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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
Languages
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

Analysis report

Not all Data Science projects will be about modeling data. Most of the time, data scientists are performing data wrangling and exploration to answer business questions and extract good insights to support the decision-making process.

Sometimes, the project itself will be about the EDA, like this one we just did. In those cases, a business report can be written, highlighting the findings. Next, the report for this EDA is presented.

Dataset: College Majors, available at https://tinyurl.com/4yx2dhpe

Dimensions: 173 observations, 21 variables

Data dictionary:

Rank

Type

Rank by median earnings

Major_code

Categorical

Major code, FO1DP in ACS PUMS

Major

Categorical

Major description

Major_category...

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