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/6226#issuecomment-1026580368,https://api.github.com/repos/pydata/xarray/issues/6226,1026580368,IC_kwDOAMm_X849MF-Q,6063709,2022-02-01T08:19:46Z,2022-02-01T08:31:17Z,CONTRIBUTOR,"Update: It is `pandas` that is the critical package. Pinning `distributed<2022.01.0`, `xarray<0.21.0` and `cftime<1.5.2` didn't fix it, but adding `pandas<1.4.0` makes the above test pass. Will now try unpinning other packages and confirm it is `pandas` that is the issue.
Edit: Confirmed it is `pandas==1.4.0` that causes this issue. Following version combination does not produce this error:
```
INSTALLED VERSIONS
------------------
commit: None
python: 3.9.10 | packaged by conda-forge | (main, Jan 30 2022, 18:04:04)
[GCC 9.4.0]
python-bits: 64
OS: Linux
OS-release: 4.18.0-348.2.1.el8.nci.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_AU.utf8
LANG: en_AU.ISO8859-1
LOCALE: ('en_US', 'UTF-8')
libhdf5: 1.10.6
libnetcdf: 4.7.4
xarray: 0.21.0
pandas: 1.3.5
numpy: 1.22.1
scipy: 1.7.3
netCDF4: 1.5.6
pydap: installed
h5netcdf: 0.13.1
h5py: 3.6.0
Nio: None
zarr: 2.10.3
cftime: 1.5.2
nc_time_axis: 1.4.0
PseudoNetCDF: None
rasterio: 1.2.6
cfgrib: 0.9.10.0
iris: 3.1.0
bottleneck: 1.3.2
dask: 2022.01.1
distributed: 2022.01.1
matplotlib: 3.5.1
cartopy: 0.19.0.post1
seaborn: 0.11.2
numbagg: None
fsspec: 2022.01.0
cupy: 10.1.0
pint: 0.18
sparse: 0.13.0
setuptools: 59.8.0
pip: 21.3.1
conda: 4.11.0
pytest: 6.2.5
IPython: 8.0.1
sphinx: 4.4.0
```","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1120276279
https://github.com/pydata/xarray/issues/5686#issuecomment-895624119,https://api.github.com/repos/pydata/xarray/issues/5686,895624119,IC_kwDOAMm_X841YiO3,6063709,2021-08-09T23:44:10Z,2021-08-09T23:44:10Z,CONTRIBUTOR,Thanks for the super fast fix. I have confirmed this fixes #5677 ,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,963688125
https://github.com/pydata/xarray/issues/5686#issuecomment-895123758,https://api.github.com/repos/pydata/xarray/issues/5686,895123758,IC_kwDOAMm_X841WoEu,6063709,2021-08-09T10:46:57Z,2021-08-09T10:46:57Z,CONTRIBUTOR,"A colleague suggested it might be some sort of pickling issue, passing the generated object back to the main thread, but it was just speculation and I had no idea how to test that.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,963688125
https://github.com/pydata/xarray/issues/5686#issuecomment-895122645,https://api.github.com/repos/pydata/xarray/issues/5686,895122645,IC_kwDOAMm_X841WnzV,6063709,2021-08-09T10:44:42Z,2021-08-09T10:44:42Z,CONTRIBUTOR,"Thanks again for the prompt response @spencerkclark. Yes your MCVE is more (less?) M than mine. Thanks.
Perhaps I shouldn't have started a new issue, but it seemed the specific problem with `.sel` was just a knock on effect from this `cftime` issue.
I should have said in #5677 that as far as I could tell I was using `cftime=1.5.0`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,963688125
https://github.com/pydata/xarray/issues/5686#issuecomment-895120951,https://api.github.com/repos/pydata/xarray/issues/5686,895120951,IC_kwDOAMm_X841WnY3,6063709,2021-08-09T10:41:18Z,2021-08-09T10:41:18Z,CONTRIBUTOR,"> Thanks for the updated report! Could you kindly share the full error traceback?
