Given a String Matrix, perform column-wise concatenation of strings, handling variable lists lengths.
Input : [[“Gfg”, “good”], [“is”, “for”]]
Output : [‘Gfgis’, ‘goodfor’]
Explanation : Column wise concatenated Strings, “Gfg” concatenated with “is”, and so on.Input : [[“Gfg”, “good”, “Lazyroar”], [“is”, “for”, “best”]]
Output : [‘Gfgis’, ‘goodfor’, “Lazyroarbest”]
Explanation : Column wise concatenated Strings, “Gfg” concatenated with “is”, and so on.
Method #1: Using loop
This is brute way in which this task can be performed. In this, we iterate for all the columns and perform concatenation.
Python3
# Python3 code to demonstrate working of # Vertical Concatenation in Matrix# Using loop# initializing liststest_list = [["Gfg", "good"], ["is", "for"], ["Best"]]# printing original listprint("The original list : " + str(test_list))# using loop for iterationres = []N = 0while N != len(test_list): temp = '' for idx in test_list: # checking for valid index / column try: temp = temp + idx[N] except IndexError: pass res.append(temp) N = N + 1res = [ele for ele in res if ele]# printing result print("List after column Concatenation : " + str(res)) |
The original list : [['Gfg', 'good'], ['is', 'for'], ['Best']] List after column Concatenation : ['GfgisBest', 'goodfor']
Time Complexity: O(n2)
Space Complexity: O(n)
Method #2 : Using join() + list comprehension + zip_longest()
The combination of above functions can be used to solve this problem. In this, we handle the null index values using zip_longest, and join() is used to perform task of concatenation. The list comprehension drives one-liner logic.
Python3
# Python3 code to demonstrate working of # Vertical Concatenation in Matrix# Using join() + list comprehension + zip_longest()from itertools import zip_longest# initializing liststest_list = [["Gfg", "good"], ["is", "for"], ["Best"]]# printing original listprint("The original list : " + str(test_list))# using join to concaternate, zip_longest filling values using # "fill"res = ["".join(ele) for ele in zip_longest(*test_list, fillvalue ="")]# printing result print("List after column Concatenation : " + str(res)) |
The original list : [['Gfg', 'good'], ['is', 'for'], ['Best']] List after column Concatenation : ['GfgisBest', 'goodfor']
Time Complexity: O(n2) -> (loop+join)
Space Complexity: O(n)
Method #3: Using numpy.transpose() and numpy.ravel()
Step-by-step approach:
- Import the numpy library.
- Initialize the list.
- Find the maximum length of a sublist using a list comprehension and the max() function.
- Pad each sublist with empty strings to make them the same length using another list comprehension.
- Convert the padded list to a numpy array using the np.array() function.
- Use the transpose (T) method to switch rows and columns.
- Use a list comprehension and join to concatenate the strings in each row of the transposed array.
- Print the result.
Below is the implementation of the above approach:
Python3
import numpy as np# initializing listtest_list = [["Gfg", "good"], ["is", "for"], ["Best"]]# find the maximum length of a sublistmax_len = max(len(sublist) for sublist in test_list)# pad the sublists with empty strings to make them the same lengthpadded_list = [sublist + [''] * (max_len - len(sublist)) for sublist in test_list]# convert the list to a numpy arrayarr = np.array(padded_list)# use transpose to switch rows and columnsarr_t = arr.T# use join to concatenate the strings in each rowres = [''.join(row) for row in arr_t]# print the resultprint("List after column concatenation: " + str(res)) |
OUTPUT:
List after column concatenation: ['GfgisBest', 'goodfor']
Time complexity: O(n^2), where n is the number of elements in the input list.
Auxiliary space: O(n), for the numpy array and the padded list.
