Sometimes, while working with dictionaries, we can have a problem in which we have many dictionaries and we are required to sum like keys. This problem seems common, but complex is if the values of keys are list and we need to add elements to list of like keys. Let’s discuss way in which this problem can be solved.
Method : Using list comprehension + items() + sum() This problem can be solved using list comprehension and sum() that can be used to sum the list content and also the items method which can be employed to get the dictionary keys and values.
Python3
# Python3 code to demonstrate working of# Equal Keys List Summation# Using items() + list comprehension + sum()# initializing dictionariestest_dict1 = {'Gfg' : [1, 2, 3], 'for' : [2, 4], 'CS' : [7, 8]}test_dict2 = {'Gfg' : [10, 11], 'for' : [5], 'CS' : [0, 18]}# printing original dictionariesprint("The original dictionary 1 is : " + str(test_dict1))print("The original dictionary 2 is : " + str(test_dict2))# Using items() + list comprehension + sum()# Equal Keys List Summationres = {key: sum(value) + sum(test_dict2[key]) for key, value in test_dict1.items()}# printing result print("The summation of dictionary values is : " + str(res)) |
The original dictionary 1 is : {'CS': [7, 8], 'for': [2, 4], 'Gfg': [1, 2, 3]}
The original dictionary 2 is : {'CS': [0, 18], 'for': [5], 'Gfg': [10, 11]}
The summation of dictionary values is : {'CS': 33, 'for': 11, 'Gfg': 27}
Time Complexity: O(n*n), where n is the length of the list test_dict
Auxiliary Space: O(n) additional space of size n is created where n is the number of elements in the res list
Method#2 : Using for loop
In this method, we first loop through the keys of the first dictionary, and for each key, we check if it exists in the second dictionary. If it does, we sum the values of the two lists using the + operator and store the result in the result_dict. If the key is not present in the second dictionary, we simply sum the values of the list from the first dictionary and store the result in the result_dict. Finally, we loop through the keys of the second dictionary, and for each key that is not already present in the result_dict, we sum the values of the list from the second dictionary and store the result in the result_dict
Python3
dict1 = {'CS': [7, 8], 'for': [2, 4], 'Gfg': [1, 2, 3]}#dictionary input 1dict2 = {'CS': [0, 18], 'for': [5], 'Gfg': [10, 11]}#dictionary input 2result_dict = {}#take empty dictionaryfor key in dict1.keys():#using loop to get keys from dict1 if key in dict2: result_dict[key] = sum(dict1[key] + dict2[key])#summation of keys else: result_dict[key] = sum(dict1[key])for key in dict2.keys():#using loop to get keys from dict2 if key not in result_dict:#summation of keys result_dict[key] = sum(dict2[key])print("The summation of dictionary values is :", result_dict)#print result |
The summation of dictionary values is : {'CS': 33, 'for': 11, 'Gfg': 27}
Time complexity: O(n)
Auxiliary Space: O(n)
Method#3 : Using itertools.chain() and itertools.groupby():
Algorithm:
1. Import the necessary modules, itertools.
2.Define two dictionaries.
3.Create an empty dictionary.
4.Merge the keys of both the dictionaries using chain() function and group them using groupby() function.
5.Find the sum of values of common keys in both the dictionaries, using get() function.
6.Store the result in a new dictionary.
7.Print the new dictionary.
Python3
from itertools import chain, groupbydict1 = {'CS': [7, 8], 'for': [2, 4], 'Gfg': [1, 2, 3]}dict2 = {'CS': [0, 18], 'for': [5], 'Gfg': [10, 11]}# printing original dictionariesprint("The original dictionary 1 is : " + str(dict1))print("The original dictionary 2 is : " + str(dict2)) merged_dict = {}for key, group in groupby(sorted(chain(dict1.keys(), dict2.keys()))): merged_dict[key] = sum(chain(dict1.get(key, []), dict2.get(key, [])))print("The summation of dictionary values is :", merged_dict)#This code is contributed by Jyothi pinjala. |
The original dictionary 1 is : {'CS': [7, 8], 'for': [2, 4], 'Gfg': [1, 2, 3]}
The original dictionary 2 is : {'CS': [0, 18], 'for': [5], 'Gfg': [10, 11]}
The summation of dictionary values is : {'CS': 33, 'Gfg': 27, 'for': 11}
Time Complexity: O(NlogN)
The use of sorted() function makes the time complexity O(NlogN).
The iteration over the merged keys has a time complexity of O(N), as does the iteration over the values of the dictionaries.
The sum() function has a time complexity of O(N).
Space Complexity: O(N)
We are using extra space for the merged dictionary which has the same number of elements as the input dictionaries. Therefore, the space complexity is O(N).