Sorry, see below
```python
Traceback (most recent call last):
File ""/g/data/v45/aph502/helpdesk/fromgithub/20210804-Navid/mcve.py"", line 28, in <module>
assert (index_microseconds == xr.open_mfdataset('2???.nc', parallel=True).xindexes['time'].array.asi8).all()
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/xarray/coding/cftimeindex.py"", line 683, in asi8
[
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/xarray/coding/cftimeindex.py"", line 684, in <listcomp>
_total_microseconds(exact_cftime_datetime_difference(epoch, date))
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-21.07/lib/python3.9/site-packages/xarray/core/resample_cftime.py"", line 358, in exact_cftime_datetime_difference
seconds = b.replace(microsecond=0) - a.replace(microsecond=0)
File ""src/cftime/_cftime.pyx"", line 1369, in cftime._cftime.datetime.__sub__
TypeError: cannot compute the time difference between dates with different calendars
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,963688125
https://github.com/pydata/xarray/issues/5677#issuecomment-894981650,https://api.github.com/repos/pydata/xarray/issues/5677,894981650,IC_kwDOAMm_X841WFYS,6063709,2021-08-09T06:30:26Z,2021-08-09T06:30:26Z,CONTRIBUTOR,"Thanks for the very prompt response @spencerkclark, the weekend intervened but I have since narrowed it down further so have submitted a new issue
https://github.com/pydata/xarray/issues/5686
Will close this one.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,962467654
https://github.com/pydata/xarray/issues/4337#issuecomment-673840314,https://api.github.com/repos/pydata/xarray/issues/4337,673840314,MDEyOklzc3VlQ29tbWVudDY3Mzg0MDMxNA==,6063709,2020-08-14T01:56:49Z,2020-08-14T01:56:49Z,CONTRIBUTOR,"Turns zero-padding years is platform dependent.
https://bugs.python.org/issue13305","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,677307460
https://github.com/pydata/xarray/issues/4336#issuecomment-673783177,https://api.github.com/repos/pydata/xarray/issues/4336,673783177,MDEyOklzc3VlQ29tbWVudDY3Mzc4MzE3Nw==,6063709,2020-08-14T01:05:33Z,2020-08-14T01:05:33Z,CONTRIBUTOR,"Thanks for the link to the tests. Your `pytest`-fu is strong! You're right, I didn't spot those.
I guess my philosophical point was that this throws an error:
```python
import cftime
import xarray
date = cftime.datetime(10,1,1)
xarray.cftime_range(date, periods=3, freq='Y')
```
but this doesn't:
```python
import cftime
import xarray
date = cftime.datetime(10,1,1).isoformat()
xarray.cftime_range(date, periods=3, freq='Y')
```
due to the latter being transformed to `cftime.DatetimeGregorian` as there is a default `calendar` attribute for `cftime_range`:
https://github.com/pydata/xarray/blob/cafab46aac8f7a073a32ec5aa47e213a9810ed54/xarray/coding/cftime_offsets.py#L788
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,677296128
https://github.com/pydata/xarray/issues/4337#issuecomment-673769082,https://api.github.com/repos/pydata/xarray/issues/4337,673769082,MDEyOklzc3VlQ29tbWVudDY3Mzc2OTA4Mg==,6063709,2020-08-14T00:08:22Z,2020-08-14T00:08:22Z,CONTRIBUTOR,"Thanks for the detailed response @spencerkclark
Seems that we're using different versions of `python` as my `datetime` implementation doesn't produce a zero padded year. I guess that was a bug that has also been fixed:
```python
In [1]: import datetime
In [2]: datetime.datetime(1, 1, 1).strftime(""%Y-%m-%dT%H:%M:%S"")
Out[2]: '1-01-01T00:00:00'
```
I agree that the `isoformat` is a good solution. I didn't know it was available in newer versions. I will upgrade my `cftime` version to `>=1.1.3` to access it.
Thanks for being open to supporting the default output. My only goal is to remove barriers to productivity and remove sources of confusion as I want these tools to be used, and embraced, as widely as possible.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,677307460
https://github.com/pydata/xarray/issues/3717#issuecomment-577936734,https://api.github.com/repos/pydata/xarray/issues/3717,577936734,MDEyOklzc3VlQ29tbWVudDU3NzkzNjczNA==,6063709,2020-01-24T00:08:50Z,2020-01-24T00:08:50Z,CONTRIBUTOR,"Thanks @ScottWales.
So using `dim` and not `axis` works, as you might expect given Scott's explanation.
