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
1206634329,I_kwDOAMm_X85H68dZ,6493,boundary conditions for differentiate(),9312831,open,0,,,9,2022-04-18T04:07:32Z,2022-04-26T14:48:33Z,,NONE,,,,"### Is your feature request related to a problem?

I need to take centered finite difference of `data` of length N along the dimension 'X', with boundary conditions (BCs) specified in flexible ways.  Before this, we need to pad `data` with BCs (length becoming N+2) so that the indicing will not be out-of-range.

Commonly used BCs are:
1. `fixed` - fill with fixed values so derivatives at BCs are `(BC - data[-1])/dx` and `(data[0] - BC)/dx`;
2. `extend` - fill BCs with second outer-most values so that derivatives at BCs are exactly zero;
3. `periodic` - fill BCs cyclic so that the derivatives are also cyclic.

### Describe the solution you'd like

The implementation of `differentiate('X')` would be like:
```python
# padded with BCs into N+2
data_pad = pad_BCs(data, type='periodic')

# it is safe to take finite difference
for i in range(len(data))
    diff[i] = data_pad [i+1] - data_pad [i-1]
```

The `pad_BCs` function could be easily implemented with [`np.pad()`](https://numpy.org/devdocs/reference/generated/numpy.pad.html) function.

Then we can call:
```python
data.differentiate('X', BCs='periodic')
```
We may also specify different kind of BCs at the two boundaries:

```python
data.differentiate('X', BCs=['extend', 'fixed'], fill_values=0)
```

### Describe alternatives you've considered

_No response_

### Additional context

I am not clear how `differentiate()` is implemented and just want to know if this can be implemented in a straightforward way.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/6493/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue
607718350,MDU6SXNzdWU2MDc3MTgzNTA=,4011,missing empty group when iterate over groupby_bins,9312831,open,0,,,4,2020-04-27T17:22:31Z,2022-04-09T03:08:14Z,,NONE,,,,"When I try to iterate over the object `grouped` returned by `groupby_bins`, I found that the empty group is missing silently.  Here is a simple case:
```python
array = xr.DataArray(np.arange(4), dims='dim_0')
# one of these bins will be empty
bins = [0,4,5]
grouped = array.groupby_bins('dim_0', bins)

for i, group in enumerate(grouped):
    print(str(i)+'  '+group)
```
When a bin contains no samples (bin of (4, 5]), the empty group will be dropped.  Then how to iterate over the full bins even when some bins contain nothing?  I've read this related issue #1019. 
 But my case here need the correct order in grouped and empty groups need to be iterated over.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/4011/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,,13221727,issue