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Data Wrangling with R

You're reading from  Data Wrangling with R

Product type Book
Published in Feb 2023
Publisher Packt
ISBN-13 9781803235400
Pages 384 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Gustavo R Santos Gustavo R Santos
Profile icon Gustavo R Santos
Toc

Table of Contents (21) Chapters close

Preface 1. Part 1: Load and Explore Data
2. Chapter 1: Fundamentals of Data Wrangling 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

Introduction to stringr

There is a lot to learn about strings. Even though R is a language that was created with statistics in mind, it has developed a lot over the years and many libraries have emerged. As already mentioned, working with strings is a good skill to have given that you will often need to deal with these objects in your daily work as a data scientist. Sentiment analysis of clients or social media, comments analysis in feedback forms, the analysis of textual information scraped from the internet, or simply parsing a city name out of an address are some of the many tasks that can be part of a data wrangling request.

To code along with this chapter, make sure that you have installed and loaded the following libraries. Of them, you may be missing the Gutenberg package. Therefore, I suggest that you use install.package("gutenbergr") before trying to load it. We will use it for an exercise at the end of this chapter:

# Use install.packages("library_name...
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