Composable friends

These functions are designed to work well together. Each does something small. Compose them to create complex results.

Usage

profile_emissions_impl(
  companies,
  co2,
  europages_companies,
  ecoinvent_activities,
  ecoinvent_europages,
  isic,
  isic_tilt = lifecycle::deprecated(),
  low_threshold = 1/3,
  high_threshold = 2/3
)

profile_emissions_upstream_impl(
  companies,
  co2,
  europages_companies,
  ecoinvent_activities,
  ecoinvent_inputs,
  ecoinvent_europages,
  isic,
  isic_tilt = lifecycle::deprecated(),
  low_threshold = 1/3,
  high_threshold = 2/3
)

profile_sector_impl(
  companies,
  scenarios,
  europages_companies,
  ecoinvent_activities,
  ecoinvent_europages,
  isic,
  isic_tilt = lifecycle::deprecated(),
  low_threshold = ifelse(scenarios$year == 2030, 1/9, 1/3),
  high_threshold = ifelse(scenarios$year == 2030, 2/9, 2/3)
)

profile_sector_upstream_impl(
  companies,
  scenarios,
  inputs,
  europages_companies,
  ecoinvent_activities,
  ecoinvent_inputs,
  ecoinvent_europages,
  isic,
  isic_tilt = lifecycle::deprecated(),
  low_threshold = ifelse(scenarios$year == 2030, 1/9, 1/3),
  high_threshold = ifelse(scenarios$year == 2030, 2/9, 2/3)
)

See also

Other profile functions: profile_emissions(), profile_sector(), transition_risk_profile()

Examples

library(readr, warn.conflicts = FALSE)
library(tiltToyData)

restore <- options(list(
  readr.show_col_types = FALSE,
  tiltIndicatorAfter.output_co2_footprint = TRUE
))

companies <- read_csv(toy_emissions_profile_any_companies())
co2 <- read_csv(toy_emissions_profile_products_ecoinvent())
europages_companies <- read_csv(toy_europages_companies())
ecoinvent_activities <- read_csv(toy_ecoinvent_activities())
ecoinvent_europages <- read_csv(toy_ecoinvent_europages())
isic_name <- read_csv(toy_isic_name())

result <- profile_emissions_impl(
  companies,
  co2,
  europages_companies = europages_companies,
  ecoinvent_activities = ecoinvent_activities,
  ecoinvent_europages = ecoinvent_europages,
  isic = isic_name
)

result
#> # A tibble: 72 × 3
#>    companies_id                              product           company 
#>  * <chr>                                     <list>            <list>  
#>  1 asteria_megalotomusquinquespinosus        <tibble [6 × 24]> <tibble>
#>  2 skarn_gallinule                           <tibble [6 × 24]> <tibble>
#>  3 relegable_southernhairnosedwombat         <tibble [6 × 24]> <tibble>
#>  4 psychodelic_airedale                      <tibble [6 × 24]> <tibble>
#>  5 ergophilic_fieldspaniel                   <tibble [6 × 24]> <tibble>
#>  6 preexistent_africanmolesnake              <tibble [6 × 24]> <tibble>
#>  7 wealthy_ocelot                            <tibble [6 × 24]> <tibble>
#>  8 fulltime_mollusk                          <tibble [6 × 24]> <tibble>
#>  9 gentlemanlike_asiaticlesserfreshwaterclam <tibble [6 × 24]> <tibble>
#> 10 frowsy_metalmarkbutterfly                 <tibble [6 × 24]> <tibble>
#> # ℹ 62 more rows

# Cleanup
options(restore)