how to calculate percentage with nested dictionary

Solution 1:

You could use a DataFrame for the first dictionary and a Series for the second and perform an aligned multiplication, then sum:

old_dict = {'X': {'a': 0.69, 'b': 0.31}, 'Y': {'a': 0.96, 'c': 0.04}}
df = pd.DataFrame(old_dict)

inpt = {"name":['X','Y'],"percentage":[0.9,0.1]}
table = pd.DataFrame(inpt)

# convert table to series:
ser = table.set_index('name')['percentage']
# alternative build directly a Series:
# ser = pd.Series(dict(zip(*inpt.values())))

# compute expected values:
out = (df*ser).sum(axis=1).to_dict()

output: {'a': 0.717, 'b': 0.279, 'c': 0.004}