Correlation Mat's and their p-vals by group

CorMatbyGroup.R

# No need to call Bill Gates! 
# here is how you get correlation tables by group with their p-val matries and even plot them
library(Hmisc); library(tidyverse); library(corrplot)

result <- iris |> # base R pipe
  #select() # remove col's you don't want in the correlation matrix
  group_by(Species) |> # grouping col
  group_map(~rcorr(as.matrix(.))) |>
  setNames(unique(sort(iris$Species)))

# rcorr(as.matrix(iris[iris$Species == "virginica",1:4])) #checking that the naming of lists worked

## Let's make some plots!
setosa_plt <- corrplot(result$setosa$r, p.mat = result$setosa$P, method = 'color', diag = FALSE, type = 'upper',
         sig.level = c(0.001, 0.01, 0.05), pch.cex = 0.9, tl.col = "black",
         insig = 'label_sig', pch.col = 'grey20', order = 'AOE')

virginica_plt <- corrplot(result$virginica$r, p.mat = result$virginica$P, method = 'color', diag = FALSE, type = 'upper',
                       sig.level = c(0.001, 0.01, 0.05), pch.cex = 0.9, tl.col = "black",
                       insig = 'label_sig', pch.col = 'grey20', order = 'AOE')

versicolor_plt <- corrplot(result$versicolor$r, p.mat = result$versicolor$P, method = 'color', diag = FALSE, type = 'upper',
                       sig.level = c(0.001, 0.01, 0.05), pch.cex = 0.9, tl.col = "black",
                       insig = 'label_sig', pch.col = 'grey20', order = 'AOE')