zoo (version 1.4-2)

aggregate.zoo: Compute Summary Statistics of zoo Objects

Description

Splits a "zoo" object into subsets along a coarser index grid, computes summary statistics for each, and returns the reduced "zoo" object.

Usage

## S3 method for class 'zoo':
aggregate(x, by, FUN, \dots, regular = NULL, frequency = NULL)

Arguments

x
an object of class "zoo".
by
index vector of the same length as index(x) which defines aggregation groups and the new index to be associated with each group. If by is a function, then it is applied to index(x) to obtain the aggregati
FUN
a scalar function to compute the summary statistics which can be applied to all subsets.
...
further arguments passed to FUN.
regular
logical. Should the aggregated series be coerced to class "zooreg" (if the series is regular)? The default is FALSE for "zoo" series and TRUE for "zooreg" series.
frequency
numeric indicating the frequency of the aggregated series (if a "zooreg" series should be returned. The default is to determine the frequency from the data if regular is TRUE. If frequency is

Value

  • An object of class "zoo" or "zooreg".

See Also

zoo

Examples

Run this code
## averaging over values in a month:
# long series
x.date <- as.Date(paste(2004, rep(1:4, 4:1), seq(1,20,2), sep = "-"))
x <- zoo(rnorm(12), x.date)
# coarser dates
x.date2 <- as.Date(paste(2004, rep(1:4, 4:1), 1, sep = "-"))
x2 <- aggregate(x, x.date2, mean)
# compare time series
plot(x)
lines(x2, col = 2)

## aggregate a daily time series to a quarterly series
# create zoo series
tt <- as.Date("2000-1-1") + 0:300
z.day <- zoo(0:300, tt)

# function which returns corresponding first "Date" of quarter
first.of.quarter <- function(tt) as.Date(as.yearqtr(tt))

# average z over quarters
# 1. via "yearqtr" index (regular)
# 2. via "Date" index (not regular)
z.qtr1 <- aggregate(z.day, as.yearqtr, mean)
z.qtr2 <- aggregate(z.day, first.of.quarter, mean)

# The last one used the first day of the quarter but suppose
# we want the first day of the quarter that exists in the series
# (and the series does not necessarily start on the first day
# of the quarter).
z.day[!duplicated(as.yearqtr(time(z.day)))]

# This is the same except it uses the last day of the quarter.
# It requires R 2.6.0 which introduced the fromLast= argument.
z.day[!duplicated(as.yearqtr(time(z.day)), fromLast = TRUE)]

# The aggregated series above are of class "zoo" (because z.day
# was "zoo"). To create a regular series of class "zooreg",
# the frequency can be automatically chosen
zr.qtr1 <- aggregate(z.day, as.yearqtr, mean, regular = TRUE)
# or specified explicitely
zr.qtr2 <- aggregate(z.day, as.yearqtr, mean, frequency = 4)


## aggregate on month and extend to monthly time series
if(require(chron)) {
y <- zoo(matrix(11:15,nr=5,nc=2), chron(c(15,20,80,100,110)))
colnames(y) <- c("A", "B")

# aggregate by month using first of month as times for coarser series
# using first day of month as repesentative time
y2 <- aggregate(y, as.Date(as.yearmon(time(y))), head, 1)

# fill in missing months by merging with an empty series containing
# a complete set of 1st of the months
yrt2 <- range(time(y2))
y0 <- zoo(,seq(from = yrt2[1], to = yrt2[2], by = "month"))
merge(y2, y0)
}

# given daily series keep only first point in each month at
# day 21 or more
z <- zoo(101:200, as.Date("2000-01-01") + seq(0, length = 100, by = 2))
zz <- z[as.numeric(format(time(z), "%d")) >= 21]
zz[!duplicated(as.yearmon(time(zz)))]

# same except times are of "yearmon" class
aggregate(zz, as.yearmon, head, 1)

# aggregate POSIXct seconds data every 10 minutes
tt <- seq(10, 2000, 10)
x <- zoo(tt, structure(tt, class = c("POSIXt", "POSIXct")))
aggregate(x, time(x) - as.numeric(time(x)) %% 600, mean)

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