# PYTHON EXERCISES

Python exercises and practice questions are vital for learning the programming language effectively. They are not just a way to test your knowledge, but also a way to reinforce what you have learned and gain practical experience. By solving Python problems and practicing exercises, you are able to apply the concepts you have learned in a real-world context, which greatly enhances your understanding of the language.

One of the main benefits of solving Python exercises is that it helps you build problem-solving skills. Programming is all about finding solutions to problems, so when you solve exercises, you develop the ability to divide the task inÂ smaller, more manageable parts. This skill is not only important in programming but also in various other aspects of life.

Another benefit of solving Python exercises is that it helps you become more familiar with the language syntax and its various features. You will have to explore different aspects of Python and gain a deeper understanding of its capabilities. This familiarity with the language will make you more efficient and effective in writing code.

Moreover, Python practice gives you the opportunity to practice and reinforce what you have learned. It is one thing to read about programming concepts, but it is another thing entirely to actually implement them in code. Exercises provide a hands-on experience that allows you to solidify your understanding of the material.### Tips

When students encounter difficult problems during their learning process, it can be discouraging. However, there are several tips that can help them confront these challenges and stay motivated. First, it is important to break down the problem into smaller parts and tackle them one at a time. By approaching the problem step by step, it becomes more manageable and less overwhelming.

Additionally, it is helpful to seek out resources such as online forums or tutorials that can provide guidance and support. Often, other programmers have faced similar challenges and can offer insights or solutions that can help overcome the difficulty. Collaboration and seeking help from others is a valuable skill in programming.

Lastly, it is crucial to stay motivated and not get discouraged by setbacks or failures. Programming is a process of trial and error, and it is normal to encounter obstacles along the way. Embrace these challenges as opportunities for growth and learning. Celebrate your successes, no matter how small they may be, and keep pushing forward.

Here you will find a compilation of different sites with exercises and problems so you can practice Python at your own pace.### Python Exercises for Beginners

SnakifyViews: 588CodeClubViews: 303EdabitViews: 943- 100 Python problems: Find the last item in an array, even/odd number, word count, reverse string order, alphabet soup, repeating letters, factorial, sort numbers, phone number formatting, etc.

W3ResourceViews: 142- 400 Exercises: strings, lists, functions, loops, conditionals, date time, data structure, recursion, math,regex, numpy, pandas.

University of HelsinkiViews: 277- 12 Python exercises (PDF, to see all exercises change number in the browser bar): dictionaries exercises. Functions with loops on dictionaries, function to invert a dictionary.

ZarkonnenViews: 100- 8 exercises of strings: sum of lengths of names, find the shortest name in text, convert a number to its string, sort names in text alphabetically, etc.

GITHUB - Jerry Git (Jupyter Notebook)Views: 89- 15 Exercises: fill in the blanks (conditionals), find bugs in code, create and merge dictionaries, custom exceptions, count average length of words in a sentence, lists,Â function to turn vowels in uppercase and consonants in lower case, create test case for a function and so on.

Practice PythonViews: 170- 36 exercises about list comprehensions, list remove duplicates, element search, write to a file, draw a game board, max of three, hangman, birthday plots, odd or even, functions, modules.

PyNativeViews: 67- 75 Exercises of data science: Assignments of Pandas, NumPy, data structure, Matplotlib, Database.

Simpliv LLCViews: 60- 50 Interview questions: theory questions and exercises.

PROGRAMIZViews: 80- 50 Exercises: Find square root, generate random numbers, display multiplication table, find sum of natural numbers,Â display calendar, add two matrices, find size of an image, etc.

### Python Exercises for Intermediates

PractityViews: 225- Real-world Python Projects: Data cleaning, OOP, Python libraries, applications with GUI, automation exercises, data analysis, games, etc.

HackerrankViews: 146- 150 Exercises of Python core topics: strings, sets, maths, loops, collections, dates, exceptions, classes, regex, XML.

University of California (Physics)Views: 96- 40 Python practice questions focused on lists, functions, loops, modules, conditionals, linear algebra, statistics.

CodeChefViews: 124- 200 Python Challenges & problems.

- 15 Fun programming problems: program of treasure hunt, chess queen attack, program for secret messages, turn roman numbers into arabic, phone words program, calculation of bowling match scores, etc.

CodeAbbeyViews: 71- 50 Problems: rounding, sum of digits, average in array, modular calculator, double dice roll, mortgage calculator, star medals, lucky tickets, etc.

- 40 Assignments + 2 projects + exam: Practice the Math module, quadratic formula, random function,Â Â nims/stones games, lists, report card function, list comprehensions, structures, OOP, inheritance.

Programming for biologistsViews: 37- 150 exercises: databases, expressions and variables, loops, functions, graphics, list comprehension, OOP, Scientific Python.

CoderByteViews: 79- 200 Exercises: letter capitalize, time convert, vowel square, longest word, coin determiner, stock picker, matrix chains, character removal, etc.

Norwegian Center of ExcellenceViews: 53- 10 Scientific Python exercises: maths, loops, functions, combine text and numbers, plot a function, numpy.

TechbeamersViews: 36- 30 Interview questions.

Oxford Cambridge and RSAViews: 69- 20 Code challenges: Email validator program, password reset program, quiz application, count words/vowels in a string, etc.

Liverpool University, Computer ScienceViews: 42- 22 Problems to perform calculations with Python: Compound interest code, time to fill swimming pool, calculator, area and circunference calculation, distance conversion, load data into dictionaries, triangle recognition, etc.

GITHUBViews: 38- Data Science interview questions: Technical (SQL, Python) and theory (statistics, Machine Learning).

### Advanced Python Exercises

- 5 Assignments, 10 labs: Data cleaning, web scrapping, Pandas, Matplotlib libraries, linear regression (SciKit learn), cross validation, map reduce, etc.

Advent for codeViews: 41GITHUB.Views: 49- 50 Examples of multiple topics: Web scrapping (Selenium), webapp with Flask, RESTful microservice, reddit bot, sentiment analysis, recommendation systems, linear regression, etc.

- 50 statistics exercises (scipy): Probability, linear models, bayesian models, hypothesis testing, cross validation.

Advent for code 2021Views: 29- Programming puzzles for a variety of skill sets and skill levels that can be solved in any programming language you like. People use them as a speed contest, interview prep, company training, university coursework, practice problems.

Project EulerViews: 101- 800 coding math problems.

Programming PraxisViews: 46- 200 exercises & interview questions: Maths, searching, classic algorithms, astronomy, prime numbers, fundamentals of computing, arithmetic, computational geometry, cryptography, data processing, games, graphs.

German Neuroinformatics Node (PDF)Views: 29- 8 Problems about decorators to cache function invocation results, generator functions, file browsing, plugin registration system and so on.

CSStackViews: 31- Python interview questions: 64 interview questions from multiple companies.

- Python challenges ofÂ former editions.

LabriViews: 81- 90 exercises focused on the Numpy library.

*QUICK SURVEY*- Fun DataSets for Python PracticeViews: 439Public datasets for data science practiceViews: 439Biggest datasets for machine learningViews: 86010M images of celebrities (Microsoft)Views: 165

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