Say "Hello, World!" With Python Easy Max Score: 5 Success Rate: 96.38%

Python if-else easy python (basic) max score: 10 success rate: 89.94%, arithmetic operators easy python (basic) max score: 10 success rate: 97.51%, python: division easy python (basic) max score: 10 success rate: 98.69%, loops easy python (basic) max score: 10 success rate: 98.19%, write a function medium python (basic) max score: 10 success rate: 90.36%, print function easy python (basic) max score: 20 success rate: 97.24%, list comprehensions easy python (basic) max score: 10 success rate: 97.78%, find the runner-up score easy python (basic) max score: 10 success rate: 94.12%, nested lists easy python (basic) max score: 10 success rate: 91.60%.

• Computer Vision

Problem Solving in Python

• Intro to DS and Algo
• Analysis of Algorithm
• Dictionaries
• Doubly Linked Lists
• Circular Singly Linked List
• Circular Doubly Linked List
• Tree/Binary Tree
• Binary Search Tree
• Binary Heap
• Sorting Algorithms
• Searching Algorithms
• Single-Source Shortest Path
• Topological Sort
• Dijkstra’s
• Bellman-Ford’s
• All Pair Shortest Path
• Minimum Spanning Tree
• Kruskal & Prim’s

Problem-solving is the process of identifying a problem, creating an algorithm to solve the given problem, and finally implementing the algorithm to develop a computer program .

An algorithm is a process or set of rules to be followed while performing calculations or other problem-solving operations. It is simply a set of steps to accomplish a certain task.

In this article, we will discuss 5 major steps for efficient problem-solving. These steps are:

• Understanding the Problem
• Exploring Examples
• Breaking the Problem Down
• Solving or Simplification
• Looking back and Refactoring

While understanding the problem, we first need to closely examine the language of the question and then proceed further. The following questions can be helpful while understanding the given problem at hand.

• Can the problem be restated in our own words?
• What are the inputs that are needed for the problem?
• What are the outputs that come from the problem?
• Can the outputs be determined from the inputs? In other words, do we have enough information to solve the given problem?
• What should the important pieces of data be labeled?

Example : Write a function that takes two numbers and returns their sum.

• Integer, Float, etc.

Once we have understood the given problem, we can look up various examples related to it. The examples should cover all situations that can be encountered while the implementation.

• Progress to more complex examples.
• Explore examples with empty inputs.
• Explore examples with invalid inputs.

Example : Write a function that takes a string as input and returns the count of each character

After exploring examples related to the problem, we need to break down the given problem. Before implementation, we write out the steps that need to be taken to solve the question.

Once we have laid out the steps to solve the problem, we try to find the solution to the question. If the solution cannot be found, try to simplify the problem instead.

The steps to simplify a problem are as follows:

• Find the core difficulty
• Temporarily ignore the difficulty
• Write a simplified solution
• Then incorporate that difficulty

Since we have completed the implementation of the problem, we now look back at the code and refactor it if required. It is an important step to refactor the code so as to improve efficiency.

The following questions can be helpful while looking back at the code and refactoring:

• Can we check the result?
• Can we derive the result differently?
• Can we understand it at a glance?
• Can we use the result or mehtod for some other problem?
• Can you improve the performance of the solution?
• How do other people solve the problem?

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Python Practice Problems for Beginner Coders

August 30, 2021

From sifting through Twitter data to making your own Minecraft modifications, Python is one of the most versatile programming languages at a coder’s disposal. The open-source, object-oriented language is also quickly becoming one of the most-used languages in data science.

According to the Association for Computing Machinery, Python is now the most popular introductory language at universities in the United States.

To help readers practice the Python fundamentals, datascience@berkeley gathered six coding problems, including some from the W200: Introduction to Data Science Programming course. The questions below cover concepts ranging from basic data types to object-oriented programming using classes.

Are You Ready to Start Your Python Practice?

Consider the following questions to make sure you have the proper prior knowledge and coding environment to continue.

How much Python do I need to already know?

This problem set is intended for people who already have familiarity with Python (or another language) and data types. Each problem highlights a few different skills, and they gradually become more complicated. To learn more about the different fundamentals tested here, use the Resources section accompanying each question.

Readers who want to learn more about Python before beginning can access the following tools:

• Python 3 Documentation
• Python for Beginners from Python.org
• First Python Notebook Course from Ben Welsh
• Python Course from Codecademy
• Python Introduction from w3schools

Where do I write my code?

datascience@berkeley created a Google Colab notebook as a starting point for readers to execute their code. Google Colab is a free computational environment that allows anyone with an Internet connection to execute Python code via the browser.

For a more thorough introduction to Google’s Colab notebooks and how to use them, check out this guide to Getting Started with Google Colab from Towards Data Science.

You can also execute code using other systems, such as a text editor on your local machine or a Jupyter notebook.

My answers don’t look the same as the provided solutions. Is my code wrong?

The solutions provided are examples of working code to solve the presented problem. However, just like multiple responses to the same essay prompt will look different, every solution to a coding problem can be unique.

As you develop your own coding style, you may prefer different approaches. Instead of worrying about matching the example code exactly, focus on making sure your code is accurate, concise, and clear.

I’m ready, let’s go!

Below are links to the Google Colab notebooks created by datascience@berkeley that you can use to create and test your code.

Python Practice Problems: QUESTIONS

This notebook contains the questions and space to create and test your code. To use it, save a copy to your local drive.

Python Practice Problems: SOLUTIONS

This notebook contains the questions and corresponding solutions.

Python Exercises

1. fly swatting: debugging and string formatting exercise.

The following code chunk contains errors that prevent it from executing properly. Find the “bugs” and correct them.

def problem_one():

for state, city in capitals.items() print(f”The capital of {state) is {‘city’}.”

Once fixed, it should return the following output:

The capital of Maryland is Annapolis. The capital of California is Sacramento. The capital of New York is Albany. The capital of Utah is Salt Lake City. The capital of Alabama is Montgomery.

Python Debugging and String Formatting Resources

• Python String Formatting Best Practices, Real Python
• PythonTutor.com

2. That’s a Wrap: Functions and Wrapped Functions Exercise

Write a function multiply() that takes one parameter, an integer x . Check that x is an integer at least three characters long. If it is not, end the function and print a statement explaining why. If it is, return the product of x ’s digits.

Write another function matching() that takes an integer x as a parameter and “wraps” your multiply() function. Compare the results of the multiply() function on x with the original x parameter and return a sorted list of any shared digits between the two. If there are none, print “No shared digits!”

Your code should reproduce the following examples:

>multiply(1468) 192

>multiply(74) This integer is not long enough!

>matching(2789475) [2,4]

Python Functions Resources

• Defining Your Own Python Function, Real Python
• Python Nested Functions, Stack Abuse

3. Show Me the Money: Data Types and Arithmetic Exercise

Write code that asks a user to input a monetary value (USD). You can assume the user will input an integer or float with no special characters. Return a print statement using string formatting that states the value converted to Euros (EUR), Japanese Yen (JPY), and Mexican Pesos (MXN). Your new values should be rounded to the nearest hundredth.

>Input a value to convert from \$USD: 189 189 USD = 160.65 EUR = 20,909.07 JPY = 3,783.78 MXN

>Input a value to convert from \$USD: 17.82 17.82 USD = 15.15 EUR = 1,971.43 JPY = 356.76 MXN

Hint: To match the exact values from the example, you can use currency conversion ratios from the time of publication. As of July 6, 2021, \$1 USD is equivalent to 0.85 EUR, 110.63 JPY, and 20.02 MXN.

Python Data Types and Arithmetic Resources:

• Python Arithmetic Operators Example, Tutorials Point
• The Real Difference between Integers and Floating-Point Values, Dummies
• Python 3 – input() function, Geeks for Geeks

4. What’s in a Name: String Slicing and If/Else Statements Exercise

Write a script that prompts the user for a name (assume it will be a one-word string). Change the string to lowercase and print it out in reverse, with only the first letter of the reversed word in uppercase. If the name is the same forward as it is backward, add an additional print statement on the next line that says “Palindrome!”

