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- datetime interpolation doesn't work · 4 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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453667107 | https://github.com/pydata/xarray/issues/2667#issuecomment-453667107 | https://api.github.com/repos/pydata/xarray/issues/2667 | MDEyOklzc3VlQ29tbWVudDQ1MzY2NzEwNw== | fujiisoup 6815844 | 2019-01-11T21:46:10Z | 2019-01-11T21:46:10Z | MEMBER | Thanks. Then, it would be probably nice if |
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datetime interpolation doesn't work 398152613 | |
453666317 | https://github.com/pydata/xarray/issues/2667#issuecomment-453666317 | https://api.github.com/repos/pydata/xarray/issues/2667 | MDEyOklzc3VlQ29tbWVudDQ1MzY2NjMxNw== | shoyer 1217238 | 2019-01-11T21:43:08Z | 2019-01-11T21:43:08Z | MEMBER | I think the best we can do is to is use masking on the result, e.g., with |
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datetime interpolation doesn't work 398152613 | |
453665698 | https://github.com/pydata/xarray/issues/2667#issuecomment-453665698 | https://api.github.com/repos/pydata/xarray/issues/2667 | MDEyOklzc3VlQ29tbWVudDQ1MzY2NTY5OA== | fujiisoup 6815844 | 2019-01-11T21:40:50Z | 2019-01-11T21:40:50Z | MEMBER | Is there a good way to convert a timedelta array including In [2]: import pandas as pd In [3]: time = np.array(pd.date_range('15/12/1999', periods=11)) In [4]: time[8: 11] = np.nan In [5]: time In [6]: time.astype(float) In [7]: (time - np.min(time)).astype(float) |
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datetime interpolation doesn't work 398152613 | |
453399209 | https://github.com/pydata/xarray/issues/2667#issuecomment-453399209 | https://api.github.com/repos/pydata/xarray/issues/2667 | MDEyOklzc3VlQ29tbWVudDQ1MzM5OTIwOQ== | fujiisoup 6815844 | 2019-01-11T06:57:01Z | 2019-01-11T06:57:01Z | MEMBER | Oops. This is definitely my bug. This line should return a Variable. I will send a fix. |
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datetime interpolation doesn't work 398152613 |
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