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1. Climatology data access with ulmo

   Task:

   easy access to climatology data 
   
   

   Solution:

   ulmo
   
   

   Notebook file

   One of the main things that bothers me most at work is data conversion. World would be a much better place for somebody like me if everybody use netCDF file format for data distribution. While situation slightly changing, and more and more organisations switch to netCDF, there are still plenty of those who distribute their data in some crazy forms.

   Would it be nice if somebody once and for all create converters for all this formats and provide a way to directly search and access data from python? Imagine - instead of spending time writing regular expressions for another converter you could watch cat videos on youtube read more

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2. Time series analysis with pandas

   Task:

   analysis of several time series data (AO, NAO)
   
   

   Modules:

   pandas
   
   

   Notebook file

   Here I am going to show just some basic pandas stuff for time series analysis, as I think for the Earth Scientists it's the most interesting topic. If you find this small tutorial useful, I encourage you to watch this video, where Wes McKinney give extensive introduction to the time series data analysis with pandas.

   On the official website you can find explanation of what problems pandas solve in general, but I can tell you what problem pandas solve for me. It makes analysis and visualisation of 1D data, especially time series, MUCH faster. Before pandas working with time series in python was a pain for me, now it's fun. Ease of use stimulate in-depth exploration of the data: why wouldn't you make some additional analysis if it's just one line of code? Hope you will also find this great tool helpful and useful. So, let's begin.

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