>Enter your name: Paul Luap

>Enter your name: ANA Ana Palindrome!

Hint: Use s.lower() and s.upper() , as appropriate.

Python String and If/Else Statement Resources:

• Python Slice Strings, w3schools
• Python if…else Statement, Programiz

5. Adventures in Loops: “For” Loops and List Comprehensions Exercise

Save the paragraph below — from Alice’s Adventures in Wonderland — to a variable named text . Write two programs using “for” loops and/or list comprehensions to do the following:

• Create a single string that contains the second-to-last letter of each word in text , sorted alphabetically and in lowercase. Save it to a variable named letters and print. If a word is less than two letters in length, use the single character available.
• Find the average number of characters per word in text , rounded to the nearest hundredth. This value should exclude special characters, such as quotation marks and semicolons. Save it to a variable named avg_chars and print.

text = “Alice was beginning to get very tired of sitting \ by her sister on the bank, and of having nothing to do: \ once or twice she had peeped into the book her sister \ was reading, but it had no pictures or conversations in \ it, ‘and what is the use of a book,’ thought Alice, \ ‘without pictures or conversations?’”

Python “for” Loop and List Comprehensions Resources:

• Python “for” Loops (Definite Iteration), Real Python
• Python – List Comprehension, w3schools

6. The Drones You’re Looking For: Classes and Objects

Make a class named Drone that meets the following requirements:

• Has an attribute named altitude that stores the altitude of the Drone . Use a property to set the altitude attribute and make it hidden.
• Create getter and setter methods for the altitude attribute. Your setter method should return an exception if the passed altitude is negative.
• Has a method named ascend that causes the Drone to ascend to a passed altitude change.
• Has an attribute named ascend_count that stores the number of ascents the Drone has done.
• Has a method named fly that returns the Drone ’s current altitude .

Your code should mimic this sample output:

> d1 = Drone(100) > d1.fly() The drone is flying at 100 feet.

> d1.altitude = 300 > d1.fly() The drone is flying at 300 feet.

> d1.ascend(100) > d1.fly() The drone is flying at 400 feet.

> d1.ascend_count 1

Python Classes and Objects Resources:

• Understanding How Python Class Works, BitDegree
• Class and Instance Attributes, OOP Python Tutorial
• Getter and Setter in Python, Tutorials Point

7. Top of the Class: Dictionaries and “While” Loops Exercise

Write a program that lets the user create and manage a gradebook for their students. Create a Gradebook class that begins with an empty dictionary. Use helper functions inside the class to run specific tasks at the user’s request. Use the input() method to ask users what task they would like to complete. The program should continue to prompt the user for tasks until the user decides to quit. Your program must allow the user to do the following:

• Add student : Creates a new entry in a dictionary called `gradebook.` The user will input the key (a student’s name) and the value (a list of grades). You can assume grades will be integers separated by commas and no spaces.
• View gradebook : Prints the entire gradebook .
• Calculate averages : Prints each student’s unweighted average grade, rounded to the nearest hundredth.
• Quit : Ends the program.

Your code should reproduce the following example:

>What would you like to do?: Add student >Enter student name: Natalie A new student! Adding them to the gradebook... >Enter student grade(s): 87,82 New entry complete!

>What would you like to do?: View gradebook {'natalie': [87.0, 82.0]}

>What would you like to do?: Calculate averages natalie: 84.50

>What would you like to do?: Quit End of program

Hint: Use a “while” loop to run the program while the input() response is anything other than “quit.” Within the “while” loop, set up if/else statements to manage each potential response.

Python Dictionaries and “While” Loop Resources:

• Python while Loop Statements, Tutorials Point
• Python Dictionaries, w3schools
• Dictionary Manipulation in Python, Python for Beginners

Additional Python Coding Exercises

Looking for more Python practice? Here are some additional problem sets to work on fundamental coding skills:

Advent of Code This site hosts a yearly advent calendar every December, with coding challenges that open daily at midnight PST. Coders can build their own small group competitions or compete in the overall one. Past years’ problems are available for non-competitive coding.

Eda Bit Thousands of Python challenges that use an interactive interface to run and check code against the solutions. Users can level up and sort by difficulty.

PracticePython.org These 36 exercises test users’ knowledge of concepts ranging from input() to data visualization.

Python exercises, w3resource A collection of hundreds of Python exercises organized by concept and module. This set also includes a section of Pandas data exercises.

Created by datascience@berkeley, the online Master of Information and Data Science from UC Berkeley

• Scratch ActiveCode
• Help for Instructors
• Report A Problem
• 1. Introduction
• 2. Analysis
• 3. Basic Data Structures
• 4. Recursion
• 5. Sorting and Searching
• 6. Trees and Tree Algorithms
• 7. Graphs and Graph Algorithms

Problem Solving with Algorithms and Data Structures using Python ¶

By Brad Miller and David Ranum, Luther College (as remixed by Jeffrey Elkner)

• 1.1. Objectives
• 1.2. Getting Started
• 1.3. What Is Computer Science?
• 1.4. What Is Programming?
• 1.5. Why Study Data Structures and Abstract Data Types?
• 1.6. Why Study Algorithms?
• 1.7. Review of Basic Python
• 1.8.1. Built-in Atomic Data Types
• 1.8.2. Built-in Collection Data Types
• 1.9.1. String Formatting
• 1.10. Control Structures
• 1.11. Exception Handling
• 1.12. Defining Functions
• 1.13.1. A Fraction Class
• 1.13.2. Inheritance: Logic Gates and Circuits
• 1.14. Summary
• 1.15. Key Terms
• 1.16. Discussion Questions
• 1.17. Programming Exercises
• 2.1. Objectives
• 2.2. What Is Algorithm Analysis?
• 2.3. Big-O Notation
• 2.4.1. Solution 1: Checking Off
• 2.4.2. Solution 2: Sort and Compare
• 2.4.3. Solution 3: Brute Force
• 2.4.4. Solution 4: Count and Compare
• 2.5. Performance of Python Data Structures
• 2.7. Dictionaries
• 2.8. Summary
• 2.9. Key Terms
• 2.10. Discussion Questions
• 2.11. Programming Exercises
• 3.1. Objectives
• 3.2. What Are Linear Structures?
• 3.3. What is a Stack?
• 3.4. The Stack Abstract Data Type
• 3.5. Implementing a Stack in Python
• 3.6. Simple Balanced Parentheses
• 3.7. Balanced Symbols (A General Case)
• 3.8. Converting Decimal Numbers to Binary Numbers
• 3.9.1. Conversion of Infix Expressions to Prefix and Postfix
• 3.9.2. General Infix-to-Postfix Conversion
• 3.9.3. Postfix Evaluation
• 3.10. What Is a Queue?
• 3.11. The Queue Abstract Data Type
• 3.12. Implementing a Queue in Python
• 3.13. Simulation: Hot Potato
• 3.14.1. Main Simulation Steps
• 3.14.2. Python Implementation
• 3.14.3. Discussion
• 3.15. What Is a Deque?
• 3.16. The Deque Abstract Data Type
• 3.17. Implementing a Deque in Python
• 3.18. Palindrome-Checker
• 3.19. Lists
• 3.20. The Unordered List Abstract Data Type
• 3.21.1. The Node Class
• 3.21.2. The Unordered List Class
• 3.22. The Ordered List Abstract Data Type
• 3.23.1. Analysis of Linked Lists
• 3.24. Summary
• 3.25. Key Terms
• 3.26. Discussion Questions
• 3.27. Programming Exercises
• 4.1. Objectives
• 4.2. What Is Recursion?
• 4.3. Calculating the Sum of a List of Numbers
• 4.4. The Three Laws of Recursion
• 4.5. Converting an Integer to a String in Any Base
• 4.6. Stack Frames: Implementing Recursion
• 4.7. Introduction: Visualizing Recursion
• 4.8. Sierpinski Triangle
• 4.9. Complex Recursive Problems
• 4.10. Tower of Hanoi
• 4.11. Exploring a Maze
• 4.12. Dynamic Programming
• 4.13. Summary
• 4.14. Key Terms
• 4.15. Discussion Questions
• 4.16. Glossary
• 4.17. Programming Exercises
• 5.1. Objectives
• 5.2. Searching
• 5.3.1. Analysis of Sequential Search
• 5.4.1. Analysis of Binary Search
• 5.5.1. Hash Functions
• 5.5.2. Collision Resolution
• 5.5.3. Implementing the Map Abstract Data Type
• 5.5.4. Analysis of Hashing
• 5.6. Sorting
• 5.7. The Bubble Sort
• 5.8. The Selection Sort
• 5.9. The Insertion Sort
• 5.10. The Shell Sort
• 5.11. The Merge Sort
• 5.12. The Quick Sort
• 5.13. Summary
• 5.14. Key Terms
• 5.15. Discussion Questions
• 5.16. Programming Exercises
• 6.1. Objectives
• 6.2. Examples of Trees
• 6.3. Vocabulary and Definitions
• 6.4. List of Lists Representation
• 6.5. Nodes and References
• 6.6. Parse Tree
• 6.7. Tree Traversals
• 6.8. Priority Queues with Binary Heaps
• 6.9. Binary Heap Operations
• 6.10.1. The Structure Property
• 6.10.2. The Heap Order Property
• 6.10.3. Heap Operations
• 6.11. Binary Search Trees
• 6.12. Search Tree Operations
• 6.13. Search Tree Implementation
• 6.14. Search Tree Analysis
• 6.15. Balanced Binary Search Trees
• 6.16. AVL Tree Performance
• 6.17. AVL Tree Implementation
• 6.18. Summary of Map ADT Implementations
• 6.19. Summary
• 6.20. Key Terms
• 6.21. Discussion Questions
• 6.22. Programming Exercises
• 7.1. Objectives
• 7.2. Vocabulary and Definitions
• 7.3. The Graph Abstract Data Type
• 7.4. An Adjacency Matrix
• 7.5. An Adjacency List
• 7.6. Implementation
• 7.7. The Word Ladder Problem
• 7.8. Building the Word Ladder Graph
• 7.9. Implementing Breadth First Search
• 7.10. Breadth First Search Analysis
• 7.11. The Knight’s Tour Problem
• 7.12. Building the Knight’s Tour Graph
• 7.13. Implementing Knight’s Tour
• 7.14. Knight’s Tour Analysis
• 7.15. General Depth First Search
• 7.16. Depth First Search Analysis
• 7.17. Topological Sorting
• 7.18. Strongly Connected Components
• 7.19. Shortest Path Problems
• 7.20. Dijkstra’s Algorithm
• 7.21. Analysis of Dijkstra’s Algorithm
• 7.22. Prim’s Spanning Tree Algorithm
• 7.23. Summary
• 7.24. Key Terms
• 7.25. Discussion Questions
• 7.26. Programming Exercises

