library(dplyr)
data <- data.frame(year = rep(2016:2017,6),month = seq(1:12),sales=rep(c(10,20,30,40),3))
year month sales
1 2016 1 10
2 2017 2 20
3 2016 3 30
4 2017 4 40
5 2016 5 10
6 2017 6 20
7 2016 7 30
8 2017 8 40
9 2016 9 10
10 2017 10 20
11 2016 11 30
12 2017 12 40
planes <- group_by(data, year)
delay <- summarise(planes,
count = n(), #个数
max_mon = max(month), #最大值
min_mon = min(month), #最小值
avg_sales = mean(sales), #平均值
sum_sales = sum(sales)) #求和
# A tibble: 2 x 6
year count max_mon min_mon avg_sales sum_sales
<int> <int> <dbl> <dbl> <dbl> <dbl>
1 2016 6 11 1 20 120
2 2017 6 12 2 30 180