Level: Intermediate (I)

This virtual course will run over 2 afternoons. It will take you through the fundamental approach of R Programming to creating automated reports.The course commences with an introduction to R Markdown and how you can embed R code directly into a document.  By the end of this course you will be able to work on your own data, importing and exporting data from spreadsheets and other data sources. You will learn how to build automated reports using data, text and graphics using R Markdown.

Course attendees are encouraged to bring their own data or sample data they would like to create a report with, however that is not essential.

For this online course, participants are not required to have R installed on their own laptops. A virtual environment, which can be accessed through a web browser, will be used to run R and view course materials.
 

Learning Outcomes

By the ends of the day participants will:

• be able to use Markdown formatting syntax to customise a document

• have the ability to embed R code into reports using {knitr}

• have learned how to dynamically embed images, plots and tables to their documents

• be able to re-render a report by defining default parameter values

• understand how dashboards and HTML widgets can give them new interactive techniques to view their data

 

Topics Covered

• R Markdown: Creating documents using rmarkdown
• Knitr: Running dynamic R code
• KableExtra & DT: Embedding tabular data into output documents
• Bookdown: Writing books and long-form reports with R Markdown
• Flexdashboard: Creating interactive dashboards
• Parameterised reports: Creating flexible reports
• Widgets: Exploring interactive HTML widgets

 

Target Audience

This course is suitable for data analysts. It is expected that participants are already familiar with R. In particular they should be familiar with basic data manipulations, functions, if statements and for loops. These concepts are covered in our Introduction to R course.

Dr Clarissa Barratt

While working towards her PhD in applied mathematics Clarissa discovered her love of science communications. Her goal is to make data science accessible to everyone, and to encourage people to engage with the goings on at Jumping Rivers.

Fees		Registration before   16 June 2024	Registration on/after 16 June 2024
Non Member  RSS Fellow  RSS CStat/Gradstat/Data Analyst   also MIS & FIS		£445.00+vat  £377.00+vat  £356.00+vat	£494.00+vat  £420.00+vat  £396.00+vat
Group discounts are also available*: 3-5 people 6-8 people 9+ people *Discount only applies to non-member price		10% discount 15% discount 20% discount