#release pyam v1.3.0 - a "compute" module for derived indicators #release
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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 email: huppmann@... Twitter: @daniel_huppmann International Institute for Applied Systems Analysis Schlossplatz 1, A-2361 Laxenburg, Austria | www.iiasa.ac.at
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