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1: Character Input Solutions
2: Odd Or Even Solutions
3: List Less Than Ten Solutions
4: Divisors Solutions
5: List Overlap Solutions
6: String Lists Solutions
7: List Comprehensions Solutions
8: Rock Paper Scissors Solutions
9: Guessing Game One Solutions
10: List Overlap Comprehensions Solutions
11: Check Primality Functions Solutions
12: List Ends Solutions
13: Fibonacci Solutions
14: List Remove Duplicates Solutions
15: Reverse Word Order Solutions
16: Password Generator Solutions
17: Decode A Web Page Solutions
18: Cows And Bulls Solutions
19: Decode A Web Page Two Solutions
20: Element Search Solutions
21: Write To A File Solutions
22: Read From File Solutions
23: File Overlap Solutions
24: Draw A Game Board Solutions
25: Guessing Game Two Solutions
26: Check Tic Tac Toe Solutions
27: Tic Tac Toe Draw Solutions
28: Max Of Three Solutions
29: Tic Tac Toe Game Solutions
30: Pick Word Solutions
31: Guess Letters Solutions
32: Hangman Solutions
33: Birthday Dictionaries Solutions
34: Birthday Json Solutions
35: Birthday Months Solutions
36: Birthday Plots Solutions
37: Functions Refactor Solution
38: f Strings Solution
39: Character Input Datetime Solution
40: Error Checking Solution

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10 Python Practice Exercises for Beginners with Solutions

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A great way to improve quickly at programming with Python is to practice with a wide range of exercises and programming challenges. In this article, we give you 10 Python practice exercises to boost your skills.

Practice exercises are a great way to learn Python. Well-designed exercises expose you to new concepts, such as writing different types of loops, working with different data structures like lists, arrays, and tuples, and reading in different file types. Good exercises should be at a level that is approachable for beginners but also hard enough to challenge you, pushing your knowledge and skills to the next level.

If you’re new to Python and looking for a structured way to improve your programming, consider taking the Python Basics Practice course. It includes 17 interactive exercises designed to improve all aspects of your programming and get you into good programming habits early. Read about the course in the March 2023 episode of our series Python Course of the Month .

Take the course Python Practice: Word Games , and you gain experience working with string functions and text files through its 27 interactive exercises. Its release announcement gives you more information and a feel for how it works.

Each course has enough material to keep you busy for about 10 hours. To give you a little taste of what these courses teach you, we have selected 10 Python practice exercises straight from these courses. We’ll give you the exercises and solutions with detailed explanations about how they work.

To get the most out of this article, have a go at solving the problems before reading the solutions. Some of these practice exercises have a few possible solutions, so also try to come up with an alternative solution after you’ve gone through each exercise.

Let’s get started!

Exercise 1: User Input and Conditional Statements

Write a program that asks the user for a number then prints the following sentence that number of times: ‘I am back to check on my skills!’ If the number is greater than 10, print this sentence instead: ‘Python conditions and loops are a piece of cake.’ Assume you can only pass positive integers.

Here, we start by using the built-in function input() , which accepts user input from the keyboard. The first argument is the prompt displayed on the screen; the input is converted into an integer with int() and saved as the variable number. If the variable number is greater than 10, the first message is printed once on the screen. If not, the second message is printed in a loop number times.

Exercise 2: Lowercase and Uppercase Characters

Below is a string, text . It contains a long string of characters. Your task is to iterate over the characters of the string, count uppercase letters and lowercase letters, and print the result:

We start this one by initializing the two counters for uppercase and lowercase characters. Then, we loop through every letter in text and check if it is lowercase. If so, we increment the lowercase counter by one. If not, we check if it is uppercase and if so, we increment the uppercase counter by one. Finally, we print the results in the required format.

Exercise 3: Building Triangles

Create a function named is_triangle_possible() that accepts three positive numbers. It should return True if it is possible to create a triangle from line segments of given lengths and False otherwise. With 3 numbers, it is sometimes, but not always, possible to create a triangle: You cannot create a triangle from a = 13, b = 2, and c = 3, but you can from a = 13, b = 9, and c = 10.

The key to solving this problem is to determine when three lines make a triangle regardless of the type of triangle. It may be helpful to start drawing triangles before you start coding anything.

Notice that the sum of any two sides must be larger than the third side to form a triangle. That means we need a + b > c, c + b > a, and a + c > b. All three conditions must be met to form a triangle; hence we need the and condition in the solution. Once you have this insight, the solution is easy!

Exercise 4: Call a Function From Another Function

Create two functions: print_five_times() and speak() . The function print_five_times() should accept one parameter (called sentence) and print it five times. The function speak(sentence, repeat) should have two parameters: sentence (a string of letters), and repeat (a Boolean with a default value set to False ). If the repeat parameter is set to False , the function should just print a sentence once. If the repeat parameter is set to True, the function should call the print_five_times() function.

This is a good example of calling a function in another function. It is something you’ll do often in your programming career. It is also a nice demonstration of how to use a Boolean flag to control the flow of your program.

If the repeat parameter is True, the print_five_times() function is called, which prints the sentence parameter 5 times in a loop. Otherwise, the sentence parameter is just printed once. Note that in Python, writing if repeat is equivalent to if repeat == True .

Exercise 5: Looping and Conditional Statements

Write a function called find_greater_than() that takes two parameters: a list of numbers and an integer threshold. The function should create a new list containing all numbers in the input list greater than the given threshold. The order of numbers in the result list should be the same as in the input list. For example:

Here, we start by defining an empty list to store our results. Then, we loop through all elements in the input list and test if the element is greater than the threshold. If so, we append the element to the new list.

Notice that we do not explicitly need an else and pass to do nothing when integer is not greater than threshold . You may include this if you like.

Exercise 6: Nested Loops and Conditional Statements

Write a function called find_censored_words() that accepts a list of strings and a list of special characters as its arguments, and prints all censored words from it one by one in separate lines. A word is considered censored if it has at least one character from the special_chars list. Use the word_list variable to test your function. We've prepared the two lists for you:

This is another nice example of looping through a list and testing a condition. We start by looping through every word in word_list . Then, we loop through every character in the current word and check if the current character is in the special_chars list.

This time, however, we have a break statement. This exits the inner loop as soon as we detect one special character since it does not matter if we have one or several special characters in the word.

Exercise 7: Lists and Tuples

Create a function find_short_long_word(words_list) . The function should return a tuple of the shortest word in the list and the longest word in the list (in that order). If there are multiple words that qualify as the shortest word, return the first shortest word in the list. And if there are multiple words that qualify as the longest word, return the last longest word in the list. For example, for the following list:

the function should return

Assume the input list is non-empty.

