#release pyam v1.7.0 - Computing quantiles of scenario ensembles #release


Daniel Huppmann
 

Dear pyam user community,

I’m happy to announce a new release v1.7 of the pyam package!

# Highlight

- Add a feature to compute (weighted) quantiles for scenario data - see this tutorial!
- Implement a require_data() method for streamlined scenario validation
- Remove 'xls' as by-default-supported file format to harmonize behavior with pandas (but you can still use it, of course*)

[* simply install the package xlrd manually]

# API changes

The method compute_bias() was removed; please use compute.bias() instead.

# Dependency changes

This release removes xlrd as a required dependency; please install it explicitly for reading .xls files.
Please bump the minimum version of pandas to v1.2.0 to support automatic engine selection.

# Known issues

The latest release of the numpy package has some issues with the plotting library. For the time being, please stick with numpy<1.24.

# Join the Slack workspace?

If you want to ask questions or read tips-and-tricks from time to time on how to use pyam more effectively in your scenario analysis or data-viz work, maybe consider joining our Slack workspace?

For more information, please read the full release notes...

Best regards,
Daniel



Dr. Daniel HUPPMANN
Research Scholar
Coordinator of the Research Theme „Scenario Services & Scientific Software"
Energy, Climate, and Environment (ECE) Program

Co-Chair of the Second Austrian Assessment Report on Climate Change (AAR2)

International Institute for Applied Systems Analysis
Schlossplatz 1, A-2361 Laxenburg, Austria | www.iiasa.ac.at

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