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
1577957904,I_kwDOAMm_X85eDboQ,7517,Getting information on netcdf file with unlimited dimensions,2853966,open,0,,,3,2023-02-09T14:08:44Z,2023-04-29T03:40:24Z,,NONE,,,,"### What is your issue?

When one reads a netCDF file, there is not solution to determine if there is an unlimited dimension, and determine which one.

I really need to be able to handle that. I need to process a variable, and write the result with the exact same informations about dimensions and coordinates, with all attributes and characteristics.



Thanks,

Olivier

```
import xarray as xr, os

print ( '==== Get an example file' )
file   = 'tas_Amon_IPSL-CM6A-LR_piControl_r1i1p1f1_gr_185001-234912.nc'
h_file = f""https://vesg.ipsl.upmc.fr/thredds/fileServer/cmip6/CMIP/IPSL/IPSL-CM6A-LR/piControl/r1i1p1f1/Amon/tas/gr/v20200326/{file}""

print ( '\n ==== Getting file ')
os.system ( f""wget --no-clobber {h_file}"")

print ( '\n ==== File header : this file has an unlimited dimension ""time""' )
os.system ( f""ncdump -h  {file} | head"")

dd = xr.open_dataset ( file, decode_times=True, use_cftime=True)

xr.set_options ( display_expand_attrs=True)
print ( '\n ==== General information : no information about the unlimited dimension(s)' )
print (dd)

print ( '\n ==== Dimensions : no information about the unlimited dimension(s)')
print ( dd.dims )

print ( '\n === Attributes : no information about the unlimited dimension(s)' )
for attr in dd.attrs :
    print ( f'{attr} : {dd.attrs[attr]}' )
```
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/7517/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
1084854762,I_kwDOAMm_X85AqZHq,6087,Computing 'seasonal means' spanning 4 months (with resample or groupy),2853966,closed,1,,,0,2021-12-20T14:27:20Z,2022-01-21T05:54:39Z,2022-01-21T05:54:39Z,NONE,,,,"Climatologists often use 'seasonal means', i.e. means over 3 months. Useful periods are DJF for December-January-February, MAM, JJA and SON. groupby or resample are nice functions to compute these seasonal means.

sea for example :
https://xarray.pydata.org/en/stable/examples/monthly-means.html
https://stackoverflow.com/questions/59234745/is-there-any-easy-way-to-compute-seasonal-mean-with-xarray

But some studies need means over 4 months : DJFM, MAMJ, JJAS and SOND. Would it be feasible that these 4-month periods are recognized by groupby and resample ?

For resample, we define 3-month means with a syntax like : resample(time='QS-DEC')

A resampling over 4 months is more tricky : it is not a real resampling, as some months are repeated. We still need 4 seasonal values ...

Thanks,

Olivier","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6087/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
865003095,MDU6SXNzdWU4NjUwMDMwOTU=,5208,DataArray attributes not present in DataSet. Coherency problem between DataSet and NetCDF file,2853966,open,0,,,4,2021-04-22T14:14:15Z,2021-04-29T22:33:05Z,,NONE,,,,"When I create a DataSet from DataArrays, attributes are lost. 

When are create attributes in a DataSet, they are know shown by `print (DataSet)`, but are written in the NetCDF file.

Below is python code showing the xarray behaviour in details.

My requests :
* When creating a DataSet from DataArrays, DataArrays attributes should be incorporated in the DataSet. (maybe optional)
* Attributes present in a DataSet should appear with a `print (DataSet)`. Like for DataArrays.

Thanks,

Olivier

```python
#!/usr/bin/env python
# coding: utf-8
import numpy  as np
import xarray as xr

# Creates DataArrays
nt = 4
time = np.arange (nt) * 86400.0
time = xr.DataArray (time, coords=[time,], dims=[""time"",])
aa   = time * 2.0

# Adding attributes to DataArrays
time.attrs['units'] = ""second""
aa.attrs['units']   = ""whatever""

# Attributes are visible in the DataArrays
print ('----------> time DataArray: ')
print (time)
print ('----------> aa DataArray : ' )
print (aa)
print ('----------> aa attributes : ')
print (aa.attrs )

# Creating a Dataset
ds = xr.Dataset(
    { ""aa"": ([""time"",], aa),  },
    coords={""time"": ([""time"",], time), },   ) 

# Attributes are not visible in the Dataset
print ('----------> DataSet before setting attributes')
print (ds)
# My request #1 : attributes of the DataArrays should be added to the DataSet (may be optional)
print ('----------> Attributes of aa in DataSet : none')
print ( ds['aa'].attrs )
print ('----------> Attributes of aa outside DataSet : still here')
print ( aa.attrs )

print ('----------> Attributes are not written to the NetCDF file')
ds.to_netcdf ('sample1.nc')

# Adding attributes directly to the Dataset
ds['time'].attrs['units'] = ""second""
ds['aa'].attrs['units']   = ""whatever""

# Attributes are still not visible in the Dataset
print ('----------> DataSet after setting attributes : attributes not shown' )
print (ds)
# My request #2 : attributes added to the DataSet should be printed

print ('----------> But they are written in the NetCDF file')
ds.to_netcdf ('sample2.nc')
# MyRequest : coherency between the DataSet and the NetCDF file

# What if I read a NetCDF file
dt = xr.open_dataset ( 'sample2.nc')

print ('----------> DataSet read in a NetCDF file : Attributes are not shown')
print (dt)

print  ('----------> Attributes of aa in DataSet : present')
print ( dt['aa'].attrs )



```
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