Time Aggregation of time series — timeAggregation • AirVeg

WARNING: This function is now deprecated and we will be removed in the future.

Usage

timeAggregation(
  mydata,
  avg.time,
  statistics = "mean",
  percentile = NA,
  name.variable = NULL,
  variables = "all",
  name.value = NULL,
  name.time = "time",
  name.station = NULL,
  stations = "all",
  val.check = FALSE,
  ...
)

Arguments

mydata: A data.frame or data.table containing a time series with time and value columns. If more than one variable is present in the data set, the table must be in "long format."
avg.time: A character vector indicating time step on which compute the statistics. It can be one of the following: "min", "hour", "day", "month" or "year". No default.
statistics: A character vector indicating the statistics to apply when aggregating data. It can be one of "mean", "min", "max", "sum", "percentile". Default = "mean".
percentile: A numeric indicating the percentile used when statistics = "percentile". No default.
name.variable: A character vector indicating the name of the column with the variables in mydata.
variables: A character vector indicating the names of variables to be select in the name.variable column. Default is "all", i.e. if only one variable is present it can be omitted.
name.value: A character vector indicating the name of the column with the values to be aggregated.
name.time: A character vector indicating the name of the column with date/time values.
name.station: A character vector indicating the name of the column with the stations code.
stations: A character vector indicating the names of stations to be computed. The output will be grouped by the selected stations. Default = "all".
val.check: If TRUE set to NA if result is not valid data according to Directive 2008/50/CE. Default is FALSE.
...: Options passed to the statistics function defined in statistic. For example: na.rm = TRUE.

Value

A data.table.

Details

Function to aggregate time series according to different statistics, selecting the time step for grouping.

The function computes time aggregation of a time series according to the statistics defined in the arguments. The input data can be a simple time series or a more complex data set in long format.

Examples

if (FALSE) {
# mydata is a `data.frame` with columns "time" and "no2". Time delta t is 1 hour.
head(mydata)
#         time               no2
# 1 2015-01-01 03:00:00 30.43931
# 2 2015-01-01 04:00:00 27.60286
# 3 2015-01-01 05:00:00 31.34683
# 4 2015-01-01 06:00:00 35.82242
# 5 2015-01-01 07:00:00 49.91434
# 6 2015-01-01 08:00:00 64.80641

# Compute daily averages:
dailyAvg <- timeAggregation(mydata, avg.time = "day", name.time = "time",
                            name.value = "no2", statistics = "mean")

# mydata is a `data.table` in long format with many concentrations of many
# pollutants: each row has one concentration value in the "conc" column;
# the pollutant is specified in the "pollutants" column:
dailyValues <- timeAggregation(mydata, variables = "PM10", name.variable = "pollutants",
                               name.value = "conc", na.rm = TRUE)
}