I have a tibble df of the form
Province/State Country/Region Lat Long `1/22/20` `1/23/20` `1/24/20` `1/25/20`
1 NA Afghanistan 33 65 0 0 0 0
2 NA Albania 41.2 20.2 0 0 0 0
3 NA Algeria 28.0 1.66 0 0 0 0
4 NA Andorra 42.5 1.52 0 0 0 0
5 NA Angola -11.2 17.9 0 0 0 0
6 NA Antigua and Bar… 17.1 -61.8 0 0 0 0
7 NA Argentina -38.4 -63.6 0 0 0 0
8 NA Armenia 40.1 45.0 0 0 0 0
9 Australian Capi… Australia -35.5 149. 5 0 0 0
10 New South Wales Australia -33.9 151. 6 0 0 0
and I would like to get the total number for each date column for every country like:
Country/Region `1/22/20` `1/23/20` `1/24/20` `1/25/20`
Afghanistan 0 0 0 0
Albania 0 0 0 0
Algeria 0 0 0 0
Andorra 0 0 0 0
Angola 0 0 0 0
Antigua and Bar… 0 0 0 0
Argentina 0 0 0 0
Armenia 0 0 0 0
Australia 11 0 0 0
It seems that I would just have to write:
df %>%
select(-"Province/State", -"Lat" , -"Long") %>%
group_by("Country/Region") %>%
summarise(sum)
but R keeps throwing the error: Error: Column sum is of unsupported type function;
in fact, it does not work for any function.
If instead I use summarise_all, I get: Error in .Primitive("sum")(Country/Region) :
invalid 'type' (character) of argument, which is understandable since "Country/Region" is
column of characters.
What am I doing wrong? How can I perform this simple computation?
