Best Python Programming Books

Python is a general-purpose interpreted programming language used for web development, machine learning, and complex data analysis. Python is a perfect language for beginners as it is easy to learn and understand.

1. Python Crash Course, 2Nd Edition: A Hands-On, Project-Based Introduction To Programming

Author: by Eric Matthes
English
544 pages
1593279280

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Reading books is a kind of enjoyment. Reading books is a good habit. We bring you a different kinds of books. You can carry this book where ever you want. It is easy to carry. It can be an ideal gift to yourself and to your loved ones.

Care instruction keep away from fire.


2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

Author: by Aurélien Géron
O'Reilly Media
English
856 pages

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Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data.

This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworksScikit-Learn and Tensor Flowauthor Aurlien Gron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks.

With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural netsUse Scikit-Learn to track an example machine-learning project end-to-endExplore several training models, including support vector machines, decision trees, random forests, and ensemble methodsUse the Tensor Flow library to build and train neural netsDive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learningLearn techniques for training and scaling deep neural nets.


3. Automate The Boring Stuff With Python, 2Nd Edition: Practical Programming For Total Beginners

Author: by Al Sweigart
English
592 pages
1593279922

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Reading books is a kind of enjoyment. Reading books is a good habit. We bring you a different kinds of books. You can carry this book where ever you want. It is easy to carry. It can be an ideal gift to yourself and to your loved ones.

Care instruction keep away from fire.


4. Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People

Author: by Aditya Bhargava

Manning Publications
English
256 pages

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SummaryGrokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You’ll start with sorting and searching and, as you build up your skills in thinking algorithmically, you’ll tackle more complex concerns such as data compression and artificial intelligence.

Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Learning about algorithms doesn’t have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you’ll find in Grokking Algorithms on Manning Publications’ YouTube channel.

Continue your journey into the world of algorithms with Algorithms in Motion, a practical, hands-on video course available exclusively at Manning.Com (www.Manning. Com/livevideo/algorithms-in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the TechnologyAn algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you’ll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, this is the book for you.


5. Learning Python, 5th Edition

Author: by Mark Lutz
O'Reilly Media
English
1648 pages

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Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages.

Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3. 3 the latest releases in the 3.X and 2. X linesplus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code.

Explore Python’s major built-in object types such as numbers, lists, and dictionariesCreate and process objects with Python statements, and learn Python’s general syntax modelUse functions to avoid code redundancy and package code for reuseOrganize statements, functions, and other tools into larger components with modulesDive into classes: Python’s object-oriented programming tool for structuring codeWrite large programs with Python’s exception-handling model and development toolsLearn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing


6. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

Author: by Wes McKinney
O'Reilly Media
English
550 pages

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Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3. 6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively.

You’ll learn the latest versions of pandas, NumPy, IPython, and Jupiter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing.

Data files and related material are available on GitHub. Use the IPython shell and Jupiter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas group by facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples.


7. Elements of Programming Interviews in Python: The Insiders' Guide

Author: by Adnan Aziz

English
441 pages
1537713949

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This is the Python version of our book. See the website for links to the C++ and Java version.Have you ever… Wanted to work at an exciting futuristic company? Struggled with an interview problem thatcould have been solved in 15 minutes?

Wished you could study real-world computing problems? If so, you need to read Elements of Programming Interviews (EPI). EPI is your comprehensive guide to interviewing for software development roles. The core of EPI is a collection of over 250 problems with detailed solutions.

The problems are representative of interview questions asked at leading software companies. The problems are illustrated with 200 figures, 300 tested programs, and 150 additional variants. The book begins with a summary of the nontechnical aspects of interviewing, such as strategies for a great interview, common mistakes, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI.

We also provide a summary of data structures, algorithms, and problem solving patterns. Coding problems are presented through a series of chapters on basic and advanced data structures, searching, sorting, algorithm design principles, and concurrency. Each chapter stars with a brief introduction, a case study, top tips, and a review of the most important library methods.


