Hassanpreet Dhaliwal

by Hassanpreet Dhaliwal
2022 Unidata summer intern

I started my summer internship with the goals of understanding software development and improving my coding practices to feel confident writing reproducible and sharable code. My time at Unidata not only gave me a structure for writing sharable pieces of software, but also helped me in exploring data manipulation and visualization practices to their full creative extent.

Izzy (Isabelle) Pfander

by Isabelle Pfander
2021 Unidata summer intern

I came into this summer internship with a goal of working on the Network Common Data Form (netCDF) libraries. NetCDF is a combination of software libraries and APIs describing a data model for scientific multidimensional arrays. I planned to improve the online user guide, write tutorial code, and learn about storage and efficiency.

Connor Cozad

by Connor Cozad
2021 Unidata summer intern

I spent this summer with Unidata contributing new features and improvements for version 1.1.0 of MetPy. This release is the first to introduce new features since 1.0 debuted in December 2020. I focused on enhancements to MetPy’s declarative interface, which allows users to plot datasets on maps. These new capabilities provide greater control over map design and introduce support for plotting additional data formats.

Lydia Bunting

by Lydia Bunting
2021 Unidata summer intern

This summer I worked with the Unidata tech team on addressing the MetPy 1.1.0 milestones we prepared for it to update from version 1.0.0. Throughout this process of learning how to navigate GitHub and MetPy and how to implement new code, code verification and testing played a large role.

Lauren Prox

by Lauren Prox
2020 Unidata summer intern

During the beginning of my internship, I devoted a great deal of time learning how to use Git and Github to collaborate on software development projects. After gaining this experience, I began improving documentation for a variety of Unidata remote repositories. I started with the netCDF-C repository and then moved on to the MetPy, Siphon, and Python Training remote repositories. This work was significant as it ensured that software users were able to locate resources, properly download software, and learn how to operate the software via informational materials.