ggally

library(GGally)

## Loading required package: ggplot2

library(ggplot2)
library(wooldridge)
ggcorr(wage1[1:7],palette = "RdBu")

p<-ggpairs(wage1[1:3],aes(color=factor(wage1$female)))+ theme_bw()
for(i in 1:p$nrow) {
  for(j in 1:p$ncol){
    p[i,j] <- p[i,j] + 
      scale_fill_manual(values=c("#00AFBB", "#E7B800", "#FC4E07")) +
      scale_color_manual(values=c("#00AFBB", "#E7B800", "#FC4E07"))  
  }
}
p

p <- ggpairs(iris, aes(color = Species))+ theme_bw()
for(i in 1:p$nrow) {
  for(j in 1:p$ncol){
    p[i,j] <- p[i,j] + 
      scale_fill_manual(values=c("#00AFBB", "#E7B800", "#FC4E07")) +
      scale_color_manual(values=c("#00AFBB", "#E7B800", "#FC4E07"))  
  }
}
p

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

data("iris")
dim(iris)

## [1] 150   5