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How to find monthly sales using date variable in R?
Sales analysis requires to find monthly sales mean, total, range, and often standard deviation. This is mostly required by FMCG (Fast-Moving Consumer Goods) companies because they want to track their sales on daily basis as well as monthly basis. If we have daily sales data then we need to create another column for months in an R data frame to find the monthly sales and this can be done with the help of strftime and aggregate function.
Example
Consider the below data frame −
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)
dfOutput
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
Updated on: 21-Aug-2020
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