In this tutorial, I will show you how to create an array using the NumPy library, a scientific computing library in Python.

Table of Contents

# Real-World Applications

- Any computer vision application written in Python that handles images or videos could use NumPy.

Let’s get started!

# Prerequisites

# Installation and Setup

We now need to make sure we have all the software packages installed. Check to see if you have **OpenCV** installed on your machine. If you are using Anaconda, you can type:

conda install -c conda-forge opencv

Alternatively, you can type:

pip install opencv-python

Make sure you have** NumPy** installed, a scientific computing library for Python.

If you’re using Anaconda, you can type:

conda install numpy

Alternatively, you can type:

pip install numpy

# Write the Code

Open up a new Python file called **numpy_array_creation.py**.

Here is the full code:

```
# Project: How To Create a NumPy Array
# Author: Addison Sears-Collins
# Date created: February 24, 2021
# Description: Basics of using the NumPy library
import numpy as np # Import the NumPy library
# Create and print a two dimensional array with 7 rows and 4 columns
my_array = np.zeros((7,4))
#print(my_array)
# Print the data type
#print(my_array.dtype)
# Print the dimensions of the array
#print(my_array.shape)
#print("Number of rows in the array = {}".format(my_array.shape[0]))
#print("Number of columns in the array = {}".format(my_array.shape[1]))
# Create an array of ones that contains 8-bit unsigned integers
my_array_ones = np.ones((7,4), dtype=np.uint8)
#print(my_array_ones)
# Create an array of random numbers
my_array_random_nums = np.random.rand(7,4)
#print(my_array_random_nums)
# Create a 4x3 two-dimensional array (i.e. a matrix)
my_2d_array = np.array([[0, 1, 2, 3],
[4, 5, 6, 7],
[8, 9, 10, 11]])
#print(my_2d_array)
# Extract the value from the matrix on row 3, column 2 (i.e. the 9)
#print(my_2d_array[2,1])
```

# Code Output

```
# Create and print a two dimensional array with 7 rows and 4 columns
my_array = np.zeros((7,4))
print(my_array)
```

```
# Print the data type
print(my_array.dtype)
```

```
# Print the dimensions of the array
print(my_array.shape)
print("Number of rows in the array = {}".format(my_array.shape[0]))
print("Number of columns in the array = {}".format(my_array.shape[1]))
```

```
# Create an array of ones that contains 8-bit unsigned integers
my_array_ones = np.ones((7,4), dtype=np.uint8)
print(my_array_ones)
```

```
# Create an array of random numbers
my_array_random_nums = np.random.rand(7,4)
print(my_array_random_nums)
```

```
# Create a 4x3 two-dimensional array (i.e. a matrix)
my_2d_array = np.array([[0, 1, 2, 3],
[4, 5, 6, 7],
[8, 9, 10, 11]])
print(my_2d_array)
```

```
# Extract the value from the matrix on row 3, column 2 (i.e. the 9)
print(my_2d_array[2,1])
```

That’s it. Keep building!