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- Towards a (temporary?) workaround for datetime issues at the xarray-level · 3 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 276719997 | https://github.com/pydata/xarray/issues/1084#issuecomment-276719997 | https://api.github.com/repos/pydata/xarray/issues/1084 | MDEyOklzc3VlQ29tbWVudDI3NjcxOTk5Nw== | jreback 953992 | 2017-02-01T17:18:17Z | 2017-02-01T17:18:17Z | MEMBER | @spencerahill as I said above, you should not need to subclass at all, just define a new frequency, maybe something like |
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Towards a (temporary?) workaround for datetime issues at the xarray-level 187591179 | |
| 276168323 | https://github.com/pydata/xarray/issues/1084#issuecomment-276168323 | https://api.github.com/repos/pydata/xarray/issues/1084 | MDEyOklzc3VlQ29tbWVudDI3NjE2ODMyMw== | jreback 953992 | 2017-01-30T19:43:09Z | 2017-01-30T19:43:09Z | MEMBER | @jhamman you just need a different frequency, in fact this one is pretty close: https://github.com/pandas-dev/pandas/blob/master/pandas/tseries/offsets.py#L2257 just a matter of defining a fixed-day month frequency (numpy has this by default anyhow). PeriodIndex would then happily take this. |
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Towards a (temporary?) workaround for datetime issues at the xarray-level 187591179 | |
| 275969458 | https://github.com/pydata/xarray/issues/1084#issuecomment-275969458 | https://api.github.com/repos/pydata/xarray/issues/1084 | MDEyOklzc3VlQ29tbWVudDI3NTk2OTQ1OA== | jreback 953992 | 2017-01-30T02:42:58Z | 2017-01-30T02:42:58Z | MEMBER | just my 2c here. You are going to end up writing a huge amount of code to re-implement essentially |
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Towards a (temporary?) workaround for datetime issues at the xarray-level 187591179 |
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