In this program, you’ll learn to display powers of the integer 2 using Python anonymous function.
To understand this example, you should have the knowledge of the following Python programming topics:
In the program below, we have used an anonymous (lambda) function inside the map() built-in function to find the powers of 2.
Source Code
# Display the powers of 2 using anonymous function
terms = 10
# Uncomment code below to take input from the user
# terms = int(input("How many terms? "))
# use anonymous function
result = list(map(lambda x: 2 ** x, range(terms)))
print("The total terms are:",terms)
for i in range(terms):
print("2 raised to power",i,"is",result[i])
Output
The total terms are: 10 2 raised to power 0 is 1 2 raised to power 1 is 2 2 raised to power 2 is 4 2 raised to power 3 is 8 2 raised to power 4 is 16 2 raised to power 5 is 32 2 raised to power 6 is 64 2 raised to power 7 is 128 2 raised to power 8 is 256 2 raised to power 9 is 512
Note: To test for different number of terms, change the value of terms variable.
Related posts:
Python Program to Shuffle Deck of Cards
Python Recursion
Python Set pop()
Python String encode()
Python object()
Python String casefold()
Python Program to Count the Number of Occurrence of a Character in String
Python String translate()
Python Program to Count the Number of Digits Present In a Number
Python min()
Python Program to Represent enum
Python Program to Make a Simple Calculator
Python any()
Python Program to Get the Full Path of the Current Working Directory
Python Program to Count the Number of Each Vowel
Python String replace()
Python vars()
Python int()
Python setattr()
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Python Dictionary copy()
Python tuple()
Python List clear()
Python String isdigit()
Python Program to Find Factorial of Number Using Recursion
Python Program to Remove Punctuations From a String
Python Dictionary setdefault()
Python Deep Learning Cookbook - Indra den Bakker
Python Dictionary pop()
Python List insert()
Python ord()
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli