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/1949#issuecomment-463309270,https://api.github.com/repos/pydata/xarray/issues/1949,463309270,MDEyOklzc3VlQ29tbWVudDQ2MzMwOTI3MA==,223250,2019-02-13T18:20:28Z,2019-02-13T18:20:28Z,CONTRIBUTOR,"I was looking for a way to drop dimensions, similar to the OP, and found this issue. I created an implementation of `Dataset.drop_dims` in #2767 which should work.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 1, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-424025935,https://api.github.com/repos/pydata/xarray/issues/1949,424025935,MDEyOklzc3VlQ29tbWVudDQyNDAyNTkzNQ==,1217238,2018-09-24T15:53:49Z,2018-09-24T15:53:49Z,MEMBER,"> So does this mean that the following line in the docs is now false: ""If a dimension name is given as an argument to drop, it also drops all variables that use that dimension""
Oops -- yes, that line in the docs / example is broken!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-424014244,https://api.github.com/repos/pydata/xarray/issues/1949,424014244,MDEyOklzc3VlQ29tbWVudDQyNDAxNDI0NA==,10946756,2018-09-24T15:21:41Z,2018-09-24T15:50:19Z,NONE,"So does this mean that the following line in the docs is now false: ""If a dimension name is given as an argument to drop, it also drops all variables that use that dimension""
This is at http://xarray.pydata.org/en/stable/data-structures.html#dataarray.
It does not seem to work as advertised. Before drop:
```
<xarray.Dataset>
Dimensions: (Frequency: 2000, Index: 1, Power: 1, Temperature: 1)
Coordinates:
* Power (Power) float64 -117.0
* Temperature (Temperature) float64 1.16
* Index (Index) int64 0
* Frequency (Frequency) float64 3.865e+09 3.865e+09 3.865e+09 3.865e+09 ...
Data variables:
I (Power, Temperature, Index, Frequency) float64 ...
Q (Power, Temperature, Index, Frequency) float64 ...
Time (Power, Temperature, Index) datetime64[ns] ...
```
Then I call `ds.drop('Frequency')`, expecting that this will kill off the Frequency dimension, coordinate, and the `I` and `Q` variables, since they depend on Frequency, but what I get is:
```
<xarray.Dataset>
Dimensions: (Frequency: 2000, Index: 1, Power: 1, Temperature: 1)
Coordinates:
* Power (Power) float64 -117.0
* Temperature (Temperature) float64 1.16
* Index (Index) int64 0
Dimensions without coordinates: Frequency
Data variables:
I (Power, Temperature, Index, Frequency) float64 ...
Q (Power, Temperature, Index, Frequency) float64 ...
Time (Power, Temperature, Index) datetime64[ns] ...
```
If I then try dropping Frequency again, it complains that there are no variables named 'Frequency'. So probably this issue should include an update to the documentation. Or maybe that should be a new issue.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-369319591,https://api.github.com/repos/pydata/xarray/issues/1949,369319591,MDEyOklzc3VlQ29tbWVudDM2OTMxOTU5MQ==,1217238,2018-02-28T17:38:59Z,2018-02-28T17:38:59Z,MEMBER,"> The second one also provides more scope to remove subsets of data (all corresponding dims, coords, vars) if the dimension becomes superfluous for any reason, whether or not the dimension is empty.
Yes, this was a useful feature that we lost.
Note that in general we try to encourage using methods to create new Datasets rather than modifying existing ones inplace. So it might also make sense to add a `drop_dims()` method that return a Dataset with the given dimensions removed.","{""total_count"": 3, ""+1"": 3, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-369315468,https://api.github.com/repos/pydata/xarray/issues/1949,369315468,MDEyOklzc3VlQ29tbWVudDM2OTMxNTQ2OA==,17178478,2018-02-28T17:27:10Z,2018-02-28T17:27:38Z,NONE,"The drop technique seems reasonable, if a bit long-winded for the programmatic case (loop over all dimensions, find any that are empty -> loop over all variables, drop any that contain those empty dimensions).
