Michael Waskom

heard of it ;) https://github.com/mwaskom/seaborn/blob/02df7590c70ca8f68282ed941b98410580c55aa9/doc/tools/nb_to_doc.py#L4

I would prefer that the notebook cleaning be more aggressive than what currently happens, although I've not checked recently as to whether the nbstripout tool has progressed since I borrowed...

Had that thought too ;) https://github.com/mwaskom/seaborn/issues/2635

I can't replicate this with the following versions ```python seaborn 0.13.0.dev0 matplotlib 3.7.0 ``` What version of matplotlib are you using? Can you try on the most recent released versions...

Ah, I see. Yeah; could probably avoid it using this: https://github.com/mwaskom/seaborn/blob/242a3312b6742f5b255c7ad6bccb7228839c9419/seaborn/utils.py#L852 (Although I think this needs to be expanded to include the newer layout-related parameters).

> a parameter to so.Hist() This wouldn't make sense unless you want to use the same weight for all values (when would you want that). > a parameter to so.Plot()...

My guess would be that this is a floating point issue: bars are stacked when they have exactly the same position and, due to floating point errors, that won't necessarily...

Floating point error is not stochastic, so just repeatedly running the script several times and seeing the same output would not be surprising.

FWIW while I can reproduce the issue when i run your code, the "MWE" remains much too complicated to play around with to try to identify any other hypotheses. If...

Thanks, this is *much* easier to work with. In fact it can be reduced even further: ```python data = pandas.DataFrame({ 'pos': ['A', 'A', 'A', 'B', 'B'], 'grp': ['a', 'b', 'c',...