Grammer of graphics with ggplot

Raju Rimal Postdoctoral Researcher

University of Oslo

December 1, 2022

Introduction

Grammer of graphics

Image adapted from the The Grammar of Graphics

Plotting system in R

Base

Book | Tutorials | Cheatsheets: 1, 2

Plotting system in R

Base

Lattice

Book | Video | Tutorial

Plotting system in R

Base

Lattice

ggplot2

Website | Book | Videos: Part-1, Part-2

More:  Github:erikgahner/awesome-ggplot2

Components of ggplot2

ggplot(<DATA>, aes(<MAPPING>)) +
  geom_*(<MAPPING>) +
  scale_x_*(<SCALE_SPEC>) +
  scale_y_*(<SCALE_SPEC>) +
  facet_grid(ROW_FACET ~ COL_FACET) +
  coord_<COORD_SYSTEM>(<SPEC>) +
  theme(<THEME_ARGUMENTS>)

Components of ggplot2

ggplot(<DATA>, aes(<MAPPING>)) +
  geom_*(<MAPPING>) +
  stat_*(geom = <GEOM>, fun = <FUN>) +
  facet_grid(ROW_FACET ~ COL_FACET) +
  coord_<COORD_SYSTEM>(<SPEC>) +
  theme(<THEME_ARGUMENTS>)

ggplot(cancer, aes(x = ph.karno, y = time)) +
  geom_*(<MAPPING>) +
  stat_*(geom = <GEOM>, fun = <FUN>) +
  facet_grid(ROW_FACET ~ COL_FACET) +
  coord_<COORD_SYSTEM>(<SPEC>) +
  theme(<THEME_ARGUMENTS>)

ggplot(cancer, aes(x = ph.karno, y = time)) +
  geom_point() +
  stat_*(geom = <GEOM>, fun = <FUN>) +
  facet_grid(ROW_FACET ~ COL_FACET) +
  coord_<COORD_SYSTEM>(<SPEC>) +
  theme(<THEME_ARGUMENTS>)

ggplot(cancer, aes(x = ph.karno, y = time)) +
  geom_point() +
  stat_summary(fun = mean, color = "red") +
  facet_grid(ROW_FACET ~ COL_FACET) +
  coord_<COORD_SYSTEM>(<SPEC>) +
  theme(<THEME_ARGUMENTS>)

ggplot(cancer, aes(x = ph.karno, y = time)) +
  geom_point() +
  stat_summary(fun = mean, color = "red") +
  facet_grid(status ~ .) +
  coord_<COORD_SYSTEM>(<SPEC>) +
  theme(<THEME_ARGUMENTS>)

ggplot(cancer, aes(x = ph.karno, y = time)) +
  geom_point() +
  stat_summary(fun = mean, color = "red") +
  facet_grid(status ~ .) +
  coord_cartesian() +
  theme(<THEME_ARGUMENTS>)

ggplot(cancer, aes(x = ph.karno, y = time)) +
  geom_point() +
  stat_summary(fun = mean, color = "red") +
  facet_grid(status ~ .) +
  coord_polar() +
  theme(<THEME_ARGUMENTS>)

ggplot(cancer, aes(x = ph.karno, y = time)) +
  geom_point() +
  stat_summary(fun = mean, color = "red") +
  facet_grid(status ~ .) +
  coord_cartesian() +
  theme_bw()

Dataset: cancer, Package: survival

Customizing ggplot2

Aesthetic mappings

• x, xmin, xmax

• y, ymin, ymax

• label

• group
• fill, color

• size, alpha
• shape, linetype

Code

ggplot(mtcars, aes(factor(carb), mpg)) +
  stat_summary(
    fun.data = mean_se, 
    geom = "pointrange", 
    width = 0.1, 
    color = "firebrick"
  ) +
  labs(
    x = "Number of carborators",
    y = "Mile per gallon"
  ) + 
  geom_point(
    position = position_jitter(width = 0.05), 
    shape = 21, 
    fill = "whitesmoke"
  ) +
  coord_flip() +
  annotate(
    geom = "text",
    y = c(23, 25.5, 27.5),
    x = c(0.8, 0.8, 0.8),
    label = c("xmin", "x", "xmax"),
    family = "consolas",
    color = "blue"
  )

