NumPy: Create a new shape to an array without changing its data

Last update on August 29 2025 12:50:04 (UTC/GMT +8 hours)

Reshape Array (Keep Data)

Write a NumPy program to create another shape from an array without changing its data.

Pictorial Presentation:

Python NumPy: Create a new shape to an array without changing its data

Sample Solution:

Python Code:

# Importing the NumPy library with an alias 'np'
import numpy as np

# Creating a 1D NumPy array with six elements
x = np.array([1, 2, 3, 4, 5, 6])

# Reshaping the array 'x' into a 3x2 matrix and assigning it to variable 'y'
y = np.reshape(x, (3, 2))
print("Reshape 3x2:")  # Printing the description for the reshaped 3x2 array
print(y)  # Displaying the reshaped 3x2 array

# Reshaping the array 'x' into a 2x3 matrix and assigning it to variable 'z'
z = np.reshape(x, (2, 3))
print("Reshape 2x3:")  # Printing the description for the reshaped 2x3 array
print(z)  # Displaying the reshaped 2x3 array

Sample Output:

Reshape 3x2:                                                           
[[1 2]                                                                 
 [3 4]                                                                 
 [5 6]]                                                                
Reshape 2x3:                                                           
[[1 2 3]                                                               
 [4 5 6]]

Explanation:

In the above code -

x = np.array([1, 2, 3, 4, 5, 6]): This line creates a one-dimensional NumPy array ‘x’ with six elements.

y = np.reshape(x,(3,2)): This line reshapes the ‘x’ array into a new two-dimensional array ‘y’ with 3 rows and 2 columns. The elements from ‘x’ are placed row-wise into the new shape.

print(y): This line prints the reshaped ‘y’ array.

z = np.reshape(x,(2,3)): This line reshapes the ‘x’ array into another two-dimensional array ‘z’ with 2 rows and 3 columns. Again, the elements from ‘x’ are placed row-wise into the new shape.

print(z): This line prints the reshaped ‘z’ array.

For more Practice: Solve these Related Problems:

Reshape a given array into different dimensions while ensuring that the data remains unchanged.
Create a function that reshapes an array and then verifies the integrity of its elements post-transformation.
Test reshaping on arrays where one dimension is inferred using -1 and check for correctness.
Compare the flattened version of the original array with the reshaped array to ensure identical ordering.

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