issues

Table actions

2 rows where repo = 13221727, state = "closed" and user = 90768774 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 · 2 ✖

repo 1

  • xarray · 2 ✖
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
1841586869 PR_kwDOAMm_X85XcrvT 8057 Count documentation Articoking 90768774 closed 0     5 2023-08-08T15:59:03Z 2023-08-09T13:50:58Z 2023-08-09T13:50:54Z CONTRIBUTOR   0 pydata/xarray/pulls/8057
  • [x] Closes #8055
  • [x] User visible changes (including notable bug fixes) are documented in whats-new.rst

I've changed the example to include a 0 value which clearly shows that only NA values are ignored in the count. I've only modified the "see also" section for count since as mentioned in #8055 it is a bit of an outlier among the aggregation methods. I believe that this is not a long term fix since the single line summary of the method is of little use, but at least with this no one will have to take a look at the source code to quickly get what count does.

Feel free to correct any problems or suggest any changes, as I am quite new to contributing to projects like this and have little idea of what I'm doing :sweat_smile: 

{
    "url": "https://api.github.com/repos/pydata/xarray/issues/8057/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
     xarray 13221727 pull
1841227199 I_kwDOAMm_X85tvuW_ 8055 Documentation of `Dataset.count()` is ambiguous Articoking 90768774 closed 0     3 2023-08-08T12:35:59Z 2023-08-09T13:50:56Z 2023-08-09T13:50:56Z CONTRIBUTOR      

What is your issue?

Hello everyone!

I've noticed that the documentation for Dataset.count and DataArray.count is a little unclear with respect to what it actually does. In my experience, it's not immediately obvious when looking at this site whether zero values are counted or not.

The given example does not contain a 0 value that would clarify this, and what is worse is that the "see also" section points to np.count and to dask.array.count which do not exist. The closest NumPy equivalent is np.count_nonzero, which has a different behavior to the xarray count method. The xarray count is actually equivalent to Pandas DataFrame.count, which count all non-NA values including 0.

I would take a shot at writing a clearer docstring but I'm not sure how to do that using the generate_aggregations.py file...

 
{
    "url": "https://api.github.com/repos/pydata/xarray/issues/8055/reactions",
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   completed 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]);