Dear Jim,
Thanks a lot for your stellar replies!
They address my questions perfectly.
Cheers
Lorenzo
On Fri, Jan 25, 2019 at 07:46:50AM -0800, jim holtman wrote:
Try this for the second question:
years <- map2(zz,
+ list(c(2000, 2001), c(2001, 2003)),
+ ~ filter(
Try this for the second question:
> years <- map2(zz,
+ list(c(2000, 2001), c(2001, 2003)),
+ ~ filter(.x, year %in% .y)
+ )
> years
[[1]]
# A tibble: 6 x 4
year tot_i relation g_rate
1 2000 22393349. EU28-Algeria 0.736
2
Does this answer the first question?
> rel <- map(zz, function(x){
+ group_by(x, relation) %>% summarise(tot = mean(tot_i))
+ })
> rel
[[1]]
# A tibble: 3 x 2
relation tot
1 EU28-Algeria 22186767.
2 Extra EU28-Algeria 12884156.
3 World-Algeria 35
Dear All,
I am making my baby steps with the tidyverse purr package and I am
stuck with some probably trivial tasks.
Consider the following data set
zz<-list(structure(list(year = c(2000, 2001, 2002, 2003, 2000, 2001,
2002, 2003, 2000, 2001, 2002, 2003), tot_i = c(22393349.081,
23000574.372, 2
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