tsibble-package {tsibble}

tsibble: tidy temporal data frames and tools

Description

The tsibble package provides a data class of tbl_ts to represent tidy temporal data. A tsibble consists of a time index, key, and other measured variables in a data-centric format, which is built on top of the tibble.

Index

An extensive range of indices are supported by tsibble:

• native time classes in R (such as Date, POSIXct, and difftime)

• tsibble's new additions (such as yearweek, yearmonth, and yearquarter).

• other commonly-used classes: ordered, hms::hms, lubridate::period, and nanotime::nanotime.

For a tbl_ts of regular interval, a choice of index representation has to be made. For example, a monthly data should correspond to time index created by yearmonth, instead of Date or POSIXct. Because months in a year ensures the regularity, 12 months every year. However, if using Date, a month containing days ranges from 28 to 31 days, which results in irregular time space. This is also applicable to year-week and year-quarter.

Tsibble supports arbitrary index classes, as long as they can be ordered from past to future. To support a custom class, you need to define index_valid() for the class and calculate the interval through interval_pull().

Key

Key variable(s) together with the index uniquely identifies each record:

• Empty: an implicit variable. NULL resulting in a univariate time series.

• A single variable: For example, data(pedestrian) uses Sensor as the key.

• Multiple variables: For example, Declare key = c(Region, State, Purpose) for data(tourism). Key can be created in conjunction with tidy selectors like starts_with().

Interval

The interval function returns the interval associated with the tsibble.

• Regular: the value and its time unit including "nanosecond", "microsecond", "millisecond", "second", "minute", "hour", "day", "week", "month", "quarter", "year". An unrecognisable time interval is labelled as "unit".

• Irregular: as_tsibble(regular = FALSE) gives the irregular tsibble. It is marked with !.

• Unknown: Not determined (⁠?⁠), if it's an empty tsibble, or one entry for each key variable.

An interval is obtained based on the corresponding index representation:

• integerish numerics between 1582 and 2499: "year" (Y). Note the year of 1582 saw the beginning of the Gregorian Calendar switch.

• yearquarter: "quarter" (Q)

• yearmonth: "month" (M)

• yearweek: "week" (W)

• Date: "day" (D)

• difftime: "week" (W), "day" (D), "hour" (h), "minute" (m), "second" (s)

• POSIXt/hms: "hour" (h), "minute" (m), "second" (s), "millisecond" (us), "microsecond" (ms)

• period: "year" (Y), "month" (M), "day" (D), "hour" (h), "minute" (m), "second" (s), "millisecond" (us), "microsecond" (ms)

• nanotime: "nanosecond" (ns)

• other numerics &ordered (ordered factor): "unit" When the interval cannot be obtained due to the mismatched index format, an error is issued.

The interval is invariant to subsetting, such as filter(), slice(), and ⁠[.tbl_ts⁠. However, if the result is an empty tsibble, the interval is always unknown. When joining a tsibble with other data sources and aggregating to different time scales, the interval gets re-calculated.

Time zone

Time zone corresponding to index will be displayed if index is POSIXct. ⁠?⁠ means that the obtained time zone is a zero-length character "".

Print options

The tsibble package fully utilises the print method from the tibble. Please refer to tibble::tibble-package to change display options.

Author(s)

Maintainer: Earo Wang [e-mail] (ORCID)

Authors:

• Di Cook (ORCID) [thesis advisor]

• Rob Hyndman (ORCID) [thesis advisor]

• Mitchell O'Hara-Wild (ORCID)

Other contributors:

• Tyler Smith [contributor]

• Wil Davis [e-mail] [contributor]

See Also

Useful links:

• https://tsibble.tidyverts.org

• Report bugs at https://github.com/tidyverts/tsibble/issues

Examples

# create a tsibble w/o a key ----
tsibble(
  date = as.Date("2017-01-01") + 0:9,
  value = rnorm(10)
)

# create a tsibble with one key ----
tsibble(
  qtr = rep(yearquarter("2010-01") + 0:9, 3),
  group = rep(c("x", "y", "z"), each = 10),
  value = rnorm(30),
  key = group
)