AMS 2014 Presentations are Available Online

Recorded talks (with any extended abstracts/handouts) for the Fourth Python Symposium at the 2014 AMS Annual Meeting are available online. Enjoy!

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UCAR Software Engineering Assembly Conference in April 2014

From Davide Del Vento, posted today to the mailing list:

Folks,

I know most of you are focused on the upcoming AMS meeting (where
unfortunately I can’t go), but I want to make sure you are aware of the
next SEA conference, which will be held in Boulder in April.

The deadline for submitting paper/posters is Friday of next week. Please
consider submitting one! You just need a title and short abstract (which
you can change later on if you need to).

Check it out! https://sea.ucar.edu/conference/2014

Cheers,
Davide Del Vento,
SEA Chair http://sea.ucar.edu/

I was able to attend in 2012; this is an awesome conference!

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Learning/Teaching Python Town Hall at AMS 2014

At the AMS meeting next week, we’ll have a Town Hall on learning and teaching Python: Tuesday, 4 February 2014, 12:15-1:15 pm, Room C302. Here are some more details. Safe travels to everyone who’s going to Atlanta!

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“Building the PyAOS Community” Workshop at AMS

Scott Collis is organizing a workshop on this topic at the 2014 AMS meeting! Here’s the email with details that he sent to the PyAOS mailing list: Continue reading

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Stages in Learning to Code

Andromeda Yelton has a very insightful article on the stages in learning to code and the implications for teaching programming to newbies.

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Aoslib Code Sprint at AMS 2014

Jonathan Helmus is organizing a code sprint for aoslib at the AMS 2014 Python Symposium! Here are the details from an email Jonathan sent out to the mailing listContinue reading

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The Homogenization of Scientific Computing

On the mailing list today, Scott Collis shared this article on why Python is dominating scientific computing. The article also discusses some amazing new Python packages for scientific computing!

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Check Out the SciPy 2013 Talks

As most folks know, SciPy is the premiere conference on doing all things scientific with Python. This is really the place to be if you want to learn about the absolute cutting-edge in using Python for scientific computing. The SciPy 2013 talks are available online, a boon if you weren’t able to make the conference (like myself). Some tracks/mini-symposia of particular interest to PyAOS folks include one on GIS and one on Meteorology, Climatology, Atmospheric and Oceanic Science. The talks all look great; I’ll specifically mention Philip Elson’s talk on Iris and Cartopy which describes a set of really useful tools for PyAOS users. Hope folks can check them out!

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Developing a Site of Examples of Python in the Geosciences

Nikolay Koldunov is developing a site, earthpy.org, of examples of the use of Python in the geosciences, and is looking for contributors. Here’s more details from him:

We are trying to create a place that would collect small tutorials and tips and tricks related to use of Python in the Earth Sciences. Initial idea was that earth scientists are already have a lot of code written in Python but there is no place to share it. If you create a module, or after one week of struggle find interesting solution to a problem, there is no place to share this information, and you can be sure that after some time somebody will write similar module that do exactly the same, and spend the same amount of time to solve similar problem. We all write code that do the same things over and over again.

So in order to address this problem we create Earth.py. If you have some examples for your module, or want to share anything else you think would be useful for other Earth Scientist who write in Python, you can send IPython notebook with your post to me ([email protected]) and I will publish it on Earthpy. If not, I hope you will visit us from time to time to see what’s new :)

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Python for Geosciences

Nikolay Koldunov has a neat introduction to the use of Python in the geosciences as a set of nbviewer files (h/t from the author). In particular I appreciated the examples of how to use pandas, Iris, Cartopy, etc. for AOS applications. Check it out!

Posted in Advanced, Beginner, Teaching, Time Series Analysis, Tutorials, Visualization | 3 Comments