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Pretty correlation matrices with ggplot

DATE: 2020-07-05

AUTHOR: John L. Godlee

I needed to make a correlation matrix plot to show the relationships between all variables in a structural equation model I was writing. I created a function which takes a dataframe of numeric variables and returns a ggplot2 object.

#' Create a pretty correlation matrix plot
#'
#' @param x dataframe of numeric variables to correlate
#'
#' @return ggplot object with correlogram
#' 
#' @examples
#' data(iris)
#' corrplot(iris[,1:4])
#' 
#' @import ggplot2 
#' @importFrom psych corr.test
#'
corrplot <- function(x, col = c("red", "white", "blue"), ...) {
  corr <- psych::corr.test(x, ...) 
  corr_ci <- data.frame(raw.lower = corr$ci$lower, raw.r = corr$ci$r, 
    raw.upper = corr$ci$upper, raw.p = corr$ci$p, 
    adj.lower = corr$ci.adj$lower.adj, adj.upper = corr$ci.adj$upper.adj)
  corr_ci$vars <- row.names(corr_ci)
  corr_ci$conf_x <- unlist(sapply(1:(length(x)-1), function(i){
      c(1:(length(x)-1))[i:(length(x)-1)]
    })) + 1
  rev_mat <- (length(x)-1):1
  corr_ci$conf_y <- unlist(sapply(1:(length(x)-1), function(i){
      rep(i, times = rev_mat[i])
    }))
  n_seq <- 2:length(x)
  corr_ci$y_var <- unlist(sapply(1:(length(x)-1), function(i){
      rep(row.names(corr[[1]])[i], rev_mat[i])
    }))
  corr_ci$x_var <- unlist(sapply(1:(length(x)-1), function(i){
      row.names(corr[[1]])[n_seq[i]:length(x)]
    }))
  corr_ci$x_var <- factor(corr_ci$x_var, levels = unique(corr_ci$x_var))
  corr_ci$y_var <- factor(corr_ci$y_var, levels = unique(corr_ci$y_var))
  corr_ci$conf <- (corr_ci$raw.lower > 0) == (corr_ci$raw.upper > 0)
  corr_ci$raw.r <- round(corr_ci$raw.r, 2)

  ggplot2::ggplot() + 
    ggplot2::geom_tile(data = corr_ci, 
      ggplot2::aes(x = x_var, y = y_var, 
        fill = raw.r), colour = "black") + 
    ggplot2::geom_text(data = corr_ci, 
      ggplot2::aes(x = x_var, y = y_var, label = raw.r),
      size = 3) + 
    ggplot2::geom_point(data = corr_ci[corr_ci$conf == FALSE,], 
      ggplot2::aes(x = x_var, y = y_var), 
      fill = NA, colour = "black", shape = 21, size = 11) + 
    ggplot2::scale_fill_gradient2(name = "r", 
      low = col[1], mid = col[2], high = col[3]) + 
    ggplot2::theme_classic() + 
    ggplot2::labs(x = "", y = "") + 
    ggplot2::coord_equal() +
    ggplot2::theme(legend.position = "none")
}

corrplot(iris[,1:4])

Correlation matrix plot

Here is the actual plot I made for the publication, which additionally colours the axis text to group variables into latent constructs:

Correlation matrix plot for publication