Overview of duke

In duke: Creating a Color-Blind Friendly Duke Color Package

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 8,
  fig.asp = 0.618
)

library(duke)
library(palmerpenguins)
library(dplyr)
library(ggplot2)
library(ggmosaic)

This vignette aims to comprehensively demonstrate the use and functionality of the package duke. duke is fully integrated with the ggplot2 and allows for the creation of Duke official branded visualizations that are color blind friendly.

student_names <- c("Jack", "Annie", "Paul", "Aidan", "Jake", "Josh", "Grace", "Suzy", "Beth", "Taylor", "Tanner", "Lisa", "Jimmy", "Larry", "Patricia", "Laura", "Yasmin", "Tim")
student_grades <- c("A+", "B", "A+", "C", "D", "A+", "E", "C", "B-", "B-", "D", "A-", "B+", "A-", "A-", "D", "B", "E")

students <- tibble(student = student_names, grade = student_grades)

Scatter Plot - Continuous Color

plot <- ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = body_mass_g)) +
  labs(
    title = "Bill Length vs. Bill Depth", 
    x = "Bill Length (mm)", 
    y = "Bill Depth (mm)"
  )

plot +
  scale_duke_continuous() +
  theme_duke()

plot +
  geom_point(aes(shape = species)) +
  scale_duke_continuous() +
  theme_duke()

plot +
  scale_duke_continuous() +
  theme_minimal()

Scatter Plot - Discrete Color

plot1 <- ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm, color = species)) +
  geom_point(size = 2) +
  labs(title = "Bill Length vs. Bill Depth", x = "Bill Length (mm)", y = "Bill Depth (mm)")

ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm)) +
  geom_point(aes(color = species)) +
  labs(
    title = "Bill Length vs. Bill Depth", 
    subtitle = "This is the subtitle", 
    caption = "All text is in Duke Royal Blue", 
    x = "Bill Length (mm)", 
    y = "Bill Depth (mm)"
  ) +
  facet_wrap(~species) +
  theme_duke() +
  scale_duke_color_discrete()

plot1 +
  theme_duke() +
  scale_duke_color_discrete()

plot1 +
  scale_duke_color_discrete() +
  theme_minimal()

Bar Plot

plot2 <- ggplot(penguins, aes(x = species, fill = species)) +
  geom_bar() +
  labs(title = "Distribution of Penguin Species", x = "Species", y = "Count")

m_penguins <- penguins %>%
  dplyr::filter(sex == "male")

plot2.1 <- ggplot(m_penguins, aes(x = sex, fill = sex)) +
  geom_bar()

plot2.1 +
  scale_duke_fill_discrete() +
  theme_duke()


# 8-category plot
plot2.2 <- ggplot(students, aes(x = grade, fill = grade)) +
  geom_bar()

plot2.2 +
  scale_duke_fill_discrete() +
  theme_duke()

# 7-category plot
plot2.3 <- students %>%
  slice(-13) %>%
  ggplot(aes(x = grade, fill = grade)) +
  geom_bar()

plot2.3 +
  scale_duke_fill_discrete() +
  theme_duke()

# 6-category plot
plot2.4 <- students %>%
  slice(-c(9, 10, 13)) %>%
  ggplot(aes(x = grade, fill = grade)) +
  geom_bar()

plot2.4 +
  scale_duke_fill_discrete() +
  theme_duke()

# 5-category plot
plot2.4 <- students %>%
  slice(-c(9, 10, 13, 7, 18)) %>%
  ggplot(aes(x = grade, fill = grade)) +
  geom_bar()

plot2.4 +
  scale_duke_fill_discrete() +
  theme_duke()

# 4-category plot
plot2.5 <- students %>%
  slice(-c(9, 10, 13, 7, 18, 4, 8)) %>%
  ggplot(aes(x = grade, fill = grade)) +
  geom_bar()

plot2.5 +
  scale_duke_fill_discrete() +
  theme_duke()

