issues

Table actions

7 rows where state = "closed" and user = 5572303 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

Suggested facets: created_at (date), updated_at (date), closed_at (date)

type 2

state 1

  • closed · 7 ✖

repo 1

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
230529125 MDU6SXNzdWUyMzA1MjkxMjU= 1420 .equals() on a coordinate takes attributes into comparison chunweiyuan 5572303 closed 0     6 2017-05-22T21:48:44Z 2019-05-23T03:11:33Z 2019-05-23T03:11:33Z CONTRIBUTOR      

Is the following the right behavior? ```

da = xr.DataArray(range(3), [('x', range(2000, 2003))]) ws = xr.DataArray([1 for i in range(3)], [('x', range(2000, 2003))]) da.coords['x'].equals(ws.coords['x']) True da['some_attr'] = 0 da.coords['x'].equals(ws.coords['x']) False `` I'm just trying to see if the coordinates are the same, but somehow the dataarray's attribute becomes part of the comparison. I'd expect that in.identical(), but not in.equals()`.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1420/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue
185017914 MDU6SXNzdWUxODUwMTc5MTQ= 1059 kwarg defaults (join="inner") for DataArray._binary_ops() chunweiyuan 5572303 closed 0     5 2016-10-25T04:45:28Z 2019-01-25T16:50:56Z 2019-01-25T16:50:56Z CONTRIBUTOR      

Currently the default is join="inner". However, there can be applications where the majority of binary operations require join="outer", not "inner".

Would it be advisable to place these default values in some config object the user can set at the beginning of the run script? Or perhaps one already exists but I've failed to locate it.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1059/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue
186036077 MDU6SXNzdWUxODYwMzYwNzc= 1067 Indexing turns 1D coordinates into scalar coordinates chunweiyuan 5572303 closed 0     1 2016-10-28T22:29:41Z 2019-01-22T19:22:17Z 2019-01-22T19:22:17Z CONTRIBUTOR      

Starting with

arr = xr.DataArray(np.arange(0, 7.5, 0.5).reshape(3, 5),dims=('x', 'y'))

This will drop the index on x:

arr[0, :]

but this won't:

arr[slice(0,1), :]

While the laymen would expect them both to return the same thing. Is there a reason to this design choice, or could I file a PR for it?

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1067/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue
225222227 MDExOlB1bGxSZXF1ZXN0MTE4MjU1ODUw 1389 Sortby chunweiyuan 5572303 closed 0     28 2017-04-29T00:44:01Z 2017-05-12T18:36:30Z 2017-05-12T00:29:12Z CONTRIBUTOR   0 pydata/xarray/pulls/1389
  • [x] closes #967
  • [x] tests added / passed
  • [x] passes git diff upstream/master | flake8 --diff
  • [x] whatsnew entry
 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1389/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
200478981 MDExOlB1bGxSZXF1ZXN0MTAxMzM5ODIw 1204 combine_first by using apply_ufunc in ops.fillna chunweiyuan 5572303 closed 0     9 2017-01-12T21:03:53Z 2017-01-23T22:43:32Z 2017-01-23T22:39:57Z CONTRIBUTOR   0 pydata/xarray/pulls/1204

Implementing ops.fillna using apply_ufunc, with a join kwarg. The new ops.fillna is then used to implement combine_first in both DataArray and Dataset objects.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1204/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
186680248 MDU6SXNzdWUxODY2ODAyNDg= 1072 Allow concat() to drop/replace duplicate index labels? chunweiyuan 5572303 closed 0     26 2016-11-01T23:59:56Z 2017-01-23T22:41:22Z 2017-01-23T22:41:22Z CONTRIBUTOR      

Right now, ```

coords_l, coords_r = [0, 1, 2], [1, 2, 3] missing_3 = xr.DataArray([11, 12, 13], [(dim, coords_l)]) missing_0 = xr.DataArray([21, 22, 23], [(dim, coords_r)]) together = xr.concat([missing_3, missing_0], dim='x') together <xarray.DataArray 'missing_3' (x: 6)> array([11, 12, 13, 21, 22, 23]) Coordinates: * x (x) int64 0 1 2 1 2 3 together.sel(x=1) <xarray.DataArray 'missing_3' (x: 2)> array([12, 21]) Coordinates: * x (x) int64 1 1 ```

Would it be OK to introduce a kwarg ("replace"?) that replaces cells of identical coordinates from right to left?

That would render ```

together <xarray.DataArray 'missing_3' (x: 6)> array([11, 21, 22, 23]) Coordinates: * x (x) int64 0 1 2 3 ```

Some people might even want to drop all cells with coordinate collisions (probably not us). If that's the case then the kwarg would be ternary.....

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1072/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed xarray 13221727 issue
185794232 MDExOlB1bGxSZXF1ZXN0OTEyOTA5MzM= 1065 Options to binary ops kwargs chunweiyuan 5572303 closed 0     11 2016-10-27T22:17:16Z 2016-11-12T04:00:10Z 2016-11-12T03:59:42Z CONTRIBUTOR   0 pydata/xarray/pulls/1065

Currently the default is join="inner". However, there can be applications where the majority of binary operations require join="outer", not "inner".

Addresses https://github.com/pydata/xarray/issues/1059

The solution we come up with is adding a default key/value to OPTIONS, and dynamically access/update it in code (_binary_op in both dataarray.py and dataset.py)

We've also added test modules in test_dataarray.py and test_dataset.py. All tests passed.

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/1065/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull

Advanced export

JSON shape: default, array, newline-delimited, object

CSV options: 

CREATE TABLE [issues] (
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [number] INTEGER,
   [title] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [state] TEXT,
   [locked] INTEGER,
   [assignee] INTEGER REFERENCES [users]([id]),
   [milestone] INTEGER REFERENCES [milestones]([id]),
   [comments] INTEGER,
   [created_at] TEXT,
   [updated_at] TEXT,
   [closed_at] TEXT,
   [author_association] TEXT,
   [active_lock_reason] TEXT,
   [draft] INTEGER,
   [pull_request] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [state_reason] TEXT,
   [repo] INTEGER REFERENCES [repos]([id]),
   [type] TEXT
);
CREATE INDEX [idx_issues_repo]
    ON [issues] ([repo]);
CREATE INDEX [idx_issues_milestone]
    ON [issues] ([milestone]);
CREATE INDEX [idx_issues_assignee]
    ON [issues] ([assignee]);
CREATE INDEX [idx_issues_user]
    ON [issues] ([user]);