html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/7385#issuecomment-1467015318,https://api.github.com/repos/pydata/xarray/issues/7385,1467015318,IC_kwDOAMm_X85XcOCW,221526,2023-03-13T21:51:19Z,2023-03-13T21:51:19Z,CONTRIBUTOR,"@dcherian Is this behavior (filling with `fill_value` -> inserting Nans) because they share common dimensionality in terms of name, but have different coordinate values? My expectation was something that operated more like numpy broadcasting (repeating values, not filling with anything else).
I can understand how xarray's data model yields this behavior, but in that case it might be good to improve the docs for `xarray.broadcast`, because it says nothing about the behavior that (seem to me) mimics `xarray.align`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1499473190
https://github.com/pydata/xarray/issues/7525#issuecomment-1448430261,https://api.github.com/repos/pydata/xarray/issues/7525,1448430261,IC_kwDOAMm_X85WVUq1,221526,2023-02-28T15:57:16Z,2023-02-28T15:57:16Z,CONTRIBUTOR,@ethanrd @haileyajohnson @tdrwenski any thoughts on the above question?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1583216781
https://github.com/pydata/xarray/issues/7350#issuecomment-1338290177,https://api.github.com/repos/pydata/xarray/issues/7350,1338290177,IC_kwDOAMm_X85PxLAB,221526,2022-12-05T22:56:30Z,2022-12-05T22:56:30Z,CONTRIBUTOR,"So I'll say that taking my dataset and running `nc.squeeze()` was illustrative to the problem here. I see now that if a `Dataset` has scalar coordinates, they apply to every `DataArray`/`Variable` inside. So I see what prompts the current behavior.
I think the mismatch in my mental model is due to me coming from netCDF CF land, where coordinates for a variable are based on:
1. Other variables that match relevant shared dimension names
2. Those explicitly listed in the `coordinates` attribute
I see now that xarray does NOT implement that model.
This was provoked by challenges creating a new `DataArray`, but I see those can be solved by passing in both `dims` and `coords` (when coords contains some scalar coords).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1473329967
https://github.com/pydata/xarray/issues/7350#issuecomment-1337859447,https://api.github.com/repos/pydata/xarray/issues/7350,1337859447,IC_kwDOAMm_X85Pvh13,221526,2022-12-05T17:57:34Z,2022-12-05T17:57:34Z,CONTRIBUTOR,"IMO, it's not correctly implementing the rule as you phrased it. You said ""still present"", which isn't the case here since the coordinate wasn't present before.
The behavior I'd advocate for is that a subsetting/selection operation should never add new coordinates that weren't previously present. That by itself would be less surprising. It would also help make things more sensible given that the coordinate is only added currently in the scalar case--if you ask for more data, the coordinate isn't added, which is also unexpected given the scalar case.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1473329967
https://github.com/pydata/xarray/issues/7191#issuecomment-1285866801,https://api.github.com/repos/pydata/xarray/issues/7191,1285866801,IC_kwDOAMm_X85MpMUx,221526,2022-10-20T16:51:21Z,2022-10-20T16:51:21Z,CONTRIBUTOR,I'm also not sure why `_FillValue` and `missing_value` should be required to have the same value.,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1416709246
https://github.com/pydata/xarray/pull/6981#issuecomment-1270591340,https://api.github.com/repos/pydata/xarray/issues/6981,1270591340,IC_kwDOAMm_X85Lu69s,221526,2022-10-06T19:38:24Z,2022-10-06T19:38:24Z,CONTRIBUTOR,"We elected not to start rebuilding things with netCDF 4.9.0 since 4.9.1 should be out realSoonNow™️ , so I don't think there's a netcdf4 package in conda-forge that has it yet.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1359914824
https://github.com/pydata/xarray/issues/7034#issuecomment-1246106470,https://api.github.com/repos/pydata/xarray/issues/7034,1246106470,IC_kwDOAMm_X85KRhNm,221526,2022-09-14T01:05:44Z,2022-09-14T01:05:44Z,CONTRIBUTOR,That just worked fine for me. What version of libnetcdf and netcdf4 do you have installed?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1372146714
https://github.com/pydata/xarray/issues/6766#issuecomment-1180471644,https://api.github.com/repos/pydata/xarray/issues/6766,1180471644,IC_kwDOAMm_X85GXJFc,221526,2022-07-11T14:20:06Z,2022-07-11T14:20:06Z,CONTRIBUTOR,"@DanCodigaMWRA Well, given that it's failing with `ncdump`, you can skip netcdf4 and go straight to [netcdf-c](https://github.com/Unidata/netcdf-c).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1299316581
https://github.com/pydata/xarray/issues/6766#issuecomment-1179403944,https://api.github.com/repos/pydata/xarray/issues/6766,1179403944,IC_kwDOAMm_X85GTEao,221526,2022-07-08T22:22:15Z,2022-07-08T22:22:15Z,CONTRIBUTOR,"I just created a new Python 3.7 environment on my Mac and that worked fine. What do these show?
```
❯ conda list curl
# packages in environment at /Users/rmay/miniconda3/envs/py37:
#
# Name Version Build Channel
curl 7.83.1 h23f1065_0 conda-forge
libcurl 7.83.1 h23f1065_0 conda-forge
❯ conda list certifi
# packages in environment at /Users/rmay/miniconda3/envs/py37:
#
# Name Version Build Channel
ca-certificates 2022.6.15 h033912b_0 conda-forge
certifi 2022.6.15 py37hf985489_0 conda-forge
```
Though I agree this is not an xarray problem at this point. Does it work if you do (with the env active):
```
ncdump -h http://psl.noaa.gov/thredds/dodsC/Datasets/NARR/monolevel/uwnd.10m.2000.nc
```
?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1299316581
https://github.com/pydata/xarray/issues/6374#issuecomment-1071517967,https://api.github.com/repos/pydata/xarray/issues/6374,1071517967,IC_kwDOAMm_X84_3hEP,221526,2022-03-17T21:30:22Z,2022-03-17T21:30:22Z,CONTRIBUTOR,Cc @WardF @DennisHeimbigner @haileyajohnson,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1172229856
https://github.com/pydata/xarray/issues/6124#issuecomment-1007746645,https://api.github.com/repos/pydata/xarray/issues/6124,1007746645,IC_kwDOAMm_X848EP5V,221526,2022-01-07T21:16:20Z,2022-01-07T21:16:20Z,CONTRIBUTOR,"$0.02 from the peanut gallery is that my mental model of `Dataset` is that it's a dictionary on steroids, so following the `Mapping` protocol (including `__bool__`) makes sense to me. I put ""I don't know"" for @shoyer's poll, but if the question was ""should"" then I would have said ""number of variables"".
While I'm not going to sit here and argue that `if ds:` is a common operation and important feature (I don't often open files that result in empty datasets), I'd personally want a truly compelling argument for breaking from the `Mapping` protocol. Right now it's ""`Dataset` works like `dict` *plus* some stuff"". It would change to be ""`Dataset` works like `dict` for all things except `__bool__`, plus some stuff"". The latter to me requires more mental effort since I'm no longer strictly supplementing past experience.","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1090229430
https://github.com/pydata/xarray/issues/5927#issuecomment-958120426,https://api.github.com/repos/pydata/xarray/issues/5927,958120426,IC_kwDOAMm_X845G8Hq,221526,2021-11-02T19:56:21Z,2021-11-02T19:56:21Z,CONTRIBUTOR,GitHub's new [automated release notes](https://docs.github.com/en/repositories/releasing-projects-on-github/automatically-generated-release-notes) may be of interest to some of this discussion. Essentially they allow you to provide a template to format the list of merged PRs on the branch since the last release.,"{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1042652334
https://github.com/pydata/xarray/issues/5913#issuecomment-954948424,https://api.github.com/repos/pydata/xarray/issues/5913,954948424,IC_kwDOAMm_X84461tI,221526,2021-10-29T18:13:34Z,2021-10-29T18:13:34Z,CONTRIBUTOR,"Is this with the netcdf or with the pydap engine? If you're not sure, can you post the full error traceback?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1039113959
https://github.com/pydata/xarray/issues/5882#issuecomment-954028015,https://api.github.com/repos/pydata/xarray/issues/5882,954028015,IC_kwDOAMm_X8443U_v,221526,2021-10-28T16:55:26Z,2021-10-28T16:55:26Z,CONTRIBUTOR,Can you post the full traceback you get?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1032694511
https://github.com/pydata/xarray/issues/5882#issuecomment-953921596,https://api.github.com/repos/pydata/xarray/issues/5882,953921596,IC_kwDOAMm_X84427A8,221526,2021-10-28T14:49:26Z,2021-10-28T14:49:26Z,CONTRIBUTOR,"@saveriogzz I'm confused why you posted results for 3.6 and 3.8, given that the original issue looks like it was posted for 3.7. 🤨 At any rate, looks like your original issue, the output from `show_versions()` lists `libnetcdf=4.7.4`. That version should be fixed with regards to the `_FillValue type mismatch` error.