So for anyone having this issue, a work-around is to specify `dim` if possible.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,553930127
https://github.com/pydata/xarray/pull/3220#issuecomment-525588616,https://api.github.com/repos/pydata/xarray/issues/3220,525588616,MDEyOklzc3VlQ29tbWVudDUyNTU4ODYxNg==,6063709,2019-08-28T05:20:40Z,2019-08-28T05:20:40Z,CONTRIBUTOR,"Thanks @shoyer. I have added a test. It contains no assertion, but does fail with
```
AttributeError: 'Array' object has no attribute 'tolist'
```
without the code update. Is that sufficient?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,481005183
https://github.com/pydata/xarray/pull/3220#issuecomment-525543137,https://api.github.com/repos/pydata/xarray/issues/3220,525543137,MDEyOklzc3VlQ29tbWVudDUyNTU0MzEzNw==,6063709,2019-08-28T01:15:25Z,2019-08-28T01:15:25Z,CONTRIBUTOR,"I can save the decoded version to a file and read it back in and it throws the error. I suppose this is traversing a different code path
```
>>> xarray.decode_cf(xarray.Dataset.from_dict(ds.to_dict()))
<xarray.Dataset>
Dimensions: (time: 5)
Coordinates:
* time (time) object 2198-07-02 12:00:00 ... 2202-07-02 12:00:00
Data variables:
average_T1 (time) datetime64[ns] ...
>>> xarray.decode_cf(xarray.Dataset.from_dict(ds.to_dict())).to_netcdf('tmp.nc')
>>> xarray.decode_cf(xarray.open_mfdataset('tmp.nc',decode_cf=False))
Traceback (most recent call last):
File ""<stdin>"", line 1, in <module>
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/conventions.py"", line 479, in decode_cf
decode_coords, drop_variables=drop_variables, use_cftime=use_cftime)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/conventions.py"", line 401, in decode_cf_variables
stack_char_dim=stack_char_dim, use_cftime=use_cftime)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/conventions.py"", line 306, in decode_cf_variable
var = coder.decode(var, name=name)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/coding/times.py"", line 419, in decode
self.use_cftime)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/coding/times.py"", line 90, in _decode_cf_datetime_dtype
last_item(values) or [0]])
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/core/formatting.py"", line 99, in last_item
return np.ravel(array[indexer]).tolist()
AttributeError: 'Array' object has no attribute 'tolist'
>>>
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,481005183
https://github.com/pydata/xarray/pull/3220#issuecomment-525538937,https://api.github.com/repos/pydata/xarray/issues/3220,525538937,MDEyOklzc3VlQ29tbWVudDUyNTUzODkzNw==,6063709,2019-08-28T00:53:53Z,2019-08-28T00:53:53Z,CONTRIBUTOR,"HI @max-sixty. I am working on making a test, but when I serialise my test file so it is suitable for inclusion in a test it doesn't throw an error!
```
>>> ds = xarray.open_mfdataset('temp_049.nc', decode_cf=False)
>>> xarray.decode_cf(ds)
Traceback (most recent call last):
File ""<stdin>"", line 1, in <module>
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/conventions.py"", line 479, in decode_cf
decode_coords, drop_variables=drop_variables, use_cftime=use_cftime)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/conventions.py"", line 401, in decode_cf_variables
stack_char_dim=stack_char_dim, use_cftime=use_cftime)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/conventions.py"", line 306, in decode_cf_variable
var = coder.decode(var, name=name)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/coding/times.py"", line 419, in decode
self.use_cftime)
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/coding/times.py"", line 90, in _decode_cf_datetime_dtype
last_item(values) or [0]])
File ""/g/data3/hh5/public/apps/miniconda3/envs/analysis3-19.07/lib/python3.6/site-packages/xarray/core/formatting.py"", line 99, in last_item
return np.ravel(array[indexer]).tolist()
AttributeError: 'Array' object has no attribute 'tolist'
>>> xarray.decode_cf(xarray.Dataset.from_dict(ds.to_dict()))
<xarray.Dataset>
Dimensions: (time: 5)
Coordinates:
* time (time) object 2198-07-02 12:00:00 ... 2202-07-02 12:00:00
Data variables:
average_T1 (time) datetime64[ns] ...
