#release pyam v1.7.0 - Computing quantiles of scenario ensembles #release
Dear pyam user community,
I’m happy to announce a new release v1.7 of the pyam package!
- 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...
Dr. Daniel HUPPMANN
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)