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Courses>Database Design & Development>Categorical Data in the Tidyverse
Data ScienceCategorical Data in the Tidyverse
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:advanced
Updated:19 February 2024
Published:12 September 2022
Similar courses
Opportunities
Courses>Database Design & Development>Categorical Data in the Tidyverse
Categorical Data in the Tidyverse
4 Hours
12101 students
Syllabus
In this chapter, you’ll learn all about factors. You’ll discover the difference between categorical and ordinal variables, how R represents them, and how to inspect them to find the number and names of the levels. Finally, you’ll find how forcats, a tidyverse package, can improve your plots by letting you quickly reorder variables by their frequency.
You’ll continue to dive into the forcats package, learning how to change the order and names of levels and even collapse them into one another.
Having gotten a good grasp of forcats, you’ll expand out to the rest of the tidyverse, learning and reviewing functions from dplyr, tidyr, and stringr. You’ll refine graphs with ggplot2 by changing axes to percentage scales, editing the layout of the text, and more.
In this final chapter, you’ll take all that you’ve learned and apply it in a case study. You’ll learn more about working with strings and summarizing data, then replicate a publication quality 538 plot.
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Careertail
Courses>Database Design & Development>Categorical Data in the Tidyverse
Data ScienceCategorical Data in the Tidyverse
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:advanced
Updated:19 February 2024
Published:12 September 2022
Similar courses
Opportunities
Courses>Database Design & Development>Categorical Data in the Tidyverse
Categorical Data in the Tidyverse
4 Hours
12101 students
Syllabus
In this chapter, you’ll learn all about factors. You’ll discover the difference between categorical and ordinal variables, how R represents them, and how to inspect them to find the number and names of the levels. Finally, you’ll find how forcats, a tidyverse package, can improve your plots by letting you quickly reorder variables by their frequency.
You’ll continue to dive into the forcats package, learning how to change the order and names of levels and even collapse them into one another.
Having gotten a good grasp of forcats, you’ll expand out to the rest of the tidyverse, learning and reviewing functions from dplyr, tidyr, and stringr. You’ll refine graphs with ggplot2 by changing axes to percentage scales, editing the layout of the text, and more.
In this final chapter, you’ll take all that you’ve learned and apply it in a case study. You’ll learn more about working with strings and summarizing data, then replicate a publication quality 538 plot.
Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot