data_dictionary (#532)data_dictionary dataset added to define the columns in
each dataset used or exported by the functions in this package
(#521).join_ald_scenario,
summarize_weighted_production and
summarize_weighted_percent_change are now soft-deprecated
(#526).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).