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
575939446,MDU6SXNzdWU1NzU5Mzk0NDY=,3830,"Documentation request: add examples for carrying out ""ncecat"" in xarray",19657652,open,0,,,4,2020-03-05T01:58:17Z,2023-04-13T20:06:20Z,,NONE,,,,"<!-- A short summary of the issue, if appropriate -->
In climate science, a very common task involves concatenating NetCDF files with identical variables, dimensions, and coordinates along a brand new ""ensemble member"" or ""record"" dimension. With the NetCDF Operators, this is accomplished using [`ncecat`](http://nco.sourceforge.net/nco.html#ncecat-netCDF-Ensemble-Concatenator
).
#### MCVE Code Sample
Currently, it seems the correct way to do this in xarray is with [`xarray.combine_nested`](http://xarray.pydata.org/en/stable/generated/xarray.combine_nested.html) as follows:
```python
import xarray as xr
files = ['member1.nc', 'member2.nc', ...]
ds = xr.open_mfdataset(
files,
combine='nested',
concat_dim='record',
)
```
#### Problem Description
While this works, there does not seem to be any mention of this use case in the [`combine_nested`](http://xarray.pydata.org/en/stable/generated/xarray.combine_nested.html) or [`open_mfdataset`](http://xarray.pydata.org/en/stable/generated/xarray.open_mfdataset.html) docs... and using `combine='nested'` to concatenate along a brand new dimension feels quite unintuitive to me.
It would be nice to have examples in `combine_nested` and/or `open_mfdataset` with this special usage or mention the possibility of creating *brand new* dimensions with `concat_dim`. For example:
```python
In [1]: import xarray as xr
...: datasets = [
...: xr.Dataset({'temp': (('x', 'y'), np.random.rand(10, 20))})
...: for i in range(3)
...: ]
...: xr.combine_nested(datasets, concat_dim='record')
Out[1]:
<xarray.Dataset>
Dimensions: (record: 3, x: 10, y: 20)
Dimensions without coordinates: record, x, y
Data variables:
temp (record, x, y) float64 0.32 0.4897 0.2659 ... 0.3485 0.0251 0.399
```
#### Output of ``xr.show_versions()``
n/a","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/3830/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
661076732,MDU6SXNzdWU2NjEwNzY3MzI=,4239,Xarray dimension interpolation strips coordinate attributes,19657652,closed,0,,,1,2020-07-19T21:19:35Z,2021-04-27T07:00:07Z,2021-04-27T07:00:07Z,NONE,,,,"<!-- Please include a self-contained copy-pastable example that generates the issue if possible.
Please be concise with code posted. See guidelines below on how to provide a good bug report:
- Craft Minimal Bug Reports: http://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports
- Minimal Complete Verifiable Examples: https://stackoverflow.com/help/mcve
Bug reports that follow these guidelines are easier to diagnose, and so are often handled much more quickly.
