Coerce xts to ts in R

Question

I have xts time-series object for 10 days of data. The data is sampled at minutes frequency. Therefore, for each day, I have 1440 observations. I need to coerce

Answer 1

library(xts)
library(ggplot2)
library(reshape2)

set.seed(42)
timevalues = "20150101 0000/20150110 2359"
timesequence <- timeBasedSeq(timevalues)
min_data <- xts(rnorm(14400),timesequence)

ts_data <- ts(as.numeric(min_data), frequency = 1440)
out <- stl(ts_data, s.window = "per")
time.series <- as.data.frame(cbind(ts_data, out$time.series))
colnames(time.series) <- c("Data", "Seasonal", "Trend", "Remainder")
time.series$Date <- timesequence
time.series <- melt(time.series, 'Date')

ggplot(time.series, aes(x=Date, y=value)) + 
  geom_line() +
  facet_free(variable~.)

Answer 2

i think what you are looking for is the below:

xts2ts <- function(XD) {
             maxRow <- nrow(XD)
             startYM <- c(.indexyear(XD[1]) + 1900, .indexmon(XD[1]) + 1L)
             endYM <- c(.indexyear(XD[maxRow]) + 1900, .indexmon(XD[maxRow]) + 1L)
             ts(as.numeric(XD), start = startYM, end = endYM, frequency = 12L)
}

Answer 3

If you hav a xts data in monthly, quarterly and yearly frequency it maby be useful (use packages: xts, stats, data.table, zoo)

xts_ts <- function(xts_data) {
  freq_list <-
    data.table::data.table(
      freq = c('month', 'quarter', 'year'),
      freq_n = c(12L, 4L, 1L),
      freq_format = c('%Y, %m', '%Y, %q', '%Y')
    )

  d_ferq <- xts::periodicity(xts_data)[["label"]]
  freq_n <- freq_list[freq == d_ferq, freq_n]
  freq_format <- freq_list[freq == d_ferq, freq_format]

  # Put NA if missing date
  empty <-
    zoo::zoo(order.by = seq.Date(zoo::index(xts_data)[1], zoo::index(xts_data)[nrow(xts_data)], by = d_ferq))
  no_misssing <- merge(xts_data, empty)

  if (d_ferq == 'quarter') {
    start_date <-
      format(zoo::as.yearqtr(xts::periodicity(xts_data)[["start"]]), freq_format)

  } else {
    start_date <-
      format(zoo::as.Date(xts::periodicity(xts_data)[["start"]]), freq_format)
  }

  stats::ts(zoo::coredata(no_misssing),
     start = as.integer(strsplit(start_date, split = ',')[[1]]),
     frequency = freq_n)
}

Answer 4

I recently have discovered a package called "tsbox".

It promises easy conversion between time series types. (here a tutorial: https://cran.r-project.org/web/packages/tsbox/vignettes/tsbox.html)

Might be useful in cases like this one.

Here an example:

library(tsbox)
nowTS <-ts_ts(formerXTS)

or the other way round if you want to convert the ts back to an xts series

library(tsbox)
nowXTS <-ts_xts(nowTS)

Answer 5

An xts-only solution, based on an idea I had from looking at Pascal's answer.

library(xts)
set.seed(42)
timevalues = "20150101 0000/20150110 2359"
timesequence <- timeBasedSeq(timevalues)
min_data <- xts(rnorm(14400),timesequence)

ts_data <- ts(as.numeric(min_data), frequency = 1440)
out <- stl(ts_data, s.window = "per")

ts_out <- merge(min_data, out$time.series)
plot.zoo(ts_out)