what is presentation r

Making a Presentation in R: Getting started

Many of us have faced this dilemma: it’s the night before a big presentation and you want to make sure you are prepared. However, as you are going through the slides, you notice there is an error in your analyses and you need to update the results on ALL of your slides. So the night before this big presentation, you end up spending more time trying to manually update the slides one by one than preparing for the presentation itself. As someone who is always searching for ways to automate the manual, error-prone parts of my work so I can spend more time on the important things, I was delighted to learn that there is an option to reduce some of the burden of creating and updating slides by creating presentations in R. In this post, along with ones to follow, I’ll walk through how to do this. First, I’ll highlight some of the biggest benefits of learning how to create presentations in R.

If you use R to run your analyses, you can easily integrate your graphics & results into your presentation. Instead of having to manually copy and paste the results of your statistical test or the output from ggplot, you can simply write a line of code or two to add those into your presentation. More notably, this means that if you need to update the slides in the future, you will be able to do so painlessly - instead of having to go in slide-by-slide and updating each.

With R, you’ll spend less time spent messing around with formatting. For instance, let’s say I want to have all of the images on my slides to be a certain size. It’s much easier to make those changes using code compared to setting the image size one each slide manually

Now that I’ve hopefully convinced you of the benefits of using R for presentations, you may be wondering…

What options do I have to make presentations in R?

xaringan presentations

reveal.js presentations

ioslides presentations

beamer presentations

slidy presentations

good old powerpoint presentations

I decided to go with xaringan because I’ve been a fan of Yihui Xie’s (creator of the xaringan package) work with other packages and was also persuaded by this post where he explains why he prefers remark.js (which is used behind the scenes to render the presentation) for xaringan presentations over other presentation frameworks. The rest of this post will be focused on setting up a presentation using the xaringan package.

To be able to create a new xaringan template, we need to install the xaringan package using install.packages("xaringan")

Once xaringan is installed, you can create the new template from the drop-down menu on RStudio (assuming you are using RStudio): File -> RMarkdown. A new window should appear, with four possible options for creating the new RMarkdown file: “Document,” “Presentation,” “Shiny,” or “From Template”. Click “From Template” and at the bottom of the list you should see “Ninja Presentation”.

Now, you should have a template slide deck that you can edit right away! Super easy. It can even be knitted immediately, which should show up right next to your code under the viewer tab - make sure to save it first!

I would highly recommend taking a few minutes to just look at the code and the presentation to see how the input affects the output.

So for instance, I immediately notice that there is a YAML header with a few unique parameters, presumably specific to xaringan. For instance, under output , the xaringan::mood_reader has the parameter highlightStyle set to “github.” Since the presentation suggests that the YAML header inputs correspond to the title slide (e.g., YAML header title is set to “Presentation Ninja”), I went ahead and changed title, author, and date for my purposes, leaving other YAML settings as they were:

So now that I’ve made those changes, I can knit again, and my title page now has my name, along with an updated date & title!

What’s great is that the template that is created is actually basically a tutorial. So you can look through the slides and follow along!

• The Infinite Moon Reader RStudio Addin mentioned on slide 5 is a great idea since you’ll be able to get real-time visual feedback as you update the code (that is, every time you SAVE the code, the visual feedback will be updated). To use this AddIn, you need to click the highlighted “Addins” drop-down here and underneath the tab for xaringan (which will likely be all the way at the bottom of menu because it is ordered alphabetically):

It’s also worth noting that the .Rmd document uses Markdown - a tool I mentioned in a previous post - as I mentioned before, you can see this link for a great introductory guide on how to format text using Markdown, which allows you to format certain pieces of text (e.g., italicize the title of your position, link text to a URL)

As I mentioned at the beginning, xaringan has remark.js render the presentation in your browser. So to be able to use xaringan for your presentations, you should have a basic understanding of remark.js. I’d recommend checking out the link provided in the knitted presentation, along with this page . In the following section, I’ll briefly describe the fundamentals of creating and editing xaringan slides.

Creating and editing slides in xaringan

Creating new slides.

To create a new slide, insert three dashes, like so:

Centering slides

Markdown may not be as flexible as you need it to be, which is why there are Markdown extensions included. So for instance, if I want to center align my entire slide - I would use the class property as follows:

Background images

Relatedly, I can include background images using a couple of lines of code. Important: background images need to be between the three dashes indicating you are starting a new slide and the name of your slide if you have one (which is indicated using a hashtag, so “Hello world” is the name for the slide below) for the image to be displayed. So for instance, if there is an image at a publicly accessible link, you can use url(insert URL for image) :

If you have an image on your computer that you want to include in the presentation, you’ll need to store the image(s) in the same folder as the .Rmd file for your slides or as a subfolder of the folder as your slides file (apparently for security reasons, as suggested here ). For instance, if I want to include a file of a picture called “widen-gap.jpg” that is stored on my computer, I’d need to store it in the same location as my .Rmd slides file. Then, if I want to populate the image when I knit the presentation and I put the image in the same folder as the .Rmd file, I would call:

The “libs” directory is the default lib_dir option in the YAML header as suggested at the end of this issue page , so I would recommend putting the image somewhere in this folder if you don’t want it in the main directory with your slides .Rmd file. Let’s say you created a subfolder called “img” within the “libs” directory automatically included with xaringan holding the .Rmd file. You would call:

Incremental slides

To make bullets or images appear incrementally, kind of like slide animations, use the template property. To be able to use the template property, you need to create a name for the slide that can later be referenced. So for instance, you can created the first slide as follows:

Then, the slide with the second bullet can be created as follows:

So when you go to knit the final document, the compiled slide with bullet 2 will contain bullet 1 as well.

