Loops

Many analyses require doing the same kind of operation again and again: apply a transformation to each column, compute a summary for each group, or keep sampling until a condition is met. Loops let you express this repetition once and have R carry it out automatically.

R offers different kinds of loops depending on how repetition is controlled. A for loop runs a fixed number of times, stepping through each element of a sequence or each column in a data frame. In contrast, conditional loops like while and repeat don’t have a predetermined number of iterations — they keep running until a logical condition is no longer satisfied. This makes them useful when the stopping point depends on the data or the outcome of previous steps.

Although loops are essential for expressing repetition, R also provides vectorized operations, which perform the same kind of element-wise work internally, but in a single, optimized command. Vectorization is important because it makes your code both faster and cleaner, reducing the need for explicit loops in many cases.