Acknowledgements ¶

We are very grateful to Franklin Beedle Publishers for allowing us to make this interactive textbook freely available. This online version is dedicated to the memory of our first editor, Jim Leisy, who wanted us to “change the world.”

Indices and tables ¶

• Module Index
• Search Page

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Python Basics: Problem Solving with Code

This course is part of Python Basics for Online Research Specialization

Taught in English

Some content may not be translated

Instructor: Seth Frey

Financial aid available

What you'll learn

Explore your own web browsing habits and manage code complexity and reading manuals.

Discuss how Python understands complex and real world things, and practice looking under the hood of a single tweet.

Apply the building blocks of Python and turn it into a little language for drawing pictures.

Practice "debugging" code and learn to think the way code thinks.

Details to know

Available in English

Subtitles: Kazakh, German, Hindi, Russian, Swedish, Korean, Portuguese (Brazilian), Greek, English, Italian, French, Chinese (Simplified), Spanish, Arabic, Thai, Ukrainian, Japanese, Indonesian, Polish, Dutch, Turkish

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• Develop job-relevant skills with hands-on projects
• Earn a shareable career certificate

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 4 modules in this course

A lot of code is building up from the most basic primitive elements of the language to increasingly faithful and meaningful things. In this course you will see how to author more complex ideas and capabilities in Python. In technical terms, you will learn dictionaries and how to work with them and nest them, functions, refactoring, and debugging, all of which are also thinking tools for the art of problem solving. We'll use this knowledge to explore our browsing history, interrogate a tweet, and draw pictures.

Examining Your Own Web Browsing Habits in Python

Can you use code to learn about...yourself? We're starting this course with a module in which you explore web browsing habits. If you installed the plugins for tracking your web history, you'll be able to explore your own. As this code gets more involved, you'll also get more advice on managing code complexity and reading manuals. Let's get started!

What's included

3 videos 5 readings 1 quiz 1 programming assignment 2 discussion prompts

3 videos • Total 20 minutes

• Course Introduction • 3 minutes • Preview module
• Hiding from the Complexity • 3 minutes
• Demo: Web History Walkthrough • 13 minutes

5 readings • Total 65 minutes

• A Note From UC Davis • 10 minutes
• Internet Mapping Glitch • 10 minutes
• Jupyter Notebook Tutorials • 30 minutes
• Demo and Code Lesson Walkthrough "How To" • 5 minutes
• SETUP: Self-Surveillance with Privacy Badger • 10 minutes

1 quiz • Total 15 minutes

• Module 1 Quiz • 15 minutes

1 programming assignment • Total 30 minutes

• Demo: Web History • 30 minutes

2 discussion prompts • Total 20 minutes

• Learning Goals • 10 minutes
• Web History • 10 minutes

Representing Complex Ideas in Python

Understanding how Python understands the world brings us to "dictionaries", which are kind of like lists, but they allow more variety and structure. This module will build up to representing increasingly complex real world things. We will build up to looking under the hood of a single tweet, and understanding the "social" in "social media".

10 videos 1 quiz 1 programming assignment 1 discussion prompt

10 videos • Total 47 minutes

• Introduction • 2 minutes • Preview module
• Python "Dictionaries" • 4 minutes
• Checking for Things in Dictionaries • 1 minute
• How is This not a List? • 2 minutes
• Collections in Collections • 2 minutes
• Dictionaries in Dictionaries • 3 minutes
• Looking at a Complex Dictionary • 3 minutes
• Looping Through a Dictionary • 9 minutes
• Representing Things in the Real World • 5 minutes
• Bringing it all Together • 11 minutes

1 quiz • Total 30 minutes

• Module 2 Quiz • 30 minutes

1 programming assignment • Total 100 minutes

• Code Lesson: Dictionaries and Nested Dictionaries • 100 minutes

1 discussion prompt • Total 10 minutes

• Obstacles and Opportunities • 10 minutes

Making Pictures with Robots

Everything you've learned in this course about Python is just basic building blocks that programmers use to build bigger building blocks of their own. In this module, we'll do precisely that, turning Python into a little language for drawing pictures, a DIY MS Paint.

8 videos 1 reading 1 quiz 1 programming assignment 1 discussion prompt

8 videos • Total 56 minutes

• Introduction • 3 minutes • Preview module
• Creating Functions • 6 minutes
• Functions are Flexible • 9 minutes
• Functions as Little Worlds • 4 minutes
• Turtle Graphics and Building Meaning with Functions • 7 minutes
• Functions for Avoiding Tedium • 8 minutes
• "Refactoring" • 11 minutes
• Bringing it all Together • 5 minutes

1 reading • Total 30 minutes

• Algorithmic Bias • 30 minutes
• Module 3 Quiz • 30 minutes

1 programming assignment • Total 120 minutes

• Code Lesson: Adding Functionality to Code • 120 minutes
• Why Code? • 10 minutes

A Strategy for Hunting Bugs

A major part of programming that no one ever tells you about is "debugging": spending seconds, minutes, hours, or even days going through code that should work to understand why it doesn't. This demoralizing subject stops a lot of beginners, but there is a way to be good at it, and that is a major part of learning to think the way code thinks.

