Themes and Arranging Plots

Data Visualization and Exploration

Ozan Kahramanoğulları

Themes

The theme system

Themes control the appearance of non-data elements.

They don’t affect:

  • how the data is rendered by geoms.

  • how the data is transformed by scales.

library(tidyverse)

Themes provide control over:

  • The title appearance
  • The axis labels
  • The axis tick labels
  • The strips
  • The legends and legend key labels
  • The background color
  • …

Themes

Built-in themes are available via ggplot2 or other packages.

You can further customize any theme.

GGplot themes

  • theme_gray() (default)

  • theme_bw()

  • theme_linedraw()

  • theme_light()

  • theme_dark()

  • theme_minimal()

  • theme_classic()

  • theme_void()

A tour of built-in themes

mtcars
                     mpg cyl  disp  hp drat    wt  qsec vs am gear carb
Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4
Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4
Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1
Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1
Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1
Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2
Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2
Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4
Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4
Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1
Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2
Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1
Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1
Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1
Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2
Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2
Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6
Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8
Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3)

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))
             ) # + theme_gray()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_gray()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_bw()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_linedraw()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_light()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_dark()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_minimal()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_classic()

A tour of built-in themes

ggplot(data = mtcars,
       mapping = aes(x=wt, 
                     y=mpg, 
                     color=factor(cyl))) +
  geom_point(size=3) + 
  facet_grid(cols=vars(factor(cyl))) + 
  theme_void()

Customizing Themes

Theme components

To customize an individual theme

plot + theme(element.name = element_function())

element.name

  • Plot

  • Axis

  • Legend

  • Panel

  • Facet

element_function()

  • Text: element_text()

  • Lines: element_line()

  • Rectangles: element_rect()

  • Nothing: element_blank()

  • Units: e.g. unit(1, "cm")

  • Margins: margin()

Theme components

To customize an individual theme

plot + theme(element.name = element_function())

Examples:

plot + theme(axis.title = element_text(color="red"))

plot + theme(panel.background = element_blank())

plot + theme(legend.key = element_rect(fill="blue"))

Element functions

Element functions:

element_text()

  • (font) family

  • (font) face

  • (font) color

  • (font) size (in points)

  • hjust [0..1] (0=left,1=right)

  • vjust [0..1] (0=bottom,1=top)

  • angle (in degrees)

  • lineheight (as a ratio of the fontcase)

  • margin(t,r,b,l)

Element functions:

element_text()

df <- data.frame(x=1:5,y=1:5)
p <- ggplot(df,aes(x,y)) + 
  geom_point() + 
  labs(title="This is a title")

Element functions:

element_text()

p

Element functions:

element_text()

p + theme(plot.title = element_text(family="Times",face="bold",size=20,
              color="#008080",hjust=0.5))

Element functions:

element_text()

p + theme(plot.title = element_text(family="Times",face="bold",size=20,
              color="#008080",hjust=0.5,margin=margin(0,0,20,0)))

Element functions:

element_line()

  • colour

  • size (thickness)

  • linetype an integer (0:8), a name (blank, solid, dashed,dotted,dotdash,longdash,twodash)

  • lineend (round,butt,square)

  • arrow

Element functions:

element_line()

p

Element functions:

element_line()

p + theme(axis.line = element_line(color="red",size=2))

Element functions:

element_line()

p + theme(axis.line = element_line(color="red",size=3,lineend="round"))

Element functions:

element_line()

p + theme(axis.line = element_line(color="red",size=3,lineend="round",arrow=arrow()))

Element functions:

element_rect()

  • fill

  • colour

  • fill

  • size

  • linetype an integer(0:8), a name(blank, solid, dashed,dotted,dotdash,longdash,twodash)

Element functions:

element_rect()

p

Element functions:

element_rect()

p + theme(panel.background = element_rect(color = "orange",size=3,fill="#00ced1"))

Element functions:

element_blank()

  • Draws nothing

  • Does not allocate space for that element

  • Does not receive parameters

Element functions:

element_blank()

p

Element functions:

element_blank()

p + theme(panel.grid = element_blank())

