This repository serves as a clearing house for examples of paleoscientific work in the form of Jupyter notebooks. Currently, most examples illustrate the scientific use of software libraries maintained by LinkedEarth, but we invite any and all contributions from the community. These examples are fully executable through Binder (click on the badge at the top). Workflows will be updated and maintained until 2024 (sunsetting of PaleoCube grant), after which this will be become a legacy repository.
If you have suggestions for more examples, please submit an issue. If you want to contribute, please see these guidelines. For more technical tutorials on how to use Pyleoclim, see PyleoTutorials. For more general information about Python-based computing in the geosciences, see Pythia Foundations.
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Pyleoclim is a Python package geared towards timeseries analysis of time-uncertain data.
The package can (but do not necessarily have to) directly work with data in the Linked Paleo Data (LiPD) format. The advantage of working with that format is that the code contains automated data transformation, making working with paleoclimate data easier and faster.
All notebooks herein are provided under an Apache 2.0 license.
We needn't tell you that making research tools accessible requires time and effort. If you find any of these resources useful and use them in your own research, please do us the kindness of one or more citations. Notebooks in this collection are registered on Zenodo, and associated with a digital object identifier (DOI). A ready-to-use citation is provided on this GitHub repository in APA and BibTex (in the "About" section on the right panel, click on "Cite this repository"). If you use any of the standards (LiPD) or the software (Pyleoclim), please cite them as well. It will make us (and our sponsors) very happy to hear that these investments spawned more research.
