When one category is composed of NANs (but other columns contain good data), pairplot fails:
For example, in the iris dataset, if all measurements of a certain species are missing measurements for "petal_width", pairplot fails. Bummer, because there are good measurements for sepal_length, etc. ! Just because one type of data is missing, doesn't mean the other kinds aren't useful to look at!
iris.loc[(iris.species=='setosa'), 'petal_width']=pd.np.nan
Gives the error:
ZeroDivisionError: 0.0 cannot be raised to a negative power
Any stragegies to fix?
Looked here, and here, without much illumination. Github indicates it's been fixed, but still getting the error in Seaborn 0.9.