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
359446339,MDU6SXNzdWUzNTk0NDYzMzk=,2412,Inconsistent signature of `apply`,4414299,closed,0,,,0,2018-09-12T11:57:06Z,2018-12-24T17:50:20Z,2018-12-24T17:50:20Z,CONTRIBUTOR,,,,"`Dataset.apply` allows passing positional arguments to `func` as `args=()`, whereas `DataArrayGroupBy.apply` and `DatasetGroupBy.apply` do not. The documentation also incorrectly suggests that the reverse is true:

`Dataset.apply`:
https://github.com/pydata/xarray/blob/4de8dbc3b1de461c0c9d3b002e55d60b46d2e6d2/xarray/core/dataset.py#L2832-L2840

`DataArrayGroupBy.apply`:
https://github.com/pydata/xarray/blob/4de8dbc3b1de461c0c9d3b002e55d60b46d2e6d2/xarray/core/groupby.py#L473-L478

`DatasetGroupBy.apply`:
https://github.com/pydata/xarray/blob/4de8dbc3b1de461c0c9d3b002e55d60b46d2e6d2/xarray/core/groupby.py#L580-L585

I feel that `func`s passed to `GroupBy` objects are generally equally deserving of positional arguments, and I don't see a reason why this isn't the case.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/2412/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
259057144,MDU6SXNzdWUyNTkwNTcxNDQ=,1582,Rasterio tags are not accessible through open_rasterio,4414299,closed,0,,,5,2017-09-20T06:48:18Z,2018-03-16T18:48:46Z,2017-12-12T14:38:53Z,CONTRIBUTOR,,,,"# The problem
When opening an ENVI file directly using rasterio, (some) metadata from the header file is available through `tags()`:
```python
import rasterio
src = rasterio.open(file)
src.tags() # dict of metadata for the whole array
src.tags(1) # same for band 1
```
Opening the same file through `open_rasterio`, the metadata is not carried through to the returned DataArray, neither as attributes nor as coordinates (which is the use case I'm interested in, since the metadata usually contains corresponding wavelengths for the bands).

## Solutions?
I don't know what kind of data `tags()` might contain in general. For my use case, parsing the tags for each band as coordinates is necessary at some point. It might be better generally if the tags are stored as an attribute and munged afterwards, but this is complicated by the fact that there's tags for the whole file as well as for separate bands.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1582/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
271000579,MDU6SXNzdWUyNzEwMDA1Nzk=,1686,Incorrect y-coordinates for non-georeferenced data from open_rasterio,4414299,closed,0,,,8,2017-11-03T14:39:21Z,2018-01-26T13:50:54Z,2018-01-26T13:50:54Z,CONTRIBUTOR,,,,"For a non-georeferenced dataset, `open_rasterio()` results in y-coordinates from the raster height to two times the height, instead of the expected 0 .. height range:

```python
import numpy as np
import rasterio
from xarray import open_rasterio

tmp_file = 'no_transform.tif'
nx, ny, nz = 4, 3, 3 
data = np.arange(nx*ny*nz,
                 dtype=rasterio.float32).reshape(nz, ny, nx)
with rasterio.open(
              tmp_file, 'w', 
              driver='GTiff', height=ny, width=nx, count=nz,
              dtype=rasterio.float32) as s:
        s.write(data)

open_rasterio(tmp_file)
```

>     <xarray.DataArray (band: 3, y: 3, x: 4)>
>     array( ... )
>     Coordinates:
>       * band     (band) int64 1 2 3
>       * y        (y) float64 3.5 4.5 5.5
>       * x        (x) float64 0.5 1.5 2.5 3.5
>     Attributes:
>          res:        (1.0, -1.0)
>          is_tiled:   0
>          transform:  (0.0, 1.0, 0.0, 0.0, 0.0, 1.0)

Passing `transform=from_origin(0,3,1,1)` (from `rasterio.transforms`) to `rasterio.open()` in the above code seems to give the expected result with y running down from 2.5:

>     <xarray.DataArray (band: 3, y: 3, x: 4)>
>     array( ... )
>     Coordinates:
>       * band     (band) int64 1 2 3
>       * y        (y) float64 2.5 1.5 0.5
>       * x        (x) float64 0.5 1.5 2.5 3.5
>     Attributes:
>         res:        (1.0, 1.0)
>         is_tiled:   0
>         transform:  (0.0, 1.0, 0.0, 3.0, 0.0, -1.0)

I'm not sure whether there's something amiss in the xarray coordinate calculations or the rasterio default transform logic. Looking at the code, I feel like there's some mismatch between the rasterio `res` property logic and the xarray coordinate generation (namely, the sign of `res[1]`):

https://github.com/mapbox/rasterio/blob/fcd361c49cca9c4ad32a2ac1f5d66b967f4b6cd4/rasterio/_base.pyx#L611-L619

https://github.com/pydata/xarray/blob/f83361c76b6aa8cdba8923080bb6b98560cf3a96/xarray/backends/rasterio_.py#L131-L139

I'm not quite sure if the xarray code is quite correct for georefenced data, since it doesn't utilize the given coordinate transform. I don't' have files to test it with though.","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/1686/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue