Even for ‘calculating machines’, as computers were called in the pre-electronics era, pioneers like Ada Lovelace, Charles Babbage and others, devised methods to implement such iterations. It is nothing more than automating a certain multi step process by organizing sequences of actions (‘batch’ processes) and grouping the parts in need of repetition.
‘Looping’, ‘cycling’, ‘iterating’ or just replicating instructions is quite an old practice that originated well before the invention of computers. Want to learn even more on loops? Start the DataCamp interactive R programming tutorial for free. And then try to get rid of those whenever the effort of learning about vectorized alternatives pays in terms of efficiency. In general, the advice of this R tutorial on loops would be: learn about loops, because they offer a detailed view of what it is supposed to happen (what you are trying to do) at the elementary level as well as an understanding of the data you are manipulating. We will present a few looping examples then criticize and deprecate these in favor of the most popular vectorized alternatives (amongst the very many) available in the rich set of libraries that R offers.
HOW TO WRITE A LOOP IN R HOW TO
In this easy-to-follow R tutorial on loops we will examine the constructs available in R for looping, and how to make use of R’s vectorization feature to perform your looping tasks more efficiently.
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