Your Python 3.8 environment *does* have an old version of libnetcdf. Can you try doing `conda install -n py38 -c conda-forge ""libnetcdf>=4.7.4""` and see if that fixes your problem?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1032694511
https://github.com/pydata/xarray/issues/5882#issuecomment-952246143,https://api.github.com/repos/pydata/xarray/issues/5882,952246143,IC_kwDOAMm_X844wh9_,221526,2021-10-26T19:29:52Z,2021-10-26T19:29:52Z,CONTRIBUTOR,@saveriogzz what is the output of `conda list libnetcdf`?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1032694511
https://github.com/pydata/xarray/pull/5845#issuecomment-951404731,https://api.github.com/repos/pydata/xarray/issues/5845,951404731,IC_kwDOAMm_X844tUi7,221526,2021-10-25T23:10:25Z,2021-10-25T23:10:25Z,CONTRIBUTOR,"You cannot use selectors with noarch conda packages. Full stop.
For conda-forge, it's perfectly fine to just unconditionally depend on the `importlib_metadata` backport, especially with the implementation done like here where you use the std lib version and fall back.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1020407925
https://github.com/pydata/xarray/issues/5711#issuecomment-900601202,https://api.github.com/repos/pydata/xarray/issues/5711,900601202,IC_kwDOAMm_X841rhVy,221526,2021-08-17T20:16:57Z,2021-08-17T20:16:57Z,CONTRIBUTOR,"The metadata for that package has been patched in conda-forge/conda-forge-repodata-patches-feedstock#161 to depend on `python >=3.7`, so this shouldn't be an issue any more. @kim-barker How are you installing xarray/setting up your environment? What `conda` commands are you running? What OS/platform architecture?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,972878124
https://github.com/pydata/xarray/issues/5291#issuecomment-841524018,https://api.github.com/repos/pydata/xarray/issues/5291,841524018,MDEyOklzc3VlQ29tbWVudDg0MTUyNDAxOA==,221526,2021-05-14T22:00:52Z,2021-05-14T22:00:52Z,CONTRIBUTOR,On conda it's usually only done to avoid problematic/heavy weight dependencies (i.e. avoiding pyqt dependency with `matplotlib-base`). I'm not sure it's worth doing for pooch.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,889162918
https://github.com/pydata/xarray/pull/5244#issuecomment-831449400,https://api.github.com/repos/pydata/xarray/issues/5244,831449400,MDEyOklzc3VlQ29tbWVudDgzMTQ0OTQwMA==,221526,2021-05-03T18:34:12Z,2021-05-03T18:34:12Z,CONTRIBUTOR,"@andersy005 I'm curious, why do you go with multiple jobs within the workflow, and using artifacts to transfer state between them, rather than multiple steps in a single job?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,873842812
https://github.com/pydata/xarray/issues/5232#issuecomment-830254596,https://api.github.com/repos/pydata/xarray/issues/5232,830254596,MDEyOklzc3VlQ29tbWVudDgzMDI1NDU5Ng==,221526,2021-04-30T17:42:09Z,2021-04-30T17:42:09Z,CONTRIBUTOR,"> We can avoid this by using the pypi github action thing to automatically build and upload when tagging a release on github. It uses a repo-level secret. Just a thought.
$0.02 from an outsider is that this has served us exceedingly well on MetPy. Our release process has become:
1. Close milestone
2. Adjust the auto-generated draft GitHub release (summary notes)
3. Click ""publish release"" -> packages uploaded to PyPI
4. Merge conda-forge update from their bots
It's almost *more* secure this way because the token from PyPI only has upload permissions--no need to store someone's password.","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,870292042
https://github.com/pydata/xarray/issues/5189#issuecomment-824227019,https://api.github.com/repos/pydata/xarray/issues/5189,824227019,MDEyOklzc3VlQ29tbWVudDgyNDIyNzAxOQ==,221526,2021-04-21T17:19:21Z,2021-04-21T17:19:21Z,CONTRIBUTOR,"> KeyError: 'tmp2m%2Etmp2m'
This looks like an issue with the encoding of the URL and what the server expects.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,861684673
https://github.com/pydata/xarray/issues/4925#issuecomment-812643265,https://api.github.com/repos/pydata/xarray/issues/4925,812643265,MDEyOklzc3VlQ29tbWVudDgxMjY0MzI2NQ==,221526,2021-04-02T18:01:21Z,2021-04-02T18:01:21Z,CONTRIBUTOR,"The message:
> ""The identifier `tmax.tmax%5b0%5d%5b0:3:620%5d%5b0:3:1404%5d' is not in the dataset.""
makes me wonder if there's some issue with how the webserver is handling the escaping of certain characters (like e.g. `[`)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,811409317
https://github.com/pydata/xarray/pull/4431#issuecomment-696963505,https://api.github.com/repos/pydata/xarray/issues/4431,696963505,MDEyOklzc3VlQ29tbWVudDY5Njk2MzUwNQ==,221526,2020-09-22T20:32:28Z,2020-09-22T20:32:28Z,CONTRIBUTOR,"@alexamici Force-pushing doesn't normally close it, so this is weird...","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,703550109
https://github.com/pydata/xarray/issues/4422#issuecomment-696954231,https://api.github.com/repos/pydata/xarray/issues/4422,696954231,MDEyOklzc3VlQ29tbWVudDY5Njk1NDIzMQ==,221526,2020-09-22T20:13:50Z,2020-09-22T20:13:50Z,CONTRIBUTOR,"I'd say in the case of `use_ctime=True` that it's a bug that it ever uses pandas for date parsing.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,701062999
https://github.com/pydata/xarray/issues/4422#issuecomment-696508013,https://api.github.com/repos/pydata/xarray/issues/4422,696508013,MDEyOklzc3VlQ29tbWVudDY5NjUwODAxMw==,221526,2020-09-22T04:56:17Z,2020-09-22T04:56:17Z,CONTRIBUTOR,"Probably shouldn't raise an error for `1-1-1` since that's valid according to the [Climate and Forecasting netCDF conventions](http://cfconventions.org/Data/cf-conventions/cf-conventions-1.8/cf-conventions.html#time-coordinate) (see examples 4.5 and 4.6). In fact, it works perfectly when using `use_cftime=True` both for the original data and reading in the data from disk.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,701062999
https://github.com/pydata/xarray/issues/4394#issuecomment-684068427,https://api.github.com/repos/pydata/xarray/issues/4394,684068427,MDEyOklzc3VlQ29tbWVudDY4NDA2ODQyNw==,221526,2020-08-31T22:08:56Z,2020-08-31T22:08:56Z,CONTRIBUTOR,Duplicate of #1672?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,689390592
https://github.com/pydata/xarray/issues/4370#issuecomment-678819159,https://api.github.com/repos/pydata/xarray/issues/4370,678819159,MDEyOklzc3VlQ29tbWVudDY3ODgxOTE1OQ==,221526,2020-08-23T20:12:14Z,2020-08-23T20:12:14Z,CONTRIBUTOR,Likely duplicate of #4283 .,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,684248425
https://github.com/pydata/xarray/pull/4332#issuecomment-671691540,https://api.github.com/repos/pydata/xarray/issues/4332,671691540,MDEyOklzc3VlQ29tbWVudDY3MTY5MTU0MA==,221526,2020-08-11T02:42:41Z,2020-08-11T02:42:41Z,CONTRIBUTOR,Packaging for `sphinx-autosummary-accessors` looks good to me. I think the build failure is for sphinx 3.2 warnings and not the extension.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,676497373
https://github.com/pydata/xarray/issues/4313#issuecomment-669666848,https://api.github.com/repos/pydata/xarray/issues/4313,669666848,MDEyOklzc3VlQ29tbWVudDY2OTY2Njg0OA==,221526,2020-08-06T03:49:34Z,2020-08-06T03:49:34Z,CONTRIBUTOR,"So to be clear, `conda` can use the `--file` argument to read those files and treat them as if they were dependency requirements passed on the command line. Not *quite* the same as an `environment.yml`, but I haven't had any problems so far. It's been really nice since dependabot doesn't understand the environment files.
