issue_comments

Table actions

5 rows where issue = 1706864252 sorted by updated_at descending

✎ View and edit SQL

This data as json, CSV (advanced)

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

author_association 2

issue 1

  • Anomaly calculation with groupby leaves seasonal cycle · 5 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
1546068136 https://github.com/pydata/xarray/issues/7838#issuecomment-1546068136 https://api.github.com/repos/pydata/xarray/issues/7838 IC_kwDOAMm_X85cJyCo haiboliucu 14111025 2023-05-12T17:33:03Z 2023-05-12T17:33:03Z NONE

Thanks, yes. The remote access and local access are different with xarray v0.20.2. remote:

local access: 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Anomaly calculation with groupby leaves seasonal cycle 1706864252
1546024198 https://github.com/pydata/xarray/issues/7838#issuecomment-1546024198 https://api.github.com/repos/pydata/xarray/issues/7838 IC_kwDOAMm_X85cJnUG dcherian 2448579 2023-05-12T16:52:29Z 2023-05-12T16:52:29Z MEMBER

Thanks! I tracked this down to the difference between reading the file remotely, or downloading first and accessing a local copy on v0.20.2 (the latter is what I used to produce my figures). Can you reproduce? remote = xr.open_dataset( "http://kage.ldeo.columbia.edu:81/SOURCES/.LOCAL/.sst.mon.mean.nc/.sst/dods" ).sst.sel(lat=20, lon=280, method="nearest") local = xr.open_dataset("~/Downloads/data.cdf").sst.sel(lat=20, lon=280, method="nearest")

(remote.groupby("time.month") - remote.groupby("time.month").mean()).plot()

(local.groupby("time.month") - local.groupby("time.month").mean()).plot() 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Anomaly calculation with groupby leaves seasonal cycle 1706864252
1545958981 https://github.com/pydata/xarray/issues/7838#issuecomment-1545958981 https://api.github.com/repos/pydata/xarray/issues/7838 IC_kwDOAMm_X85cJXZF haiboliucu 14111025 2023-05-12T15:56:52Z 2023-05-12T15:58:16Z NONE

v 2022.11.0 v0.20.2 

{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Anomaly calculation with groupby leaves seasonal cycle 1706864252
1545930953 https://github.com/pydata/xarray/issues/7838#issuecomment-1545930953 https://api.github.com/repos/pydata/xarray/issues/7838 IC_kwDOAMm_X85cJQjJ dcherian 2448579 2023-05-12T15:32:47Z 2023-05-12T15:35:02Z MEMBER

Can you compare ds_anom at a point in both versions please? I get a plot that looks quite similar

v0.20.2:

v2022.03.0:

v2023.04.2

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Anomaly calculation with groupby leaves seasonal cycle 1706864252
1545060540 https://github.com/pydata/xarray/issues/7838#issuecomment-1545060540 https://api.github.com/repos/pydata/xarray/issues/7838 IC_kwDOAMm_X85cF8C8 welcome[bot] 30606887 2023-05-12T03:34:09Z 2023-05-12T03:34:09Z NONE

Thanks for opening your first issue here at xarray! Be sure to follow the issue template! If you have an idea for a solution, we would really welcome a Pull Request with proposed changes. See the Contributing Guide for more. It may take us a while to respond here, but we really value your contribution. Contributors like you help make xarray better. Thank you!

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Anomaly calculation with groupby leaves seasonal cycle 1706864252

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]);