Python – Vertical Concatenation in Matrix

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”, “geeks”], [“is”, “for”, “best”]] 
Output : [‘Gfgis’, ‘goodfor’, “geeksbest”] 
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 lists
test_list = [["Gfg", "good"], ["is", "for"], ["Best"]]

# printing original list
print("The original list : " + str(test_list))

# using loop for iteration
res = []
N = 0
while 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 + 1

res = [ele for ele in res if ele]

# printing result
print("List after column Concatenation : " + str(res))

Output

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 lists
test_list = [["Gfg", "good"], ["is", "for"], ["Best"]]

# printing original list
print("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))

Output

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 list
test_list = [["Gfg", "good"], ["is", "for"], ["Best"]]

# find the maximum length of a sublist
max_len = max(len(sublist) for sublist in test_list)

# pad the sublists with empty strings to make them the same length
padded_list = [sublist + [''] * (max_len - len(sublist)) for sublist in test_list]

# convert the list to a numpy array
arr = np.array(padded_list)

# use transpose to switch rows and columns
arr_t = arr.T

# use join to concatenate the strings in each row
res = [''.join(row) for row in arr_t]

# print the result
print("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.