In the following example, the loop will break on the sixth iteration (that won’t be evaluated) despite the full loop has 15 iterations, and will also skip the third iteration.
For that, you can use the break and next functions.
#For loop in r code how to#
The code snippet below shows how to loop through the list by using the FOR loop and then subset each ame, which seems more complicated than how it should be. Sometimes you need to stop the loop at some index if some condition is met or to avoid evaluating some code for some index or condition. data(iris)Įxpr = expression(Sepal.Length > 7 & Sepal.Width > 3) First of all, we need to get things ready by converting the ame into a list with 2 ames named “lst” and defining a subsetting function named “fn”, similar to what we did before. In the example below that is borrowed from, let’s see how to get the job done with the FOR loop. The braces and square bracket are compulsory. Loop can be used to iterate over a list, data frame, vector, matrix or any other object. A for loop is very valuable when we need to iterate over a list of elements or a range of numbers. One might wonder why we need to go through the hassle. For Loop in R with Examples for List and Matrix. 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.
#For loop in r code series#
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. Basic for loop Code takes the first value from volumes and assigns it to volume and does the calculation and prints it Then it takes the second value from.
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. 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.