因素是用于对数据进行分类并将其存储为级别的数据对象.它们可以存储字符串和整数.它们在具有有限数量的唯一值的列中很有用.像"男性"，"女性"和"真"，"假"等.它们在统计建模的数据分析中很有用.
使用 factor()函数创建因子通过将矢量作为输入.
# 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时，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
在使用一列文本数据创建任何数据框时，R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时，它会产生以下结果 :
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
因子的级别顺序可以通过应用因子函数再次使用新的水平顺序.
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时，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
我们可以使用 gl()函数生成因子水平.它需要两个整数作为输入，表示每个级别有多少级别和多少次.
gl(n，k，labels)
以下是所用参数的说明及减号;
n 是一个给出级别数的整数.
k 是一个给出复制次数的整数.
标签是结果因素的标签向量等级.
v <- gl(3, 4, labels = c("Tampa", "Seattle","Boston"))
print(v)当我们执行上面的代码时，它产生以下结果 :
Tampa Tampa Tampa Tampa Seattle Seattle Seattle Seattle Boston [10] Boston Boston Boston Levels: Tampa Seattle Boston
