target_market_share
now outputs target_*
value for all year
s 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 sector
s 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).