Open In App

How to create an empty and a full NumPy array?

Last Updated : 15 Jul, 2025
Comments
Improve
Suggest changes
Like Article
Like
Report

Creating arrays is a basic operation in NumPy.

  • Empty array: This array isn’t initialized with any specific values. It’s like a blank page, ready to be filled with data later. However, it will contain random leftover values in memory until you update it.
  • Full array: This is an array where all the elements are set to the same specific value right from the start. It’s like a sheet filled with one number everywhere.

NumPy provides simple functions numpy.empty() for empty arrays numpy.full() empty arrays and full arrays.

Python
import numpy as np

# Create an empty array of shape (3, 4)
empty_array = np.empty((3, 4))
print("Empty Array:\n", empty_array)

# Create a full array of shape (3, 3) filled with the value 5
full_array = np.full((3, 3), 5)
print("Full Array:\n", full_array)

Output
Empty Array:
 [[4.63714601e-310 0.00000000e+000 0.00000000e+000 0.00000000e+000]
 [0.00000000e+000 0.00000000e+000 0.00000000e+000 0.00000000e+000]
 [0.00000000e+000 0.00000000e+000 0.00000000e+000 0....

How to Create an Empty NumPy Array?

Creating an empty array is useful when you need a placeholder for future data that will be populated later. It allocates space without initializing it, which can be efficient in terms of performance.

  • Use the np.empty() function.
  • Specify the shape of the array as a tuple.
  • Optionally, define the data type using the dtype parameter.
Python
import numpy as np

empty_array_2d = np.empty((3, 4))
print(empty_array_2d)

Output
[[1.13473609e-313 0.00000000e+000 2.10077583e-312 6.79038654e-313]
 [2.22809558e-312 2.14321575e-312 2.35541533e-312 6.79038654e-313]
 [2.22809558e-312 2.14321575e-312 2.46151512e-312 2.41907520e-312]...

How to Create a Full NumPy Array?

A full array is ideal when you need an array initialized with a specific value, such as zeros or ones, which is common in many mathematical computations. Steps:

  • Use the np.full() function.
  • Pass the desired shape and fill value.
  • Optionally, specify the data type.
Python
import numpy as np

full_array_2d = np.full((3, 4), 5)
print(full_array_2d)

Output
[[5 5 5 5]
 [5 5 5 5]
 [5 5 5 5]]

Next Article

Similar Reads

pFad - Phonifier reborn

Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


Alternative Proxies:

Alternative Proxy

pFad Proxy

pFad v3 Proxy

pFad v4 Proxy