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Author: Alex Nordeen
Publisher: Guru99
ISBN:
Category : Computers
Languages : en
Pages : 349
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Book Description
R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?
Author: Alex Nordeen
Publisher: Guru99
ISBN:
Category : Computers
Languages : en
Pages : 349
Get Book
Book Description
R is a programming language developed is widely used for statistical and graphical analysis. It can execute advance machine learning algorithms including earning algorithm, linear regression, time series, statistical inference. R programming language is used by Fortune 500 companies and tech bellwethers like Uber, Google, Airbnb, Facebook, Apple. R provides a data scientist tools and libraries (Dplyr) to perform the 3 steps of analysis 1) Extract 2) Transform, Cleanse 3) Analyze. Table of Contents Chapter 1: What is R Programming Language? Introduction & Basics Chapter 2: How to Download & Install R, RStudio, Anaconda on Mac or Windows Chapter 3: R Data Types, Arithmetic & Logical Operators with Example Chapter 4: R Matrix Tutorial: Create, Print, add Column, Slice Chapter 5: Factor in R: Categorical & Continuous Variables Chapter 6: R Data Frame: Create, Append, Select, Subset Chapter 7: List in R: Create, Select Elements with Example Chapter 8: R Sort a Data Frame using Order() Chapter 9: R Dplyr Tutorial: Data Manipulation(Join) & Cleaning(Spread) Chapter 10: Merge Data Frames in R: Full and Partial Match Chapter 11: Functions in R Programming (with Example) Chapter 12: IF, ELSE, ELSE IF Statement in R Chapter 13: For Loop in R with Examples for List and Matrix Chapter 14: While Loop in R with Example Chapter 15: apply(), lapply(), sapply(), tapply() Function in R with Examples Chapter 16: Import Data into R: Read CSV, Excel, SPSS, Stata, SAS Files Chapter 17: How to Replace Missing Values(NA) in R: na.omit & na.rm Chapter 18: R Exporting Data to Excel, CSV, SAS, STATA, Text File Chapter 19: Correlation in R: Pearson & Spearman with Matrix Example Chapter 20: R Aggregate Function: Summarise & Group_by() Example Chapter 21: R Select(), Filter(), Arrange(), Pipeline with Example Chapter 22: Scatter Plot in R using ggplot2 (with Example) Chapter 23: How to make Boxplot in R (with EXAMPLE) Chapter 24: Bar Chart & Histogram in R (with Example) Chapter 25: T Test in R: One Sample and Paired (with Example) Chapter 26: R ANOVA Tutorial: One way & Two way (with Examples) Chapter 27: R Simple, Multiple Linear and Stepwise Regression [with Example] Chapter 28: Decision Tree in R with Example Chapter 29: R Random Forest Tutorial with Example Chapter 30: Generalized Linear Model (GLM) in R with Example Chapter 31: K-means Clustering in R with Example Chapter 32: R Vs Python: What's the Difference? Chapter 33: SAS vs R: What's the Difference?
Author: Andy Nicholls
Publisher: Sams Publishing
ISBN: 9780672338489
Category : Computer programming
Languages : en
Pages : 0
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Book Description
With the open source R programming language and its immense library of packages, you can perform virtually any data analysis task. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to import, manipulate, summarize, model, and plot data with R; formalize analytical code; and build powerful R packages using current best practices. Each short, easy lesson builds on all that's come before: you'll learn all of R's essentials as you create real R solutions. R in 24 hours, Sams Teach Yourself covers the entire data analysis workflow from the viewpoint of professionals whose code must be efficient, reproducible and suitable for sharing with others.
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Category : Computers
Languages : en
Pages : 521
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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: Tilman M. Davies
Publisher: No Starch Press
ISBN: 1593277792
Category : Computers
Languages : en
Pages : 833
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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: Norman Matloff
Publisher: No Starch Press
ISBN: 1593273843
Category : Computers
Languages : en
Pages : 404
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Book Description
R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly. The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro. Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: –Create artful graphs to visualize complex data sets and functions –Write more efficient code using parallel R and vectorization –Interface R with C/C++ and Python for increased speed or functionality –Find new R packages for text analysis, image manipulation, and more –Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.
