Summing rows (based on year/country)

General
1

I have foreign trade data divided by country/year, but I need to sum all the Reporters to get a new value, which will be "South America".
So, in the end, I should have for each year the TradeValue of South America to Australia, Canada, China, etc (Partners).

I have a reprex below:

data.frame(
  stringsAsFactors = FALSE,
              Year = c(1991,1991,1991,1991,1991,
                       1991,1991,1991,1991,1991,1991,1991,1991,1991,1991,
                       1991,1991,1991,1991,1991,1991,1991,1991,1991,
                       1991,1991,1991,1991,1991,1991,1991,1991,1991,1991,
                       1991,1991,1991,1991,1991,1991,1991,1991,1991,
                       1991,1991,1991,1991,1991,1991,1991,1991,1991,1991,
                       1991,1991,1991,1991,1991,1991,1991,1991,1991,
                       1991,1991,1991,1991,1991,1991,1991,1991,1991,1991,
                       1991,1991,1991,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992,1992,1992,
                       1992,1992,1992,1992,1992,1992,1992),
          Reporter = c("Brazil","Chile","Colombia",
                       "Ecuador","Paraguay","Brazil","Chile","Colombia",
                       "Ecuador","Paraguay","Brazil","Chile","Colombia",
                       "Ecuador","Paraguay","Brazil","Chile","Colombia","Ecuador",
                       "Paraguay","Brazil","Chile","Colombia","Ecuador",
                       "Paraguay","Brazil","Chile","Colombia","Ecuador",
                       "Paraguay","Brazil","Chile","Colombia","Ecuador",
                       "Paraguay","Brazil","Chile","Colombia","Ecuador","Paraguay",
                       "Brazil","Chile","Colombia","Ecuador","Paraguay",
                       "Brazil","Chile","Colombia","Ecuador","Paraguay",
                       "Brazil","Chile","Colombia","Ecuador","Paraguay",
                       "Brazil","Chile","Colombia","Ecuador","Paraguay","Brazil",
                       "Chile","Colombia","Ecuador","Paraguay","Brazil",
                       "Chile","Colombia","Ecuador","Paraguay","Brazil",
                       "Chile","Colombia","Ecuador","Paraguay",
                       "Bolivia (Plurinational State of)","Brazil","Chile","Colombia","Ecuador",
                       "Peru","Bolivia (Plurinational State of)","Brazil",
                       "Chile","Colombia","Ecuador","Paraguay","Peru",
                       "Bolivia (Plurinational State of)","Brazil","Chile",
                       "Colombia","Ecuador","Peru","Bolivia (Plurinational State of)",
                       "Brazil","Chile","Colombia","Ecuador","Paraguay",
                       "Peru","Bolivia (Plurinational State of)","Brazil",
                       "Chile","Colombia","Ecuador","Paraguay","Peru",
                       "Bolivia (Plurinational State of)","Brazil","Chile","Colombia",
                       "Paraguay","Peru","Bolivia (Plurinational State of)",
                       "Brazil","Chile","Colombia","Ecuador","Paraguay",
                       "Peru","Bolivia (Plurinational State of)","Brazil",
                       "Chile","Colombia","Ecuador","Paraguay","Peru",
                       "Bolivia (Plurinational State of)","Brazil","Chile","Colombia",
                       "Ecuador","Paraguay","Peru",
                       "Bolivia (Plurinational State of)","Brazil","Chile","Colombia","Ecuador",
                       "Paraguay","Peru","Bolivia (Plurinational State of)",
                       "Brazil","Chile","Colombia","Ecuador","Paraguay","Peru",
                       "Bolivia (Plurinational State of)","Brazil","Chile",
                       "Colombia","Ecuador","Paraguay","Peru","Brazil","Chile",
                       "Colombia","Ecuador","Paraguay","Peru",
                       "Bolivia (Plurinational State of)","Brazil","Chile","Colombia",
                       "Ecuador","Paraguay","Peru",
                       "Bolivia (Plurinational State of)","Brazil","Chile","Colombia","Ecuador",
                       "Paraguay","Peru","Bolivia (Plurinational State of)","Brazil",
                       "Chile","Colombia","Ecuador","Paraguay","Peru"),
           Partner = c("Australia","Australia",
                       "Australia","Australia","Australia","Canada","Canada",
                       "Canada","Canada","Canada","China","China","China",
                       "China","China","France","France","France","France",
                       "France","Germany","Germany","Germany","Germany",
                       "Germany","India","India","India","India","India",
                       "Indonesia","Indonesia","Indonesia","Indonesia","Indonesia",
                       "Italy","Italy","Italy","Italy","Italy","Japan",
                       "Japan","Japan","Japan","Japan","Mexico","Mexico",
                       "Mexico","Mexico","Mexico","Rep. of Korea",
                       "Rep. of Korea","Rep. of Korea","Rep. of Korea","Rep. of Korea",
                       "Turkey","Turkey","Turkey","Turkey","Turkey",
                       "United Kingdom","United Kingdom","United Kingdom",
