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# Categorical Data in the Tidyverse

via DataCamp

### Overview

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

As a data scientist, you will often find yourself working with non-numerical data, such as job titles, survey responses, or demographic information. R has a special way of representing them, called factors, and this course will help you master working with them using the tidyverse package forcats. Weâ€™ll also work with other tidyverse packages, including ggplot2, dplyr, stringr, and tidyr and use real world datasets, such as the fivethirtyeight flight dataset and Kaggleâ€™s State of Data Science and ML Survey. Following this course, youâ€™ll be able to identify and manipulate factor variables, quickly and efficiently visualize your data, and effectively communicate your results. Get ready to categorize!

### Syllabus

• Introduction to Factor Variables
• In this chapter, youâ€™ll learn all about factors. Youâ€™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, youâ€™ll find how forcats, a tidyverse package, can improve your plots by letting you quickly reorder variables by their frequency.
• Manipulating Factor Variables
• Youâ€™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.
• Creating Factor Variables
• Having gotten a good grasp of forcats, youâ€™ll expand out to the rest of the tidyverse, learning and reviewing functions from dplyr, tidyr, and stringr. Youâ€™ll refine graphs with ggplot2 by changing axes to percentage scales, editing the layout of the text, and more.
• Case Study on Flight Etiquette
• In this final chapter, youâ€™ll take all that youâ€™ve learned and apply it in a case study. Youâ€™ll learn more about working with strings and summarizing data, then replicate a publication quality 538 plot.

Emily Robinson

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