GGPLOT with Summary Stats Table Under the Plot

Create a ggplot with summary stats (n, median, mean, iqr) table under the plot. Read more: How to Create a Beautiful Plots in R with Summary Statistics Labels.

ggsummarytable(
  data,
  x,
  y,
  digits = 0,
  size = 3,
  color = "black",
  palette = NULL,
  facet.by = NULL,
  labeller = "label_value",
  position = "identity",
  ggtheme = theme_pubr(),
  ...
)

ggsummarystats(
  data,
  x,
  y,
  summaries = c("n", "median", "iqr"),
  ggfunc = ggboxplot,
  color = "black",
  fill = "white",
  palette = NULL,
  facet.by = NULL,
  free.panels = FALSE,
  labeller = "label_value",
  heights = c(0.8, 0.2),
  digits = 0,
  table.font.size = 3,
  ggtheme = theme_pubr(),
  ...
)

# S3 method for ggsummarystats
print(x, heights = c(0.8, 0.2), ...)

# S3 method for ggsummarystats_list
print(x, heights = c(0.8, 0.2), legend = NULL, ...)

Arguments

data: a data frame
x: a list of ggsummarystats.
y: character vector containing one or more variables to plot
digits: integer indicating the number of decimal places (round) to be used.
size: Numeric value (e.g.: size = 1). change the size of points and outlines.
color: outline color.
palette: the color palette to be used for coloring or filling by groups. Allowed values include "grey" for grey color palettes; brewer palettes e.g. "RdBu", "Blues", ...; or custom color palette e.g. c("blue", "red"); and scientific journal palettes from ggsci R package, e.g.: "npg", "aaas", "lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty".
facet.by: character vector, of length 1 or 2, specifying grouping variables for faceting the plot into multiple panels. Should be in the data.
labeller: Character vector. An alternative to the argument short.panel.labs. Possible values are one of "label_both" (panel labelled by both grouping variable names and levels) and "label_value" (panel labelled with only grouping levels).
position: Position adjustment, either as a string, or the result of a call to a position adjustment function.
ggtheme: function, ggplot2 theme name. Default value is theme_pubr(). Allowed values include ggplot2 official themes: theme_gray(), theme_bw(), theme_minimal(), theme_classic(), theme_void(), ....
...: other arguments passed to the function ggpar(), facet() or ggarrange() when printing the plot.
summaries: summary stats to display in the table. Possible values are those returned by the function get_summary_stats(), including: "n", "min", "max", "median", "q1", "q2", "q3", "mad", "mean", "sd", "se", "ci".
ggfunc: a ggpubr function, including: ggboxplot, ggviolin, ggdotplot, ggbarplot, ggline, etc. Can be any other ggplot function that accepts the following arguments data, x, color, fill, palette, ggtheme, facet.by.
fill: fill color.
free.panels: logical. If TRUE, create free plot panels when the argument facet.by is specified.
heights: a numeric vector of length 2, specifying the heights of the main and the summary table, respectively.
table.font.size: the summary table font size.
legend: character specifying legend position. Allowed values are one of c("top", "bottom", "left", "right", "none"). To remove the legend use legend = "none".

Functions

ggsummarytable(): Create a table of summary stats
ggsummarystats(): Create a ggplot with a summary stat table under the plot.

Examples

# Data preparation
#::::::::::::::::::::::::::::::::::::::::::::::::
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)
#>    len supp dose   qc
#> 1  4.2   VC  0.5 pass
#> 2 11.5   VC  0.5 pass
#> 3  7.3   VC  0.5 pass
#> 4  5.8   VC  0.5 fail
#> 5  6.4   VC  0.5 pass
#> 6 10.0   VC  0.5 fail


# Basic summary stats
#::::::::::::::::::::::::::::::::::::::::::::::::
# Compute summary statistics
summary.stats <- df %>%
  group_by(dose) %>%
  get_summary_stats(type = "common")
summary.stats
#> # A tibble: 3 × 11
#>   dose  variable     n   min   max median   iqr  mean    sd    se    ci
#>   <fct> <fct>    <dbl> <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 0.5   len         20   4.2  21.5   9.85  5.03  10.6  4.5  1.01   2.11
#> 2 1     len         20  13.6  27.3  19.2   7.12  19.7  4.42 0.987  2.07
#> 3 2     len         20  18.5  33.9  26.0   4.3   26.1  3.77 0.844  1.77

# Visualize summary table
ggsummarytable(
  summary.stats, x = "dose", y = c("n", "median", "iqr"),
  ggtheme = theme_bw()
)



# Create plots with summary table under the plot
#::::::::::::::::::::::::::::::::::::::::::::::::
# Basic plot
ggsummarystats(
  df, x = "dose", y = "len",
  ggfunc = ggboxplot, add = "jitter"
)


# Color by groups
ggsummarystats(
  df, x = "dose", y = "len",
  ggfunc = ggboxplot, add = "jitter",
  color = "dose", palette = "npg"
)


# Create a barplot
ggsummarystats(
  df, x = "dose", y = "len",
  ggfunc = ggbarplot, add = c("jitter", "median_iqr"),
  color = "dose", palette = "npg"
)


# Facet
#::::::::::::::::::::::::::::::::::::::::::::::::
# Specify free.panels = TRUE for free panels
ggsummarystats(
  df, x = "dose", y = "len",
  ggfunc = ggboxplot, add = "jitter",
  color = "dose", palette = "npg",
  facet.by = c("supp", "qc"),
  labeller = "label_both"
)
#> Warning: NaNs produced