BUG: Groupby.sum, DataFrame.sum and Series.sum for object type should be NA instead of 0 for all-nan values
- [ ] partly addresses #60229
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [ ] Added [type annotations](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#type-hints) to new arguments/methods/functions.
- [ ] Added note to whatsnew/v3.0.0.rst
This pull request is stale because it has been open for thirty days with no activity. Please [update](https://pandas.pydata.org/pandas-docs/stable/development/contributing.html#updating-your-pull-request) and respond to this comment if you're still interested in working on this. @snitish - This looks good to me if you'd like to reopen. I'm handling the string case in #60936 @rhshadrach sure I'd be happy to. There was some debate on the original thread on whether the default sum value for `object` dtype should be `NA` or `""` (empty string). Any thoughts on this? > There was some debate on the original thread on whether the default sum value for `object` dtype should be `NA` or `""` (empty string). Any thoughts on this?

For object dtype, I'm only seeing support for NA in that thread. Am I missing any contrary opinions? The only hesitation I see is [@Dr-Irv on how this impacts users](https://github.com/pandas-dev/pandas/issues/60229#issuecomment-2529761812), but I do not see an easy deprecation path and I am comfortable with listing this in the breaking changes for 3.0

When I say NA here, I mean "the NA value for the given dtype". For object dtype, the NA value is `np.nan`. Thanks for approving, @WillAyd. This PR still doesn't address the issue for `DataFrame.sum()` and `Series.sum()`. I'm working on that. Closing this so someone else can take over. I ran into too many issues trying to support this behavior for object dtype, and not sure if it's worth it.