# If Else Conditions in R Made Easy with Examples

This tutorial explains various ways to apply IF ELSE conditional statements in R. This tutorial covers two ways to handle conditional statements: the `ifelse()` function and the `if-else` statement. We will also see how IF ELSE statements are used in popular R packages.

## ifelse() Function

In this section, we will cover ifelse() Function in detail.

### Syntax of ifelse() function

Below is the syntax of the `ifelse()` function in R. It works similar to MS Excel IF function.

ifelse(condition, value if condition is true, value if condition is false)

### Examples : ifelse Function

Below are examples showing the application of the ifelse() function in R.

Sample Data
Let's create a sample data to show how to perform IF ELSE function. This data frame would be used further in examples.
x1 x2 x3
1 129 A
3 178 B
5 140 C
7 186 D
9 191 E
11 104 F
13 150 G
15 183 H
17 151 I
19 142 J

Run the program below to generate the above table in R.
```set.seed(123)
mydata = data.frame(x1 = seq(1,20,by=2),
x2 = sample(100:200,10,FALSE),
x3 = LETTERS[1:10])
```
• `x1 = seq(1,20,by=2)`: The variable 'x1' contains alternate numbers starting from 1 to 20. In total, these are 10 numeric values.
• `x2 = sample(100:200,10,FALSE)`: The variable 'x2' constitutes 10 non-repeating random numbers ranging between 100 and 200.
• `x3 = LETTERS[1:10]`: The variable 'x3' contains 10 alphabets starting from A to Z.
Example 1 : Simple ifelse Function

Suppose you are asked to create a binary variable - 1 or 0 based on the variable 'x2'. If value of a variable 'x2' is greater than 150, assign 1 else 0.

mydata\$x4 = ifelse(mydata\$x2>150,1,0)
In this case, it creates a variable x4 on the same data frame 'mydata'. The output is shown in the image below - ifelse : Output
Create variable in a new data frame Suppose you need to add the above created binary variable in a new data frame. You can do it by using the code below -
```x = ifelse(mydata\$x2>150,1,0)
newdata = cbind(x,mydata)
```
The cbind() is used to combine two vectors, matrices or data frames by columns.

Apply ifelse() on Character Variables If variable 'x3' contains character values - 'A', 'D', the variable 'x1' should be multiplied by 2. Otherwise it should be multiplied by 3.
mydata\$y = ifelse(mydata\$x3 %in% c("A","D") ,mydata\$x1*2,mydata\$x1*3)
The output is shown in the table below
```x1 x2 x3 y
1 129 A 2
3 178 B 9
5 140 C 15
7 186 D 14
9 191 E 27
11 104 F 33
13 150 G 39
15 183 H 45
17 151 I 51
19 142 J 57
```
Example 2 : Nested ifelse Function in R

Multiple ifelse functions can be written similarly to excel's If function. In this case, we are telling R to multiply variable x1 by 2 if variable x3 contains values 'A' 'B'. If values are 'C' 'D', multiply it by 3. Else multiply it by 4.

```mydata\$y = ifelse(mydata\$x3 %in% c("A","B") ,mydata\$x1*2,
ifelse(mydata\$x3 %in% c("C","D"), mydata\$x1*3,
mydata\$x1*4))
```
Do you hate specifying data frame multiple times with each variable?

You can use with() function to avoid mentioning data frame each time. It makes writing R code faster.

```mydata\$y = with(mydata, ifelse(x3 %in% c("A","B") , x1*2,
ifelse(x3 %in% c("C","D"), x1*3, x1*4)))
```

Let's dive into the important points regarding the ifelse function, which is commonly used to solve real-world data problems.

### How to treat missing values in ifelse Function?

In R, missing values are denoted by the special value NA (Not Available).

Incorrect Method
```x = NA
ifelse(x==NA,1,0)
```
Result : NA
It should have returned 1.
Correct Method
```x = NA
ifelse(is.na(x),1,0)
```
Result : 1
The is.na() function tests whether a value is NA or not.

### How to use OR and AND operators in ifelse Function

The & symbol is used to perform AND conditions
ifelse(mydata\$x1<10 & mydata\$x2>150,1,0)
Result : 0 1 0 1 1 0 0 0 0 0

The | symbol is used to perform OR conditions
ifelse(mydata\$x1<10 | mydata\$x2>150,1,0)
Result : 1 1 1 1 1 0 0 1 1 0

### How to combine summary and ifelse functions?

In this example, we can counting the number of records where the condition meets. The condition is x1<10 and x2>150.
sum(ifelse(mydata\$x1<10 | mydata\$x2>150,1,0))
Result : 7

## If Else Statement

There is one more way to define conditional statement in R i.e. `if-else statement`. This style of writing If-Else is mostly used when we use conditional statements in loop and R functions. In other words, it is used when we need to perform various actions based on a condition.

