stack_bmkDF {gseries}R Documentation

Stack benchmarks data

Description

(version française: https://StatCan.github.io/gensol-gseries/fr/reference/stack_bmkDF.html)

Convert a multivariate benchmarks data frame (see ts_to_bmkDF()) for the benchmarking functions (benchmarking() and stock_benchmarking()) into a stacked (tall) data frame with six variables (columns):

Missing (NA) benchmark values are not included in the output stacked data frame by default. Specify argument keep_NA = TRUE in order to keep them.

This function is useful when intending to use the by argument (BY-group processing mode) of the benchmarking functions in order to benchmark multiple series in a single function call.

Usage

stack_bmkDF(
  bmk_df,
  ser_cName = "series",
  startYr_cName = "startYear",
  startPer_cName = "startPeriod",
  endYr_cName = "endYear",
  endPer_cName = "endPeriod",
  val_cName = "value",
  keep_NA = FALSE
)

Arguments

bmk_df

(mandatory)

Data frame (object of class "data.frame") that contains the multivariate benchmarks to be stacked.

ser_cName

(optional)

String specifying the name of the character variable (column) in the output stacked data frame that will contain the benchmark names (name of the benchmark variables in the input multivariate benchmarks data frame). This variable can then be used as the BY-group variable (argument by) with the benchmarking functions.

Default value is ser_cName = "series".

startYr_cName, startPer_cName, endYr_cName, endPer_cName

(optional)

Strings specifying the name of the numeric variables (columns) in the input multivariate benchmarks data frame that define the benchmark coverage, i.e., the starting and ending year and period (cycle) identifiers. These variables are transferred to the output stacked data frame with the same variable names.

Default values are startYr_cName = "startYear", startPer_cName = "startPeriod" endYr_cName = "endYear" and endPer_cName = "endPeriod".

val_cName

(optional)

String specifying the name of the numeric variable (column) in the output stacked data frame that will contain the benchmark values.

Default value is val_cName = "value".

keep_NA

(optional)

Logical argument specifying whether missing (NA) benchmark values in the input multivariate benchmarks data frame should be kept in the output stacked data frame.

Default value is keep_NA = FALSE.

Value

The function returns a data frame with six variables:

Note: the function returns a "data.frame" object than can be explicitly coerced to another type of object with the appropriate ⁠as*()⁠ function (e.g., tibble::as_tibble() would coerce it to a tibble).

See Also

stack_tsDF() ts_to_bmkDF() benchmarking() stock_benchmarking()

Examples

# Create an annual benchmarks data frame for 2 quarterly indicator series 
# (with missing benchmark values for the last 2 years)
my_benchmarks <- ts_to_bmkDF(ts(data.frame(ser1 = c(1:3 *  10, NA, NA), 
                                           ser2 = c(1:3 * 100, NA, NA)), 
                                start = c(2019, 1), frequency = 1),
                             ind_frequency = 4)
my_benchmarks


# Stack the benchmarks ...

# discarding `NA` values in the output stacked data frame (default behavior)
stack_bmkDF(my_benchmarks)

# keep `NA` values in the output stacked data frame
stack_bmkDF(my_benchmarks, keep_NA = TRUE)

# using custom variable (column) names
stack_bmkDF(my_benchmarks, ser_cName = "bmk_name", val_cName = "bmk_val")

[Package gseries version 3.0.2 Index]