Calculate the summary of selected columns in dplyr

Question

I have a df which contains names of countries number of cases(covid) and number of population by countries. So i want to sum up the number of cases. The problem is that in every row there are the population numbers which is the same in every row so they should not be summed up. So how can i summarise only the cases column.

cases_names_pop <- cases_names_pop %>%  group_by(countriesAndTerritories) %>% summarise_all((sum))

Here is my used data:

structure(list(countriesAndTerritories = c("Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", 
"Afghanistan", "Afghanistan", "Afghanistan"), cases = c(272L, 
0L, 228L, 214L, 0L, 200L, 185L, 246L, 252L, 154L, 232L, 282L, 
0L, 383L, 65L, 163L, 205L, 66L, 360L, 146L, 0L, 224L, 80L, 126L, 
58L, 40L, 121L, 86L, 95L, 132L, 76L, 157L, 123L, 0L, 113L, 199L, 
65L, 81L, 61L, 116L, 135L, 88L, 87L, 59L, 68L, 47L, 0L, 32L, 
66L, 129L, 96L, 0L, 10L, 77L, 68L, 62L, 145L, 44L, 7L, 5L, 17L, 
14L, 15L, 12L, 0L, 35L, 6L, 16L, 25L, 71L, 30L, 0L, 125L, 47L, 
0L, 17L, 40L, 99L, 75L, 35L, 34L, 28L, 24L, 26L, 96L, 74L, 20L, 
16L, 45L, 38L, 9L, 34L, 19L, 3L, 11L, 3L, 55L, 1L, 71L, 0L), 
    popData2019 = c(38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 
    38041757L, 38041757L, 38041757L, 38041757L, 38041757L, 38041757L
    )), row.names = c(NA, 100L), class = "data.frame")

Thank you for your help in advance!

Please use `dput(head(cases_names_pop,100))` and paste the output along with your question, otherwise you will get weird answers without adressing your issue! — Duck, Dec 12 '20 at 18:07
Is this what you are looking for `df %>% group_by(countriesAndTerritories) %>% summarise(total=sum(cases), population=mean(popData2019))` ? — Matias Andina, Dec 12 '20 at 18:47

Calculate the summary of selected columns in dplyr

0 Answers0