There is actually a shortcut to creating these templates, instead of having to create names & referencing the previous slide based on its name, you can use two dashes between slides to indicate the you want the latter slide to use the former slide as a template, so using the example above:

More details on creating incremental slides here

Default layouts

There’s an option to create a slide that can set the default layout throughout all of your slides. To me, it seems this would be especially useful if you need to have a company’s logo on all of your slides throughout the presentation. To create this default layout, you can set the layout property to true on the slide you want to be used as the default. So for instance, if I wanted the image from the xaringan slides to be on all of my slides, I would write the following at the beginning of the presentation (or wherever you want the logo to start showing up, since the layout will only be applied to slides presented after the layout is set):

Changing theme

If you want to change things like the font that are pre-set, there are a couple of options:

• you can edit the CSS (the difficult way, unless you, unlike me, have previous experience with CSS)
• you can use themes that R users have created. To explore some theme options, run:

Let’s say I want to change the theme to rladies .

I can edit the css argument of the YAML header as follows to set the theme as rladies , along with the associated font:

Hiding slides

Finally, if you need to hide a slide from the presentation but don’t want to delete all of the work you put into it, you can set the exclude property to true at the top of the slide to hide that specific slide, like so:

Adding figures and results

Now that we’ve covered some of what I think are the most relevant features of remark.js to get you up and running with creating and editing slides, we’ll move onto the part that I’m particularly excited about and one of the main reasons I wanted to create presentations in R: seamless integration of code with the rest of the presentation.

Let’s say I want to include the results of a logistic regression model. To present these results, you use the same basic structure you would use in a normal RMarkdown document to include code in the text-based parts. That is, you include the code you want to run within two backtick marks after you indicate the language you want to use (e.g., r ). So for example, in one of my presentations, I included the following code in the .Rmd document:

which is knitted in the presentation as follows:

There are two options for including plots of your data in a Xaringan presentation:

• The first option is: You can save the plot as a file in the folder or subfolder associated with the .Rmd slides file and then call the image in using the include_graphics() method described above:
• The second option is: You can just import the data and run the code within the presentation itself when it knits! Just make sure to store the data file that will be used in the same folder/subfolder as the .Rmd slides file. For example, if I had the data file in a subfolder of the libs subdirectory associated with my slide .Rmd file:

You can either show the code you used to create the plots, OR you can hide the code using {r, echo = F} (which is most likely what you will be using unless everyone you are presenting to knows R and wants to double-check your work…). If you want code-hiding to be your default option across all slides, you can insert the code I’ve been using at the top of nearly all of my RMarkdown documents that I plan to present to an audience:

One final note about figures: it took me a while to adjust the figure size (i.e., to make sure the figure didn’t look too large or small). The settings for the figure size that seemed to work the best (at least for me) were: fig.width=10, fig.height=5, dpi=300 . Just enter that into the header of the code chunk, and of course feel free to adjust as needed.

You can also show tables of your data or models! 😄 Usually, the kable or DT package will work beautifully. One of the useful benefits of integrating your code and presentation is that you can interact with the data live! For instance, let’s say someone asks you what the minimum value of a certain variable is. If you’ve added a table of the dataset using the DT package for instance, you can actually click the sort button on the table in the presentation and answer the question that way.

Presenting and sharing slides

Slide transitions.

You can transition from slide to slide like pretty much any presentation. There are also a number of awesome keyboard shortcuts that I highly recommend checking out here

Presenter notes

I hadn’t even thought of this before, but there’s a presenter mode! Which I’m now realizing is incredibly important for most of my presentations, since I almost always have notes. To create notes for yourself, insert three question marks in a row:

Once you have the final version of your presentation open in your browser, you want to make sure that your audience doesn’t see your notes - so the way to have them only see the presentation is to open a cloned version of the presentation in a new window which allows you to change slides both in the version with the presenter view and the presentation view with slide notes simultaneously. To create this clone, press “c” and a new window should appear. Press the left and right arrow on your keyboard and you’ll see that both windows change slides at the same time! Super cool. Make sure that when you are presenting your slide using screen sharing, share the new window that popped up when you pressed “c” and not the original tab with your presentation, since that is where your presentation notes will be. Now that you are sharing your presentation, you can simply press “p” on your keyboard while in the original tab (not the new window that you recently opened) to open presenter mode (and to close it, just press “p” again).

A quick note about presenter notes: if you do not have more than one display, I would double-check that you are able to share your screen without your audience seeing your notes. I know there are certain platforms like Google slides that lets you use your notes while you are only sharing one screen, but it may be difficult to present your slides without your audience seeing your notes with one screen using Xaringan from what I can tell.

Converting to different formats

It looks like there is an option to convert your slides to a .pptx and other formats in case you need to send a specific document type over before your big presentation for whatever reason. See this package for instructions on how to create different document types (e.g., png, pdf, pptx, etc.) from your .Rmd file. If your slides are relatively simple (e.g., they don’t include interactive graphics), you should be able to convert to many output types without a hitch. However, if you are including interactive graphics or other advanced features (e.g., panels from the xaringanExtra package ), you should set complex_slides = TRUE when you call one of the build_*() functions. Although I will admit, when I tested this out, it did not seem to completely capture what the original .html file was doing with the cooler features, so I personally would try to avoid having to convert to .pptx unless absolutely necessary.

If you want to use your slides offline, you can download a copy of remark.js beforehand, since the default option in the xaringan package is to use an online version of the presentation. See instructions on how to accomplish this here .