Element functions:

element_blank()

p + theme(panel.grid = element_blank(),panel.background = element_blank())

Element functions:

element_blank()

p + theme(panel.grid = element_blank(),panel.background = element_blank(),axis.ticks = element_blank())

Theme components

Theme components

To customize an individual theme

plot + theme(element.name = element_function())

element.name

  • Plot

  • Axis

  • Legend

  • Panel

  • Facet

element_function()

  • Text: element_text()

  • Lines: element_line()

  • Rectangles: element_rect()

  • Nothing: element_blank()

  • Units: e.g. unit(1, "cm")

  • Margins: margin()

Theme elements

Plot elements

  • plot.background

  • plot.title

  • plot.title.position

  • plot.caption

  • plot.caption.position

  • plot.tag

  • plot.tag.position

  • plot.margin

ggplot(df,aes(x,y)) + 
  geom_point() + 
  labs(title="This is a title",
       subtitle="This is a subtitle",
       tag= "(a)",
       caption = "This is a caption") +
  theme(plot.background = element_rect(fill="#AFEEEE"),
          plot.tag.position = "topleft",
          plot.margin=margin(0,10,0,0))

Theme elements

Axis elements

  • axis.title

  • axis.title.x

  • axis.title.x.top

  • axis.title.x.bottom

  • axis.title.y

  • axis.title.y.left

  • axis.title.y.right

  • axis.text

  • axis.text.x

  • axis.text.x.top

  • axis.text.x.bottom

  • axis.text.y

  • axis.text.y.left

  • axis.text.y.right

  • axis.ticks

  • axis.ticks.x

  • axis.ticks.x.top

  • axis.ticks.x.bottom

  • axis.ticks.y

  • axis.ticks.y.left

  • axis.ticks.y.right

  • axis.ticks.length

  • axis.ticks.length.x

  • axis.ticks.length.x.top

  • axis.ticks.length.x.bottom

  • axis.ticks.length.y

  • axis.ticks.length.y.left

  • axis.ticks.length.y.right

  • axis.line

  • axis.line.x

  • axis.line.x.top

  • axis.line.x.bottom

  • axis.line.y

  • axis.line.y.top

  • axis.line.y.bottom

Theme elements

Axis elements

ggplot(df,aes(x,y)) + 
  geom_point() +
  theme(axis.ticks = element_line(size=2,color="red"),
        axis.ticks.length = unit(.25, "cm"),
        axis.text=element_text(colour = "blue",size=20, angle = 45),
        axis.title = element_text(colour="#045c54",size=25),
        axis.line = element_line(size=4,colour="darkgrey"))

Theme elements

Panel elements

  • panel.background

  • panel.border

  • panel.grid

  • panel.grid.major

  • panel.grid.minor

  • panel.grid.major.x

  • panel.grid.major.y

  • panel.grid.minor.x

  • panel.grid.minor.y

ggplot(df,aes(x,y)) + 
  geom_point() + 
  theme(panel.background = element_rect(fill="#AFEEEE"),
        panel.grid.major=element_line(size=2,color="grey"),
        panel.grid.minor=element_line(size=1,color="black"),
        panel.border = element_rect(colour = "red", 
                                    fill=NA, 
                                    size=5))

Theme elements

Legend elements

  • legend.background

  • legend.margin

  • legend.spacing

  • legend.spacing.x

  • legend.spacing.y

  • legend.key

  • legend.key.size

  • legend.key.height

  • legend.key.width

  • legend.text

  • legend.text.align

  • legend.title

  • legend.position

  • legend.direction

  • legend.justification

  • legend.box

  • legend.box.just

  • legend.box.margin

  • legend.box.background

  • legend.spacing

ggplot(df,aes(x,y,color=factor(x))) + 
  geom_point(size=10) + 
  theme(legend.key=element_rect(colour = "red",fill="blue"),
        legend.background = element_rect(fill="darkolivegreen4"),
        legend.margin = margin(5,5,5,40),
        legend.text=element_text(size=20),
        legend.title = element_text(family="Times",hjust = 1),
        legend.position = "top")

