销售分析需要找到每月的销售平均值，总数，范围以及通常的标准偏差。FMCG（快速消费品）公司最需要这样做，因为它们希望跟踪每天和每月的销售额。如果我们有每日销售数据，那么我们需要在R数据框中创建数月的另一列以查找每月销售，这可以借助strftime和聚合函数来完成。
请看以下数据帧-
date<-c("2020/05/05","2020/05/05","2020/05/06","2020/06/10","2020/06/25",
+ "2020/06/25","2020/04/15","2020/05/25","2020/03/02","2020/02/25",
+ "2020/03/12","2020/02/21","2020/03/04","2020/04/21","2020/05/24",
+ "2020/02/17","2020/06/07","2020/04/08","2020/01/25","2020/01/04",
+ "2020/05/20","2020/01/24","2020/04/01")
sales<-c(17,25,14,19,21,24,26,28,18,25,26,18,19,25,20,17,10,18,26,27,21,24,18)
df<-data.frame(date,sales)
df输出结果
date sales 1 2020/05/05 17 2 2020/05/05 25 3 2020/05/06 14 4 2020/06/10 19 5 2020/06/25 21 6 2020/06/25 24 7 2020/04/15 26 8 2020/05/25 28 9 2020/03/02 18 10 2020/02/25 25 11 2020/03/12 26 12 2020/02/21 18 13 2020/03/04 19 14 2020/04/21 25 15 2020/05/24 20 16 2020/02/17 17 17 2020/06/07 10 18 2020/04/08 18 19 2020/01/25 26 20 2020/01/04 27 21 2020/05/20 21 22 2020/01/24 24 23 2020/04/01 18 m.date<-strftime(df$date,"%m") Monthly_Sales_Mean<-aggregate(df$sales~m.date,FUN=mean) Monthly_Sales_Mean m.date df$sales 1 01 25.66667 2 02 20.00000 3 03 21.00000 4 04 21.75000 5 05 20.83333 6 06 18.50000 Monthly_Sales_Total<-aggregate(df$sales~m.date,FUN=sum) Monthly_Sales_Total m.date df$sales 1 01 77 2 02 60 3 03 63 4 04 87 5 05 125 6 06 74 Monthly_Sales_Range<-aggregate(df$sales~m.date,FUN=range) Monthly_Sales_Range m.date df$sales.1 df$sales.2 1 01 24 27 2 02 17 25 3 03 18 26 4 04 18 26 5 05 14 28 6 06 10 24 Monthly_Sales_SD<-aggregate(df$sales~m.date,FUN=sd) Monthly_Sales_SD m.date df$sales 1 01 1.527525 2 02 4.358899 3 03 4.358899 4 04 4.349329 5 05 5.115336 6 06 6.027714