5 videos 2 readings 1 quiz 2 discussion prompts

5 videos • Total 57 minutes

• How to Debug Code, Part 1 • 19 minutes • Preview module
• How to Debug Code, Part 2 • 21 minutes
• How to Debug Code, Part 3 • 3 minutes
• Becoming a Good Coder • 10 minutes
• Course Summary • 2 minutes

2 readings • Total 20 minutes

• Additional Resources • 10 minutes
• Course Credits • 10 minutes
• Module 4 Quiz • 15 minutes

2 discussion prompts • Total 40 minutes

• Debugging • 30 minutes
• Self-Reflection • 10 minutes

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Python Projects

• Python Interview Questions
• Python Database
• Data Science With Python
• Machine Learning with Python

• Explore Our Geeks Community

Python Exercises, Practice Questions and Solutions

• Python List Exercise
• Python String Exercise
• Python Tuple Exercise
• Python Dictionary Exercise
• Python Set Exercise

Python Matrix Exercises

• Python program to a Sort Matrix by index-value equality count
• Python Program to Reverse Every Kth row in a Matrix
• Python Program to Convert String Matrix Representation to Matrix
• Python - Count the frequency of matrix row length
• Python - Convert Integer Matrix to String Matrix
• Python Program to Convert Tuple Matrix to Tuple List
• Python - Group Elements in Matrix
• Python - Assigning Subsequent Rows to Matrix first row elements
• Adding and Subtracting Matrices in Python
• Python - Convert Matrix to dictionary
• Python - Convert Matrix to Custom Tuple Matrix
• Python - Matrix Row subset
• Python - Group similar elements into Matrix
• Python - Row-wise element Addition in Tuple Matrix
• Create an n x n square matrix, where all the sub-matrix have the sum of opposite corner elements as even

Python Functions Exercises

• Python splitfields() Method
• How to get list of parameters name from a function in Python?
• How to Print Multiple Arguments in Python?
• Python program to find the power of a number using recursion
• Sorting objects of user defined class in Python
• Assign Function to a Variable in Python
• Returning a function from a function - Python
• What are the allowed characters in Python function names?
• Defining a Python function at runtime
• Explicitly define datatype in a Python function
• Functions that accept variable length key value pair as arguments
• How to find the number of arguments in a Python function?
• How to check if a Python variable exists?
• Python - Get Function Signature
• Python program to convert any base to decimal by using int() method

Python Lambda Exercises

• Python - Lambda Function to Check if value is in a List
• Difference between Normal def defined function and Lambda
• Python: Iterating With Python Lambda
• How to use if, else & elif in Python Lambda Functions
• Python - Lambda function to find the smaller value between two elements
• Lambda with if but without else in Python
• Python Lambda with underscore as an argument
• Difference between List comprehension and Lambda in Python
• Nested Lambda Function in Python
• Python lambda
• Python | Sorting string using order defined by another string
• Python | Find fibonacci series upto n using lambda
• Overuse of lambda expressions in Python
• Python program to count Even and Odd numbers in a List
• Intersection of two arrays in Python ( Lambda expression and filter function )

Python Pattern printing Exercises

• Simple Diamond Pattern in Python
• Python - Print Heart Pattern
• Python program to display half diamond pattern of numbers with star border
• Python program to print Pascal's Triangle
• Python program to print the Inverted heart pattern
• Python Program to print hollow half diamond hash pattern
• Program to Print K using Alphabets
• Program to print half Diamond star pattern
• Program to print window pattern
• Python Program to print a number diamond of any given size N in Rangoli Style
• Python program to right rotate n-numbers by 1
• Python Program to print digit pattern
• Print with your own font using Python !!
• Python | Print an Inverted Star Pattern
• Program to print the diamond shape

Python DateTime Exercises

• Python - Iterating through a range of dates
• How to add time onto a DateTime object in Python
• How to add timestamp to excel file in Python
• Convert string to datetime in Python with timezone
• Isoformat to datetime - Python
• Python datetime to integer timestamp
• How to convert a Python datetime.datetime to excel serial date number
• How to create filename containing date or time in Python
• Convert "unknown format" strings to datetime objects in Python
• Extract time from datetime in Python
• Convert Python datetime to epoch
• Python program to convert unix timestamp string to readable date
• Python - Group dates in K ranges
• Python - Divide date range to N equal duration
• Python - Last business day of every month in year

Python OOPS Exercises

• Get index in the list of objects by attribute in Python
• Python program to build flashcard using class in Python
• How to count number of instances of a class in Python?
• Shuffle a deck of card with OOPS in Python
• What is a clean, Pythonic way to have multiple constructors in Python?
• How to Change a Dictionary Into a Class?
• How to create an empty class in Python?
• Student management system in Python
• How to create a list of object in Python class

Python Regex Exercises

• Validate an IP address using Python without using RegEx
• Python program to find the type of IP Address using Regex
• Converting a 10 digit phone number to US format using Regex in Python
• Python program to find Indices of Overlapping Substrings
• Python program to extract Strings between HTML Tags
• Python - Check if String Contain Only Defined Characters using Regex
• How to extract date from Excel file using Pandas?
• Python program to find files having a particular extension using RegEx
• How to check if a string starts with a substring using regex in Python?
• How to Remove repetitive characters from words of the given Pandas DataFrame using Regex?
• Extract punctuation from the specified column of Dataframe using Regex
• Extract IP address from file using Python
• Python program to Count Uppercase, Lowercase, special character and numeric values using Regex
• Categorize Password as Strong or Weak using Regex in Python
• Python - Substituting patterns in text using regex

• Python program to Search an Element in a Circular Linked List
• Implementation of XOR Linked List in Python
• Pretty print Linked List in Python
• Python Library for Linked List
• Python | Stack using Doubly Linked List
• Python | Queue using Doubly Linked List
• Program to reverse a linked list using Stack
• Python program to find middle of a linked list using one traversal
• Python Program to Reverse a linked list

Python Searching Exercises

• Binary Search (bisect) in Python
• Python Program for Linear Search
• Python Program for Anagram Substring Search (Or Search for all permutations)
• Python Program for Binary Search (Recursive and Iterative)
• Python Program for Rabin-Karp Algorithm for Pattern Searching
• Python Program for KMP Algorithm for Pattern Searching

Python Sorting Exercises

• Python Code for time Complexity plot of Heap Sort
• Python Program for Stooge Sort
• Python Program for Recursive Insertion Sort
• Python Program for Cycle Sort
• Bisect Algorithm Functions in Python
• Python Program for BogoSort or Permutation Sort
• Python Program for Odd-Even Sort / Brick Sort
• Python Program for Gnome Sort
• Python Program for Cocktail Sort
• Python Program for Bitonic Sort
• Python Program for Pigeonhole Sort
• Python Program for Comb Sort
• Python Program for Iterative Merge Sort
• Python Program for Binary Insertion Sort
• Python Program for ShellSort

Python DSA Exercises

• Saving a Networkx graph in GEXF format and visualize using Gephi
• Dumping queue into list or array in Python
• Python program to reverse a stack
• Python - Stack and StackSwitcher in GTK+ 3
• Multithreaded Priority Queue in Python
• Python Program to Reverse the Content of a File using Stack
• Priority Queue using Queue and Heapdict module in Python
• Box Blur Algorithm - With Python implementation
• Python program to reverse the content of a file and store it in another file
• Check whether the given string is Palindrome using Stack
• Take input from user and store in .txt file in Python
• Change case of all characters in a .txt file using Python
• Finding Duplicate Files with Python

Python File Handling Exercises

• Python Program to Count Words in Text File
• Python Program to Delete Specific Line from File
• Python Program to Replace Specific Line in File
• Python Program to Print Lines Containing Given String in File
• Python - Loop through files of certain extensions
• Compare two Files line by line in Python
• How to keep old content when Writing to Files in Python?
• How to get size of folder using Python?
• How to read multiple text files from folder in Python?
• Read a CSV into list of lists in Python
• Python - Write dictionary of list to CSV
• Convert nested JSON to CSV in Python
• How to add timestamp to CSV file in Python

Python CSV Exercises

• How to create multiple CSV files from existing CSV file using Pandas ?
• How to read all CSV files in a folder in Pandas?
• How to Sort CSV by multiple columns in Python ?
• Working with large CSV files in Python
• How to convert CSV File to PDF File using Python?
• Visualize data from CSV file in Python
• Python - Read CSV Columns Into List
• Sorting a CSV object by dates in Python
• Python program to extract a single value from JSON response
• Convert class object to JSON in Python
• Convert multiple JSON files to CSV Python
• Convert JSON data Into a Custom Python Object
• Convert CSV to JSON using Python

