Title: Datasets to Measure the Alignment of Corporate Loan Books with Climate Goals
Version: 0.6.1
Description: These datasets support the implementation in R of the software 'PACTA' (Paris Agreement Capital Transition Assessment), which is a free tool that calculates the alignment between corporate lending portfolios and climate scenarios (https://www.transitionmonitor.com/). Financial institutions use 'PACTA' to study how their capital allocation decisions align with climate change mitigation goals. Because both financial institutions and market data providers keep their data private, this package provides fake, public data to enable the development and use of 'PACTA' in R.
License: CC0
URL: https://rmi-pacta.github.io/r2dii.data/, https://github.com/RMI-PACTA/r2dii.data
BugReports: https://github.com/RMI-PACTA/r2dii.data/issues
Depends: R (≥ 3.4)
Imports: lifecycle, stats, utils
Suggests: charlatan, covr, readr, rlang, rmarkdown, stringi, testthat (≥ 2.1.0)
Config/testthat/edition: 3
Config/Needs/website: rmi-pacta/pacta.pkgdown.rmitemplate
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-06-17 13:05:02 UTC; cjrmi
Author: Jacob Kastl ORCID iD [aut, cre, ctr], Alex Axthelm ORCID iD [aut, ctr, dtc], Jackson Hoffart ORCID iD [aut, ctr, dtc], Mauro Lepore ORCID iD [aut, ctr], RMI [cph, fnd]
Maintainer: Jacob Kastl <jacob.kastl@gmail.com>
Repository: CRAN
Date/Publication: 2025-06-18 08:00:11 UTC

r2dii.data: Datasets to Measure the Alignment of Corporate Loan Books with Climate Goals

Description

logo

These datasets support the implementation in R of the software 'PACTA' (Paris Agreement Capital Transition Assessment), which is a free tool that calculates the alignment between corporate lending portfolios and climate scenarios (https://www.transitionmonitor.com/). Financial institutions use 'PACTA' to study how their capital allocation decisions align with climate change mitigation goals. Because both financial institutions and market data providers keep their data private, this package provides fake, public data to enable the development and use of 'PACTA' in R.

Author(s)

Maintainer: Jacob Kastl jacob.kastl@gmail.com (ORCID) [contractor]

Authors:

Other contributors:

See Also

Useful links:


An asset-based company dataset for demonstration

Description

Fake data about physical assets (e.g. wind turbine power plant capacities), aggregated to company-level. These data are used to assess the climate alignment of financial portfolios. It imitates data from market-intelligence databases.

Demo datasets are synthetic because most financial data is strictly private; they help to demonstrate and test the implementation in R of 'PACTA' (https://www.transitionmonitor.com/).

Usage

abcd_demo

Format

An object of class tbl_df (inherits from tbl, data.frame) with 4972 rows and 12 columns.

Definitions

See Also

data_dictionary

Other demo datasets: co2_intensity_scenario_demo, loanbook_demo, overwrite_demo, region_isos_demo, scenario_demo_2020

Examples

head(abcd_demo)

A prepared CO2 intensity climate scenario dataset for demonstration

Description

Fake CO2 intensity climate scenario dataset, prepared for the software PACTA (Paris Agreement Capital Transition Assessment). It imitates climate scenario data (e.g. from the International Energy Agency (IEA)) including the change through time in production across industrial sectors.

Demo datasets are synthetic because most financial data is strictly private; they help to demonstrate and test the implementation in R of 'PACTA' (https://www.transitionmonitor.com/).

Usage

co2_intensity_scenario_demo

Format

An object of class tbl_df (inherits from tbl, data.frame) with 22 rows and 7 columns.

Definitions

See Also

data_dictionary

Other demo datasets: abcd_demo, loanbook_demo, overwrite_demo, region_isos_demo, scenario_demo_2020

Examples

head(co2_intensity_scenario_demo)

Column definitions of all datasets

Description

This dataset provides metadata about all datasets in the package r2dii.data.

Usage

data_dictionary

Format

An object of class tbl_df (inherits from tbl, data.frame) with 96 rows and 4 columns.

Definitions

Examples

head(data_dictionary)

Dataset to bridge (translate) common sector-classification codes

Description

This dataset serves as a translation key between common sector-classification systems and sectors relevant to the 'PACTA' tool (https://www.transitionmonitor.com/).

Usage

gics_classification

Format

An object of class tbl_df (inherits from tbl, data.frame) with 282 rows and 5 columns.

