Zoos with Great Pandas in their exhibitions, as pr. medio March ’19.
And Copenhagen Zoo, which will get their pandas in april.
Month: marts 2019
Propagandabjørne
Lige om lidt lander der pandabjørne i København. Danmark har fået lov at låne et par pandaer af Kina. Det fordrer normalt at vi efterfølgende ikke taler for højt om menneskerettigheder og den slags, og det hjalp sikkert også at den danske regering (eller i hvert fald politiet, helt på eget initiativ, og slet ikke efter opfordring fra nogen som helst, og i hvert fald ikke fra ministre der kunne tænkes at blive holdt politisk ansvarlige) viste sig villige til at se stort på Grundloven.
Anyway. Hvis man godt vil se pandabjørne, hvor kan man så gøre det? Hvilke zoos har pandaer? Om lidt kan man gøre det i København. Men der er også andre steder:
Dette er, pr. midten af marts 2019, de zoologiske haver, der har pandaer i deres samling. Og så Københavns Zoo, på forventet efterbevilling.
Corresponding value to a max-value
One of our users need to find the max-value of a variable. He also needs to find the corresponding value in another variable.
As in – the maximum value in column A is in row 42. What is the value in column B, row 42.
And of course we need to do it for several groups.
Let us begin by making a dataset. Four groups in id,
library(tidyverse)
id <- 1:3
val <- c(10,20)
kor <- c("a", "b", "c")
example <- expand.grid(id,val) %>%
as_tibble() %>%
arrange(Var1) %>%
cbind(kor, stringsAsFactors=F) %>%
rename(group=Var1, value=Var2, corr = kor)
example
## group value corr ## 1 1 10 a ## 2 1 20 b ## 3 2 10 c ## 4 2 20 a ## 5 3 10 b ## 6 3 20 c
We have six observations, divided into three groups. They all have a value, and a letter in “corr” that is the corresponding value we are interested in.
So. In group 1 we should find the maximum value 20, and the corresponding value “b”.
In group 2 the max value is stil 20, but the corresponding value we are looking for is “a”.
And in group 3 the max value is yet again 20, but the corresponding value is now “c”.
How to do that?
example %>%
group_by(group) %>%
mutate(max=max(value)) %>%
mutate(max_corr=corr[(value==max)]) %>%
ungroup()
## # A tibble: 6 x 5 ## group value corr max max_corr ## <int> <dbl> <chr> <dbl> <chr> ## 1 1 10. a 20. b ## 2 1 20. b 20. b ## 3 2 10. c 20. a ## 4 2 20. a 20. a ## 5 3 10. b 20. c ## 6 3 20. c 20. c
The maximum value for all groups is 20. And the corresponding value to that in the groups is b, a and c respectively.
Isn’t there an easier solution using summarise function? Probably. But our user needs to do this for a lot of variables. And their names have nothing in common.