How do I split values into equal ranges in one column and sum the associated value of another column in R?

Question

I have a dataframe named Cust_Amount which is as follows:

Age    Amount_Spent
25       20
43       15
32       27
37       10
45       17
29       10

I want to break it down into equal sized age groups and sum the amount spent for each age groups as given below:

Age_Group  Total_Amount
 20-30     30
 30-40     37
 40-50     32

Answer 1

We can use cut to group the 'Age' and get the sum of 'Amount_Spent' based on the grouping variable.

library(data.table)
setDT(df1)[,.(Total_Amount = sum(Amount_Spent)) , 
       by = .(Age_Group = cut(Age, breaks = c(20, 30, 40, 50)))]

---

Or with dplyr

library(dplyr)
df1 %>%
    group_by(Age_Group = cut(Age, breaks = c(20, 30, 40, 50))) %>%
    summarise(Total_Amount = sum(Amount_Spent))
#     Age_Group Total_Amount
#      <fctr>        <int>
#1   (20,30]           30
#2   (30,40]           37
#3   (40,50]           32

Answer 2

Here's a base solution using cut and aggregate , and then using setNames to name the resulting columns:

mydf$Age_Group <- cut(mydf$Age, breaks = seq(20,50, by = 10))
with(mydf, setNames(aggregate(Amount_Spent ~ Age_Group, FUN = sum), 
                    c('Age_Group', 'Total_Spent')))

  Age_Group Total_Spent
1   (20,30]          30
2   (30,40]          37
3   (40,50]          32

We can take it a step further using gsub to match your desired output (note that I'm no regular expression expert):

mydf$Age_Group <- 
    gsub(pattern = ',',
     x = gsub(pattern = ']', 
     x = gsub(pattern = '(', x = mydf$Age_Group, replacement = '', fixed = T),
     replacement = '', fixed = T),
     replacement = ' - ', fixed = T)
with(mydf, setNames(aggregate(Amount_Spent ~ Age_Group, FUN = sum), 
                  c('Age_Group', 'Total_Spent')))

  Age_Group Total_Spent
1   20 - 30          30
2   30 - 40          37
3   40 - 50          32