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Author: Jaynal Abedin Publisher: Packt Publishing Ltd ISBN: 1787288773 Category : Computers Languages : en Pages : 225
Book Description
Recipes for emerging developers in R programming and data scientists to simplify their R programming capabilities About This Book Develop strategies to speed up your R code Tackle programming problems and explore both functional and object-oriented programming techniques Learn how to address the core problems of programming in R with the most popular R packages for common tasks Who This Book Is For This book is for developers who would like to enhance the R programming skills. Basic knowledge of R programming is assumed. What You Will Learn Install R and its various IDE for a given platform along with installing libraries from different repositories and version control Learn about basic data structures in R and how to work with them Write customized R functions and handle recursions, exceptions in R environments Create the data processing task as a step by step computer program and execute using dplyr Extract and process unstructured text data Interact with database management system to develop statistical applications Formulate and implement parallel processing in R In Detail R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications. Style and approach This book will be a companion for R programmer and emerging developers in R programming areas. This book will contain recipes related to advanced R programming which will enable users to solve complex problems efficiently.
Author: Jaynal Abedin Publisher: Packt Publishing Ltd ISBN: 1787288773 Category : Computers Languages : en Pages : 225
Book Description
Recipes for emerging developers in R programming and data scientists to simplify their R programming capabilities About This Book Develop strategies to speed up your R code Tackle programming problems and explore both functional and object-oriented programming techniques Learn how to address the core problems of programming in R with the most popular R packages for common tasks Who This Book Is For This book is for developers who would like to enhance the R programming skills. Basic knowledge of R programming is assumed. What You Will Learn Install R and its various IDE for a given platform along with installing libraries from different repositories and version control Learn about basic data structures in R and how to work with them Write customized R functions and handle recursions, exceptions in R environments Create the data processing task as a step by step computer program and execute using dplyr Extract and process unstructured text data Interact with database management system to develop statistical applications Formulate and implement parallel processing in R In Detail R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications. Style and approach This book will be a companion for R programmer and emerging developers in R programming areas. This book will contain recipes related to advanced R programming which will enable users to solve complex problems efficiently.
Author: Jaynal Abedin Publisher: Packt Publishing ISBN: 9781787129054 Category : Computers Languages : en Pages : 236
Book Description
Recipes for emerging developers in R programming and data scientists to simplify their R programming capabilitiesAbout This Book* Develop strategies to speed up your R code* Tackle programming problems and explore both functional and object-oriented programming techniques* Learn how to address the core problems of programming in R with the most popular R packages for common tasksWho This Book Is ForThis book is for developers who would like to enhance the R programming skills. Basic knowledge of R programming is assumed.What You Will Learn* Install R and its various IDE for a given platform along with installing libraries from different repositories and version control* Learn about basic data structures in R and how to work with them* Write customized R functions and handle recursions, exceptions in R environments* Create the data processing task as a step by step computer program and execute using dplyr* Extract and process unstructured text data* Interact with database management system to develop statistical applications* Formulate and implement parallel processing in RIn DetailR is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.Style and approachThis book will be a companion for R programmer and emerging developers in R programming areas. This book will contain recipes related to advanced R programming which will enable users to solve complex problems efficiently.
