issue_comments
5 rows where author_association = "CONTRIBUTOR" and issue = 324740017 sorted by updated_at descending
This data as json, CSV (advanced)
Suggested facets: created_at (date), updated_at (date)
issue 1
- holoviews / bokeh doesn't like cftime coords · 5 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
453278625 | https://github.com/pydata/xarray/issues/2164#issuecomment-453278625 | https://api.github.com/repos/pydata/xarray/issues/2164 | MDEyOklzc3VlQ29tbWVudDQ1MzI3ODYyNQ== | jbusecke 14314623 | 2019-01-10T22:24:50Z | 2019-01-10T22:24:50Z | CONTRIBUTOR | I have taken a swing at restoring the internal plotting capabilities in #2665. Feedback would be very much appreciated since I am still very unfamiliar with the xarray plotting internals. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
holoviews / bokeh doesn't like cftime coords 324740017 | |
404500806 | https://github.com/pydata/xarray/issues/2164#issuecomment-404500806 | https://api.github.com/repos/pydata/xarray/issues/2164 | MDEyOklzc3VlQ29tbWVudDQwNDUwMDgwNg== | aidanheerdegen 6063709 | 2018-07-12T12:50:09Z | 2018-07-12T12:50:09Z | CONTRIBUTOR | Sounds like a great idea. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
holoviews / bokeh doesn't like cftime coords 324740017 | |
404468603 | https://github.com/pydata/xarray/issues/2164#issuecomment-404468603 | https://api.github.com/repos/pydata/xarray/issues/2164 | MDEyOklzc3VlQ29tbWVudDQwNDQ2ODYwMw== | aidanheerdegen 6063709 | 2018-07-12T10:35:04Z | 2018-07-12T10:35:04Z | CONTRIBUTOR | Hi @rabernat, I apologise if what I said is discouraging. I didn't intend it that way. It was the result of exasperation, as I think array is a fantastic tool, and I thought with the development of cftime support all barriers to widespread adoption had pretty much been overcome. When I said "another" it was in reference to the previous barrier of not supporting long time, or old time, indices which had since been overcome As far as recommending, it is to the researchers at the centre of excellence where I am one of the people who is paid to support climate models and the support infrastructure to run and analyse their outputs. I guess I've outed myself as one of those paid computational support staff you referred to. My initial comment above was a clumsy attempt to highlight what I thought was an important feature to support to further increase xarray adoption. From my perspective as someone who has to support users I'm often having to decide what I think the majority of users will be able to use efficiently, taking into account very wide levels of expertise and motivation. Before the cftime upgrades I did not wholeheartedly evangelise for xarray adoption because I knew there were many cases where it was not simple and easy to use. For every edge and corner case I have to support users when they encounter them. In some ways, having a tool that can do such amazing things as xarray, but which don't work in some circumstances for some datasets is very frustrating for users. It can take a lot of work to find out what doesn't work. Having said which, we're currently doing half way through a 2 hour training session for xarray for researchers in the CoE who are interested, but not being able to easily plot cftime datasets will harm adoption, and all those who are volunteering their time developing xarray want it to be adopted as widely as possible right? Thanks for the pointer to the contributor guide, I did read it, and I will try and find some time to make a positive contribution to xarray. I had started down that path already (https://github.com/pydata/xarray/issues/2244) |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
holoviews / bokeh doesn't like cftime coords 324740017 | |
404404401 | https://github.com/pydata/xarray/issues/2164#issuecomment-404404401 | https://api.github.com/repos/pydata/xarray/issues/2164 | MDEyOklzc3VlQ29tbWVudDQwNDQwNDQwMQ== | aidanheerdegen 6063709 | 2018-07-12T06:32:20Z | 2018-07-12T06:32:20Z | CONTRIBUTOR | Darn. Just when I thought the time stuff was sorted. This is (yet another) deal breaker as far as recommending mass adoption goes. Is there an estimate when, or if, |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
holoviews / bokeh doesn't like cftime coords 324740017 | |
403950093 | https://github.com/pydata/xarray/issues/2164#issuecomment-403950093 | https://api.github.com/repos/pydata/xarray/issues/2164 | MDEyOklzc3VlQ29tbWVudDQwMzk1MDA5Mw== | jbusecke 14314623 | 2018-07-10T20:10:16Z | 2018-07-10T20:10:16Z | CONTRIBUTOR | I encountered this problem right now with the xarray built-in plotting. Does anybody know a workaround for the xarray plotting by any chance? |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
holoviews / bokeh doesn't like cftime coords 324740017 |
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 2