# R tutorials for Business Analyst – R For Loop with Examples

Hits: 28

A for loop is very valuable when we need to iterate over a list of elements or a range of numbers. Loop can be used to iterate over a list, data frame, vector, matrix or any other object. The braces and square bracket are compulsory.

In this tutorial, we will learn,

• For Loop Syntax and Examples
• For Loop over a list
• For Loop over a matrix

## For Loop Syntax and Examples

```For (i in vector) {
Exp
}
```

Here,

R will loop over all the variables in vector and do the computation written inside the exp. Let’s see a few examples.

Example 1: We iterate over all the elements of a vector and print the current value.

```fruit <- c('Apple', 'Orange', 'Passion fruit', 'Banana')
# Create the for statement
for ( i in fruit){
print(i)
}
```

Output:

```##  "Apple"
##  "Orange"
##  "Passion fruit"
##  "Banana"
```

Example 2: creates a non-linear function by using the polynomial of x between 1 and 4 and we store it in a list

```# Create an empty list
list <- c()
# Create a for statement to populate the list
for (i in seq(1, 4, by=1)) {
list[[i]] <- i*i
}
print(list)
```

Output:

`##    1  4 9 16`

The for loop is very valuable for machine learning tasks. After we have trained a model, we need to regularize the model to avoid over-fitting. Regularization is a very tedious task because we need to find the value that minimizes the loss function. To help us detect those values, we can make use of a for loop to iterate over a range of values and define the best candidate.

Python tutorials for Business Analyst – Python for Loop

## For Loop over a list

Looping over a list is just as easy and convenient as looping over a vector. Let’s see an example

```# Create a list with three vectors
fruit <- list(Basket = c('Apple', 'Orange', 'Passion fruit', 'Banana'),
Money = c(10, 12, 15), purchase = FALSE)
for (p  in fruit)
{
print(p)
}
```

Output:

```##  "Apple" "Orange" "Passion fruit" "Banana"
##  10 12 15
##  FALSE
```

## For Loop over a matrix

A matrix has 2-dimension, rows and columns. To iterate over a matrix, we have to define two for loop, namely one for the rows and another for the column.

```# Create a matrix
mat <- matrix(data = seq(10, 20, by=1), nrow = 6, ncol =2)
# Create the loop with r and c to iterate over the matrix
for (r in 1:nrow(mat))
for (c in 1:ncol(mat))
print(paste("Row", r, "and column",c, "have values of", mat[r,c]))
```

Output:

```##  "Row 1 and column 1 have values of 10"
##  "Row 1 and column 2 have values of 16"
##  "Row 2 and column 1 have values of 11"
##  "Row 2 and column 2 have values of 17"
##  "Row 3 and column 1 have values of 12"
##  "Row 3 and column 2 have values of 18"
##  "Row 4 and column 1 have values of 13"
##  "Row 4 and column 2 have values of 19"
##  "Row 5 and column 1 have values of 14"
##  "Row 5 and column 2 have values of 20"
##  "Row 6 and column 1 have values of 15"
##  "Row 6 and column 2 have values of 10"

```

# Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

## Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

# Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only) `Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.`

# Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!

Snowflake for Beginners – Convert Columns Into Rows

Python Example – Write a Python program to iterate over dictionaries using for loops

Pandas Example – Write a Pandas program to iterate over rows in a DataFrame