将值标签分配给变量的形状

Question

我有一个数据框“CB”，其中有一列“性别”，其中包含两个变量“男性”和“女性”。 我希望“男性”的值为 0，而“女性”的值为 1。

我这样做了：

CB$gender <- ifelse(CB$gender == "Male", 0, ifelse(CB$gender == "Female", 1, 
999))

当我查看该列时，我得到以下结果：

head(CB$gender, 3)
[1] 1 0 0

没关系！

当我制作表格时，我得到了这个结果：

table(CB$gender)

  0    1 
3555 3488 

我希望 0 表示“男性”，1 表示“女性”

为了更好地理解：

在 SPSS 中，可以将值 0 分配给“男性”，将值 1 分配给“女性”。当我打印一张表格时，它看起来像这样：

Male Female
3555 3488 

但列看起来像这样：

gender
0
1
1
0

这就是我想要的。

谢谢！

Answer 1

您可以使用factor 将变量转换为因子并标记它：

CB <- data.frame(gender= c("Male", "Female", "Male", "Male", "Female", "Female", "Male", "Male"))
CB$gender <- ifelse(CB$gender == "Male", 0, ifelse(CB$gender == "Female", 1, 999))
str(CB)
#'data.frame':  8 obs. of  1 variable:
# $ gender: num  0 1 0 0 1 1 0 0
CB$gender <- factor(CB$gender ,
                labels=c("Male", "Female"))
str(CB)
#'data.frame':  8 obs. of  1 variable:
# $ gender: Factor w/ 2 levels "Male","Female": 1 2 1 1 2 2 1 1
table(CB$gender)
#Male Female 
#   5      3 

注意：R 通过转换为因子分配级别 1（在本例中为 1 和 2）

或者，您可以使用包lfactors：

library(lfactors)
CB <- data.frame(gender= c("Male", "Female", "Male", "Male", "Female", "Female", "Male", "Male"))
CB$gender <- ifelse(CB$gender == "Male", 0, ifelse(CB$gender == "Female", 1, 999))
CB$gender <- lfactor(CB$gender,
                 levels=0:1,
                 labels=c("Male", "Female"))
print(CB$gender)
#[1] Male   Female Male   Male   Female Female Male   Male  
#Levels: Male Female
#Numeric levels: 0 1 
table(CB$gender)
#  Male Female 
#     5      3 
attributes(CB$gender)$llevels
#[1] 0 1

另一个最接近 SPSS 类比的选项是使用包 labelled 和 sjmisc，如下所示：

library(labelled)
library(sjmisc) #access to function to_label()
CB <- data.frame(gender= c("Male", "Female", "Male", "Male", "Female", "Female", "Male", "Male"))
CB$gender <- ifelse(CB$gender == "Male", 0, ifelse(CB$gender == "Female", 1, 999))
val_labels(CB$gender) <- c("Male" = 0, "Female" = 1)
print(CB$gender)
#<Labelled double>
#[1] 0 1 0 0 1 1 0 0
#Labels:
# value  label
#     0   Male
#     1 Female
table(to_label(CB$gender))
#  Male Female 
#     5      3 

此外，您可以组合使用包sjmisc 和sjlabelled。

library(sjmisc) #access to function to_label()
library(sjlabelled) #function set_labels()
CB <- data.frame(gender= c("Male", "Female", "Male", "Male", "Female", "Female", "Male", "Male"))
CB$gender <- ifelse(CB$gender == "Male", 0, ifelse(CB$gender == "Female", 1, 999))
CB$gender <- set_labels(CB$gender, labels=c("Male", "Female"))
print(CB$gender)
#[1] 0 1 0 0 1 1 0 0
#attr(,"labels")
#  Male Female 
#     0      1 
table(to_label(CB$gender))
#  Male Female 
#     5      3 

函数to_label() 与包lfactors、labelled 和sjlabelled 的工作方式类似。