Python JSON Exercises

• Flattening JSON objects in Python
• Saving Text, JSON, and CSV to a File in Python
• Convert Text file to JSON in Python
• Convert JSON to CSV in Python
• Convert JSON to dictionary in Python
• Python Program to Get the File Name From the File Path
• How to get file creation and modification date or time in Python?
• Menu driven Python program to execute Linux commands
• Menu Driven Python program for opening the required software Application
• Open computer drives like C, D or E using Python

Python OS Module Exercises

• Rename a folder of images using Tkinter
• Kill a Process by name using Python
• Finding the largest file in a directory using Python
• Python - Get list of running processes
• Python - Get file id of windows file
• Python - Get number of characters, words, spaces and lines in a file
• Change current working directory with Python
• How to move Files and Directories in Python
• How to get a new API response in a Tkinter textbox?
• Build GUI Application for Guess Indian State using Tkinter Python
• How to stop copy, paste, and backspace in text widget in tkinter?
• How to temporarily remove a Tkinter widget without using just .place?
• How to open a website in a Tkinter window?

Python Tkinter Exercises

• Create Address Book in Python - Using Tkinter
• Changing the colour of Tkinter Menu Bar
• How to check which Button was clicked in Tkinter ?
• How to add a border color to a button in Tkinter?
• How to Change Tkinter LableFrame Border Color?
• Looping through buttons in Tkinter
• Visualizing Quick Sort using Tkinter in Python
• How to Add padding to a tkinter widget only on one side ?
• Python NumPy - Practice Exercises, Questions, and Solutions
• Pandas Exercises and Programs
• How to get the Daily News using Python
• How to Build Web scraping bot in Python
• Scrape LinkedIn Using Selenium And Beautiful Soup in Python
• Scraping Reddit with Python and BeautifulSoup
• Scraping Indeed Job Data Using Python

Python Web Scraping Exercises

• How to Scrape all PDF files in a Website?
• How to Scrape Multiple Pages of a Website Using Python?
• Quote Guessing Game using Web Scraping in Python
• How to extract youtube data in Python?
• How to Download All Images from a Web Page in Python?
• Test the given page is found or not on the server Using Python
• How to Extract Wikipedia Data in Python?
• How to extract paragraph from a website and save it as a text file?
• Automate Youtube with Python
• Controlling the Web Browser with Python
• How to Build a Simple Auto-Login Bot with Python
• How To Automate Google Chrome Using Foxtrot and Python

Python Selenium Exercises

• How to scroll down followers popup in Instagram ?
• How to switch to new window in Selenium for Python?
• Python Selenium - Find element by text
• How to scrape multiple pages using Selenium in Python?
• Python Selenium - Find Button by text
• Scrape Table from Website using Python - Selenium
• Selenium - Search for text on page

Python Exercise: Practice makes a man perfect. This proverb always proves itself correct. Just like this, if you are a Python learner, then Python coding practice makes you more confident and sharpens your skills. So, to test your skills, go through these Python exercises with solutions.

Python is a widely used general-purpose high-level language that can be used for many purposes like creating GUI, web Scraping, web development, etc. You might have seen various Python tutorials that explain the concepts in detail but that might not be enough to get hold of this language. The best way to learn is by practising it more and more.

The best thing about this Python practice exercise is that it helps you learn Python using sets of detailed programming questions from basic to advance. It covers questions on core Python concepts as well as applications of Python in various domains.

Python List Exercises

• Python program to interchange first and last elements in a list
• Python program to swap two elements in a list
• Python | Ways to find length of list
• Maximum of two numbers in Python
• Minimum of two numbers in Python

>> More Programs on List

Python String Exercises

• Python program to check whether the string is Symmetrical or Palindrome
• Reverse words in a given String in Python
• Ways to remove i’th character from string in Python
• Find length of a string in python (4 ways)
• Python program to print even length words in a string

>> More Programs on String

Python Tuple Exercises

• Python program to Find the size of a Tuple
• Python – Maximum and Minimum K elements in Tuple
• Python – Sum of tuple elements
• Python – Row-wise element Addition in Tuple Matrix
• Create a list of tuples from given list having number and its cube in each tuple

>> More Programs on Tuple

Python Dictionary Exercises

• Python | Sort Python Dictionaries by Key or Value
• Handling missing keys in Python dictionaries
• Python dictionary with keys having multiple inputs
• Python program to find the sum of all items in a dictionary
• Python program to find the size of a Dictionary

>> More Programs on Dictionary

Python Set Exercises

• Find the size of a Set in Python
• Iterate over a set in Python
• Python – Maximum and Minimum in a Set
• Python – Remove items from Set
• Python – Check if two lists have atleast one element common

>> More Programs on Sets

• Python – Assigning Subsequent Rows to Matrix first row elements
• Python – Group similar elements into Matrix

>> More Programs on Matrices

>> More Programs on Functions

• Python | Find the Number Occurring Odd Number of Times using Lambda expression and reduce function

>> More Programs on Lambda

• Programs for printing pyramid patterns in Python

>> More Programs on Python Pattern Printing

• Python program to get Current Time
• Get Yesterday’s date using Python
• Python program to print current year, month and day
• Python – Convert day number to date in particular year
• Get Current Time in different Timezone using Python

>> More Programs on DateTime

>> More Programs on Python OOPS

• Python – Check if String Contain Only Defined Characters using Regex

>> More Programs on Python Regex

>> More Programs on Linked Lists

>> More Programs on Python Searching

• Python Program for Bubble Sort
• Python Program for QuickSort
• Python Program for Insertion Sort
• Python Program for Selection Sort
• Python Program for Heap Sort

>> More Programs on Python Sorting

• Program to Calculate the Edge Cover of a Graph
• Python Program for N Queen Problem

>> More Programs on Python DSA

• Read content from one file and write it into another file
• Write a dictionary to a file in Python
• How to check file size in Python?
• Find the most repeated word in a text file
• How to read specific lines from a File in Python?

>> More Programs on Python File Handling

• Update column value of CSV in Python
• How to add a header to a CSV file in Python?
• Get column names from CSV using Python
• Writing data from a Python List to CSV row-wise

>> More Programs on Python CSV

>> More Programs on Python JSON

• Python Script to change name of a file to its timestamp

>> More Programs on OS Module

• Python | Create a GUI Marksheet using Tkinter
• Python | ToDo GUI Application using Tkinter
• Python | GUI Calendar using Tkinter
• File Explorer in Python using Tkinter
• Visiting Card Scanner GUI Application using Python

>> More Programs on Python Tkinter

NumPy Exercises

• How to create an empty and a full NumPy array?
• Create a Numpy array filled with all zeros
• Create a Numpy array filled with all ones
• Replace NumPy array elements that doesn’t satisfy the given condition
• Get the maximum value from given matrix

>> More Programs on NumPy

Pandas Exercises

• Make a Pandas DataFrame with two-dimensional list | Python
• How to iterate over rows in Pandas Dataframe
• Create a pandas column using for loop
• Create a Pandas Series from array
• Pandas | Basic of Time Series Manipulation

>> More Programs on Python Pandas

>> More Programs on Web Scraping

• Download File in Selenium Using Python
• Bulk Posting on Facebook Pages using Selenium
• Google Maps Selenium automation using Python
• Count total number of Links In Webpage Using Selenium In Python
• Extract Data From JustDial using Selenium

>> More Programs on Python Selenium

• Number guessing game in Python
• 2048 Game in Python
• Get Live Weather Desktop Notifications Using Python
• 8-bit game using pygame
• Tic Tac Toe GUI In Python using PyGame

>> More Projects in Python

In closing, we just want to say that the practice of solving Python problems always helps to clear your core concepts. We have designed these Python practice exercises after deep research so that one can easily enhance their skills and logic abilities.

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Problem Solving with Algorithms and Data Structures using Python ¶

By Brad Miller and David Ranum, Luther College

There is a wonderful collection of YouTube videos recorded by Gerry Jenkins to support all of the chapters in this text.