So you can point dependabot to a directory, where for pypi it looks for files ending in `.txt`. You can make a subset by using a directory, or on MetPy we've remove the `.txt` from files we don't want dependabot to update. It feels like a bit of a hack, but it works.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,673682661
https://github.com/pydata/xarray/issues/4313#issuecomment-669502001,https://api.github.com/repos/pydata/xarray/issues/4313,669502001,MDEyOklzc3VlQ29tbWVudDY2OTUwMjAwMQ==,221526,2020-08-05T20:52:33Z,2020-08-05T20:52:33Z,CONTRIBUTOR,"So on MetPy we moved to treating our CI system as an application and pinning every direct dependency in a requirements.txt (which can be used by conda as well). We then let dependabot handle the updates. This let's us manage the updates on a package-by-package basis, where we have a single PR that lets us see what the ramifications are with regards to tests, CI, even linting.
We've been running for a limited time, but so far it has done a good job of insulating general development (coming in on PRs) from changes in the environment, which now shouldn't change on CI from run to run (yeah, yeah 2nd-order dependencies, just pin problematic ones too). For instance, for the pandas 1.1.0 breakage, we just haven't merged the PR that moves the pin there, and that has kept our doc builds green on MetPy.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,673682661
https://github.com/pydata/xarray/issues/4295#issuecomment-668891516,https://api.github.com/repos/pydata/xarray/issues/4295,668891516,MDEyOklzc3VlQ29tbWVudDY2ODg5MTUxNg==,221526,2020-08-05T00:07:38Z,2020-08-05T00:07:38Z,CONTRIBUTOR,"*cough* Solving the ""setuptools won't work in `setup_requires` because it's too late"" was basically the entire driving force of `pyproject.toml`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,671019427
https://github.com/pydata/xarray/issues/4295#issuecomment-668405710,https://api.github.com/repos/pydata/xarray/issues/4295,668405710,MDEyOklzc3VlQ29tbWVudDY2ODQwNTcxMA==,221526,2020-08-04T06:27:20Z,2020-08-04T06:27:20Z,CONTRIBUTOR,Wow...two years for `pip` to gain support...I would not have expected that.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,671019427
https://github.com/pydata/xarray/issues/4295#issuecomment-668395780,https://api.github.com/repos/pydata/xarray/issues/4295,668395780,MDEyOklzc3VlQ29tbWVudDY2ODM5NTc4MA==,221526,2020-08-04T05:56:44Z,2020-08-04T05:56:44Z,CONTRIBUTOR,"I'm not here to argue, but `pyproject.toml` was introduced in [PEP-518](https://www.python.org/dev/peps/pep-0518/), which was accepted over 4 years ago. I know packaging moves slowly but I'm curious how long something has to be around before becoming ""established"" and ceases to be ""novel"". 😉","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,671019427
https://github.com/pydata/xarray/issues/4295#issuecomment-667581142,https://api.github.com/repos/pydata/xarray/issues/4295,667581142,MDEyOklzc3VlQ29tbWVudDY2NzU4MTE0Mg==,221526,2020-08-01T20:10:55Z,2020-08-01T20:10:55Z,CONTRIBUTOR,"Rolling window seems fine to me. I will say that I don't generally bother bumping that on other projects until we run into an issue/new feature that necessitates it, though.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,671019427
https://github.com/pydata/xarray/issues/4287#issuecomment-666714053,https://api.github.com/repos/pydata/xarray/issues/4287,666714053,MDEyOklzc3VlQ29tbWVudDY2NjcxNDA1Mw==,221526,2020-07-30T21:27:14Z,2020-07-30T21:27:14Z,CONTRIBUTOR,The exception looks like the identical problem as #4283 .,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,668166816
https://github.com/pydata/xarray/issues/4283#issuecomment-665435320,https://api.github.com/repos/pydata/xarray/issues/4283,665435320,MDEyOklzc3VlQ29tbWVudDY2NTQzNTMyMA==,221526,2020-07-29T05:13:27Z,2020-07-29T05:13:27Z,CONTRIBUTOR,"Looks like (to my eye anyway) it stems from:
```python
import numpy as np
import pandas as pd
t = np.array(['2017-09-05T12:00:00.000000000', '2017-09-05T15:00:00.000000000'], dtype='datetime64[ns]')
index = pd.DatetimeIndex(t)
index.get_loc(t[0].item()) # Fails with KeyError
index.get_loc(t[0]) # Works
```
Fails on 1.1.0. What I have no idea is whether the `.item()` call is supposed to work. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,667550022
https://github.com/pydata/xarray/issues/4043#issuecomment-657136785,https://api.github.com/repos/pydata/xarray/issues/4043,657136785,MDEyOklzc3VlQ29tbWVudDY1NzEzNjc4NQ==,221526,2020-07-11T22:01:55Z,2020-07-11T22:01:55Z,CONTRIBUTOR,Probably worth raising upstream with the THREDDS team. I do wonder if there's some issues with the chunking/compression of the native .nc files that's at play here.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,614144170
https://github.com/pydata/xarray/issues/4208#issuecomment-657135521,https://api.github.com/repos/pydata/xarray/issues/4208,657135521,MDEyOklzc3VlQ29tbWVudDY1NzEzNTUyMQ==,221526,2020-07-11T21:49:36Z,2020-07-11T21:49:54Z,CONTRIBUTOR,Does/should any of this also consider #4212 (CuPy)?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,653430454
https://github.com/pydata/xarray/issues/4212#issuecomment-657135369,https://api.github.com/repos/pydata/xarray/issues/4212,657135369,MDEyOklzc3VlQ29tbWVudDY1NzEzNTM2OQ==,221526,2020-07-11T21:48:17Z,2020-07-11T21:48:17Z,CONTRIBUTOR,@jacobtomlinson Any idea how this would play with the work that's been going on for units here; I'm specifically wondering if xarray ( pint ( cupy )) would/could work.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,654135405
https://github.com/pydata/xarray/pull/3998#issuecomment-618815341,https://api.github.com/repos/pydata/xarray/issues/3998,618815341,MDEyOklzc3VlQ29tbWVudDYxODgxNTM0MQ==,221526,2020-04-24T05:50:33Z,2020-04-24T05:50:33Z,CONTRIBUTOR,"Ah, didn't realize bug fixes went in there too. And I *thought* I could get away without black, but I missed the quote style. All done.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,605920781
https://github.com/pydata/xarray/pull/3998#issuecomment-618709181,https://api.github.com/repos/pydata/xarray/issues/3998,618709181,MDEyOklzc3VlQ29tbWVudDYxODcwOTE4MQ==,221526,2020-04-23T22:44:21Z,2020-04-23T22:44:21Z,CONTRIBUTOR,cc @dcamron,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,605920781
https://github.com/pydata/xarray/pull/2844#issuecomment-597883721,https://api.github.com/repos/pydata/xarray/issues/2844,597883721,MDEyOklzc3VlQ29tbWVudDU5Nzg4MzcyMQ==,221526,2020-03-11T21:19:31Z,2020-03-11T21:19:31Z,CONTRIBUTOR,"Thanks for the info. Based on that, I lean towards `attrs`.