Author: Michael Tyler Givens
Publisher: Pearson Education
ISBN: 9780768685732
Category : Computers
Languages : en
Pages : 432
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Book Description
This is the eBook version of the printed book. If the print book includes a CD-ROM, this content is not included within the eBook version. Sams Teach Yourself Adobe® AIR™ Programming in 24 Hours Michael Givens Covers version 1.5 of Adobe AIR In just 24 sessions of one hour or less, you will be up and running with Adobe AIR 1.5. Using a straightforward, step-by-step approach, each lesson builds upon a real-world foundation allowing you to learn the essentials of Adobe AIR from the ground up. Step-by-step instructions carefully walk you through the most common Adobe AIR 1.5 tasks. Quizzes and Exercises at the end of each chapter help you test your knowledge of Adobe AIR 1.5. By the Way notes present interesting information related to the discussion. Did You Know? tips offer advice or show you alternative ways to do something. Watch Out! cautions alert you to possible problems and give you advice on how to avoid them. Learn how to… Utilize the AIR SDK Write an AIR application with HTML Write an AIR application with Flash CS3 or Dreamweaver CS3 Write an AIR application with PDF integration Debug an AIR application Distribute an AIR application Use the AIR APIs Leverage server-side features for AIR Michael Givens is the CTO of U Saw It Enterprises, a Web technology consulting firm based in Spring, Texas. He is an Adobe Community Expert and an Adobe Corporate Champion known to share his experience and evangelism of all things Adobe. Certified in ColdFusion 5 and as an Advanced CFMX Developer, he has been using ColdFusion since the days of Allaire Spectra and Flex since it was known as Royale. He is the coauthor of Adobe AIR Programming Unleashed (Sams Publishing) and has written articles for the ColdFusion Developer’s Journal and the Flex Developer’s Journal. He also wrote a digital Short Cut titled Apollo in Flight for Sams Publishing. Michael blogs regularly at www.flexination.info. Category: Programming/Application Development Covers: Adobe AIR User Level: Beginning–Intermediate
Author: Andy Nicholls
Publisher: Sams Publishing
ISBN: 0134288807
Category : Computers
Languages : en
Pages : 1544
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Book Description
In just 24 lessons of one hour or less, Sams Teach Yourself R in 24 Hours helps you learn all the R skills you need to solve a wide spectrum of real-world data analysis problems. You’ll master the entire data analysis workflow, learning to build code that’s efficient, reproducible, and suitable for sharing with others. This book’s straightforward, step-by-step approach teaches you how to import, manipulate, summarize, model, and plot data with R; formalize your analytical code; and build powerful R packages using current best practices. Practical, hands-on examples show you how to apply what you learn. Quizzes and exercises help you test your knowledge and stretch your skills. Learn How To Install, configure, and explore the R environment, including RStudio Use basic R syntax, objects, and packages Create and manage data structures, including vectors, matrices, and arrays Understand lists and data frames Work with dates, times, and factors Use common R functions, and learn to write your own Import and export data and connect to databases and spreadsheets Use the popular tidyr, dplyr and data.table packages Write more efficient R code with profiling, vectorization, and initialization Plot data and extend your graphical capabilities with ggplot2 and Lattice graphics Develop common types of models Construct high-quality packages, both simple and complex Write R classes: S3, S4, and Reference Classes Use R to generate dynamic reports Build web applications with Shiny Register your book at informit.com/register for convenient access to updates and corrections as they become available. This book’s source code can be found at http://www.mango-solutions.com/wp/teach-yourself-r-in-24-hours-book/.
Author: Hadley Wickham
Publisher: CRC Press
ISBN: 1498759807
Category : Mathematics
Languages : en
Pages : 476
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Book Description
An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory-efficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.
Author: Kun Ren
Publisher: Packt Publishing Ltd
ISBN: 1785880624
Category : Computers
Languages : en
Pages : 576
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Book Description
Become an efficient data scientist with R About This Book Explore the R language from basic types and data structures to advanced topics Learn how to tackle programming problems and explore both functional and object-oriented programming techniques Learn how to address the core problems of programming in R and leverage the most popular packages for common tasks Who This Book Is For This is the perfect tutorial for anyone who is new to statistical programming and modeling. Anyone with basic programming and data processing skills can pick this book up to systematically learn the R programming language and crucial techniques. What You Will Learn Explore the basic functions in R and familiarize yourself with common data structures Work with data in R using basic functions of statistics, data mining, data visualization, root solving, and optimization Get acquainted with R's evaluation model with environments and meta-programming techniques with symbol, call, formula, and expression Get to grips with object-oriented programming in R: including the S3, S4, RC, and R6 systems Access relational databases such as SQLite and non-relational databases such as MongoDB and Redis Get to know high performance computing techniques such as parallel computing and Rcpp Use web scraping techniques to extract information Create RMarkdown, an interactive app with Shiny, DiagramR, interactive charts, ggvis, and more In Detail R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset. Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques. Style and approach Developed to make learning easy and intuitive, this book comes packed with a wide variety of statistical and graphical techniques and a wealth of practical information for anyone looking to get started with this exciting and powerful language.
Author: Andy Nicholls
Publisher:
ISBN: 9780134288819
Category : R (Computer program language)
Languages : en
Pages :
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Book Description