The key to this problem is to start with a “guess” for the shortest and longest words. We do this by creating variables shortest_word and longest_word and setting both to be the first word in the input list.

We loop through the words in the input list and check if the current word is shorter than our initial “guess.” If so, we update the shortest_word variable. If not, we check to see if it is longer than or equal to our initial “guess” for the longest word, and if so, we update the longest_word variable. Having the >= condition ensures the longest word is the last longest word. Finally, we return the shortest and longest words in a tuple.

Exercise 8: Dictionaries

As you see, we've prepared the test_results variable for you. Your task is to iterate over the values of the dictionary and print all names of people who received less than 45 points.

Here, we have an example of how to iterate through a dictionary. Dictionaries are useful data structures that allow you to create a key (the names of the students) and attach a value to it (their test results). Dictionaries have the dictionary.items() method, which returns an object with each key:value pair in a tuple.

The solution shows how to loop through this object and assign a key and a value to two variables. Then, we test whether the value variable is greater than 45. If so, we print the key variable.

Exercise 9: More Dictionaries

Write a function called consonant_vowels_count(frequencies_dictionary, vowels) that takes a dictionary and a list of vowels as arguments. The keys of the dictionary are letters and the values are their frequencies. The function should print the total number of consonants and the total number of vowels in the following format:

For example, for input:

the output should be:

Working with dictionaries is an important skill. So, here’s another exercise that requires you to iterate through dictionary items.

We start by defining a list of vowels. Next, we need to define two counters, one for vowels and one for consonants, both set to zero. Then, we iterate through the input dictionary items and test whether the key is in the vowels list. If so, we increase the vowels counter by one, if not, we increase the consonants counter by one. Finally, we print out the results in the required format.

Exercise 10: String Encryption

Implement the Caesar cipher . This is a simple encryption technique that substitutes every letter in a word with another letter from some fixed number of positions down the alphabet.

For example, consider the string 'word' . If we shift every letter down one position in the alphabet, we have 'xpse' . Shifting by 2 positions gives the string 'yqtf' . Start by defining a string with every letter in the alphabet:

Name your function cipher(word, shift) , which accepts a string to encrypt, and an integer number of positions in the alphabet by which to shift every letter.

This exercise is taken from the Word Games course. We have our string containing all lowercase letters, from which we create a shifted alphabet using a clever little string-slicing technique. Next, we create an empty string to store our encrypted word. Then, we loop through every letter in the word and find its index, or position, in the alphabet. Using this index, we get the corresponding shifted letter from the shifted alphabet string. This letter is added to the end of the new_word string.

This is just one approach to solving this problem, and it only works for lowercase words. Try inputting a word with an uppercase letter; you’ll get a ValueError . When you take the Word Games course, you slowly work up to a better solution step-by-step. This better solution takes advantage of two built-in functions chr() and ord() to make it simpler and more robust. The course contains three similar games, with each game comprising several practice exercises to build up your knowledge.

Do You Want More Python Practice Exercises?

We have given you a taste of the Python practice exercises available in two of our courses, Python Basics Practice and Python Practice: Word Games . These courses are designed to develop skills important to a successful Python programmer, and the exercises above were taken directly from the courses. Sign up for our platform (it’s free!) to find more exercises like these.

We’ve discussed Different Ways to Practice Python in the past, and doing interactive exercises is just one way. Our other tips include reading books, watching videos, and taking on projects. For tips on good books for Python, check out “ The 5 Best Python Books for Beginners .” It’s important to get the basics down first and make sure your practice exercises are fun, as we discuss in “ What’s the Best Way to Practice Python? ” If you keep up with your practice exercises, you’ll become a Python master in no time!

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Python Exercise with Practice Questions and Solutions

Python Exercise: Practice makes you perfect in everything. This proverb always proves itself correct. Just like this, if you are a Python learner, then regular practice of Python exercises 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 advanced. It covers questions on core Python concepts as well as applications of Python in various domains. So if you are at any stage like beginner, intermediate or advanced this Python practice set will help you to boost your programming skills in Python.

List of Python Programming Exercises

In the below section, we have gathered chapter-wise Python exercises with solutions. So, scroll down to the relevant topics and try to solve the Python program practice set.

Table of Content

Python List Exercises

Python string exercises, python tuple exercises, python dictionary exercises, python set exercises, python matrix exercises, python functions exercises, python lambda exercises.

Python Pattern printing Exercises

Python DateTime Exercises

Python oops exercises, python regex exercises, python linkedlist exercises, python searching exercises, python sorting exercises, python dsa exercises, python file handling exercises, python csv exercises, python json exercises, python os module exercises, python tkinter exercises, numpy exercises, pandas exercises, python web scraping exercises, python selenium exercises.

In this section, we have compiled a variety of Python list exercises that range from basic to advanced levels. These exercises are designed to help you master the fundamentals of Python lists, including list creation, indexing, slicing, and common operations like appending, inserting, and removing elements.

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

In this section, we provide a variety of Python string exercises designed to enhance your understanding of string manipulation and operations. Explore these exercises and upsacle your Python programming skills.

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

Here, you’ll find a range of Python tuple exercises designed to help you understand and master this essential data structure. Tuples are immutable sequences used to store collections of items, and they’re a fundamental part of Python programming.

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

In this section, you’ll find a variety of Python dictionary exercises designed to help you master the use of dictionaries, one of Python’s most powerful and versatile data structures.

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

This section offers a range of Python set exercises that will help you build a strong understanding of set operations in Python. You’ll practice adding and removing elements, performing operations like union, intersection, and difference, and using set comprehensions.

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

Here, in this section you’ll find a collection of Python matrix exercises tailored for beginners and advanced Python programmers. These exercises focus on essential skills such as creating and manipulating matrices, performing operations like addition, subtraction, multiplication, and more.

Python – Assigning Subsequent Rows to Matrix first row elements
Adding and Subtracting Matrices in Python
Python – Group similar elements into Matrix
Create an n x n square matrix, where all the sub-matrix have the sum of opposite corner elements as even

>> More Programs on Matrices

This section offers a variety of exercises focused on Python functions to help you master this essential programming concept. You’ll learn how to define functions, work with parameters and return values, and explore advanced topics like lambda functions, decorators, and recursion.

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
Functions that accept variable length key value pair as arguments

>> More Programs on Functions

In this section, we’ve compiled a series of exercises focused on Python’s lambda functions, which allow you to write small, anonymous functions with concise syntax. These exercises will help you understand how to use lambda functions for quick data manipulation, sorting, filtering, and mapping operations.

