Riccardo Cappuzzo
Riccardo Cappuzzo
Hi @shivanshutiwari35, thanks for offering your help! Yes, you're more than welcome to work on this issue. You might want to work on this a few tests at a time...
Closed by #1618
> From a user standpoint, this separation would make usage more complex. > > Our story with TableVectorizer is that it is a one-stop object to add support for complex...
> And this makes me argue for avoiding composition in how we present things to the user I feel like "the horse is out of the barn" for that part,...
The TableReport is already accepting an`order_by` parameter that allows to sort by a numerical or time column (though it has problems #1464) I think the main issue with doing this...
There are a few different approaches that we can take: - We don't raise errors in either fit or transform if we try to drop a column that isn't found...
> Hello [@rcap107](https://github.com/rcap107) > > Newbie here! > > I ran the exemplary code above, and with a non-existent column `d` As expected, both `drop.fit(df)` and `drop.fit_transform(df)` threw the same...
> okay, I get it now. Hey @Faith-Nchifor, if you are considering working on this issue I would suggest picking a different one, because at the moment the direction we...
From IRL discussion: The current behavior of DropCols is that an exception is raised if one of the columns that isn't supposed to be dropped is missing from the list...
Something else that should be fixed in the same PR is renaming the attributes of `DropCols` and `SelectCols` so they end with `_`, see https://github.com/scikit-learn/scikit-learn/issues/32910