Let X be a random variable taking values in N
$ \sum_{k \geq 0} \mathbb{P} (X>k) \dots (0)$
$= \sum_{k \geq 0} \sum_{i \geq k+1} \mathbb{P}(X=i) \dots (1)$
$= \sum_{i \geq 1} \sum_{k=0}^{i-1}\mathbb{P}(X=i) \dots (2) $
$= \sum_{i \geq1} i \mathbb{P}(X=i) \dots (3) $
$= \mathbb{E} [X] $
I am having a problem with the double sum, I don't see how to think of coming up with this, or how do we go from (0) to (2) , the way I reason by default is like :
$\mathbb{E} [X] = \sum_{k \in N} k \mathbb{P}(X=k) = 1 P(1) + 2 P(2) + ... $ then I block
I'm not sure if this is "visual" in the sense that you want, but I think the following is a nice illustration. As you note, we have $\mathbb{E}[X]=\sum_{n=1}^{\infty}n\mathbb{P}(X=n)$. Think of this as summing all the terms in the following picture: $$ \begin{matrix} \mathbb{P}(X=1)&&\\ \mathbb{P}(X=2)&\mathbb{P}(X=2)&\\ \mathbb{P}(X=3)&\mathbb{P}(X=3)&\mathbb{P}(X=3)\\ \vdots&&&\ddots \end{matrix} $$ Now, if you sum these terms row by row, you get $\sum_{n=1}^{\infty}n\mathbb{P}(X=n)$. If you instead sum column by column, you get $\sum_{n=1}^{\infty}\mathbb{P}(X\ge n)$.
You can picture any exchange of double sums in a similar manner. The mathematical justification for this and much more general types of exchanges is given by Fubini's and/or Tonelli's theorem.