Calculates multiple percentile values from a time series, with flexible time
aggregation. This function is a wrapper for timeAverage(), making it easier
to calculate several percentiles at once. Like timeAverage(), it requires a
data frame with a date field and one other numeric variable.
calcPercentile(
mydata,
pollutant = "o3",
avg.time = "month",
percentile = 50,
type = "default",
data.thresh = 0,
start.date = NA,
end.date = NA,
prefix = "percentile."
)Returns a data.frame with a date column plus an additional
column for each given percentile.
A data frame containing a date field . Can be class POSIXct
or Date.
Name of column containing variable to summarise, likely a
pollutant (e.g., "o3").
This defines the time period to average to. Can be "sec",
"min", "hour", "day", "DSTday", "week", "month", "quarter" or
"year". For much increased flexibility a number can precede these options
followed by a space. For example, a timeAverage of 2 months would be
period = "2 month". In addition, avg.time can equal "season", in
which case 3-month seasonal values are calculated with spring defined as
March, April, May and so on.
Note that avg.time can be less than the time interval of the original
series, in which case the series is expanded to the new time interval. This
is useful, for example, for calculating a 15-minute time series from an
hourly one where an hourly value is repeated for each new 15-minute period.
Note that when expanding data in this way it is necessary to ensure that
the time interval of the original series is an exact multiple of avg.time
e.g. hour to 10 minutes, day to hour. Also, the input time series must have
consistent time gaps between successive intervals so that timeAverage()
can work out how much 'padding' to apply. To pad-out data in this way
choose fill = TRUE.
A vector of percentile values; for example, percentile = 50 will calculate median values. Multiple values may also be provided as a
vector, e.g., percentile = c(5, 50, 95) or percentile = seq(0, 100, 10).
type allows timeAverage() to be applied to cases where there
are groups of data that need to be split and the function applied to each
group. The most common example is data with multiple sites identified with
a column representing site name e.g. type = "site". More generally,
type should be used where the date repeats for a particular grouping
variable. However, if type is not supplied the data will still be averaged
but the grouping variables (character or factor) will be dropped.
The data capture threshold to use (%). A value of zero
means that all available data will be used in a particular period
regardless if of the number of values available. Conversely, a value of 100
will mean that all data will need to be present for the average to be
calculated, else it is recorded as NA. See also interval, start.date
and end.date to see whether it is advisable to set these other options.
A string giving a start date to use. This is sometimes
useful if a time series starts between obvious intervals. For example, for
a 1-minute time series that starts 2009-11-29 12:07:00 that needs to be
averaged up to 15-minute means, the intervals would be 2009-11-29 12:07:00, 2009-11-29 12:22:00, etc. Often, however, it is better to
round down to a more obvious start point, e.g., 2009-11-29 12:00:00 such
that the sequence is then 2009-11-29 12:00:00, 2009-11-29 12:15:00, and
so on. start.date is therefore used to force this type of sequence. Note
that this option does not truncate a time series if it already starts
earlier than start.date; see selectByDate() for that functionality.
A string giving an end date to use. This is sometimes useful
to make sure a time series extends to a known end point and is useful when
data.thresh > 0 but the input time series does not extend up to the final
full interval. For example, if a time series ends sometime in October but
annual means are required with a data capture of >75 % then it is necessary
to extend the time series up until the end of the year. Input in the format
yyyy-mm-dd HH:MM. Note that this option does not truncate a time series if
it already ends later than end.date; see selectByDate() for that
functionality.
Each new column is named by appending a prefix to
percentile. For example, the default "percentile." will name the new
column as percentile.95 when percentile = 95.
David Carslaw
timePlot(), timeAverage()
# 95th percentile monthly o3 concentrations
percentiles <- calcPercentile(mydata,
pollutant = "o3",
avg.time = "month", percentile = 95
)
head(percentiles)
# 5, 50, 95th percentile monthly o3 concentrations
if (FALSE) {
percentiles <- calcPercentile(mydata,
pollutant = "o3",
avg.time = "month", percentile = c(5, 50, 95)
)
head(percentiles)
}
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