>>> ds.identical(xarray.Dataset.from_dict(ds.to_dict()))
True
>>>
```
Seems `Dataset.identical` is failing to find something that traversing `decode_cf` does. Odd.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,481005183
https://github.com/pydata/xarray/issues/3215#issuecomment-521524233,https://api.github.com/repos/pydata/xarray/issues/3215,521524233,MDEyOklzc3VlQ29tbWVudDUyMTUyNDIzMw==,6063709,2019-08-15T05:56:18Z,2019-08-15T05:57:40Z,CONTRIBUTOR,"Confirmed that `NUMPY_EXPERIMENTAL_ARRAY_FUNCTION=0` fixes this issue for me.
Have submitted a PR with your suggested fix https://github.com/pydata/xarray/pull/3220
Confirmed the submitted code fixes my issue.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,480512400
https://github.com/pydata/xarray/issues/3215#issuecomment-521504317,https://api.github.com/repos/pydata/xarray/issues/3215,521504317,MDEyOklzc3VlQ29tbWVudDUyMTUwNDMxNw==,6063709,2019-08-15T03:55:00Z,2019-08-15T03:55:00Z,CONTRIBUTOR,Thanks for the explanation.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,480512400
https://github.com/pydata/xarray/issues/3215#issuecomment-521502195,https://api.github.com/repos/pydata/xarray/issues/3215,521502195,MDEyOklzc3VlQ29tbWVudDUyMTUwMjE5NQ==,6063709,2019-08-15T03:40:27Z,2019-08-15T03:40:27Z,CONTRIBUTOR,"Thanks @shoyer.
I still don't understand the different code paths between `decode_cf=True` and `decode_cf=False` + explicit call to `xarray.decode_cf()`","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,480512400
https://github.com/pydata/xarray/issues/3215#issuecomment-521456728,https://api.github.com/repos/pydata/xarray/issues/3215,521456728,MDEyOklzc3VlQ29tbWVudDUyMTQ1NjcyOA==,6063709,2019-08-14T23:28:35Z,2019-08-14T23:28:35Z,CONTRIBUTOR,"Seems that this is by design, from [here](https://docs.dask.org/en/latest/array.html?highlight=tolist#scope)
> Dask Array doesn’t implement operations like tolist that would be very inefficient for larger datasets. Likewise, it is very inefficient to iterate over a Dask array with for loops
So `dask` has never had a `tolist` method, so in one case the object is a `dask` array, but not in the other case.
I still don't understand why it fails when `decode_cf` is called separately. Suggests there is a different code path as all underlying packages are identical.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,480512400
https://github.com/pydata/xarray/issues/470#issuecomment-441486969,https://api.github.com/repos/pydata/xarray/issues/470,441486969,MDEyOklzc3VlQ29tbWVudDQ0MTQ4Njk2OQ==,6063709,2018-11-26T00:14:46Z,2018-11-26T00:14:46Z,CONTRIBUTOR,"In the absence of a dedicated method, it is possible to obtain a scatterplot with the keyword options to `plot.line()`:
```
rho_so_remap.plot.line(marker='o',linewidth=0.)
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,94787306
https://github.com/pydata/xarray/issues/2231#issuecomment-410950987,https://api.github.com/repos/pydata/xarray/issues/2231,410950987,MDEyOklzc3VlQ29tbWVudDQxMDk1MDk4Nw==,6063709,2018-08-07T06:43:26Z,2018-08-07T06:59:22Z,CONTRIBUTOR,"> Sorry, xarray doesn’t handle time bounds directly, nor does it update metadata according to cfconventions. These were intentional design choices to keep xarray simple, but in principle you could layer cf convention handling on top of xarray.
Nor does it bring along bounds variables when extracting variables from a dataset, e.g.
```
double time(time) ;
time:long_name = ""time"" ;
time:cartesian_axis = ""T"" ;
time:calendar_type = ""NOLEAP"" ;
time:bounds = ""time_bounds"" ;
time:units = ""days since 0001-01-01"" ;
time:calendar = ""NOLEAP"" ;
```
When a variable using the `time` dimension is extracted from a `Dataset`, the `time_bounds` variable is missing.
Is this also an intentional choice or something that xarray could/should support? Or does already and I've missed how to invoke this.
