PieGlyph: Creating scatter plots with points replaced with axis invariant pie-glyphs

Extends 'ggplot2' to help replace points in a scatter plot with pie-chart glyphs showing the relative proportions of different categories (presented as columns with non-negative values in the dataset). The pie glyphs are independent of the axes and plot dimensions to prevent distortions when the plot dimensions are changed.

Author

Maintainter: Rishabh Vishwakarma vishwakr@tcd.ie (ORCID)

Authors:

Caroline Brophy
Catherine Hurley

Examples

## Load libraries
library(dplyr)
library(tidyr)
library(PieGlyph)
library(ggplot2)

## Simulate raw data

set.seed(123)
plot_data <- data.frame(response = rnorm(30, 100, 30),
                        system = 1:30,
                        group = sample(size = 30,
                                       x = c('G1', 'G2', 'G3'),
                                       replace = TRUE),
                        A = round(runif(30, 3, 9), 2),
                        B = round(runif(30, 1, 5), 2),
                        C = round(runif(30, 3, 7), 2),
                        D = round(runif(30, 1, 9), 2))

head(plot_data)
#>    response system group    A    B    C    D
#> 1  83.18573      1    G1 5.80 1.57 4.78 8.31
#> 2  93.09468      2    G3 6.07 3.76 3.87 8.21
#> 3 146.76125      3    G1 6.60 3.48 5.01 3.19
#> 4 102.11525      4    G2 5.00 4.57 4.42 3.57
#> 5 103.87863      5    G1 5.93 3.69 5.60 8.89
#> 6 151.45195      6    G1 8.73 3.95 4.50 5.96

## The data has 30 observations and seven columns. `response` is a continuous
## variable measuring system output while `system` describes the 30
## individual systems of interest. Each system is placed in one of three
## groups shown in `group`. Columns `A`, `B`, `C`, and `D` measure system attributes.

## Basic plot showing the outputs for each system as a scatterplot and
## replacing the points with pie-chart glyphs showing the relative proportions
## of the four system attributes

ggplot(data = plot_data, aes(x = system, y = response))+
   geom_pie_glyph(slices = c('A', 'B', 'C', 'D'))+
   theme_minimal()



##### Stack the attributes in one column
## The four attributes can also be stacked and combined into one column
## to generate the plot.

plot_data_stacked <- plot_data %>%
                        pivot_longer(cols = c('A','B','C','D'),
                                     names_to = 'Attributes',
                                     values_to = 'values')

## This is the same data as before, just that the four attributes
## are combined into a single column, i.e. each system is now represented
## by four rows instead of the one row from before.

head(plot_data_stacked, 8)
#> # A tibble: 8 × 5
#>   response system group Attributes values
#>      <dbl>  <int> <chr> <chr>       <dbl>
#> 1     83.2      1 G1    A            5.8 
#> 2     83.2      1 G1    B            1.57
#> 3     83.2      1 G1    C            4.78
#> 4     83.2      1 G1    D            8.31
#> 5     93.1      2 G3    A            6.07
#> 6     93.1      2 G3    B            3.76
#> 7     93.1      2 G3    C            3.87
#> 8     93.1      2 G3    D            8.21
head(plot_data, 2)
#>   response system group    A    B    C    D
#> 1 83.18573      1    G1 5.80 1.57 4.78 8.31
#> 2 93.09468      2    G3 6.07 3.76 3.87 8.21

## This is the same plot as before showing a scatter plot of the different
## systems and their outputs with pie-chart glyphs showing the proportions
## of the different system attributes.

## This version of the function is useful for situation when the data is in
## tidy format. See vignette('tidy-data') and vignette('pivot') for more information.

ggplot(data = plot_data_stacked, aes(x = system, y = response))+
  # Along with slices column, values column is also needed now
  geom_pie_glyph(slices = 'Attributes', values = 'values')+
  theme_minimal()

PieGlyph: Creating scatter plots with points replaced with axis invariant pie-glyphs

See also

Author

Examples