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id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
1306543211 PR_kwDOAMm_X847f3yo 6792 Raise an error if you pass an invalid key in `chunks` jsignell 4806877 closed 0     3 2022-07-15T21:23:20Z 2022-08-02T15:57:50Z 2022-07-22T16:52:32Z CONTRIBUTOR   0 pydata/xarray/pulls/6792
  • [x] Tests added

This was a minor issue that came up at the Dask BOF. Currently if the key of chunks dict isn't included in the dims then it gets silently ignored. This PR makes xarray raise an error instead.

I'm not sure if this is the right place to put this change. So just let me know if it should go somewhere else.

I changed an existing test. I am pretty sure it was not intentionally using a key that isn't in the dims. 

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1301237961 PR_kwDOAMm_X847OKqc 6774 Make the `sel` error more descriptive when `method` is unset jsignell 4806877 closed 0     1 2022-07-11T21:17:07Z 2022-07-13T14:49:24Z 2022-07-12T20:33:00Z CONTRIBUTOR   0 pydata/xarray/pulls/6774
  • [x] Tests added

This came up in the tutorial and I was wondering if the error could be made a little clearer. Not sure if the error message should hint that a user might want to use method.

```python import numpy as np import pandas as pd import xarray as xr

arr = xr.DataArray( data=np.arange(48).reshape(4, 2, 6), dims=("u", "v", "time"), coords={ "u": [-3.2, 2.1, 5.3, 6.5], "v": [-1, 2.6], "time": pd.date_range("2009-01-05", periods=6, freq="M"), }, ) arr.sel(u=5, time="2009-04-28") # I removed method="nearest" ```

Before this PR:

python-traceback ... KeyError: 5.0

After this PR:

python-traceback ... KeyError: "not all values found in index 'u'. Did you mean to set `method=`?"

 
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392361367 MDExOlB1bGxSZXF1ZXN0MjM5NjUxOTU3 2618 Adding mask to open_rasterio jsignell 4806877 closed 0     17 2018-12-18T22:24:04Z 2021-06-24T13:44:33Z 2021-06-23T16:14:28Z CONTRIBUTOR   0 pydata/xarray/pulls/2618
  • [x] Discussed in #1736
  • [x] Tests added
  • [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API

Not sure if this is the right approach @snowman2

 
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573007307 MDExOlB1bGxSZXF1ZXN0MzgxNTk3Mzkw 3812 Turn on html repr by default jsignell 4806877 closed 0     6 2020-02-28T21:12:43Z 2020-03-26T02:19:22Z 2020-03-02T23:01:44Z CONTRIBUTOR   0 pydata/xarray/pulls/3812
  • [x] Closes #3806
  • [x] Passes isort -rc . && black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API
 
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512071129 MDExOlB1bGxSZXF1ZXN0MzMyMTUyMDg4 3443 jupyterlab dark theme jsignell 4806877 closed 0     11 2019-10-24T17:08:27Z 2019-10-29T03:47:28Z 2019-10-29T03:47:28Z CONTRIBUTOR   0 pydata/xarray/pulls/3443
  • [ ] Closes #xxxx
  • [ ] Tests added
  • [x] Passes black . && mypy . && flake8
  • [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API

Follow on to #3425 to include support for jupyterlab dark theme. Note that this includes slight color changes. The most striking of which is that in jupyterlab light and regular notebook the even rows are white like the background.

Jlab dark

Jlab light

notebook

 
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510294810 MDExOlB1bGxSZXF1ZXN0MzMwNjk0MDc5 3425 Html repr jsignell 4806877 closed 0     54 2019-10-21T21:08:54Z 2019-10-25T07:00:26Z 2019-10-24T16:48:47Z CONTRIBUTOR   0 pydata/xarray/pulls/3425

This PR supersedes #1820 - see that PR for original discussion. See this gist to try out the new MultiIndex and options functionality.

  • [x] Closes #1627, closes #1820
  • [x] Tests added
  • [x] Passes black . && mypy . && flake8
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API

TODO:

  • [x] Add support for Multi-indexes
  • [x] Probably good to have some opt-in or fail back system in case where we (or users) know that the rendering will not work
  • [x] Add some tests
 
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512162755 MDExOlB1bGxSZXF1ZXN0MzMyMjI2NzU0 3444 Escaping dtypes jsignell 4806877 closed 0     2 2019-10-24T20:24:33Z 2019-10-24T21:51:18Z 2019-10-24T21:50:20Z CONTRIBUTOR   0 pydata/xarray/pulls/3444
