例

# 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))

当我们执行上面的代码，它产生以下结果 -

 [1] "East"  "West"  "East"  "North" "North" "East"  "West"  "West"  "West"  "East" "North"
[1] FALSE
 [1] East  West  East  North North East  West  West  West  East  North
Levels: East North West
[1] TRUE

数据帧的因子

在创建具有文本数据列的任何数据框时，R语言将文本列视为分类数据并在其上创建因子。

# 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)

当我们执行上面的代码，它产生以下结果 -

  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
[1] TRUE
[1] male   male   female female male   female male  
Levels: female male

更改级别顺序

可以通过使用新的等级次序再次应用因子函数来改变因子中的等级的顺序。

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)

当我们执行上面的代码，它产生以下结果 -

 [1] East  West  East  North North East  West  West  West  East  North
Levels: East North West
 [1] East  West  East  North North East  West  West  West  East  North
Levels: East West North

生成因子级别

我们可以使用gl()函数生成因子级别。 它需要两个整数作为输入，指示每个级别有多少级别和多少次。

语法

gl(n, k, labels)

以下是所使用的参数的说明 -

• n是给出级数的整数。

• k是给出复制数目的整数。

• labels是所得因子水平的标签向量。

例

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

当我们执行上面的代码，它产生以下结果 -

Tampa   Tampa   Tampa   Tampa   Seattle Seattle Seattle Seattle Boston 
[10] Boston  Boston  Boston 
Levels: Tampa Seattle Boston