Hands-On Data Structures and Algorithms with Python. Write complex and powerful code using the latest features of Python 3.7 - Second Edition

Dr. Basant Agarwal, Benjamin Baka

Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications.This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail.By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms.

Data Wrangling with Python. Creating actionable data from raw sources

Dr. Tirthajyoti Sarkar, Shubhadeep Roychowdhury

For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain.The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets.By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.

Hands-On Bitcoin Programming with Python. Build powerful online payment centric applications with Python

Harish Garg

Bitcoin is a cryptocurrency that’s changing the face of online payments. Hands-On Bitcoin Programming with Python teaches you to build software applications for mining and creating Bitcoins using Python.This book starts with the basics of both Bitcoin and blockchain and gives you an overview of these inherent concepts by showing you how to build Bitcoin-driven applications with Python. Packed with clear instructions and practical examples, you will learn to understand simple Python coding examples that work with this cryptocurrency.By the end of the book, you’ll be able to mine Bitcoins, accept Bitcoin payments on the app, and work with the basics of blockchain technology to create simply distributed ledgers.

Mastering Functional Programming. Functional techniques for sequential and parallel programming with Scala

Anatolii Kmetiuk

Functional programming is a paradigm specifically designed to deal with the complexity of software development in large projects. It helps developers to keep track of the interdependencies in the code base and changes in its state in runtime. Mastering Functional Programming provides detailed coverage of how to apply the right abstractions to reduce code complexity, so that it is easy to read and understand.Complete with explanations of essential concepts, practical examples, and self-assessment questions, the book begins by covering the basics such as what lambdas are and how to write declarative code with the help of functions. It then moves on to concepts such as pure functions and type classes, the problems they aim to solve, and how to use them in real-world scenarios. You’ll also explore some of the more advanced patterns in the world of functional programming such as monad transformers and Tagless Final. In the concluding chapters, you’ll be introduced to the actor model, which you can implement in modern functional languages, and delve into parallel programming.By the end of the book, you will be able to apply the concepts of functional programming and object-oriented programming (OOP)in order to build robust applications.

Ethereum Cookbook. Over 100 recipes covering Ethereum-based tokens, games, wallets, smart contracts, protocols, and Dapps

Manoj P R

Ethereum and Blockchain will change the way software is built for business transactions. Most industries have been looking to leverage these new technologies to gain efficiencies and create new business models and opportunities.The Ethereum Cookbook covers various solutions such as setting up Ethereum, writing smart contracts, and creating tokens, among others. You’ll learn about the security vulnerabilities, along with other protocols of Ethereum.Once you have understood the basics, you’ll move on to exploring various design decisions and tips to make your application scalable and secure. In addition to this, you’ll work with various Ethereum packages such as Truffle, Web3, and Ganache.By the end of this book, you’ll have comprehensively grasped the Ethereum principles and ecosystem.

IPython Interactive Computing and Visualization Cookbook. Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook - Second Edition

Cyrille Rossant

Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform.IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning.The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.

Drupal 8 Module Development. Build modules and themes using the latest version of Drupal 8 - Second Edition

Daniel Sipos

Drupal 8 comes with a release cycle that allows for new functionality to be added at a much faster pace. However, this also means code deprecations and changing architecture that you need to stay on top of. This book updates the first edition and includes the new functionality introduced in versions up to, and including 8.7.The book will first introduce you to the Drupal 8 architecture and its subsystems before diving into creating your first module with basic functionality. You will work with the Drupal logging and mailing systems, learn how to output data using the theme layer and work with menus and links programmatically. Then, you will learn how to work with different kinds of data storages, create custom entities, field types and leverage the Database API for lower level database queries. You will further see how to introduce JavaScript into your module, work with the various file systems and ensure the code you write works on multilingual sites. Finally, you will learn how to programmatically work with Views, write automated tests for your functionality and also write secure code in general.By the end, you will have learned how to develop your own custom module that can provide complex business solutions. And who knows, maybe you’ll even contribute it back to the Drupal community.Foreword by Dries Buytaert, founder of Drupal.

Regression Analysis with R. Design and develop statistical nodes to identify unique relationships within data at scale

Giuseppe Ciaburro

Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables.This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples.By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects.