issue_comments: 112984626
This data as json
html_url | issue_url | id | node_id | user | created_at | updated_at | author_association | body | reactions | performed_via_github_app | issue |
---|---|---|---|---|---|---|---|---|---|---|---|
https://github.com/pydata/xarray/issues/435#issuecomment-112984626 | https://api.github.com/repos/pydata/xarray/issues/435 | 112984626 | MDEyOklzc3VlQ29tbWVudDExMjk4NDYyNg== | 6405510 | 2015-06-18T00:16:19Z | 2015-06-18T00:16:19Z | NONE | xray definitely seems to be the correct tool, as you suggested. For the record, this is my first pass at coming up with the Dataset:
Full notebook: https://github.com/richardotis/pycalphad/blob/178f150b492099c32e197b417c11729f12d6dfe8/research/xrayTest.ipynb I decided I'm better off giving each phase its own Some initial queries of the data seem to function well and at a fraction of the memory cost of the pandas-based approach, so I'm feeling optimistic here. |
{ "total_count": 0, "+1": 0, "-1": 0, "laugh": 0, "hooray": 0, "confused": 0, "heart": 0, "rocket": 0, "eyes": 0 } |
88868867 |