Pareto Random Variable-Conditional Expectation Logic

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Question:

$$\text {Let X be a Pareto random variable with } \lambda = 3. $$

$$ Find: E[X | X > 0] $$

The solution given skips some steps which makes it a bit unclear to me. It makes sense logically but I want to derive the solution using symbols.

I tried doing this:

$$ \sum_{x=0}^\infty x * \frac{Pr[X > 0, X=x]} {Pr [X>0]} $$

The solution is just this:

$$ E[X | X > 0] = \frac{E[X]}{Pr[X>0]} $$

which leads me to believe that my expression simplifies to this:

$$ \frac{1}{Pr[X>0]}\sum_{x=0}^\infty x * Pr[X=x] = \frac{E[X]}{Pr[X>0]} $$

What is the logic that makes $$ Pr[X>0, X = x] = Pr[X=x]? $$

I tried doing this also using the Bayes rule as well, like this:

$$ \sum_{x=0}^\infty x * \frac{Pr[X>0 | X = x] * Pr[X = x]}{Pr[X>0]} $$

which would imply that $$ Pr[X>0 | X = x] = 1 $$ to give us the same answer as above.

Can somebody explain this logic to me? For some reason this escapes me and losing sleep over this sucks. Thanks for any help.

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$$\mathbb{E}[X]=\mathbb{E}[X|X>0]Pr(X>0)+\mathbb{E}[X|X=0]Pr(X=0)$$

Hence

$$\mathbb{E}[X]=\mathbb{E}[X|X>0]Pr(X>0)+0$$

That is $$\mathbb{E}[X]=\mathbb{E}[X|X>0]Pr(X>0)$$

Final conclusion:

$$\mathbb{E}[X|X>0]=\frac{\mathbb{E}[X]}{Pr(X>0)}$$

Remark:

$$Pr(X>0, X=x)=Pr(X=x)$$ is not true when $x=0$.