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One might wonder why we need to go through the hassle. invisible(Vectorize(function(i) print(paste("iter", i)), SIMPLIFY = F) (1:3))įrom what has been shown so far, it appears that the solution with a FOR loop is most intuitive and easier to understand. In order to have the anonymous function consuming the whole series instead of the single item, we should create a so-called vectorized function by using the Vectorize() function and then apply this newly created function to the series directly, as shown below. It is noted that the anonymous function created above can only be applied to each item in the series. invisible(lapply(1:3, function(i) print(paste("iter", i)))) Please note that the invisible() function used below doesn’t do anything material but suppress printing out the object value.
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To migrate the above FOR loop, we just need to wrap the operation “print(paste(“iter”, i))” into an anonymous function and then to apply this anonymous function to each element in the series by using the lapply() function. We first created a dummy loop that iterates 3 times and then prints out itself.
#R studio for loop how to
The second option is to “vectorize” a function by using the Vectorize() function such that the newly vectorized function can consume the list directly.īelow is a quick demonstration showing how to recode a FOR loop by using lapply() and Vectorize() functions. The first option is the lapply() or sapply() function that applies a function to each item in the list, which is very similar to the Map() function that I showed in and. In R, there are two ways to implement the same functionality of a FOR loop. A FOR loop is the most intuitive way to apply an operation to a series by looping through each item one by one, which makes perfect sense logically but should be avoided by useRs given the low efficiency.