Lambda with if but without else in Python
Python | Sorting string using order defined by another string
Python | Find fibonacci series upto n using lambda
Python program to count Even and Odd numbers in a List
Python | Find the Number Occurring Odd Number of Times using Lambda expression and reduce function

>> More Programs on Lambda

Program to print half Diamond star pattern
Programs for printing pyramid patterns in Python
Program to print the diamond shape
Python | Print an Inverted Star Pattern
Python Program to print digit pattern

>> More Programs on Python Pattern Printing

Enhance your Python skills by diving into various DateTime exercises that focus on handling dates and times effectively. These exercises will teach you how to use the datetime module to format dates, calculate time differences, manage time zones, and build time-sensitive applications.

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

Here in this practice section, you’ll find exercises focused on Object-Oriented Programming (OOP) concepts in Python. These exercises are designed to help you understand and implement key OOP principles such as classes, objects, inheritance, polymorphism, encapsulation, and abstraction.

Python program to build flashcard using class in Python
Shuffle a deck of card with OOPS in Python
How to create an empty class in Python?
Student management system in Python

>> More Programs on Python OOPS

Python Regex exercises to help you master the art of pattern matching and text manipulation. Regular expressions, or Regex, are powerful tools used to search, match, and manipulate strings based on specific patterns.

Python program to find the type of IP Address using Regex
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
Python program to find files having a particular extension using RegEx

>> More Programs on Python Regex

In this section, we’ve compiled a series of exercises focused on implementing and manipulating linked lists using Python. These exercises cover various operations, such as inserting nodes, deleting nodes, reversing linked lists, and detecting cycles, allowing you to practice and master linked list concepts.

Python program to Search an Element in a Circular Linked List
Pretty print Linked List in Python
Python | Stack using Doubly Linked List
Python | Queue using Doubly Linked List
Python program to find middle of a linked list using one traversal

>> More Programs on Linked Lists

This section offers a range of exercises designed to help you master searching algorithms in Python. You’ll learn how to implement techniques like linear search and binary search, as well as more advanced methods such as interpolation and exponential search.

Python Program for Linear Search
Python Program for Binary Search (Recursive and Iterative)
Python Program for Anagram Substring Search (Or Search for all permutations)

>> More Programs on Python Searching

This section provides a collection of exercises to help you practice and understand sorting in Python. You’ll explore various sorting algorithms, like bubble sort, merge sort, quicksort, and others, each with its unique approach to arranging data.

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

Strengthen your Python skills with Data Structures and Algorithms (DSA) exercises tailored to help you master the fundamental concepts of programming. These exercises cover a wide range of topics, including arrays, linked lists, stacks, queues, trees, graphs, and sorting algorithms, providing a hands-on approach to learning.

Python program to reverse a stack
Multithreaded Priority Queue in Python
Check whether the given string is Palindrome using Stack
Program to Calculate the Edge Cover of a Graph
Python Program for N Queen Problem

>> More Programs on Python DSA

In this section, you’ll find a variety of exercises focused on Python file handling to help you master reading from and writing to files. These exercises will guide you through the essentials, such as opening, reading, writing, closing files and more.

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

Working with CSV (Comma-Separated Values) files is a fundamental skill in data handling and analysis with Python. These exercises are designed to help you learn how to read, write, and manipulate CSV files using Python’s built-in csv module and libraries like pandas.

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
Convert multiple JSON files to CSV Python

>> More Programs on Python CSV

In this section, we provide a variety of exercises to help you master JSON (JavaScript Object Notation) in Python. JSON is a popular data format used for exchanging information between web clients and servers.

Convert class object to JSON in Python
Convert JSON data Into a Custom Python Object
Flattening JSON objects in Python
Convert CSV to JSON using Python

>> More Programs on Python JSON

Here in this section, we have compiled a list of exercises that will help you practice using the Python OS module to create, delete, and navigate directories, manage files, and interact with system processes.

How to get file creation and modification date or time in Python?
Menu Driven Python program for opening the required software Application
Python Script to change name of a file to its timestamp
Kill a Process by name using Python
Finding the largest file in a directory using Python

>> More Programs on OS Module

Python’s Tkinter library is a powerful tool for creating graphical user interfaces (GUIs). These exercises are designed to help you learn the basics of GUI development, such as creating buttons, labels, text boxes, and handling events.

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

Enhance your Python programming skills by diving into NumPy exercises designed to teach you the fundamentals of this powerful library. NumPy is essential for numerical computing in Python, providing support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on them.

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

In this section, you’ll find a variety of exercises designed to help you master the Pandas library in Python, a powerful tool for data manipulation and analysis. These exercises range from basic operations like data filtering, sorting, and grouping.

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

Explore a variety of Python web scraping exercises that will help you learn how to extract data from websites efficiently.

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?

>> More Programs on Web Scraping

Here you’ll find exercises that help you master web automation using Selenium, a powerful tool for controlling web browsers through Python scripts.

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 or solving Python problems always helps to clear your core concepts and programming logic. Hence, we have designed this Python exercises after deep research so that one can easily enhance their skills and logic abilities.

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24/7 support : Need help at any hour? DoMyAssignments runs 24/7, providing immediate access to competent technicians via live chat. Whether you have urgent questions about their policies or need clarification on specific details, you can expect fast and clear answers.
Individual approach : Personalized service is a standout feature of DoMyAssignments. You can contact your helper at predetermined hours to discuss your project’s progress. This direct communication allows for real-time updates and changes, offering a convenient way to ensure that your project aligns perfectly with your requirements.

You should also know that it practices an individual approach. You are welcome to contact your helper during the predetermined hours. Just discuss with him or her when both of you can be online and check the progress of your project. It’s a fast and convenient way to offer changes on demand and without delays.

3. AssignCode.com: Fast and Reliable Python Homework Help

If speed is your priority, AssignCode is an excellent choice. How fast can you do my Python homework? Well, a lot depends on the demands you have. Nonetheless, most projects are completed there in 4–5 hours only!

Thus, you can place an order even later at night to get it done early in the morning. Just be sure you set manageable conditions. If it’s so, your order will be accepted and completed according to your demands. It will be delivered on time. As for other vital guarantees, you may count on:

Great quality. This company has a professional staff, which consists of outstanding programmers. They all have confirmed their qualifications and were trained to match the top demands of every high school, college, or university. They can help even already working coders who face some issues at the moment.
Fair prices. You will surely like the prices set by this coding company. They are quite cheap, and ordinary students will not face problems with ordering professional help on this site. There is a possibility to quickly regulate the prices online. You only need to change the quality, type, volume, or deadline of your assignment. A refund guarantee is given as well.
All kinds of features . This platform is able to satisfy the slightest demands of the strictest customers. Everything will be done exactly as you want, and can contact your helper directly. He or she will offer all the necessary skills to complete your project perfectly. The platform’s specialists handle all assignment types. Python is only one of the possible areas of their competence.
A responsive customer support team. In case you don’t understand some policies or limits of this company, turn to its team of support. It consists of polite and knowledgeable operators. They work day and night to provide detailed responses in about 2 minutes or so.

