# yearmon

##### An Index Class for Monthly Data

`"yearmon"`

is a class for representing monthly data.

- Keywords
- ts

##### Usage

`yearmon(x)`

##### Arguments

- x
- numeric (interpreted as being
in years ).

##### Details

The yearmon class is used to represent monthly data. Internally it holds
the data as year plus 0 for January, 1/12 for February, 2/12 for March
and so on in order that its internal representation is the same as
`ts`

class with `frequency = 12`

. If `x`

is not in this
format it is rounded via `floor(12*x + .0001)/12`

.
There are coercion methods available for various classes including:
default coercion to `"yearmon"`

(which coerces to `"numeric"`

first)
and coercion from `"yearmon"`

to `"Date"`

(see below),
`"POSIXct"`

,
`"POSIXlt"`

, `"numeric"`

, `"character"`

. In the case of
`as.yearmon.character`

the `format`

argument is the same as for
`"Date"`

. One can specify a year and month with no day.
`as.Date.yearmon`

and `as.yearmon.yearqtr`

both have an optional
second argument of `"frac"`

which is a number between 0 and 1 inclusive
that indicates the fraction of the way through the period that the result
represents. The default is 0 which means the beginning of the period.

##### Value

- Returns its argument converted to class
`yearmon`

.

##### See Also

##### Examples

```
x <- yearmon(2000 + seq(0, 23)/12)
x
as.yearmon("mar07", "%b%y")
as.yearmon("2007-03-01")
as.yearmon("2007-12")
# returned Date is the fraction of the way through
# the period given by frac (= 0 by default)
as.Date(x)
as.Date(x, frac = 1)
as.POSIXct(x)
# given a Date, x, return the Date of the next Friday
nextfri <- function(x) 7 * ceiling(as.numeric(x - 1)/7) + as.Date(1)
# 3rd Friday in last month of the quarter of Date x
as.Date(as.yearmon(as.yearqtr(x)) + 2/12) + 14
z <- zoo(rnorm(24), x, frequency = 12)
z
as.ts(z)
## convert data fram to multivariate monthly "ts" series
## 1.read raw data
Lines.raw <- "ID Date Count
123 20 May 1999 1
123 21 May 1999 3
222 1 Feb 2000 2
222 3 Feb 2000 4
"
DF <- read.table(textConnection(Lines.raw), skip = 1,
col.names = c("ID", "d", "b", "Y", "Count"))
## 2. fix raw date
DF$yearmon <- as.yearmon(paste(DF$b, DF$Y), "%b %Y")
## 3. aggregate counts over months, convert to zoo and merge over IDs
ag <- function(DF) aggregate(zoo(DF$Count), DF$yearmon, sum)
z <- do.call("merge.zoo", lapply(split(DF, DF$ID), ag))
## 4. convert to "zooreg" and then to "ts"
frequency(z) <- 12
as.ts(z)
xx <- zoo(seq_along(x), x)
## aggregating over year
as.year <- function(x) as.numeric(floor(as.yearmon(x)))
aggregate(xx, as.year, mean)
```

*Documentation reproduced from package zoo, version 1.5-4, License: GPL-2*