Facet elements

Panel elements

  • panel.background

  • panel.background.x

  • panel.background.y

  • panel.placement

  • strip.text

  • strip.text.x

  • strip.text.y

  • strip.switch.pad.grid

  • strip.switch.pad.wrap

  • panel.spacing

  • panel.spacing.x

  • panel.spacing.y

df <-  data.frame(x=1:5,y=1:5,z=c(0,0,0,1,1))
ggplot(df,aes(x,y)) + 
  geom_point() + 
  facet_grid(cols=vars(factor(z))) + 
  theme(panel.spacing = unit(2,"cm"),
        strip.background = element_rect(fill="darkolivegreen",color="red"),
        strip.text = element_text(color="white",size=12))

Creating your own custom theme

p <- ggplot(data = mtcars, 
       mapping = aes(x=mpg,
                     y=hp,
                     color=factor(cyl))) +
  geom_point(size=3) + 
  scale_colour_brewer(type="qual",
                      palette=7, 
                      name = "Number of cylinders") + 
  labs(title = "Fuel consumption", x = "Miles per gallon", y = "Horse power")
p

Creating your own custom theme

p + theme_light(base_size=10, base_family = "Courier") +
  theme(panel.border = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.ticks = element_blank(),
        legend.position = "top",
        axis.title.x = element_text(margin=margin(t=10)),
        axis.title.y = element_text(margin=margin(r=10)),
        legend.text=element_text(margin=margin(0,10,0,0)),
        plot.title = element_text(face="bold"))

Creating your own custom theme

my_theme <- function(){
  theme_light(base_size=10, base_family = "Courier") +
  theme(panel.border = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.ticks = element_blank(),
        legend.position = "top",
        axis.title.x = element_text(margin=margin(t=10)),
        axis.title.y = element_text(margin=margin(r=10)),
        legend.text=element_text(margin=margin(0,10,0,0)),
        plot.title = element_text(face="bold")) 
  }

Creating your own custom theme

p + my_theme()

Arranging Plots

Arranging plots in a grid

The essentials.

library(ggthemes)

Then, install the cowplot library.

install.packages('cowplot')
library(cowplot)
theme_set(theme_cowplot())

