corrgram

Homepage: https://kwstat.github.io/corrgram

Repository: https://github.com/kwstat/corrgram

The corrgram package provides a simple way to create correlograms from raw data or a correlation matrix.

Package overview

The corrgram package provides functions for creating corrgrams using three different graphics systems, base, grid, and lattice.

Base R graphics

• single function corrgram() for dataframes or matrices.
• Enables most features found in the paper by @friendly2002corrgrams.

• No automatic legend.
• Not easily combined with other graphics.

lattice graphics

• Separate panel functions for lattice::levelplot() for dataframes and lattice::splom() for correlation matrices.
• Enables automatic legend.
• Enables corrgrams conditioned on other variables.
• Can be combined with other lattice graphics for complex figures.

• Not feature complete compared to base R.

grid graphics

• single function corrgram2() for either dataframes or correlation matrices.
• Enables automatic legend.
• Can be combined with other grid graphics for complex figures.

• Not feature complete compared to base R.

• Faster than base R when evaluated inside Positron.

Installation

# Install the released version from CRAN:
install.packages("corrgram")

# Install the development version from GitHub:
install.packages("devtools")
# devtools::install_github("kwstat/corrgram")
install.packages("corrgram", repos = c('https://kwstat.r-universe.dev', 'https://cloud.r-project.org'))

Usage for base R

require(corrgram)
# Base R
corrgram(mtcars, order=TRUE, lower.panel=panel.shade, upper.panel=panel.pie,
         text.panel=panel.txt, main="mtcars")

Usage for grid version

# grid
vars6 <- setdiff(colnames(auto), c("Model", "Origin"))
corrgram2(auto[, vars6], 
          lower.panel = grid_panel.shade, upper.panel=grid_panel.pie,
          title = "auto data", legend = TRUE)

Usage for lattice version

library(lattice)
pengvars <- c("bill_len", "bill_dep", "flipper_len", "body_mass")
splom(~penguins[ , pengvars]|penguins$species, upper.panel=splom_panel.pie, 
      pscales=0, main="penguins data in lattice")