Extract an S_units matrix from a tidy data frame

The .tidydf should be grouped as needed.

Usage

S_units_from_tidy(
  .tidydf,
  Product = IEATools::iea_cols$product,
  Unit = IEATools::iea_cols$unit,
  S_units = Recca::psut_cols$S_units
)

Arguments

.tidydf

the data frame from which an S_units matrix is to be formed

Product

the name of the Product column in .tidydf. Default is "Product".

Unit

the name of the Unit column in .tidydf. Default is "Unit".

S_units

the name of the S_units column to be added to .tidydf. Default is "S_unit".

Value

a data frame containing grouping variables and a new S_unit column

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(matsindf)
library(Recca)
UKEnergy2000tidy |>
  group_by(Country, Year, EnergyType, LastStage) |>
  S_units_from_tidy()
#>   Country Year EnergyType LastStage
#> 1     GBR 2000          E     Final
#> 2     GBR 2000          E  Services
#> 3     GBR 2000          E    Useful
#> 4     GBR 2000          X  Services
#>                                                                                                                                                                                                                                                                                                      S_units
#> 1                                                                                                                                                                                                                                                                         1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
#> 2 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1
#> 3                                                                                                                                                                                                                                                             1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1
#> 4 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1