Loops in R

What are loops in R?

Loops in the R programming language are essential features used to process multiple data elements for business logic. This is a generic programming logic supported by the R language to process iterative R statements. R language supports several loops, such as while loops, for loops, and repeat loops. Loops help R programmers to implement complex logic while developing the code for the requirements of the repetitive step. These are syntax-specific and support various use cases in R programming. These are controlled by the loop condition check, which determines the loop iterations, entry, and exit of the loop scope.

Explain loops in R Programming

R is a programming language used by data scientists and data miners for statistical analysis and reporting. They are an important concept to get a deeper understanding of R. To perform Monte Carlo methods in R loops is helpful. Especially for loops are useful for the simulation part – for example, the Markov chain process, which uses a set of random variables. The state-space involves many finite loops at the origin. In machine learning models, saving memory using generators is the key benefit. It is done by defining a function that loops over the elements it defines. In data science, code duplication makes an impact on code mistakes. It is necessary to identify and remove duplicate values from the dataset. The tool used to reduce them is iteration which performs multiple sample inputs on different data sets. Therefore, it is necessary to use three iteration paradigms: for loops, repeat, and while loops.

1. For Loops in R

For loop works on many data structures like arrays, matrix, lists, and vectors. The basic syntax of For loop in R Programming is given below-

Syntax:

for ( i in 1:n)
{
Body of the statements
}
Nested For loops
for (i in 1: n)
{
for ( i in 1:n)
{
Body of the statements
}
}

Flow Diagram in For Loop

The loop gets executed in the diagram below for each value in the sequence. When there is no more value, it returns to exit.

Example:

Here is a simple example to print the numbers.

for (n in 1:6)
{
print (5 * n)
}

Output:

5

10

15

20

25

30

To count the number of odd values in the list

a <- c (2,7,3,13,8,11,6)
ct <- 0
for (val in a) {
if (! val %% 2 == 0)
ct = ct+1
}
print(ct)

Output:

[1] 4

1. Nested for Loop

Example:

for (i in 1: 4)
{
for ( j in 1:3)
{
print (i*j)
}
}

Output:

1 2 3 2 4 6 3 6 9 4 8 12

2. For Loop using List

Example:

Creation of list using Three vectors

a <- list ("Sunday", "Monday", c (24,63,01), FALSE, 33.9, 12.6)
print (a)

Output:

[[1]] [1] “Sunday”

[[2]] [1] “Monday”

[[3]] [1] 24 36 1

[[4]] [1] False

[[5]] [1] 33.9

[[6]] [1] 12.6

3. Using Vector

x<- 1:6
y<- 1:6
tw <- numeric (length = length(x))
for (i in seq_along(x)) {
tw[i] <- x[i] + y[i] }
tw

Output:

2 4 6 8 10 12

The above program has three components:

1. Assigning vector length(). It is necessary to allocate sufficient space to maintain efficiency. And the vector has a type of datatypes.
2. Second, comes the sequence to determine indices for each element.
3. The third is the body of the statements. This is the place where the code performs its work; it runs each time iteratively with a different value of i.

2. While Loop in R

The block of code is executed until the condition is false (Logical condition), which gives a comparison expression.

Syntax:

While (test condition)
{
Body of the statement
}

Flow Diagram in While Loop

The below diagram shows the flow diagram of the while-loop in R.

Example:

Well, here is an example of a While loop. To compute the square of the number until 3.

i <- 1
while(i<=3)
{
print(i*i)
i=i+1
}

Output:

1

4

9

In the above example, it is clear that ‘i’ is declared initially 1, and the condition here is (i<3), checks for the true statement since 1 is less than 3. the body of the statement is executed, and I value is incremented. The loop is executed until the condition is false and the while loop exits.

3. Repeat loops in R

This loop helps to execute the code repeatedly until a stop condition is reached(break). The below flow diagram gives a clear workflow or repeat statement. It uses a repeated keyword followed by the executable statements and if statements depict the constraint condition. Finally, executing break statements is the only way to terminate the loop. It is an alternative to the do-while keyword of traditional programming.

Syntax:

repeat
{
commands
if (condition expression) {
break}}

Flow Diagram

Example:

Let’s see an example for understanding the repeat statement

s  <- 1
repeat
{
s <- s+3;
print (s);
if (s>10)
break;
}

Output:

4

7

10

13

Example:

s <- 0
repeat {
s = s+1
print(s)
if (s == 4) {
print (" ends");
break
}
}

Output:

1

2

3

4

“ends”

Conclusion

Now the basic concepts and examples of loops are understood in R. To conclude, using these reduces time and memory saving. Another controversy is that loops are a little slower in R. It is good if you try to put little code inside the loop, and the repeat statements in R should be appropriately terminated. And the use of it is preferred when an operation is to be repeated. After reading all the key points, care should be taken during the implementation of R. To improve the performance of the loop, avoid using the loop on the intensive objects. For loops are quite simple, but we should avoid them and use the vectorization concept, which is faster.

Recommended Articles

This is a guide on loops in R. Here, we have discussed the Concept, Type, and Examples of Loops in R. You may also look at the following articles to learn more –

1. Loops in C++ with Examples
2. XGBoost Algorithm
3. Introduction to While Loop in R
4. Different Types of Loops in PowerShell
5. Top 3 Types of Loops in Shell Scripting