tinytable is a small but powerful R package to draw beautiful tables in a variety of formats: HTML, LaTeX, Word, PDF, PNG, Markdown, and Typst. The user interface is minimalist and easy to learn, while giving users access to powerful frameworks to create endlessly customizable tables.



There are already many excellent table-drawing packages in the R ecosystem. Why release a new one? As the maintainer of modelsummary, I needed a table-drawing package which was:

  • Simple: Streamlined, consistent, and uncluttered user interface, with few functions to learn.
  • Flexible: Expressive frameworks to customize tables in HTML and LaTeX formats.1
  • Zero-dependency: Avoid importing any other R package.2
  • Concise: Draw beautiful tables without typing a lot of code.
  • Safe: User inputs are checked thoroughly, and informative errors are returned early.
  • Maintainable: A small code base which does not rely on too many complex regular expressions.
  • Readable: HTML and LaTeX code should be human-readable and editable.
  • Free: This package will always be free. Tiny tables for a tiny price!

To achieve these goals, the design philosophy of tinytable rests on three pillars:

  1. Data is separate from style. The code that this package creates keeps the content of a table separate from the style sheet that applies to its cells. This is in contrast to other R packages that modify the actual text in each cell to style it. Keeping data and style separate allows tinytable to create human-readable files which are easy to edit, debug, and extend. It also enables developers to keep a simpler code base, with minimal use of messy regular expressions.

  2. Flexibility. Users’ needs are extremely varied, and a table-drawing package must be flexible enough to accomodate different ideas. To achieve this, tinytable builds on battle-tested and versatile frameworks like Bootstrap for HTML and tabularray for LaTeX.

  3. Lightweight is the right weight. Some of the most popular table-drawing packages in the R ecosystem are very heavy: A single library() call can sometimes load upwards of 65 R packages. In contrast, tinytable imports zero 3rd party R package by default.


Install the stable version from CRAN:


tinytable is a relatively new package with rapid development. If you want to benefit from the latest features—showcased on the package website—you may want to install the development version from Github.


Restart R completely for the installation to take effect.

Get started

Alternative packages

Several people have asked me how tinytable compares to alternative table-drawing packages in R. And indeed, there are many fantastic table-drawing packages already out there. Most of theses alternatives have features that tinytable does not (yet) support. If you don’t find what you need in tinytable, I recommend you try one of these:

Here are a few totally biased (and possibly unfair) comments about each of them.

The first difference between tinytable and alternatives is that tinytable covers much of the same functionality without loading any other R package by default. I think it is very important for R package developers to have access to a table-drawing package that does not force them to import half of the tidyverse. In my view, this service to developers alone justifies writing a new package.

Now let’s consider alternatives one by one.

gt (65 dependencies) is an amazingly powerful table-drawing package; possibly the most powerful in R. I like it a lot, and it is the one I recommend if you don’t find the features you need in tinytable. The reasons I don’t personally use gt on a day-to-day basis are entirely subjective. First, and least important, I find its syntax very verbose: customizing any aspect of a table always seems to take many keystrokes. Second, and this is obviously a reflection of my own limitations, but I have never quite figured out how gt actually works; it has so many exported functions (180+!) that I get lost. gt is more powerful than tinytable, but that power comes at the price of complexity. One goal of tinytable is to let you do 98% of what you need by learning 4 simple functions; then you can use a bit of CSS or LaTeX if you need extreme customization.

kableExtra (49 dependencies) is a very flexible package with amazing documentation. Before writing tinytable, I actually made a few very minor contributions and bug fixes to kableExtra. In the end, however, I concluded that while the package is great, its code base is too hard to maintain and extend. The challenge on the backend is that kableExtra accepts tables drawn as raw strings by the knitr package, and then modifies them using a series of complex regular expressions. The author has done truly amazing work, but it’s just a really difficult strategy to implement, scale, and maintain. (Incidentally, kableExtra is not very actively developed anymore.) Finally, I really like the concept of separating styling from data, and kableExtra modifies the content of every cell to style its content. That sometimes makes LaTeX and HTML code pretty hard to read and edit.

huxtable (29 dependencies) is an interesting and powerful-looking package, but I know it less well than the others. The key design decision of the author is that each feature is implemented with a distinct function. I understand that design impulse: going through the documentation of a function with 50 arguments can be daunting. That said, I feel that sifting through a manual with 300+ exported functions also makes for a steep learning curve. In addition, I prefer HTML and LaTeX code to be human-readable, in case I need to tweak them by hand before publication; huxtable tables are not that.

DT (43 dependencies) is nice, but it only draws HTML table, so that’s a non-starter for me. I need HTML, LaTeX, Word, PNG, PDF, and Typst output, depending on the project I am working on.

flextable (43 dependencies) is nice, but it does not support LaTeX, and I need that format for “real work.”

At this point, it’s useful to point out that there are also many packages to compute statistics and build tables (ex: modelsummary, gtsummary, table1). Many of those packages delegate the actual drawing of the tables (ie: lines and colors) to one of the table-drawing packages listed above. In that sense, tinytable should be seen as more of a complement than an alternative to data summary packages. The goal of tinytable is to help users and developers convert data frames into beautiful tables easily. What people put in those tables is outside the scope of tinytable. If you are interested in a package to create data summaries and regression tables/plots, please check out my modelsummary package: https://modelsummary.com

Did I miss your favorite package? Drop me a note and I’ll add it to the list.


  1. Other formats like Markdown and Typst are also available, but less flexible.↩︎

  2. Some extra packages can be imported to access specific functionality, such as integration with Quarto, inserting ggplot2 objects as inline plots, and saving tables to PNG images or PDF documents.↩︎