issue_comments: 236984774
This data as json
| html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| https://github.com/pydata/xarray/issues/934#issuecomment-236984774 | https://api.github.com/repos/pydata/xarray/issues/934 | 236984774 | MDEyOklzc3VlQ29tbWVudDIzNjk4NDc3NA== | 5635139 | 2016-08-02T17:48:39Z | 2016-08-02T17:48:39Z | MEMBER | That's very clear @shoyer. I know you've discussed in the past whether indexes are really that different from arrays (they are treated very different in pandas, for example). To reiterate the above, the only real difference is one is designed for lookups (and so uses a hash table), and the other is designed for data access (and so mutation is easier). We try to never use mutation, but our data is not that big, so making a copy is generally OK. But that's probably not the main use case. Another option (potentially 1b in your list) is to slice the array rather than select from an index - i.e. sugar over @fmaussion 's solution above. Not as fast to do multiple times, but simple and probably as fast to do a single time. Or to add that to the docs. |
{
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
168901028 |