8. Coding for Kids: Python: Learn to Code with 50 Awesome Games and Activities

Author: by Adrienne Tacke
English
232 pages
1641521759

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Games and activities that teach kids ages 10+ to code with Python Learning to code isn’t as hard as it soundsyou just have to get started! Coding for Kids: Python starts kids off right with 50 fun, interactive activities that teach them the basics of the Python programming language.

From learning the essential building blocks of programming to creating their very own games, kids will progress through unique lessons packed with helpful examplesand a little silliness! Kids will follow along by starting to code (and debug their code) step by step, seeing the results of their coding in real time.

Activities at the end of each chapter help test their new knowledge by combining multiple concepts. For young programmers who really want to show off their creativity, there are extra tricky challenges to tackle after each chapter. All kids need to get started is a computer and this book.

This beginner’s guide to Python for kids includes: 50 Innovative exercisesCoding concepts come to life with game-based exercises for creating code blocks, drawing pictures using a prewritten module, and more. Easy-to-follow guidanceNew coders will be supported by thorough instructions, sample code, and explanations of new programming terms.


9. Python for Kids: A Playful Introduction to Programming

Author: by Jason R. Briggs
English
348 pages
1593274076

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Python is a powerful, expressive programming language that’s easy to learn and fun to use! But books about learning to program in Python can be kind of dull, gray, and boring, and that’s no fun for anyone. Python for Kids brings Python to life and brings you (and your parents) into the world of programming.

The ever-patient Jason R. Briggs will guide you through the basics as you experiment with unique (and often hilarious) example programs that feature ravenous monsters, secret agents, thieving ravens, and more. New terms are defined; code is colored, dissected, and explained; and quirky, full-color illustrations keep things on the lighter side.

Chapters end with programming puzzles designed to stretch your brain and strengthen your understanding. By the end of the book you’ll have programmed two complete games: a clone of the famous Pong and “Mr. Stick Man Races for the Exit”a platform game with jumps, animation, and much more.

As you strike out on your programming adventure, you’ll learn how to:Use fundamental data structures like lists, tuples, and mapsOrganize and reuse your code with functions and modulesUse control structures like loops and conditional statementsDraw shapes and patterns with Python’s turtle moduleCreate games, animations, and other graphical wonders with tkinterWhy should serious adults have all the fun?

10. Python Programming Language

Author: by Berajah Jayne
English
6 pages
1423241886

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Created for developers of all skill levels to find the essentials of common operations combined with the fastest reference guide for writing code. This handy 6 page laminated guide is a concise desktop reference to key concepts behind Python logic, syntax, and operation.

Expertly written to concisely cover the planning of a program written in Python, assigning your first variables, importing other libraries, formatting output strings, and creating classes. Beginning students or seasoned programmers will find this tool a perfect go-to for reference to those core concepts.

This unbeatable value makes it easy to add this reference to your programmer’s toolbox. 6 page laminated guide includes: Working with Python Using Python CodeImporting ModulesScope (Indentation)Naming ConventionsReserved KeywordsCommentsWriting Code Basics Making VariablesTypesConsoleError HandlingSaving & Loading FilesCoding Structures Math Operators (int, float & complex)List Operations (list, tuple & dict)StringsStatementsFunctionsDictionariesUsing Structures String FormattingString MethodsEscape SequencesBool CharactersWriting Boolean StatementsRecursion & IterationClassesCoding Concepts InheritanceGeneratorsPolymorphismLambda Expressions

11. Teach Yourself Data Analytics in 30 Days: Learn to use Python and Jupyter Notebooks by exploring fun, real-world data projects

Author: by David Clinton
English
136 pages
1777721008

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Would you like to learn how to extract useful insights from all the data around you without having to take years’ worth of courses? College data science programs teach many valuable skills, but sometimes all you need is some quick and direct tools.

Welcome to Teach Yourself Data Analytics in 30 Days. The book’s curriculum is organized into eight data “stories.” The stories are interesting on their own, but there’s no doubt what they’re really all about is Python data analytics. Each story/chapter contains all the information you would need to go out and get the raw data and then write the Python analytics code necessary to solve a specific problem.

