Summary tables using 2-sided formulae: crosstabs, frequencies, table 1s and more.

Description

datasummary can use any summary function which produces one numeric or character value per variable. The examples section of this documentation shows how to define custom summary functions.

modelsummary also supplies several shortcut summary functions which can be used in datasummary() formulas: Min, Max, Mean, Median, Var, SD, NPercent, NUnique, Ncol, P0, P25, P50, P75, P100.

See the Details and Examples sections below, and the vignettes on the modelsummary website:

• https://modelsummary.com/

• https://modelsummary.com/vignettes/datasummary.html

Usage

datasummary(
  formula,
  data,
  output = getOption("modelsummary_output", default = "default"),
  fmt = 2,
  title = getOption("modelsummary_title", default = NULL),
  notes = getOption("modelsummary_notes", default = NULL),
  align = getOption("modelsummary_align", default = NULL),
  add_columns = getOption("modelsummary_add_columns", default = NULL),
  add_rows = getOption("modelsummary_add_rows", default = NULL),
  sparse_header = getOption("modelsummary_sparse_header", default = TRUE),
  escape = getOption("modelsummary_escape", default = TRUE),
  ...
)

Arguments

formula	A two-sided formula to describe the table: rows ~ columns. See the Examples section for a mini-tutorial and the Details section for more resources. Grouping/nesting variables can appear on both sides of the formula, but all summary functions must be on one side.
data	A data.frame (or tibble)
output	filename or object type (character string) Supported filename extensions: .docx, .html, .tex, .md, .txt, .csv, .xlsx, .png, .jpg Supported object types: "default", "html", "markdown", "latex", "latex_tabular", "typst", "data.frame", "tinytable", "gt", "kableExtra", "huxtable", "flextable", "DT", "jupyter". The "modelsummary_list" value produces a lightweight object which can be saved and fed back to the modelsummary function. The "default" output format can be set to "tinytable", "kableExtra", "gt", "flextable", "huxtable", "DT", or "markdown" If the user does not choose a default value, the packages listed above are tried in sequence. Session-specific configuration: options(“modelsummary_factory_default” = “gt”) Persistent configuration: config_modelsummary(output = “markdown”) Warning: Users should not supply a file name to the output argument if they intend to customize the table with external packages. See the ‘Details’ section. LaTeX compilation requires the booktabs and siunitx packages, but siunitx can be disabled or replaced with global options. See the ‘Details’ section.
fmt	how to format numeric values: integer, user-supplied function, or modelsummary function. Integer: Number of decimal digits User-supplied functions: Any function which accepts a numeric vector and returns a character vector of the same length. modelsummary functions: fmt = fmt_significant(2): Two significant digits (at the term-level) fmt = fmt_sprintf(“%.3f”): See ?sprintf fmt = fmt_identity(): unformatted raw values
title	string. Cross-reference labels should be added with Quarto or Rmarkdown chunk options when applicable. When saving standalone LaTeX files, users can add a label such as \label{tab:mytable} directly to the title string, while also specifying escape=FALSE.
notes	list or vector of notes to append to the bottom of the table.
align	A string with a number of characters equal to the number of columns in the table (e.g., align = “lcc”). Valid characters: l, c, r, d. "l": left-aligned column "c": centered column "r": right-aligned column "d": dot-aligned column. For LaTeX/PDF output, this option requires at least version 3.0.25 of the siunitx LaTeX package. See the LaTeX preamble help section below for commands to insert in your LaTeX preamble.
add_columns	a data.frame (or tibble) with the same number of rows as your main table.
add_rows	a data.frame (or tibble) with the same number of columns as your main table. By default, rows are appended to the bottom of the table. Positions can be defined using integers. In the modelsummary() function (only), you can also use string shortcuts: "coef_start", "coef_end", "gof_start", "gof_end" attr(new_rows, 1:2) attr(new_rows, “gof_start”) See Examples section below.
sparse_header	TRUE or FALSE. TRUE eliminates column headers which have a unique label across all columns, except for the row immediately above the data. FALSE keeps all headers. The order in which terms are entered in the formula determines the order in which headers appear. For example, x~mean*z will print the mean-related header above the z-related header.’
escape	boolean TRUE escapes or substitutes LaTeX/HTML characters which could prevent the file from compiling/displaying. TRUE escapes all cells, captions, and notes. Users can have more fine-grained control by setting escape=FALSE and using an external command such as: modelsummary(model, “latex”) |> tinytable::format_tt(tab, j=1:5, escape=TRUE)
…	all other arguments are passed through to the table-making functions tinytable::tt, kableExtra::kbl, gt::gt, DT::datatable, etc. depending on the output argument. This allows users to pass arguments directly to datasummary in order to affect the behavior of other functions behind the scenes.

