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ggEDA

ggEDA streamlines exploratory data analysis by providing turnkey approaches to visualising n-dimensional data which can graphically reveal correlative or associative relationships between two or more features:

• ggstack: tiled one-dimensional visualisations that more effectively show missingness and complex categorical relationships in smaller datasets.
• ggparallel: parallel coordinate plots (PCPs) for examining large datasets with mostly quantitative features.

Installation

install.packages("ggEDA")

Development Version

You can install the development version of ggEDA from GitHub with:

if (!require("remotes"))
    install.packages("remotes")

remotes::install_github("CCICB/ggEDA")

Or from R-universe with:

install.packages("ggEDA", repos = "https://ropensci.r-universe.dev")

Quick Start

For examples of interactive EDA plots see the ggEDA gallery

# Load library
library(ggEDA)

# Plot data, sort by Glasses
ggstack(
  baseballfans,
  col_id = "ID",
  col_sort = "Glasses",
  interactive = FALSE,
  verbose = FALSE,
  options = ggstack_options(legend_nrow = 2)
)

Customise Colours

Customise colours by supplying a named list to the palettes argument

ggstack(
  baseballfans,
  col_id = "ID",
  col_sort = "Glasses",
  palettes = list("EyeColour" = c(
    Brown = "rosybrown4",
    Blue = "steelblue",
    Green = "seagreen"
  )),
  interactive = FALSE,
  verbose = FALSE,
  options = ggstack_options(legend_nrow = 2)
)

Parallel Coordinate Plots

For datasets with many observations and mostly numeric features, parallel coordinate plots may be more appropriate.

ggparallel(
 data = minibeans,
 col_colour = "Class",
 order_columns_by = "auto",
 interactive = FALSE
)
#> ℹ Ordering columns based on mutual information with [Class]

 ggparallel(
   data = minibeans,
   col_colour = "Class",
   highlight = "DERMASON",
   order_columns_by = "auto",
   interactive = FALSE
 )
#> ℹ Ordering columns based on how well they differentiate 1 group from the rest [DERMASON] (based on mutual information)

 ggparallel(
   data = minibeans,
   order_columns_by = "auto",
   interactive = FALSE
 )
#> ℹ To add colour to plot set `col_colour` to one of: Class
#> ℹ Ordering columns to minimise crossings
#> ℹ Choosing axis order via repetitive nearest neighbour with two-opt refinement

Community Contributions

All types of contributions are encouraged and valued. See our guide to community contributions for different ways to help.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.