Issues that popped up

Presenter notes don’t display at the correct time if you place the notes right before the next slide while using incremental slides. Here’s a brief description of this issue: https://github.com/yihui/xaringan/issues/55 . My workaround is to place all of my presenter notes at the top of a slide that is incremental and write “(CLICK)” in the notes when I want to click. There might be a more elegant way around this issue though, so I’d recommend exploring Stack Overflow for other recommendations!

Occasionally incremental slides do not work as expected. For instance, I inserted the two little dash lines when I wanted to add a new bullet to a slide, but it shows both bullets at the same time. After some exploration, I realized that there was trailing white space after the dashed lines! remark.js is extremely sensitive to this, so make sure that you delete all spaces after the two dashed lines to be able to create your incremental slides. This problem also popped up with presenter notes, make sure not to have white space after question marks or the notes will be rendered as regular text. One option to completely avoid this in the future is to go to the top of the RStudio window, click “Tools” -> “Global Options” -> “Code” -> “Saving” -> “Strip trailing horizontal whitespace when saving”

Resources to explore xaringan further

• https://spcanelon.github.io/xaringan-basics-and-beyond/slides/day-01-basics.html?panelset4=remark.js2&panelset5=nhsrtheme2&panelset6=moon-reader2&panelset7=markdown2#1
• https://www.verouden.net/slides/presentation-xaringan/#1
• https://alison.rbind.io/talk/2019-rsc-xaringan/
• https://www.kirenz.com/slides/xaringan-demo-slides.html#1

Keana Richards

Doctoral researcher.

Studying psychology and statistics at the University of Pennsylvania.

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Slide Presentations

R Markdown renders to four presentation formats:

• beamer_presentation - PDF presentations with beamer
• ioslides_presentation - HTML presentations with ioslides
• slidy_presentation - HTML presentations with slidy
• powerpoint_presentation - PowerPoint presentation
• revealjs::revealjs_presentation - HTML presentations with reveal.js

Each format will intuitively divide your content into slides, with a new slide beginning at each first or second level header.

Insert a horizontal rule ( *** ) into your document to create a manual slide break. Create incremental bullets with >- , as in the .Rmd file below, which is available here on RStudio Cloud.

Continue to Dashboards

Mastering R presentations

Do you want to know how to make elegant and simple reproducible presentations? In this talk, we are going to explain how to do presentations in different output formats using one of the easiest and most exhaustive statistical software, R. Now, it is possible create Beamer, PowerPoint, or HTML presentations, including R code, \(\LaTeX\) equations, graphics, or interactive content.

After the tutorial, you will be able to create R presentations on your own with R Markdown in RStudio. But don’t worry if you don’t know a lot of R Markdown, because it’s really simple to use it with RStudio and you will discover the keys to master the language.

We have several options to create amazing technical presentations in pdf format with tools like PowerPoint or \(\LaTeX\) . But the truth is that when we want to generate a full and complete document with graphs, code, and text, then we invest more time in the appearance than in the content itself, or learning how to add content easily. So here I want to show you a good alternative using R. The best feature R has is the flexibility and simplicity of the code to reproduce amazing presentations with little work. To achieve it, R uses Markdown. But, what is exactly Markdown?

What is Markdown?

Markdown is a simple language to write web-based content easy both for writing and reading. The key is that it can be converted to many output formats with a simplified syntax.

Basics of Markdown

Here you have a summary guide of the main style syntax.

Code and syntax highlighting

Blockquotes, tex formula.

Besides these basics, you can to add tables, rulers, links to videos, HTML code, etc. To know more visit the creator’s web site: https://daringfireball.net/projects/markdown/ or this cheatsheet https://github.com/adam-p/markdown-here/wiki/Markdown-Cheatsheet .

R has a specific file format for this type of documents .Rmd . R Markdown has an online book really useful and detailed here https://bookdown.org/yihui/rmarkdown/ . This tool let you build different type of documents like the next ones:

• Documents : HTML, \(\LaTeX\) /PDF, Microsoft Word, Tufte-style handouts
• Interactive documents : HTML Widgets, Shiny
• Dashboards : Gauges, values boxes, HTML Widgets, Shiny, Storyboard
• Books : HTML, PDF, EPUB
• JSS templates, R Journal, Skeleton, CV
• Package Vignettes
• Presentations : Beamer, Slidy, ioslides, reveal.js, xaringan

In the next link, you will find some examples of each one https://rmarkdown.rstudio.com/gallery.HTML . And in this cheatsheet, a good summary of R Markdown is presented https://rmarkdown.rstudio.com/lesson-15.HTML .

How to start

The first step is to get R and RStudio, and install the package rmarkdown with the code

In the last versions you can directly create presentations going to File -> New File -> R Presentation . Then, a .RPres document is going to be created. This is the simplest, really simplest, way to start but my advice is to go quickly to the next step if you want more flexibility in the slides and final appearance.

So going to File -> New File -> R Markdown and selecting the option Presentation , you are going to have different options to create your slides. Selecting any of them, a file like this is automatically generated:

Depending on the final style of the output there are different output options. In the next points, we are going to explain in detail the main features of all them.

• ioslides : the option output: ioslides_presentation
• slidy : the option output: slidy_presentation
• beamer : the option output: beamer_presentation

The R Markdown file

The header is the R Markdown document part where you can set the title, the author, the date, and the output as the image shows:

But at the same time, other options can be determined as follows:

Once the header is completed, you can add any kind of content that you can practically imagine: R code, equations, charts, images, videos etc. In the next points we are going to see how to add each type of content.

