Accessing values from data frames, data tables, tibbles, matrices, and vectors (CC278)
Watch along as Pat shows a variety of approaches for obtaining rows from data frames, data tables, tibbles, sparse matrices, and vectors and then compares their performance. Which do you think will be the most performant? You’ll likely be surprised by the results! This episode is part of an ongoing effort to develop an R package that implements the naive Bayesian classifier.
Code
You can browse the state of the repository at the