| subset.DTSg {DTSg} | R Documentation |
Subset time series data
Description
Filters rows and/or selects columns of a DTSg object.
Usage
## S3 method for class 'DTSg'
subset(
x,
i,
cols = self$cols(),
funby = NULL,
ignoreDST = FALSE,
na.status = "implicit",
clone = getOption("DTSgClone"),
multiplier = 1L,
funbyHelpers = NULL,
funbyApproach = self$funbyApproach,
...
)
Arguments
x |
A |
i |
An integerish vector indexing rows (positive numbers pick and
negative numbers omit rows) or a filter expression accepted by the |
cols |
A character vector specifying the columns to select. Another
possibility is a character string containing either comma separated column
names, for example, |
funby |
One of the temporal aggregation level functions described in
|
ignoreDST |
A logical specifying if day saving time shall be ignored
by |
na.status |
A character string. Either |
clone |
A logical specifying if the object shall be modified in place or if a deep clone (copy) shall be made beforehand. |
multiplier |
A positive integerish value “multiplying” the
temporal aggregation level of certain |
funbyHelpers |
An optional |
funbyApproach |
A character string specifying the flavour of the applied
temporal aggregation level function. Either |
... |
Further arguments passed on to |
Value
Returns a DTSg object.
Status of missing values
Please note that filtering rows and having or making missing timestamps
explicit equals to setting the values of all other timestamps to missing. The
default value of na.status is therefore "implicit". To simply filter for
a consecutive range of a DTSg object while leaving the na.status
untouched, alter is probably the better choice.
User defined TALFs, TALFs helper data and multiplier
User defined temporal aggregation level functions have to return a
POSIXct vector of the same length as the time series and accept two
arguments: a POSIXct vector as its first and a list with helper data
as its second. The default elements of this list are as follows:
-
timezone: Same as the
timezonefield. -
ignoreDST: Same as the
ignoreDSTargument. -
periodicity: Same as the
periodicityfield. -
na.status: Same as the
na.statusfield. -
multiplier: Same as the
multiplierargument. -
funbyApproach: Same as the
funbyApproachargument.
Any additional element specified in the funbyHelpers argument is appended
to the end of the helper data list. In case funbyHelpers contains an
ignoreDST, multiplier or funbyApproach element, it takes precedence over
the respective method argument. timezone, periodicity and na.status
elements are rejected, as they are always taken directly from the object.
The temporal aggregation level of certain TALFs can be adjusted with the
help of the multiplier argument. A multiplier of 10, for example, makes
byY_____ aggregate to decades instead of years. Another example
is a multiplier of 6 provided to by_m____. The function
then aggregates all months of all first and all months of all second half
years instead of all months of all years separately. This feature is
supported by the following TALFs of the package:
-
byYmdH__(UTC and equivalent as well as all Etc/GMT time zones only) -
by___H__(UTC and equivalent as well as all Etc/GMT time zones only)
Ignore day saving time
ignoreDST tells a temporal aggregation level function if it is supposed to
ignore day saving time while transforming the timestamps. This can be a
desired feature for time series strictly following the position of the sun
such as hydrological time series. Doing so ensures that diurnal variations
are preserved by all means and all intervals are of the “correct”
length, however, a possible limitation might be that the day saving time
shift is invariably assumed to be one hour long. This feature requires that
the periodicity of the time series was recognised and is supported by the
following TALFs of the package:
See Also
Examples
# new DTSg object
x <- DTSg$new(values = flow)
# filter for the first six observations
## R6 method
x$subset(i = 1:6)$print()
## S3 method
print(subset(x = x, i = 1:6))
# filter for the last two observations per year
## R6 method
x$subset(
i = (.N - 1):.N,
funby = function(x, ...) {data.table::year(x)}
)$print()
## S3 method
print(subset(
x = x,
i = (.N - 1):.N,
funby = function(x, ...) {data.table::year(x)}
))