Arranging plots in a grid

iris
    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species
1            5.1         3.5          1.4         0.2     setosa
2            4.9         3.0          1.4         0.2     setosa
3            4.7         3.2          1.3         0.2     setosa
4            4.6         3.1          1.5         0.2     setosa
5            5.0         3.6          1.4         0.2     setosa
6            5.4         3.9          1.7         0.4     setosa
7            4.6         3.4          1.4         0.3     setosa
8            5.0         3.4          1.5         0.2     setosa
9            4.4         2.9          1.4         0.2     setosa
10           4.9         3.1          1.5         0.1     setosa
11           5.4         3.7          1.5         0.2     setosa
12           4.8         3.4          1.6         0.2     setosa
13           4.8         3.0          1.4         0.1     setosa
14           4.3         3.0          1.1         0.1     setosa
15           5.8         4.0          1.2         0.2     setosa
16           5.7         4.4          1.5         0.4     setosa
17           5.4         3.9          1.3         0.4     setosa
18           5.1         3.5          1.4         0.3     setosa
19           5.7         3.8          1.7         0.3     setosa
20           5.1         3.8          1.5         0.3     setosa
21           5.4         3.4          1.7         0.2     setosa
22           5.1         3.7          1.5         0.4     setosa
23           4.6         3.6          1.0         0.2     setosa
24           5.1         3.3          1.7         0.5     setosa
25           4.8         3.4          1.9         0.2     setosa
26           5.0         3.0          1.6         0.2     setosa
27           5.0         3.4          1.6         0.4     setosa
28           5.2         3.5          1.5         0.2     setosa
29           5.2         3.4          1.4         0.2     setosa
30           4.7         3.2          1.6         0.2     setosa
31           4.8         3.1          1.6         0.2     setosa
32           5.4         3.4          1.5         0.4     setosa
33           5.2         4.1          1.5         0.1     setosa
34           5.5         4.2          1.4         0.2     setosa
35           4.9         3.1          1.5         0.2     setosa
36           5.0         3.2          1.2         0.2     setosa
37           5.5         3.5          1.3         0.2     setosa
38           4.9         3.6          1.4         0.1     setosa
39           4.4         3.0          1.3         0.2     setosa
40           5.1         3.4          1.5         0.2     setosa
41           5.0         3.5          1.3         0.3     setosa
42           4.5         2.3          1.3         0.3     setosa
43           4.4         3.2          1.3         0.2     setosa
44           5.0         3.5          1.6         0.6     setosa
45           5.1         3.8          1.9         0.4     setosa
46           4.8         3.0          1.4         0.3     setosa
47           5.1         3.8          1.6         0.2     setosa
48           4.6         3.2          1.4         0.2     setosa
49           5.3         3.7          1.5         0.2     setosa
50           5.0         3.3          1.4         0.2     setosa
51           7.0         3.2          4.7         1.4 versicolor
52           6.4         3.2          4.5         1.5 versicolor
53           6.9         3.1          4.9         1.5 versicolor
54           5.5         2.3          4.0         1.3 versicolor
55           6.5         2.8          4.6         1.5 versicolor
56           5.7         2.8          4.5         1.3 versicolor
57           6.3         3.3          4.7         1.6 versicolor
58           4.9         2.4          3.3         1.0 versicolor
59           6.6         2.9          4.6         1.3 versicolor
60           5.2         2.7          3.9         1.4 versicolor
61           5.0         2.0          3.5         1.0 versicolor
62           5.9         3.0          4.2         1.5 versicolor
63           6.0         2.2          4.0         1.0 versicolor
64           6.1         2.9          4.7         1.4 versicolor
65           5.6         2.9          3.6         1.3 versicolor
66           6.7         3.1          4.4         1.4 versicolor
67           5.6         3.0          4.5         1.5 versicolor
68           5.8         2.7          4.1         1.0 versicolor
69           6.2         2.2          4.5         1.5 versicolor
70           5.6         2.5          3.9         1.1 versicolor
71           5.9         3.2          4.8         1.8 versicolor
72           6.1         2.8          4.0         1.3 versicolor
73           6.3         2.5          4.9         1.5 versicolor
74           6.1         2.8          4.7         1.2 versicolor
75           6.4         2.9          4.3         1.3 versicolor
76           6.6         3.0          4.4         1.4 versicolor
77           6.8         2.8          4.8         1.4 versicolor
78           6.7         3.0          5.0         1.7 versicolor
79           6.0         2.9          4.5         1.5 versicolor
80           5.7         2.6          3.5         1.0 versicolor
81           5.5         2.4          3.8         1.1 versicolor
82           5.5         2.4          3.7         1.0 versicolor
83           5.8         2.7          3.9         1.2 versicolor
84           6.0         2.7          5.1         1.6 versicolor
85           5.4         3.0          4.5         1.5 versicolor
86           6.0         3.4          4.5         1.6 versicolor
87           6.7         3.1          4.7         1.5 versicolor
88           6.3         2.3          4.4         1.3 versicolor
89           5.6         3.0          4.1         1.3 versicolor
90           5.5         2.5          4.0         1.3 versicolor
91           5.5         2.6          4.4         1.2 versicolor
92           6.1         3.0          4.6         1.4 versicolor
93           5.8         2.6          4.0         1.2 versicolor
94           5.0         2.3          3.3         1.0 versicolor
95           5.6         2.7          4.2         1.3 versicolor
96           5.7         3.0          4.2         1.2 versicolor
97           5.7         2.9          4.2         1.3 versicolor
98           6.2         2.9          4.3         1.3 versicolor
99           5.1         2.5          3.0         1.1 versicolor
100          5.7         2.8          4.1         1.3 versicolor
101          6.3         3.3          6.0         2.5  virginica
102          5.8         2.7          5.1         1.9  virginica
103          7.1         3.0          5.9         2.1  virginica
104          6.3         2.9          5.6         1.8  virginica
105          6.5         3.0          5.8         2.2  virginica
106          7.6         3.0          6.6         2.1  virginica
107          4.9         2.5          4.5         1.7  virginica
108          7.3         2.9          6.3         1.8  virginica
109          6.7         2.5          5.8         1.8  virginica
110          7.2         3.6          6.1         2.5  virginica
111          6.5         3.2          5.1         2.0  virginica
112          6.4         2.7          5.3         1.9  virginica
113          6.8         3.0          5.5         2.1  virginica
114          5.7         2.5          5.0         2.0  virginica
115          5.8         2.8          5.1         2.4  virginica
116          6.4         3.2          5.3         2.3  virginica
117          6.5         3.0          5.5         1.8  virginica
118          7.7         3.8          6.7         2.2  virginica
119          7.7         2.6          6.9         2.3  virginica
120          6.0         2.2          5.0         1.5  virginica
121          6.9         3.2          5.7         2.3  virginica
122          5.6         2.8          4.9         2.0  virginica
123          7.7         2.8          6.7         2.0  virginica
124          6.3         2.7          4.9         1.8  virginica
125          6.7         3.3          5.7         2.1  virginica
126          7.2         3.2          6.0         1.8  virginica
127          6.2         2.8          4.8         1.8  virginica
128          6.1         3.0          4.9         1.8  virginica
129          6.4         2.8          5.6         2.1  virginica
130          7.2         3.0          5.8         1.6  virginica
131          7.4         2.8          6.1         1.9  virginica
132          7.9         3.8          6.4         2.0  virginica
133          6.4         2.8          5.6         2.2  virginica
134          6.3         2.8          5.1         1.5  virginica
135          6.1         2.6          5.6         1.4  virginica
136          7.7         3.0          6.1         2.3  virginica
137          6.3         3.4          5.6         2.4  virginica
138          6.4         3.1          5.5         1.8  virginica
139          6.0         3.0          4.8         1.8  virginica
140          6.9         3.1          5.4         2.1  virginica
141          6.7         3.1          5.6         2.4  virginica
142          6.9         3.1          5.1         2.3  virginica
143          5.8         2.7          5.1         1.9  virginica
144          6.8         3.2          5.9         2.3  virginica
145          6.7         3.3          5.7         2.5  virginica
146          6.7         3.0          5.2         2.3  virginica
147          6.3         2.5          5.0         1.9  virginica
148          6.5         3.0          5.2         2.0  virginica
149          6.2         3.4          5.4         2.3  virginica
150          5.9         3.0          5.1         1.8  virginica