Histogram

plot3 <- ggplot2::ggplot(penguins, aes(body_mass_g)) +
  geom_histogram(ggplot2::aes(fill = species), alpha = 0.8) +
  labs(title = "Distribution of Penguin Body Mass", caption = "(Colors used) \n Duke Royal Blue, Duke Navy Blue, Copper", x = "Body Mass (g)", y = "Count")

plot3 +
  scale_duke_fill_discrete() +
  theme_duke()

plot3 +
  scale_duke_fill_discrete() +
  theme_minimal()

Box Plot

plot4 <- ggplot2::ggplot(penguins, ggplot2::aes(sex, body_mass_g)) +
  ggplot2::geom_boxplot() +
  ggplot2::labs(title = "Comparison of Body Mass By Sex", x = "Sex", y = "Body Mass (g)")

plot4 +
  theme_duke()

plot4 +
  theme_minimal()

Density Plot

plot5 <- ggplot2::ggplot(penguins, ggplot2::aes(bill_depth_mm)) +
  ggplot2::geom_density(ggplot2::aes(fill = species)) +
  ggplot2::labs(title = "Density of Penguin Bill Depth", x = "Bill Depth (mm)", y = "Densiy")

plot5 +
  scale_duke_fill_discrete() +
  theme_duke()

plot5 +
  scale_duke_fill_discrete() +
  theme_minimal()

Jitter Plot - Discrete Color

plot6 <- ggplot2::ggplot(penguins, ggplot2::aes(year, body_mass_g)) +
  ggplot2::geom_jitter(ggplot2::aes(color = species)) +
  ggplot2::labs(title = "Comparison of Body Mass By Year", x = "Year", y = "Body Mass (g)")

plot6 +
  scale_duke_color_discrete() +
  theme_duke()

plot6 +
  scale_duke_color_discrete() +
  theme_minimal()

Jitter Plot - Discrete Color

plot6.1 <- ggplot2::ggplot(penguins, ggplot2::aes(year, body_mass_g)) +
  ggplot2::geom_jitter(ggplot2::aes(color = bill_length_mm)) +
  ggplot2::labs(title = "Comparison of Body Mass By Year", x = "Year", y = "Body Mass (g)")

plot6.1 +
  scale_duke_continuous() +
  theme_duke()

plot6.1 +
  scale_duke_continuous() +
  theme_minimal()

Line Plot

yearly_avg <- penguins %>%
  filter(!is.na(bill_length_mm)) %>%
  group_by(island, year) %>%
  summarize(island, year, mean = mean(bill_length_mm)) %>%
  distinct(island, year, .keep_all = T)

lineplot <- ggplot(data = yearly_avg, aes(x = as.factor(year), y = mean, group = island)) +
  geom_line(aes(color = island), linewidth = 1) +
  geom_point(aes(color = island)) +
  labs(title = "Average Island Bill Length(mm) Per Year", x = "Year", y = "Average Bill Length (mm)") +
  theme_duke() +
  scale_duke_color_discrete()
lineplot

# with point shape and line pattern
lineplot.2 <- ggplot(data = yearly_avg, aes(x = as.factor(year), y = mean, group = island)) +
  geom_line(aes(color = island, linetype = island), linewidth = 1) +
  geom_point(aes(color = island, shape = island)) +
  labs(title = "Average Island Bill Length(mm) Per Year", x = "Year", y = "Average Bill Length (mm)") +
  theme_duke() +
  scale_duke_color_discrete()
lineplot.2

Mosaic Plot

plot7 <- ggplot(data = penguins) +
  ggmosaic::geom_mosaic(aes(x = ggmosaic::product(sex, island), fill = sex)) +
  labs(title = "Penguin Sex vs. Island", x = "Island", y = "Penguin Sex", caption = "(Color from top to bottom) \n Granite, Duke Navy Blue, Duke Royal Blue")

plot7 +
  scale_duke_fill_discrete() +
  theme_duke()

plot7 +
  scale_duke_fill_discrete() +
  theme_minimal()