-->
**What happened**: `DataArray.interp` strips the dimension coordinate attributes.
**What you expected to happen**: Preserved coordinate attributes.
**Minimal Complete Verifiable Example**:
Input:
```python
import xarray as xr
import numpy as np
data = xr.DataArray(
np.random.rand(5),
dims='x',
coords={'x': ('x', np.arange(5), {'foo': 'bar'})}
)
print(data.x.attrs) # initial attributes
print(data.sel(x=2).x.attrs) # sel and isel preserve attributes
print(data.interp(x=2.5).x.attrs) # interp does not preserve attributes
with xr.set_options(keep_attrs=True):
print(data.interp(x=2.5).x.attrs) # keep_attrs does nothing
```
Output:
```python
{'foo': 'bar'}
{'foo': 'bar'}
{}
{}
```
**Environment**:
<details><summary>Output of <tt>xr.show_versions()</tt></summary>
<!-- Paste the output here xr.show_versions() here -->
INSTALLED VERSIONS
------------------
commit: None
python: 3.8.3 | packaged by conda-forge | (default, Jun 1 2020, 17:43:00)
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-957.27.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.6
libnetcdf: 4.7.4
xarray: 0.15.1
pandas: 1.0.4
numpy: 1.18.4
scipy: 1.4.1
netCDF4: 1.5.3
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: 1.1.3
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2.17.2
distributed: 2.18.0
matplotlib: 3.2.1
cartopy: 0.18.0
seaborn: None
numbagg: None
setuptools: 47.3.0.post20200616
pip: 20.1.1
conda: 4.8.3
pytest: None
IPython: 7.15.0
sphinx: None
</details>
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639618568,MDU6SXNzdWU2Mzk2MTg1Njg=,4161,Dark theme-friendly HTML Dataset and DataArray reprs for jupyter notebooks?,19657652,closed,0,,,2,2020-06-16T12:18:23Z,2020-06-17T18:33:58Z,2020-06-17T18:33:58Z,NONE,,,,"<!-- A short summary of the issue, if appropriate -->
Xarray's HTML `Dataset` and `DataArray` reprs are evidently not compatible with ""dark"" jupyter notebook themes. They seem to work fine with the dark jupyter lab theme, and since jupyter lab is the way of the future perhaps this issue is obsolete, but thought I'd mention it.
The below example is from a jupyter notebook with the ""onedork"" dark theme from [jupyter-themes](https://github.com/dunovank/jupyter-themes). It results in black text against a dark background for the section headers (Coordinates, Dimensions, etc.) and DataArray data tables, and a light background for the coordinate and Dataset data tables.
```python
# Dataset repr
import numpy as np
import xarray as xr
ds = xr.Dataset(
{
'temp': (('x', 'y'), np.random.rand(10, 20), {'long_name': 'temperature', 'units': 'degrees_Celsius'}),
'x': ('x', np.arange(10)),
'y': ('y', np.arange(20)),
},
attrs={'description': 'example dataset'}
)
ds
```
<img width=""810"" alt=""Screen Shot 2020-06-16 at 4 45 48 AM"" src=""https://user-images.githubusercontent.com/19657652/84765299-43714380-af8c-11ea-9a73-8f21107a0429.png"">
```python
# DataArray repr
ds.temp
```
<img width=""806"" alt=""Screen Shot 2020-06-16 at 4 55 56 AM"" src=""https://user-images.githubusercontent.com/19657652/84766229-ae6f4a00-af8d-11ea-9c90-0bcc97a24041.png"">
Note that, by contrast, the text repr is dark theme friendly:
```python
# Text repr
xr.set_options(display_style='text')
ds
```
<img width=""874"" alt=""Screen Shot 2020-06-16 at 5 01 40 AM"" src=""https://user-images.githubusercontent.com/19657652/84766683-7a485900-af8e-11ea-95f6-ab0f015a42b5.png"">
#### Versions
<details><summary>Jupyter versions</summary>
jupyter core : 4.6.3
jupyter-notebook : 6.0.3
qtconsole : 4.7.4
ipython : 7.15.0
ipykernel : 5.3.0
jupyter client : 6.1.3
jupyter lab : not installed
nbconvert : 5.6.1
ipywidgets : 7.5.1
nbformat : 5.0.6
traitlets : 4.3.3
</details>
<details><summary>Output of <tt>xr.show_versions()</tt></summary>
INSTALLED VERSIONS
------------------
commit: None
python: 3.8.3 | packaged by conda-forge | (default, Jun 1 2020, 17:43:00)
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-957.27.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: None
libnetcdf: None
xarray: 0.15.1
pandas: 1.0.4
numpy: 1.18.4
scipy: 1.4.1
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2.17.2
distributed: 2.18.0
matplotlib: 3.2.1
cartopy: 0.18.0
seaborn: None
numbagg: None
setuptools: 47.1.1.post20200529
pip: 20.1.1
conda: 4.8.3
pytest: None
IPython: 7.15.0
sphinx: None
</details>
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