Code

ggplot(mtcars, aes(factor(carb), mpg)) +
  stat_summary(
    fun.data = mean_se, 
    geom = "pointrange", 
    width = 0.1, 
    color = "firebrick"
  ) +
  labs(
    x = "Number of carborators",
    y = "Mile per gallon"
  ) + 
  geom_point(
    position = position_jitter(width = 0.05), 
    shape = 21, 
    fill = "whitesmoke"
  ) +
  annotate(
  geom = "text",
  y = c(23, 25.5, 27.5),
  x = c(0.8, 0.8, 0.8),
  label = c("ymin", "y", "ymax"),
  family = "consolas",
  color = "blue"
)

Code

ggplot(mtcars, aes(factor(carb), mpg)) +
  stat_summary(
    fun.data = mean_se, 
    geom = "pointrange", 
    width = 0.1, 
    color = "firebrick"
  ) +
  labs(
    x = "Number of carborators",
    y = "Mile per gallon"
  ) + 
  geom_point(
    position = position_jitter(width = 0.05), 
    shape = 21, 
    fill = "whitesmoke"
  ) +
  geom_text(
    data = ~subset(.x, carb >= 6),
    aes(label = model),
    check_overlap = TRUE,
    vjust = -1
  )

Code

ggplot(mtcars, aes(factor(carb), mpg, group = am, color = factor(am))) +
  geom_point(
    position = position_jitter(width = 0.05), 
    fill = "whitesmoke"
  ) +
  stat_summary(
    fun = mean,
    geom = "line"
  ) +
  stat_summary(
    fun.data = mean_se, 
    geom = "pointrange", 
    width = 0.1,
    fill = "whitesmoke"
  ) +
  labs(
    x = "Number of carborators",
    y = "Mile per gallon",
    color = "Engine",
    fill = "Engine",
  ) +
  theme(
    legend.position = c(1, 1),
    legend.justification = c(1, 1) + 0.25
  )

Code

ggplot(mtcars, aes(factor(carb), mpg, group = am)) +
  geom_point(
    position = position_jitter(width = 0.05), 
    fill = "whitesmoke",
    aes(shape = factor(am))
  ) +
  stat_summary(
    fun = mean,
    geom = "line",
    aes(linetype = factor(am))
  ) +
  stat_summary(
    fun.data = mean_se, 
    geom = "pointrange", 
    width = 0.1,
    fill = "whitesmoke",
    aes(shape = factor(am), linetype = factor(am))
  ) +
  labs(
    x = "Number of carborators",
    y = "Mile per gallon",
    color = "Engine",
    linetype = "Engine",
    fill = "Engine",
    shape = "Engine"
  ) +
  scale_shape_discrete(solid = FALSE) +
  theme(
    legend.position = c(1, 1),
    legend.justification = c(1, 1) + 0.25
  )

Dataset: mtcars, Package: datasets

Summary statistics

• mean, median
• standard error (mean_se)
• standard deviation (mean_sdl)

• fitted model (geom_smooth)

Code

ggplot(mtcars, aes(factor(carb), mpg, group = am)) +
  geom_point(
    position = position_jitter(width = 0.05), 
    fill = "whitesmoke",
    aes(shape = factor(am))
  ) +
  stat_summary(
    fun = mean,
    geom = "line",
    aes(linetype = factor(am))
  ) +
  stat_summary(
    fun.data = mean_se, 
    geom = "pointrange", 
    width = 0.1,
    fill = "whitesmoke",
    aes(shape = factor(am), linetype = factor(am))
  ) +
  labs(
    x = "Number of carborators",
    y = "Mile per gallon",
    color = "Engine",
    linetype = "Engine",
    fill = "Engine",
    shape = "Engine"
  ) +
  scale_shape_discrete(solid = FALSE) +
  theme(
    legend.position = c(1, 1),
    legend.justification = c(1, 1) + 0.25
  )

