issue_comments

Table actions

2 rows where issue = 88897697 and user = 1217238 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

user 1

  • shoyer · 2 ✖

issue 1

  • Examples combining multiple files · 2 ✖

author_association 1

id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
113340207 https://github.com/pydata/xarray/issues/436#issuecomment-113340207 https://api.github.com/repos/pydata/xarray/issues/436 MDEyOklzc3VlQ29tbWVudDExMzM0MDIwNw== shoyer 1217238 2015-06-19T02:00:27Z 2015-06-19T02:00:27Z MEMBER

@j08lue good idea! Right now that page is mostly targeted at non-climate scientists, but it would be nice to include an example for climate scientists, too.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Examples combining multiple files 88897697
112651491 https://github.com/pydata/xarray/issues/436#issuecomment-112651491 https://api.github.com/repos/pydata/xarray/issues/436 MDEyOklzc3VlQ29tbWVudDExMjY1MTQ5MQ== shoyer 1217238 2015-06-17T04:46:52Z 2015-06-17T04:46:52Z MEMBER

Have you tried xray.open_mfdataset? All of the examples should work the same with a dataset loaded with that function as from a single file.

In your case, something like the following should work:

``` python

load data

ds = xray.open_mfdataset('path/to/my/files/*.nc')

calculate anomalies

clim = ds.groupby('time.month').mean('time') anom = ds.groupby('time.month') - clim

plot anomalies over time

(in practice, would probably want to use .sel here to do

labeled lookups)

anom.temperature.isel(x=0, y=0).to_pandas().plot()

plot anomalies over space

plt.imshow(anom.temperature.isel(time=0).values) ```

Plotting is currently not so easy as it should be with xray (hence why you see me exporting everything to pandas), but that's something we plan to start work on very soon.

 
{
    "total_count": 1,
    "+1": 1,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Examples combining multiple files 88897697

Advanced export

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

CSV options: 

CREATE TABLE [issue_comments] (
   [html_url] TEXT,
   [issue_url] TEXT,
   [id] INTEGER PRIMARY KEY,
   [node_id] TEXT,
   [user] INTEGER REFERENCES [users]([id]),
   [created_at] TEXT,
   [updated_at] TEXT,
   [author_association] TEXT,
   [body] TEXT,
   [reactions] TEXT,
   [performed_via_github_app] TEXT,
   [issue] INTEGER REFERENCES [issues]([id])
);
CREATE INDEX [idx_issue_comments_issue]
    ON [issue_comments] ([issue]);
CREATE INDEX [idx_issue_comments_user]
    ON [issue_comments] ([user]);