I want to preface this with: I am not the best statistician. So please bear with me if this is either really simple or riddled with errors.
I have a dataset of geographic areas classified by decile. I have been able to gather a number of events in each decile and calculate an expected number of events in each decile based on population sizes. These are not the true numbers as this is a dummy dataset, but the pattern is very similar. Red is observed.
Decile 5 and 6 are obviously very similar. However, there is a difference in Obs/Exp on the lower and higher ends. My question is: how can I show if the differences are statistically significant or not?
I recognise that each individual point on its own does not have enough degrees of freedom (N-1 = 0 as I have one point for each decile). There are several areas included in each decile, so I do have more degrees of freedom available. However, many have a value an observed value of 0. Can anyone advise before I go too far down a rabbit hole of wrongness? Thanks very much in advance.

Deciles are calculated based on a score. It's a standard way of classifying areas here, it seems.
I want to use these values because, if I show them in a meeting, I know someone is going to ask "are those differences statistically significant?" Decile 1 is very likely a significant difference just looking at it, but it's not so clear for 3 and 4; maybe even 8.
– JamesW Dec 23 '22 at 14:16