Code

ggplot(mtcars, aes(factor(carb), mpg)) +
  geom_point(
    position = position_jitter(width = 0.05), 
    aes(shape = am),
    fill = "whitesmoke",
    size = rel(3)
  ) +
  geom_smooth(
    method = "lm",
    formula = "y ~ x",
    se = FALSE,
    aes(linetype = am, group = am)
  ) +
  labs(
    x = "Number of carborators",
    y = "Mile per gallon",
    color = "Engine",
    linetype = "Engine",
    fill = "Engine",
    shape = "Engine"
  ) +
  scale_shape_discrete(solid = FALSE) +
  theme(
    legend.position = c(1, 1),
    legend.justification = c(1, 1) + 0.25
  )

Dataset: mtcars, Package: datasets

Faceting

facet_grid

facet_wrap

labeller

Code

ggplot(survival::cancer, aes(time)) +
  geom_histogram(
    aes(y = after_stat(density)), 
    fill = "#afafaf",
    binwidth = 365.241/4, 
    color = "#a0a0a0", 
    na.rm = TRUE
  ) +
  geom_density(na.rm = TRUE) +
  facet_grid(
    cols = vars(sex), 
    rows = vars(status)
  ) +
  labs(title = "Example of facet grid")

Code

cancer <- as.data.table(survival::cancer)
cancer[, age_group := cut(age, seq(35, 85, 10))]
ggplot(cancer, aes(time)) +
  geom_histogram(
    aes(y = after_stat(density)), 
    fill = "#afafaf",
    binwidth = 365.241/4, 
    color = "#a0a0a0", 
    na.rm = TRUE
  ) +
  geom_density(na.rm = TRUE) +
  facet_wrap(
    facets = vars(age_group),
  ) +
  labs(title = "Example of facet wrap")

Code

cancer <- as.data.table(survival::cancer)
cancer[, age_group := cut(age, seq(35, 85, 10))]
ggplot(cancer, aes(time)) +
  geom_histogram(
    aes(y = after_stat(density)), 
    fill = "#afafaf",
    binwidth = 365.241/4, 
    color = "#a0a0a0", 
    na.rm = TRUE
  ) +
  geom_density(na.rm = TRUE) +
  facet_wrap(
    facets = vars(age_group),
    labeller = labeller(
      age_group = function(x) {
        gsub("\\((.*?),(.*?)\\]", "Age Group: \\1-\\2", x)
      }
    )
  ) +
  labs(title = "Example of facet wrap")

Dataset: cancer, Package: survival

Scale

Function to specify (customize) scales. Usually takes the form scale_<GEOM>_<TYPE>.

• scale_x_contineous
• scale_x_discrete

• scale_y_contineous
• scale_y_discrete

Code

cancer <- as.data.table(survival::cancer)
cancer[, age_group := cut(age, seq(35, 85, 10))]
ggplot(cancer, aes(time)) +
  geom_histogram(
    aes(y = after_stat(density)), 
    fill = "#afafaf",
    binwidth = 365.241/4, 
    color = "#a0a0a0", 
    na.rm = TRUE
  ) +
  geom_density(na.rm = TRUE) +
  facet_wrap(
    facets = vars(age_group),
    labeller = labeller(
      age_group = function(x) {
        gsub("\\((.*?),(.*?)\\]", "Age Group: \\1-\\2", x)
      }
    )
  ) +
  labs(title = "Example of facet wrap")

Code

ggplot(cancer, aes(time)) +
  geom_histogram(
    aes(y = after_stat(density)), 
    fill = "#afafaf",
    binwidth = 365.241/4, 
    color = "#a0a0a0", 
    na.rm = TRUE
  ) +
  geom_density(na.rm = TRUE) +
  facet_wrap(
    facets = vars(age_group),
    labeller = labeller(
      age_group = function(x) {
        gsub("\\((.*?),(.*?)\\]", "Age Group: \\1-\\2", x)
      }
    )
  ) +
  labs(title = "Example of facet wrap") +
  scale_x_continuous(
    breaks = seq(0, 3, 0.5) * 365.241,
    labels = function(x) x / 365.241
  )