Details

Visit the ‘modelsummary’ website for more usage examples: https://modelsummary.com

The ‘datasummary’ function is a thin wrapper around the ‘tabular’ function from the ‘tables’ package. More details about table-making formulas can be found in the ‘tables’ package documentation: ?tables::tabular

Hierarchical or "nested" column labels are only available for these output formats: tinytable, kableExtra, gt, html, rtf, and LaTeX. When saving tables to other formats, nested labels will be combined to a "flat" header.

Version 2.0.0, kableExtra, and tinytable

Since version 2.0.0, modelsummary uses tinytable as its default table-drawing backend. Learn more at: https://vincentarelbundock.github.io/tinytable/",

Revert to kableExtra for one session:

options(modelsummary_factory_default = ‘kableExtra’) options(modelsummary_factory_latex = ‘kableExtra’) options(modelsummary_factory_html = ‘kableExtra’)

Global Options

The behavior of modelsummary can be modified by setting global options. In particular, most of the arguments for most of the package’s functions cna be set using global options. For example:

• options(modelsummary_output = “modelsummary_list”)

• options(modelsummary_statistic = ‘({conf.low}, {conf.high})’)

• options(modelsummary_stars = TRUE)

Options not specific to given arguments are listed below.

Model labels: default column names

These global option changes the style of the default column headers:

• options(modelsummary_model_labels = “roman”)

The supported styles are: "model", "arabic", "letters", "roman", "(arabic)", "(letters)", "(roman)"

Table-making packages

modelsummary supports 6 table-making packages: tinytable, kableExtra, gt, flextable, huxtable, and DT. Some of these packages have overlapping functionalities. To change the default backend used for a specific file format, you can use ’ the options function:

options(modelsummary_factory_html = ‘kableExtra’) options(modelsummary_factory_word = ‘huxtable’) options(modelsummary_factory_png = ‘gt’) options(modelsummary_factory_latex = ‘gt’) options(modelsummary_factory_latex_tabular = ‘kableExtra’)

Table themes

Change the look of tables in an automated and replicable way, using the modelsummary theming functionality. See the vignette: https://modelsummary.com/vignettes/appearance.html

• modelsummary_theme_gt

• modelsummary_theme_kableExtra

• modelsummary_theme_huxtable

• modelsummary_theme_flextable

• modelsummary_theme_dataframe

Model extraction functions

modelsummary can use two sets of packages to extract information from statistical models: the easystats family (performance and parameters) and broom. By default, it uses easystats first and then falls back on broom in case of failure. You can change the order of priorities or include goodness-of-fit extracted by both packages by setting:

options(modelsummary_get = “easystats”)

options(modelsummary_get = “broom”)

options(modelsummary_get = “all”)

The "all" option (default) means easystats then broom.

Formatting numeric entries

By default, LaTeX tables enclose all numeric entries in the command from the siunitx package. To prevent this behavior, or to enclose numbers in dollar signs (for LaTeX math mode), users can call:

options(modelsummary_format_numeric_latex = “plain”)

options(modelsummary_format_numeric_latex = “mathmode”)

A similar option can be used to display numerical entries using MathJax in HTML tables:

options(modelsummary_format_numeric_html = “mathjax”)

LaTeX preamble

When creating LaTeX via the tinytable backend (default in version 2.0.0 and later), it is useful to include the following commands in the LaTeX preamble of your documents. These commands are automatically added to the preamble when compiling Rmarkdown or Quarto documents, except when the modelsummary() calls are cached.

\usepackage{tabularray}
\usepackage{float}
\usepackage{graphicx}
\usepackage[normalem]{ulem}
\UseTblrLibrary{booktabs}
\UseTblrLibrary{siunitx}
\newcommand{\tinytableTabularrayUnderline}[1]{\underline{#1}}
\newcommand{\tinytableTabularrayStrikeout}[1]{\sout{#1}}
\NewTableCommand{\tinytableDefineColor}[3]{\definecolor{#1}{#2}{#3}}

Examples

library("modelsummary")

library(modelsummary)