In addition to plain text, headers and other Markdown elements, you have the option of inserting R code which will be executed every time you run the file. These parts of the document are called R chunks . To insert an R Chunk you can use RStudio toolbar Insert button or the keyboard shortcut Ctrl + Alt + I on Windows and Cmd + Option + I on macOS.

There are a lot of options referring to how to include tables, text output, figures, etc. For example, to add the option to show in the output the R code before the results you have to add between the brackets {r } the option echo as follows {r echo=TRUE} . By default, the code is not shown.

More options:

• cache : cache results for future knits (default = FALSE)
• cache.path : directory to save cached results in (default = “cache/”)
• child : file(s) to knit and then include (default = NULL)
• collapse : collapse all output into single block (default = FALSE)
• comment : prefix for each line of results (default = ‘##’)
• dependson : chunk dependencies for caching (default = NULL)
• echo : Display code in output document (default = TRUE)
• engine : code language used in chunk (default = ‘R’)
• error : Display error messages in doc (TRUE) or stop render when errors occur (FALSE) (default = FALSE)
• eval : Run code in chunk (default = TRUE)
• message : display code messages in document (default = TRUE)
• results=asis : passthrough results
• results=hide : do not display results
• results=hold : put all results below all code
• tidy : tidy code for display (default = FALSE)
• warning : display code warnings in document (default = TRUE)
• fig.align : ‘lef’, ‘right’, or ‘center’ (default = ‘default’)
• fig.cap : figure caption as character string (default = NULL)
• fig.height, fig.width : Dimensions of plots in inches
• highlight : highlight source code (default = TRUE)
• include : Include chunk in doc after running (default = TRUE)

In the next link you can find more details about R chunks: https://bookdown.org/yihui/rmarkdown/r-code.HTML

There is the chance to add equations to your presentations with MathJax scripts. These are included in HTML documents for rendering \(\LaTeX\) and MathML equations. To control how MathJax is included you have the next options:

• default to use an HTTPS URL from a CDN host (currently provided by RStudio)
• local : to use a local version of MathJax (which is copied into the output directory). Note that when using “local” you also need to set the self_contained option to false.
• URL indicating the location to load MathJax
• null to exclude MathJax entirely.

For example, to use a local copy of MathJax:

To use a self-hosted copy of MathJax:

You have four options to add tables. First one, directly from R Markdown

or the next ones, from R code with the libraries knitr , xtable , or stargazer .

Interactive graphs

In R there are a lot of packages to create interactive graphs. Highcharter is one of them, as well as the well-known HTMLwidgets . Here we have an example of a highcharter graph.

Presentation formats

We just explored the different contents and parts of our R Markdown document. Let’s see what type of output format we can obtain.

Ioslides is a nice R presentation format characterized by the simplicity of the result. There are some features specific from ioslides, such as the display mode

• f : enable fullscreen mode
• w : toggle widescreen mode
• o : enable overview mode
• h : enable code highlight mode
• p : show presenter notes

or the incremental bullets:

Moreover, you can change the presentation size, the text size, or even the transition speed in the header of the document. Specifically, for the transition speed you can set the number of seconds for each slide or use the standard options: default , slower , faster .

For another hand, there is a quick way to add a background image without editing the CSS file,

But if you want to add specific style changes to your presentation, I recommend you to edit the CSS file and add it to the header of the RMarkdown document:

One of the disadvantages of ioslides is that customization is limited compared with other output formats. At the end of this tutorial we explain how to modify by your own a CSS file.

Slidy has more flexibility than ioslides as to appearance and style. Now we are going to see some of the main special features that slidy has.

There is the chance to change the display mode with the next shortcuts;

• c : Show table of contents
• c : Toggles the display of the footer
• a : Toggles display of current vs all slides (useful for printing handouts)
• s : Make fonts smaller
• b : Make fonts larger

And we can adjust the font directly in the header of the document without editing the CSS file:

You will find other interesting features of slidy such as the countdown timer in the footer or the customized footer text that can be easily added with the options duration and footer .

Slidy themes

In slidy, there are different Boostrap themes to use drawn from the Bootswatch theme library. The themes are default , cerulean , journal , flatly , darkly , readable , spacelab , united , cosmo , lumen , paper , sandstone , simplex , and yeti . To add your own style with a CSS file, pass null in the theme parameter.

Moreover, the syntax highlighting style can be specified with the option highlight . Supported styles are default , tango , pygments , kate , monochrome , espresso , zenburn , haddock , and textmate . And you have the option of preventing syntax highlighting passing null to the parameter.

Beamer is a \(\LaTeX\) class to produce presentations and slides. It is so common in academia and so useful to add mathematical formulas and expressions. You can create your own Beamer presentations from R without a deep knowledge of \(\LaTeX\) (only Markdown).

So the first step is to install tex. Tex is a typesetting for complex mathematical formulae used in \(\LaTeX\) . To install it, download tone of the next programs, depending on your OS system: - MikTeX on Windows - MacTeX 2013+ on OS X - TeX Live 2013+ on Linux

Beamer themes are the same that you can find in \(\LaTeX\) . In the next link https://hartwork.org/beamer-theme-matrix/ you have the list of the different available header options related to the appearance and style:

There are other interesting options to create presentations in R such as reveal.js and xaringan. Reveal is very well-known because of the flexibility in the themes and transitions by default, the vertical slides or the possibility to include a web site inside a slide. In this part, we are going to explain how to generate a revealjs file and the main features of this awesome library.