Edit: I've just realised, how is xarray supposed to ""bring along"" another variable in a DataArray object? I'll leave this query as maybe there is a solution? Have a `bounds` attribute similar to the `coords` attribute?
Is this just a dupe of https://github.com/pydata/xarray/issues/1475 ?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,332018176
https://github.com/pydata/xarray/issues/2164#issuecomment-404500806,https://api.github.com/repos/pydata/xarray/issues/2164,404500806,MDEyOklzc3VlQ29tbWVudDQwNDUwMDgwNg==,6063709,2018-07-12T12:50:09Z,2018-07-12T12:50:09Z,CONTRIBUTOR,Sounds like a great idea.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,324740017
https://github.com/pydata/xarray/issues/2164#issuecomment-404468603,https://api.github.com/repos/pydata/xarray/issues/2164,404468603,MDEyOklzc3VlQ29tbWVudDQwNDQ2ODYwMw==,6063709,2018-07-12T10:35:04Z,2018-07-12T10:35:04Z,CONTRIBUTOR,"Hi @rabernat,
I apologise if what I said is discouraging. I didn't intend it that way. It was the result of exasperation, as I think array is a fantastic tool, and I thought with the development of cftime support all barriers to widespread adoption had pretty much been overcome. When I said ""another"" it was in reference to the previous barrier of not supporting long time, or old time, indices which had since been overcome
As far as recommending, it is to the researchers at the centre of excellence where I am one of the people who is paid to support climate models and the support infrastructure to run and analyse their outputs. I guess I've outed myself as one of those paid computational support staff you referred to.
My initial comment above was a clumsy attempt to highlight what I thought was an important feature to support to further increase xarray adoption. From my perspective as someone who has to support users I'm often having to decide what I think the majority of users will be able to use efficiently, taking into account very wide levels of expertise and motivation. Before the cftime upgrades I did not wholeheartedly evangelise for xarray adoption because I knew there were many cases where it was not simple and easy to use. For every edge and corner case I have to support users when they encounter them. In some ways, having a tool that can do such amazing things as xarray, but which don't work in some circumstances for some datasets is very frustrating for users. It can take a lot of work to find out what doesn't work.
Having said which, we're currently doing half way through a 2 hour training session for xarray for researchers in the CoE who are interested, but not being able to easily plot cftime datasets will harm adoption, and all those who are volunteering their time developing xarray want it to be adopted as widely as possible right?
Thanks for the pointer to the contributor guide, I did read it, and I will try and find some time to make a positive contribution to xarray. I had started down that path already (https://github.com/pydata/xarray/issues/2244)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,324740017
https://github.com/pydata/xarray/issues/2164#issuecomment-404404401,https://api.github.com/repos/pydata/xarray/issues/2164,404404401,MDEyOklzc3VlQ29tbWVudDQwNDQwNDQwMQ==,6063709,2018-07-12T06:32:20Z,2018-07-12T06:32:20Z,CONTRIBUTOR,"Darn. Just when I thought the time stuff was sorted. This is (yet another) deal breaker as far as recommending mass adoption goes.
Is there an estimate when, or if, `cftime` indexes will be supported by `xarray`'s `.plot()` method?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,324740017
https://github.com/pydata/xarray/issues/2244#issuecomment-399421816,https://api.github.com/repos/pydata/xarray/issues/2244,399421816,MDEyOklzc3VlQ29tbWVudDM5OTQyMTgxNg==,6063709,2018-06-22T12:11:44Z,2018-06-22T12:11:44Z,CONTRIBUTOR,"Great! Thanks @spencerkclark
I agree this is an excellent work around.
One of the most frustrating aspect of using an otherwise brilliant tool like `xarray` (and other python packages) is knowing what NOT to try and do. It is otherwise almost magical in the things it does well, so there is something of an expectation that it can and should do everything. If this work-around was part of the official documentation (until `shift` is implemented) that would be very useful.
