tk_zooreg: Coerce time series objects and tibbles with date/date-time...

In timetk: A Tool Kit for Working with Time Series

Coerce time series objects and tibbles with date/date-time columns to ts.

Description

Coerce time series objects and tibbles with date/date-time columns to ts.

Usage

tk_zooreg(
  data,
  select = NULL,
  date_var = NULL,
  start = 1,
  end = numeric(),
  frequency = 1,
  deltat = 1,
  ts.eps = getOption("ts.eps"),
  order.by = NULL,
  silent = FALSE
)

tk_zooreg_(
  data,
  select = NULL,
  date_var = NULL,
  start = 1,
  end = numeric(),
  frequency = 1,
  deltat = 1,
  ts.eps = getOption("ts.eps"),
  order.by = NULL,
  silent = FALSE
)

Arguments

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 zooreg class.
date_var	Applicable to tibbles and data frames only. Column name to be used to order.by. NULL by default. If NULL, function will find the date or date-time column.
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.
end	the time of the last observation, specified in the same way as start.
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 frequency or deltat should be provided.
ts.eps	time series comparison tolerance. Frequencies are considered equal if their absolute difference is less than ts.eps.
order.by	a vector by which the observations in x are ordered. If this is specified the arguments start and end are ignored and zoo(data, order.by, frequency) is called. See zoo for more information.
silent	Used to toggle printing of messages and warnings.

Details

tk_zooreg() is a wrapper for zoo::zooreg() that is designed to coerce tibble objects that have a "time-base" (meaning the values vary with time) to zooreg class objects. There are two main advantages:

1. Non-numeric columns get removed instead causing coercion issues.

2. If an index is present, the returned zooreg object retains an index retrievable using tk_index().

The select argument is used to select subsets of columns from the incoming data.frame. The date_var can be used to specify the column with the date index. If date_var = NULL, the date / date-time column is interpreted. Optionally, the order.by argument from the underlying xts::xts() function can be used. The user must pass a vector of dates or date-times if order.by is used. 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 zoo::zooreg().

tk_zooreg_ is a nonstandard evaluation method.

Value

Returns a zooreg object.

See Also

tk_tbl(), tk_xts(), tk_zoo(), tk_ts()

Examples

### tibble to zooreg: Comparison between tk_zooreg() and zoo::zooreg()
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))

# zoo::zooreg: Values coerced to character; Result does not retain index
data_zooreg <- zoo::zooreg(data_tbl[,-1], start = 2016, freq = 365)
data_zooreg                # Numeric values coerced to character
rownames(data_zooreg)      # NULL, no dates retained

# tk_zooreg: Only numeric columns get coerced; Result retains index as rownames
data_tk_zooreg <- tk_zooreg(data_tbl, start = 2016, freq = 365)
data_tk_zooreg             # No inadvertent coercion to character class

# timetk index
tk_index(data_tk_zooreg, timetk_idx = FALSE)   # Regularized index returned
tk_index(data_tk_zooreg, timetk_idx = TRUE)    # Original date index returned

### Using select and date_var
tk_zooreg(data_tbl, select = y, date_var = date, start = 2016, freq = 365)


### NSE: Enables programming
select   <- "y"
date_var <- "date"
tk_zooreg_(data_tbl, select = select, date_var = date_var, start = 2016, freq = 365)

timetk documentation built on Nov. 2, 2023, 6:18 p.m.