I think a better rationale, though, would be to formalize the role of `encoding` in xarray.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,424265093
https://github.com/pydata/xarray/pull/2844#issuecomment-597374274,https://api.github.com/repos/pydata/xarray/issues/2844,597374274,MDEyOklzc3VlQ29tbWVudDU5NzM3NDI3NA==,221526,2020-03-10T23:47:43Z,2020-03-10T23:47:43Z,CONTRIBUTOR,"As a downstream user, I just want to be told what to do (assuming `encoding` is part of the public API for xarray). I'd love not to have to modify our code, but that's not essential necessarily.
So to clarify: is this about whether they should be in one spot or the other? Or is it about having `grid_mapping` and `bounds` in both?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,424265093
https://github.com/pydata/xarray/issues/3653#issuecomment-570089112,https://api.github.com/repos/pydata/xarray/issues/3653,570089112,MDEyOklzc3VlQ29tbWVudDU3MDA4OTExMg==,221526,2020-01-01T22:34:46Z,2020-01-01T22:34:46Z,CONTRIBUTOR,"This isn't accessing netCDF using opendap, it's directly accessing using HTTP. Did xarray or netCDF gain support for this and I failed to notice?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,543197350
https://github.com/pydata/xarray/issues/3256#issuecomment-565183733,https://api.github.com/repos/pydata/xarray/issues/3256,565183733,MDEyOklzc3VlQ29tbWVudDU2NTE4MzczMw==,221526,2019-12-12T20:57:56Z,2019-12-12T20:57:56Z,CONTRIBUTOR,"Yeah, it's not much shorter, but it's a much easier concept for new users to grasp, IMO.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484699415
https://github.com/pydata/xarray/issues/3256#issuecomment-563511116,https://api.github.com/repos/pydata/xarray/issues/3256,563511116,MDEyOklzc3VlQ29tbWVudDU2MzUxMTExNg==,221526,2019-12-10T01:00:00Z,2019-12-10T01:00:00Z,CONTRIBUTOR,"Well it'd be nice to have something, because what we have to do right now is:
```python
times[0].values.astype('datetime64[ms]').astype('O')
```
which is an abomination and terrible for teaching.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484699415
https://github.com/pydata/xarray/pull/3537#issuecomment-554457858,https://api.github.com/repos/pydata/xarray/issues/3537,554457858,MDEyOklzc3VlQ29tbWVudDU1NDQ1Nzg1OA==,221526,2019-11-15T17:41:52Z,2019-11-15T19:02:03Z,CONTRIBUTOR,"IMO, it's always best to release code that you *know* will work rather than rely on upstream to get something into the next release in order for you not to be broken. I say that both as a downstream user of xarray and a library maintainer.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,523438384
https://github.com/pydata/xarray/pull/3111#issuecomment-547592948,https://api.github.com/repos/pydata/xarray/issues/3111,547592948,MDEyOklzc3VlQ29tbWVudDU0NzU5Mjk0OA==,221526,2019-10-29T19:33:20Z,2019-10-29T19:33:20Z,CONTRIBUTOR,I just got it to render fine--I blame general GitHub flakiness around notebooks lately.,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,467746047
https://github.com/pydata/xarray/pull/3367#issuecomment-538684049,https://api.github.com/repos/pydata/xarray/issues/3367,538684049,MDEyOklzc3VlQ29tbWVudDUzODY4NDA0OQ==,221526,2019-10-05T20:05:58Z,2019-10-05T20:05:58Z,CONTRIBUTOR,"All good, thanks.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,501730864
https://github.com/pydata/xarray/pull/3367#issuecomment-537694464,https://api.github.com/repos/pydata/xarray/issues/3367,537694464,MDEyOklzc3VlQ29tbWVudDUzNzY5NDQ2NA==,221526,2019-10-02T21:44:03Z,2019-10-02T21:44:03Z,CONTRIBUTOR,"You don’t run into a problem when doing `pip install xarray` on Python 2. We have run into problems on our CI builds where we install from our own cache on S3, which has a list of wheels in index.html, which we install from using `pip install -f xarray`. When we have an xarray wheel in there with the incorrect name, python 2.7 tries to install from it.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,501730864
https://github.com/pydata/xarray/issues/3257#issuecomment-525441141,https://api.github.com/repos/pydata/xarray/issues/3257,525441141,MDEyOklzc3VlQ29tbWVudDUyNTQ0MTE0MQ==,221526,2019-08-27T19:06:42Z,2019-08-27T19:06:42Z,CONTRIBUTOR,"On Travis I have some deploy hooks:
1. Using Travis' built-in PyPI support, it uploads wheels and sdist, only on tags
2. Execute a custom script to commit built docs to github pages (not RTD). On master builds, this updates dev docs. On a tag, it adds a new directory for that version of the docs.
[Travis Config](https://github.com/Unidata/MetPy/blob/master/.travis.yml)
[Doc Deploy Script](https://github.com/Unidata/MetPy/blob/master/ci/deploy_docs.sh)","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 1, ""rocket"": 0, ""eyes"": 0}",,484711431
https://github.com/pydata/xarray/issues/3257#issuecomment-525405541,https://api.github.com/repos/pydata/xarray/issues/3257,525405541,MDEyOklzc3VlQ29tbWVudDUyNTQwNTU0MQ==,221526,2019-08-27T17:34:55Z,2019-08-27T17:34:55Z,CONTRIBUTOR,"The benefit to automation also makes it easier to distribute the workload to other people, helping with project sustainability. On my projects, I find it very nice that I make a new release on GitHub and packages appear on PyPI and the web docs are automatically updated to the new version.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484711431
https://github.com/pydata/xarray/issues/3268#issuecomment-525404631,https://api.github.com/repos/pydata/xarray/issues/3268,525404631,MDEyOklzc3VlQ29tbWVudDUyNTQwNDYzMQ==,221526,2019-08-27T17:32:32Z,2019-08-27T17:32:32Z,CONTRIBUTOR,I don't mind needing to update our accessor code. My only request is don't have a version that suddenly breaks it so that we only work on the old version or the new version. 😉 ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,485708282
https://github.com/pydata/xarray/pull/3247#issuecomment-524400034,https://api.github.com/repos/pydata/xarray/issues/3247,524400034,MDEyOklzc3VlQ29tbWVudDUyNDQwMDAzNA==,221526,2019-08-23T17:35:49Z,2019-08-23T17:35:49Z,CONTRIBUTOR,cc: @jthielen Might make some things in MetPy easier...,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484243962
https://github.com/pydata/xarray/pull/2956#issuecomment-523228118,https://api.github.com/repos/pydata/xarray/issues/2956,523228118,MDEyOklzc3VlQ29tbWVudDUyMzIyODExOA==,221526,2019-08-20T23:02:38Z,2019-08-20T23:02:38Z,CONTRIBUTOR,"Yeah, `pint` doesn't do `__array_function__` yet. It'd be great to get this is, if for only that it lowers the barrier to make sure xarray works with pint in the future.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,443157666
