Data wrangling for the "IEA Net Zero by 2050" Roadmap

Copyright 2021 Daniel Huppmann

Scope and aim

This repository contains scripts and notebooks to transform the data supporting the IEA's Net Zero by 2050 flagship report (published May 2021) to the IAMC format.

Input data

Please download the data files from the IEA Net Zero by 2050 data page
and save them in the data folder of the cloned or downloaded repository.

Output data

The scripts and notebooks in this repository extract the data from the Excel spreadsheets of the Annex and each chapter's figures and tables and transform it to the format established by the Integrated Assessment Modeling Consortium (IAMC) and used in recent reports of the Intergovernmental Panel on Climate Change (IPCC) as well as several EU Horizon 2020 projects.

model	scenario	region	variable	unit	2005	2010	2015
MESSAGE	CD-LINKS 400	World	Primary Energy	EJ/y	462.5	500.7	...
...	...	...	...	...	...	...	...

An illustration of the IAMC template using a scenario from the CD-LINKS project
via the The IAMC 1.5°C Scenario Explorer

Dependencies

The Python package pyam was developed to facilitate working with timeseries data following the data format developed by the IAMC. Features include validation of values, aggregation and downscaling of data, and import/export (i/o) with various file formats (xlsx, csv, ...) and table layouts (wide vs. long data).

Read the docs for more information!

TL;DR - Quick install

You can install pyam and all its dependencies via the Python Package Index (PyPI) and on Conda.

# conda
conda install -c conda-forge pyam

# PyPI
pip install pyam-iamc

License

The scripts and notebooks in this repository are licensed under the Apache License, Version 2.0;
see the LICENSE and NOTICE for details.