Definitions

Details

Classification datasets help to standardize sector classification codes from the wild to a relevant subset including 'power', 'oil and gas', 'coal', 'automotive', 'aviation', 'concrete', 'steel', and 'shipping'.

See Also

data_dictionary.

Other datasets for bridging sector classification codes: isic_classification, nace_classification, naics_classification, psic_classification, sector_classifications, sic_classification

Examples

head(gics_classification)

Determine if a technology is increasing or decreasing

Description

This dataset provides a simple lookup table to determine if a technology is meant to increase or decrease to align with a scenario that predicts a less than 2 degree temperature rise.

Usage

increasing_or_decreasing

Format

An object of class tbl_df (inherits from tbl, data.frame) with 20 rows and 3 columns.

Definitions

See Also

data_dictionary

Examples

head(increasing_or_decreasing)

Dataset to bridge (translate) common sector-classification codes

Description

This dataset serves as a translation key between common sector-classification systems and sectors relevant to the 'PACTA' tool (https://www.transitionmonitor.com/).

Usage

isic_classification

Format

An object of class tbl_df (inherits from tbl, data.frame) with 830 rows and 6 columns.

Definitions

Details

Classification datasets help to standardize sector classification codes from the wild to a relevant subset including 'power', 'oil and gas', 'coal', 'automotive', 'aviation', 'concrete', 'steel', and 'shipping'.

See Also

data_dictionary.

Other datasets for bridging sector classification codes: gics_classification, nace_classification, naics_classification, psic_classification, sector_classifications, sic_classification

Examples

head(isic_classification)

Countries and codes

Description

This dataset maps countries to codes.

For information about the ISO standard for country codes see https://www.iso.org/iso-3166-country-codes.html.

Usage

iso_codes

Format

An object of class tbl_df (inherits from tbl, data.frame) with 286 rows and 2 columns.

Definitions

See Also

data_dictionary

Other iso codes: region_isos, region_isos_demo

Examples

head(iso_codes)

A loanbook dataset for demonstration

Description

Fake financial portfolio.

Demo datasets are synthetic because most financial data is strictly private; they help to demonstrate and test the implementation in R of 'PACTA' (https://www.transitionmonitor.com/).

Usage

loanbook_demo

Format

An object of class tbl_df (inherits from tbl, data.frame) with 283 rows and 13 columns.

Definitions

See Also

data_dictionary

Other demo datasets: abcd_demo, co2_intensity_scenario_demo, overwrite_demo, region_isos_demo, scenario_demo_2020

Examples

head(loanbook_demo)

Dataset to bridge (translate) common sector-classification codes

Description

This dataset serves as a translation key between common sector-classification systems and sectors relevant to the 'PACTA' tool (https://www.transitionmonitor.com/).

Usage

nace_classification

Format

An object of class tbl_df (inherits from tbl, data.frame) with 1047 rows and 6 columns.

Definitions

Details

Classification datasets help to standardize sector classification codes from the wild to a relevant subset including 'power', 'oil and gas', 'coal', 'automotive', 'aviation', 'concrete', 'steel', and 'shipping'.

See Also

data_dictionary.

Other datasets for bridging sector classification codes: gics_classification, isic_classification, naics_classification, psic_classification, sector_classifications, sic_classification

Examples

head(nace_classification)

Dataset to bridge (translate) common sector-classification codes

Description

This dataset serves as a translation key between common sector-classification systems and sectors relevant to the 'PACTA' tool (https://www.transitionmonitor.com/).

Usage

naics_classification

Format

An object of class tbl_df (inherits from tbl, data.frame) with 2125 rows and 5 columns.

Definitions

Details

Classification datasets help to standardize sector classification codes from the wild to a relevant subset including 'power', 'oil and gas', 'coal', 'automotive', 'aviation', 'concrete', 'steel', and 'shipping'.

See Also

data_dictionary.

Other datasets for bridging sector classification codes: gics_classification, isic_classification, nace_classification, psic_classification, sector_classifications, sic_classification

Examples

head(naics_classification)

A demonstration dataset used to overwrite specific entity names or sectors

Description

Fake dataset used to manually link loanbook entities to mismatched asset level entities.

Demo datasets are synthetic because most financial data is strictly private; they help to demonstrate and test the implementation in R of 'PACTA' (https://www.transitionmonitor.com/).

