What are loops in R?
Loops in R programming language are important features which are used to process multiple data elements for business logic. This is a generic programming logic supported by R language to process iterative R statements .R language supports several loops such as while loops, for loops, 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 uses 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, data miners for statistical analysis and reporting. Loops are an important concept to get a deeper understanding of R. To perform Monte Carlo methods in R loops are helpful. Especially for loops are helpful when it comes to simulation part – for example Markov chain process which uses a set of random variables. The state-space involves many finite loops at the origin. In machine learning models to save memory using generators is the key benefit. It is done by defining a function that loops over the elements it defines. In data science, the 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 input 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, list, 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
In the below diagram for each value in the sequence, the loop gets executed. 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)
}
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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] 41. 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:
- Assigning vector length(). It is necessary to allocate sufficient space to maintain efficiency. And the vector has a type of datatypes.
- Second, comes the sequence to determine indices for each element.
- The third is the body of the statements. This is the place where the code performs its work, it runs iteratively each time 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
Below diagram shows the flow diagram of 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 same code repeatedly until a stop condition is reached(break). Below flow diagram gives a clear workflow or repeat statement. At the start, it uses repeat keyword followed by the executable statements written inside the loop and if statements depict the constraint condition. And finally, the only way to terminate the loop is by the execution of break statements. It is an alternative of the do-while keyword of traditional programming (a reflection of it).
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 it is understood the basic concepts and examples of loops in R. To conclude, use of these reduces the time and memory saving and other controversial is loops are little slower in R. It is good if you try to put little code inside the loop and the use of repeat statement in R should be terminated with proper condition. And the use of Loop in R is preferred when an operation is to be repeated. After reading all the key points on Loop with R 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 should avoid them and use the vectorization concept which is better fast.
Recommended Articles
This has been a guide on loops in R. Here we have discussed the Concept, Use to Reduce Time, Type and Examples of Loops in R. You may also look at the following articles to learn more –