Author: Paul Teetor Publisher: "O'Reilly Media, Inc." ISBN: 1449307264 Category : Computers Languages : en Pages : 438
Book Description
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform other basic functions Input and output data Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals, and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data "Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author
Author: Marius Bancila Publisher: Packt Publishing Ltd ISBN: 1788994027 Category : Computers Languages : en Pages : 321
Book Description
Test your C++ programming skills by solving real-world programming problems covered in the book Key Features Solve a variety of real-world programming and logic problems by leveraging the power of C++17 Test your skills in using language features, algorithms, data structures, design patterns, and more Explore areas such as cryptography, communication, and image handling in C++ Book Description C++ is one of the most widely-used programming languages and has applications in a variety of fields, such as gaming, GUI programming, and operating systems, to name a few. Through the years, C++ has evolved into (and remains) one of the top choices for software developers worldwide. This book will show you some notable C++ features and how to implement them to meet your application needs. Each problem is unique and doesn't just test your knowledge of the language; it tests your ability to think out of the box and come up with the best solutions. With varying levels of difficulty, you'll be faced with a wide variety of challenges. And in case you're stumped, you don't have to worry: we've got the best solutions to the problems in the book. So are you up for the challenge? What you will learn Serialize and deserialize JSON and XML data Perform encryption and signing to facilitate secure communication between parties Embed and use SQLite databases in your applications Use threads and asynchronous functions to implement generic purpose parallel algorithms Compress and decompress files to/from a ZIP archive Implement data structures such as circular buffer and priority queue Implement general purpose algorithms as well as algorithms that solve specific problems Create client-server applications that communicate over TCP/IP Consume HTTP REST services Use design patterns to solve real-world problems Who this book is for This book will appeal to C++ developers of all levels. There's a challenge inside for everyone.
Author: JD Long Publisher: "O'Reilly Media, Inc." ISBN: 1492040630 Category : Computers Languages : en Pages : 600
Book Description
Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression. Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an intermediate user, this book will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process. Create vectors, handle variables, and perform basic functions Simplify data input and output Tackle data structures such as matrices, lists, factors, and data frames Work with probability, probability distributions, and random variables Calculate statistics and confidence intervals and perform statistical tests Create a variety of graphic displays Build statistical models with linear regressions and analysis of variance (ANOVA) Explore advanced statistical techniques, such as finding clusters in your data
Author: Tilman M. Davies Publisher: No Starch Press ISBN: 1593277792 Category : Computers Languages : en Pages : 833
Book Description
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Author: Michael J. Crawley Publisher: John Wiley & Sons ISBN: 9780470515068 Category : Mathematics Languages : en Pages : 953
Book Description
The high-level language of R is recognized as one of the mostpowerful and flexible statistical software environments, and israpidly becoming the standard setting for quantitative analysis,statistics and graphics. R provides free access to unrivalledcoverage and cutting-edge applications, enabling the user to applynumerous statistical methods ranging from simple regression to timeseries or multivariate analysis. Building on the success of the author’s bestsellingStatistics: An Introduction using R, The R Book ispacked with worked examples, providing an all inclusive guide to R,ideal for novice and more accomplished users alike. The bookassumes no background in statistics or computing and introduces theadvantages of the R environment, detailing its applications in awide range of disciplines. Provides the first comprehensive reference manual for the Rlanguage, including practical guidance and full coverage of thegraphics facilities. Introduces all the statistical models covered by R, beginningwith simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression andanalysis of variance, through to generalized linear models,generalized mixed models, time series, spatial statistics,multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates andprofessionals in science, engineering and medicine. It is alsoideal for students and professionals in statistics, economics,geography and the social sciences.
Author: Hadley Wickham Publisher: "O'Reilly Media, Inc." ISBN: 1491910364 Category : Computers Languages : en Pages : 521
Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author: Richard Cotton Publisher: "O'Reilly Media, Inc." ISBN: 1449357180 Category : Computers Languages : en Pages : 400
Book Description
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you’ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you’ve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code
Author: Rick J. Scavetta Publisher: "O'Reilly Media, Inc." ISBN: 1492093378 Category : Computers Languages : en Pages : 199
Book Description
Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language Understand the strengths and weaknesses of each language Identify use cases where one language is better suited than the other Understand the modern open source ecosystem available for both, including packages, frameworks, and workflows Learn how to integrate R and Python in a single workflow Follow a case study that demonstrates ways to use these languages together
Author: Jaynal Abedin
Author: Jaynal Abedin
Author: Jaynal Abedin
Author: Paul Teetor
Author: Marius Bancila
Author: JD Long
Author: Tilman M. Davies
Author: Michael J. Crawley
Author: Hadley Wickham
Author: Richard Cotton
Author: Rick J. Scavetta