As an addition, if the empty dimension also has an associated empty coordinate then it requires an extra step to get rid of it:
``` python
In [21]: test_dataset = xr.Dataset(dict(
...: empty_array=xr.DataArray([], dims='a', coords={'a':[]}),
...: populated_array=xr.DataArray([1], {'b':['1']}, 'b')
...: ))
In [22]: test_dataset
Out[22]:
<xarray.Dataset>
Dimensions: (a: 0, b: 1)
Coordinates:
* a (a) float64
* b (b) <U1 '1'
Data variables:
empty_array (a) float64
populated_array (b) int32 1
In [23]: test_dataset.drop('empty_array')
Out[23]:
<xarray.Dataset>
Dimensions: (a: 0, b: 1)
Coordinates:
* a (a) float64
* b (b) <U1 '1'
Data variables:
populated_array (b) int32 1
In [24]: del test_dataset['a']
In [25]: test_dataset.drop('empty_array')
Out[25]:
<xarray.Dataset>
Dimensions: (b: 1)
Coordinates:
* b (b) <U1 '1'
Data variables:
populated_array (b) int32 1
```
Fixes seem reasonable, based on how we use xarray over at https://github.com/calliope-project/calliope/. The second one also provides more scope to remove subsets of data (all corresponding dims, coords, vars) if the dimension becomes superfluous for any reason, whether or not the dimension is empty.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-369294450,https://api.github.com/repos/pydata/xarray/issues/1949,369294450,MDEyOklzc3VlQ29tbWVudDM2OTI5NDQ1MA==,1217238,2018-02-28T16:23:40Z,2018-02-28T16:23:40Z,MEMBER,"If you're OK creating a new Dataset, it works to remove any variables using a dimension, e.g.,
```
In [25]: test_dataset = xr.Dataset(dict(
...: empty_array=xr.DataArray([], dims='a'),
...: populated_array=xr.DataArray([1], {'b':['1']}, 'b')
...: ))
...:
In [26]: test_dataset
Out[26]:
<xarray.Dataset>
Dimensions: (a: 0, b: 1)
Coordinates:
* b (b) <U1 '1'
Dimensions without coordinates: a
Data variables:
empty_array (a) float64
populated_array (b) int64 1
In [27]: test_dataset.drop('empty_array')
Out[27]:
<xarray.Dataset>
Dimensions: (b: 1)
Coordinates:
* b (b) <U1 '1'
Data variables:
populated_array (b) int64 1
```
You're right that this doesn't work to remove dimensions from existing datasets (e.g., with `del`). But this isn't specific to dimensions of length 0 -- you can't delete any dimensions. At best, you can delete a coordinate variable corresponding to a dimension:
```
In [46]: test_dataset
Out[46]:
<xarray.Dataset>
Dimensions: (a: 0, b: 1)
Coordinates:
* b (b) <U1 '1'
Dimensions without coordinates: a
Data variables:
empty_array (a) float64
populated_array (b) int64 1
In [47]: del test_dataset['b']
In [48]: test_dataset
Out[48]:
<xarray.Dataset>
Dimensions: (a: 0, b: 1)
Dimensions without coordinates: a, b
Data variables:
empty_array (a) float64
populated_array (b) int64 1
In [49]: del test_dataset['populated_array']
In [50]: test_dataset
Out[50]:
<xarray.Dataset>
Dimensions: (a: 0, b: 1)
Dimensions without coordinates: a, b
Data variables:
empty_array (a) float64
```
> Is there a way to remove a dimension (and possibly then all data variables which depend on it)?
This *used* to be possible in the xarray data model prior to v0.9.0. `del` should to delete a dimension corresponding to a coordinate variable and all other associated variables.
When we made coordinates optional, I updated `del` to only delete data/coordinate variables. This made sense, but meant there is now no way to get rid of dimensions.
I'd like to suggest two possible fixes:
1. Update `del dataset[key]` to remove all ""orphaned"" dimensions that don't correspond to a dimension on any variable. This would enforce the invariant ""all dimensions on a dataset correspond to a dimension on one of its variables."" If there are other places where we violate this invariant those should be fixed, too.
2. Update `Dataset.dims` to allow deleting elements. Deleting a dimension on a dataset means all associated variables are also deleted.","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-369267269,https://api.github.com/repos/pydata/xarray/issues/1949,369267269,MDEyOklzc3VlQ29tbWVudDM2OTI2NzI2OQ==,5635139,2018-02-28T15:03:56Z,2018-02-28T15:03:56Z,MEMBER,"Hmmm, this is harder than I originally expected. I imagine someone will comment with an easy solution, otherwise I'll have another look ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-369247490,https://api.github.com/repos/pydata/xarray/issues/1949,369247490,MDEyOklzc3VlQ29tbWVudDM2OTI0NzQ5MA==,17178478,2018-02-28T14:00:26Z,2018-02-28T14:00:26Z,NONE,"I don't think it's actually possible to purge `a`, hence why I started an issue rather than SO Q. As you can see, squeeze() removes `b` from the list of dimensions, but not `a` (as `a` has a length 0, not 1). ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693
https://github.com/pydata/xarray/issues/1949#issuecomment-369246561,https://api.github.com/repos/pydata/xarray/issues/1949,369246561,MDEyOklzc3VlQ29tbWVudDM2OTI0NjU2MQ==,5635139,2018-02-28T13:57:18Z,2018-02-28T13:59:43Z,MEMBER,"I think SO is the best place for user Qs, so the answers can be searchable for future generations.
To respond immediately though, have you tried `.squeeze`? Or, to confirm, you actually want to remove `a` rather than `b` here?
```python
In [1]: import xarray as xr
In [2]: test_dataset = xr.Dataset(dict(
...: empty_array=xr.DataArray([], dims='a'),
...: populated_array=xr.DataArray([1], {'b':['1']}, 'b')
...: ))
In [3]: test_dataset
Out[3]:
<xarray.Dataset>
Dimensions: (a: 0, b: 1)
Coordinates:
* b (b) <U1 '1'
Dimensions without coordinates: a
Data variables:
empty_array (a) float64
populated_array (b) int64 1
In [4]: test_dataset.squeeze()
Out[4]:
<xarray.Dataset>
Dimensions: (a: 0)
Coordinates:
b <U1 '1'
Dimensions without coordinates: a
Data variables:
empty_array (a) float64
populated_array int64 1
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,301031693