tsl_aggregate {distantia} | R Documentation |
Aggregate Time Series List Over Time Periods
Description
Time series aggregation involves grouping observations and summarizing group values with a statistical function. This operation is useful to:
Decrease (downsampling) the temporal resolution of a time series.
Highlight particular states of a time series over time. For example, a daily temperature series can be aggregated by month using
max
to represent the highest temperatures each month.Transform irregular time series into regular.
This function aggregates time series lists with overlapping times. Please check such overlap by assessing the columns "begin" and "end " of the data frame resulting from df <- tsl_time(tsl = tsl)
. Aggregation will be limited by the shortest time series in your time series list. To aggregate non-overlapping time series, please subset the individual components of tsl
one by one either using tsl_subset()
or the syntax tsl = my_tsl[[i]]
.
Methods
Any function returning a single number from a numeric vector can be used to aggregate a time series list. Quoted and unquoted function names can be used. Additional arguments to these functions can be passed via the argument ...
. Typical examples are:
-
mean
or"mean"
: seemean()
. -
median
or"median"
: seestats::median()
. -
quantile
or "quantile": seestats::quantile()
. -
min
or"min"
: seemin()
. -
max
or"max"
: seemax()
. -
sd
or"sd"
: to compute standard deviation, seestats::sd()
. -
var
or"var"
: to compute the group variance, seestats::var()
. -
length
or"length"
: to compute group length. -
sum
or"sum"
: seesum()
.
This function supports a parallelization setup via future::plan()
, and progress bars provided by the package progressr.
Usage
tsl_aggregate(tsl = NULL, new_time = NULL, f = mean, ...)
Arguments
tsl |
(required, list) Time series list. Default: NULL |
new_time |
(required, numeric, numeric vector, Date vector, POSIXct vector, or keyword) Definition of the aggregation pattern. The available options are:
|
f |
(required, function name) Name of function taking a vector as input and returning a single value as output. Typical examples are |
... |
(optional) further arguments for |
Value
time series list
See Also
Other tsl_processing:
tsl_resample()
,
tsl_smooth()
,
tsl_stats()
,
tsl_transform()
Examples
# yearly aggregation
#----------------------------------
#long-term monthly temperature of 20 cities
tsl <- tsl_initialize(
x = cities_temperature,
name_column = "name",
time_column = "time"
)
#plot time series
if(interactive()){
tsl_plot(
tsl = tsl[1:4],
guide_columns = 4
)
}
#check time features
tsl_time(tsl)[, c("name", "resolution", "units")]
#aggregation: mean yearly values
tsl_year <- tsl_aggregate(
tsl = tsl,
new_time = "year",
f = mean
)
#' #check time features
tsl_time(tsl_year)[, c("name", "resolution", "units")]
if(interactive()){
tsl_plot(
tsl = tsl_year[1:4],
guide_columns = 4
)
}
# other supported keywords
#----------------------------------
#simulate full range of calendar dates
tsl <- tsl_simulate(
n = 2,
rows = 1000,
time_range = c(
"0000-01-01",
as.character(Sys.Date())
)
)
#mean value by millennia (extreme case!!!)
tsl_millennia <- tsl_aggregate(
tsl = tsl,
new_time = "millennia",
f = mean
)
if(interactive()){
tsl_plot(tsl_millennia)
}
#max value by centuries
tsl_century <- tsl_aggregate(
tsl = tsl,
new_time = "century",
f = max
)
if(interactive()){
tsl_plot(tsl_century)
}
#quantile 0.75 value by centuries
tsl_centuries <- tsl_aggregate(
tsl = tsl,
new_time = "centuries",
f = stats::quantile,
probs = 0.75 #argument of stats::quantile()
)