# The left-hand side of the formula describes rows, and the right-hand side
# describes columns. This table uses the "mpg" variable as a row and the "mean"
# function as a column:

datasummary(mpg ~ mean, data = mtcars)

	mean
mpg	20.09

# This table uses the "mean" function as a row and the "mpg" variable as a column:

datasummary(mean ~ mpg, data = mtcars)

	mpg
mean	20.09

# Display several variables or functions of the data using the "+"
# concatenation operator. This table has 2 rows and 2 columns:

datasummary(hp + mpg ~ mean + sd, data = mtcars)

	mean	sd
hp	146.69	68.56
mpg	20.09	6.03

# Nest variables or statistics inside a "factor" variable using the "*" nesting
# operator. This table shows the mean of "hp" and "mpg" for each value of
# "cyl":

mtcars$cyl <- as.factor(mtcars$cyl)
datasummary(hp + mpg ~ cyl * mean, data = mtcars)

	4	6	8
hp	82.64	122.29	209.21
mpg	26.66	19.74	15.10

# If you don't want to convert your original data
# to factors, you can use the 'Factor()'
# function inside 'datasummary' to obtain an identical result:

datasummary(hp + mpg ~ Factor(cyl) * mean, data = mtcars)

	4	6	8
hp	82.64	122.29	209.21
mpg	26.66	19.74	15.10

# You can nest several variables or statistics inside a factor by using
# parentheses. This table shows the mean and the standard deviation for each
# subset of "cyl":

datasummary(hp + mpg ~ cyl * (mean + sd), data = mtcars)

	4		6		8
	mean	sd	mean	sd	mean	sd
hp	82.64	20.93	122.29	24.26	209.21	50.98
mpg	26.66	4.51	19.74	1.45	15.10	2.56

# Summarize all numeric variables with 'All()'
datasummary(All(mtcars) ~ mean + sd, data = mtcars)

	mean	sd
mpg	20.09	6.03
disp	230.72	123.94
hp	146.69	68.56
drat	3.60	0.53
wt	3.22	0.98
qsec	17.85	1.79
vs	0.44	0.50
am	0.41	0.50
gear	3.69	0.74
carb	2.81	1.62

# Define custom summary statistics. Your custom function should accept a vector
# of numeric values and return a single numeric or string value:

minmax <- function(x) sprintf("[%.2f, %.2f]", min(x), max(x))
mean_na <- function(x) mean(x, na.rm = TRUE)

datasummary(hp + mpg ~ minmax + mean_na, data = mtcars)

	minmax	mean_na
hp	[52.00, 335.00]	146.69
mpg	[10.40, 33.90]	20.09

# To handle missing values, you can pass arguments to your functions using
# '*Arguments()'

datasummary(hp + mpg ~ mean * Arguments(na.rm = TRUE), data = mtcars)

	mean
hp	146.69
mpg	20.09

# For convenience, 'modelsummary' supplies several convenience functions
# with the argument `na.rm=TRUE` by default: Mean, Median, Min, Max, SD, Var,
# P0, P25, P50, P75, P100, NUnique, Histogram

#datasummary(hp + mpg ~ Mean + SD + Histogram, data = mtcars)

# These functions also accept a 'fmt' argument which allows you to
# round/format the results

datasummary(hp + mpg ~ Mean * Arguments(fmt = "%.3f") + SD * Arguments(fmt = "%.1f"), data = mtcars)

	Mean	SD
hp	146.688	68.6
mpg	20.091	6.0

# Save your tables to a variety of output formats:
f <- hp + mpg ~ Mean + SD
#datasummary(f, data = mtcars, output = 'table.html')
#datasummary(f, data = mtcars, output = 'table.tex')
#datasummary(f, data = mtcars, output = 'table.md')
#datasummary(f, data = mtcars, output = 'table.docx')
#datasummary(f, data = mtcars, output = 'table.pptx')
#datasummary(f, data = mtcars, output = 'table.jpg')
#datasummary(f, data = mtcars, output = 'table.png')

# Display human-readable code
#datasummary(f, data = mtcars, output = 'html')
#datasummary(f, data = mtcars, output = 'markdown')
#datasummary(f, data = mtcars, output = 'latex')

# Return a table object to customize using a table-making package
#datasummary(f, data = mtcars, output = 'tinytable')
#datasummary(f, data = mtcars, output = 'gt')
#datasummary(f, data = mtcars, output = 'kableExtra')
#datasummary(f, data = mtcars, output = 'flextable')
#datasummary(f, data = mtcars, output = 'huxtable')

# add_rows
new_rows <- data.frame(a = 1:2, b = 2:3, c = 4:5)
attr(new_rows, 'position') <- c(1, 3)
datasummary(mpg + hp ~ mean + sd, data = mtcars, add_rows = new_rows)

	mean	sd
1.00	2.00	4.00
mpg	20.09	6.03
2.00	3.00	5.00
hp	146.69	68.56