pyam: analysis and visualization of integrated-assessment scenarios

Release v0.10.0+23.gb2c050b.

Overview

The open-source Python package pyam [1] provides a suite of tools and functions for analyzing and visualizing input data (i.e., assumptions/parametrization) and results (model output) of integrated-assessment scenarios, energy systems analysis, and sectoral studies.

Key features:

• Simple analysis of timeseries data in the IAMC format (more about it here)
  with an interface similar in feel & style to the widely used pandas.DataFrame

• Advanced visualization and plotting functions (see the gallery)

• Features for scripted validation & processing of scenario data and results

The source code for pyam is available on Github.

Table of Contents

• Installation
  • Via your favourite Python Package Manager
  • Installing From Source
  • Dependencies
  • References
• Authors and Developers
• Support and Contributing
  • Have a question? Get in touch!
  • Interested in contributing? Join the team!
• Data Model
  • Background: The IAMC timeseries scenario data format
  • The pyam data model
  • Filtering
  • References
• Tutorials
  • First steps with the pyam package
  • Importing various data table formats
  • Read directly from IIASA data resources
  • Read directly from the UNFCCC Data Inventory
  • Importing results from a GAMS model to an IamDataFrame
  • Performing unit conversions
  • Aggregating and downscaling timeseries data
  • Aggregating subannual timeseries data
  • Using IPCC Color Palettes
  • Customizing legends
  • Plotting aggregate variables
  • Make our Logo!
• Plotting Gallery
• API Reference
  • Input/output file formats
  • General functions
  • The IamDataFrame class
  • Data resources integration
  • Advanced filtering
  • Plotting library
  • The Connection class
  • The Statistics class
  • Timeseries utilities
  • Variables utilities
  • String utilities

• Integration with R

Copyright & License

The development of the pyam package was started at the IIASA Energy Program, with contributions from a number of individuals & institutions over the years.

The package is available under the open-source Apache License. Refer to the NOTICE in the GitHub repository for more information.

Scientific reference

1

Matthew Gidden and Daniel Huppmann. pyam: a Python package for the analysis and visualization of models of the interaction of climate, human, and environmental Systems. Journal of Open Source Software (JOSS), 4(33):1095, 2019. doi:10.21105/joss.01095.