### Syntax : If-Else Statement

Below is the syntax of the If-Else statement in R.

```if(condition) {
yes
}
else {
no
}
```
Here 'yes' refers to the value when the condition is true, otherwise it refers to 'no'.

It can also be written in a single line like this - `if(condition) yes else no`

### Examples : If..Else If..Else Statements

The code below would return the value 0 because the condition k > 100 is false.

```k = 99
if(k > 100) 1 else 0
```
Result : 0
How to handle multiple conditions?
k = 100
if(k > 100){
print("Greater than 100")
} else if (k < 100){
print("Less than 100")
} else {
print ("Equal to 100")
}
Result : "Equal to 100"
1. The variable `k` is assigned the value 100. The `if` statement first evaluates the condition `k > 100`. Since the value of `k` is not greater than 100, the condition is false.
2. Next, the `else if` statement is evaluated. The condition `k < 100` is also false because the value of `k` is not less than 100. Since both the initial `if` and the subsequent `else if` conditions are false, the control flow moves to the `else` block.
3. Within the `else` block, the code `print("Equal to 100")` is executed, resulting in the message "Equal to 100" being printed.

## ifelse function vs If-Else Statement

Below are the main differences between the ifelse function and the if-else statement in R.

1. Usage: ifelse() function is commonly used when applying a condition to an entire vector or column of data. whereas, if-else statement is typically used when dealing with more complex conditional logic.
2. Vectorized vs Scalar: The ifelse() function can work with entire vectors or columns of data at once, while the if-else statement operates on individual values.
3. Output Length: The ifelse() function returns a vector with the same length as the input. On the other hand, the if-else statement returns a single value or executes blocks of code.

## If Else in Popular Packages

Other than base R, there are functions available in packages for If Else conditions.

### dplyr package: If Else

Below is the syntax of if_else( ) function of dplyr package in R.

if_else(condition, value if condition is true, value if condition is false, value if NA)
The following program checks whether a value is a multiple of 2
```library(dplyr)
x=c(1,NA,2,3)
if_else(x%%2==0, "Multiple of 2", "Not a multiple of 2", "Missing")
```
```Result :
Not a multiple of 2
Missing
Multiple of 2
Not a multiple of 2
```
The %% symbol returns remainder after a value is divided by divisor. In this case, first element 1 is divided by 2.

### sqldf package: If Else

We can write SQL query in R using sqldf package. In SQL, If Else statement is defined in CASE WHEN.

```df=data.frame(k=c(2,NA,3,4,5))
library(sqldf)
sqldf(
"SELECT *,
CASE WHEN (k%2)=0  THEN 'Multiple of 2'
WHEN  k is NULL  THEN 'Missing'
ELSE 'Not a multiple of 2'
END AS T
FROM df"
)
```
```Output

k T
2 Multiple of 2
NA Missing
3 Not a multiple of 2
4 Multiple of 2
5 Not a multiple of 2
```

## Operators

Below is a list of operators frequently used in if-else conditions in the R programming language.

1. Comparison Operators:
• `==`: Equal to
• `!=`: Not equal to
• `<`: Less than
• `>`: Greater than
• `<=`: Less than or equal to
• `>=`: Greater than or equal to
2. Logical Operators:
• `&`: Logical AND
• `|`: Logical OR
• `!`: Logical NOT
3. Compound Operator : `%in%`: Multiple OR conditions. Checks if a value is in a vector or set
Related Posts
Share Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and HR.

5 Responses to "If Else Conditions in R Made Easy with Examples"
1. 2. how to apply this ( use ifelse with more than one condition0. i want to highlight any brand contain "lifestyle". this code gave me error

library(dplyr) # for data manipulation
library(tidyr)
df <- df %>%
mutate(Make = row.names(df),
ID = ifelse(names.effectifs %in% c("Lifestyle","Diet Lifestyle","Lifestyle Plus", TRUE, FALSE),

ggplot(df, aes(reorder(names.effectifs, -effectifs),effectifs, fill = ID)) +
geom_bar(stat = "identity") +
coord_flip() +
scale_fill_manual(values = c("grey90", "dodgerblue")) +
annotate("text", x = "Lifestyle", y =-8, label = "Eff=-10", color = "white") +
theme_minimal() +
theme(legend.position = "none")+
ggtitle(" DECREASED | INCREASED")

3. Hello, great examples thank you.

Could you please make an example from this Excel formula? =IF(AT57=1;1;IF(B57=\$C\$50;1;B57+1))
Thanx

4. 5. HI , I have three location denoted as 1,2,3 in the data set , i wanted to change the location name 1,2,3 to A, B and 3 respectively . How can i change that in r?

Next → ← Prev
Looks like you are using an ad blocker!

To continue reading you need to turnoff adblocker and refresh the page. We rely on advertising to help fund our site. Please whitelist us if you enjoy our content.