issues: 188996339
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| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 188996339 | MDU6SXNzdWUxODg5OTYzMzk= | 1115 | Feature request: Compute cross-correlation (similar to pd.Series.corr()) of gridded data | 6334793 | closed | 0 | 31 | 2016-11-13T21:29:04Z | 2020-05-25T16:57:48Z | 2020-05-25T16:57:48Z | NONE | As a earth scientist regularly dealing with 3D data (time, latitude, longitude), I believe it would be great to be able to perform cross-correlation on DataArrays by specifying the axis. It's usage could look like: a.corr(b, axis = 0). It would be even more useful if the two arrays need not have the same dimensions (e.g. 'b' could be a time series). Currently, the only way to compute this that I am aware of, is by looping through each grid, converting the time series to pd.Series(), and then computing the correlation. This takes a long time. Would also appreciate suggestions to a faster algorithm. |
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completed | 13221727 | issue |