Visualization and Reporting

Visualization and Reporting

We offer a large number of different individual modules that can be flexibly combined. We will be happy to support you in putting together your individual training.

When you analyze data, how you communicate results is critical. These modules help you to visualize your data and results as graphics, PDF reports, or even interactive web applications.

Module 4.1 Graphics with ggplot2

Prerequisites: Introduction to R (module 1.1 or equivalent skills)

ggplot2 is a widely-used package for creating graphics in R such as bar plots, histograms, line plots, scatter plots, pie charts, and box plots. A great strength of ggplot2 is the limitless possibility to customize your plots (including colors, fonts, and element sizes).

Duration: approx. 2.5 hours

Module 4.2 Dynamic Reporting with R Markdown

Prerequisites: Introduction to R (module 1.1 or equivalent skills)

With R markdown you can flexibly create reproducible reports. R Markdown documents combine text with R code chunks, which are executed when you compile the report. This means that you can include the results of an analysis (graphics, tables, etc.) automatically. With "child files", you can repeat the same set of analyses for different variables. Possible outputs include HTML and PDFs, for example.

Duration: approx. 3 hour

Module 4.3 Automated Reports in your Corporate Design in R

Prerequisites: Introduction to R (module 1.1 or equivalent skills), Dynamic Reporting with R Markdown (module 4.2 or equivalent skills); experience with ggplot2 (module 4.1) is of advantage

When you combine R markdown reports (possibly containing ggplot2 graphics) with the open source R packages ireports and ggCorpIdent by INWT, you can customize your reports and graphics to adopt your individual corporate style.

Duration: approx. 2 hours

Module 4.4 Shiny Apps

Prerequisites: Introduction to R (module 1.1 or equivalent skills); experience with ggplot2 (module 4.1) is of advantage

With shiny you can create interactive web apps with R, such as dashboards. We give an introduction to shiny and cover best practices.

Duration: approx. 3 hours