Python | Nth Column vertical string in Matrix

Sometimes, while working with Python Matrix, we can have a problem in which we need to access the Matrix in vertical form and extract strings from same, that too as a string, not merely as a list of characters. This task has it’s application in gaming in which we need to extract string during crosswords. Let’s discuss a way in which this task can be performed. 
Method : Using list comprehension + join() We achieve the task in this method in 2 steps. In 1st step the Nth column elements are extracted using list comprehension. In 2nd step, these elements are joined together to perform the characters to string conversion. 

Python3

# Python3 code to demonstrate working of
# Nth Column vertical string in Matrix
# Using join() + list comprehension

# initializing list
test_list = [('a', 'g', 'v'), ('e', 'f', 8), ('b', 'g', 0)]

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

# initializing Nth column
N = 1

# Nth Column vertical string in Matrix
# Using join() + list comprehension
temp = [sub[N] for sub in test_list]
res = "".join(temp)

# Printing result
print("Constructed vertical string : " + str(res))

Output

The original list : [('a', 'g', 'v'), ('e', 'f', 8), ('b', 'g', 0)]
Constructed vertical string : gfg

Method : Using numpy() 

Note: Install numpy module using command “pip install numpy”

Another approach could be using numpy, which can extract the Nth column of a matrix as a numpy array and then use numpy.array2string() to convert the array to a string. This approach would have a time complexity of O(n) where n is the number of rows in the matrix, and a space complexity of O(n) as well, as it requires a new numpy array to be created.

Python3

import numpy as np
test_matrix = np.array([['a', 'g', 'v'], ['e', 'f', 8], ['b', 'g', 0]])
#initializing Nth column
N = 1
# Extracting Nth column
temp = test_matrix[:, N]
# Converting numpy array to string
# Printing result
print("Constructed vertical string : " + "".join(temp))

Output:
Constructed vertical string : gfg

This approach using numpy would have O(n) time complexity and O(n) Auxiliary space as well.