I am trying to find a way to get summary stats such as means by group and overall in one step using dplyr
#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
Is there a way this in shorter step using group_by_at
or group_by_all
or a similar functions using tidyverse and dplyr
Any help would be greatly appreciated
One option could perhaps be:
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