R dplyr 按 X 列分组并汇总其余列

Question

我使用以下数据集作为示例:

       Age      Gender  CarType     Group   Education
1      46        Male      Sedan     1        BS
2      37        Male      SUV       1        MS
3      47      Female      Sedan     2        PhD
4      20        Male      SUV       2        HS
5      41        Male      SUV       1        MS 
6      52        Male      Sedan     2        MS

我的目标是使用 Group 变量进行分组，然后按组显示每列的统计信息。

Group   Male  Female Female-Mean-age Male-Mean-AGE Sedan SUV PhD BS MS
 1       3      0         0               41.3      1     2    0  1  2

df %>% group_by(Group) %>% summarise(n = n()) 只是给出计数但是当我尝试为每个性别添加变异和收集计数时我得到错误

df %>% group_by(Group, Gender) %>% summarize(n=n()) %>% mutate(male = count('Male'))

我是否需要将所有列都包含在 group_by 中以便稍后访问求和或计数，或者最好的方法是什么？

Answer 1

一个选择是将收集成“长”格式并获取多列的“计数”，展开到“宽”格式然后做一个加入由“Group”和“Gender”计算的“Age”的mean

library(tidyr)
library(dplyr)
res1 <- gather(df1, key, val, Gender, CarType, Education) %>% 
               group_by(Group, key, val) %>% 
               summarise(n = n()) %>%
               ungroup %>% select(-key) %>% 
               spread(val, n, fill = 0)
res2 <- df1 %>% 
           group_by(Group, Gender) %>%
           summarise(Age_Mean = mean(Age))  %>% 
           mutate(Gender = paste0(Gender, "_Mean")) %>%
           spread(Gender, Age_Mean, fill = 0)
left_join(res1, res2)
# A tibble: 2 x 11
#  Group    BS Female    HS  Male    MS   PhD Sedan   SUV Female_Mean Male_Mean
#  <int> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>       <dbl>     <dbl>
#1     1  1.00   0     0     3.00  2.00  0     1.00  2.00         0        41.3
#2     2  0      1.00  1.00  2.00  1.00  1.00  2.00  1.00        47.0      36.0