one more: `stats` skew and kurtosis divide by variance which is zero

```
>>> stats.poisson.stats(1e-10)
(array(1e-10), array(1e-10))
>>> stats.poisson.stats(1e-20)
(array(9.9999999999999995e-21), array(9.9999999999999995e-21))
>>> stats.poisson.stats(1e-20, moments='mvsk')
(array(9.9999999999999995e-21), array(9.9999999999999995e-21), array(10000000000.0), array(1e+20))
>>> stats.poisson.stats(1e-100, moments='mvsk')
(array(1e-100), array(1e-100), array(1.0000000000000001e+50), array(1e+100))
```

I have no idea what skew and kurtosis of a one point distribution are. I would have though nan, nan, but from the limit it looks like inf, inf


unlikely usecase but weird limit:
```
>>> stats.poisson.interval(0.95, 1e-8)
(0.0, 0.0)
>>> stats.poisson.interval(0.95, 1e-10)
(0.0, 0.0)
>>> stats.poisson.interval(0.95, 1e-20)
(1e+100, 0.0)
>>> stats.poisson.interval(0.95, 1e-30)
(1e+100, 0.0)
```