Also read: The 10 Commandments of Coding: Study, Learn and Put into Practice

4. CWAssignments.com: Unique and Customized Python Assistance

Many students cannot create unique projects in coding, and that is why they may require the unique Python assignment help of CWAssignments . Its rating is 9.4 out of 10, which is a sign of a top-class coding site.

It does all the projects anew and never uses the projects of other coders. Its experts don’t reuse even their old assignments. The new conditions are taken into account and fulfilled uniquely. It also offers other vital benefits. These are as follows:

Reasonable pricing . You will not spend too much if you request assistance there. The site sets relatively cheap prices and offers full customization of the orders. This puts you in full charge of the total cost. Fill out the compulsory fields and change them to see how you can impact the cost to stop when it suits your budget.
Top quality. The agency hires only educated and talented coders. They surely understand how to handle any assignment in computer science, engineering, and math. They stick to the official requirements of all educational institutions and can satisfy even the most scrupulous educators. Thus, your chance to get an A+ grade sufficiently increases.
A personified approach. You may get in touch with your solver whenever his or her aid may be required. Just set a reasonable schedule when both of you can be online to discuss the peculiarities of your order. The specialists will provide updated reports to let you know where your project stands.
Total online confidentiality . This is a reliable and respectful coding platform that always protects the private data of its clients. It never shares any facts about them with anyone else. It utilizes effective software that protects its databases from all types of online dangers. Thanks to the billing methods offered by the site, you may not worry about your transactions within it. They are encrypted and hidden from other users.

5. HelpHomework.net: Personalized Approach to Python Coding

Many learners seek personalized attention for their coding projects. If you need a tailored approach to Python homework help, HelpHomework is the place to go. It offers flexible scheduling for real-time collaboration with your solver.

Simply coordinate a schedule to be online with your solver, using your preferred instant messenger for quick updates. Along with this personalized approach, the platform also provides other key guarantees, including:

Outstanding Quality: This platform hires only certified coders who pass a rigorous selection process. They’re trained to handle any assignments in computer science, engineering, and math, ensuring precise completion to boost your success.
Plagiarism-Free Projects: The platform ensures uniqueness in every project. Though coding may seem repetitive, the specialists craft each project from scratch, meeting educators’ expectations for originality.
24/7 Support and Supervision: Visit this site anytime, day or night. It operates around the clock, with kind operators ready to provide swift, detailed responses in live chat.
Reasonable Prices: Offering affordable rates to fit students’ budgets, the company allows you to customize your order’s price by adjusting the project’s quality, size, type, and deadline.

6. CodingAssignments.com: A Wide Range of Python Experts at Your Service

A rich choice of specialists is significant to all. If you want to be sure that you will always find the kind of help with Python assignments or other programming languages, you should opt for CodingAssignments .

This highly reputed coding company boasts over 700 specialists. Thus, you will never be deprived of some privileges. You will find perfect solvers for whatever coding project you must do. The company likewise provides the next benefits:

On-time deliveries. The experts of the company value the precious time of their customers. They polish all the necessary skills and master the most effective time management methods to meet really short deadlines. Just provide manageable terms. If the assignment is too large and urgent, place it as early as you can. The specialists will check the odds and will surely accept it if it can be completed within the stated period of time.
Fair pricing . You can count on relatively cheap prices when you deal with this programming site. Thus, common students will be able to afford its aid. Besides, you can count on pleasant promo codes and discounts to save up even more of your funds. Thanks to the refund guarantee, all your investments are secured.
Full online anonymity. Don’t worry about your online safety when you visit this site. It guards its databases and your private information with reliable antivirus software. The site never reveals any details about its customers to anybody else.
Hourly supervision . This coding platform operates 24 hours round the clock to let its customers place urgent orders even late at night. Find the chat window and specify the problem you’re facing. There are always operators at work. They provide detailed answers in a couple of minutes or faster.

Also check: Python Course for Beginners Online FREE

FAQs About The Best Python Homework Help Websites

Let’s answer some of the commonly asked questions around our topic of discussion today.

Can I pay someone to do my Python assignment?

Using a legal online coding site requires payment, so choose wisely as different sites set different prices. While 2 sites offer the same level of quality, it would not be wise to choose the one with a more expensive price policy. You’d better study this case before you place the first order.

How can I pay someone to do my Python homework?

To pay for Python homework, register on the site and add a billing method such as PayPal, Visa, or Pioneer. The methods are very convenient and safe. Make sure your debit or credit card has enough money. When you place an order, you will pay the price automatically. The money will be in escrow until the job is done. Check its quality, and if it suits you, release the final payment to your solver.

How can I receive assistance with Python projects?

You can receive professional coding assistance by finding the right coding platforms and hiring the most suitable Python experts. Conduct thorough research to identify the most reliable and suitable sites.

One of the components of your research is surely reading reviews similar to ours. It helps to narrow down the list of potential helping platforms.

Once you’re on the site, check its top performers. Although their prices are higher, you will be safe about the success of your project. Yet, other experts with low ratings can suit you as well. Just check their detailed profiles and read reviews of other clients to be sure they can satisfy all your needs. Hire the required solver, explain what must be done, and pay to get it started.

Where can I get help with Python programming?

You can find Python programming homework help on the Internet. Open the browser and write an accurate keyword search combination.

It may be something like this – the swiftest or cheapest, or best coding site. Check the results, read customers’ reviews, check the reviews of rating agencies (like ours), compare the conditions, and select the most beneficial option for you.

What kind of guarantees can I expect from Python help services?

If you want to find help with Python projects and you will be treated fairly, you need to know the main guarantees every highly reputed programming site is supposed to ensure. These are as follows:

High quality
Availability of all skills and assignments
An individual approach
Full privacy of your data
Timely deliveries
100% authentic projects
24/7 access and support
Refunds and free revisions

These are the essential guarantees that every legitimate coding site must provide. If some of them lack, it may be better to switch to another option. These guarantees are compulsory, and you should enjoy them all automatically.

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.

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.

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

12 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.

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.

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

What is Python language?

Python is a widely used high-level, general-purpose, interpreted, dynamic programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than possible in languages such as C++ or Java.

Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library

The best way we learn anything is by practice and exercise questions. We have started this section for those (beginner to intermediate) who are familiar with Python.

Hope, these exercises help you to improve your Python coding skills. Currently, following sections are available, we are working hard to add more exercises .... Happy Coding!

You may read our Python tutorial before solving the following exercises.

Latest Articles : Python Interview Questions and Answers Python PyQt

List of Python Exercises :

Python Basic (Part -I) [ 150 Exercises with Solution ]
Python Basic (Part -II) [ 150 Exercises with Solution ]
Python Programming Puzzles [ 100 Exercises with Solution ]
Mastering Python [ 150 Exercises with Solution ]
Python Advanced [ 15 Exercises with Solution ]
Python Conditional statements and loops [ 44 Exercises with Solution]
Recursion [ 11 Exercises with Solution ]
Python Data Types - String [ 113 Exercises with Solution ]
Python JSON [ 9 Exercises with Solution ]
Python Data Types - List [ 281 Exercises with Solution ]
Python Data Types - List Advanced [ 15 Exercises with Solution ]
Python Data Types - Dictionary [ 80 Exercises with Solution ]
Python Data Types - Tuple [ 33 Exercises with Solution ]
Python Data Types - Sets [ 30 Exercises with Solution ]
Python Data Types - Collections [ 36 Exercises with Solution ]
Python Array [ 24 Exercises with Solution ]
Python Enum [ 5 Exercises with Solution ]
Python Class [ 28 Exercises with Solution ]
Python Unit test [ 10 Exercises with Solution ]
Python Exception Handling [ 10 exercises with solution ]
Python Object-Oriented Programming [ 11 Exercises with Solution ]
Python Decorator [ 12 Exercises with Solution ]
Python functions [ 21 Exercises with Solution ]
Python Lambda [ 52 Exercises with Solution ]
Python Map [ 17 Exercises with Solution ]
Python Itertools [ 44 exercises with solution ]
Python - Filter Function [ 11 Exercises with Solution ]
Python Date Time [ 63 Exercises with Solution ]
Python Pendulum (DATETIMES made easy) Module [34 Exercises with Solution]
Python File Input Output [ 21 Exercises with Solution ]
Python CSV File Reading and Writing [ 11 exercises with solution ]
Python Regular Expression [ 58 Exercises with Solution ]
Search and Sorting [ 39 Exercises with Solution ]
Linked List [ 14 Exercises with Solution ]
Binary Search Tree [ 6 Exercises with Solution ]
Python heap queue algorithm [ 29 exercises with solution ]
Python Bisect [ 9 Exercises with Solution ]
Python Boolean Data Type [ 10 Exercises with Solution ]
Python None Data Type [ 10 Exercises with Solution ]
Python Bytes and Byte Arrays Data Type [ 10 Exercises with Solution ]
Python Memory Views Data Type [ 10 Exercises with Solution ]
Python frozenset Views [ 10 Exercises with Solution ]
Python NamedTuple [ 9 Exercises with Solution ]
Python OrderedDict [ 10 Exercises with Solution ]
Python Counter [ 10 Exercises with Solution ]
Python Ellipsis (...) [ 9 Exercises with Solution ]
Python Multi-threading and Concurrency [ 7 exercises with solution ]
Python Asynchronous [ 8 Exercises with Solution ]
Python built-in Modules [ 31 Exercises with Solution ]
Python Operating System Services [ 18 Exercises with Solution ]
Python Math [ 94 Exercises with Solution ]
Python Requests [ 9 exercises with solution ]
Python SQLite Database [ 13 Exercises with Solution ]
Python SQLAlchemy [ 14 exercises with solution ]
Python - PPrint [ 6 Exercises with Solution ]
Python - Cyber Security [ 10 Exercises with Solution ]
Python Generators Yield [ 17 exercises with solution ]
More to come

Python GUI Tkinter, PyQt

Python Tkinter Home
Python Tkinter Basic [ 16 Exercises with Solution ]
Python Tkinter layout management [ 11 Exercises with Solution ]
Python Tkinter widgets [ 22 Exercises with Solution ]
Python Tkinter Dialogs and File Handling [ 13 Exercises with Solution ]
Python Tkinter Canvas and Graphics [ 14 Exercises with Solution ]
Python Tkinter Events and Event Handling [ 13 Exercises with Solution ]
Python Tkinter Customs Widgets and Themes [ 12 Exercises with Solution ]
Python Tkinter - File Operations and Integration [12 exercises with solution]
Python PyQt Basic [10 exercises with solution]
Python PyQt Widgets[12 exercises with solution]
Python PyQt Connecting Signals to Slots [15 exercises with solution]
Python PyQt Event Handling [10 exercises with solution]

Python Challenges :

Python Challenges: Part -1 [ 1- 64 ]

Python Projects :

Python Numbers : [ 11 Mini Projects with solution ]
Python Web Programming: [ 12 Mini Projects with solution ]
100 Python Projects for Beginners with solution.
Python Projects: Novel Coronavirus (COVID-19) [ 14 Exercises with Solution ]

Learn Python packages using Exercises, Practice, Solution and explanation

Python urllib3 :

Python urllib3 [ 26 exercises with solution ]

Python Metaprogramming :

Python Metaprogramming [ 12 exercises with solution ]

Python GeoPy Package :

Python GeoPy Package [ 7 exercises with solution ]

Python BeautifulSoup :

Python BeautifulSoup [ 36 exercises with solution ]

Python Arrow Module :

Python Arrow Module [ 27 exercises with solution ]

Python Web Scraping :

Python Web Scraping [ 27 Exercises with solution ]

Python Natural Language Toolkit :

Python NLTK [ 22 Exercises with solution ]

Python NumPy :

Mastering NumPy [ 100 Exercises with Solutions ]
Python NumPy Basic [ 59 Exercises with Solution ]
Python NumPy arrays [ 205 Exercises with Solution ]
Python NumPy Linear Algebra [ 19 Exercises with Solution ]
Python NumPy Random [ 17 Exercises with Solution ]
Python NumPy Sorting and Searching [ 9 Exercises with Solution ]
Python NumPy Mathematics [ 41 Exercises with Solution ]
Python NumPy Statistics [ 14 Exercises with Solution ]
Python NumPy DateTime [ 7 Exercises with Solution ]
Python NumPy String [ 22 Exercises with Solution ]
NumPy Broadcasting [ 20 exercises with solution ]
NumPy Memory Layout [ 19 exercises with solution ]
NumPy Performance Optimization [ 20 exercises with solution ]
NumPy Interoperability [ 20 exercises with solution ]
NumPy I/O Operations [ 20 exercises with solution ]
NumPy Advanced Indexing [ 20 exercises with solution ]
NumPy Universal Functions [ 20 exercises with solution ]
NumPy Masked Arrays [ 20 exercises with solution ]
NumPy Structured Arrays [ 20 exercises with solution ]
NumPy Integration with SciPy [ 19 exercises with solution ]
Advanced NumPy [ 33 exercises with solution ]