Usage

overwrite_demo

Format

An object of class tbl_df (inherits from tbl, data.frame) with 2 rows and 5 columns.

Definitions

See Also

data_dictionary

Other demo datasets: abcd_demo, co2_intensity_scenario_demo, loanbook_demo, region_isos_demo, scenario_demo_2020

Examples

head(overwrite_demo)

Dataset to bridge (translate) common sector-classification codes

Description

This dataset serves as a translation key between common sector-classification systems and sectors relevant to the 'PACTA' tool (https://www.transitionmonitor.com/).

Usage

psic_classification

Format

An object of class tbl_df (inherits from tbl, data.frame) with 1271 rows and 5 columns.

Definitions

Details

Classification datasets help to standardize sector classification codes from the wild to a relevant subset including 'power', 'oil and gas', 'coal', 'automotive', 'aviation', 'concrete', 'steel', and 'shipping'.

See Also

data_dictionary.

Other datasets for bridging sector classification codes: gics_classification, isic_classification, nace_classification, naics_classification, sector_classifications, sic_classification

Examples

head(psic_classification)

A dataset outlining various region definitions

Description

This dataset maps codes representing countries to regions.

For information about the ISO standard for country codes see https://www.iso.org/iso-3166-country-codes.html.

Usage

region_isos

Format

An object of class tbl_df (inherits from tbl, data.frame) with 9262 rows and 3 columns.

Definitions

See Also

data_dictionary

Other iso codes: iso_codes, region_isos_demo

Examples

head(region_isos)

A dataset outlining various region definitions

Description

This dataset maps codes representing countries to regions. It is similar to but smaller than region_isos.

Demo datasets are synthetic because most financial data is strictly private; they help to demonstrate and test the implementation in R of 'PACTA' (https://www.transitionmonitor.com/).

For information about the ISO standard for country codes see https://www.iso.org/iso-3166-country-codes.html.

Usage

region_isos_demo

Format

An object of class tbl_df (inherits from tbl, data.frame) with 358 rows and 3 columns.

Definitions

See Also

Other iso codes: iso_codes, region_isos

Other demo datasets: abcd_demo, co2_intensity_scenario_demo, loanbook_demo, overwrite_demo, scenario_demo_2020

Examples

region_isos_demo

A prepared climate scenario dataset for demonstration

Description

Fake climate scenario dataset, prepared for the software PACTA (Paris Agreement Capital Transition Assessment). It imitates climate scenario data (e.g. from the International Energy Agency (IEA)) including the change through time in production across industrial sectors.

Demo datasets are synthetic because most financial data is strictly private; they help to demonstrate and test the implementation in R of 'PACTA' (https://www.transitionmonitor.com/).

Usage

scenario_demo_2020

Format

An object of class tbl_df (inherits from tbl, data.frame) with 1512 rows and 8 columns.

Definitions

See Also

data_dictionary

Other demo datasets: abcd_demo, co2_intensity_scenario_demo, loanbook_demo, overwrite_demo, region_isos_demo

Examples

head(scenario_demo_2020)

A view of available sector classification datasets

Description

This dataset lists all sector classification code standards used by 'PACTA' (https://www.transitionmonitor.com/).

Usage

sector_classifications

Format

An object of class tbl_df (inherits from tbl, data.frame) with 6559 rows and 4 columns.

Definitions

Details

Classification datasets help to standardize sector classification codes from the wild to a relevant subset including 'power', 'oil and gas', 'coal', 'automotive', 'aviation', 'concrete', 'steel', and 'shipping'.

See Also

data_dictionary.

Other datasets for bridging sector classification codes: gics_classification, isic_classification, nace_classification, naics_classification, psic_classification, sic_classification

Examples

head(sector_classifications)

Dataset to bridge (translate) common sector-classification codes

Description

This dataset serves as a translation key between common sector-classification systems and sectors relevant to the 'PACTA' tool (https://www.transitionmonitor.com/).

Usage

sic_classification

Format

An object of class tbl_df (inherits from tbl, data.frame) with 1005 rows and 5 columns.

Definitions

Details

Classification datasets help to standardize sector classification codes from the wild to a relevant subset including 'power', 'oil and gas', 'coal', 'automotive', 'aviation', 'concrete', 'steel', and 'shipping'.

See Also

data_dictionary.

Other datasets for bridging sector classification codes: gics_classification, isic_classification, nace_classification, naics_classification, psic_classification, sector_classifications

Examples

head(sic_classification)