Very small Python project

Implement the Random Walk algorithm and apply it to the Twitch graph. Suppose the weight (transition probability) from node i to its neighbor node r is wi, = ¿ where d; is the degree of node i. For instance, in the following graph, the probability of walking from node i to any of its neighbors is ;, i.e., all neighbors are equally possible to be visited. For an initial node of your choice (v0), run your implemented algorithm 100 times and record the frequency of visited nodes. For instance, if in the first and second runs P= {vo, v1, V1, v2, v3} and P = {v0, v0, U1, V1, V3) respectively, then freq(vo) = 3, freq(v1) = 4, freq(v2) = 1, and freq(v3) = 2. Assume t = 5. Is there any correlation between the distance from vo and the frequency of visited nodes? You can use Networkx or any other Python package.