Successful Python-Focused Software Training Workshop at Jackson State University

JSU Workshop

A Python-focused Unidata Software Training Workshop took place August 30-31, 2018, at Jackson State University. The workshop was sponsored by the Department of Chemistry, Physics, and Atmospheric Sciences (CPAS), and organized by Drs. Remata S. Reddy and the author, in collaboration with Unidata Program Center Staff. Topics covered included the use of Unidata's MetPy and Siphon packages, focusing on atmospheric science applications such as: Upper air data analysis and the Skew-T, making maps with Cartopy, working with surface data analysis, model data, satellite data, time series analysis and more.

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MetPy 0.9.1 Released

MetPy 0.9.1 has been released. New features of the 0.9 series include cross-section support, more calculations, and support for plotting U.S. counties with CartoPy. For full release notes see the GitHub Release Page.

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MetPy 0.8 Released

MetPy 0.8.0 has been released. This release has a wide collection of new features as well as minor bug fixes, including several contributions from our community. For full release notes see the GitHub Release Page.

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MetPy 0.7 Released

MetPy 0.7.0 has been released. This release has a wide collection of new features as well as minor bug fixes, including several contributions from our community. For full release notes see the GitHub Release Page.

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Reminder: Register for MetPy Short Course at 2018 AMS Annual Meeting

AMS

Unidata developers Ryan May and John Leeman, together with Kevin Goebbert from Valparaiso University, will be teaching a one-day short course titled “Python for Dynamical Meteorology Using MetPy” at the 2018 AMS Annual Meeting in Austin, Texas. The format of the course is like that of our larger Python workshop, relying on Jupyter notebooks to teach several core concepts. The crux of the course is to access remote data sets and use MetPy to perform analyses relevant to synoptic/dynamic meteorology. The goal is to go beyond the traditional introduction to Python and work on some concrete, meteorology-specific problems. As a result, familiarity with Python, NumPy, and Matplotlib is assumed.

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News and information from the Unidata Program Center
News@Unidata
News and information from the Unidata Program Center

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