• 1.1. Objectives
• 1.2. Getting Started
• 1.3. What Is Computer Science?
• 1.4. What Is Programming?
• 1.5. Why Study Data Structures and Abstract Data Types?
• 1.6. Why Study Algorithms?
• 1.7. Review of Basic Python
• 1.8.1. Built-in Atomic Data Types
• 1.8.2. Built-in Collection Data Types
• 1.9.1. String Formatting
• 1.10. Control Structures
• 1.11. Exception Handling
• 1.12. Defining Functions
• 1.13.1. A Fraction Class
• 1.13.2. Inheritance: Logic Gates and Circuits
• 1.14. Summary
• 1.15. Key Terms
• 1.16. Discussion Questions
• 1.17. Programming Exercises
• 2.1.1. A Basic implementation of the MSDie class
• 2.2. Making your Class Comparable
• 3.1. Objectives
• 3.2. What Is Algorithm Analysis?
• 3.3. Big-O Notation
• 3.4.1. Solution 1: Checking Off
• 3.4.2. Solution 2: Sort and Compare
• 3.4.3. Solution 3: Brute Force
• 3.4.4. Solution 4: Count and Compare
• 3.5. Performance of Python Data Structures
• 3.7. Dictionaries
• 3.8. Summary
• 3.9. Key Terms
• 3.10. Discussion Questions
• 3.11. Programming Exercises
• 4.1. Objectives
• 4.2. What Are Linear Structures?
• 4.3. What is a Stack?
• 4.4. The Stack Abstract Data Type
• 4.5. Implementing a Stack in Python
• 4.6. Simple Balanced Parentheses
• 4.7. Balanced Symbols (A General Case)
• 4.8. Converting Decimal Numbers to Binary Numbers
• 4.9.1. Conversion of Infix Expressions to Prefix and Postfix
• 4.9.2. General Infix-to-Postfix Conversion
• 4.9.3. Postfix Evaluation
• 4.10. What Is a Queue?
• 4.11. The Queue Abstract Data Type
• 4.12. Implementing a Queue in Python
• 4.13. Simulation: Hot Potato
• 4.14.1. Main Simulation Steps
• 4.14.2. Python Implementation
• 4.14.3. Discussion
• 4.15. What Is a Deque?
• 4.16. The Deque Abstract Data Type
• 4.17. Implementing a Deque in Python
• 4.18. Palindrome-Checker
• 4.19. Lists
• 4.20. The Unordered List Abstract Data Type
• 4.21.1. The Node Class
• 4.21.2. The Unordered List Class
• 4.22. The Ordered List Abstract Data Type
• 4.23.1. Analysis of Linked Lists
• 4.24. Summary
• 4.25. Key Terms
• 4.26. Discussion Questions
• 4.27. Programming Exercises
• 5.1. Objectives
• 5.2. What Is Recursion?
• 5.3. Calculating the Sum of a List of Numbers
• 5.4. The Three Laws of Recursion
• 5.5. Converting an Integer to a String in Any Base
• 5.6. Stack Frames: Implementing Recursion
• 5.7. Introduction: Visualizing Recursion
• 5.8. Sierpinski Triangle
• 5.9. Complex Recursive Problems
• 5.10. Tower of Hanoi
• 5.11. Exploring a Maze
• 5.12. Dynamic Programming
• 5.13. Summary
• 5.14. Key Terms
• 5.15. Discussion Questions
• 5.16. Glossary
• 5.17. Programming Exercises
• 6.1. Objectives
• 6.2. Searching
• 6.3.1. Analysis of Sequential Search
• 6.4.1. Analysis of Binary Search
• 6.5.1. Hash Functions
• 6.5.2. Collision Resolution
• 6.5.3. Implementing the Map Abstract Data Type
• 6.5.4. Analysis of Hashing
• 6.6. Sorting
• 6.7. The Bubble Sort
• 6.8. The Selection Sort
• 6.9. The Insertion Sort
• 6.10. The Shell Sort
• 6.11. The Merge Sort
• 6.12. The Quick Sort
• 6.13. Summary
• 6.14. Key Terms
• 6.15. Discussion Questions
• 6.16. Programming Exercises
• 7.1. Objectives
• 7.2. Examples of Trees
• 7.3. Vocabulary and Definitions
• 7.4. List of Lists Representation
• 7.5. Nodes and References
• 7.6. Parse Tree
• 7.7. Tree Traversals
• 7.8. Priority Queues with Binary Heaps
• 7.9. Binary Heap Operations
• 7.10.1. The Structure Property
• 7.10.2. The Heap Order Property
• 7.10.3. Heap Operations
• 7.11. Binary Search Trees
• 7.12. Search Tree Operations
• 7.13. Search Tree Implementation
• 7.14. Search Tree Analysis
• 7.15. Balanced Binary Search Trees
• 7.16. AVL Tree Performance
• 7.17. AVL Tree Implementation
• 7.18. Summary of Map ADT Implementations
• 7.19. Summary
• 7.20. Key Terms
• 7.21. Discussion Questions
• 7.22. Programming Exercises
• 8.1. Objectives
• 8.2. Vocabulary and Definitions
• 8.3. The Graph Abstract Data Type
• 8.4. An Adjacency Matrix
• 8.5. An Adjacency List
• 8.6. Implementation
• 8.7. The Word Ladder Problem
• 8.8. Building the Word Ladder Graph
• 8.9. Implementing Breadth First Search
• 8.10. Breadth First Search Analysis
• 8.11. The Knight’s Tour Problem
• 8.12. Building the Knight’s Tour Graph
• 8.13. Implementing Knight’s Tour
• 8.14. Knight’s Tour Analysis
• 8.15. General Depth First Search
• 8.16. Depth First Search Analysis
• 8.17. Topological Sorting
• 8.18. Strongly Connected Components
• 8.19. Shortest Path Problems
• 8.20. Dijkstra’s Algorithm
• 8.21. Analysis of Dijkstra’s Algorithm
• 8.22. Prim’s Spanning Tree Algorithm
• 8.23. Summary
• 8.24. Key Terms
• 8.25. Discussion Questions
• 8.26. Programming Exercises

Acknowledgements ¶

We are very grateful to Franklin Beedle Publishers for allowing us to make this interactive textbook freely available. This online version is dedicated to the memory of our first editor, Jim Leisy, who wanted us to “change the world.”

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35 Python Programming Exercises and Solutions

To understand a programming language deeply, you need to practice what you’ve learned. If you’ve completed learning the syntax of Python programming language, it is the right time to do some practice programs.

In this article, I’ll list down some problems that I’ve done and the answer code for each exercise. Analyze each problem and try to solve it by yourself. If you have any doubts, you can check the code that I’ve provided below. I’ve also attached the corresponding outputs.

1. Python program to check whether the given number is even or not.

2. python program to convert the temperature in degree centigrade to fahrenheit, 3. python program to find the area of a triangle whose sides are given, 4. python program to find out the average of a set of integers, 5. python program to find the product of a set of real numbers, 6. python program to find the circumference and area of a circle with a given radius, 7. python program to check whether the given integer is a multiple of 5, 8. python program to check whether the given integer is a multiple of both 5 and 7, 9. python program to find the average of 10 numbers using while loop, 10. python program to display the given integer in a reverse manner, 11. python program to find the geometric mean of n numbers, 12. python program to find the sum of the digits of an integer using a while loop, 13. python program to display all the multiples of 3 within the range 10 to 50, 14. python program to display all integers within the range 100-200 whose sum of digits is an even number, 15. python program to check whether the given integer is a prime number or not, 16. python program to generate the prime numbers from 1 to n, 17. python program to find the roots of a quadratic equation, 18. python program to print the numbers from a given number n till 0 using recursion, 19. python program to find the factorial of a number using recursion, 20. python program to display the sum of n numbers using a list, 21. python program to implement linear search, 22. python program to implement binary search, 23. python program to find the odd numbers in an array, 24. python program to find the largest number in a list without using built-in functions, 25. python program to insert a number to any position in a list, 26. python program to delete an element from a list by index, 27. python program to check whether a string is palindrome or not, 28. python program to implement matrix addition, 29. python program to implement matrix multiplication, 30. python program to check leap year, 31. python program to find the nth term in a fibonacci series using recursion, 32. python program to print fibonacci series using iteration, 33. python program to print all the items in a dictionary, 34. python program to implement a calculator to do basic operations, 35. python program to draw a circle of squares using turtle.

