15 Chart: Mosaic

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15.1 Overview

This section covers how to make Mosaic plots

15.2 tl;dr

library(vcd)
mosaic(Favorite ~ Age + Music, 
       labeling = labeling_border(
         abbreviate_labs = c(3, 10, 6),
         rot_labels=c(0,0,-45)
       ),
       direction=c('v','v','h'), # Age = Vertical, Music = Vertical, Favoriate = Horizonal (a.k.a DoubleDecker)
       gp = gpar(fill=c('lightblue', 'gray')),
       df)

15.3 Simple Example Walkthrough

15.3.1 Order of splits

It is best to draw mosaic plots incrementally: start with splitting on one variable and then add additional variables one at a time. The full mosaic plot will have one split per variable.

Important: if your data is in a data frame (see above), the count column must be called Freq.

Split on Age only:

library(vcd)
mosaic(~Age, df)

Split on Age, then Music:

mosaic(Music ~ Age, df)

Note that the first split is between “young” and “old”, while the second set of splits divides each age group into “classical” and “rock”.

Split on Age, then Music, then Favorite:

mosaic(Favorite ~ Age + Music, df)

15.3.2 Direction of splits

Note that in the previous example, the direction of the splits is as follows:

  1. Age – horizontal split

  2. Music – vertical split

  3. Favorite – horizontal split

This is the default direction pattern: alternating directions beginning with horizontal. Therefore we get the same plot with the following:

mosaic(Favorite ~ Age + Music, 
       direction = c("h", "v", "h"), df)

The directions can be altered as desired. For example, to create a doubledecker plot, make all splits vertical except the last one:

mosaic(Favorite ~ Age + Music,
       direction = c("v", "v", "h"), df)

Note that the direction vector is in order of splits (Age, Music, Favorite), not in the order in which the variables appear in the formula, where the last variable to be split is listed first, before the “~”.

15.3.3 Options

15.3.3.1 Fill color:

library(grid) # needed for gpar
mosaic(Favorite ~ Age + Music, 
       gp = gpar(fill = c("lightblue", "blue")),
       df)

15.3.3.2 Rotate labels:

mosaic(Favorite ~ Age + Music, 
       labeling = labeling_border(rot_labels = c(45, -45, 0, 0)),
       df)

The rot_labels = vector sets the rotation in degrees on the four sides of the plot in this order: top, right, bottom, left. (Different from the typical base graphics order!) The default is rot_labels = c(0, 90, 0, 90).

15.3.3.3 Abbreviate labels:

mosaic(Favorite ~ Age + Music, 
       labeling = labeling_border(abbreviate_labs = c(3, 1, 6)), 
       df)

Labels are abbreviated in the order of the splits (as for direction =). The abbreviation algorithm appears to return the specified number of characters after vowels are eliminated (if necessary).

For more formatting options, see >?vcd::labeling_border.

15.3.3.4 Remove spacing between cells

mosaic(Favorite ~ Age + Music,
       spacing = spacing_equal(sp = unit(0, "lines")),
       df)

For more details, see >?vcd::spacings

15.3.3.5 Change border color (must also set fill(?))

mosaic(Favorite ~ Age + Music,
       gp = gpar(fill = c("lightblue", "blue"),
                 col = "white"),
       spacing = spacing_equal(sp = unit(0, "lines")),
       df)

15.4 Mosaic using base R

library(vcdExtra)
mosaicplot(xtabs(count ~ lake + sex, data=Alligator), main="")

mosaicplot(xtabs(Freq ~ Favorite + Age + Music, data=df), main="",
           dir=c('h', 'v', 'v'))

15.4.1 Mosaic using vcd::doubledecker

data(Arthritis)
vcd::doubledecker(Improved ~ Treatment + Sex, data=Arthritis)

vcd::doubledecker(Music ~ Favorite + Age, 
                  xtabs(Freq ~ Age + Music + Favorite, df))

15.5 Mosaic using ggplot

For a comprehensive overview of mosaic plot in ggplot check out the link below. https://cran.r-project.org/web/packages/ggmosaic/vignettes/ggmosaic.html

library(ggmosaic)

# equivalent to doing Favorite ~ Age + Music in vcd::mosaic with doubledecker style cut
ggplot(df) + 
  geom_mosaic(
    aes(x=product(Favorite, Age, Music), # cut from right to left 
        weight=Freq,
        fill=Favorite
        ),
    divider=c("vspine" , "hspine", "hspine") # equivalent to divider=ddecker()
  )

15.6 Theory

15.7 When to use

When you want to see the relationships in Multivariate Categorical Data

15.8 Considerations

15.8.1 Labels

Legibility of the labels is problematic in mosaic plot especially when there are a lot of dimensions. This can be alleviated by - Abbreviate names - Rotating the labels

15.8.2 Aspect Ratio

  • lengths are easier to judge than area, so try to use rectangles with same width or height
  • Taller thinner rectangles are better (we are better at distinguishing length than area)

15.8.3 Gaps between rectangles

  • No gap = most efficient

However, a gap can help improve legibility, so try out different combinations

  • Can have a gap at splits
  • Can Vary gap size down the hierarchy

15.8.4 Color

  • good for rates in the subgroup
  • displaying residual
  • emphasizing particular subgroup

15.9 External resources







with