useR! 2024

{admiral} is a package developed across the pharmaceutical industry to derive datasets that comply with industry specific data standards. In this presentation, we'd like to give a brief exposition of the {admiral} package. The talk commences by introducing our problem statement, how we solve it in {admiral} by compartmentalizing domain specific functionalities, and how the package and its family expanded to a wide cross-industry collaboration. We conclude showcasing a case-study where pandemic-driven interests led to an industry effort to create a vaccine-specific {admiral} toolset.

Reading tabular data with formatted cell in Microsoft Excel can be really tricky. Unexpected things may happen if I read it blindly in R using readxl::read_excel. I have tried to use the col_types argument but it was not enough for me. Unfortunately, there are limited resources to deal with reading tabular data with formatted cells in Excel. In my presentation, I will share some problematic formatted columns that I have encountered during my work with clinical data. Examples are Date in General (Text) and Date number format Numeric column with different colour font representing different units of the same measurements Numeric columns with some numbers provided in text More importantly, I will share how I managed to handle them in R using these three R packages collateral (https://collateral.jamesgoldie.dev/), pointblank (https://rstudio.github.io/pointblank/index.html) and tidyxl (https://nacnudus.github.io/tidyxl/index.html). For more details, I have written a blog post on https://jeremy-selva.netlify.app/blog/2024-02-15-tackling-formatted-cell-data/