issues: 1748712825
This data as json
| 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1748712825 | I_kwDOAMm_X85oOz15 | 7904 | Clarifying the meaning of NA in .open_dataset docs | 64946569 | closed | 1 | 2 | 2023-06-08T22:05:35Z | 2023-06-12T23:49:53Z | 2023-06-12T23:49:53Z | NONE | The description of the parameter mask_and_scale says: "If True, replace array values equal to _FillValue with NA and scale values according to the formula original_values * scale_factor + add_offset, where _FillValue, scale_factor and add_offset are taken from variable attributes (if they exist). If the _FillValue or missing_value attribute contains multiple values a warning will be issued and all array values matching one of the multiple values will be replaced by NA. mask_and_scale defaults to True except for the pseudonetcdf backend. This keyword may not be supported by all the backends." It is honestly extremely confusing. There is NA (which is clearly not a NaN). And there is a formula according to which FillValue is constructed. Could anyone provide a clarification for this option, please? |
{
"url": "https://api.github.com/repos/pydata/xarray/issues/7904/reactions",
"total_count": 0,
"+1": 0,
"-1": 0,
"laugh": 0,
"hooray": 0,
"confused": 0,
"heart": 0,
"rocket": 0,
"eyes": 0
} |
completed | 13221727 | issue |