r2dii.analysis is now stable.
target_market_share now outputs target_* value for all years in scenario (#481).ald in favour of abcd (#466).target_market_share now correctly handles input scenarios with a hyphen in their name (#425).target_market_share now handles abcd with rows where production is NA by filling with 0 (#423).target_sda now uses final year of scenario as convergence target when by_company = TRUE (#445).target_market_share gains argument increasing_or_decreasing (#426).r2dii.analysis has transferred to a new organization:
https://github.com/RMI-PACTA/.New argument abcd of target_market_share() and target_sda supersedes the
argument ald (#404).
target_sda() now only outputs data for sector values that are in all three
input datasets (data, ald and co2_intensity_scenario) (#390).
target_sda() now outputs unweighted emission_factor if by_company is
TRUE (#376).
target_sda() gains region_isos argument (#323).
target_market_share() now only outputs values for years that are in both
ald and scenario inputs (#394).
target_market_share() now outputs two new columns, percentage_of_initial_production_by_scope
and scope (ADO #4143).
target_market_share() now outputs 0 technology_share, for companies with
0 sectoral production (#306 @Antoine-Lalechere).
target_sda() now filters scenario start year to be consistent with ald
start year (#346 @waltjl).
target_market_share() now sets all negative smsp targets to zero (#336).
target_market_share() now only outputs sectors that are present in all
input datasets (#329).
target_market_share() now always adds targets for green technologies
(defined by r2dii.data::green_or_brown), even when not present in input
data (#318 @Antoine-Lalechere).
target_market_share() now correctly groups by region when calculating
technology_share (#315 @Antoine-Lalechere).
target_sda() now only outputs sector values that are present in the input
co2_intensity_scenario data (#308).
target_sda() now outputs targets for the range of years in the input
co2_intenstiy_scenario (#307).
target_market_share() now correctly outputs target technology share, in
line with methodology (@georgeharris2deg #277).
target_market_share() now correctly projects technology share as
'production / total production' when computing by company,
unweighted by relative loan size (@KapitanKombajn #288).
target_market_share() no longer outputs columns
sector_weighted_production or technology_weighted_production. Those
columns are internal so they shouldn't face users (#291).
target_market_share() now correctly outputs technology_share with
multiple loans at different level to the same company (@ab-bbva #265).target_market_share() now errors if input data has an unexpected column
(@georgeharris2deg #267).
target_market_share() now correctly outputs technology_share with
multiple loans to the same company (@georgeharris2deg #262, @ab-bbva #265).
target_market_share() now correctly outputs unweighted production by
company, equal to ald-production for one company with multiple loans of
different size (#255 @georgeharris2deg).target_market_share() now correctly outputs unweighted production when
multiple levels exist for the same company (#249).target_market_share() now outputs weighted_technology_share that
correctly sums to 1 when grouped by sector, metric and scenario (#218).
target_market_share() now correctly outputs unweighted production when
multiple loans exist for the same company (#239).
target_market_share() now outputs empty named tibble if no matching region
definitions can be found (#236).
target_market_share now outputs all technologies present in ald, even if
they are not present in data (#235).
target_sda() now interpolates input scenario file by year and correctly
calculates target, regardless of the time-horizon of ald (#234).
Hyperlinks on the "Get Started" tab of the website now points to correct links (#222 @apmanning).
Depend on dplyr >= 0.8.5, explicitly. We commit to this version because the newer dplyr 1 is still relatively new, and represents a major change which some users initially resist.
Relax dependency on rlang, as it is mostly driven dynamically by the by our recursive dependencies. For example, dplyr 0.8.5 depends on a specific version of rlang that is more recent than the version we explicitly depended on -- which suggests that being explicit about rlang is unhelpful and misleading.
New internal data loanbook_stable and region_isos_stable make regression
tests more stable (#227).
Change license to MIT.
The website's home page now thanks founders.
target_market_share() now works as expected when some value of the column
scenario is missing for some value of the column region. It no longer
results in output columns production and technology_share of type "list"
(#203).
The website now shows the News tab.
target_sda() now correctly handles differing country_of_domicile inputs
(#171).
target_market_share() now outputs technology_share (#184).
join_ald_scenario() now returns visibly with dev-magrittr (#188 @lionel-).
target_market_share() gains weight_production parameter (#181).
target_market_share() now correctly use sector_ald column from input
data argument (#178).
target_sda() now automatically filters out ald rows where the
emissions_factor values are NA (#173).
join_ald_scenario() now converts to lower case the values of the columns
sector_ald and technology (#172).
target_sda() now aggregates input ald by technology and plant_location
prior to calculating targets (@QianFeng2020 #160).
target_sda() now errors if input data has any duplicated id_loan
(@QianFeng2020 #164).
target_sda() gains by_company parameter (#155).
target_market_share() now outputs the actual aggregated corporate economy.
Previously, the output would, erroneously, be normalized to the starting
portfolio value (#158).
target_sda() now correctly calculates SDA targets (#153):
Targets are now calculated using scenario data that is adjusted to corporate
economy data.
The adjusted scenario data is also output by the function along with the usual
metrics.
Methodology error fixed, and reflected in the code. Previously, the target
was, incorrectly, calculated by multiplying the adjusted scenario. Now the
scenario data is added instead.
New summarize_weighted_percent_change() allows user to calculate a new
indicator (#141).
target_market_share() no longer errors if the combination of sector and
scenario_target_value does not uniquely identify an observation
(@georgeharris2deg #142).