Once you’ve worked through the whole book, you’ll have enough Python skills to solve a wide range of data problems on your own. If you’re motivated and have some time to invest, there’s no reason you can’t use those stories to teach yourself data analytics in 30 days.

You’ll find everything you need to build your own basic data analytics skills, including:Getting Python up and running on Jupyter Notebooks (or, if you prefer, JupyterLab)Finding and cleaning data sourcesPlotting your dataUsing Python functionsUnderstanding results through domain knowledge and tools like regression lines

12. Data Science from Scratch: First Principles with Python

Author: by Joel Grus
O'Reilly Media
English
406 pages

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To really learn data science, you should not only master the toolsdata science libraries, frameworks, modules, and toolkitsbut also understand the ideas and principles underlying them. Updated for Python 3. 6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.

If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist.

Packed with New material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today’s messy glut of data. Get a crash course in PythonLearn the basics of linear algebra, statistics, and probabilityand how and when they’re used in data scienceCollect, explore, clean, munge, and manipulate dataDive into the fundamentals of machine learningImplement models such as k-nearest neighbors, Nave Bayes, linear and logistic regression, decision trees, neural networks, and clusteringExplore recommender systems, natural language processing, network analysis, MapReduce, and databases..

13. Fluent Python: Clear, Concise, and Effective Programming

Author: by Luciano Ramalho
O'Reilly Media
English
792 pages

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Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its bestand possibly most neglectedfeatures. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.

Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3. This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.

14. Python for Excel: A Modern Environment for Automation and Data Analysis

Author: by Felix Zumstein
O'Reilly Media
English
338 pages

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While Excel remains ubiquitous in the business world, recent Microsoft feedback forums are full of requests to include Python as an Excel scripting language. In fact, it’s the top feature requested. What makes this combination so compelling? In this hands-on guide, Felix Zumstein-creator of xlwings, a popular open source package for automating Excel with Python-shows experienced Excel users how to integrate these two worlds efficiently.

Excel has added quite a few new capabilities over the past couple of years, but its automation language, VBA, stopped evolving a long time ago. Many Excel power users have already adopted Python for daily automation tasks. This guide gets you started.

Use Python without extensive programming knowledgeGet started with modern tools, including Jupyter notebooks and Visual Studio codeUse pandas to acquire, clean, and analyze data and replace typical Excel calculationsAutomate tedious tasks like consolidation of Excel workbooks and production of Excel reportsUse xlwings to build interactive Excel tools that use Python as a calculation engineConnect Excel to databases and CSV files and fetch data from the internet using Python codeUse Python as a single tool to replace VBA, Power Query, and Power Pivot

15. Black Hat Python, 2nd Edition: Python Programming for Hackers and Pentesters

Author: by Justin Seitz
English
216 pages
1718501129

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Fully-updated for Python 3, the second edition of this worldwide bestseller (over 100,000 copies sold) explores the stealthier side of programming and brings you all new strategies for your hacking projects. When it comes to creating powerful and effective hacking tools, Python is the language of choice for most security analysts.

In this second edition of the bestselling Black Hat Python, you’ll explore the darker side of Python’s capabilities: everything from writing network sniffers, stealing email credentials, and bruteforcing directories to crafting mutation fuzzers, investigating virtual machines, and creating stealthy trojans.

All of the code in this edition has been updated to Python 3.X. You’ll also find new coverage of bit shifting, code hygiene, and offensive forensics with the Volatility Framework as well as expanded explanations of the Python libraries ctypes, struct, lxml, and BeautifulSoup, and offensive hacking strategies like splitting bytes, leveraging computer vision libraries, and scraping websites.

16. Python Data Science Handbook: Essential Tools for Working with Data

Author: by Jake VanderPlas
O'Reilly Media
English
548 pages

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For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them allIPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models.

Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use:IPython and Jupyter: provide computational environments for data scientists using PythonNumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in PythonPandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in PythonMatplotlib: includes capabilities for a flexible range of data visualizations in PythonScikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms