How to get a nice table in R?

→ gtExtras : more styling for gt It allows to create even more sophisticated and visually appealing tables. It comes with a set of themes to make your table good-looking with just one more line of code. It provides functions to easily add plots in table cells. It also has helper functions to help with colors and icons.

How can I make my table prettier?

Use colors and lines to help readers navigate your table . Highlight important cells by applying a subtle background color or group related values by creating thicker lines. Include the source of your data to make your table look more professional and allow readers to analyze the topic more deeply.

What is the best table package in R?

flextable (Gohel and Skintzos 2023) and huxtable (Hugh-Jones 2024) : If you are looking for a table package that supports the widest range of output formats, flextable and huxtable are probably the two best choices.

Can you create tables in R?

Tables are often essential for organzing and summarizing your data, especially with categorical variables. When creating a table in R, it considers your table as a specifc type of object (called “table”) which is very similar to a data frame.

How do you set a classy table?

Place bread-and-butter plates above the forks, to the left of the place setting and don't remove them until the dessert course. Stemware is set above and to the right of the dinner plate. The water glass stands above the dinner knife, white wine to its right, and red wine top center.

How do you make a table look aesthetic?

Pick colours and things you like for aesthetic study table decoration. Use colourful pens, and stylish notebooks, and add cute decorations . A small plant can bring freshness, and keeping things organised with trays or containers makes it look neat.

What makes a table more beautiful and attractive?

Matching the hues can give your table a huge makeover. You can use neutral shades with earthy tones to give your table warmth.

Is data table better than tidyverse?

table and tidyverse . In cases when we are handling very large dataset, data. table would be a good choice since it runs extremely fast . In cases when we are not requiring the speed so much, especially when collaborating with others, we can choose tidyverse since its code is more readable.

What is the difference between Dataframes and tables in R?

frame in R is similar to the data table which is used to create tabular data but data table provides a lot more features than the data frame so, generally, all prefer the data. table instead of the data. frame.

What does table () in R do?

Table function (table())in R performs a tabulation of categorical variable and gives its frequency as output . It is further useful to create conditional frequency table and Proportinal frequency table. This recipe demonstrates how to use table() function to create the following two tables: Frequency table.

How do I get the best table?

When you arrive at the restaurant, dress smartly and look the part - you are far more likely to get the best table if you dress to impress. Arrive early, or at least on time, and be polite to everyone when you arrive. Then ask again about the table if you've requested a specific one. If you are late, you might lose it.

How do you make a nice table in markdown?

A table is an arrangement of data in rows and columns. To add a table in Markdown, use the vertical line | to separate each column, and use three or more dashes --- to create each column's header . A vertical line should also be added at either end of the row. The output will look exactly the same.

How to Make Beautiful Tables in R (2024)

Updated March 12, 2022 with info on the reactablefmtr and gtextras packages.

Want to learn to make beautiful tables?

It doesn't matter how good your data analysis is if you don't effectively communicate your results. In most reports, communication of results happens through a combination of data visualization and tables. Along with narrative text, these make up the bulk of content used to communicate results.

Clear writing is a topic for another venue. Data visualization in R is a huge topic (and one covered expertly in Kieran Healy's Data Visualization: A Practical Introduction and Claus Wilke's Fundamentals of Data Visualization). But what about tables? Fortunately for R users, there are many ways to create beautiful tables that effectively communicate your results.

Customizing Default Table Output in RMarkdown

If you are using RMarkdown (and, if you're not, you should really consider it), any data frame that you call in a code chunk is displayed using the data frame printing method set in your YAML. As Yihui Xie puts it, "printing objects in R code chunks basically emulates the R console." This default output leaves much to be desired. "Table" output with fixed-width fonts like this never inspired anyone to take action.

It is quite easy to improve this output. You can change the default data frame print method in the YAML to one of the following options.

Of these, the one most likely to improve your table output is paged, which creates paged tables that work well when you have particularly long tables and want to give users the ability to look at pieces of the output:

My Favorite R Packages to Make Tables

There are also many packages that provide functions to produce nicely formatted tables. Here are some of the packages I have used that produce tables that look good and effectively communicate results.

gt

gt is a new(ish) package. It “is designed to be both straightforward yet powerful … [with] an emphasis is on simple functions for the everyday display table needs.” The package has functions designed to do things like:

Modify the locations of outputs
Format text as well as background shading
See Also
Top 7 Packages for Making Beautiful Tables in R
Add titles, subtitles, captions, etc.

The gt package provides a general philosophy of tables (similar to the grammar of graphics theory that underlies the ggplot2 package) that enables it to be easy to use (with some practice) and extremely flexible.

Learn more about gt

gtextras

There’s also a package called gtextras that provides add-ons for the gt package. This package, by Thomas Mock, provides some nice themes like this modeled on New York Times tables.

The package also lets you add visualizations into tables, including sparklines and bar plots.

Learn more about gtextras.

kable + kableExtra

The kableExtra package builds on the kable output from the knitr package. As author Hao Zhu puts it:

The goal ofkableExtrais to help you build common complex tables and manipulate table styles. It imports the pipe%>%symbol frommagrittrand verbalize all the functions, so basically you can add “layers” to a kable output in a way that is similar withggplot2andplotly.

Sharla Gelfand used the kableExtra package in a report she did for the College of Nurses of Ontario and loved it.

Learn more about kableExtra

formattable

Kun Ren's formattable package" is designed for applying formatting on vectors and data frames to make data presentation easier, richer, more flexible and hopefully convey more information."

One of the most unique features is the ability to add colors, background shading, bars, and other features that move tables beyond hulking blocks of text.

If you're looking for an example of the formattable package in use, Laura Ellis has a really nice walkthrough.

Learn more about formattable

DT

The main appeal of the DT package is its ability to add filtering, pagination, and sorting to HTML tables. Users can slice, scroll through, and arrange tables in ways that help them to make sense of your results.

Learn more about DT

reactable

I had not heard of this package until Mara Averick tweeted about it recently. Though I haven't used it, the docs look incredible. Like the DT package, it offers the ability to sort and filter data. It's also much more visually appealing than the DT package. One of the examples (below) looks exactly like the gorgeous tables made by FiveThirtyEight.

Learn more about reactable

reactablefmtr

The reactable package can be a bit more challenging to work with. To simplify the process of creating tables in reactable, Kyle Cuilla developed the reactablefmtr package. As Kyle puts it:

The {reactablefmtr} package simplifies and enhances the styling and formatting of tables built with the {reactable}Rpackage. The {reactablefmtr} package provides many conditional formatters that are highly customizable and easy to use.

Among other things, the reactablefmtr package makes it easier to conditionally add colors to tables, add interactive sparklines, use custom themes, embed images in tables, and save tables in PNG and HTML format.

Learn more about reactablefmtr

flextable

The above packages are designed to produce HTML tables. If you are knitting to Word, your best for tables is the flextable package (though the tables this package produces can also be embedded within HTML and PDF outputs). Designed by David Gohel, the flextable package provides a straightforward syntax to shape the content and format of your tables.

Learn more about flextable

Packages Recommended by Others

The above packages are ones that I've used and had good success with. When I put the call out on Twitter for other packages to make tables in R, I got some promising-looking responses!

huxtable

The huxtable package produces:

LaTeX and HTML tables, with a friendly, modern interface. Features include control over text styling, number format, background color, borders, padding and alignment. Cells can span multiple rows and/or columns. Tables can be manipulated with standard R subsetting or dplyr functions.

Learn more about huxtable

rhandsontable

Like the DT package, the rhandsontable package gives users the ability to manipulate data in tables. It comes with "powerful features like data validation, sorting, grouping, data binding, formula support or column ordering." Working with tables feels like viewing data in Excel, which can be helpful for users used to working with Microsoft's ubiquitous spreadsheet program. Users can even make changes to data in tables made with this package.

Learn more about rhandsontable

pixiedust

The fantastically-named pixedust package is designed to produce a specific type of table: model output that has been tidied using the broom package. Using pixiedust is a three-step process:

Run your model using a base R function (e.g. lm for a linear model)
Use the tidy function from the broom package to convert the results into a tidy format
Use the pixiedust package (the sprinkle_ set of functions in particular) to improve the output, removing “stats-speak” and putting it into a “format that is suitable for publication or submission to a client.”

The sprinkle_ functions enable you to do things like removing excess decimal places, convert p-values to not use scientific notation, and more.

If you want to ensure that end users read and understand the results of your complex statistical analyses, this looks like a great package!

Learn more about pixiedust

There are surely more table packages that I've missed (in wrapping up this post, I came across this list from the RStudio RMarkdown tutorials), but this should give you a good place to start in making your tables more beautiful and more effective.

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