First of all, it is required to install revealjs package

Then, you can directly change in the R Markdown document header the output argument to revealjs_presentation or go to menu File -> New File -> R Markdown -> From template and select reveal.js presentation.

There are some amazing keyboard shortcuts:

- f for fullscreen - o or ESC for overview mode - alt or ( ctrl in Linux) and click an element, to zoom this element - s for speaker view (so pretty!) - B or . to pause the presentation

And there is a lot of variety about appearance and styles. If you want to change how the presentation looks like, you can choose any of the next theme options: default , simple , sky , beige , serif , solarized , blood , moon , night , black , league , and white . And for the syntax highlighting style: default , tango , pygments , kate , monochrome , espresso , zenburn , and haddock . Pass null to prevent syntax highlighting. The way to specify it is the same than the previous presentation types.

In revealjs you can center the text of the slides changing the center option to true, which by default is false, as well as the possibility of modifying the transitions and backgrounds, i.e. how the slide is going to move to the next one. Available transitions and background_transitions are default , fade , slide , convex , concave , zoom or none . Any of these global options can be overriden specifying the data-transition attribute in the header of the slide:

Moreover, Revealjs lets add different backgrounds like color, image, video, and iframe:

Finally, you can specify the level of heading will be used with the slide_level option. For example, if the slide_level is 2, the level-1 headers will be built horizontally and level-2 headers, vertically.

Other interesting features are the great look on touch devices, the fragmented slides, easy to export to pdf, keyboard bindings, or the parallax scrolling background.

References https://CRAN.R-project.org/package=revealjs .

Ninja presentation

The last type of presentations that we are going to see is the xaringan library. It is an R Markdown extension based on the JavaScript library remark.js ( https://remarkjs.com ). This package was originally designed for “ninja”, so it is recommended to people that have a well-known of CSS. For another hand, if you need slides to be self-contained, then xaringan it is not a good option because needs a webserver to run. Another bad news is that xaringan doesn’t work well with HTML widgets.

To install the library type

or install it directly from GitHub to ensure that you are downloading the last version

Once you get installed, go to the menu File -> New File -> R Markdown -> From template and click on ninja presentation.

Note: If you understand chinese you can select the last option ;).

The header is going to look like this

A lit bit more complicated than others and as you will see, there are some funny arguments that make this library really different.

• css : to add your own CSS file,
• self_contained : to produce a self-contained HTML file
• seal : to generate a title slide automatically using the YAML metadata of the R Markdown document (if FALSE, you should write the title slide by yourself)
• yolo : to insert the Mustache Karl (TM) randomly in the slides. Using TRUE, a number between 0-1 to insert the Mustache Karl in a percentage of the slides, or even a list(times = n, img = path)
• chakra : path to the remark.js library (can be either local or remote).
• nature : (Nature transformation) A list of configurations to be passed to remark.create(), e.g. list(ratio = ‘16:9’, navigation = list(click = TRUE)); see https://github.com/gnab/remark/wiki/Configuration

Besides the options provided by remark.js, there are others such interesting like autoplay the slides or the countdown timer. Slides can be automatically played setting the autoplay option under nature (in milliseconds). For example, to display slides every 30 seconds and see the countdown timer:

It is possible to highlight code lines turning the option highlightLines to true or to extend the markdown syntax defining custom macros with the beforeInit option under the option nature.

Adding your CSS file

Some of the previous presentation formats give us the chance to add a customized CSS file. To know how to change a specific element you can inspect it with any web browser and focus exactly on what you want to modify by yourself. An example of a basic modification in a CSS file is the next one. Here we are selecting the background color of the body, the color of the headers and the full text for the reveal presentation, and the size of the h1 header:

Then you have to save the CSS file in the same path that your R presentation document.

How to export the presentation

With all the HTML output it is possible to export the presentation to pdf with any web browser using the menu Print to PDF from Google Chrome, for example. But there is another alternative like publishing the presentation online in RPubs or GitHub. You must be registered in any of the two platforms to be able to add your work. For RPubs, you have to invoke the More -> Publish to RPubs command from the presentation toolbar, and in GitHub, you have to create a new repository with the HTML document and all the style files associated, and enable to GitHub pages to this repository. Here you have the steps to do it: https://pages.github.com/ .

Basic example

Finally, let’s show you a simple reveal.js example to get you started.

After knitting this, here is the result:

Conclusions

RStudio is an awesome framework that provides you the chance to create nice presentations with a simple syntax, adding interactive content, and with a professional and modern style. Moreover, your presentation will be reproducible if you want to make any change, as well as you can save your templates to use them in the future. In my opinion, it is a really good alternative to other traditional software to create presentations and so easy to work with it. I hope it is so useful for you too :)

• Getting from flat data a world of relationships to visualise with Gephi
• Simple yet elegant Object-Oriented programming in R with S3
• An introduction to Stan with R
• LSTM with Keras & TensorFlow
• Online resources for teaching

8   Slideshow Presentations

You are reading the free online version of this book. if you’d like to purchase a physical or electronic copy, you can buy it from no starch press , powell’s , barnes and noble or amazon ..

If you need to create a slideshow presentation, like one you might create in PowerPoint, R has you covered. In this chapter, you’ll learn how to produce presentations using xaringan . This package, which uses R Markdown, is the most widely used tool for creating slideshows in R.

You’ll use xaringan to turn the penguin report from Chapter 6 into a slideshow. You’ll learn how to create new slides, selectively reveal content, adjust text and image alignment, and style your presentation with CSS.

Why Use xaringan?

