R: Aggregate indicators

Aggregate.coin

R Documentation

Aggregate indicators

Description

Aggregates a named data set specified by dset using aggregation function f_ag, weights w, and optional function parameters f_ag_para. Note that COINr has a number of aggregation functions built in, all of which are of the form a_*(), e.g. a_amean(), a_gmean() and friends.

Usage

## S3 method for class 'coin'
Aggregate(
  x,
  dset,
  f_ag = NULL,
  w = NULL,
  f_ag_para = NULL,
  dat_thresh = NULL,
  by_df = FALSE,
  out2 = "coin",
  write_to = NULL,
  ...
)

Arguments

`x`	A coin class object.
`dset`	The name of the data set to apply the function to, which should be accessible in `.$Data`.
`f_ag`	The name of an aggregation function, a string. This can either be a single string naming a function to use for all aggregation levels, or else a character vector of function names of length `n-1`, where `n` is the number of levels in the index structure. In this latter case, a different aggregation function may be used for each level in the index: the first in the vector will be used to aggregate from Level 1 to Level 2, the second from Level 2 to Level 3, and so on.
`w`	An optional data frame of weights. If `f_ag` does not require accept weights, set to `"none"`.
`f_ag_para`	Optional parameters to pass to `f_ag`, other than `x` and `w`. As with `f_ag`, this can specified to have different parameters for each aggregation level by specifying as a nested list of length `n-1`.
`dat_thresh`	An optional data availability threshold, specified as a number between 0 and 1. If a row within an aggregation group has data availability lower than this threshold, the aggregated value for that row will be `NA`. Data availability, for a row `x_row` is defined as `sum(!is.na(x_row))/length(x_row)`, i.e. the fraction of non-`NA` values.
`by_df`	Controls whether to send a numeric vector to `f_ag` (if `FALSE`, default) or a data frame (if `TRUE`) - see details.
`out2`	Either `"coin"` (default) to return updated coin or `"df"` to output the aggregated data set.
`write_to`	If specified, writes the aggregated data to `.$Data[[write_to]]`. Default `write_to = "Aggregated"`.
`...`	arguments passed to or from other methods.

Details

Aggregation is performed row-wise using the function f_ag, such that for each row x_row, the output is f_ag(x_row, f_ag_para), and for the whole data frame, it outputs a numeric vector. The data frame x must only contain numeric columns.

The function f_ag must be supplied as a string, e.g. "a_amean", and it must take as a minimum an input x which is either a numeric vector (if by_df = FALSE), or a data frame (if by_df = TRUE). In the former case f_ag should return a single numeric value (i.e. the result of aggregating x), or in the latter case a numeric vector (the result of aggregating the whole data frame in one go).

f_ag can optionally have other parameters, e.g. weights, specified as a list in f_ag_para.

Note that COINr has a number of aggregation functions built in, all of which are of the form a_*(), e.g. a_amean(), a_gmean() and friends. To see a list browse COINr functions alphabetically or type a_ in the R Studio console and press the tab key (after loading COINr).

Optionally, a data availability threshold can be assigned below which the aggregated value will return NA (see dat_thresh argument). If by_df = TRUE, this will however be ignored because aggregation is not done on individual rows. Note that more complex constraints could be built into f_ag if needed.

Value

An updated coin with aggregated data set added at .$Data[[write_to]] if out2 = "coin", else if out2 = "df" outputs the aggregated data set as a data frame.

Examples

# build example up to normalised data set
coin <- build_example_coin(up_to = "Normalise")

# aggregate normalised data set
coin <- Aggregate(coin, dset = "Normalised")