CODAP is a widely-used programming environment for secondary school data science. Its direct-manipulation-based design offers many advantages to learners, especially younger students. Unfortunately, these same advantages can become a liability when it comes to repeating operations consistently, replaying operations (for reproducibility), and also for learning abstraction. In response, we have extended CODAP with CODAP Transformers, which add a notion of functions to CODAP. These provide a gentle introduction to reuse and abstraction in the data science context. We present a critique of CODAP that justifies our extension, describe the extension, and showcase some novel operations. Our extension has been integrated into the CODAP codebase, and is now part of the standard CODAP tool. It is already in use by the Bootstrap curriculum.