<｜begin▁of▁sentence｜>### Instruction:
As a skilled baker, imagine you've been keeping a meticulous ledger where each entry details which ingredients are often used together, as well as the frequency of their combinations—a sort of recipe web, if you will. This ledger has matured into a complex record, akin to a dictionary of dictionaries, where each key represents an ingredient and each associated value is yet another dictionary detailing the ingredients it pairs with and the number of times this combination has been used.

For instance, your ledger might resemble something like this: 

```json
{
    "Flour": {"Yeast": 10, "Salt": 7},
    "Yeast": {"Flour": 10, "Sugar": 5},
    "Salt": {"Flour": 7},
    "Sugar": {"Yeast": 5} 
}
```

In this scenario where the key-value pairs represent ingredients and their connection weights (in the context of recipe frequency), could you demonstrate how to transpose this intricate web of ingredients into a visual map or graph, using a tool such as NetworkX? Furthermore, how would you go about displaying this graph in such a manner that it clearly exhibits the ingredients (nodes) along with the number of times they have been paired (weights on the edges)?
### Response:
import networkx as nx

dod = {
    0: {1: {'weight': 1}},
    1: {2: {'weight': 2}, 3: {'weight': 3}},
    2: {},
    3: {}
}

G = nx.from_dict_of_dicts(dod, create_using=nx.Graph)
print(G.edges(data=True))
<|EOT|>
