NumPy: Create a 2-dimensional array of size 2 x 3

Last update on March 24 2025 13:37:13 (UTC/GMT +8 hours)

Create 2D Array & Print Shape/Type

Write a NumPy program to create a 2-dimensional array of size 2 x 3 (composed of 4-byte integer elements), also print the shape, type and data type of the array.

Pictorial Presentation:

Sample Solution:

Python Code:

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

# Creating a 2D NumPy array with two rows and three columns with data type np.int32
x = np.array([[2, 4, 6], [6, 8, 10]], np.int32)

# Checking and displaying the type of variable 'x'
print(type(x))

# Displaying the shape of the NumPy array 'x' (number of rows, number of columns)
print(x.shape)

# Displaying the data type of the elements in the array 'x'
print(x.dtype) 

Sample Output:

<class 'numpy.ndarray'>                                                
(2, 3)                                                                 
int32 

Explanation:

In the above code -

x = np.array([[2, 4, 6], [6, 8, 10]], np.int32): The current line creates a two-dimensional NumPy array x with two rows and three columns using the provided list of lists. The data type of the array is specified as np.int32 (32-bit integers).

print(type(x)): The current line prints the type of the ‘x’ array, which is <class 'numpy.ndarray'>.

print(x.shape): The current line prints the shape of the ‘x’ array, which is (2, 3) - two rows and three columns.

print(x.dtype): The current line prints the data type of the elements in the ‘x’ array, which is int32, as specified during the array creation.

For more Practice: Solve these Related Problems:

• Create a 2D array with a specified shape and data type, then print its shape and dtype attributes.
• Write a function that accepts an array and returns its shape, type, and size in a formatted string.
• Compare the output of type() with np.dtype for elements in the array to ensure consistency.
• Generate a 2D array dynamically and verify that its dimensions match the expected values.

Python-Numpy Code Editor: