Created
October 31, 2022 21:53
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Correlation Mat's and their p-vals by group
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# 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') |
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