如何用基于另一列的总和值替换df行中的值

Question

Okay so I have a dataframe where one column has characters and another has a value associated with those characters. The problem is that some of the characters are listed twice and so have two different values. For the multiple values, I want to sum them together so there's one value. The trouble I'm having is that all the characters repeat based on ID and I only need to sum the values for each Id not the whole column. The df looks something like this:

    Color   Amount    ID
[1] Purple  45        566
[2] Blue    56        566
[3] Blue    53        566
[4] Yellow  68        566
[5] Green   76        566
[6] Purple  93        789
[7] Purple  35        789
[8] Blue    56        789
[9] Yellow  37        789

And I need to get it to this:

    Color   Amount    ID
[1] Purple  45        566
[2] Blue    109       566
[4] Yellow  68        566
[5] Green   76        566
[6] Purple  128       789
[8] Blue    56        789
[9] Yellow  37        789

Answer 1

You might want to look at the dplyr package that allow you to perform this type of cleaning.

Here is how you can achieve this:

df %>% group_by(ID, Color) %>% summarize(Amount = sum(Amount))

# A tibble: 7 x 3
# Groups:   ID [2]
     ID Color  Amount
  <int> <chr>   <int>
1   566 Blue      109
2   566 Green      76
3   566 Purple     45
4   566 Yellow     68
5   789 Blue       56
6   789 Purple    128
7   789 Yellow     37

Data:

---

df = read.table( text =   "Color Amount  ID
            1 Purple     45 566
            2   Blue     56 566
            3   Blue     53 566
            4 Yellow     68 566
            5  Green     76 566
            6 Purple     93 789
            7 Purple     35 789
            8   Blue     56 789
            9 Yellow     37 789", header =TRUE)