https://github.com/pydata/xarray/issues/2871#issuecomment-499921424,https://api.github.com/repos/pydata/xarray/issues/2871,499921424,MDEyOklzc3VlQ29tbWVudDQ5OTkyMTQyNA==,221526,2019-06-07T15:06:29Z,2019-06-07T15:06:29Z,CONTRIBUTOR,"Just to correct something here, `missing_value` is no longer considered deprecated in the current version of the standard: http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/cf-conventions.html
Near the bottom is a specific note about removing the deprecation.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,429914958
https://github.com/pydata/xarray/issues/2419#issuecomment-499699528,https://api.github.com/repos/pydata/xarray/issues/2419,499699528,MDEyOklzc3VlQ29tbWVudDQ5OTY5OTUyOA==,221526,2019-06-06T23:04:11Z,2019-06-06T23:04:11Z,CONTRIBUTOR,"So I ran into this working with a climate scientist the other day. The use case we had was given some model output that had data like:
```
[106831872 values with dtype=float32]
Coordinates:
* lat (lat) float32 -90.0 -89.057594 -88.11518 ... 89.057594 90.0
* lon (lon) float32 0.0 1.25 2.5 3.75 5.0 ... 355.0 356.25 357.5 358.75
* time (time) object 1850-02-01 00:00:00 ... 2011-01-01 00:00:00
```
we wanted to reshape to turn time into two dimensions (""year"", ""month""). This was to facilitate looking at the `max` and `min` as a function of ""month"", take the difference, and then average over ""year"". Is there a way to do this already that I'm not aware of?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,361237908
https://github.com/pydata/xarray/pull/2989#issuecomment-497885383,https://api.github.com/repos/pydata/xarray/issues/2989,497885383,MDEyOklzc3VlQ29tbWVudDQ5Nzg4NTM4Mw==,221526,2019-05-31T23:04:03Z,2019-05-31T23:04:03Z,CONTRIBUTOR,Thanks for bringing this to the 🏁 @abrammer !,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,448330247
https://github.com/pydata/xarray/pull/2144#issuecomment-495770271,https://api.github.com/repos/pydata/xarray/issues/2144,495770271,MDEyOklzc3VlQ29tbWVudDQ5NTc3MDI3MQ==,221526,2019-05-24T19:56:21Z,2019-05-24T19:56:21Z,CONTRIBUTOR,"So I finally have time to work on this...but if someone has working code to do this instead, I'm totally fine with that going in instead.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,323823894
https://github.com/pydata/xarray/issues/2697#issuecomment-484758877,https://api.github.com/repos/pydata/xarray/issues/2697,484758877,MDEyOklzc3VlQ29tbWVudDQ4NDc1ODg3Nw==,221526,2019-04-19T03:47:37Z,2019-04-19T03:47:37Z,CONTRIBUTOR,"I haven't had any time to start on this (and I'm a few more weeks out), so feel free to take a cut. I'm not sure what @shoyer or @rabernat have in mind for API.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,401874795
https://github.com/pydata/xarray/issues/525#issuecomment-483799967,https://api.github.com/repos/pydata/xarray/issues/525,483799967,MDEyOklzc3VlQ29tbWVudDQ4Mzc5OTk2Nw==,221526,2019-04-16T18:54:37Z,2019-04-16T18:54:37Z,CONTRIBUTOR,"@shoyer I agree with that wrapping order. I think I'd also be in favor of starting with an experiment to disable coercing to arrays.
@nbren12 The non-communicative multiplication is a consequence of operator dispatch in Python, and the reason why we want `__array_function__` from numpy. Your first example dispatches to `dask.array.__mul__`, which doesn't know anything about pint and doesn't know how to compose its operations because there are no hooks--the pint array just gets coerced to a numpy array. The second goes to `pint.Quantity.__mul__`, which assumes it can wrap the `dask.array` (because it duck typing) and seems to succeed in doing so.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,100295585
https://github.com/pydata/xarray/issues/2656#issuecomment-454179986,https://api.github.com/repos/pydata/xarray/issues/2656,454179986,MDEyOklzc3VlQ29tbWVudDQ1NDE3OTk4Ng==,221526,2019-01-14T22:07:19Z,2019-01-14T22:07:19Z,CONTRIBUTOR,"I'm not aware of any standard out there for JSON representation of netCDF, but I know it's been at least (briefly) discussed. @WardF, anything out there you're aware of?
Another spelling of this could be `ds.to_dict(header_only=True)`, which I only suggest to mirror `ncdump -h`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,396285440
https://github.com/pydata/xarray/issues/2583#issuecomment-443908495,https://api.github.com/repos/pydata/xarray/issues/2583,443908495,MDEyOklzc3VlQ29tbWVudDQ0MzkwODQ5NQ==,221526,2018-12-03T23:20:29Z,2018-12-03T23:20:29Z,CONTRIBUTOR,@lesserwhirls @dennisHeimbigner Is there any reason to expect a difference between the downloaded file and the opendap view on TDS?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,386268842
https://github.com/pydata/xarray/issues/2503#issuecomment-432747410,https://api.github.com/repos/pydata/xarray/issues/2503,432747410,MDEyOklzc3VlQ29tbWVudDQzMjc0NzQxMA==,221526,2018-10-24T17:13:14Z,2018-10-24T17:13:14Z,CONTRIBUTOR,"Oh, I didn't even catch that the original was on defaults.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 1, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,373121666
https://github.com/pydata/xarray/issues/2503#issuecomment-432744441,https://api.github.com/repos/pydata/xarray/issues/2503,432744441,MDEyOklzc3VlQ29tbWVudDQzMjc0NDQ0MQ==,221526,2018-10-24T17:06:01Z,2018-10-24T17:06:01Z,CONTRIBUTOR,That version has the fix for the issue.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,373121666
https://github.com/pydata/xarray/issues/2503#issuecomment-432739449,https://api.github.com/repos/pydata/xarray/issues/2503,432739449,MDEyOklzc3VlQ29tbWVudDQzMjczOTQ0OQ==,221526,2018-10-24T16:54:05Z,2018-10-24T16:54:05Z,CONTRIBUTOR,"The original version of libnetcdf in @rabernat 's environment definitely had the opendap timeout issue. Not sure if that's the root cause of the problem, or not, but it's suspect.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,373121666
https://github.com/pydata/xarray/issues/2503#issuecomment-432422763,https://api.github.com/repos/pydata/xarray/issues/2503,432422763,MDEyOklzc3VlQ29tbWVudDQzMjQyMjc2Mw==,221526,2018-10-23T21:16:05Z,2018-10-23T21:16:16Z,CONTRIBUTOR,"@lesserwhirls That's an interesting idea. (@rsignell-usgs That's the one.)
@rabernat What version of the conda-forge libnetcdf package is deployed wherever you're running?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,373121666
https://github.com/pydata/xarray/issues/2503#issuecomment-432370887,https://api.github.com/repos/pydata/xarray/issues/2503,432370887,MDEyOklzc3VlQ29tbWVudDQzMjM3MDg4Nw==,221526,2018-10-23T18:43:23Z,2018-10-23T18:43:23Z,CONTRIBUTOR,"Just so I'm clear on how the workflow looks:
1. Open dataset with NetCDF/OPeNDAP
2. Serialize NetCDFDataStore (pickle? netcdf file?)
3. Ship to Dask workers
4. Reconstitute NetCDFDataStore
Certainly does seem like there's something stale in what the remote workers are getting. Confused why it works for the others, though.
