Description Usage Arguments Details Value See Also Examples
Coerce time series objects and tibbles with date/date-time columns to ts.
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data |
A time-based tibble or time-series object. |
select |
Applicable to tibbles and data frames only.
The column or set of columns to be coerced to |
start |
the time of the first observation. Either a single number or a vector of two integers, which specify a natural time unit and a (1-based) number of samples into the time unit. See the examples for the use of the second form. |
end |
the time of the last observation, specified in the same way
as |
frequency |
the number of observations per unit of time. |
deltat |
the fraction of the sampling period between successive
observations; e.g., 1/12 for monthly data. Only one of
|
ts.eps |
time series comparison tolerance. Frequencies are
considered equal if their absolute difference is less than
|
silent |
Used to toggle printing of messages and warnings. |
tk_ts() is a wrapper for stats::ts() that is designed
to coerce tibble objects that have a "time-base" (meaning the values vary with time)
to ts class objects. There are two main advantages:
Non-numeric columns get removed instead of being populated by NA's.
The returned ts object retains a "timekit index" (and various other attributes) if detected.
The "timekit index" can be used to coerce between tbl, xts, zoo, and ts data types.
The select argument is used to select subsets
of columns from the incoming data.frame.
Only columns containing numeric data are coerced. At a minimum, a frequency
and a start should be specified.
For non-data.frame object classes (e.g. xts, zoo, timeSeries, etc) the objects are coerced
using stats::ts().
tk_ts_ is a nonstandard evaluation method.
Returns a ts object.
tk_index(), tk_tbl(), tk_xts(), tk_zoo(), tk_zooreg()
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | library(tidyverse)
library(timekit)
### tibble to ts: Comparison between tk_ts() and stats::ts()
data_tbl <- tibble::tibble(
date = seq.Date(as.Date("2016-01-01"), by = 1, length.out = 5),
x = rep("chr values", 5),
y = cumsum(1:5),
z = cumsum(11:15) * rnorm(1))
# as.ts: Character columns introduce NA's; Result does not retain index
stats::ts(data_tbl[,-1], start = 2016)
# tk_ts: Only numeric columns get coerced; Result retains index in numeric format
data_ts <- tk_ts(data_tbl, start = 2016)
data_ts
# timekit index
tk_index(data_ts, timekit_idx = FALSE) # Regularized index returned
tk_index(data_ts, timekit_idx = TRUE) # Original date index returned
# Coerce back to tibble
data_ts %>% tk_tbl(timekit_idx = TRUE)
### Using select
tk_ts(data_tbl, select = y)
### NSE: Enables programming
select <- "y"
tk_ts_(data_tbl, select = select)
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