Coiled Xarray Example

Many people use Dask and Coiled for geospatial analysis with Xarray. This example goes through two short notebooks that process a small dataset, and then a larger dataset (6TB) in a couple of minutes. We show how Xarray works with Dask to parallelize analyses and how Coiled scales up both to process large volumes of data on the cloud. For further engagement we recommend people check out the Pangeo Discourse: https://discourse.pangeo.io/ Notebooks here: - https://github.com/coiled/examples/blob/main/geospatial.ipynb - https://github.com/coiled/examples/blob/main/geospatial-large.ipynb conda install -c conda-forge xarray dask coiled s3fs geogif Libraries and things to check out: Xarray: https://docs.xarray.dev/en/stable/ Geopandas: https://geopandas.org/en/stable/ Pangeo: https://pangeo.io/ Dask Infrastructure with Coiled for Pangeo: https://www.youtube.com/watch?v=DpA-pfBZfCk For more info on getting started with Coiled for free: https://coiled.io/start Key Moments 00:00 Intro 01:50 Larger Example 03:33 Computation Starts and Scaling 06:00 Inspect results 06:50 Summary --- Scale Your Python Workloads with Dask and Coiled. Coiled is a Dask company. With Coiled's rock-solid infrastructure, you can quickly and securely create Dask clusters in your cloud account. Learn more about Coiled and get started for free https://coiled.io/start More content on our blog: https://coiled.io/blog