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https://github.com/pydata/xarray/issues/1262#issuecomment-279505323 https://api.github.com/repos/pydata/xarray/issues/1262 279505323 MDEyOklzc3VlQ29tbWVudDI3OTUwNTMyMw== 1217238 2017-02-13T20:00:53Z 2017-02-13T20:09:43Z MEMBER

So question: Is it sensible to add logical dtype information to XArray?

Sure, this would pretty sensible, especially if there is a nice story for wrapping upstream libraries providing alternate physical arrays such as dask.array and bolt (cc @freeman-lab).

There are certainly plenty of use-cases. A few more examples that would be particularly relevant for xarray:

  • a generic optional dtype for handling missing values (e.g., for integers)
  • a generic wrapper for 1D pandas dtypes into N-dimensional arrays
  • physical units (https://github.com/pydata/xarray/issues/525)

Can this be done with only moderate effort and maintenance costs to the XArray project?

If we have a well defined interface that defines the right operations, my guess is indeed "yes, probably". See https://github.com/bolt-project/bolt/issues/58 for a list of operations worth considering wrapping (obviously some of these, like arithmetic, are not needed for all dtypes).

If the answer is "yes, probably", then what is the right way to go about this?

I think it should start as a separate package to ensure a cleanly separated interface and because there are definitely other clients than xarray. We can quickly add it as an optional dependency to xarray for testing purposes.

I'm excited about this, but I'm unlikely to have much time available to work on this directly.

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