R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Author: Hadley Wickham, Garrett Grolemund
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.
In this book, you will find a practicum of skills for data science. It contains all basic skills a person needs to learn as a data scientist. You’ll learn how to clean data and draw plots, explore and communicate meaningful insights that you obtain from the data. These are the skills that allow data science to happen. Here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data.
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.
What will you learn:
- 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