Python Pandas :

Pandas Data Series [ 40 exercises with solution ]
Pandas DataFrame [ 81 exercises with solution ]
Pandas Index [ 26 exercises with solution ]
Pandas String and Regular Expression [ 41 exercises with solution ]
Pandas Joining and merging DataFrame [ 15 exercises with solution ]
Pandas Grouping and Aggregating [ 32 exercises with solution ]
Pandas Time Series [ 32 exercises with solution ]
Pandas Filter [ 27 exercises with solution ]
Pandas GroupBy [ 32 exercises with solution ]
Pandas Handling Missing Values [ 20 exercises with solution ]
Pandas Style [ 15 exercises with solution ]
Pandas Excel Data Analysis [ 25 exercises with solution ]
Pandas Pivot Table [ 32 exercises with solution ]
Pandas Datetime [ 25 exercises with solution ]
Pandas Plotting [ 19 exercises with solution ]
Pandas Performance Optimization [ 20 exercises with solution ]
Pandas Advanced Indexing and Slicing [ 15 exercises with solution ]
Pandas SQL database Queries [ 24 exercises with solution ]
Pandas Resampling and Frequency Conversion [ 15 exercises with solution ]
Pandas Advanced Grouping and Aggregation [ 15 exercises with solution ]
Pandas IMDb Movies Queries [ 17 exercises with solution ]
Mastering NumPy: 100 Exercises with solutions for Python numerical computing
Pandas Practice Set-1 [ 65 exercises with solution ]

Pandas and NumPy Exercises :

Pandas and NumPy for Data Analysis [ 37 Exercises ]

Python Machine Learning :

Python Machine learning Iris flower data set [38 exercises with solution]

Note : Download Python from https://www.python.org/ftp/python/3.2/ and install in your system to execute the Python programs. You can read our Python Installation on Fedora Linux and Windows 7, if you are unfamiliar to Python installation. You may accomplish the same task (solution of the exercises) in various ways, therefore the ways described here are not the only ways to do stuff. Rather, it would be great, if this helps you anyway to choose your own methods.

List of Exercises with Solutions :

HTML CSS Exercises, Practice, Solution
JavaScript Exercises, Practice, Solution
jQuery Exercises, Practice, Solution
jQuery-UI Exercises, Practice, Solution
CoffeeScript Exercises, Practice, Solution
Twitter Bootstrap Exercises, Practice, Solution
C Programming Exercises, Practice, Solution
C# Sharp Programming Exercises, Practice, Solution
PHP Exercises, Practice, Solution
R Programming Exercises, Practice, Solution
Java Exercises, Practice, Solution
SQL Exercises, Practice, Solution
MySQL Exercises, Practice, Solution
PostgreSQL Exercises, Practice, Solution
SQLite Exercises, Practice, Solution
MongoDB Exercises, Practice, Solution

More to Come !

Do not submit any solution of the above exercises at here, if you want to contribute go to the appropriate exercise page.

[ Want to contribute to Python exercises? Send your code (attached with a .zip file) to us at w3resource[at]yahoo[dot]com. Please avoid copyrighted materials.]

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Python Programming

Python Object-Oriented Programming (OOP) Exercise: Classes and Objects Exercises

Updated on: December 8, 2021 | 52 Comments

This Object-Oriented Programming (OOP) exercise aims to help you to learn and practice OOP concepts. All questions are tested on Python 3.

Python Object-oriented programming (OOP) is based on the concept of “objects,” which can contain data and code: data in the form of instance variables (often known as attributes or properties), and code, in the form method. I.e., Using OOP, we encapsulate related properties and behaviors into individual objects.

What is included in this Python OOP exercise?

This OOP classes and objects exercise includes 8 different programs, questions, and challenges. All solutions are tested on Python 3.

This OOP exercise covers questions on the following topics :

Class and Object creation
Instance variables and Methods, and Class level attributes
Model systems with class inheritance i.e., inherit From Other Classes
Parent Classes and Child Classes
Extend the functionality of Parent Classes using Child class
Object checking

When you complete each question, you get more familiar with the Python OOP. Let us know if you have any alternative solutions . It will help other developers.

Use Online Code Editor to solve exercise questions.

Guide on Python OOP
Inheritance in Python

Oop exercise 1: create a class with instance attributes, oop exercise 2: create a vehicle class without any variables and methods, oop exercise 3: create a child class bus that will inherit all of the variables and methods of the vehicle class, oop exercise 4: class inheritance, oop exercise 5: define a property that must have the same value for every class instance (object), oop exercise 6: class inheritance, oop exercise 7: check type of an object, oop exercise 8: determine if school_bus is also an instance of the vehicle class.

Write a Python program to create a Vehicle class with max_speed and mileage instance attributes.

Classes and Objects in Python
Instance variables in Python

Create a Bus object that will inherit all of the variables and methods of the parent Vehicle class and display it.

Expected Output:

Refer : Inheritance in Python

Create a Bus class that inherits from the Vehicle class. Give the capacity argument of Bus.seating_capacity() a default value of 50.

Use the following code for your parent Vehicle class.

Expected Output :

Polymorphism in Python
First, use method overriding.
Next, use default method argument in the seating_capacity() method definition of a bus class.

Define a class attribute” color ” with a default value white . I.e., Every Vehicle should be white.

Use the following code for this exercise.

Refer : Class Variable in Python

Define a color as a class variable in a Vehicle class

Variables created in .__init__() are called instance variables . An instance variable’s value is specific to a particular instance of the class. For example, in the solution, All Vehicle objects have a name and a max_speed, but the name and max_speed variables’ values will vary depending on the Vehicle instance.

On the other hand, the class variable is shared between all class instance s. You can define a class attribute by assigning a value to a variable name outside of .__init__() .

Create a Bus child class that inherits from the Vehicle class. The default fare charge of any vehicle is seating capacity * 100 . If Vehicle is Bus instance, we need to add an extra 10% on full fare as a maintenance charge. So total fare for bus instance will become the final amount = total fare + 10% of the total fare.

Note: The bus seating capacity is 50 . so the final fare amount should be 5500. You need to override the fare() method of a Vehicle class in Bus class.

Use the following code for your parent Vehicle class. We need to access the parent class from inside a method of a child class.

