issue_comments
1 row where issue = 134376872 and user = 4992424 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- save/load DataArray to numpy npz functions · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 187245860 | https://github.com/pydata/xarray/issues/768#issuecomment-187245860 | https://api.github.com/repos/pydata/xarray/issues/768 | MDEyOklzc3VlQ29tbWVudDE4NzI0NTg2MA== | darothen 4992424 | 2016-02-22T16:04:39Z | 2016-02-22T16:04:39Z | NONE | Hi @jonathanstrong, Just thought it would be useful to point out that the people who maintain NetCDF is Unidata, a branch of the University Corporation for Atmospheric Research. In fact, netCDF-4 is essentially built on top of HDF5 - a much more widely-known file format, with first-class support including an I/O layer in pandas. While it would certainly be great to "sell" netCDF as a format in the documentation, those of us who still have to write netCDF-based I/O modules for our Fortran models might have to throw up a little in our mouths when we do so... |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
save/load DataArray to numpy npz functions 134376872 |
Advanced export
JSON shape: default, array, newline-delimited, object
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]);
user 1