People using R for applied research are often not taught basic programming practices such as writing functions, efficient iterative processing, vectorization, and other practices that would make their research far more efficient and reproducible.  Understandably, focus is on basic data manipulation and getting model results.  Unfortunately, this can mean the data isn’t as explored as it should be, or other opportunities are lost (e.g. feature engineering), because of the presumed effort that would be required to deal with the data more fully.