You might have noticed the Presentation option while creating a new R Markdown document in RStudio. This option offers several ways to make slides, such as knitting an R Markdown document to PowerPoint. However, using the xaringan package provides advantages over these options.

For example, because xaringan creates slides as HTML documents, you can post them online versus having to email them or print them out for viewers. You can send someone the presentation simply by sharing a link. Chapter 9 will discuss ways to publish your presentations online.

A second benefit of using xaringan is accessibility. HTML documents are easy to manipulate, giving viewers control over their appearance. For example, people with limited vision can access HTML documents in ways that allow them to view the content, such as by increasing the text size or using screen readers. Making presentations with xaringan lets more people engage with your slides.

How xaringan Works

To get started with xaringan , run install.packages("xaringan") in RStudio to install the package. Next, navigate to File > New File > R Markdown to create a new project. Choose the From Template tab and select the template called Ninja Presentation , then click OK .

You should get an R Markdown document containing some default content. Delete this and add the penguin R report you created in Chapter 6 . Then, change the output format in the YAML to xaringan::moon_reader like so:

The moon_reader output format takes R Markdown documents and knits them as slides. Try clicking Knit to see what this looks like. You should get an HTML file with the same name as the R Markdown document (such as xaringan-example.html ), as shown in Figure  8.1 .

If you scroll to the next slide with the right arrow key, you should see familiar content. Figure  8.2 shows the second slide, which has the same text as the report from Chapter 6 and a cut-off version of its histogram.

Although the syntax for making slides with xaringan is nearly identical to that used to make reports with R Markdown, you need to make a few tweaks so that the content can fit on the slides. When you’re working in a document that will be knitted to Word, its length doesn’t matter, because reports can have 1 page or 100 pages. Working with xaringan , however, requires you to consider how much content can fit on a single slide. The cut-off histogram demonstrates what happens if you don’t. You’ll fix it next.

Creating a New Slide

You’ll make this histogram fully visible by putting it in its own slide. To make a new slide, add three dashes ( --- ) where you’d like it to begin. I’ve added them before the histogram code:

When you knit the document again, what was one slide should now be broken into two: an Introduction slide and a Bill Length slide. However, if you look closely, you’ll notice that the bottom of the histogram is still slightly cut off. To correct this, you’ll change its size.

Adjusting the Size of Figures

Adjust the size of the histogram using the code chunk option fig.height :

Doing this fits the histogram fully on the slide and also reveals the text that was hidden below it. Keep in mind that fig.height adjusts only the figure’s output height; sometimes you may need to adjust the output width using fig.width in addition or instead.

Revealing Content Incrementally

When presenting a slideshow, you might want to show only a portion of the content on each slide at a time. Say, for example, that when you’re presenting the first slide, you want to talk a bit about each penguin species. Rather than show all three species when you open this slide, you might prefer to have the names come up one at a time.

You can do this using a feature xaringan calls incremental reveal . Place two dashes (–) between any content you want to display incrementally, like so:

This code lets you show Adelie onscreen first; then Adelie and Gentoo; and then Adelie, Gentoo, and Chinstrap. When presenting your slides, use the right arrow to incrementally reveal the species.

Aligning Content with Content Classes

You’ll also likely want to control how your content is aligned. To do so, you add the content classes .left[] , right[] , and center[] to specify the desired alignment for a piece of content. For example, to center-align the histogram, use .center[] as follows:

This code centers the chart on the slide.

Other built-in options can make two-column layouts. Adding .pull-left[] and .pull-right[] will make two equally spaced columns. Use the following code to display the histogram on the left side of the slide and the accompanying text on the right:

Figure  8.3 shows the result.

To make a narrow left column and wide right column, use the content classes .left-column[] and .right-column[]. Figure  8.4 shows what the slide looks like with the text on the left and the histogram on the right.

In addition to aligning particular pieces of content on slides, you can also horizontally align the entire content using the left , right , and center classes. To do so, specify the class right after the three dashes that indicate a new slide, but before any content:

This code produces a horizontally centered slide. To adjust the vertical position, you can use the classes top , middle , and bottom .

Adding Background Images to Slides

Using the same syntax you just used to center the entire slide, you can also add a background image. Create a new slide, use the classes center and middle to horizontally and vertically align the content, and add a background image by specifying the path to the image within the parentheses of url() :

To run this code, you’ll need a file called penguins.jpg in your project (you can download it at https://data.rfortherestofus.com/penguins.jpg ). Knitting the document should produce a slide that uses this image as a background with the text Penguins in front of it, as shown in Figure  8.5 .

Now you’ll add custom CSS to further improve this slide.

Applying CSS to Slides

One issue with the slide you just made is that the word Penguins is hard to read. It would be better if you could make the text bigger and a different color. To do this, you’ll need to use Cascading Style Sheets (CSS) , the language used to style HTML documents. If you’re thinking, I’m reading this book to learn R, not CSS , don’t worry: you’ll need only a bit of CSS to make tweaks to your slides. To apply them, you can write your own custom code, use a CSS theme, or combine the two approaches using the xaringanthemer package.

To add custom CSS, create a new code chunk and place css between the curly brackets:

This code chunk tells R Markdown to make the second-level header ( h2 ) 150 pixels large and white. Adding .remark-slide-content before the header targets specific elements in the presentation. The term remark comes from remark.js , a JavaScript library for making presentations that xaringan uses under the hood.

To change the font in addition to the text’s size and color, add this CSS:

The first new line makes a font called Inter available to the slides, because some people might not have the font installed on their computers. Next, this code applies Inter to the header and makes it bold. You can see the slide with bold Inter font in Figure  8.6 .