For practicing more such exercises, I suggest you go to  hackerrank.com  and sign up. You’ll be able to practice Python there very effectively.

Once you become comfortable solving coding challenges, it’s time to move on and build something cool with your skills. If you know Python but haven’t built an app before, I suggest you check out my  Create Desktop Apps Using Python & Tkinter  course. This interactive course will walk you through from scratch to building clickable apps and games using Python.

I hope these exercises were helpful to you. If you have any doubts, feel free to let me know in the comments.

Happy coding.

I'm the face behind Pythonista Planet. I learned my first programming language back in 2015. Ever since then, I've been learning programming and immersing myself in technology. On this site, I share everything that I've learned about computer programming.

10 thoughts on “ 35 Python Programming Exercises and Solutions ”

I don’t mean to nitpick and I don’t want this published but you might want to check code for #16. 4 is not a prime number.

Thanks man for pointing out the mistake. I’ve updated the code.

# 8. Python program to check whether the given integer is a multiple of both 5 and 7:

You can only check if integer is a multiple of 35. It always works the same – just multiply all the numbers you need to check for multiplicity.

For reverse the given integer n=int(input(“enter the no:”)) n=str(n) n=int(n[::-1]) print(n)

very good, tnks

Please who can help me with this question asap

A particular cell phone plan includes 50 minutes of air time and 50 text messages for \$15.00 a month. Each additional minute of air time costs \$0.25, while additional text messages cost \$0.15 each. All cell phone bills include an additional charge of \$0.44 to support 911 call centers, and the entire bill (including the 911 charge) is subject to 5 percent sales tax.

We are so to run the code in phyton

this is best app

Hello Ashwin, Thanks for sharing a Python practice

May be in a better way for reverse.

#”’ Reverse of a string

v_str = str ( input(‘ Enter a valid string or number :- ‘) ) v_rev_str=” for v_d in v_str: v_rev_str = v_d + v_rev_str

print( ‘reverse of th input string / number :- ‘, v_str ,’is :- ‘, v_rev_str.capitalize() )

#Reverse of a string ”’

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• ISBN-10 1590282574
• ISBN-13 978-1590282571
• Edition 2nd
• Publisher Franklin, Beedle & Associates
• Publication date August 22, 2011
• Language English
• Dimensions 7.5 x 0.9 x 9.2 inches
• Print length 438 pages
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Product details

• Publisher ‏ : ‎ Franklin, Beedle & Associates; 2nd edition (August 22, 2011)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 438 pages
• ISBN-10 ‏ : ‎ 1590282574
• ISBN-13 ‏ : ‎ 978-1590282571
• Item Weight ‏ : ‎ 1.7 pounds
• Dimensions ‏ : ‎ 7.5 x 0.9 x 9.2 inches
• #13 in Data Structure and Algorithms
• #265 in Computer Programming Languages
• #480 in Python Programming

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• The Anaconda Distribution of Python
• Installing Anaconda on Windows
• Installing Anaconda on MacOS
• Installing Anaconda on Linux
• Installing Python from Python.org
• Review Questions

Why Python?

You might be wondering "Why should I solve problems with Python?" There are other programming languages in the world such as MATLAB, LabView, C++ and Java. What makes Python useful for solving problems?

Python is a powerful programming language

Python defines the types of objects you build into your code. Unlike some other languages such as C, you do not need to declare the object type. The object type is also mutable, you can change the type of object easily and on the fly. There is a wide array of object types built into Python. Objects can change in size. Python objects can also contain mixed data types. Strings and floating point numbers can be part of the same list.

Python has an extensive Standard Library. A huge number of object types, functions and methods are available for use without importing any external modules. These include math functions, list methods, and calls to a computer's system. There is a lot that can be done with the Python Standard Library. The first couple of chapters of this book will just use the standard library. It can do a lot.

Python has over 100,000 external packages available for download and use. They are easy to install off of the Python Package Index, commonly called PyPI ("pie pee eye"). There is a Python package for just about everything. There are packages which can help you: interact with the web, make complex computations, calculate unit conversions, plot data, work with .csv, .xls, and .pdf files, manipulate images and video, read data from sensors and test equipment, train machine learning algorithms, design web apps, work with GIS data, work with astronautical data. There are and many more Python packages added to PyPI every day. In this book, we will use some of the more useful Python packages for problem solvers such as NumPy, Matplotlib, and SymPy.

Python is easy to learn and use

One way Problem solvers code solutions faster in Python faster than coding solutions in other programming languages is that Python is easy to learn and use. Python programs tend to be shorter and quicker to write than a program which completes a similar function in another languages. In the rapid design, prototype, test, iterate cycle programming solutions in Python can be written and tested quickly. Python is also an easy language for fellow problem solvers on your team to learn. Python's language syntax is also quite human readable. While programmers can become preoccupied with a program's runtime, it is development time that takes the longest.

Python is transportable

Python can be installed and run on each of the three major operating systems: Windows, Mac and Linux. On Mac and Linux Python comes installed out of the box. Just open up a terminal in on a MacOS or Linux machine and type python . That's it, you are now using Python. On Windows, I recommend downloading and installing the Anaconda distribution of Python. The Anaconda distribution of Python is free and can be installed on all three major operating systems.

Python is free

Some computer languages used for problem solving such as MATLAB and LabView cost money to download and install. Python is free to download and use. Python is also open source and individuals are free to modify, contribute to, and propose improvements to Python. All of the packages available on the Python Package Index are free to download and install. Many more packages, scripts and utilities can be found in open source code repositories on GitHub and BitBucket.

Python is growing

Python is growing in popularity. Python is particularly growing in the data sciences and in use with GIS systems, physical modeling, machine learning and computer vision. These are growing team problem-solving areas for engineers.

Take coding to new frontiers in space using Python

Get ready to embark on a journey of discovery, creativity, and problem-solving, with the amazing chance of having your code run on the International Space Station (ISS)! Astro Pi Mission Space Lab launches today, Monday 6 November, with a new scientific challenge for teams. In this brand-new version of Mission Space Lab, we have set teams a specific task: to calculate the speed of the ISS using live data from the Astro Pi sensors and camera modules. Watch ESA Astronaut candidate Rosemary Coogan announce this year’s challenge!

Calculate the speed of the ISS using Astro Pi sensors

Working in teams of 2 to 6 people, young people are invited to write a Python program that captures data from the Astro Pi computers on board the ISS to calculate its speed as it orbits planet Earth. Teams must write a program that performs this task in 10 minutes, the allotted time for running each program aboard the ISS, handling data and doing calculations in real time.

The Astro Pis are two Raspberry Pi computers stationed on the ISS, each equipped with a High Quality Camera, Sense HAT add-on board, Coral machine learning accelerator, all inside a hard casing designed especially for space travel.

The Sense HAT has a number of sensors that teams can choose to use to capture data:

• A gyroscope, accelerometer, and magnetometer inertial measurement unit (IMU) sensor
• A temperature sensor
• A humidity sensor
• A pressure sensor

To make the most of the Astro Pi Mission Space Lab learning challenge, we suggest running the activity as a series of sessions that gets your team(s)' thinking about how they can use the different sensors and camera modules,  and write a code that accomplishes its goal.

Getting started

One of the most exciting things about this year's Mission Space Lab is that it can be adapted based on the degree of knowledge/experience in coding of your team(s). Beginner programmers can follow the provided guide to write their program, while teams with more programming experience can come up with their own innovative solution.

Teams can use the Mission Space Lab creator guide to help design and write their programs, which contains all of the information you’ll need to write a program that can be run on the ISS. It is split into several sections for flexibility of delivery, and it includes talking points for planning and design, as well as technical instructions to support you to complete the coding of the applications in Python. We have also created a project guide which shows you how to calculate the ISS’ speed using static photos, just one of the ways that teams can approach this challenge.

