home / github

Menu
  • Search all tables
  • GraphQL API

issues

Table actions
  • GraphQL API for issues

3 rows where state = "open" and user = 5637662 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

type 2

  • pull 2
  • issue 1

state 1

  • open · 3 ✖

repo 1

  • xarray 3
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
799335646 MDExOlB1bGxSZXF1ZXN0NTY1OTk1OTI3 4857 Add support for errorbars in scatter plots dschwoerer 5637662 open 0     0 2021-02-02T14:33:23Z 2022-06-09T14:50:17Z   CONTRIBUTOR   0 pydata/xarray/pulls/4857
  • [ ] Tests added
  • [ ] Passes pre-commit run --all-files
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst

I have added the possibility to add yerr and/or xerr to Dataset.plot.scatter.

I know that this needs tests and so on, but I wanted to know whether this is of general interest?

I have found https://github.com/pydata/xarray/pull/2264 for dataarrays, which wasn't merged, and one of the issues was that the return type changed, as is here the case.

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/4857/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    xarray 13221727 pull
987559143 MDExOlB1bGxSZXF1ZXN0NzI2NjI3NTQ5 5763 remove _ensure_plottable dschwoerer 5637662 open 0     6 2021-09-03T08:55:19Z 2022-06-09T14:50:16Z   CONTRIBUTOR   0 pydata/xarray/pulls/5763

The plotting backend does more reliable checking and thus removing avoids false negatives, which are causing easily avoidable plot failures

  • [x] Closes #5762
  • [ ] Tests added
  • [ ] Passes pre-commit run --all-files
  • [ ] User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [ ] New functions/methods are listed in api.rst
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/5763/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    xarray 13221727 pull
700907310 MDU6SXNzdWU3MDA5MDczMTA= 4420 Multi-mesh support dschwoerer 5637662 open 0     0 2020-09-14T08:52:46Z 2020-09-14T08:52:46Z   CONTRIBUTOR      

Is your feature request related to a problem? Please describe. I am not sure what the best way to have data from different meshes is. My simulations use logical Cartesian meshes, but they can be of different sizes (number of points). They describe 2D surfaces in 3D and aren't necessarily connected.

Describe the solution you'd like I would like to store the different meshes in the same dataset with a nice interface.

Describe alternatives you've considered I have considered several options: 1) I could use a list of datasets. That would be easy to implement, but it feels wrong, as this is really one dataset. 2) Add another dimension some index for the mesh number. That would require to expand all meshes to the largest one (in each spatial dimension). Then the coordinates (x,y,z) would also be required to be 3D, a 2D slice for each index. That has some overhead, as all structures are expanded, and it is not easy to see what shape each slice has. This might also cause issues with plotting, as the data seems to be 3D rather then 2D. 3) merge all data, e.g. merging all data in x direction, with an index-offset in x, that different meshes have different indices. Then only the y-dimension would need to be alligned, thus it would involve less storage cost. Plotting would work somewhat - only ensuring that non-connected meshes are not plotted connected might be a bit tricky. 4) suffix all data and coordinates with an index. Would allow to e.g. plot by iterating over the index - a variation of 1) but allows to store as one file 5) use unstructured grids. That would avoid the additional storage cost, as the full grid info is anyway stored, but then plotting or searching in the data will be (much) more expensive.

Additional context The data is not point-centered, but area/volume based (see #1475) - thus recovering whether data needs to be plotted together or not in 3) would be doable, but transforming from the xarray format to the format for plt.pcolormesh becomes much harder if not connected meshes are merged.

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/4420/reactions",
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
    xarray 13221727 issue

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]);
Powered by Datasette · Queries took 21.099ms · About: xarray-datasette