因子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”，“女”，“真”，“假”等。它们在统计建模的数据分析中很有用。
因子可通过factor()函数使用向量作为输入来创建。
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))
当我们执行上述代码时，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
在数据帧中的因子
在使用一列文本数据创建数据帧时，R将文本列视为分类数据并在其上创建因子。参考以下示例代码 -
# 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)
当我们执行上述代码时，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
改变级别顺序
可以通过用新的级别顺序再次应用因子函数来改变因子中级别的顺序。参考以下实现代码 -
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)
当我们执行上述代码时，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
产生因子级别
可以通过使用gl()函数来生成因子级别。它需要两个整数作为输入，它表示每个级别有多少级别和多少次。
语法
gl(n, k, labels)
以下是使用的参数的描述 -
- n - 是给出级别数的整数。
- k - 是给出复制次数的整数。
- labels - 是所得因子水平的标签向量。
例子
v <- gl(3, 4, labels = c("Tampa", "Seattle","Boston"))
print(v)
当我们执行上述代码时，会产生以下结果 -
Tampa Tampa Tampa Tampa Seattle Seattle Seattle Seattle Boston
[10] Boston Boston Boston
Levels: Tampa Seattle Boston
