The range of $X$ and $Y$ is the set of positive integers $\mathbb{N}^+$. So the range of $Z$ is the set of all positive rationals $\mathbb{Q}^+$. By “range” I mean the set of values that can be taken with positive probability.
Let’s start with the expectation of $Z$. Since $X$ and $Y$ are independent, $\mathbb{E}[\frac{X}{Y}]=\mathbb{E}[X]\mathbb{E}[\frac{1}{Y}]$. We know $\mathbb{E}[X]=\frac{1}{p}$. For the other bit, use the Taylor expansion $$\operatorname{ln}(1-t)=-\sum_{n=1}^{+\infty}\frac{t^n}{n}$$ for $|t|<1$. We have $$\mathbb{E}[\frac{1}{Y}]=\sum_{n=1}^{+\infty}\frac{1}{n}(1-p)^{n-1}p=\frac{p}{1-p}\sum_{n=1}^{+\infty}\frac{(1-p)^n}{n}\\=-\frac{p\operatorname{ln}(p)}{1-p}.$$ Ultimately we get $\mathbb{E}[Z]=-\frac{\operatorname{ln}(p)}{1-p}$.
Now, for the distribution of $Z$, take any positive rational $q_0$ and write uniquely $q_0=\frac{a}{b}$ where $a,b$ are positive integers that are prime to each other. Write $$\mathbb{P}(Z=q_0)=\mathbb{P}\Big(\bigcup_{n=1}^{+\infty}\{X=na,Y=nb\}\Big)\\=\sum_{n=1}^{+\infty}\mathbb{P}(X=na)\mathbb{P}(Y=nb)\\=\sum_{n=1}^{+\infty}(1-p)^{na-1}p(1-p)^{nb-1}p\\=\frac{p^2}{(1-p)^2}\sum_{n=1}^{+\infty}\big((1-p)^{a+b}\big)^n\\= \frac{p^2}{(1-p)^2}\Big(\frac{1}{1-(1-p)^{a+b}}-1\Big)\\=\frac{p^2}{(1-p)^2}\frac{(1-p)^{a+b}}{1-(1-p)^{a+b}}.$$