Describe the topic for the talk
The project "Xarray Tutorial" provides a series of Jupyter notebooks introducing the xarray library to a scientific audience. Having a talk series (particularly focussed on the "Fundamental Path") would allow us to introduce IMAU to xarray leveraging these great resources.
In particular, it would be good to have a mix of tutorial as well as case studies (where we get example workflows from members at IMAU and see how those can be adapted to use xarray).
The fact that xarray tutorial has Binder/GitHub codespaces support already set up means that we can easily drop into an environment where the notebooks can be run.
Describe the benefit
Working with NetCDF data (or data adhering to the NetCDF/Unidata data model) is core to climate science. Leveraging xarray and the powerful data model it provides in these workflows is really impactful, and would allow users to greatly speed up and simplify analysis (compared to numpy based Python workflows or Matlab workflows).
Would you be capable/willing to give the talk?
Yes (though it would be good to have input from others as well)
Additional comments
I think a good setup would be a 2 part series on 2025-05-29 and 2025-06-12 (2hr each?), with the first session being a motivating case study where we get matlab or numpy code and convert it to an xarray workflow (/data pipeline if it's a data transformation task).
Describe the topic for the talk
The project "Xarray Tutorial" provides a series of Jupyter notebooks introducing the xarray library to a scientific audience. Having a talk series (particularly focussed on the "Fundamental Path") would allow us to introduce IMAU to xarray leveraging these great resources.
In particular, it would be good to have a mix of tutorial as well as case studies (where we get example workflows from members at IMAU and see how those can be adapted to use xarray).
The fact that xarray tutorial has Binder/GitHub codespaces support already set up means that we can easily drop into an environment where the notebooks can be run.
Describe the benefit
Working with NetCDF data (or data adhering to the NetCDF/Unidata data model) is core to climate science. Leveraging xarray and the powerful data model it provides in these workflows is really impactful, and would allow users to greatly speed up and simplify analysis (compared to numpy based Python workflows or Matlab workflows).
Would you be capable/willing to give the talk?
Yes (though it would be good to have input from others as well)
Additional comments
I think a good setup would be a 2 part series on 2025-05-29 and 2025-06-12 (2hr each?), with the first session being a motivating case study where we get matlab or numpy code and convert it to an xarray workflow (/data pipeline if it's a data transformation task).