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/pull/7694#issuecomment-1488734179,https://api.github.com/repos/pydata/xarray/issues/7694,1488734179,IC_kwDOAMm_X85YvEfj,35968931,2023-03-29T14:28:12Z,2023-03-29T14:28:12Z,MEMBER,"Hi @harshitha1201 - thanks for this!

We do already have a section covering these methods in https://docs.xarray.dev/en/stable/user-guide/computation.html#missing-values. I suggest that we don't need to duplicate all of this information on the FAQ page. 

That said the examples and explanation you have written here are still useful! Perhaps they can either be used to improve the page I just linked, or go into the docstrings of those particular methods.

For the FAQ page instead I think we probably just want to provide a summary in a couple of sentences and a link to the more detailed information on specific methods. The summary should mention that 
- xarray can handle missing values, 
- it uses `np.NaN` to do so, 
- most computation methods will automatically handle missing values appropriately, 
- aggregation methods have a `skipna` argument,
- plotting will just leave them as blank spaces (link to [plotting page](https://docs.xarray.dev/en/stable/user-guide/plotting.html#missing-values)), 
- we have a set of special methods for manipulating missing and filling values ([link to here](https://docs.xarray.dev/en/stable/user-guide/computation.html#missing-values)).","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,1644759739