Label Plot

plot8 <- ggplot2::ggplot(penguins, ggplot2::aes(bill_length_mm, bill_depth_mm, fill = island)) +
  ggplot2::geom_label(aes(label = island)) +
  ggplot2::labs(title = "Bill Length/Depth by Island", x = "Bill Length (mm)", y = "Bill Depth (mm)")

plot8 +
  scale_duke_fill_discrete() +
  theme_duke()

plot8 +
  scale_duke_fill_discrete() +
  theme_minimal()

Quantile Plot

plot9 <- ggplot2::ggplot(penguins, ggplot2::aes(bill_length_mm, bill_depth_mm, color = species)) +
  ggplot2::geom_quantile() +
  ggplot2::labs(title = "Bill Length/Depth Quantiles", x = "Bill Length (mm)", y = "Bill Depth (mm)")

plot9 +
  scale_duke_color_discrete() +
  theme_duke()

plot9 +
  scale_duke_color_discrete() +
  theme_minimal()

Area Plot

plot10 <- ggplot2::ggplot(penguins, ggplot2::aes(body_mass_g, fill = species)) +
  ggplot2::geom_area(stat = "bin") +
  ggplot2::labs(title = "Area of Body Mass Index", x = "BMI")

plot10 +
  scale_duke_fill_discrete() +
  theme_duke()

plot10 +
  scale_duke_fill_discrete() +
  theme_minimal()

Dot Plot

plot11 <- ggplot2::ggplot(penguins, ggplot2::aes(body_mass_g)) +
  ggplot2::geom_dotplot(aes(fill = species)) +
  ggplot2::labs(title = "Dotplot of BMI", x = "BMI")

plot11 +
  scale_duke_fill_discrete() +
  theme_duke()

plot11 +
  scale_duke_fill_discrete() +
  theme_minimal()

Frequency Polynomial Plot

plot12 <- ggplot2::ggplot(penguins, ggplot2::aes(body_mass_g)) +
  ggplot2::geom_freqpoly(aes(color = species)) +
  ggplot2::labs(title = "Frequency Polynomial Plot of BMI", x = "BMI")

plot12 +
  scale_duke_color_discrete() +
  theme_duke()

plot12 +
  scale_duke_color_discrete() +
  theme_minimal()

Column Plot

plot13 <- ggplot2::ggplot(penguins, ggplot2::aes(species, body_mass_g, color = species)) +
  ggplot2::geom_col() +
  ggplot2::labs(title = "BMI By Species of BMI", x = "Species", y = "BMI")

plot13 +
  scale_duke_color_discrete() +
  theme_duke()

plot13 +
  scale_duke_color_discrete() +
  theme_minimal()

Violin Plot

plot14 <- ggplot2::ggplot(penguins, ggplot2::aes(species, body_mass_g, fill = species)) +
  geom_violin(scale = "area") +
  ggplot2::labs(title = "BMI By Species", x = "Species", y = "BMI")

plot14 +
  scale_duke_fill_discrete() +
  theme_duke()

plot14 +
  scale_duke_fill_discrete() +
  theme_minimal()

Count Plot

plot15 <- ggplot2::ggplot(penguins, ggplot2::aes(species, island, color = species)) +
  geom_count() +
  ggplot2::labs(title = "Species Count by Island", x = "Species", y = "Island")

plot15 +
  scale_duke_color_discrete() +
  theme_duke()

plot15 +
  scale_duke_color_discrete() +
  theme_minimal()

Step Plot

plot16 <- ggplot2::ggplot(penguins, ggplot2::aes(year, body_mass_g, color = species)) +
  geom_step()
ggplot2::labs(title = "BMI By Year", x = "Year", y = "BMI")

plot16 +
  scale_duke_color_discrete() +
  theme_duke()

plot16 +
  scale_duke_color_discrete() +
  theme_minimal()

Coordinate Polar

plot1 +
  facet_wrap(~species) +
  theme_bw() +
  scale_duke_color_discrete()

duke documentation built on May 29, 2024, 10:39 a.m.