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Aggregate data frame

Source: R/aggregate.R
Aggregate.data.frame.Rd

Aggregates a data frame into a single column using a specified function. 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 data.frame
Aggregate(
  x,
  f_ag = NULL,
  f_ag_para = NULL,
  dat_thresh = NULL,
  by_df = FALSE,
  ...
)

Arguments

x

Data frame to be aggregated

f_ag

The name of an aggregation function, as a string.

f_ag_para

Any additional parameters to pass to f_ag, as a named list.

dat_thresh

An optional data availability threshold, specified as a number between 0 and 1. If a row of x 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.

...

arguments passed to or from other methods.

Value

A numeric vector

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), or see the online documentation.

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.

Examples

# get some indicator data - take a few columns from built in data set
X <- ASEM_iData[12:15]

# normalise to avoid zeros - min max between 1 and 100
X <- Normalise(X,
               global_specs = list(f_n = "n_minmax",
                                    f_n_para = list(l_u = c(1,100))))

# aggregate using harmonic mean, with some weights
y <- Aggregate(X, f_ag = "a_hmean", f_ag_para = list(w = c(1, 1, 2, 1)))