pratyushsharan

I won't say this is a bug, as `union` was supposed to work with DatetimeIndex only, rather than list[DatetimeIndex]. For that purpose, `union_many` is supposed to be used, which will...

I believe the issue is 2-fold: - using `pd.Grouper(..., freq="D")` creates an empty group when a date is missing - this I think is by design because we set `freq="D"`....

> Further, using `pd.Grouper(..., freq=None)` does not solve the issue, as I want to group by the date component. Can you please elaborate? `pd.Grouper(..., freq=None)` will group by whatever `...`...

I see - my point was that you can replicate `groupby` simply by setting `freq=None` in Grouper. Setting `freq='D'` results in a more resampling like approach. I believe this is...

Can you give an example of where `pd.Grouper(..., freq=None)` would fail to match with `.groupby()`? > as surely both `.groupby` and `pd.Grouper` are resampling? I wouldn't equate both of these...

Maybe we should just add in documentation that setting `freq != None` would result in a more resampling like approach.

@jreback any thoughts if this should be treated as a bug or a documentation issue (enhancement)?

Can you please provide with an example of what is broken?

While this is a bug, I would say that the second test actually gives the correct results (because you're adding one month at a time, when you add 1 month...

I had another look into this, looks like the problem is inside cython code. Applying offset to`df['S']` does this: `months = (kwds.get("years", 0) * 12 + kwds.get("months", 0)) * self.n`...