R 因素
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。它们在唯一值数量有限的列中很有用。像"男"、"女"和"真"、"假"等。它们在统计建模的数据分析中很有用。
因子是使用
factor () 函数通过将向量作为输入来创建的。
示例
# 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时，它会产生以下结果-
[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
数据帧中的因素
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
更改关卡顺序
可以通过再次应用因子函数并使用新的级别顺序来更改因子中级别的顺序。
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时，它会产生以下结果-
[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
生成因子水平
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，表示有多少个级别以及每个级别的次数。
语法
以下是所用参数的说明-
n 是一个整数，表示级别数。
k 是一个整数，表示重复次数。
labels 是结果因子水平的标签向量。
示例
v <-gl(3, 4, labels = c("Tampa", "Seattle","Boston"))
print(v)
当我们执行上面的代码时，它会产生以下结果-
Tampa Tampa Tampa Tampa Seattle Seattle Seattle Seattle Boston
[10] Boston Boston Boston
Levels: Tampa Seattle Boston
