25 Recipes for Getting Started with R

Author: Paul Teetor
Publisher: "O'Reilly Media, Inc."
ISBN: 1449303234
Category : Computers
Languages : en
Pages : 56

Book Description
R is a powerful tool for statistics and graphics, but getting started with this language can be frustrating. This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to use R for basic statistics, graphics, and regression. You'll find recipes on reading data files, creating data frames, computing basic statistics, testing means and correlations, creating a scatter plot, performing simple linear regression, and many more. These solutions were selected from O'Reilly's R Cookbook, which contains more than 200 recipes for R that you'll find useful once you move beyond the basics.

Cook This Book

Author: Molly Baz
Publisher: Clarkson Potter
ISBN: 0593138279
Category : Cooking
Languages : en
Pages : 306

Book Description
NEW YORK TIMES BESTSELLER • A thoroughly modern guide to becoming a better, faster, more creative cook, featuring fun, flavorful recipes anyone can make. ONE OF THE BEST COOKBOOKS OF THE YEAR: NPR, Food52, Taste of Home “Surprising no one, Molly has written a book as smart, stylish, and entertaining as she is.”—Carla Lalli Music, author of Where Cooking Begins If you seek out, celebrate, and obsess over good food but lack the skills and confidence necessary to make it at home, you’ve just won a ticket to a life filled with supreme deliciousness. Cook This Book is a new kind of foundational cookbook from Molly Baz, who’s here to teach you absolutely everything she knows and equip you with the tools to become a better, more efficient cook. Molly breaks the essentials of cooking down to clear and uncomplicated recipes that deliver big flavor with little effort and a side of education, including dishes like Pastrami Roast Chicken with Schmaltzy Onions and Dill, Chorizo and Chickpea Carbonara, and of course, her signature Cae Sal. But this is not your average cookbook. More than a collection of recipes, Cook This Book teaches you the invaluable superpower of improvisation though visually compelling lessons on such topics as the importance of salt and how to balance flavor, giving you all the tools necessary to make food taste great every time. Throughout, you’ll encounter dozens of QR codes, accessed through the camera app on your smartphone, that link to short technique-driven videos hosted by Molly to help illuminate some of the trickier skills. As Molly says, “Cooking is really fun, I swear. You simply need to set yourself up for success to truly enjoy it.” Cook This Book will help you do just that, inspiring a new generation to find joy in the kitchen and take pride in putting a home-cooked meal on the table, all with the unbridled fun and spirit that only Molly could inspire.

R for Data Science

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

R Cookbook

Author: JD Long
Publisher: "O'Reilly Media, Inc."
ISBN: 1492040630
Category : Computers
Languages : en
Pages : 625

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

R Data Visualization Cookbook

Author: Atmajitsinh Gohil
Publisher: Packt Publishing Ltd
ISBN: 1783989513
Category : Computers
Languages : en
Pages : 236

Book Description
If you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.

R Graphics Cookbook

Author: Winston Chang
Publisher: "O'Reilly Media, Inc."
ISBN: 1449316956
Category : Computers
Languages : en
Pages : 414

Book Description
"Practical recipes for visualizing data"--Cover.

Data Mashups in R

Author: Jeremy Leipzig
Publisher: "O'Reilly Media, Inc."
ISBN: 1449307256
Category : Computers
Languages : en
Pages : 40

Book Description
How do you use R to import, manage, visualize, and analyze real-world data? With this short, hands-on tutorial, you learn how to collect online data, massage it into a reasonable form, and work with it using R facilities to interact with web servers, parse HTML and XML, and more. Rather than use canned sample data, you'll plot and analyze current home foreclosure auctions in Philadelphia. This practical mashup exercise shows you how to access spatial data in several formats locally and over the Web to produce a map of home foreclosures. It's an excellent way to explore how the R environment works with R packages and performs statistical analysis. Parse messy data from public foreclosure auction postings Plot the data using R's PBSmapping package Import US Census data to add context to foreclosure data Use R's lattice and latticeExtra packages for data visualization Create multidimensional correlation graphs with the pairs() scatterplot matrix package

Quantitative Trading with R

Author: Harry Georgakopoulos
Publisher: Springer
ISBN: 1137437472
Category : Business & Economics
Languages : en
Pages : 364

Book Description
Quantitative Finance with R offers a winning strategy for devising expertly-crafted and workable trading models using the R open source programming language, providing readers with a step-by-step approach to understanding complex quantitative finance problems and building functional computer code.

Using R for Introductory Statistics

Author: John Verzani
Publisher: CRC Press
ISBN: 1315360306
Category : Computers
Languages : en
Pages : 522

Book Description
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.

Hands-On Machine Learning with R

Author: Brad Boehmke
Publisher: CRC Press
ISBN: 1000730433
Category : Business & Economics
Languages : en
Pages : 373

Book Description
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.