Data storytelling with tables: using tableHTML to emphasise key information for your audience

One of the most important tasks in data science is to communicate findings to a non-technical audience. Data visualisation is a powerful tool to make insights actionable. The R ecosystem has wonderful tools, such as ggplot2, to create powerful visualisations. While working on a project that would automate a planning process done manually by a business analyst using Excel, we were faced with a challenge to come up with a report that would look and feel like Excel but could be easily automated. Since the planning algorithm was implemented in R, it was only natural to use it for this purpose. In the process of creating the report, we found that when it comes to showing tables that can be easily styled to make them visually appealing or even to highlight certain values based on some logic, that should not be hard coded and ready to be automated, tableHTML would be the perfect package to do just that.
tableHTML is an R package to create and style HTML tables with CSS from a data.frame or matrix. These tables can be exported and used in any application that accepts HTML, e.g. shiny or rmarkdown. In this talk, we will show how tableHTML can be used in a business context where Excel is commonly used in the business to interact with data in tabular form, how to adjust the appearance to align it to the corporate identity guidelines, and how conditional formatting can help to put emphasis on the most important information.
Clemens Zauchner
Senior Data Scientist, IT Power Services
Studied business informatics in Innsbruck and data science in London. Worked with companies like OMV, easyJet, Sainsbury’s, and The Unbelievable Machine Company. Co-author of open source R package tableHTML, a tool to create and style HTML tables from R
Dana Jomar
Data Scientist, IT Power Services
A learner and a data scientist, with a logical and a mathematical background started a journey in the world of big data and data science, during which Dana is able to work on solving a variety of business problems and use many of the data scientist’s must-haves tools. Recently Dana had the chance to contribute in the development of the open source R package tableHTML version 2.0.0.