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Efficiently Aggregating Data from Multiple Dictionaries
When working with multiple dictionaries, the need may arise to merge their data, collecting values for matching keys into a new dictionary. This task poses a challenge when the dictionaries may contain keys that are missing in others.
To address this challenge effectively, we can utilize the defaultdict from the collections module. Here's how it works:
from collections import defaultdict d1 = {1: 2, 3: 4} d2 = {1: 6, 3: 7} dd = defaultdict(list) for d in (d1, d2): # Include all dictionaries here for key, value in d.items(): dd[key].append(value)
This code iterates over each dictionary, adding each key-value pair to the defaultdict. The defaultdict automatically initializes missing keys with an empty list. Thus, when a key is encountered in a dictionary but not in the previous ones, a new list is created for its values.
The final result obtained in dd is a defaultdict where each key corresponds to a list of values collected from all the input dictionaries.
print(dd) # Result: defaultdict(<type 'list'>, {1: [2, 6], 3: [4, 7]})
This solution ensures efficient and comprehensive data aggregation from multiple dictionaries, handling even cases with missing keys.
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