Mission Space Lab is open for submissions from 6 November 2023 until 19 February 2024. Don’t miss the chance to participate in this unique space activity!

Check out the Astro Pi website for full details astro-pi.org/mission-space-lab .

The European Astro Pi Challenge is an ESA Education project run in collaboration with the Raspberry Pi Foundation.

You can keep up with all Astro Pi news by following the Astro Pi X account (formerly Twitter) or signing up to the newsletter at astro-pi.org .

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Problem-Solving Method of Teaching: All You Need to Know

Ever wondered about the problem-solving method of teaching? We’ve got you covered, from its core principles to practical tips, benefits, and real-world examples.

The problem-solving method of teaching is a student-centered approach to learning that focuses on developing students’ problem-solving skills. In this method, students are presented with real-world problems to solve, and they are encouraged to use their own knowledge and skills to come up with solutions. The teacher acts as a facilitator, providing guidance and support as needed, but ultimately the students are responsible for finding their own solutions.

Problem-Solving Method of Teaching – Agenda of the Day

5 most important benefits of problem-solving method of teaching, find out examples of the problem-solving method of teaching, 5 how tos for using the problem-solving method of teaching, how to choose: let’s draw a comparison.

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The new way of teaching primarily helps students develop critical thinking skills and real-world application abilities. It also promotes independence and self-confidence in problem-solving.

The problem-solving method of teaching has a number of benefits. It helps students to:

1. Enhances critical thinking: By presenting students with real-world problems to solve, the problem-solving method of teaching forces them to think critically about the situation and to come up with their own solutions. This process helps students to develop their critical thinking skills, which are essential for success in school and in life.

2. Fosters creativity: The problem-solving method of teaching encourages students to be creative in their approach to solving problems. There is often no one right answer to a problem, so students are free to come up with their own unique solutions. This process helps students to develop their creativity, which is an important skill in all areas of life.

3. Encourages real-world application: The problem-solving method of teaching helps students learn how to apply their knowledge to real-world situations. By solving real-world problems, students are able to see how their knowledge is relevant to their lives and to the world around them. This helps students to become more motivated and engaged learners.

4. Builds student confidence: When students are able to successfully solve problems, they gain confidence in their abilities. This confidence is essential for success in all areas of life, both academic and personal.

5. Promotes collaborative learning: The problem-solving method of teaching often involves students working together to solve problems. This collaborative learning process helps students to develop their teamwork skills and to learn from each other.

Know 6 Steps in the Problem-Solving Method of Teaching

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The problem-solving method of teaching typically involves the following steps:

• Identifying the problem. The first step is to identify the problem that students will be working on. This can be done by presenting students with a real-world problem, or by asking them to come up with their own problems.
• Understanding the problem. Once students have identified the problem, they need to understand it fully. This may involve breaking the problem down into smaller parts or gathering more information about the problem.
• Generating solutions. Once students understand the problem, they need to generate possible solutions. This can be done by brainstorming, or by using problem-solving techniques such as root cause analysis or the decision matrix.
• Evaluating solutions. Students need to evaluate the pros and cons of each solution before choosing one to implement.
• Implementing the solution. Once students have chosen a solution, they need to implement it. This may involve taking action or developing a plan.
• Evaluating the results. Once students have implemented the solution, they need to evaluate the results to see if it was successful. If the solution is not successful, students may need to go back to step 3 and generate new solutions.

Here are a few examples of how the problem-solving method of teaching can be used in different subjects:

• Math: Students could be presented with a real-world problem such as budgeting for a family or designing a new product. Students would then need to use their math skills to solve the problem.
• Science: Students could be presented with a science experiment, or asked to research a scientific topic and come up with a solution to a problem. Students would then need to use their science knowledge and skills to solve the problem.
• Social studies: Students could be presented with a historical event or current social issue, and asked to come up with a solution. Students would then need to use their social studies knowledge and skills to solve the problem.

Here are a few tips for using the problem-solving method of teaching effectively:

• Choose problems that are relevant to students’ lives and interests.
• Make sure that the problems are challenging but achievable.
• Provide students with the resources they need to solve the problems, such as books, websites, or experts.
• Encourage students to work collaboratively and to share their ideas.
• Be patient and supportive. Problem-solving can be a challenging process, but it is also a rewarding one.

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The following table compares the different problem-solving methods:

Which Method is the Most Suitable?

The most suitable method of teaching will depend on a number of factors, such as the subject matter, the student’s age and ability level, and the teacher’s own preferences. However, the problem-solving method of teaching is a valuable approach that can be used in any subject area and with students of all ages.

Here are some additional tips for using the problem-solving method of teaching effectively:

• Differentiate instruction. Not all students learn at the same pace or in the same way. Teachers can differentiate instruction to meet the needs of all learners by providing different levels of support and scaffolding.
• Use formative assessment. Formative assessment can be used to monitor students’ progress and to identify areas where they need additional support. Teachers can then use this information to provide students with targeted instruction.
• Create a positive learning environment. Students need to feel safe and supported in order to learn effectively. Teachers can create a positive learning environment by providing students with opportunities for collaboration, celebrating their successes, and creating a classroom culture where mistakes are seen as learning opportunities.

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Some Unique Examples to Refer to Before We Conclude

Here are a few unique examples of how the problem-solving method of teaching can be used in different subjects:

• English: Students could be presented with a challenging text, such as a poem or a short story, and asked to analyze the text and come up with their own interpretation.
• Art: Students could be asked to design a new product or to create a piece of art that addresses a social issue.
• Music: Students could be asked to write a song about a current event or to create a new piece of music that reflects their cultural heritage.

The problem-solving method of teaching is a powerful tool that can be used to help students develop the skills they need to succeed in school and in life. By creating a learning environment where students are encouraged to think critically and solve problems, teachers can help students to become lifelong learners.

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2. Python Practice Problems: Get Ready for Your Next Interview

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4. Python Practice Problems for Beginner Coders

The solutions provided are examples of working code to solve the presented problem. However, just like multiple responses to the same essay prompt will look different, every solution to a coding problem can be unique. As you develop your own coding style, you may prefer different approaches.

5. Python Exercises, Practice, Challenges

Select the exercise you want to solve. Basic Exercise for Beginners Practice and Quickly learn Python's necessary skills by solving simple questions and problems. Topics: Variables, Operators, Loops, String, Numbers, List Python Input and Output Exercise Solve input and output operations in Python. Also, we practice file handling.

6. PDF Algorithmic Problem Solving with Python

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8. Python Basics: Problem Solving with Code

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9. Simplest way to solve mathematical equations in Python

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10. Programming and Problem Solving using Python

This textbook is designed to learn python programming from scratch. At the beginning of the book general problem solving concepts such as types of problems, difficulties in problem solving, and problem solving aspects are discussed.From this book, you will start learning the Python programming by knowing about the variables, constants, keywords, data types, indentation and various programming ...

11. Python Exercises, Practice Questions and Solutions

Practice Python Exercise: Practice makes a man perfect. This proverb always proves itself correct. Just like this, if you are a Python learner, then Python coding practice makes you more confident and sharpens your skills. So, to test your skills, go through these Python exercises with solutions.

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13. Problem Solving with Algorithms and Data Structures using Python

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17. 35 Python Programming Exercises and Solutions

Analyze each problem and try to solve it by yourself. If you have any doubts, you can check the code that I've provided below. I've also attached the corresponding outputs. 1. Python program to check whether the given number is even or not.

18. Hands-On Linear Programming: Optimization With Python

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21. Why Python?

Some computer languages used for problem solving such as MATLAB and LabView cost money to download and install. Python is free to download and use. Python is also open source and individuals are free to modify, contribute to, and propose improvements to Python. All of the packages available on the Python Package Index are free to download and ...

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24. Problem-Solving Method of Teaching: All You Need to Know

The problem-solving method of teaching is a student-centered approach to learning that focuses on developing students' problem-solving skills. In this method, students are presented with real-world problems to solve, and they are encouraged to use their own knowledge and skills to come up with solutions. The teacher acts as a facilitator ...