I am often in the position of recommending software solutions to scientists who need to analyse their data, and the date issue with `xarray` (which CFTime has mostly alleviated) always made me hesitant to recommend it whole-heartedly. So thanks for your part in adding this to `xarray`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,334778045
https://github.com/pydata/xarray/issues/2244#issuecomment-399352855,https://api.github.com/repos/pydata/xarray/issues/2244,399352855,MDEyOklzc3VlQ29tbWVudDM5OTM1Mjg1NQ==,6063709,2018-06-22T07:44:03Z,2018-06-22T07:44:03Z,CONTRIBUTOR,"Submitted issue brought up in this thread
https://github.com/pydata/xarray/issues/2191#issuecomment-399337976","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,334778045
https://github.com/pydata/xarray/issues/2191#issuecomment-399320016,https://api.github.com/repos/pydata/xarray/issues/2191,399320016,MDEyOklzc3VlQ29tbWVudDM5OTMyMDAxNg==,6063709,2018-06-22T04:51:16Z,2018-06-22T04:51:16Z,CONTRIBUTOR,"Does this need it's own issue then, so it doesn't get lost?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,327089588
https://github.com/pydata/xarray/issues/2159#issuecomment-399319465,https://api.github.com/repos/pydata/xarray/issues/2159,399319465,MDEyOklzc3VlQ29tbWVudDM5OTMxOTQ2NQ==,6063709,2018-06-22T04:47:36Z,2018-06-22T04:47:36Z,CONTRIBUTOR,👍 for this feature,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,324350248
https://github.com/pydata/xarray/issues/2191#issuecomment-399315302,https://api.github.com/repos/pydata/xarray/issues/2191,399315302,MDEyOklzc3VlQ29tbWVudDM5OTMxNTMwMg==,6063709,2018-06-22T04:12:11Z,2018-06-22T04:45:03Z,CONTRIBUTOR,"I'm not sure if my issue belongs in here, but I didn't want to create a new Issue (there are already 455 open ones).
I am experimenting with the new `CFTimeIndex` functionality (thanks heaps BTW! That was a mammoth effort if the PR thread is anything to go by).
I am trying to `shift` a time index as I need to align datasets to a common start point. So using the example code above,
```python
da.time.get_index('time').shift(1,'D')
---------------------------------------------------------------------------
NotImplementedError Traceback (most recent call last)
<ipython-input-71-db48b2fbb340> in <module>()
----> 1 da.time.get_index('time').shift(1,'D')
/g/data3/hh5/public/apps/miniconda3/envs/analysis27-18.04/lib/python2.7/site-packages/pandas/core/indexes/base.pyc in shift(self, periods, freq)
2627 """"""
2628 raise NotImplementedError(""Not supported for type %s"" %
-> 2629 type(self).__name__)
2630
2631 def argsort(self, *args, **kwargs):
NotImplementedError: Not supported for type CFTimeIndex
```
Is this not implemented because it might require resampling?
I ask because this works:
```python
times[0] + pd.Timedelta('365 days')
cftime.DatetimeNoLeap(2, 1, 1, 0, 0, 0, 0, -1, 1)
```
I guess I am asking, if I want to shift a time index is the best (only?) way currently is to loop over all the individual elements of the index and add a time offset to each?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,327089588
https://github.com/pydata/xarray/issues/548#issuecomment-134420461,https://api.github.com/repos/pydata/xarray/issues/548,134420461,MDEyOklzc3VlQ29tbWVudDEzNDQyMDQ2MQ==,6063709,2015-08-25T00:05:40Z,2015-08-25T04:09:18Z,CONTRIBUTOR,"Brilliant. Thanks. I looked into the code but thought the encoding information was being stripped out.
So I've confirmed xray will round-trip fine. Shallow copies also round trip. Similarly making a new dataset from a variable with encoding information preserves that information and will output properly.
``` python
% tmp = xray.open_dataset('saved_on_disk_compressed.nc')
% tmp
<xray.Dataset>
Dimensions: (time: 3, x: 2, y: 2)
Coordinates:
reference_time datetime64[ns] 2014-09-05
lon (x, y) float64 -99.83 -99.32 -99.79 -99.23
* time (time) datetime64[ns] 2014-09-06 2014-09-07 2014-09-08
lat (x, y) float64 42.25 42.21 42.63 42.59
* x (x) int64 0 1
* y (y) int64 0 1
Data variables:
temperature (x, y, time) float64 10.66 8.539 6.713 8.519 29.07 27.86 ...
precipitation (x, y, time) float64 0.3385 6.773 8.985 0.9651 0.1359 ...
