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Data Wrangling in the Tidyverse

Data Wrangling in the Tidyverse

Course Level: Foundation

If you work with data, you probably spend a lot of time cleaning it and wrangling it into the correct shape. This course will show you how you can use R to efficiently clean and wrangle your data into a format that’s ready for analysis. You will learn about the Tidyverse, what tidy data really is, and how to practically achieve it with packages such as {dplyr}, {tidyr}, {lubridate} and {forcats}.

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Course Details

  • Course Outline
  • Learning Outcomes
  • Materials
  • Prior Knowledge

Course Outline

  • What is tidy data and the {tidyverse}?
  • Solving data manipulation challenges with {dplyr}
  • Dates and times with the {lubridate} package
  • Creating tidy data with {tidyr}
  • Dealing with categorical variables using {forcats}

Learning Outcomes

Session 1:

By the end of session 1 participants will …

  • be familiar with the {dplyr} data wrangling package, and be able to use its main functions.
  • be able to combine data based on specific columns using {dplyr} join functions.
  • be able to manipulate dates and times in R using {lubridate}.

Session 2:

By the end of session 2 participants will …

  • be able to transform their data between long and wide data formats using {tidyr}.
  • be able to join and separate columns of a dataset.
  • be familiar with different methods of dealing with both explicit and implicit missing values.
  • understand how to apply the {forcats} package to create and re-level factors in datasets, and also reorder variables in a plot.

This course does not include:

  • Content from the {stringr} package, which helps with splitting and combining strings, manipulating text data and working with regular expressions. We have a Text Mining in R course which covers {stringr} in detail.

  • The {purrr} package. If you want to learn more about {purrr} see our Functional Programming with {purrr} course.

  • Although {ggplot2} features in this course, we recommend attending our Data Visualisation with ggplot2 course if you want to learn more about creating data visualisations in R.

Materials

  • Page 1 of example course material for Data Wrangling in the Tidyverse
  • Page 2 of example course material for Data Wrangling in the Tidyverse
  • Page 3 of example course material for Data Wrangling in the Tidyverse
  • Page 4 of example course material for Data Wrangling in the Tidyverse
  • Page 5 of example course material for Data Wrangling in the Tidyverse

Prior Knowledge

This course assumes familiarity with the concepts taught in our Introduction to R course. In particular, we build on the underlying {tidyverse} theory by introducing new {tidyverse} packages. If you have limited or no experience in R, we would advise you to complete our Introduction to R course, before attending.

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