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1 row where comments = 3, "created_at" is on date 2023-12-10 and user = 14371165 sorted by updated_at descending
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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2034462507 | PR_kwDOAMm_X85hniLB | 8535 | Filter null values before plotting | Illviljan 14371165 | closed | 0 | 3 | 2023-12-10T17:31:27Z | 2023-12-13T15:44:55Z | 2023-12-13T15:44:55Z | MEMBER | 0 | pydata/xarray/pulls/8535 | I noticed that seaborn's plot was responding much faster than xarray's version with the same data. Turn's out seaborn drops any nulls: https://github.com/mwaskom/seaborn/blob/056413d7393e3daec597d430c076e45938d53376/seaborn/relational.py#L399
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xarray 13221727 | pull |
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