zoo (version 1.7-3)

merge.zoo: Merge Two or More zoo Objects

Description

Merge two zoo objects by common indexes (times), or do other versions of database join operations.

Usage

## S3 method for class 'zoo':
merge(\dots, all = TRUE, fill = NA, suffixes = NULL,
  check.names = FALSE, retclass = c("zoo", "list", "data.frame"),
  drop = TRUE)

Arguments

...
two or more objects, usually of class "zoo".
all
logical vector having the same length as the number of "zoo" objects to be merged (otherwise expanded).
fill
an element for filling gaps in merged "zoo" objects (if any).
suffixes
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.
check.names
See link{read.table}.
retclass
character that specifies the class of the returned result. It can be "zoo" (the default), "list" or NULL. For details see below.
drop
logical. If a "zoo" object without observations is merged with a one-dimensional "zoo" object (vector or 1-column matrix), should the result be a vector (drop = TRUE) or a 1-column matrix (drop = FA

Value

  • An object of class "zoo" if retclass="zoo", an object of class "list" if 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.

Details

The merge method for "zoo" objects combines the columns of several objects along the union of the dates for all = TRUE, the default, or the intersection of their dates for all = FALSE filling up the created gaps (if any) with the fill pattern.

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 "zoo" using 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 "zoo" objects to merged (if not, it is expanded): All indexes (times) of the objects corresponding to TRUE are included, for those corresponding to FALSE only the indexes present in all objects are included. This allows intersection, union and left and right joins to be expressed.

If retclass is "zoo" (the default) a single merged "zoo" object is returned. If it is set to "list" a list of "zoo" 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).

The default cbind method is essentially the default merge method, but does not support the retclass argument. The rbind 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 rbind method.

See Also

zoo

Examples

Run this code
## 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))

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