Coerce to a Data Frame

Coerce to a Data Frame

Usage

# S4 method for TimeSeries
as.data.frame(x, ..., calendar = NULL)

Arguments

x

A TimeSeries object.

...

Further parameters to be passed to data.frame().

calendar

A TimeScale object specifying the target calendar (see calendar()). If NULL (the default), rata die are returned.

Value

A long data.frame with the following columns:

time

The (decimal) years at which the time series was sampled.

series

The name of the time series.

variable

The name of the variables.

value

The observed value.

See also

Other time series tools: series(), span(), start(), time(), window()

Author

N. Frerebeau

Examples

## Create time-series of 20 observations

## Univariate
## Sampled every years starting from 1029 BCE
(X <- series(rnorm(30), time = 1029:1000, calendar = BCE()))
#> 30 x 1 x 1 time series observed between -376199 and -365607 r.d.

## Terminal and sampling times (returns rata die)
start(X)
#> [1] -376199
end(X)
#> [1] -365607
time(X)
#> Rata die: number of days since 01-01-01 (Gregorian).
#>  [1] -376199 -375834 -375468 -375103 -374738 -374373 -374007 -373642 -373277
#> [10] -372912 -372546 -372181 -371816 -371451 -371085 -370720 -370355 -369990
#> [19] -369624 -369259 -368894 -368529 -368163 -367798 -367433 -367068 -366702
#> [28] -366337 -365972 -365607
span(X)
#> [1] 10592

## Multivariate
## Sampled every century starting from 1000 CE
(Y <- series(matrix(rnorm(90), 30, 3), time = 1000:1029, calendar = CE()))
#> 30 x 3 x 1 time series observed between 364878 and 375470 r.d.

## Terminal and sampling times (returns Gregorian Common Era years)
start(Y, calendar = CE())
#> [1] 1000
end(Y, calendar = CE())
#> [1] 1029
time(Y, calendar = CE())
#>  [1] 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014
#> [16] 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029
span(Y, calendar = CE())
#> [1] 29.99726

## Coerce to data frame
df <- as.data.frame(Y, calendar = BP())
head(df)
#>   time series variable      value
#> 1  950     S1        A  0.9353632
#> 2  949     S1        A  0.1764886
#> 3  948     S1        A  0.2436855
#> 4  947     S1        A  1.6235489
#> 5  946     S1        A  0.1120381
#> 6  945     S1        A -0.1339970