#release pyam v1.3.0 - a "compute" module for derived indicators #release


Daniel Huppmann
 

Dear pyam user community,

Happy to announce a new release v1.3 of the pyam package!

# Highlight

A compute module and new functions to easily derive advanced indicators from any timeseries data in the IAMC format.

# Usage of the new module

We added a growth_rate() method, which can be called as 
df.compute.growth_rate({"Primary Energy|Wind": "Growth rate of Wind"})
where df is an IamDataFrame, or
pyam.timeseries.growth_rate(x)
where x is a pd.Series indexed over an (integer) time domain.

Read the Docs for more info!

Warning 

I noticed that the IIASA API does not work with the latest pandas release (v1.4) - I hope that this will be fixed by a pandas patch release, will investigate if the problem persists…

# 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?

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

emailhuppmann@...
webwww.iiasa.ac.at/staff/huppmann

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