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GGPLOT with Summary Stats Table Under the Plot

Source: R/ggsummarystats.R
ggsummarystats.Rd

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.

Usage

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 class 'ggsummarystats'
print(x, heights = c(0.8, 0.2), ...)

# S3 method for class '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: There was 1 warning in `mutate()`.
#> ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
#> Caused by warning:
#> ! There was 1 warning in `mutate()`.
#> ℹ In argument: `ci = abs(stats::qt(alpha/2, .data$n - 1) * .data$se)`.
#> Caused by warning in `stats::qt()`:
#> ! NaNs produced