Code

ggplot(cancer, aes(time)) +
  geom_histogram(
    aes(y = after_stat(density)), 
    fill = "#afafaf",
    binwidth = 365.241/4, 
    color = "#a0a0a0", 
    na.rm = TRUE
  ) +
  geom_density(na.rm = TRUE) +
  facet_wrap(
    facets = vars(age_group),
    labeller = labeller(
      age_group = function(x) {
        gsub("\\((.*?),(.*?)\\]", "Age Group: \\1-\\2", x)
      }
    )
  ) +
  labs(title = "Example of facet wrap") +
  scale_x_continuous(
    breaks = seq(0, 3, 0.5) * 365.241,
    labels = function(x) x / 365.241
  ) +
  scale_y_continuous(
    labels = scales::label_scientific()
  )

Dataset: cancer, Package: survival

Scale

• scale_color_*
• scale_fill_*
• scale_shape_*
• scale_linetype_*
• scale_alpha_*
• scale_size_*

Code

mtcars$gear <- as.factor(mtcars$gear)
ggplot(mtcars, aes(hp, mpg, color = gear)) +
  geom_point(aes(size = wt), alpha = 0.8) +
  scale_size_continuous(breaks = seq(1, 6, 2), limits = c(1, 6)) +
  theme(
    legend.position = c(1, 1),
    legend.justification = c(1.5, 1.5),
    legend.direction = "horizontal"
  ) +
  labs(
    x = "Horse power", 
    y = "Mile per gallon",
    color = "Gear",
    size = "Weight"
  )

See more at: Scales and Guides

Dataset: mtcars, Package: datasets

Theming ggplot2

axis

title, text, ticks, line

legend

background, margin, spacing, key, title,

position, direction justification, box

panel

spacing, grid, background

plot

title, subtitle, caption, tag, margin

strip

background, text

Code

mtcars$gear <- as.factor(mtcars$gear)
plt <- ggplot(mtcars, aes(hp, mpg, color = gear)) +
  geom_point(aes(size = wt), alpha = 0.8) +
  scale_size_continuous(breaks = seq(1, 6, 2), limits = c(1, 6)) +
  facet_grid(rows = vars(am)) +
  theme(
    legend.position = c(1, 1),
    legend.justification = c(1.5, 1.5),
    legend.direction = "horizontal"
  ) +
  labs(
    title = "Power vs Consumption",
    x = "Horse power", 
    y = "Mile per gallon",
    color = "Gear",
    size = "Weight"
  )
plt

Helpers:

• element_text
• element_line
• element_rect
• element_blank
• margin
• unit

Sourcehttps://github.com/isabellabenabaye/ggplot2-reference/blob/master/ggplot2-theme-elements-reference.pdf

Annotations

• Use geom to add custom elements
• geom can be point, line, segment, rect and more
• Add custom grob using annotation_custom

Code

plt +
  annotate(
    geom = "rect",
    xmin = 150, xmax = 250,
    ymin = 10, ymax = 20,
    fill = "ghostwhite",
    alpha = 0.25,
    color = "grey"
  ) +
  annotate(
    geom = "text",
    x = 200,
    y = 20,
    label = "heavy vehicle and\nlow fuel efficint",
    vjust = -0.5,
    family = "mono"
  )

Extensions

patchwork, cowplot

Composing multiple ggplot plots

gganimate

Grammar of animated graphics with ggpolot2

ggstatsplot and ggpubr

Enhance ggplot2 with statistics and annotations

ggthemes, ggtech, see, ggsci

Extra themes and schemes for ggplot2

ggraph

Visualize network, graphs and trees

ggrepel, geomtextpath

Manage and direct text in your plot

More: survminer, ggridge, ggh4x

See more at: https://exts.ggplot2.tidyverse.org/gallery/

Demo

Resources

Books and Resources

• https://posit.co/resources/cheatsheets
• https://ggplot2.tidyverse.org/
• https://ggplot2-book.org/
• https://github.com/erikgahner/awesome-ggplot2

Dataset collection

https://vincentarelbundock.github.io/Rdatasets/datasets.html