## 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

## Table of contents

- Preface
- I. Explore
- 1. Data Visualization with ggplot2
- 2. Workflow: Basics
- 3. Data Transformation with dplyr
- 4. Workflow: Scripts
- 5. Exploratory Data Analysis
- 6. Workflow: Projects
- II. Wrangle
- 7. Tibbles with tibble
- 8. Data Import with readr
- 9. Tidy Data with tidyr
- 10. Relational Data with dplyr
- 11. Strings with stringr
- 12. Factors with forcats
- 13. Dates and Times with lubridate
- III. Program
- 14. Pipes with magrittr
- 15. Functions
- 16. Vectors
- 17. Iteration with purrr
- IV. Model
- 18. Model Basics with modelr
- 19. Model Building
- 20. Many Models with purrr and broom
- V. Communicate
- 21. R Markdown
- 22. Graphics for Communication with ggplot2
- 23. R Markdown Formats
- 24. R Markdown Workflow
- Index

## Product information

- Title: R for Data Science
- Author(s):
- Release date: December 2016
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491910344

## You might also like

book

### R for Data Science, 2nd Edition

Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data …

video

### R Programming for Statistics and Data Science

Waste no time and jump right into hands-on coding in R. We start off light and …

book

### Machine Learning with R, the tidyverse, and mlr

Machine learning (ML) is a collection of programming techniques for discovering relationships in data. With ML …

book

### Python and R for the Modern Data Scientist

Success in data science depends on the flexible and appropriate use of tools. That includes Python …