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R for Data Science

Import, Tidy, Transform, Visualize, and Model Data

Paperback Engels 2023 2e druk 9781492097402
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Samenvatting

Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse—a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly.

You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Updated for the latest tidyverse features and best practices, new chapters show you how to get data from spreadsheets, databases, and websites. Exercises help you practice what you've learned along the way.

You'll understand how to:
- Visualize: Create plots for data exploration and communication of results
- Transform: Discover variable types and the tools to work with them
- Import: Get data into R and in a form convenient for analysis
- Program: Learn R tools for solving data problems with greater clarity and ease
- Communicate: Integrate prose, code, and results with Quarto

Specificaties

ISBN13:9781492097402
Taal:Engels
Bindwijze:paperback
Aantal pagina's:494
Uitgever:O'Reilly
Druk:2
Verschijningsdatum:2-7-2023
Hoofdrubriek:IT-management / ICT
ISSN:

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Over Hadley Wickham

Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor at Stanford University and the University of Auckland, and a member of the R Foundation. He is the lead developer of the tidyverse, a collection of R packages, including ggplot2 and dplyr, designed to support data science. He is also the author of R for Data Science (with Garrett Grolemund), R Packages, and ggplot2: elegant graphics for data analysis.

Andere boeken door Hadley Wickham

Over Garrett Grolemund

Garrett Grolemund is a statistician, teacher and R developer who currently works for RStudio. He sees data analysis as a largely untapped fountain of value for both industry and science. Garrett received his Ph.D at Rice University in Hadley Wickham's lab, where his research traced the origins of data analysis as a cognitive process and identified how attentional and epistemological concerns guide every data analysis. Garrett is passionate about helping people avoid the frustration and unnecessary learning he went through while mastering data analysis. Even before he finished his dissertation, he started teaching corporate training in R and data analysis for Revolutions Analytics. He's taught at Google, eBay, Axciom and many other companies, and is currently developing a training curriculum for RStudio that will make useful know-how even more accessible. Outside of teaching, Garrett spends time doing clinical trials research, legal research, and financial analysis. He also develops R software, he's co-authored the lubridate R package--which provides methods to parse, manipulate, and do arithmetic with date-times--and wrote the ggsubplot package, which extends the ggplot2 package.

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Inhoudsopgave

Introduction

I. Whole Game
1. Data Visualization
2. Workflow: Basics
3. Data Transformation
4. Workflow: Code Style
5. Data Tidying
6. Workflow: Scripts and Projects
7. Data Import
8. Workflow: Getting Help

II. Visualize
9. Layers
10. Exploratory Data Analysis
11. Communication

III. Transform
12. Logical Vectors
13. Numbers
14. Strings
15. Regular Expressions
16. Factors
17. Dates and Times
18. Missing Values
19. Joins

IV. Import
20. Spreadsheets
21. Databases
22. Arrow
23. Hierarchical Data
24. Web Scraping

V. Program
25. Functions
26. Iteration
27. A Field Guide to Base R

VI. Communicate
28. Quarto
29. Quarto Formats

Index
About the Authors

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        R for Data Science