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
1233153233,PR_kwDOAMm_X843rYdt,6595,Minor Dataset.map docstr clarification,2049051,closed,0,,,1,2022-05-11T20:28:38Z,2022-05-12T18:06:51Z,2022-05-11T22:06:07Z,CONTRIBUTOR,,0,pydata/xarray/pulls/6595,"The summary line in the docstr for `Dataset.map()` says that it operates on variables in the dataset. This is a very minor update clarifying that it operates on *data* variables, as opposed to all variables (data + coord) in the Dataset.

- [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst`
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6595/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
891510053,MDExOlB1bGxSZXF1ZXN0NjQ0MzcwMjE4,5305,Fix broken Pydagogue URL,2049051,closed,0,,,1,2021-05-14T01:34:15Z,2021-05-14T06:30:30Z,2021-05-14T06:27:28Z,CONTRIBUTOR,,0,pydata/xarray/pulls/5305,"Another minor doc fix. This points Pydagogue link in contributing docs to correct URL. It was a broken link.

Thanks!","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5305/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
891503575,MDExOlB1bGxSZXF1ZXN0NjQ0MzY1MTYy,5304,Remove bad extra Returns in Dataset.drop_dims docstr,2049051,closed,0,,,1,2021-05-14T01:16:49Z,2021-05-14T01:27:25Z,2021-05-14T01:27:25Z,CONTRIBUTOR,,0,pydata/xarray/pulls/5304,"This is a minor docstr correction.

`Dataset.drop_dims` docstr said it was returning errors in golang-like way that made me double-take.

Thanks!
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/5304/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
188655510,MDExOlB1bGxSZXF1ZXN0OTMyNTg0NzM=,1107,Very minor spelling correction on dask docs,2049051,closed,0,,,1,2016-11-11T00:25:07Z,2016-11-11T00:28:46Z,2016-11-11T00:28:43Z,CONTRIBUTOR,,0,pydata/xarray/pulls/1107,,"{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1107/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
185512138,MDExOlB1bGxSZXF1ZXN0OTEwODk4NjQ=,1063,Update installing.rst to clarify and fix formatting,2049051,closed,0,,,1,2016-10-26T21:14:44Z,2016-10-27T04:38:34Z,2016-10-27T04:38:33Z,CONTRIBUTOR,,0,pydata/xarray/pulls/1063,"_Very_ minor fix to poor formatting and clarification on new conda-forge blurb on the ""Installation"" docs page. This came about from 633aa112ae03214b76a913edbf3b1f43d0e9281b which addressed #944.
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1063/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,pull
158518147,MDU6SXNzdWUxNTg1MTgxNDc=,869,open netCDF gives 'time' dim with 1969 change in timezone,2049051,closed,0,,,5,2016-06-04T18:46:38Z,2016-06-04T20:20:46Z,2016-06-04T19:47:39Z,CONTRIBUTOR,,,,"I'm on xarray version 0.7.2
netCDF4-python version 1.2.2
Python version via Conda: 3.5.1 |Continuum Analytics, Inc.| (default, Dec  7 2015, 11:16:01)  [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]

The `time` dim on Datasets read in from netCDF files seems to change timezones in 1969. This is especially a pain for annual data because the bug causes annual indexes to shift by one year. I've seen this problem in reanalysis for NCEP/NCAR, Twentieth Century Reanalysis, and some reconstructed SST fields.

For example, if a read in a netCDF file. Take NCEP/NCAR Reanalysis 1 monthly mean geopotential height as an example (ftp://ftp.cdc.noaa.gov/Datasets/ncep.reanalysis.derived/pressure/hgt.mon.mean.nc ; a 278 MB file).

``` python
import xarray as xr

ds = xr.open_dataset('~/Downloads/hgt.mon.mean.nc')
print(ds.time)
```

The interesting part of this printed time dim is always around 1969:

```
   ...
   '1969-09-01T00:00:00.000000000Z', '1969-10-01T00:00:00.000000000Z',
   '1969-11-01T00:00:00.000000000Z', '1969-12-01T00:00:00.000000000Z',
   '1969-12-31T17:00:00.000000000-0700',
   '1970-01-31T17:00:00.000000000-0700',
   '1970-02-28T17:00:00.000000000-0700',
    ...
```

You can see we go from `Z` to`-0700`. It also gives me an extra measure for Dec 1969 :-\

I don't think this is a hidden calendar or datetime-like feature that I'm unaware of...? Seems like a bug with you guys or upstream.

Thanks for your help!
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