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📜  R因素

📅  最后修改于: 2021-01-08 09:45:37             🧑  作者: Mango

R因子

该因子是一种数据结构，用于仅采用预定义的有限数量的值的字段。这些是采用有限数量的不同值的变量。这些是数据对象，用于对数据进行分类并将其存储在多个级别上。它既可以存储整数值也可以存储字符串值，并且在唯一值数量有限的列中很有用。

因子具有与存储在其中的唯一整数关联的标签。它包含称为水平的预定义设置值，默认情况下，R始终按字母顺序对水平排序。

因素的属性

R中有一个因子的以下属性

  • X它是要转换为因子的输入向量。
  • 级别这是一个输入向量，代表x所取的一组唯一值。
  • 标签它是一个字符向量，对应于标签的数量。
  • 排除用于指定我们要排除的值，
  • 有序逻辑是确定级别是否有序的逻辑属性。
  • nmax用于指定最大级别数的上限。

如何创建一个因素?

在R中，创建因子非常简单。分两个步骤创建因子

  • 第一步，我们创建一个向量。
  • 下一步是将向量转换为因子，

R提供factor()函数以将向量转换为factor。 factor()函数具有以下语法

factor_data<- factor(vector)

让我们看一个示例，以了解如何使用因子函数。

例

# Creating a vector as input.
data <- c("Shubham","Nishka","Arpita","Nishka","Shubham","Sumit","Nishka","Shubham","Sumit","Arpita","Sumit")

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

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

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

输出量

[1] "Shubham" "Nishka"  "Arpita"  "Nishka"  "Shubham" "Sumit"   "Nishka"
 [8] "Shubham" "Sumit"   "Arpita"  "Sumit"
[1] FALSE
 [1] Shubham Nishka Arpita Nishka Shubham Sumit Nishka Shubham Sumit
[10] Arpita Sumit
Levels: Arpita Nishka Shubham Sumit
[1] TRUE

访问因子的组成部分

像向量一样，我们可以访问因子的组成部分。访问因子分量的过程与向量更相似。我们可以借助索引方法或使用逻辑向量来访问元素。让我们看一个示例，在该示例中我们了解访问组件的不同方式。

例

# Creating a vector as input.
data <- c("Shubham","Nishka","Arpita","Nishka","Shubham","Sumit","Nishka","Shubham","Sumit","Arpita","Sumit")

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

#Printing all elements of factor
print(factor_data)

#Accessing 4th element of factor
print(factor_data[4])

#Accessing 5th and 7th element
print(factor_data[c(5,7)])

#Accessing all elemcent except 4th one
print(factor_data[-4])

#Accessing elements using logical vector
print(factor_data[c(TRUE,FALSE,FALSE,FALSE,TRUE,TRUE,TRUE,FALSE,FALSE,FALSE,TRUE)])

输出量

[1] Shubham Nishka Arpita Nishka Shubham Sumit Nishka Shubham Sumit
[10] Arpita Sumit
Levels: Arpita Nishka Shubham Sumit

[1] Nishka
Levels: Arpita Nishka Shubham Sumit
 
[1] Shubham Nishka
Levels: Arpita Nishka Shubham Sumit

 [1] Shubham Nishka Arpita Shubham Sumit Nishka Shubham Sumit Arpita
[10] Sumit
Levels: Arpita Nishka Shubham Sumit

[1] Shubham Shubham Sumit Nishka Sumit
Levels: Arpita Nishka Shubham Sumit

因子修改

像数据框一样，R允许我们修改因子。我们可以通过简单地重新分配因子来修改它的值。在R中，我们不能选择超出其预定义级别的值，这意味着如果其级别不存在，则无法插入值。为此，我们必须创建该值的级别，然后将其添加到我们的因子中。

让我们看一个示例，以了解如何在因素中进行修改。

例

# Creating a vector as input.
data <- c("Shubham","Nishka","Arpita","Nishka","Shubham")

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

#Printing all elements of factor
print(factor_data)

#Change 4th element of factor with sumit
factor_data[4] <-"Arpita"
print(factor_data)

#change 4th element of factor with "Gunjan"
factor_data[4] <- "Gunjan"    # cannot assign values outside levels
print(factor_data)

#Adding the value to the level
levels(factor_data) <- c(levels(factor_data),"Gunjan")#Adding new level
factor_data[4] <- "Gunjan"
print(factor_data)

输出量

[1] Shubham Nishka Arpita Nishka Shubham
Levels: Arpita Nishka Shubham
[1] Shubham Nishka Arpita Arpita Shubham
Levels: Arpita Nishka Shubham
Warning message:
In `[<-.factor`(`*tmp*`, 4, value = "Gunjan") :
  invalid factor level, NA generated
[1] Shubham Nishka Arpita  Shubham
Levels: Arpita Nishka Shubham
[1] Shubham Nishka Arpita Gunjan Shubham
Levels: Arpita Nishka Shubham Gunjan

数据帧中的因素

当我们创建带有一列文本数据的框架时，R将此文本列视为分类数据并在其上创建因子。

例

# Creating the vectors for data frame.
height <- c(132,162,152,166,139,147,122)
weight <- c(40,49,48,40,67,52,53)
gender <- c("male","male","female","female","male","female","male")

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

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

# Printing the gender column to see the levels.
print(input_data$gender)

输出量

height weight gender
1    132     40   male
2    162     49   male
3    152     48 female
4    166     40 female
5    139     67   male
6    147     52 female
7    122     53   male
[1] TRUE
[1] male   male   female female male   female male
Levels: female male

更改级别顺序

在R中，我们可以借助因子函数来更改因子中水平的顺序。

例

data <- c("Nishka","Gunjan","Shubham","Arpita","Arpita","Sumit","Gunjan","Shubham")
# Creating the factors
factor_data<- factor(data)
print(factor_data)

# Apply the factor function with the required order of the level.
new_order_factor<- factor(factor_data,levels = c("Gunjan","Nishka","Arpita","Shubham","Sumit"))
print(new_order_factor)

输出量

[1] Nishka Gunjan Shubham Arpita Arpita Sumit Gunjan Shubham
Levels: Arpita Gunjan Nishka Shubham Sumit
[1] Nishka Gunjan Shubham Arpita Arpita Sumit Gunjan Shubham
Levels: Gunjan Nishka Arpita Shubham Sumit

产生因子水平

R提供gl()函数来生成因子水平。此函数采用三个参数，即n，k和标签。在这里，n和k是整数，表示我们想要多少个水平以及每个水平需要多少次。

gl()函数的语法如下：

gl(n, k, labels)
  • n表示级别数。
  • k表示复制数量。
  • 标签是结果因子水平的标签向量。

例

gen_factor<- gl(3,5,labels=c("BCA","MCA","B.Tech"))
gen_factor

输出量

[1] BCA BCA BCA BCA BCA MCA MCA MCA MCA MCA
[11] B.Tech B.Tech B.Tech B.Tech B.Tech
Levels: BCA MCA B.Tech