Managing String Data with GAUSS Dataframes
Working with strings hasn’t always been easy in GAUSS. In the past, the only option in GAUSS was to store strings separately from numeric data. It made it difficult to work with datasets that contained mixed types. With the introduction of GAUSS dataframes in GAUSS 21 and the enhanced string capabilities of GAUSS 23, that has all changed! I would argue that GAUSS now offers one of the best environments for managing and cleaning mixed-type data. I recently used GAUSS to perform the very practical task of creating an email list from a string-heavy dataset – something I never would have chosen GAUSS for in the past. In this blog, we walk through this data cleaning task, highlighting several key features for handling strings.