Show reduction targets for all tilt_subsectors per grouping_sector
Source: R/show_reduction_targets_for_tilt_subsectors_per_scenario_year.R
show_reduction_targets_for_tilt_subsectors_per_grouping_sector.RdThis function shows reduction targets for all tilt_subsectors per
grouping_sector using product-level output of Sector profile indicator.
Examples
library(dplyr)
sector_product_example <- product_sector |>
select(c("tilt_sector" ,"tilt_subsector", "scenario", "year", "reduction_targets")) |>
distinct()
sector_product_example
#> # A tibble: 12 × 5
#> tilt_sector tilt_subsector scenario year reduction_targets
#> <chr> <chr> <chr> <dbl> <dbl>
#> 1 construction construction residential 1.5C RPS 2030 0.18
#> 2 construction construction residential 1.5C RPS 2050 0.98
#> 3 construction construction residential NZ 2050 2030 0.4
#> 4 construction construction residential NZ 2050 2050 0.97
#> 5 metals other metals 1.5C RPS 2030 0.09
#> 6 metals other metals 1.5C RPS 2050 0.95
#> 7 metals other metals NZ 2050 2030 0.22
#> 8 metals other metals NZ 2050 2050 0.96
#> 9 metals iron & steel 1.5C RPS 2030 0.22
#> 10 metals iron & steel 1.5C RPS 2050 0.96
#> 11 metals iron & steel NZ 2050 2030 0.23
#> 12 metals iron & steel NZ 2050 2050 0.94
show_reduction_targets_for_tilt_subsectors_per_grouping_sector(
sector_product_example
)
#> # A tibble: 3 × 6
#> tilt_sector tilt_subsector IPR_2030 IPR_2050 WEO_2030 WEO_2050
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 construction construction residential 0.18 0.98 0.4 0.97
#> 2 metals iron & steel 0.22 0.96 0.23 0.94
#> 3 metals other metals 0.09 0.95 0.22 0.96