  • [ ] Closes #xxxx
  • [x] Tests added
  • [x] Passes black . && mypy . && flake8
  • [ ] Fully documented, including whats-new.rst for all changes and api.rst for new API

Follow-on to https://github.com/pydata/xarray/pull/3425 to make html_repr work with dtypes like '<U5'

 
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354324342 MDExOlB1bGxSZXF1ZXN0MjExMTE0MDUz 2384 Adding data kwarg to copy to create new objects with same structure as original jsignell 4806877 closed 0     17 2018-08-27T13:42:28Z 2018-09-19T13:04:39Z 2018-09-19T01:19:08Z CONTRIBUTOR   0 pydata/xarray/pulls/2384
  • [x] Tests added (for all bug fixes or enhancements)
  • [x] Tests passed (for all non-documentation changes)
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)

This is a PR for the follow on work set out in https://github.com/pydata/xarray/pull/2375#issuecomment-415227870

 
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352677925 MDExOlB1bGxSZXF1ZXN0MjA5OTMxMjYz 2375 Make `dim` optional on unstack jsignell 4806877 closed 0     13 2018-08-21T19:29:06Z 2018-09-05T16:01:23Z 2018-09-05T15:19:07Z CONTRIBUTOR   0 pydata/xarray/pulls/2375
  • [x] Tests added (for all bug fixes or enhancements)
  • [x] Tests passed (for all non-documentation changes)
  • [x] Fully documented, including whats-new.rst for all changes and api.rst for new API (remove if this change should not be visible to users, e.g., if it is an internal clean-up, or if this is part of a larger project that will be documented later)

Not sure if this is a desirable change but I thought it could be easily discussed as a PR. Just for context I was looking at flattening spatial data for machine learning pipelines and then reshaping after the output had been acquired.

I have a NxM array called b and am flattening it like:

python flat_input = b.stack(z=('y', 'x'))

Then I use that flat_input in my ML pipeline and get back an np.array (called output) which I want to unstack using all the metadata that went into stacking my original NxM array b.

python xr.full_like(flat_input, output).unstack(dim='z')

This PR just makes the dim argument optional in unstack so that we can use

python xr.full_like(flat_input, output).unstack()

As a follow on PR I was thinking of making a function called xr.unstack_like(other: xr.DataArray|xr.Dataset, data: array_like) to encompass this functionality. A couple questions:

1) Would something like xr.unstack_like be desirable? 2) Should we be using xr.full_like in this way? The documentation in xarray and numpy only mentions scalars, but arrays work fine in both. If this is a supported behavior I could add docs, and if not perhaps a copy and overwrite is a better approach?

Here is a gist of the workflow using a tweaked datashader example and datashader example data https://gist.github.com/jsignell/79a6cf2da5c1458211d9dcf34d4417df

 
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268171878 MDExOlB1bGxSZXF1ZXN0MTQ4NTAyNDE0 1654 [DOCS] PyNIO is now available on conda-forge jsignell 4806877 closed 0     1 2017-10-24T20:19:28Z 2017-10-24T20:20:02Z 2017-10-24T20:19:59Z CONTRIBUTOR   0 pydata/xarray/pulls/1654

Just a docs change. Updated instructions for installing PyNIO to use conda-forge.

 
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183792892 MDExOlB1bGxSZXF1ZXN0ODk4OTEzNzQ= 1052 catch numpy arrays in attrs before converting to dict jsignell 4806877 closed 0     4 2016-10-18T20:22:50Z 2016-10-25T18:19:50Z 2016-10-25T18:19:45Z CONTRIBUTOR   0 pydata/xarray/pulls/1052

Makes it easier to dump to json (after conversation on #917)

 
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167091064 MDExOlB1bGxSZXF1ZXN0Nzg1MTAyMDk= 917 added to_dict function for xarray objects jsignell 4806877 closed 0     23 2016-07-22T17:14:03Z 2016-10-17T20:33:02Z 2016-08-11T21:54:25Z CONTRIBUTOR   0 pydata/xarray/pulls/917

After the conversation #432 

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Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

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