Cookbooks Gallery
Pythia Cookbooks provide example workflows on more advanced and domain-specific problems developed by the Pythia community. Cookbooks build on top of skills you learn in Pythia Foundations.
Cookbooks are created from Jupyter Notebooks that we strive to binderize so each Cookbook can be executed in the cloud with a single click from your browser, but in some instances executing a Cookbook will require running the notebooks locally.
Interested in contributing a new Cookbook or contributing to an existing Cookbook? Great! Please see the Project Pythia Cookbook Contributor’s Guide, and consider opening a discussion under the Project Pythia category of the Pangeo Discourse.

CESM LENS on AWS Cookbook
Author: Banihirwe, Anderson, Bonnlander, Brian, de La Beaujardière, Jeff, Henderson, Scott, CESM LENS on AWS Cookbook contributors
Notebooks developed to demonstrate analysis of CESM LENS data publicly available on Amazon S3 (us-west-2 region) using Xarray and Dask.

CMIP6 Cookbook
Author: Abernathey, Ryan, Drake, Henri, Ford, Robert R., CMIP6 Cookbook contributors
Examples of analysis of Google Cloud CMIP6 data using Pangeo tools.

HRRR AWS Cookbook
Author: Tyle, Kevin, HRRR-AWS Cookbook contributors
A cookbook for working with AWS-served HRRR model output data.

Radar Cookbook
Author: Grover, Maxwell, Sherman, Zachary, Sharma, Milind, Ladino, Alfonso, Camron, Crystal, Radar Cookbook contributors
A cookbook meant to work with various weather radar data.
Intake Cookbook
Author: Morley, James, Intake Cookbook contributors
This cookbook shows examples of using and creating Intake catalogs to access data.

Landsat ML Cookbook
Author: Roumis, Demetris, Landsat ML Cookbook contributors
Machine learning on Landsat data.

Kerchunk Cookbook
Author: Hagen, Norland Raphael, Kerchunk Cookbook contributors
Kerchunk provides cloud-friendly access to archival data. With Kerchunk you can read collections of legacy file formats (NetCDF, GRIB2 etc.) as if they were ARCO (Analysis-Ready Cloud-Optimized) formats such as Zarr, without creating a copy of the original dataset.

xbatcher for Machine Learning Part 1 Cookbook
Author: Dupuis, Christopher, Sinha, Anirban, Abernathey, Ryan, xbatcher for Machine Learning Part 1 Cookbook contributors
A complete workflow for a convolutional neural network using xbatcher.

Dask Cookbook
Author: Sobhani, Negin, Brian, Vanderwende, Cherian, Deepak, Kirk, Ben, Dask Cookbook contributors
A cookbook for Dask workflows.

ARCO ERA-5 Interactive Visualization Cookbook
Author: Tyle, Kevin, Barletta, Michael, ARCO ERA-5 Cookbook contributors
A cookbook to interactively explore and visualize ERA-5 data in ARCO format.

Web Map / Feature Services Cookbook
Author: Huang, Andrew, Web Map / Feature Services Cookbook contributors
Learn how to use web map and feature services to easily and quickly provide spatial context, without the need to download and process GBs of data!

Sentinel-2 L2A Interactive Dashboard
Author: Das, Pritam, This Cookbook contributors
This Project Pythia Cookbook provides a recipe for building an interactive dashboard for the Sentinel-2 L2A satellite imagery using the holoviews ecosystem.

(re)Gridding with xarray
Author: Martin, Thomas, (re)Gridding with xarray contributors
A small collection of notebooks that explores some (re)gridding options within the Xarray ecosystem. The thumbnail image was created with the assistance of DALL·E 2.

Vapor Python Cookbook
Author: Cherukuru, Nihanth, Jarosynski, Stanislaw 'Stas', Austin, Philip, VAPOR python cookbook contributors
The Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) provides an interactive 3D visualization environment for exploratory visual analysis and the production of captivating animations and high-quality images. VAPOR runs on most UNIX and Windows systems equipped ... more

Vapor Python Cookbook
Author: Cherukuru, Nihanth, Jarosynski, Stanislaw 'Stas', Austin, Philip, VAPOR python cookbook contributorsThe Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers (VAPOR) provides an interactive 3D visualization environment for exploratory visual analysis and the production of captivating animations and high-quality images. VAPOR runs on most UNIX and Windows systems equipped with modern 3D graphics cards.
3D-visualizations climate numpy particles weather xarray

Advanced Visualization Cookbook
Author: Kent, Julia, Zacharias, Anissa, Advanced Visualization Cookbook contributors
This Cookbook demonstrates advanced plotting routines using the Python packages matplotlib, cartopy, metpy, and geocat-viz.