pull_requests: 13356616
This data as json
| id | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 13356616 | MDExOlB1bGxSZXF1ZXN0MTMzNTY2MTY= | 59 | closed | 0 | Ensure decoding as datetime64[ns] | 1217238 | Pandas seems to have trouble constructing multi-indices when it's given datetime64 arrays which don't have ns precision. The current version of decode_cf_datetime will give datetime arrays with the default precision, which is us. Hence, when coupled with the dtype restoring wrapper from PR #54, the `to_series()` and `to_dataframe()` methods were broken when using decoded datetimes. | 2014-03-10T01:26:54Z | 2014-03-13T06:58:16Z | 2014-03-12T16:55:57Z | 2014-03-12T16:55:57Z | b1cb962620454febeef888e934debab3fe84818b | 0 | 931db2433594b34396beac945854d655306edc13 | 74d43ffde7f7c285715315f26de39d41c3b931bb | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/59 |
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