Write a program to determine which class a given Bus object belongs to.

Use Python’s built-in function type() .

Use isinstance() function

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About Vishal

I’m Vishal Hule , the Founder of PYnative.com. As a Python developer, I enjoy assisting students, developers, and learners. Follow me on Twitter .

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Course catalog, class schedule, recommendations, prospective students & parents handbook, current students & parents handbook, general information, the homework, more information, information for parents.

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Homework in the Programming Courses

The homework assignments in our Introduction to Programming with Python and Intermediate Programming with Python courses are slightly different than in our other courses.

The First Ten Weeks

For the first ten weeks of the Introduction to Programming with Python course, the homework will consist of readings from the textbook, 6-10 short-answer Challenge Problems and auto-graded Python problems, and one graded Python problem per week.

The Last Two Weeks

During the last two weeks of our Introduction to Programming with Python course, you'll work on just one final project instead of multiple shorter assignments. Over these two weeks, you'll choose one of three games to create. You should expect to spend more time than usual per week on the course while working on your final project.

At the end of the last week of the course, you will submit your final project. As with the earlier graded Python problems, a grader and your instructor will review your submission and provide you with detailed feedback.

This course is 12 weeks long and culminates in two large final projects completed in the last four weeks of class. Take a look at the Description of Homework Types for more details about each component.

The First Eight Weeks

For the first eight weeks of the Intermediate Programming with Python course, the homework will consist of readings from the textbook, 4-8 short-answer Challenge Problems and auto-graded Python problems, and one graded Python problem per week.

The Last Four Weeks

During the last four weeks of our Intermediate Programming with Python course, students work on 2 two-week projects instead of multiple shorter assignments. Students are asked to implement the game Minesweeper in Weeks 9-10, and then the game Checkers in Weeks 11-12.

As with the earlier graded Python problems, a grader and your instructor will review your submission to each project and provide you with detailed feedback.

Description of Homework Types in Python Courses

Textbook Readings : We use an adapted version of How to Think Like a Computer Scientist . Each enrolled student will have access to the book for the duration of the course—no separate book purchase is required. The textbook readings are listed on the Overview tab of the course homepage, and the book can be accessed from the Textbook tab on the course homepage.

Short-Answer Challenge Problems: Like the short-answer challenge problems in other AoPS Courses, these problems will only require you to enter a final answer. You'll be able to try again with any problem you answer incorrectly, and you'll be shown a full solution after you've completed the problem. You may need to write or edit some Python code in order to come up with your final answer!

Auto-Graded Python Problem: These problems will ask you to write some Python code based on a prompt. You'll be able to submit your code once, and you'll be shown a full solution after completing the problem. Your response will not be graded, but you will receive points for submitting a response. If you request a grade at the end of the course, your instructor will take a closer look at your solutions to these problems when determining a grade.

Graded Python Problems: These problems will ask you to write some Python code based a prompt. Like the Writing Problems in our subject courses, these responses are collected at the end of the due date and individually graded. You'll receive personalized feedback from a grader and the instructor, including comments about the accuracy and efficiency of the code and how easy the code is for others to understand.

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An introduction to programming using a language called Python. Learn how to read and write code as well as how to test and “debug” it. Designed for students with or without prior programming experience who’d like to learn Python specifically. Learn about functions, arguments, and return values (oh my!); variables and types; conditionals and Boolean expressions; and loops. Learn how to handle exceptions, find and fix bugs, and write unit tests; use third-party libraries; validate and extract data with regular expressions; model real-world entities with classes, objects, methods, and properties; and read and write files. Hands-on opportunities for lots of practice. Exercises inspired by real-world programming problems. No software required except for a web browser, or you can write code on your own PC or Mac.

Whereas CS50x itself focuses on computer science more generally as well as programming with C, Python, SQL, and JavaScript, this course, aka CS50P, is entirely focused on programming with Python. You can take CS50P before CS50x, during CS50x, or after CS50x. But for an introduction to computer science itself, you should still take CS50x!

How to Take this Course

Even if you are not a student at Harvard, you are welcome to “take” this course for free via this OpenCourseWare by working your way through the course’s ten weeks of material. For each week, follow this workflow:

And then submit the course’s final project .

To submit the course’s problem sets and final project for feedback, be sure to create an edX account , if you haven’t already. Ask questions along the way via any of the course’s communities !

If interested in a verified certificate from edX , enroll at cs50.edx.org/python instead.
If interested in a professional certificate from edX , enroll at cs50.edx.org/programs/python (for Python) or cs50.edx.org/programs/data (for Data Science) instead.

How to Teach this Course

If you are a teacher, you are welcome to adopt or adapt these materials for your own course, per the license .

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Calculating the Homework Scores

Discussion (1)

00:00 Let’s take a look at all of the columns that have the maximum number of points for the homework assignments. I just want to view these, I want to show you something.

00:09 Let’s pull these out using a list comprehension. I’m going to take a look at the columns in the DataFrame. This will be simply a Series of the titles for the columns.

00:22 And I want to keep those, So I’ll say x for x in that contain the word 'Home' , because that’ll contain 'Homework' ,

00:35 and also if the 'Max' word, or string, is in the column heading. So if I run that, we just get the maximum number of points field names, and those are the ones that I want to pull out. So let’s take a look at those.

00:53 You see that, of course, not all the homework assignments are worth the same number of points. And when this happens, you have to make a decision about how you’re going to compute an average score for, in this case, the homework assignments.

01:07 There’s a couple of ways to do that.

01:11 The two ways to do that are, one, by total score. This involves taking the sum of all of the raw scores of the homework assignments and then the sum of all of the maximum points independently, and then we just simply take the ratio.

01:27 We just sum up all the scores that the student earned for the homework assignments and we divide it by the sum of all the maximum points, and then we get our percentage that way.

01:38 The second way is to take an average of the averages. In other words, we divide each raw score by its respective maximum points, so we get an average for each individual homework assignment, and then we just average the resulting ratios.

01:54 We’re taking an average of the averages.

01:59 By total score, it will favor students who did well on homework assignments that were worth more points. So, for example, if a student did really well on the homework assignments that were worth 100 points or 90 points or 80 points, then that’s going to outweigh all of the assignments that maybe the student didn’t do so well that were worth fewer points.

02:22 Then vice versa, by average score it’s going to favor students who performed consistently. So if they did well in terms of percentage of the homework assignments throughout the semester, it’s going to favor students by average score.

02:38 What we’re going to want to do is compute both homework scores using total score and average score and then computing a maximum for each student. So let me just give you a quick example of how by total score or average score there is a difference.