I can prioritize this a bit and dig in to see what I can figure out--though I'm teaching through tomorrow. May be able to dig into this while at ECMWF.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,373121666
https://github.com/pydata/xarray/pull/2144#issuecomment-424100432,https://api.github.com/repos/pydata/xarray/issues/2144,424100432,MDEyOklzc3VlQ29tbWVudDQyNDEwMDQzMg==,221526,2018-09-24T19:44:21Z,2018-09-24T19:44:21Z,CONTRIBUTOR,Just haven't had the cycles to bring this to the finish line.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,323823894
https://github.com/pydata/xarray/pull/2398#issuecomment-420470343,https://api.github.com/repos/pydata/xarray/issues/2398,420470343,MDEyOklzc3VlQ29tbWVudDQyMDQ3MDM0Mw==,221526,2018-09-12T00:25:54Z,2018-09-12T00:25:54Z,CONTRIBUTOR,Why would you sort the array? Aren't you taking differences of values and dividing by differences between the matching coordinates?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,356698348
https://github.com/pydata/xarray/issues/2368#issuecomment-419225007,https://api.github.com/repos/pydata/xarray/issues/2368,419225007,MDEyOklzc3VlQ29tbWVudDQxOTIyNTAwNw==,221526,2018-09-06T20:10:24Z,2018-09-06T20:10:24Z,CONTRIBUTOR,"That sounds reasonable to me. I don't necessarily expect all of the xarray goodness to work with those files, but I do expect them to open without error.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,350899839
https://github.com/pydata/xarray/issues/2368#issuecomment-419176628,https://api.github.com/repos/pydata/xarray/issues/2368,419176628,MDEyOklzc3VlQ29tbWVudDQxOTE3NjYyOA==,221526,2018-09-06T17:28:14Z,2018-09-06T17:28:14Z,CONTRIBUTOR,"@rabernat While I agree that they're (somewhat) confusing files, I think you're missing two things:
1. netCDF doesn't enforce naming on dimensions and variables. Full stop. The only naming netCDF will care about is any conflict with an internal reserved name (I'm not sure that those even exist for anything besides attributes.) IMO that's a good thing, but more importantly it's not the netCDF library's job to enforce any of it.
2. CF is an attribute convention. This also means that the conventions say absolutely nothing about naming of variables and dimensions.
IMO, xarray is being overly pedantic here. XArray states that it adopts the Common Data Model (CDM); netCDF-java and the CDM were the tools used to generate the failing examples above.","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,350899839
https://github.com/pydata/xarray/issues/988#issuecomment-413723632,https://api.github.com/repos/pydata/xarray/issues/988,413723632,MDEyOklzc3VlQ29tbWVudDQxMzcyMzYzMg==,221526,2018-08-17T00:33:47Z,2018-08-17T00:33:47Z,CONTRIBUTOR,"I see your argument, but here's my problem. In this future where things work (assuming that NEP is accepted), and I want distributed computing with dask, units, and xarray, I have: xarray wrapping a pint array wrapping a dask array. I like composition, but that level of wrapping...feels wrong to me for some reason. Is there some elegance I'm missing here? (Other than array-like things playing together.)
And then I still need hooks in xarray so that when pint does a calculation, it can update the metadata in xarray; so it feels like we're back here anyway.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,173612265
https://github.com/pydata/xarray/issues/988#issuecomment-413360749,https://api.github.com/repos/pydata/xarray/issues/988,413360749,MDEyOklzc3VlQ29tbWVudDQxMzM2MDc0OQ==,221526,2018-08-15T22:36:21Z,2018-08-15T22:36:21Z,CONTRIBUTOR,"@shoyer I know elsewhere you said you weren't sure about this idea any more, but personally I'd like to push forward on this idea. Do you have problems with this approach we need to resolve? Any chance you have some preliminary code?
I think this is the right way to solve the unit issue in XArray, since at it's core unit handling is mostly a metadata operation. ","{""total_count"": 2, ""+1"": 2, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,173612265
https://github.com/pydata/xarray/issues/2368#issuecomment-413281638,https://api.github.com/repos/pydata/xarray/issues/2368,413281638,MDEyOklzc3VlQ29tbWVudDQxMzI4MTYzOA==,221526,2018-08-15T17:58:12Z,2018-08-15T17:58:12Z,CONTRIBUTOR,"Here's a sample CDL for a file:
```
netcdf temp {
dimensions:
profile = 1 ;
station = 1 ;
isobaric = 31 ;
station_name_strlen = 10 ;
station_description_strlen = 33 ;
variables:
float isobaric(station, profile, isobaric) ;
isobaric:standard_name = ""isobaric"" ;
isobaric:long_name = ""isobaric"" ;
isobaric:units = ""Pa"" ;
isobaric:positive = ""down"" ;
isobaric:axis = ""Z"" ;
float Geopotential_height_isobaric(station, profile, isobaric) ;
Geopotential_height_isobaric:standard_name = ""Geopotential_height_isobaric"" ;
Geopotential_height_isobaric:long_name = ""Geopotential_height_isobaric"" ;
Geopotential_height_isobaric:units = ""gpm"" ;
Geopotential_height_isobaric:coordinates = ""time longitude latitude isobaric"" ;
char station_name(station, station_name_strlen) ;
station_name:long_name = ""station name"" ;
station_name:cf_role = ""timeseries_id"" ;
char station_description(station, station_description_strlen) ;
station_description:long_name = ""station description"" ;
station_description:standard_name = ""platform_name"" ;
double latitude(station) ;
latitude:units = ""degrees_north"" ;
latitude:long_name = ""profile latitude"" ;
double longitude(station) ;
longitude:units = ""degrees_east"" ;
longitude:long_name = ""profile longitude"" ;
double time(station, profile) ;
time:units = ""Hour since 2018-08-15T12:00:00Z"" ;
time:calendar = ""proleptic_gregorian"" ;
time:standard_name = ""time"" ;
time:long_name = ""GRIB forecast or observation time"" ;
// global attributes:
:Conventions = ""CDM-Extended-CF"" ;
:history = ""Written by CFPointWriter"" ;
:title = ""Extract Points data from Grid file /data/ldm/pub/native/grid/NCEP/GFS/Global_0p5deg/GFS_Global_0p5deg_20180815_1200.grib2.ncx3#LatLon_361X720-p25S-180p0E"" ;
:featureType = ""timeSeriesProfile"" ;
:time_coverage_start = ""2018-08-15T18:00:00Z"" ;
:time_coverage_end = ""2018-08-15T18:00:00Z"" ;
:geospatial_lat_min = 39.9995 ;
:geospatial_lat_max = 40.0005 ;
:geospatial_lon_min = -105.0005 ;
:geospatial_lon_max = -104.9995 ;
}
```
which gives:
```pytb
---------------------------------------------------------------------------
MissingDimensionsError Traceback (most recent call last)
in ()
4 query.add_lonlat().accept('netcdf4')
5 nc = ncss.get_data(query)
----> 6 xr.open_dataset(NetCDF4DataStore(nc))
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, autoclose, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables, backend_kwargs)
352 store = backends.ScipyDataStore(filename_or_obj)
353
--> 354 return maybe_decode_store(store)
355
356
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in maybe_decode_store(store, lock)
256 store, mask_and_scale=mask_and_scale, decode_times=decode_times,
257 concat_characters=concat_characters, decode_coords=decode_coords,
--> 258 drop_variables=drop_variables)
259
260 _protect_dataset_variables_inplace(ds, cache)
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables)
428 vars, attrs, concat_characters, mask_and_scale, decode_times,
429 decode_coords, drop_variables=drop_variables)
--> 430 ds = Dataset(vars, attrs=attrs)
431 ds = ds.set_coords(coord_names.union(extra_coords).intersection(vars))
432 ds._file_obj = file_obj
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in __init__(self, data_vars, coords, attrs, compat)
363 coords = {}
364 if data_vars is not None or coords is not None:
--> 365 self._set_init_vars_and_dims(data_vars, coords, compat)
366 if attrs is not None:
367 self.attrs = attrs
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in _set_init_vars_and_dims(self, data_vars, coords, compat)
381
382 variables, coord_names, dims = merge_data_and_coords(
--> 383 data_vars, coords, compat=compat)
384
385 self._variables = variables
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_data_and_coords(data, coords, compat, join)
363 indexes = dict(extract_indexes(coords))
364 return merge_core(objs, compat, join, explicit_coords=explicit_coords,
--> 365 indexes=indexes)
366
367
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_core(objs, compat, join, priority_arg, explicit_coords, indexes)
433 coerced = coerce_pandas_values(objs)
434 aligned = deep_align(coerced, join=join, copy=False, indexes=indexes)
--> 435 expanded = expand_variable_dicts(aligned)
436
437 coord_names, noncoord_names = determine_coords(coerced)
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in expand_variable_dicts(list_of_variable_dicts)
209 var_dicts.append(coords)
210
--> 211 var = as_variable(var, name=name)
212 sanitized_vars[name] = var
213
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/variable.py in as_variable(obj, name)
112 'dimensions %r. xarray disallows such variables because they '
113 'conflict with the coordinates used to label '
--> 114 'dimensions.' % (name, obj.dims))
115 obj = obj.to_index_variable()
116
MissingDimensionsError: 'isobaric' has more than 1-dimension and the same name as one of its dimensions ('station', 'profile', 'isobaric'). xarray disallows such variables because they conflict with the coordinates used to label dimensions.
