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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

Exercises

  1. What function is used to filter data?
  2. What happens when group_by() is used without the summarizing function?
  3. Write the code to return the capital_gain mean grouped by native_country.
  4. What’s function is used to drop all NAs from a dataset?
  5. Write the code to replace NAs with another value.
  6. Write the code to return the average net gain (capital_gain – capital_loss) by education level, arranged in decreasing order.
  7. What is the main function to be used to create new variables?
  8. List all the types of joins.
  9. What is the difference between left join and inner join?
  10. What are the two functions used to reshape data?
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