R-CMD-check CRAN status Codecov test coverage DOI:10.32614/RJ-2021-053


The {gtsummary} package provides an elegant and flexible way to create publication-ready analytical and summary tables using the R programming language. The {gtsummary} package summarizes data sets, regression models, and more, using sensible defaults with highly customizable capabilities.

By leveraging {broom}, {gt}, and {labelled} packages, {gtsummary} creates beautifully formatted, ready-to-share summary and result tables in a single line of R code!

Check out the examples below, review the vignettes for a detailed exploration of the output options, and view the gallery for various customization examples.


The {gtsummary} package was written as a companion to the {gt} package from RStudio. You can install {gtsummary} with the following code.


Install the development version of {gtsummary} with:



Summary Table

Use tbl_summary() to summarize a data frame.


Example basic table:


# summarize the data with our package
table1 <- 
  trial %>%
  tbl_summary(include = c(age, grade, response))

There are many customization options to add information (like comparing groups) and format results (like bold labels) in your table. See the tbl_summary() tutorial for many more options, or below for one example.

table2 <-
    include = c(age, grade, response),
    by = trt, # split table by group
    missing = "no" # don't list missing data separately
  ) %>%
  add_n() %>% # add column with total number of non-missing observations
  add_p() %>% # test for a difference between groups
  modify_header(label = "**Variable**") %>% # update the column header

Regression Models

Use tbl_regression() to easily and beautifully display regression model results in a table. See the tutorial for customization options.

mod1 <- glm(response ~ trt + age + grade, trial, family = binomial)

t1 <- tbl_regression(mod1, exponentiate = TRUE)

Side-by-side Regression Models

You can also present side-by-side regression model results using tbl_merge()


# build survival model table
t2 <-
  coxph(Surv(ttdeath, death) ~ trt + grade + age, trial) %>%
  tbl_regression(exponentiate = TRUE)

# merge tables
tbl_merge_ex1 <-
    tbls = list(t1, t2),
    tab_spanner = c("**Tumor Response**", "**Time to Death**")

Review even more output options in the table gallery.

gtsummary + R Markdown

The {gtsummary} package was written to be a companion to the {gt} package from RStudio. But not all output types are supported by the {gt} package. Therefore, we have made it possible to print {gtsummary} tables with various engines.

Review the gtsummary + R Markdown vignette for details.

Save Individual Tables

{gtsummary} tables can also be saved directly to file as an image, HTML, Word, RTF, and LaTeX file.

tbl %>%
  as_gt() %>%
  gt::gtsave(filename = ".") # use extensions .png, .html, .docx, .rtf, .tex, .ltx

Additional Resources

Cite gtsummary

> citation("gtsummary")

To cite gtsummary in publications use:

  Sjoberg DD, Whiting K, Curry M, Lavery JA, Larmarange J. Reproducible summary tables with the gtsummary package.
  The R Journal 2021;13:570–80. https://doi.org/10.32614/RJ-2021-053.

A BibTeX entry for LaTeX users is

    author = {Daniel D. Sjoberg and Karissa Whiting and Michael Curry and Jessica A. Lavery and Joseph Larmarange},
    title = {Reproducible Summary Tables with the gtsummary Package},
    journal = {{The R Journal}},
    year = {2021},
    url = {https://doi.org/10.32614/RJ-2021-053},
    doi = {10.32614/RJ-2021-053},
    volume = {13},
    issue = {1},
    pages = {570-580},


Big thank you to @jeffreybears for the hex sticker!

Please note that the {gtsummary} project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms. Thank you to all contributors!