Tables no longer just live in flat PDFs and reports, but should be able to go from apps to PDFs and Word documents with ease. To have the flexibility to do this we need to separate the analysis from the formatting. Additionally, in the pharmaceutical industry our tables need to be able to change their format. Many journals have different requirements on how to present p-value, and other styling questions. So, we built a package devoted to the formatting of tables based on semi-structured analysis results datasets. This package is unique because it allows users to create tables without data, which helps build mock shells, a key part of table creation within pharma. Additionally, we wanted to be able to layer formats on top of each other as most tables in the industry are built to an internal standard, with minor tweaks around the edges. The code to create the shells can then be reused for the final tables, which saves time and brings table formatting off the critical path. Through the utilization of analysis results datasets, layerable and data-independent formatting, we’ve been able to create a package to meet the specific needs of our business.