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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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Author (1):
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Gustavo Santos Gustavo Santos
Author Profile Icon Gustavo Santos
Gustavo Santos
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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

Date and time with lubridate

Dates and times have their formatting as the main characteristic to distinguish this type of data. A quick look at the variables where a YYYY-MM-DD number appears is enough to tell that it is a date object. However, as mentioned, computers calculate date and time based on seconds, so it is not difficult to see a dataset that brings a variable date or time as an integer number. In those cases, the solution is to recur to the data dictionary (document with the description of each variable) or to the dataset owner and align if that column should indeed be treated as a datetime object or a regular number. Later in this chapter, we will see this problem in action and how to solve it.

Before that, let’s set the base by learning some fundamental functions that will help us to parse datetime objects, splitting them into separate objects. Once again, I will ask you to go over the table from Figure 6.2 to get familiar with the logic of the lubridate library...

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