Because xaringan slides are built as HTML documents, you can customize them with CSS however you’d like. The sky’s the limit!

You may not care to know the ins and outs of CSS. Fortunately, you can customize your slides in two ways without writing any CSS yourself. The first way is to apply xaringan themes created by other R users. Run this code to get a list of all available themes:

The output should look something like this:

Some CSS files change fonts only, while others change general elements, such as text size, colors, and whether slide numbers are displayed. Using prebuilt themes usually requires you to use both a general theme and a fonts theme, as follows:

This code tells xaringan to use the default CSS, as well as customizations made in the metropolis and metropolis-fonts CSS themes. These come bundled with xaringan , so you don’t need to install any additional packages to access them. Figure  8.7 shows how the theme changes the look and feel of the slides.

If writing custom CSS is the totally flexible but more challenging option for tweaking your xaringan slides, then using a custom theme is simpler but a lot less flexible. Custom themes allow you to easily use others’ prebuilt CSS but not to tweak it further.

The xaringanthemer Package

A nice middle ground between writing custom CSS and applying someone else’s theme is to use the xaringanthemer package by Garrick Aden-Buie. This package includes several built-in themes but also allows you to easily create your own custom theme. After installing the package, adjust the css line in your YAML to use the xaringan-themer.css file like so:

Now you can customize your slides by using the style_xaringan() function. This function has over 60 arguments, enabling you to tweak nearly any part of your xaringan slides. To replicate the custom CSS you wrote earlier in this chapter using xaringanthemer , you’ll use just a few of the arguments:

This code sets the header size to 150 pixels and makes all the headers use the bold, white Inter font.

One particularly nice thing about the xaringanthemer package is that you can use any font available on Google Fonts by simply adding its name to header_font_family or another argument that sets font families ( text_font_family and code_font_family are the other two, for styling body text and code, respectively). This means you won’t have to include the line that makes the Inter font available.

In this chapter, you learned how to create presentations using the xaringan package. You saw how to incrementally reveal content on slides, create multi-column layouts, and add background images to slides. You also changed your slides’ appearance by applying custom themes, writing your own CSS, and using the xaringanthemer package.

With xaringan , you can create any type of presentation you want and then customize it to match your desired look and feel. Creating presentations with xaringan also allows you to share your HTML slides easily and enables greater accessibility.

Additional Resources

Garrick Aden-Buie, Silvia Canelón, and Shannon Pileggi, “Professional, Polished, Presentable: Making Great Slides with xaringan,” workshop materials, n.d., https://presentable-user2021.netlify.app .

Silvia Canelón, “Sharing Your Work with xaringan: An Introduction to xaringan for Presentations: The Basics and Beyond,” workshop for the NHS-R Community 2020 Virtual Conference, November 2, 2020, https://spcanelon.github.io/xaringan-basics-and-beyond/index.html .

Alison Hill, “Meet xaringan: Making Slides in R Markdown,” slideshow presentation, January 16, 2019, https://arm.rbind.io/slides/xaringan.html .

Yihui Xie, J. J. Allaire, and Garrett Grolemund, “xaringan Presentations,” in R Markdown: The Definitive Guide (Boca Raton, FL: CRC Press, 2019), https://bookdown.org/yihui/rmarkdown/ .

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How to create PowerPoint slides from R

Learn how to generate powerpoint slides straight from an r markdown document. plus, create interactive html slides in r with the xaringan package..

Executive Editor, Data & Analytics, InfoWorld |

There are lots of ways to share results of your R analysis: Word documents , interactive apps , even in the body of an email .

But sometimes, you want a slide presentation. It’s easy to generate a PowerPoint file from your R code – complete with charts and graphs – directly from an R Markdown document.

Create a PowerPoint from R Markdown

To create a PowerPoint from R, you need three things on your system:

• PowerPoint or OpenOffice,
• The rmarkdown package, version 1.9 or later, and
• Pandoc version 2.0.5 or newer.

Pandoc isn’t an R package. It’s not R at all; it’s a separate piece of open source software designed for file format conversions.

RStudio ships with Pandoc, so you probably have a version of it installed if you use RStudio. You can run the rmarkdown package’s pandoc_version() function to see if you’ve got it installed and, if so, what version. If your pandoc is too old, try updating RStudio (or install pandoc directly from pandoc.org ).

There is an option to create a PowerPoint file from R Markdown when you create a new markdown file in RStudio.

Next, create an R Markdown document. If you do that from RStudio’s menu with File > New File > R Markdown, you’ll have a few choices . If you click on the second choice, Presentation, you should see an option for PowerPoint under Default Output Format.

The resulting R Markdown file created by RStudio includes examples for mixing text and R code results. If you save that file and then “knit” it by clicking the knit button in RStudio, you'll get a PowerPoint presentation with the same information.

How did R know where to break the content into new slides? The default is “the highest level of headline that’s not followed immediately by another headline.” In this case that’s headline level two, or all titles starting with ## .

You don’t need to use that default rule, though. You can specify another headline level to auto-divide your document into new slides. That’s done in the doc’s YAML header  with the slide_level option, such as

But if you don’t want to fiddle with all that, you can divide content into new slides manually with three dashes. Make sure the three dashes are on a completely new line.

Presenting the weather

Here is an R Markdown file that’s a bit more interesting than the default doc, at least for me: One with weather data.

