How to generate random numbers using NumP1

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In this article of today, we are going to see how to generate random numbers using any of the following methods:

• Generating a random number
• Generating a random float and integer
• Generating random number arrays
• Generating random number from an array

What is a random number?

This is a number which cannot be predicted before its occurrence. This number might not different every time.

Programmatically, they are two categories of random numbers:

•     Pseudo-Random numbers 
•     True Random numbers.

Just as programs which are written by programmers are a set of instructions, we must follow an algorithm to generate random numbers.

Random numbers which are generated using an algorithm are called Pseudo-Random numbers. To generate a true random number, it is important to get the data from sources such as the keyboards, mouse activities, etc.

In this article of today, we are concerned only the Pseudo-Random numbers using NumPy

Generating a random NumPy module/number

NumPy library has a random module which can be used to generate numbers.

from numpy import random
x = random.randint(80)
print(x)

Following the instructions of the randint method, the compiler returns the output as a number between 0 and 80. That is the randint() method is used to generate a number between a given range.

OUTPUT

Generating a float

just as with the case above, we are going to use the rand() method to generate a float. This method returns a random float between 0 and 1.

Example

from numpy import random
num = random.rand()
print(num)

OUTPUT

Generating random number arrays

Just like with the two examples above, we can also the randit() and rand() method to generate random number array. To use these methods this case, we are going to be more specific, that is we are going to specify the shape of the array.

• Generating integers using randit()method

we are going to specify the size of the array

from numpy import random
num = random.randint(50,size=(4))
print(num)

The size being specified, the compiler returns an array of 4 random numbers.

OUTPUT

• Generating a 2-D array 

from numpy import random
num = random.randint(50,size=(2,2))
print(num)

OUTPUT

• Generating a float

We are going to use the rand() method

from numpy import random
num = random.rand(2, 3)
print(num)

OUTPUT

Generating a 2-D array float

Example

from numpy import random
num1D = random.rand(2,3)
print(num1D)

OUTPUT

Generating Random Number from an Array

We are going to use a method called the choice() method to randomly select a value from a given array.

Example

from numpy import random
num = random.choice([1,5,4,2,8,3])
print(num)

The compiler randomly selects a value from the given array. 

OUTPUT

Generating a 2-D array using the choice()method

This is possible if we add a specific size to the array to be generated.

Example

from numpy import random
num = random.choice([1,5,4,2,8,3], size=(2,3))
print(num)

A specific size has been given for the array to be created. The compiler generates an array randomly according to this size.

OUTPUT

Take note that the output changes every time the program is executed. Hope this article was very exciting. If so, stay tune on the platform to get more knowledge on NumPy and other programming languages. Have a time coding.