The problem of conventional type conversion is quite common and can be easily done using the built-in converters of python libraries. But sometimes, we may require the same functionality in a more complex scenario vis. for keys of list of dictionaries. Let’s discuss certain ways in which this can be achieved.
Method #1 : Naive Method
In the naive method, we employ 2 loops, nested. One for all the dictionaries in the list and the second one for the dictionary key-value pairs in a specific dictionary.
Python3
# Python3 code to demonstrate# Type conversion in list of dicts.# using naive method# initializing list of dictionarytest_list = [{'a' : '1', 'b' : '2'}, { 'c' : '3', 'd' : '4'}]# printing original listprint ("The original list is : " + str(test_list))# using naive method# type conversation in list of dicts.for dicts in test_list: for keys in dicts: dicts[keys] = int(dicts[keys]) # printing resultprint ("The modified converted list is : " + str(test_list)) |
Output :
The original list is : [{'a': '1', 'b': '2'}, {'c': '3', 'd': '4'}]
The modified converted list is : [{'a': 1, 'b': 2}, {'c': 3, 'd': 4}]
Time complexity: O(n*n), where n is the number of key-value pairs in the dictionary.
Auxiliary space: O(n), to store the keys and values in dictionary.
Method #2 : Using items() + list comprehension
This can easily performed using just a one line with the help of list comprehension. The items function can be exploited to extract the list values as when required and list comprehension part handles the iteration part.
Python3
# Python3 code to demonstrate# Type conversion in list of dicts.# using items() + list comprehension# initializing list of dictionarytest_list = [{'a' : '1', 'b' : '2'}, { 'c' : '3', 'd' : '4'}]# printing original listprint ("The original list is : " + str(test_list))# using items() + list comprehension# type conversation in list of dicts.res = [dict([key, int(value)] for key, value in dicts.items()) for dicts in test_list] # printing resultprint ("The modified converted list is : " + str(res)) |
Output :
The original list is : [{'b': '2', 'a': '1'}, {'c': '3', 'd': '4'}]
The modified converted list is : [{'a': 1, 'b': 2}, {'c': 3, 'd': 4}]
Method #3 : Using map() function and a lambda
Another approach that you can use is to use a combination of the map() function and a lambda function to perform the type conversion on the dictionary values.
Here is an example of how this can be done:
This code converts the values in a list of dictionaries from strings to integers. It does this by using the map() function to apply a lambda function to each dictionary in the list. The lambda function creates a new dictionary with the same keys as the original dictionary, but the values are converted to integers using the int() function.
The time complexity of this code is O(n), where n is the number of dictionaries in the list. This is because the code iterates over each dictionary in the list once.
The space complexity of this code is also O(n), because the code creates a new dictionary for each dictionary in the list.
Python3
# create a list of dictionariestest_list = [{'a' : '1', 'b' : '2'}, { 'c' : '3', 'd' : '4'}]# use the map() function to apply the lambda function to each dictionary in the list# the lambda function creates a new dictionary with the keys and values from the original dictionary# but the values are converted to integers using int()result = [{k: int(v) for k, v in d.items()} for d in map(lambda x: dict(x), test_list)]# print the resulting list of dictionariesprint(result)#This code is contributed by Edula Vinay Kumar Reddy |
[{'a': 1, 'b': 2}, {'c': 3, 'd': 4}]
