target_sda outputs NAs when supplied with scenario containing sectors not in data or ald

[jdhoffa]

In the function target_sda(), if the input co2_intensity_scenario contains some sectors (e.g. "cement" and "steel'), but the other input datasets data and ald do not (e.g. they only contain "cement"), target_sda() will output NAs for the missing sector.

I would expect the function to not output any information for this sector.

suppressPackageStartupMessages(library(dplyr))
library(r2dii.data)
library(r2dii.analysis)

matched <- tibble::tribble(
  ~id_loan, ~loan_size_outstanding, ~loan_size_outstanding_currency, ~loan_size_credit_limit, ~loan_size_credit_limit_currency, ~id_2dii,            ~level, ~score,  ~sector,         ~name_ald, ~sector_ald,
  "L162",                      1,                           "EUR",                       2,                            "EUR",    "UP1", "ultimate_parent",      1, "cement", "american cement",    "cement"
)

ald <- tibble::tribble(
  ~company_id,     ~name_company, ~lei,  ~sector,           ~technology,  ~production_unit, ~year, ~production, ~emission_factor, ~country_of_domicile, ~plant_location, ~is_ultimate_owner, ~ald_timestamp,               ~emission_factor_unit,
  "18", "american cement",   NA, "cement", "integrated facility", "tonnes per year", 2020L, 6196233.305,      0.683651289,                 "GE",            "SM",              FALSE,       "1994Q1", "tonnes of CO2 per tonne of cement"
)

scenario <- tibble::tribble(
  ~scenario_source, ~scenario,  ~sector,  ~region, ~year,               ~emission_factor_unit, ~emission_factor,
  "demo_2020",    "demo", "cement", "global",  2020, "tonnes of CO2 per tonne of Cement",              0.7,
  "demo_2020",    "demo", "cement", "global",  2021, "tonnes of CO2 per tonne of Cement",              0.4,
  "demo_2020",    "demo",  "steel", "global",  2020,  "tonnes of CO2 per tonne of Steel",                2,
  "demo_2020",    "demo",  "steel", "global",  2021,  "tonnes of CO2 per tonne of Steel",              1.5
)

out <- matched %>% 
  target_sda(
    ald_demo,
    scenario
  )
#> Warning: Removing ald rows where `emission_factor` is NA

filter(out, emission_factor_metric == "target_demo")
#> # A tibble: 4 × 4
#>   sector  year emission_factor_metric emission_factor_value
#>   <chr>  <dbl> <chr>                                  <dbl>
#> 1 cement  2020 target_demo                            0.684
#> 2 steel   2020 target_demo                           NA    
#> 3 cement  2021 target_demo                            0.378
#> 4 steel   2021 target_demo                           NA

^{Created on 2022-04-05 by the reprex package (v2.0.1)}

[jdhoffa]

The above reprex is not that useful. I have isolated the issue more precisely.
It occurs when:
Both ald and scenario contain multiple sectors, but data only matches to a company within one of those sectors:

suppressPackageStartupMessages(library(dplyr))
library(r2dii.data)
library(r2dii.analysis)

matched <- tibble::tribble(
  ~id_loan, ~loan_size_outstanding, ~loan_size_outstanding_currency, ~loan_size_credit_limit, ~loan_size_credit_limit_currency, ~id_2dii,            ~level, ~score,      ~sector,      ~name_ald, ~sector_ald,
  "L162",                      1,                           "EUR",                       2,                            "EUR",    "UP1", "ultimate_parent",      1, "automotive", "shaanxi auto",    "cement"
)

ald <- tibble::tribble(
  ~name_company,  ~sector, ~technology, ~year, ~production, ~emission_factor, ~plant_location, ~is_ultimate_owner,
  "shaanxi auto", "cement",       "ice",  2025,           1,                1,            "BF",               TRUE,
  "shaanxi auto",  "steel",       "ice",  2025,           1,                1,            "BF",               TRUE
)

scenario <- tibble::tribble(
  ~scenario,  ~sector,  ~region, ~year, ~emission_factor,           ~emission_factor_unit, ~scenario_source,
  "b2ds", "cement", "global",  2025,                1, "tons of CO2 per ton of cement",      "demo_2020",
  "b2ds", "cement", "global",  2026,                2, "tons of CO2 per ton of cement",      "demo_2020",
  "b2ds",  "steel", "global",  2025,                1, "tons of CO2 per ton of cement",      "demo_2020",
  "b2ds",  "steel", "global",  2026,                2, "tons of CO2 per ton of cement",      "demo_2020"
)

out <- target_sda(
  matched,
  ald,
  scenario,
  region_isos = region_isos_demo
)

out %>% filter(emission_factor_metric == "target_b2ds")
#> # A tibble: 4 × 6
#>   sector  year region scenario_source emission_factor_metric emission_factor_va…
#>   <chr>  <dbl> <chr>  <chr>           <chr>                                <dbl>
#> 1 cement  2025 global demo_2020       target_b2ds                              1
#> 2 steel   2025 global demo_2020       target_b2ds                             NA
#> 3 cement  2026 global demo_2020       target_b2ds                              2
#> 4 steel   2026 global demo_2020       target_b2ds                             NA

^{Created on 2022-04-25 by the reprex package (v2.0.1)}