Need help with gtsummary?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

495 Stars 51 Forks Other 1.5K Commits 20 Opened issues


Presentation-Ready Data Summary and Analytic Result Tables

Services available


Need anything else?

Contributors list

Codecov test
coverage R build
status CRAN
status Lifecycle:
maturing <!-- badges: end -->


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.

  • Summarize data frames or tibbles easily in R. Perfect for presenting descriptive statistics, comparing group demographics (e.g creating a Table 1 for medical journals), and more. Automatically detects continuous, categorical, and dichotomous variables in your data set, calculates appropriate descriptive statistics, and also includes amount of missingness in each variable.

  • Summarize regression models in R and include reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers (i.e. Odds Ratio and Hazard Ratio).

  • Customize gtsummary tables using a growing list of formatting/styling functions. Bold labels, italicize levels, add p-value to summary tables, style the statistics however you choose, merge or stack tables to present results side by side… there are so many possibilities to create the table of your dreams!

  • Report statistics inline from summary tables and regression summary tables in R markdown. Make your reports completely reproducible!

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


to summarize a data frame.


Example basic table:

# make dataset with a few variables to summarize
trial2 % select(age, grade, response, trt)

summarize the data with our package


There are many customization options to add information (like comparing groups) and format results (like bold labels) in your table. See the

tutorial for many more options, or below for one example.

table2 %
  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


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


Side-by-side Regression Models

You can also present side-by-side regression model results using


build survival model table

t2 % tbl_regression(exponentiate = TRUE)

merge tables


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, RTF, LaTeX, and Word file.

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

For a Word file, use

tbl %>%
  as_flex_table() %>%


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!
@ablack3, @aghaynes, @ahinton-mmc, @albertostefanelli, @alexis-catherine, @anaavu, @angelgar, @arbet003, @arnmayer, @asshah4, @awcm0n, @barthelmes, @BeauMeche, @benediktclaus, @calebasaraba, @CarolineXGao, @CodieMonster, @ctlamb, @davidgohel, @davidkane9, @dax44, @ddsjoberg, @DeFilippis, @denis-or, @djbirke, @emilyvertosick, @ercbk, @gjones1219, @gorkang, @GuiMarthe, @hughjonesd, @iaingallagher, @IndrajeetPatil, @IsadoraBM, @j-tamad, @jalavery, @jeanmanguy, @jemus42, @jennybc, @JeremyPasco, @JesseRop, @jflynn264, @jjallaire, @joelgautschi, @JonGretar, @juseer, @jwilliman, @karissawhiting, @khizzr, @kmdono02, @larmarange, @leejasme, @ltin1214, @lucavd, @maia-sh, @margarethannum, @Marsus1972, @matthieu-faron, @mbac, @MelissaAssel, @michaelcurry1123, @moleps, @MyKo101, @oranwutang, @Pascal-Schmidt, @proshano, @raphidoc, @ryzhu75, @sammo3182, @sbalci, @simonpcouch, @slb2240, @slobaugh, @StaffanBetner, @storopoli, @TarJae, @tjmeyers, @tormodb, @UAB-BST-680, @uriahf, @zabore, @zachariae, @zeyunlu, @zlkrvsm, and @zongell-star

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.