Shape and Reshape in Python HackerRank Solution

Hello Programmers, In this post, you will know how to solve the Shape and Reshape in Python HackerRank Solution. This problem is a part of the HackerRank Python Programming Series.

One more thing to add, don’t directly look for the solutions, first try to solve the problems of Hackerrank by yourself. If you find any difficulty after trying several times, then you can look for solutions.

Shape and Reshape in Python HackerRank Solutions

Problem

Shape :
The shape tool gives a tuple of array dimensions and can be used to change the dimensions of an array.(a). Using shape to get array dimensions

import numpy
my__1D_array = numpy.array([1, 2, 3, 4, 5])
print my_1D_array.shape     #(5,) -> 5 rows and 0 columns
my__2D_array = numpy.array([[1, 2],[3, 4],[6,5]])
print my_2D_array.shape     #(3, 2) -> 3 rows and 2 columns

(b). Using shape to change array dimensions

import numpy
change_array = numpy.array([1,2,3,4,5,6])
change_array.shape = (3, 2)
print change_array
#Output
[[1 2]
[3 4]
[5 6]]

ReshapeThe reshape tool gives a new shape to an array without changing its data. It creates a new array and does not modify the original array itself.

import numpy
my_array = numpy.array([1,2,3,4,5,6])
print numpy.reshape(my_array,(3,2))
#Output
[[1 2]
[3 4]
[5 6]]

Task :

You are given a space separated list of nine integers. Your task is to convert this list into a 3X3 NumPy array.

Input Format :

A single line of input containing 9 space separated integers.

Output Format :

Print the 3X3 NumPy array.

Sample Input :

1 2 3 4 5 6 7 8 9

Sample Output :

[[1 2 3]
 [4 5 6]
 [7 8 9]]

Shape and Reshape in Python HackerRank Solutions

import numpy
# Shape and Reshape in Python - Hacker Rank Solution START
print(numpy.array(input().split(), int).reshape(3, 3))
# Shape and Reshape in Python - Hacker Rank Solution END

Disclaimer: The above Problem (Shape and Reshape in Python) is generated by Hackerrank but the Solution is Provided by BrokenProgrammers. This tutorial is only for Educational and Learning purposes.

Next: Transpose and Flatten in Python HackerRank Solution