Is there advice around handling NaNs and how to translate Numpy code to using the Array API?

In particular I have code like np.nanmin(X, axis=0) that I would like to rewrite so that it works with Numpy, Torch, etc arrays.

To me the "obvious" translation seems to be xp.min(X[~xp.isnan(X)], axis=0) but this doesn't work if X has a shape like (7500, 4) (here xp is the namespace of the array X). Another option I looked for is a where= argument to min(), but that doesn't exist unfortunately.

Does anyone have advice on this topic or knows if there is work planned on this?