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R Data Science Quick Reference

2019-08-07 Computers
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Release : 2019-08-07
Genre : Computers
Kind : eBook
Book Rating : 945/5 ( reviews)

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Book Synopsis R Data Science Quick Reference by : Thomas Mailund

Download or read book R Data Science Quick Reference written by Thomas Mailund. This book was released on 2019-08-07. Available in PDF, EPUB and Kindle. Book excerpt: In this handy, practical book you will cover each concept concisely, with many illustrative examples. You'll be introduced to several R data science packages, with examples of how to use each of them. In this book, you’ll learn about the following APIs and packages that deal specifically with data science applications: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more. After using this handy quick reference guide, you'll have the code, APIs, and insights to write data science-based applications in the R programming language. You'll also be able to carry out data analysis. What You Will LearnImport data with readrWork with categories using forcats, time and dates with lubridate, and strings with stringrFormat data using tidyr and then transform that data using magrittr and dplyrWrite functions with R for data science, data mining, and analytics-based applicationsVisualize data with ggplot2 and fit data to models using modelr Who This Book Is For Programmers new to R's data science, data mining, and analytics packages. Some prior coding experience with R in general is recommended.

R for Data Science

2016-12-12 Computers
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Release : 2016-12-12
Genre : Computers
Kind : eBook
Book Rating : 364/5 ( reviews)

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Book Synopsis R for Data Science by : Hadley Wickham

Download or read book R for Data Science written by Hadley Wickham. This book was released on 2016-12-12. Available in PDF, EPUB and Kindle. Book excerpt: 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 4 Data Science Quick Reference

2022
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Release : 2022
Genre :
Kind : eBook
Book Rating : 811/5 ( reviews)

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Book Synopsis R 4 Data Science Quick Reference by : Thomas Mailund

Download or read book R 4 Data Science Quick Reference written by Thomas Mailund. This book was released on 2022. Available in PDF, EPUB and Kindle. Book excerpt: In this handy, quick reference book you'll be introduced to several R data science packages, with examples of how to use each of them. All concepts will be covered concisely, with many illustrative examples using the following APIs: readr, dibble, forecasts, lubridate, stringr, tidyr, magnittr, dplyr, purrr, ggplot2, modelr, and more. With R 4 Data Science Quick Reference, you'll have the code, APIs, and insights to write data science-based applications in the R programming language. You'll also be able to carry out data analysis. All source code used in the book is freely available on GitHub.. You will: Implement applicable R 4 programming language specification features Import data with readr Work with categories using forcats, time and dates with lubridate, and strings with stringr Format data using tidyr and then transform that data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications Visualize data with ggplot2 and fit data to models using modelr.

R in a Nutshell

2012-10-09 Computers
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Release : 2012-10-09
Genre : Computers
Kind : eBook
Book Rating : 08X/5 ( reviews)

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Book Synopsis R in a Nutshell by : Joseph Adler

Download or read book R in a Nutshell written by Joseph Adler. This book was released on 2012-10-09. Available in PDF, EPUB and Kindle. Book excerpt: Presents a guide to the R computer language, covering such topics as the user interface, packages, syntax, objects, functions, object-oriented programming, data sets, lattice graphics, regression models, and bioconductor.

R Quick Syntax Reference

2019-04-24 Computers
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Release : 2019-04-24
Genre : Computers
Kind : eBook
Book Rating : 052/5 ( reviews)

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Book Synopsis R Quick Syntax Reference by : Margot Tollefson

Download or read book R Quick Syntax Reference written by Margot Tollefson. This book was released on 2019-04-24. Available in PDF, EPUB and Kindle. Book excerpt: This handy reference book detailing the intricacies of R updates the popular first edition by adding R version 3.4 and 3.5 features. Starting with the basic structure of R, the book takes you on a journey through the terminology used in R and the syntax required to make R work. You will find looking up the correct form for an expression quick and easy. Some of the new material includes information on RStudio, S4 syntax, working with character strings, and an example using the Twitter API. With a copy of the R Quick Syntax Reference in hand, you will find that you are able to use the multitude of functions available in R and are even able to write your own functions to explore and analyze data. What You Will LearnDiscover the modes and classes of R objects and how to use them Use both packaged and user-created functions in R Import/export data and create new data objects in R Create descriptive functions and manipulate objects in R Take advantage of flow control and conditional statements Work with packages such as base, stats, and graphics Who This Book Is For Those with programming experience, either new to R, or those with at least some exposure to R but who are new to the latest version.

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