Sometimes, while working with Python strings, we can have an option in which we need to perform the task of converting a character matrix to a single string. This can have applications in domains in which we need to work with data. Let us discuss certain ways in which we can perform this task.
Method #1 : Using join() + list comprehension
The combination of the above functionalities can be used to perform this task. In this, we just iterate for all lists and join them using join().
Python3
# Python3 code to demonstrate working of# Convert Character Matrix to single String# Using join() + list comprehension# initializing listtest_list = [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']]# printing original listprint("The original list is : " + str(test_list))# Convert Character Matrix to single String# Using join() + list comprehensionres = ''.join(ele for sub in test_list for ele in sub)# printing resultprint("The String after join : " + res) |
The original list is : [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']] The String after join : gfgisbest
Time Complexity: O(n), where n is the length of the input list. This is because we’re using the join() + list comprehension which has a time complexity of O(n) in the worst case.
Auxiliary Space: O(n), as we’re using additional space res other than the input list itself with the same size of input list.
Method #2: Using join() + chain()
The combination of the above functionalities can be used to perform this task. In this, we perform the task performed by list comprehension by chain() method.
Python3
# Python3 code to demonstrate working of# Convert Character Matrix to single String# Using join() + chain()from itertools import chain# Initializing listtest_list = [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']]# Printing original listprint("The original list is : " + str(test_list))# Convert Character Matrix to single String# Using join() + chain()res = "".join(chain(*test_list))# Printing resultprint("The String after join : " + res) |
The original list is : [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']] The String after join : gfgisbest
Time Complexity: O(n), where n is the length of the input list. This is because we’re using the join() + chain() which has a time complexity of O(n) in the worst case.
Auxiliary Space: O(n), as we’re using additional space res other than the input list itself with the same size of input list.
Method #3 : Here is another approach using sum and map:
Python3
# Python3 code to demonstrate working of# Convert Character Matrix to single String# Using sum() + map()# initializing listtest_list = [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']]# printing original listprint("The original list is : " + str(test_list))# Convert Character Matrix to single String# Using sum() + map()res = ''.join(sum(map(list, test_list), []))# printing resultprint("The String after join : " + res) |
The original list is : [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']] The String after join : gfgisbest
Time complexity: O(n) where n is the total number of elements in the list.
Auxiliary Space: O(n) where n is the total number of elements in the list.
Explanation: The map function maps the lists in the input list to lists and the sum function sums these lists and converts the list of lists to a single list. The join function is used to join all the elements in the list to form a single string.
Method 4 : using the reduce() function from the functools module:
Python3
# Python3 code to demonstrate working of# Convert Character Matrix to single String# Using reduce()from functools import reduce# initializing listtest_list = [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']]# printing original listprint("The original list is : " + str(test_list))# Convert Character Matrix to single String# Using reduce()res = reduce(lambda x, y: x+y, [char for row in test_list for char in row])# printing resultprint("The String after join : " + res) |
The original list is : [['g', 'f', 'g'], ['i', 's'], ['b', 'e', 's', 't']] The String after join : gfgisbest
Time complexity: O(n^2) since we need to iterate over each character in the matrix.
Auxiliary Space: O(n) since we create a new list of characters using a list comprehension.
