issue_comments

Table actions

2 rows where issue = 931591247 and user = 4160723 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

  • benbovy · 2 ✖

issue 1

  • Increase default `display_max_rows` · 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
872459805 https://github.com/pydata/xarray/issues/5545#issuecomment-872459805 https://api.github.com/repos/pydata/xarray/issues/5545 MDEyOklzc3VlQ29tbWVudDg3MjQ1OTgwNQ== benbovy 4160723 2021-07-01T18:27:04Z 2021-07-01T18:27:04Z MEMBER

From what I see in the examples by @Illviljan , setting display_max_rows affects everything equally, coords, data_vars, and attrs. So there would be no need to treat them separately. Or I misunderstood your comment.

My suggestion is to ignore display_max_rows for the repr of the Dataset.coords and Dataset.data_vars properties, but not for the "coordinates" and "data variables" sections of the Dataset text-based repr. This way we could do print(ds.data_vars) to check that all variables made it into the data set correctly while keeping concise the output of print(ds).

 
{
    "total_count": 4,
    "+1": 4,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Increase default `display_max_rows` 931591247
872009559 https://github.com/pydata/xarray/issues/5545#issuecomment-872009559 https://api.github.com/repos/pydata/xarray/issues/5545 MDEyOklzc3VlQ29tbWVudDg3MjAwOTU1OQ== benbovy 4160723 2021-07-01T07:47:51Z 2021-07-01T07:47:51Z MEMBER

My 2 cents (no strong view either, I'm mostly using the HTML repr with a rather small number of variables):

I do agree with both arguments "fit the screen" vs "need to see all the variables", so why not have different display rules for the Dataset, Dataset.data_vars and Dataset.coords reprs?

For the Dataset repr, I think the motivation is mostly to get a quick overview of the whole dataset and basic answers on questions like:

  • What are the dimensions and their size?
  • How many coordinates and data variables?
  • Is the dataset fully loaded in memory or lazily loaded? Are the variables chunked? What's the type of arrays (dask vs. numpy)?
  • Is there a lot of metadata or no metadata at all (global attributes)?

All those questions can be answered with a short, truncated repr.

For the Dataset.data_vars and Dataset.coords reprs, it's more obvious that we want to see all of them, so I'd suggest not limiting the maximum of rows displayed (or have a much larger limit? but then we duplicate the display options, which is not very nice).

 
{
    "total_count": 2,
    "+1": 2,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   Increase default `display_max_rows` 931591247

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]);