Arranging plots in a grid

scatter_petal <- ggplot(
    data=iris, 
    aes(x=Petal.Length, 
        y=Petal.Width, 
        color=Species)) +
      geom_point()

scatter_petal

Arranging plots in a grid

kde_width <- ggplot(
  iris,
  aes(x=Petal.Width, 
      color=Species, 
      fill=Species)) +
  geom_density(alpha=0.2)

kde_width

Arranging plots in a grid

kde_length <- ggplot(
  iris,
  aes(x=Petal.Length, 
      color=Species, 
      fill=Species)) +
  geom_density(alpha=0.2)

kde_length

Arranging plots in a grid

We can put the plots in a grid, aligning them on the x axis, appropriately changing the scales.

plot_grid(
  kde_length + 
    scale_x_continuous(limits = c(0,8)),
  kde_width + 
    scale_x_continuous(limits = c(0,8)),
  ncol=1,
  align="v"
)

Arranging plots in a grid

We can put the plots in a grid, aligning them on the x axis, appropriately changing the scales.

plot_grid(
  kde_length + 
    scale_x_continuous(limits = c(0,8)),
  kde_width + 
    scale_x_continuous(limits = c(0,8)),
  ncol=1
)

Arranging plots in a grid

We can put the plots in a grid, aligning them on the x axis, appropriately changing the scales.

plot_grid(
  kde_length + 
    scale_x_continuous(limits = c(0,8)),
  kde_width + 
    scale_x_continuous(limits = c(0,8))
)

