Given a dictionary, I want the sum of the values of Node 1 with Bank 1, Node 2 with Bank 2 and so on.

data1 = {"Node 1": 256,"Node 2":25,"Bank 1":16,"Bank 2":20}

Expected Output: 272 45

CodePudding user response：

I'm working under the assumption that all your values look exactly like that

You can first split your nodes and banks

nodes = {k:v for k,v in data1.items() if k.startswith('Node')}
banks = {k:v for k,v in data1.items() if k.startswith('Bank')}

Then just sum the values of the arrays

np.array(list(nodes.values()))   np.array(list(banks.values()))

CodePudding user response：

If all your dictionary will contain are banks and nodes (and without duplicates or missing values), this is easy.

1. Get the number n of pairs (which is half the number of elements in the dictionary).
2. Use a for loop with n iterations.
3. In each iteration, index the values you need and add them up.

Here is an example to get them as a list.

from json import dumps
data1 = {"Node 1": 256, "Node 2": 25, "Bank 1": 16, "Bank 2": 20}

sums = [0] * len(data1) // 2

for i, sum in enumerate(sums):
    sums[i] = data1[f"Node {i   1}"]   data1[f"Bank {i   1}"]

print(sums)

NOTE: It's ususally un-Pythonic to use an index for lists, but I think this is a really straightforward answer to your question.

CodePudding user response：

This code will sum all the matching Node-Bank pairs and ignore the rest.

data1 = {"Node 1": 256,"Node 2":25, "Bank 1":16,"Bank 2":20}

keys = set([key if "Node" in key else "" for key in list(data1.keys())])
keys.remove("")

for key in keys:
    if "Bank "   str(key.split(" ")[1]) in data1.keys():
        print(data1[key]   data1["Bank "   str(key.split(" ")[1])], end=" ")