The tidy format provides a standardized way of organizing data values within a dataset. By leveraging tidy data principles, statisticians, analysts, and data scientists can spend less time cleaning data and more time tackling the more compelling aspects of data analysis. In this course, learn about the principles of tidy data, discover how to create and manipulate data tibbles, and find out how to use the tibbles in importing, transforming, and cleaning your data. Instructor Mike Chapple uses R and the tidyverse packages to teach the concept of data wrangling—the data cleaning and data transformation tasks that consume a substantial portion of analysts’ time. He wraps up with three hands-on case studies that reinforce the data wrangling principles and tactics covered in this course.
