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- lazily load dask arrays to dask data frames by calling to_dask_dataframe · 7 ✖
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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340127569 | https://github.com/pydata/xarray/pull/1489#issuecomment-340127569 | https://api.github.com/repos/pydata/xarray/issues/1489 | MDEyOklzc3VlQ29tbWVudDM0MDEyNzU2OQ== | jmunroe 6181563 | 2017-10-28T00:46:58Z | 2017-10-28T00:46:58Z | CONTRIBUTOR | @shoyer Sound good. Thanks. |
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lazily load dask arrays to dask data frames by calling to_dask_dataframe 245624267 | |
338118973 | https://github.com/pydata/xarray/pull/1489#issuecomment-338118973 | https://api.github.com/repos/pydata/xarray/issues/1489 | MDEyOklzc3VlQ29tbWVudDMzODExODk3Mw== | jmunroe 6181563 | 2017-10-20T06:36:43Z | 2017-10-20T06:36:43Z | CONTRIBUTOR | I don't understand how only test (TestDataArrayAndDataset::test_to_dask_dataframe_2D) can pass on TravisCI yet fail on Appveyor. |
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lazily load dask arrays to dask data frames by calling to_dask_dataframe 245624267 | |
335719811 | https://github.com/pydata/xarray/pull/1489#issuecomment-335719811 | https://api.github.com/repos/pydata/xarray/issues/1489 | MDEyOklzc3VlQ29tbWVudDMzNTcxOTgxMQ== | jmunroe 6181563 | 2017-10-11T07:55:44Z | 2017-10-11T07:55:44Z | CONTRIBUTOR | Hi @shoyer and @jhamman . Thanks for your patience. Please let me know if there is still anything needed to be done on this PR. |
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lazily load dask arrays to dask data frames by calling to_dask_dataframe 245624267 | |
335316753 | https://github.com/pydata/xarray/pull/1489#issuecomment-335316753 | https://api.github.com/repos/pydata/xarray/issues/1489 | MDEyOklzc3VlQ29tbWVudDMzNTMxNjc1Mw== | jmunroe 6181563 | 2017-10-09T23:28:45Z | 2017-10-09T23:28:45Z | CONTRIBUTOR | Hi @jhamman. Thanks for the nudge. I'll look at this again today and either a) just get it done or b) ask for help where needed. |
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lazily load dask arrays to dask data frames by calling to_dask_dataframe 245624267 | |
327073701 | https://github.com/pydata/xarray/pull/1489#issuecomment-327073701 | https://api.github.com/repos/pydata/xarray/issues/1489 | MDEyOklzc3VlQ29tbWVudDMyNzA3MzcwMQ== | jmunroe 6181563 | 2017-09-05T05:19:08Z | 2017-09-05T05:19:08Z | CONTRIBUTOR | Sorry for the delay. I think this task is now complete. |
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lazily load dask arrays to dask data frames by calling to_dask_dataframe 245624267 | |
322022140 | https://github.com/pydata/xarray/pull/1489#issuecomment-322022140 | https://api.github.com/repos/pydata/xarray/issues/1489 | MDEyOklzc3VlQ29tbWVudDMyMjAyMjE0MA== | jmunroe 6181563 | 2017-08-13T05:04:11Z | 2017-08-13T05:04:11Z | CONTRIBUTOR | I agree that using dask.dataframe.from_array and dask.dataframe.concat should work. Sorry I haven't had a chance to get back to this recently. I'll try to make the change early next week. |
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lazily load dask arrays to dask data frames by calling to_dask_dataframe 245624267 | |
318246117 | https://github.com/pydata/xarray/pull/1489#issuecomment-318246117 | https://api.github.com/repos/pydata/xarray/issues/1489 | MDEyOklzc3VlQ29tbWVudDMxODI0NjExNw== | jmunroe 6181563 | 2017-07-27T03:08:35Z | 2017-07-27T03:08:35Z | CONTRIBUTOR | After working on this for a little while, I agree that this really should be a to_dask_dataframe() method. I'll make that change. |
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lazily load dask arrays to dask data frames by calling to_dask_dataframe 245624267 |
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