[R] dataframe to a timeseries object

[Daniele Amberti]

I’m wondering which is the most efficient (time, than memory usage) way to obtain a multivariate time series object from a data frame (the easiest data structure to get data from a database trough RODBC).
I have a starting point using timeSeries or xts library (these libraries can handle time zones), below you can find code to test.
Merging parallelization (cbind) is something I’m thinking at (suggestions from users with experience on this topic is highly appreciated), any suggestion is welcome.
My platform is Windows XP, R 2.12.1, latest available packages on CRAN for timeSeries and xts.


set.seed(123)

N <- 9000
X <- data.frame(
  ID = c(rep(1,N), rep(2,N,), rep(3,N), rep(4,N)),
  DATE = rep(as.POSIXct("2000-01-01", tz = "GMT")+ 0:(N-1), 4),
  VALUE = runif(N*4))

library(timeSeries)
buildTimeSeriesFromDataFrame <- function(x, env)
{
  {
    if(exists("xx", envir = env))
      assign("xx",
        cbind(get("xx", env), timeSeries(x$VALUE, x$DATE, format = '%Y-%m-%d %H:%M:%S',
          zone = 'GMT', units = as.character(x$ID[1]))),
        envir = env)
    else
      assign("xx",
        timeSeries(x$VALUE, x$DATE, format = '%Y-%m-%d %H:%M:%S',
          zone = 'GMT', units = as.character(x$ID[1])),
        envir = env)

    return(TRUE)
  }
}


fooBy <- function(...)
{
  e1 <- new.env(parent = baseenv())
  res <- by(X, X$ID, buildTimeSeriesFromDataFrame,
      env = e1, simplify = TRUE)
  return(get("xx", e1))
}

Time01 <- replicate(100,
  system.time(fooBy(X,
    X$ID, buildTimeSeriesFromDataFrame,
    simplify = TRUE))[[1]])

median(Time01)
hist(Time01)

library(xts)

buildXtsFromDataFrame <- function(x, env)
{
  {
    if(exists("xx", envir = env))
      assign("xx",
        cbind(get("xx", env), xts(x$VALUE,
          as.POSIXct(x$DATE, format = '%Y-%m-%d %H:%M:%S'),
          tzone = 'GMT')),
        envir = env)
    else
      assign("xx",
        xts(x$VALUE, as.POSIXct(x$DATE, format = '%Y-%m-%d %H:%M:%S'),
          tzone = 'GMT'),
        envir = env)

    return(TRUE)
  }
}

fooBy <- function(...)
{
  e1 <- new.env(parent = baseenv())
  res <- by(X, X$ID, buildXtsFromDataFrame,
      env = e1, simplify = TRUE)
  return(get("xx", e1))
}

Time02 <- replicate(100,
  system.time(fooBy(X,
    X$ID, buildTimeSeriesFromDataFrame,
    simplify = TRUE))[[1]])

median(Time02)
hist(Time02)

plot(density(Time02), xlim = c(min(c(Time02, Time01)), max(c(Time02, Time01))))
lines(density(Time01))


Best regards,
Daniele Amberti



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