使用另一个变量的选定水平创建一个新变量

Question

我在使用另一个变量的选定水平创建新变量时遇到了问题。数据集是gss，变量是class有5个水平"Lower Class""Working Class""Middle Class""Upper Class""No Class"和NA

如果我运行,

gss %>% 
select(class) %>%
str()

它给了我

'data.frame':   57061 obs. of  1 variable:
$ class: Factor w/ 5 levels "Lower Class",..: 3 3 2 3 2 3 3 2 2 2 ...

因为我只对那些指定了经济 class 的人感兴趣，所以我想去掉 "No Class" 水平和 NA。我不知道有什么更好的方法，所以我做了

gss <- gss %>%
mutate(filteredclass = ifelse(class == "Lower Class", "Lower Class", 
ifelse(class == "Working Class", "Working Class", ifelse(class == "Middle 
Class", "Middle Class", ifelse(class == "Upper Class", "Upper Class", NA)))))

然后，我试着看看它是否有效，所以我运行:

with (gss, table(filteredclass))

然后给了我如下的混合订单：

filteredclass
Lower Class  Middle Class   Upper Class Working Class 
     3147         24289          1741         24458

我希望新变量 filteredclass 显示为与变量 'class' 相同的顺序。因为如果我对变量 'class' 做同样的事情，它会给我：

with (gss, table(class))
class
Lower Class Working Class  Middle Class   Upper Class 
     3147         24458         24289          1741 
 No Class 
        1

有什么办法可以解决这个问题吗？或者，有没有什么办法可以在不通过我上面执行的 mutate 命令的情况下取消 No Class 级别？

提前感谢您的帮助！

Answer 1

以后如果你提供一个reproducible example就容易多了。

如果你想摆脱 "No Class" 你可以使用 filter

gss <- gss %>% 
  filter(class != "No Class") %>%
  droplevels()

要删除 NA，只需使用

gss <- na.omit(gss)

Answer 2

最简单的方法可能是 factor 在 class 上：

gss$filteredclass <- factor(gss$class, c("Lower Class", "Working Class",
                             "Middle Class", "Upper Class"))

这将省略 "No class" 并将其设置为 NA。

Answer 3

您必须按照与 gss$class 相同的顺序重新调整因子。为此，您可以在 mutate() 语句中添加另一行，您可以在其中创建具有相同水平的因子并删除未使用的水平（否 Class）。

library(tidyverse)
# Generate the data you showed
gss <- data.frame(class = factor(sample(c("Lower Class",  "Working Class",  "Middle Class",    "Upper Class", NA, "No Class"), 
                                        45000, replace = TRUE))) %>%
  mutate(class = factor(class, levels = c("Lower Class",  "Working Class",  "Middle Class",    "Upper Class", "No Class", NA)))

# Sampled data
with(gss, table(class, useNA = "always"))

# Mutate gss the way you did it
gss <-  gss %>%
  mutate(filteredclass = ifelse(class == "Lower Class", "Lower Class", 
                                ifelse(class == "Working Class", "Working Class",
                                       ifelse(class == "Middle Class", "Middle Class", 
                                              ifelse(class == "Upper Class", "Upper Class", NA)))),
         # Then make filteredclass into a factor with the same levels as class
         # Use droplevels() to remove unused classes (since we removed the No Class)
         filteredclass = droplevels(factor(filteredclass, levels = levels(class))))

with(gss, table(class))
with(gss, table(filteredclass))

输出是这样的，

> with(gss, table(class, useNA = "always"))
class
  Lower Class Working Class  Middle Class   Upper Class      No Class 
         7362          7469          7626          7450          7457 
         <NA> 
         7636 

> with(gss, table(class))
class
  Lower Class Working Class  Middle Class   Upper Class      No Class 
         7362          7469          7626          7450          7457 

> with(gss, table(filteredclass))
filteredclass
  Lower Class Working Class  Middle Class   Upper Class 
         7362          7469          7626          7450

一种更快的方法是使用 droplevels() 而不是 ifelse() 语句链

# Filter/remove obs where class is No Class or NA
with(gss %>% mutate(filteredclass = droplevels(class, exclude = c(NA, "No Class"))),
     table(filteredclass))


filteredclass
  Lower Class Working Class  Middle Class   Upper Class 
         7362          7469          7626          7450

使用另一个变量的选定水平创建一个新变量

Make a new variable with selected levels of another variable

r

dplyr

r-factor