#release pyam v0.12.0 - Algebraic operations directly on IamDataFrame timeseries #release

Daniel Huppmann

Dear pyam user community, happy to announce a new release v0.12.0 of the pyam package!

Sneak preview

A manuscript describing the pyam package was just accepted in Open Research Europe, a new open-access journal by the European Commission to publish Horizon-2020-funded research. And we will celebrate the publication of this manuscript to officially mark pyam as a „mature“ project - so there will be a release v1.0 soon!

Warning: we will also use release v1.0 to remove all functions that are currently marked as deprecated. I apologize for any inconvenience!

Highlight of release v0.12

Thanks to an initiative by Patrick Jürgens (Fraunhofer ISE) and with some valuable input from core developers (hat tip to Zeb Nicholls), pyam can now perform algebraic operations (add, subtract, multiply, divide) directly on the timeseries data - and it will even handle units correctly for you! 

The screenshot below will give you a quick flavor of the power of this new feature - then check out this new tutorial for details!


And for power users, there is now also an IamDataFrame.apply() function very similar to the pandas apply() function, so that you can execute custom functions on the timeseries data.

More highlights

  • Drop negative weights by default when performing weighted regional aggregation to avoid very „odd“ results (welcome to the developers team, Laura Wienpahl, recently joining the IIASA research software engineers squad).
  • Allow recursive aggregation when (some) intermediate variables exist and perform validation of the existing intermediate variables (again Patrick Jürgens).

More info

Take a look at the complete release notes on GitHub!

Best regards,


Dr. Daniel Huppmann
Research Scholar, Energy Program (ENE)

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
+43(0) 2236 807-572

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