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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

Table of Contents (21) Chapters

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

Working with Strings

Strings, in the programming world, are textual information: a single letter, a word, a phrase, or, more generally, anything that comes in between single or double quotes will be understood as a string by the computer once it is assigned to a variable. See the following code and comments:

# If not assigned to a variable, a text is just a comment.
"This is a text."
# These are strings
my_string1 <- "a"
my_string2 <- "Hello, World! I am learning!"
my_string1 <- "42"

The manipulation of strings is a good skill to have due to the amount of good data that is found on the internet in textual format. Natural Language Processing (NLP) is one of the largest areas in data science, and a lot of it relies on wrangling strings.

Most of what can be done with strings involves tasks such as the following:

  • Parsing: Separating parts of the text that are divided by a pattern, extracting parts of it and combining words...
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