(Newbie) Decision Tree Classifier Splitting precedure
sklearn doesn't know that your feature is categorical; it's treating it as continuous, for which only splits of the form $x \leq \alpha$ are checked, so your second listed split candidate isn't actually a candidate.

In general, sklearn doesn't support categorical variables (yet?), and you'll need to encode it differently (one-hot?) if you want different behavior.

See also
https://datascience.stackexchange.com/a/52103/55122
how to make a decision tree when i have both continous and categorical variables in my dataset?