issue_comments: 465289567

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https://github.com/pydata/xarray/issues/2191#issuecomment-465289567 https://api.github.com/repos/pydata/xarray/issues/2191 465289567 MDEyOklzc3VlQ29tbWVudDQ2NTI4OTU2Nw== 6628425 2019-02-19T20:06:15Z 2019-02-19T20:06:15Z MEMBER

@zzheng93 sure thing!

I hope NCAR will support the next release of xarray.

I know you didn't ask for help with this, but I can't resist :) -- I recommend you set up your own Python environment on Cheyenne. This is nice because it gives you full control over the packages you install (so you don't need to wait until someone else installs them for you). A good place to start on how to do this is the "Getting started with Pangeo on HPC" page on the Pangeo website.

A follow-up question is that when we using xarray to manipulate the large dataset such as <xarray.DataArray (time: 14600, lat: 192, lon: 288)> and want to save the results for further machine learning applications (e.g., using sklearn or XGBoost, even deep learning), what will be a good format to store the data on server or local machine that will be easily used by sklearn or XGBoost?

I think with some more specific details regarding what you are looking to do, this could potentially be a good question to ask in the (relatively new) pangeo-data/ml-workflow-examples repo, where they are discussing machine learning workflows connected to xarray.

 
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