PYTHON END TO END FUNCTIONS ON RANDOM NUMBERS

PYTHON END TO END FUNCTIONS ON RANDOM NUMBERS

Random Module:

The Python random module functions depend on a pseudo-random number generator function random(), which generates the float number between 0.0 and 1.0.

There are different types of functions used in a random module . Lets get into them.

1)random.random(): Generates a random float number between 0.0 to 1.0. The function doesn't need any arguments.

In [1]:

import random

print ("A random number between 0 and 1 is : ", end="")

print (random.random())

A random number between 0 and 1 is : 0.7019698935234014

This function generates a new random number each time you run it. If you want the same random number to get generated each time you the code ,then you can seed them.

2)random.seed():The seed() method is used to initialize the random number generator. The random number generator needs a number to start with (a seed value), to be able to generate a random number.If you use the same seed value twice you will get the same random number twice.

In [2]:

print("Random number intializing a seed value : ")

random.seed(10)

print(random.random())

 

random.seed(10)

print(random.random())

 

print("Random number without intializing a seed value : ")

print(random.random()946899135

Random number without intializing a seed value :

0.4288890546751146

3)random.randint():The randint() method returns an integer number selected element from the specified range.This method is an alias for randrange(start, stop+1).

In [3]:

rn=random.randint(1,10)

print("The random integer between the specified range is : ",rn)

The random integer between the specified range is :  10

4)random.randrange(): The randrange() method returns a randomly selected element from the specified range.

In [4]:

print ("A random number from range is : ",end="")

print (random.randrange(1,10))

A random number from range is : 1

5)random.choice():This method returns a randomly selected element from the specified sequence.The sequence can be a string, a range, a list, a tuple or any other kind of sequence.

In [5]:

print ("A random number from list is : ",end="")

print (random.choice([1, 4, 8, 10, 3]))

# String manipulation:

x = "WELCOME"

print("Random character from the given string : ",random.choice(x))

A random number from list is : 4

Random character from the given string :  C

6) random.sample(): This method returns a list with a randomly selection of a specified number of items from a sequnce.

In [6]:

mylist = ["apple", "banana", "cherry"]

print("The randomly selected items are:")

print(random.sample(mylist, k=2))

 

string = "PythonProgramming"

print("With string:", random.sample(string, 4))

 

# Prints list of random items of length 4 from the given tuple.

tuple1 = ("ankit", "geeks", "computer", "science",

                   "portal", "scientist", "btech")

print("With tuple:", random.sample(tuple1, 4))

 

#Prints list of random items of length 3 from the given set.

set1 = {"a", "b", "c", "d", "e"}

print("With set:", random.sample(set1, 3))

The randomly selected items are:

7) random.shuffle(): This method takes a sequence (list, string, or tuple) and reorganize the order of the items.

In [7]:

li = [1, 4, 5, 10, 2]

print("The list after shuffling :")

random.shuffle(li)

print(li)

 

mylist = ["apple", "banana", "cherry"]

random.shuffle(mylist)

print("mylist after shuffling : ")

print(mylist)

 

from random import shuffle

x = [i for i in range(10)]

random.shuffle(x)

print("x :",x)

, 7]

8) random.uniform(): This method returns a random floating number between the two specified numbers (both included).

In [8]:

print(random.uniform(20, 60))

44.53307282186836

Random numbers using numpy

1D Array :

In [9]:

import numpy as np

  

# 1D Array

array = np.random.randn(5)

print("1D Array filled with random values : \n", array)

1D Array filled with random values :

 0.79780742 -1.49681385]

2D Array

np.random.randn(no. of rows,no. of columns)

In [10]:

array = np.random.randn(3, 4)

print("2D Array filled with random values : \n", array);

1.08453488 -1.21153574 -0.0549759 ]]

3D Array

np.random.randn(no.of matrix,no. of rows,no. of columns)

In [11]:

array = np.random.randn(2, 2 ,2)

print("3D Array filled with random values : \n", array);

3D Arra

]]]

Discrete random variables using Scipy:

In [12]:

from scipy.stats import rv_discrete

values = [10, 20, 30]

probabilities = [0.2, 0.5, 0.3]

distrib = rv_discrete(values=(values, probabilities))

distrib.rvs(size=10)

Out[12]: