Fwd: [pyam] #release pyam v1.7.0 - Computing quantiles of scenario ensembles

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Daniel Huppmann

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Dec 22, 2022, 4:21:37 AM12/22/22
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Hi openmod community,

I don’t usually send pyam release announcements to consortium lists (to reduce spam), but my colleague Matt Gidden just added a feature that may be useful for many of you…

When analyzing large ensembles of scenarios, we often want to compute quantiles across the „spaghetti“ of timeseries data. pyam now has a feature to easily do this. Simply run

df.compute.quantiles([0.25, 0.5, 0.75])

and then do further analysis or plot the data! See this tutorial for more information… 

And if you’re still reading this and thinking „well, it’s not difficult to compute quantiles, I can do that in five lines myself…“ - the whole point of the pyam package is to reduce common operations from five lines to one, and have that method be well-tested and easily chain-able to other operations, plotting or data i/o...

We’d appreciate any feedback or comments to make this even more useful.

Have a nice holiday season and good start into 2023!

All the best,
Daniel


Von: "Daniel Huppmann" <d...@dergelbesalon.at>
Betreff: [pyam] #release pyam v1.7.0 - Computing quantiles of scenario ensembles
Datum: 21. Dezember 2022 um 09:52:35 MEZ

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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