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.

Data Wrangling in the Tidyverse