How to Create a Beautiful Plots in R with Summary Statistics Labels

library(tidyverse)
library(rstatix)
library(ggpubr)
# Demo data
data("ToothGrowth")
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add random QC column
set.seed(123)
qc <- rep(c("pass", "fail"), 30)
df$qc <- as.factor(sample(qc, 60))
# Inspect the data
head(df)
# Basic plot
ggsummarystats(
  df, x = "dose", y = "len", 
  ggfunc = ggboxplot, add = "jitter"
)

library(tidyverse)
library(rstatix)
library(ggpubr)
# Demo data
data("ToothGrowth")
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add random QC column
set.seed(123)
qc <- rep(c("pass", "fail"), 30)
df$qc <- as.factor(sample(qc, 60))
# Inspect the data
head(df)
# Color by groups
ggsummarystats(
  df, x = "dose", y = "len", 
  ggfunc = ggboxplot, add = "jitter",
  color = "dose", palette = "npg"
)

# Grouped plots
ggsummarystats(
  df, x = "dose", y = "len", 
  ggfunc = ggboxplot, add = "jitter",
  color = "supp", palette = "npg"
  )

# Change plot type to violin
ggsummarystats(
  df, x = "dose", y = "len", 
  ggfunc = ggviolin, add = c("jitter", "median_iqr"),
  color = "supp", palette = "npg"
  )

library(tidyverse)
library(rstatix)
library(ggpubr)
# Demo data
data("ToothGrowth")
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add random QC column
set.seed(123)
qc <- rep(c("pass", "fail"), 30)
df$qc <- as.factor(sample(qc, 60))
# Inspect the data
head(df)
# Compute summary statistics
summary.stats <- df %>%
  group_by(dose) %>%
  get_summary_stats() %>%
  select(dose, n, median, iqr)
summary.stats

# Create a boxplot
bxp <- ggboxplot(
  df, x = "dose", y = "len", add = "jitter", 
  ggtheme = theme_bw()
)

# Visualize the summary statistics
summary.plot <- ggsummarytable(
  summary.stats, x = "dose", y = c("n", "median", "iqr"),
  ggtheme = theme_bw()
) +
  clean_table_theme()

# Combine the boxplot and the summary statistics plot
ggarrange(
  bxp, summary.plot, ncol = 1, align = "v",
  heights = c(0.80, 0.20)
)
# Create barplot
ggsummarystats(
  df, x = "dose", y = "len", 
  ggfunc = ggbarplot, add = c("jitter", "median_iqr"), position = position_dodge(),
  color = "supp", palette = "npg"
)

library(tidyverse)
library(rstatix)
library(ggpubr)
# Demo data
data("ToothGrowth")
df <- ToothGrowth
df$dose <- as.factor(df$dose)
# Add random QC column
set.seed(123)
qc <- rep(c("pass", "fail"), 30)
df$qc <- as.factor(sample(qc, 60))
# Inspect the data
head(df)
# Create line plots
ggsummarystats(
  df, x = "dose", y = "len", 
  ggfunc = ggline, add = c("jitter", "median_iqr"), 
  color = "supp", palette = "npg"
)

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