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,350899839
https://github.com/pydata/xarray/issues/2368#issuecomment-413279893,https://api.github.com/repos/pydata/xarray/issues/2368,413279893,MDEyOklzc3VlQ29tbWVudDQxMzI3OTg5Mw==,221526,2018-08-15T17:52:36Z,2018-08-15T17:52:36Z,CONTRIBUTOR,"```python
import xarray as xr
xr.open_dataset('http://thredds.ucar.edu/thredds/dodsC/grib/NCEP/GFS/Global_0p5deg/TwoD')
```
```pytb
---------------------------------------------------------------------------
MissingDimensionsError Traceback (most recent call last)
in ()
----> 1 xr.open_dataset(gfs_cat.datasets[0].access_urls['OPENDAP'])
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, autoclose, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables, backend_kwargs)
344 lock = _default_lock(filename_or_obj, engine)
345 with close_on_error(store):
--> 346 return maybe_decode_store(store, lock)
347 else:
348 if engine is not None and engine != 'scipy':
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in maybe_decode_store(store, lock)
256 store, mask_and_scale=mask_and_scale, decode_times=decode_times,
257 concat_characters=concat_characters, decode_coords=decode_coords,
--> 258 drop_variables=drop_variables)
259
260 _protect_dataset_variables_inplace(ds, cache)
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables)
428 vars, attrs, concat_characters, mask_and_scale, decode_times,
429 decode_coords, drop_variables=drop_variables)
--> 430 ds = Dataset(vars, attrs=attrs)
431 ds = ds.set_coords(coord_names.union(extra_coords).intersection(vars))
432 ds._file_obj = file_obj
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in __init__(self, data_vars, coords, attrs, compat)
363 coords = {}
364 if data_vars is not None or coords is not None:
--> 365 self._set_init_vars_and_dims(data_vars, coords, compat)
366 if attrs is not None:
367 self.attrs = attrs
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in _set_init_vars_and_dims(self, data_vars, coords, compat)
381
382 variables, coord_names, dims = merge_data_and_coords(
--> 383 data_vars, coords, compat=compat)
384
385 self._variables = variables
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_data_and_coords(data, coords, compat, join)
363 indexes = dict(extract_indexes(coords))
364 return merge_core(objs, compat, join, explicit_coords=explicit_coords,
--> 365 indexes=indexes)
366
367
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_core(objs, compat, join, priority_arg, explicit_coords, indexes)
433 coerced = coerce_pandas_values(objs)
434 aligned = deep_align(coerced, join=join, copy=False, indexes=indexes)
--> 435 expanded = expand_variable_dicts(aligned)
436
437 coord_names, noncoord_names = determine_coords(coerced)
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in expand_variable_dicts(list_of_variable_dicts)
209 var_dicts.append(coords)
210
--> 211 var = as_variable(var, name=name)
212 sanitized_vars[name] = var
213
~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/variable.py in as_variable(obj, name)
112 'dimensions %r. xarray disallows such variables because they '
113 'conflict with the coordinates used to label '
--> 114 'dimensions.' % (name, obj.dims))
115 obj = obj.to_index_variable()
116
MissingDimensionsError: 'time' has more than 1-dimension and the same name as one of its dimensions ('reftime', 'time'). xarray disallows such variables because they conflict with the coordinates used to label dimensions.
```","{""total_count"": 5, ""+1"": 5, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,350899839
https://github.com/pydata/xarray/issues/2304#issuecomment-410782982,https://api.github.com/repos/pydata/xarray/issues/2304,410782982,MDEyOklzc3VlQ29tbWVudDQxMDc4Mjk4Mg==,221526,2018-08-06T17:17:38Z,2018-08-06T17:17:38Z,CONTRIBUTOR,"Ah, ok, not scaling per-se (i.e. `* 0.01`), but a second round of value conversion. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,343659822
https://github.com/pydata/xarray/issues/2304#issuecomment-410779271,https://api.github.com/repos/pydata/xarray/issues/2304,410779271,MDEyOklzc3VlQ29tbWVudDQxMDc3OTI3MQ==,221526,2018-08-06T17:06:22Z,2018-08-06T17:06:22Z,CONTRIBUTOR,"I'm not following why the data are scaled twice.
Your point about the rounding being different is well-taken, though.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,343659822
https://github.com/pydata/xarray/issues/2304#issuecomment-410774955,https://api.github.com/repos/pydata/xarray/issues/2304,410774955,MDEyOklzc3VlQ29tbWVudDQxMDc3NDk1NQ==,221526,2018-08-06T16:52:42Z,2018-08-06T16:52:53Z,CONTRIBUTOR,"@shoyer But since it's a downstream calculation issue, and does not impact the actual precision of what's being read from the file, what's wrong with saying ""Use `data.astype(np.float64)`"". It's completely identical to doing it internally to xarray.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,343659822
https://github.com/pydata/xarray/issues/2304#issuecomment-410769706,https://api.github.com/repos/pydata/xarray/issues/2304,410769706,MDEyOklzc3VlQ29tbWVudDQxMDc2OTcwNg==,221526,2018-08-06T16:34:44Z,2018-08-06T16:36:16Z,CONTRIBUTOR,"A float32 values has 24 bits of precision in the significand, which is more than enough to store the 16-bits in in the original data; the exponent (8 bits) will more or less take care of the `* 0.01`:
```python
>>> import numpy as np
>>> np.float32(2194 * 0.01)
21.94
```
What you're seeing is an artifact of printing out the values. I have no idea why something is printing out a float (only 7 decimal digits) out to 17 digits. Even float64 only has 16 digits (which is overkill for this application).
The difference in subtracting the 32- and 64-bit values above are in the 8th decimal place, which is beyond the actual precision of the data; what you've just demonstrated is the difference in precision between 32-bit and 64-bit values, but it had nothing to do whatsoever with the data.
If you're really worried about precision round-off for things like std. dev, you should probably calculate it using the raw integer values and scale afterwards. (I don't actually think this is necessary, though.)","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,343659822
https://github.com/pydata/xarray/issues/2176#issuecomment-391783509,https://api.github.com/repos/pydata/xarray/issues/2176,391783509,MDEyOklzc3VlQ29tbWVudDM5MTc4MzUwOQ==,221526,2018-05-24T16:47:20Z,2018-05-24T16:47:20Z,CONTRIBUTOR,"My problem with custom classes (subclasses or composition) is that you will never get those from a `Dataset` that you get from `open_dataset()`. That’s a problem for me when I’m trying to make things work for users who want to do simple scripted data analysis. I’m much more interested in #1938 (or #1118).
