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# R – Factors

Factors are the data objects which are used to categorize the data and store it as levels. They can store both strings and integers. They are useful in the columns which have a limited number of unique values. Like “Male, “Female” and True, False etc. They are useful in data analysis for statistical modeling.

Factors are created using the factor () function by taking a vector as input.

## Example

# Create a vector as input.
data <- c(“East”,“West”,“East”,“North”,“North”,“East”,“West”,“West”,“West”,“East”,“North”)

print(data)
print(is.factor(data))

# Apply the factor function.
factor_data <- factor(data)

print(factor_data)
print(is.factor(factor_data))

When we execute the above code, it produces the following result −

 “East”  “West” “East”  “North” “North” “East”  “West” “West” “West” “East” “North”
 FALSE
 East  West East North North East  West West West East North
Levels: East North West
 TRUE

## Factors in Data Frame

On creating any data frame with a column of text data, R treats the text column as categorical data and creates factors on it.

# Create the vectors for data frame.
height <- c(132,151,162,139,166,147,122)
weight <- c(48,49,66,53,67,52,40)
gender <- c(“male”,“male”,“female”,“female”,“male”,“female”,“male”)

# Create the data frame.
input_data <- data.frame(height,weight,gender)
print(input_data)

# Test if the gender column is a factor.
print(is.factor(input_data\$gender))

# Print the gender column so see the levels.
print(input_data\$gender)

When we execute the above code, it produces the following result −

height weight gender
1    132   48 male
2    151   49 male
3    162   66 female
4    139   53 female
5    166   67 male
6    147   52 female
7    122   40 male
 TRUE
 male   male female female male   female male
Levels: female male

## Changing the Order of Levels

The order of the levels in a factor can be changed by applying the factor function again with new order of the levels.

data <- c(“East”,“West”,“East”,“North”,“North”,“East”,“West”,“West”,“West”,“East”,“North”)
# Create the factors
factor_data <- factor(data)
print(factor_data)

# Apply the factor function with required order of the level.
new_order_data <- factor(factor_data,levels = c(“East”,“West”,“North”))
print(new_order_data)

When we execute the above code, it produces the following result −

 East  West East  North North East  West West West East  North
Levels: East North West
 East  West East North North East  West West West East North
Levels: East West North

## Generating Factor Levels

We can generate factor levels by using the gl() function. It takes two integers as input which indicates how many levels and how many times each level.

### Syntax

gl(n, k, labels)

Following is the description of the parameters used −

• n is a integer giving the number of levels.
• k is a integer giving the number of replications.
• labels is a vector of labels for the resulting factor levels.

### Example

v <- gl(3, 4, labels = c(“Tampa”, “Seattle”,“Boston”))
print(v)

When we execute the above code, it produces the following result −

Tampa   Tampa Tampa   Tampa Seattle Seattle Seattle Seattle Boston
 Boston  Boston Boston
Levels: Tampa Seattle Boston