, fill = 0) ## if different index classes are merged, as in ## the next merge example then ## a warning is issued and ### the indexes are coerced. ## It is up to the user to ensure that the result makes sense. merge(x, y1, y2, all = TRUE) ## extend an irregular series to a regular one: # create a constant series z <- zoo(1, seq(4)[-2]) # create a 0 dimensional zoo series z0 <- zoo(, 1:4) # do the extension merge(z, z0) # same but with zero fill merge(z, z0, fill = 0) merge(z, coredata(z), 1) ## merge multiple series represented in a long form data frame ## into a multivariate zoo series and plot, one series for each site. ## Additional examples can be found here: ## https://stat.ethz.ch/pipermail/r-help/2009-February/187094.html ## https://stat.ethz.ch/pipermail/r-help/2009-February/187096.html ## m <- 5 # no of years n <- 6 # no of sites sites <- LETTERS[1:n] set.seed(1) DF <- data.frame(site = sites, year = 2000 + 1:m, data = rnorm(m*n)) tozoo <- function(x) zoo(x$data, x$year) Data <- do.call(merge, lapply(split(DF, DF$site), tozoo)) plot(Data, screen = 1, col = 1:n, pch = 1:n, type = "o", xlab = "") legend("bottomleft", legend = sites, lty = 1, pch = 1:n, col = 1:n) ## for each index value in x merge it with the closest index value in y ## but retaining x's times. x<-zoo(1:3,as.Date(c("1992-12-13", "1997-05-12", "1997-07-13"))) y<-zoo(1:5,as.Date(c("1992-12-15", "1992-12-16", "1997-05-10","1997-05-19", "1997-07-13"))) f <- function(u) which.min(abs(as.numeric(index(y)) - as.numeric(u))) ix <- sapply(index(x), f) cbind(x, y = coredata(y)[ix]) ## this merges each element of x with the closest time point in y at or ## after x's time point (whereas in previous example it could be before ## or after) window(na.locf(merge(x, y), fromLast = TRUE), index(x))