Sometimes in the world of competitive programming, we need to initialise the matrix, but we don’t wish to do it in a longer way using a loop. We need a shorthand for this. This type of problem is quite common in dynamic programming domain. Let’s discuss certain ways in which this can be done.
Method #1 : Using List comprehension
List comprehension can be treated as a shorthand for performing this particular operation. In list comprehension, we can initialise the inner list and then extend this logic to each row again using the list comprehension.
Python3
# Python3 code to demonstrate # initializing matrix # using list comprehension # Declaring rows N = 5 # Declaring columns M = 4 # using list comprehension # to initializing matrix res = [ [ 0 for i in range (M) ] for j in range (N) ] # printing result print ( "The matrix after initializing : " + str (res)) |
The matrix after initializing : [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
Method #2 : Using list comprehension + “*” operator
This problem can also be simplified using the * operator which can slightly reduce the tedious way task is done and can simply use multiply operator to extent the initialization to all N rows.
Python3
# Python3 code to demonstrate # initializing matrix # using list comprehension # and * operator # Declaring rows N = 5 # Declaring columns M = 4 # using list comprehension # to initializing matrix res = [ [ 0 for i in range (M)]] * N # printing result print ( "The matrix after initializing : " + str (res)) |
The matrix after initializing : [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
Method #3 : Using + “*” operator twice
Similar to above example we can also initialize the columns using “*” operator twice.
Python3
# Python3 code to demonstrate # initializing matrix # * operator twice # By: Pushpak Jalan, Tezpur University # Declaring rows N = 5 # Declaring columns M = 4 # Using * operator twice to initialize matrix res = [[ 0 ] * M] * N # printing result print ( "The matrix after initializing : " + str (res)) |
The matrix after initializing : [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.