02:57 Here’s just some hypothetical data. We’ve got a list of homework scores and then we’ve got the maximum number of points for each of the homework assignments.

03:07 The first homework assignment is worth 50 and the student scored 25 , then the second homework assignment was worth 90 and the students scored 85 , and so on. By total, all we do is simply take the sum of the homework scores and we just divide by the sum of all of the maximum number of points that the student could have earned for each homework. And then if we do it by average, we just simply take the ratio of each individual homework assignment.

03:35 So we take the score divided by the maximum number of points, take that ratio, and then we sum up all those ratios and we divide by the number of homework assignments. So in other words, we’re taking a ratio of all of the ratios. And then for this hypothetical data, by total score, the student would have a homework score of 82%, whereas by average score, they would only have a 76%.

04:03 That’s reflected in the fact that for the homework assignment that was worth 90 and the one that was worth 100 , they did really well, whereas, for example, in the ones that were worth fewer—so 50 — they didn’t do so well. So percentage-wise, they didn’t do well, but because these two, worth 90 and 100 , the student did so well, it favors that particular student to have a homework score based on total score.

04:31 Let’s go back to Jupyter and do this computation. We’ll compute a homework score based on total score and a homework score based on average score and then we’ll take the maximum and that will be the final homework score for the student. So back here in Jupyter, we’re going to pull out the column names that have to do with the maximum number of points for the homework, and also just the scores for each individual homework assignment.

05:00 I’m going to keep this list comprehension, and as we saw, this is giving us the column names that contain the max points for each homework assignment. We’ll call this “homework max,” and these are the columns,

05:15 and then we’ll do a similar thing for the homework columns. I’ll take the same list comprehension and instead of having 'Max' in x we want 'Max' not in x . All right, so let me run that just so that you can see what these contain.

05:37 We know that hw_max_cols (homework max columns), this just contains the heading names for the homework assignment max points, and then hw_cols (homework columns), these are just the column names for the homework.

05:53 The reason why I’m doing this is just so that we can easily pull these out whenever we need to, when we’re computing the homework score by total or by average.

06:04 All right, so let’s clear that up.

06:07 Let’s first compute the homework score by total. This is the one that’s pretty straightforward because all we need to do is, from the DataFrame, let’s pull out the homework scores.

06:20 These are just the homework values, that’s its own DataFrame. And then all we need to do is sum along the columns, right? So we want to fix a row and sum along the columns.

06:32 So the .sum() function in this DataFrame, we’re going to call it with the key argument parameter axis=1 . If I run that, that’s just giving me the sum of the scores of all of the homework assignments for each individual student.

06:50 Then all we need to do is divide this by the maximum number of points.

07:00 And likewise, we need to sum along the columns, and so we’re going to pass in an axis value of 1 . Let me run that. And so that’s the easy one. This is the homework score by total.

07:14 Maybe what we’ll do is let’s save this by, say, hw_score_by_total (homework score by total). Okay. Then we will create a new column in our DataFrame, so we’ll say final_df , we’ll say 'HW by Total' , and we’ll set that equal to this new Series that we just computed, hw_score_by_total .

07:41 Let’s just make sure all is good. Let’s take a look at the first five rows. Now at the very end of the DataFrame, we’ve got that HW by Total . All right, so let’s clear that up and now let’s do everything by average.

08:01 Let’s get rid of this cell. To do this by average, what we sort of want to do abstractly is take the columns that give us the scores for the homework assignments and we want to divide these by the columns that give us the maximum number of points for each individual homework assignment.

08:24 For both of these DataFrames, the index is the same. This one is going to have the NetID and so will the second one but there aren’t going to be any matching columns, so if we try to run this, we’re going to get a whole bunch of NaN (not a number) because pandas doesn’t know, because these two columns, the columns in each of these individual DataFrames, are distinct, there’s nothing to divide, to match up column by column.

08:53 So what we need to do is change the column names of, for example, this DataFrame so that they match the column names for the numerator DataFrame. A way to do this is we’re going to use the .set_axis() method for the DataFrame and we’re going to give the columns, which are contained in the axis number 1 , which is the second axis— we want to simply call these columns the same name as the columns in the homework assignment scores. All right, so if we run this now, now we’ve got exactly the homework assignments and the percentages for all of the homework assignments.

09:43 Now, the average homework score, then, what we want to do is simply add all of these homework ratios for each student and then divide by the number of homework assignments. In other words, we want to do the same thing by computing the average of the averages.

10:01 So, because this is getting a little long, let’s take that DataFrame and define, say, a new DataFrame called hw_max_data (homework max data).

10:13 That’ll be that DataFrame that contains the maximum number of points for each homework but now the columns are named Homework 1 , Homework 2 , and so on. And then we’re going to take

10:28 the final_data[hw_cols] (homework columns), just like we had, and we’re going to divide this by hw_max_data .

10:37 Then we want to sum up along the columns so that we get the sum of all of the homework ratios for each student. Then we want to take the average of those, so we want to divide by the length of the number of homework assignments.

10:54 For this, we can use, for example, the length— so, the number of columns, right? That would give us the total number of homework assignments. And this final series here is what we could call, say, hw_score_by_avg (homework score by average).

11:15 And it looks like I made a little typo. This should be final_df . All right, so, this is the Series, then, that we’re going to add to the DataFrame, and this one we’ll call 'HW by Average' and this is going to be set to this Series that we just computed, which is by average. All right, so let’s take a look at what we’ve got so far.

11:41 We’ve got another new column, and this is going to be HW by Average . So, notice there is a little difference in some of them, right? If a student did particularly better in a homework that had more weight or more points, then they would have scored a little bit better than if we did the homework by the average.

12:05 And then the final homework score that we want to assign to each student is going to be the maximum of these two columns. So if I pull out

12:19 'HW by Total' , and let’s also pull out 'HW by Average' ,

12:28 and we want to simply take the maximum

12:33 of these two values per row, and so we want to take the max along the columns— this is then going to give us the final

12:44 column that will determine the homework score for each student. Let’s take a look at that,

12:55 and that’s the final homework score. So far, we’ve got the exam scores for 1, 2, and 3. We’ve got the homework score. All of these are percentages. We’ll multiply these by the weights.

13:09 The only thing we need to do now is do what we did for the homework score to the quizzes.

jrtirado5933 on Aug. 24, 2021

Anyone know how we can view all columns if we’re running this in PyCharm?

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01:07 There's a couple of ways to do that. 01:11 The two ways to do that are, one, by total score. This involves taking the sum of all of the raw scores of the homework assignments and then the sum of all of the maximum points independently, and then we just simply take the ratio. 01:27 We just sum up all the scores that the student earned ...
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