Summarize 和 group_by 不使用因子变量

Posted 2023-02-16

【中文标题】Summarize 和 group_by 不使用因子变量

【英文标题】：Summarise and group_by not working with factor variables

【发布时间】：2021-11-23 14:12:42

【问题描述】：

我目前使用的是 tidyverse 包版本 1.3.1，当我运行以下代码时：

data <- data.frame(gender = c(1,2,1,2,2,2,2,1,2,1), age = c(18,20,21,24,25,24,24,25,22,21))

data <- data%>%
  mutate(gender = factor(gender, levels = c("male", "female")))

data%>%
  group_by(gender)%>%
  summarise(mean = mean(age))

我得到了这些结果

   # A tibble: 1 × 2
  gender  mean
  <fct>  <dbl>
1 NA      22.4

【参考方案1】：

是的，您应该更改 labels 而不是 levels。

library(dplyr)

data%>%
  mutate(gender = factor(gender, labels = c("male", "female"))) %>%
  group_by(gender)%>%
  summarise(mean = mean(age))

#  gender  mean
#  <fct>  <dbl>
#1 male    21.2
#2 female  23.2

【参考方案2】：

我们不需要转换为factor 进行重新编码。可以通过使用“性别”（数字变量）作为替换值的索引来直接完成

library(dplyr)
data %>%
    group_by(gender = c("male", "female")[gender]) %>%
    summarise(mean = mean(age, na.rm = TRUE))

-输出

# A tibble: 2 × 2
  gender  mean
  <chr>  <dbl>
1 female  23.2
2 male    21.2

---

或者使用fct_recode

library(forcats)
data %>%
   group_by(gender = fct_recode(as.character(gender), male = "1",
         female = "2")) %>% 
   summarise(mean = mean(age, na.rm = TRUE))
# A tibble: 2 × 2
  gender  mean
  <fct>  <dbl>
1 male    21.2
2 female  23.2