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https://github.com/pydata/xarray/issues/3984#issuecomment-616214519 https://api.github.com/repos/pydata/xarray/issues/3984 616214519 MDEyOklzc3VlQ29tbWVudDYxNjIxNDUxOQ== 34353851 2020-04-19T19:49:19Z 2020-04-19T19:49:19Z NONE

I dont try it, but i know your problem. If you try to create from dataarray df.to_dataset(name='participant_A') df.to_dataset(name='participant_B') and after merge them?

xr.merge([ds1, ds2], compat='no_conflicts')

http://xarray.pydata.org/en/stable/combining.html

In potter case you could create nan values to create the same dimensions.

But i have never tried. I found another solution for my data, but it was my alternative.

El dom., 19 abr. 2020 20:57, (Ray) Jinbiao Yang notifications@github.com escribió:

I always use Pandas to deal with my neuroscience data (multi-dimension). It is annoying to stack and unstack all the time and I heard Xarray is designed for multi-dimension data.

In neuroscience research, we usually have multiple participants and we will test them different times, which means the data may look like this:

  • participant A:
    • 25100 matrix
  • participant B:
    • 25101 matrix

(100 and 101 are the testing times)

But Dataset doesn't support to have 25100 DataArray and 25101 DataArray together. Is there any solution to deal with that kind of data in Xarray?

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