% tmp.temperature.encoding
{'chunksizes': (2, 2, 3),
'complevel': 5,
'contiguous': False,
'dtype': dtype('float64'),
'fletcher32': False,
'shuffle': True,
'source': 'saved_on_disk_compressed.nc',
'zlib': True}
% tmp2 = tmp
% tmp2.to_netcdf('saved_on_disk_comp_tmp2.nc')
% tmp3 = xray.open_dataset('saved_on_disk_comp_tmp2.nc')
% tmp3.temperature.encoding
{'chunksizes': (2, 2, 3),
'complevel': 5,
'contiguous': False,
'dtype': dtype('float64'),
'fletcher32': False,
'shuffle': True,
'source': 'saved_on_disk_comp_xray.nc',
'zlib': True}
```
Setting encoding dictionary works fine too (in this case copying from an existing variable):
``` python
% tmp4 = xray.DataArray(tmp.temperature.values).to_dataset(name='temperature')
% tmp4.temperature.encoding
{}
% tmp4.temperature.encoding = tmp.temperature.encoding
% tmp4.temperature.encoding
{'chunksizes': (2, 2, 3),
'complevel': 5,
'contiguous': False,
'dtype': dtype('float64'),
'fletcher32': False,
'shuffle': True,
'source': 'saved_on_disk_compressed.nc',
'zlib': True}
% tmp4.to_netcdf('saved_on_disk_comp_tmp4.nc')
% tmp5 = xray.open_dataset('saved_on_disk_comp_tmp4.nc')
% tmp.temperature.encoding
{'chunksizes': (2, 2, 3),
'complevel': 5,
'contiguous': False,
'dtype': dtype('float64'),
'fletcher32': False,
'shuffle': True,
'source': 'saved_on_disk_compressed.nc',
'zlib': True}
```
That will do nicely. Thanks.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,102703065
https://github.com/pydata/xarray/issues/516#issuecomment-133992153,https://api.github.com/repos/pydata/xarray/issues/516,133992153,MDEyOklzc3VlQ29tbWVudDEzMzk5MjE1Mw==,6063709,2015-08-24T02:21:43Z,2015-08-24T02:21:43Z,CONTRIBUTOR,"What is the netCDF4 chunking scheme for your compressed data? (use 'ncdump -hs' to reveal the per variable chunking scheme).
[Very large datasets can have very long load times depending on the access pattern](http://www.unidata.ucar.edu/blogs/developer/entry/chunking_data_why_it_matters).
This can be overcome with an appropriately chosen chunking scheme, but if the chunk sizes are not well chosen (and the default library chunking is pretty terrible) then certain access patterns might still be very slow.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,99026442
https://github.com/pydata/xarray/issues/349#issuecomment-91437792,https://api.github.com/repos/pydata/xarray/issues/349,91437792,MDEyOklzc3VlQ29tbWVudDkxNDM3Nzky,6063709,2015-04-10T05:49:17Z,2015-04-10T05:49:17Z,CONTRIBUTOR,"Great to see open_mfdataset implemented! Awesome. The links on the documentation pages seem borked though:
https://github.com/xray/xray/blob/0cd100effc3866ed083c366723da0b502afa5a96/doc/io.rst
e.g. "":py:func:`~xray.auto_combine`"" https://github.com/xray/xray/blob/0cd100effc3866ed083c366723da0b502afa5a96/doc/io.rst#id30
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,59467251
https://github.com/pydata/xarray/issues/349#issuecomment-81422044,https://api.github.com/repos/pydata/xarray/issues/349,81422044,MDEyOklzc3VlQ29tbWVudDgxNDIyMDQ0,6063709,2015-03-16T05:16:08Z,2015-03-16T05:16:08Z,CONTRIBUTOR,"Sorry, I thought I had read the docs (which are very good BTW). Thanks.
I have some large files and only want to pick out a single variable from each, and was hoping for some lazy-loading goodness.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,59467251
https://github.com/pydata/xarray/issues/349#issuecomment-81399209,https://api.github.com/repos/pydata/xarray/issues/349,81399209,MDEyOklzc3VlQ29tbWVudDgxMzk5MjA5,6063709,2015-03-16T04:11:37Z,2015-03-16T04:11:37Z,CONTRIBUTOR,"Is there support for an MFDataset-like multiple file open in xray?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,59467251