How do I make a summary and then multiply the result by group?

Question

So this is my data frame. Country1 represent the people that live in Germany and Country 2 represent the country that they used to live 5 years before moving to Country1 .

Country1	Country2	Weight	obs
Germany	Germany	4	1
Germany	Germany	119	2
France	Germany	3	3
France	Germany	2	4
Italy	France	1	5

Basically what I want is to make a summary of the columns weights for each combination and the multiply by the observation (represented by the column obs. For example, in the first row I have the combination Germany to Germany so what I want is to sum the weights of the column Weight (119+4=123) and then multiply the result of this sum (123* 1=123) to the respective observation of the column Obs (1) (in the first row). For the second row would be the same the summary of the weight for Germany would be (119+4=123)and this result have to be multiplied by the observation of this row in this case (123* 2=246). In the third row the sum of weights would be (3+2=5) and then multiply this result by the observations for this row (5* 3=15) and so on.

The output that I want is represented by the column x and it would be something like this.

Country1	Country2	Weight	obs	x
Germany	Germany	4	1	123
Germany	Germany	119	2	246
France	Germany	3	3	15
France	Germany	2	4	20
Italy	France	1	5	5

Also the formula that im trying to apply is this one.

Answer 1

Try this:

library(dplyr)
#Code
new <- df %>% group_by(Country1) %>%
  mutate(x=sum(Weight)*obs)

Output:

# A tibble: 5 x 5
# Groups:   Country1 [3]
  Country1 Country2 Weight   obs     x
  <chr>    <chr>     <int> <int> <int>
1 Germany  Germany       4     1   123
2 Germany  Germany     119     2   246
3 France   Germany       3     3    15
4 France   Germany       2     4    20
5 Italy    France        1     5     5

Some data used:

#Data
df <- structure(list(Country1 = c("Germany", "Germany", "France", "France", 
"Italy"), Country2 = c("Germany", "Germany", "Germany", "Germany", 
"France"), Weight = c(4L, 119L, 3L, 2L, 1L), obs = 1:5), class = "data.frame", row.names = c(NA, 
-5L))