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Data Wrangling with R

You're reading from   Data Wrangling with R Load, explore, transform and visualize data for modeling with tidyverse libraries

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781803235400
Length 384 pages
Edition 1st Edition
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Concepts
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Author (1):
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Gustavo Santos Gustavo Santos
Author Profile Icon Gustavo Santos
Gustavo Santos
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Toc

Table of Contents (21) Chapters Close

Preface 1. Part 1: Load and Explore Data
2. Chapter 1: Fundamentals of Data Wrangling FREE CHAPTER 3. Chapter 2: Loading and Exploring Datasets 4. Chapter 3: Basic Data Visualization 5. Part 2: Data Wrangling
6. Chapter 4: Working with Strings 7. Chapter 5: Working with Numbers 8. Chapter 6: Working with Date and Time Objects 9. Chapter 7: Transformations with Base R 10. Chapter 8: Transformations with Tidyverse Libraries 11. Chapter 9: Exploratory Data Analysis 12. Part 3: Data Visualization
13. Chapter 10: Introduction to ggplot2 14. Chapter 11: Enhanced Visualizations with ggplot2 15. Chapter 12: Other Data Visualization Options 16. Part 4: Modeling
17. Chapter 13: Building a Model with R 18. Chapter 14: Build an Application with Shiny in R 19. Conclusion 20. Other Books You May Enjoy

Summary

We progressed a lot in this chapter and learned so much about datetime objects and variables. Knowing how to use them will enhance your analytical skills, opening room for better insights.

We started this chapter by learning how to create data objects. Next, we acquired knowledge on how to make good use of the lubridate library, and we are now able to parse dates in many different formats.

After that, the subject changed to math operations with date and time and all the specificities that surround it, including the usage of time zones. That was followed by guidance on how to use the customization power of regexp to parse dates out of texts.

Closing the chapter, we viewed a practical exercise where we used a dataset about songs containing a datetime variable, and how you can use that to extract insight for analysis.

The end of this chapter is also the completion of the building blocks for data wrangling. With it, we now have worked with the three major object types...

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