我正在尝试找到一种方法来使用 dplyr
一步获得汇总统计数据,例如按组和整体的方式
#Data set-up
sex <- sample(c("M", "F"), size=100, replace=TRUE)
age <- rnorm(n=100, mean=20 + 4*(sex=="F"), sd=0.1)
dsn <- data.frame(sex, age)
library("tidyverse")
#Using dplyr to get means by group and overall
mean_by_sex <- dsn %>%
group_by(sex) %>%
summarise(mean_age = mean(age))
mean_all <- dsn %>%
summarise(mean_age = mean(age)) %>%
add_column(sex = "All")
#combining the results by groups and overall
final_result <- rbind(mean_by_sex, mean_all)
final_result
#> # A tibble: 3 x 2
#> sex mean_age
#> <fct> <dbl>
#> 1 F 24.0
#> 2 M 20.0
#> 3 All 21.9
#This is the table I want but I wonder if is the only way to do this
有没有办法使用
group_by_at
或 group_by_all
或使用 tidyverse 和 dplyr
的类似函数在更短的步骤中做到这一点任何帮助将不胜感激
最佳答案
一种选择可能是:
dsn %>%
group_by(sex) %>%
summarise(mean_age = mean(age)) %>%
add_row(sex = "ALL", mean_age = mean(dsn$age))
sex mean_age
<fct> <dbl>
1 F 24.0
2 M 20.0
3 ALL 21.9
关于r - 使用 tidyverse 按组和整体获取摘要,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/60437783/