R Tidy correlogram by group

Question

I would like to use a tidy approach to produce correlograms by group. My attempt with iris and libraries dplyr and corrplot :

library(corrplot)
library(dplyr)

par(mfrow=c(2,2))
iris %>%
  group_by(Species) %>%
  group_map(~ corrplot::corrplot(cor(.x,use = "complete.obs"),tl.cex=0.7,title =""))

It works but I would like to add the Species name on each plot. Also, any other tidy approaches/ functions are very welcome!

Answer 1

We could use cur_group()

library(dplyr)
library(corrplot)
out <- iris %>% 
      group_by(Species) %>%
       summarise(outr = list( corrplot::corrplot(cor(cur_data(),
            use = "complete.obs"),tl.cex=0.7,title = cur_group()[[1]])))

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Or if we are using group_map , the .keep = FALSE by default. Specify it as TRUE and extract the group element

iris %>%
  group_by(Species) %>%
  group_map(~ corrplot::corrplot(cor(select(.x, where(is.numeric)),
      use = "complete.obs"),tl.cex=0.7,title = first(.x$Species)), .keep = TRUE)

Answer 2

You can use split and map approach with imap -

library(dplyr)
library(purrr)

iris %>%
  split(.$Species) %>%
  imap(~corrplot::corrplot(cor(.x[-5],use ="complete.obs"),tl.cex=0.7,title =.y))