Training Course Details

Next Steps in the Tidyverse

Course Level: Intermediate

The tidyverse is essential for any statistician or data scientist who deals with data on a day-to-day basis. By focusing on small key tasks, the {tidyverse} suite of packages removes the pain of data manipulation. This course takes the next steps in using the {tidyverse} and examines how and where to use packages such as {purrr}, {stringr}, {forcats} and {tidytext} in an analysis.


Online | March 1, 2021

£250.00 ex VAT per person
Venue Details:
This event will be held online via Zoom
March 1, 2021
9.00 am - 5:00 pm (GMT)
1 day
This course will take place, from 9:00am - 5:00pm (GMT), on the 1st of March. We have an early bird offer of £250, which runs until the 7th of February. The price is £300 thereafter.
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Course Details

Course Outline

The course will cover

  • {purrr}: A functional programming toolkit
  • {stringr}: Strings, the band of a data scientist’s life
  • Regular expressions: Matching complicated string patterns to known strings
  • {forcats}: Factors for the tidyverse
  • {tidytext}: A collection of methods for text mining

View course PDF

Learning Outcomes

By the end of the day participants will understand…

  • what tidy data means for statistical modelling
  • the challenges and solutions when working with strings
  • the basics of functional programming and how it relates to the tidyverse
  • when and where to use factors
  • the types of problems regular expressions can help with

Course Structure

Factors are used to work with categorical variables, variables that have a fixed and known set of possible values. Used correctly, factors are incredibly useful. However, base R’s obsession with converting everything to a factor is annoying.

  • The what, why and where of factors
  • Manipulating factors with the forcats package

R is a functional programming language, e.g. the apply family. However, due to the evolution of the language, the interface has some idiosyncrasies. The purrr package provides a complete and consistent set of tools for working with functions and vectors.

  • The map() functions and formula notation
  • Using nest() and unnest()

Strings aren’t glamorous, and while base R can handle all tasks, it isn’t always clear how to approach each task. The stringr package provides a cohesive set of functions designed to make working with strings straightforward.

  • Getting to grips with strings
  • The fundamentals of regular expressions

Prior Knowledge

This course assumes basic familiarity with R and the tidyverse. Attending our Getting to Grips with the Tidyverse course, is more than sufficient in providing you with the prerequisite knowledge required for this course!