Arranging plots in a grid

We can use NULL to leave “holes” in the tables.

plot_grid(
  kde_length + 
    scale_x_continuous(limits = c(0,8)),
  scatter_petal,
  kde_width + 
    scale_x_continuous(limits = c(0,8)),
  NULL,
  ncol=2,
  align="v"
)

Arranging plots in a grid

We can also nest grids into one another, to create more complex arrangements.

plot_grid(
  plot_grid(
    kde_length + 
      scale_x_continuous(limits = c(0,8)),
    kde_width + 
      scale_x_continuous(limits = c(0,8)),
    ncol=1,
    align="v"
  ),
  scatter_petal,
  ncol=2
)

Arranging plots in a grid

And adjust the widths

plot_grid(
  plot_grid(
    kde_length + 
      scale_x_continuous(limits = c(0,8)),
    kde_width + 
      scale_x_continuous(limits = c(0,8)),
    ncol=1,
    align="v"
  ),
  scatter_petal,
  ncol=2,
  rel_widths = c(1,2)
)

Shared legends

species_legend <- get_legend(kde_length)

plot_grid(
  kde_length + 
    scale_x_continuous(limits = c(0,8)) +
    theme(legend.position='none'),
  scatter_petal,
  kde_width + 
    scale_x_continuous(limits = c(0,8)) +
    theme(legend.position='none'),
  species_legend,
  ncol=2,
  align="v",
  axis="b"
)

Plot overlays

iris_grid <- plot_grid(
  plot_grid(
    kde_length + 
      scale_x_continuous(limits = c(0,8)) +
      theme(legend.position="none"),
    kde_width + 
      scale_x_continuous(limits = c(0,8)) +
      theme(legend.position="none"),
    ncol=1,
    align="v"
  ),
  scatter_petal + 
    theme(legend.position='none'),
  ncol=2, rel_widths = c(1,2)
)

ggdraw(iris_grid) +
  draw_grob(species_legend, x=0.8, y=-0.25)

Margin plots

length_v <- kde_length + 
  theme_void() + 
  theme(legend.position="none")
width_v <- kde_width + 
  coord_flip() +
  theme_void() + 
  theme(legend.position="none")

p1 <- insert_xaxis_grob(
  scatter_petal + 
    theme(legend.position = "none"),
  length_v, position="top")
p2 <- insert_yaxis_grob(
  p1, width_v,
  position="right")

ggdraw(p2) +
  draw_grob(species_legend, x=0.15, y=0.15)

Margin plots

Margin plots

Creating the plot with empty axis lines.

scatter_petal

Margin plots

Creating the plot with empty axis lines.

scatter_petal + 
    theme(
      legend.position = "none",
      axis.line = element_blank()
    )

Margin plots

length_v

Inserting the density plot length_v.

p1 <- insert_xaxis_grob(
        scatter_petal + 
          theme(
            legend.position = "none",
            axis.line = element_blank()
          ),
        length_v, 
        position="top"
        )

Margin plots

width_v

Inserting the density plot width_v.

p2 <- insert_yaxis_grob(
  p1,
  width_v,
  position="right"
)

Margin plots

length_box <- ggplot(iris, aes(y=Petal.Length)) +
  geom_boxplot(x=0) +
  coord_flip() +
  theme_void() +
  theme(legend.position = "none")

length_box

Margin plots

length_box

Inserting the box plot length_box.

p3 <- insert_xaxis_grob(
  p2,
  length_box,
  position="bottom",
  height=unit(8, "pt")
)

Margin plots

width_box <- ggplot(iris, aes(y=Petal.Width)) +
  geom_boxplot(x=0) +
  theme_void() +
  theme(legend.position = "none")

width_box

Margin plots

width_box

Inserting the box plot width_box.

p4 <- insert_yaxis_grob(
  p3,
  width_box,
  position="left",
  width=unit(8, "pt")
)

Margin plots

Drawing the plot with the legend.

ggdraw(p4) +
  draw_grob(species_legend, x=0.7, y=-0.2)

Data Visualization and Exploration - Themes and Arranging Plots - ozan-k.com