I’m also looking at moving from pint to [unyt](https://github.com/yy-project/unyt), which is Yt’s unit support, brought into a standalone package. Beyond some performance benefits (I’ve heard), it has the benefit of being a ndarray subclass, which means `asanyarray` will leave it alone. That would seem to make it easier to cram into a `DataArray`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,325810810
https://github.com/pydata/xarray/pull/2163#issuecomment-390345890,https://api.github.com/repos/pydata/xarray/issues/2163,390345890,MDEyOklzc3VlQ29tbWVudDM5MDM0NTg5MA==,221526,2018-05-18T22:10:36Z,2018-05-18T22:10:36Z,CONTRIBUTOR,Versioneer has worked great for us. Cutting a release is triggered just by making a new release on GitHub.,"{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,324544072
https://github.com/pydata/xarray/pull/2144#issuecomment-389730062,https://api.github.com/repos/pydata/xarray/issues/2144,389730062,MDEyOklzc3VlQ29tbWVudDM4OTczMDA2Mg==,221526,2018-05-17T03:04:56Z,2018-05-17T03:04:56Z,CONTRIBUTOR,"Since this can wait for 0.10.5, I can go slowly and get this right.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,323823894
https://github.com/pydata/xarray/pull/2144#issuecomment-389699324,https://api.github.com/repos/pydata/xarray/issues/2144,389699324,MDEyOklzc3VlQ29tbWVudDM4OTY5OTMyNA==,221526,2018-05-16T23:40:32Z,2018-05-16T23:40:32Z,CONTRIBUTOR,Any chance this makes it into 0.10.4?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,323823894
https://github.com/pydata/xarray/pull/817#issuecomment-388440871,https://api.github.com/repos/pydata/xarray/issues/817,388440871,MDEyOklzc3VlQ29tbWVudDM4ODQ0MDg3MQ==,221526,2018-05-11T18:04:18Z,2018-05-11T18:04:18Z,CONTRIBUTOR,"Regarding the testing issue, another option is to use something like vcrpy to record and playback http responses for opendap requests. I've had good luck with that for Siphon.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,146079798
https://github.com/pydata/xarray/pull/2016#issuecomment-382906786,https://api.github.com/repos/pydata/xarray/issues/2016,382906786,MDEyOklzc3VlQ29tbWVudDM4MjkwNjc4Ng==,221526,2018-04-19T23:04:25Z,2018-04-19T23:04:25Z,CONTRIBUTOR,@shoyer Happy to put in a PR to address...provided you can tell me what that should actually look like. 😁 ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,308768432
https://github.com/pydata/xarray/pull/2016#issuecomment-377049291,https://api.github.com/repos/pydata/xarray/issues/2016,377049291,MDEyOklzc3VlQ29tbWVudDM3NzA0OTI5MQ==,221526,2018-03-28T21:50:46Z,2018-03-28T21:50:46Z,CONTRIBUTOR,Reworked due to corner case with PyNio on Python 2.7. Final solution looks simpler to me.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,308768432
https://github.com/pydata/xarray/pull/2016#issuecomment-377030861,https://api.github.com/repos/pydata/xarray/issues/2016,377030861,MDEyOklzc3VlQ29tbWVudDM3NzAzMDg2MQ==,221526,2018-03-28T20:47:34Z,2018-03-28T20:47:34Z,CONTRIBUTOR,Fixed flake8 (unnecessary import),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,308768432
https://github.com/pydata/xarray/pull/2016#issuecomment-376993012,https://api.github.com/repos/pydata/xarray/issues/2016,376993012,MDEyOklzc3VlQ29tbWVudDM3Njk5MzAxMg==,221526,2018-03-28T18:41:36Z,2018-03-28T18:41:36Z,CONTRIBUTOR,Rebased on current master.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,308768432
https://github.com/pydata/xarray/pull/2016#issuecomment-376352184,https://api.github.com/repos/pydata/xarray/issues/2016,376352184,MDEyOklzc3VlQ29tbWVudDM3NjM1MjE4NA==,221526,2018-03-27T00:08:47Z,2018-03-27T00:08:47Z,CONTRIBUTOR,"Test failures look unrelated--they also happen to me locally. Installing SciPy 1.0.0 locally fixes them, so I'm guessing they're caused by SciPy 1.0.1.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,308768432
https://github.com/pydata/xarray/pull/1899#issuecomment-374351614,https://api.github.com/repos/pydata/xarray/issues/1899,374351614,MDEyOklzc3VlQ29tbWVudDM3NDM1MTYxNA==,221526,2018-03-19T20:01:29Z,2018-03-19T20:01:29Z,CONTRIBUTOR,"So did this remove/rename `LazilyIndexedArray` in 0.10.2? Because I'm getting an attribute in the custom xarray backend I wrote: https://github.com/Unidata/siphon/blob/master/siphon/cdmr/xarray_support.py
I don't mind updating, but I wanted to make sure this was intentional.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,295838143
https://github.com/pydata/xarray/issues/1976#issuecomment-371888626,https://api.github.com/repos/pydata/xarray/issues/1976,371888626,MDEyOklzc3VlQ29tbWVudDM3MTg4ODYyNg==,221526,2018-03-09T17:45:35Z,2018-03-09T17:45:35Z,CONTRIBUTOR,Somehow managed to forget about an issue I was previously involved with. Lovely. Closing in favor of that issue.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,303727896
https://github.com/pydata/xarray/pull/1962#issuecomment-371681303,https://api.github.com/repos/pydata/xarray/issues/1962,371681303,MDEyOklzc3VlQ29tbWVudDM3MTY4MTMwMw==,221526,2018-03-09T01:20:03Z,2018-03-09T01:20:03Z,CONTRIBUTOR,Right. But such hooks would be sufficient to properly maintain the `units` attribute on a `DataArray` and check whether math made sense. This could use `pint` under the covers.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,302153432
https://github.com/pydata/xarray/pull/1962#issuecomment-371680160,https://api.github.com/repos/pydata/xarray/issues/1962,371680160,MDEyOklzc3VlQ29tbWVudDM3MTY4MDE2MA==,221526,2018-03-09T01:13:16Z,2018-03-09T01:13:16Z,CONTRIBUTOR,"At this point I'd be happy to have hooks that let me intercept/wrap ufunc operations, though I guess that's what #1938 is supporting in a more systematic way.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,302153432
https://github.com/pydata/xarray/pull/1962#issuecomment-371650629,https://api.github.com/repos/pydata/xarray/issues/1962,371650629,MDEyOklzc3VlQ29tbWVudDM3MTY1MDYyOQ==,221526,2018-03-08T22:43:26Z,2018-03-08T22:43:26Z,CONTRIBUTOR,This looks awesome. Thoughts on where you think units fits in here?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,302153432
https://github.com/pydata/xarray/issues/1935#issuecomment-368171446,https://api.github.com/repos/pydata/xarray/issues/1935,368171446,MDEyOklzc3VlQ29tbWVudDM2ODE3MTQ0Ng==,221526,2018-02-23T23:43:07Z,2018-02-23T23:43:07Z,CONTRIBUTOR,"@tlechauve One way or another, I'm sure @lesserwhirls would be interested to hear your thoughts on THREDDS.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,299346082
https://github.com/pydata/xarray/pull/1924#issuecomment-367778778,https://api.github.com/repos/pydata/xarray/issues/1924,367778778,MDEyOklzc3VlQ29tbWVudDM2Nzc3ODc3OA==,221526,2018-02-22T18:40:25Z,2018-02-22T18:40:25Z,CONTRIBUTOR,"I don't have much preference between the two--I picked one and it worked for me. I just fixed up the initial import cleanups by hand and didn't find the need for a tool to do so.
In my experience, having formatting errors hold up a PR hasn't been a problem. IMO, import ordering is a more important style issue than many of the things that flake8 catches.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,298437967
https://github.com/pydata/xarray/pull/1924#issuecomment-367771955,https://api.github.com/repos/pydata/xarray/issues/1924,367771955,MDEyOklzc3VlQ29tbWVudDM2Nzc3MTk1NQ==,221526,2018-02-22T18:17:27Z,2018-02-22T18:17:27Z,CONTRIBUTOR,"I recommend [flake8-import-order](https://github.com/PyCQA/flake8-import-order). If you install that plugin, then flake8 will enforce import ordering and grouping.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,298437967
https://github.com/pydata/xarray/issues/1749#issuecomment-348634874,https://api.github.com/repos/pydata/xarray/issues/1749,348634874,MDEyOklzc3VlQ29tbWVudDM0ODYzNDg3NA==,221526,2017-12-01T22:48:58Z,2017-12-01T22:48:58Z,CONTRIBUTOR,"Given the definitions of these two, as I understand them, I think it makes sense to mask both values.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,278122300