                       "United Kingdom","United Kingdom","USA","USA","USA","USA",
                       "USA","World","World","World","World","World",
                       "Australia","Australia","Australia","Australia","Australia",
                       "Australia","Canada","Canada","Canada","Canada",
                       "Canada","Canada","Canada","China","China","China",
                       "China","China","China","France","France","France",
                       "France","France","France","France","Germany","Germany",
                       "Germany","Germany","Germany","Germany","Germany",
                       "India","India","India","India","India","India",
                       "Indonesia","Indonesia","Indonesia","Indonesia",
                       "Indonesia","Indonesia","Indonesia","Italy","Italy","Italy",
                       "Italy","Italy","Italy","Italy","Japan","Japan",
                       "Japan","Japan","Japan","Japan","Japan","Mexico",
                       "Mexico","Mexico","Mexico","Mexico","Mexico","Mexico",
                       "Rep. of Korea","Rep. of Korea","Rep. of Korea",
                       "Rep. of Korea","Rep. of Korea","Rep. of Korea","Rep. of Korea",
                       "Russian Federation","Russian Federation",
                       "Russian Federation","Russian Federation","Russian Federation",
                       "Russian Federation","Russian Federation","Turkey",
                       "Turkey","Turkey","Turkey","Turkey","Turkey",
                       "United Kingdom","United Kingdom","United Kingdom",
                       "United Kingdom","United Kingdom","United Kingdom","United Kingdom",
                       "USA","USA","USA","USA","USA","USA","USA","World",
                       "World","World","World","World","World","World"),
        TradeValue = c(218912768,27441404,6225037,
                       1707259,19750,464262208,54218664,80623096,3863359,
                       83675,226395312,80425792,17249908,38649,3613293,
                       864403904,388162560,174076960,26088384,11224829,
                       2157795072,715506624,547410304,136968800,36220492,165651680,
                       8043120,1433446,5712,21627,198796464,29507986,
                       4444402,473919,2847511,1352686848,339006144,110004128,
                       59227224,39323916,2557230080,1677971072,231723664,
                       62739576,3810567,757917248,44211744,55279904,18738534,
                       1025552,672131776,270350464,17244088,296872448,
                       8018309,147786880,17739464,350431,3510437,105672,
                       1056959232,558879680,189760976,11399010,3802803,6387453440,
                       1387587072,2823803136,1402672640,35005528,31621120000,
                       8960062464,7268634624,2851399168,737040576,99388,
                       206919888,23384686,7786584,1334356,13851797,3343210,
                       401470240,62851868,55501984,3801285,790413,111656400,
                       16430,460024576,221297344,3507554,776396,251797408,
                       32243824,844323456,380851936,128588496,33135612,
                       14062889,68804600,31681680,2073711232,609494016,
                       592327936,107913240,20328764,147660208,695350,148693040,
                       1560390,181986,188572,1820345,297072,136855792,
                       45968904,240673,195450,2215903,257624,1955013,1597161472,
                       376975200,127655384,93458240,22486636,193796240,
                       1628093,2311336192,1714072448,197430480,62416536,
                       2449286,291650816,6630893,1113647104,90115840,69851224,
                       33132368,1601389,96924528,328158,571327040,242961680,
                       13110620,347820480,2633642,58812932,122988,
                       126059496,34904880,6627143,6728042,202759,5252825,216010688,
                       18605626,307684,6632587,1230180,3263960,127588432,
                       1286679680,619276736,186427696,15229376,5336958,
                       218111472,153707584,7081407488,1581919616,2722496768,
                       1421556608,34994072,705768960,765313792,35975315456,
                       9913288704,6916042752,3042286848,656554304,3359371520)
)

I appreciate your help!

2

Something like this?

library(dplyr)
df %>% 
  group_by(Year, Partner) %>% 
  summarise(TradeValue = sum(TradeValue)) %>% 
  ungroup() %>% 
  mutate(Reporter = "South America") %>% 
  relocate(Reporter, .after = Year)

# A tibble: 31 × 4
    Year Reporter      Partner   TradeValue
   <dbl> <chr>         <chr>          <dbl>
 1  1991 South America Australia  254306218
 2  1991 South America Canada     603051002
 3  1991 South America China      327722954
 4  1991 South America France    1463956637
 5  1991 South America Germany   3593901292
 6  1991 South America India      175155585
 7  1991 South America Indonesia  236070282
 8  1991 South America Italy     1900248260
 9  1991 South America Japan     4533474959
10  1991 South America Mexico     877172982
# … with 21 more rows
1 Like
3

Precisely that! Thank you so much

1 Like
4

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