Notice the R chunk options I’ve set.  echo = FALSE  means my R code won’t show up in my slides. warning and message set to FALSE makes sure any warnings or messages from my code don’t appear in the slides either. I’ve also set a default figure width and cache = TRUE  . (I don’t usually cache results for a file I want to update regularly, but I did so to save time on the accompanying video.)

Get National Weather Service forecast data via R

My R Markdown setup code chunk also sources a separate file on GitHub that includes two functions for fetching weather data. Here is that code, if of interest:

The first function pulls a forecast data frame from the National Weather Service API using the city name and the city’s forecast URL as function arguments. 

You need to know the API’s forecast URL for a location in order to get its forecast data. If you don’t know that URL, you can get it from another National Weather Service API using the format 

The initial API result from the httr GET request is a list. The function adds code that returns only the portion of the list with the data I want, formatted as a data frame.

The second function takes that forecast data frame and generates a ggplot line graph for high and low temperatures.

Change the PowerPoint default font

If you want a different default font or font size for your R-generated slides, you can set those with a reference PowerPoint document and add info about that document in the R Markdown YAML header. I did that for these slides, as you can see in this portion of the YAML document header:

My reference file, CorporateStyle.pptx ,  is a regular PowerPoint file and not a PowerPoint template. To turn it into a reference file, I went into the file’s Master Slide view and set some styles. You can edit any PowerPoint file’s Master Slide view in the PowerPoint menu with View > Slide Master.

Whenever I want an updated version of that forecast PowerPoint, I just need to re-knit the document. I could even set this up to run automatically using Windows scheduler or launchd on a Mac.

Create HTML slides from R

There might be many times when you specifically need or want a PowerPoint file. One thing PowerPoint slides lack, though, is interactivity. For example, you can’t roll over a graph and see underlying data.

You could if these were HTML slides, though.

There are a few ways to generate HTML slides from R. One of the most popular is with the xaringan R package . xaringan is built on top of the remark.js JavaScript library. There is a bit of a learning curve to do more than the basics, but the look and feel are extremely customizable.

xaringan would need its own series to cover all you can do with it. But even basics can work for a lot of use cases. Below is an example of an R Markdown document with just a bit of customization.

Three dashes create a new slide. That first slide after the title slide won’t display; it’s setting defaults for the other slides. layout: true means “this is a slide setting up layout defaults.” class: center centers everything – header text, graphics – unless I specifically code it otherwise. 

The xaringan::moonreader output option regenerates the slides each time you save the file so you don’t need to click the knit button. 

The body of the file includes a graphing function I wrote using one of my favorite dataviz packages, echarts4r , to visualize my weather data. You can hover over lines on the graphs in these slides to see underlying data, as well as click legend items to turn lines off and on.

An HTML slide presentation lets you interact with visualizations, such as hovering over a graph to see underlying data.

There is a ton more you can do with xaringan, from adding your own CSS file to creating your own theme to animating slides. Here are some resources to learn more:

• xaringan slide presentation about xaringan by creator Yihui Xie
• Incremental slides with xaringan by creator Yihui Xie
• xaringan presentations from R Markdown: the Definitive Guide by Yihui Xie, J. J. Allaire, and Garrett Grolemund
• xaringan gallery of examples and themes by Emil Hvitfeldt
• Meet xaringan: Making slides in R Markdown by Alison Hill (RStudio Conference 2019 workshop slides)
• xaringanExtra package (enhancements and extensions to the xaringan package) by Garrick Aden-Buie
• xaringanthemer package (lots of xaringan styling options)  by Garrick Aden-Buie

And for more R tips, head to the Do More With R page .

Next read this:

• Why companies are leaving the cloud
• 5 easy ways to run an LLM locally
• Coding with AI: Tips and best practices from developers
• Meet Zig: The modern alternative to C
• What is generative AI? Artificial intelligence that creates
• The best open source software of 2023
• Business Intelligence
• Data Visualization

Sharon Machlis is Director of Editorial Data & Analytics at Foundry, where she works on data analysis and in-house editor tools in addition to writing. Her book Practical R for Mass Communication and Journalism was published by CRC Press. She was named Digital Analytics Association's 2021 Top (Data) Practitioner, winner of the 2023 Jesse H. Neal journalism award for best instructional content, 2014 Azbee national gold award for investigative reporting, and 2017 Azbee gold for how-to article, among other awards. You can find her on Mastodon at masto.machlis.com/@smach .

Copyright © 2022 IDG Communications, Inc.

R news and tutorials contributed by hundreds of R bloggers

How to make a powerpoint presentation using r markdown.

Posted on February 13, 2022 by Dario Radečić in R bloggers | 0 Comments

[social4i size="small" align="align-left"] --> [This article was first published on r – Appsilon | Enterprise R Shiny Dashboards , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

PowerPoint is the most recognized presentation-making software, but it isn’t for everyone. Some may find it packed with unnecessary features, and to some extent that’s true. Microsoft updates it regularly and invents things you never even knew you needed.

If you’re a programmer at heart, you likely value simplicity. That’s where this article comes in. We’ll ditch PowerPoint and make presentations in a way you didn’t know was possible. After reading, you’ll know how to make an entire editable PowerPoint presentation using only R Markdown.

Interested in a real-world use case? Here’s how we applied R Markdown in Pharma .

Table of contents:

• Getting Started

What Can You Do With Markdown?

• Images, Tables, and Custom Layout
• How to Style Your R Markdown Presentation

R Markdown PowerPoint Presentation – Getting Started

We assume you have R and RStudio installed. Once in RStudio, go to File – New File – R Markdown . A window like the one below should appear:

Image 1 – Creating a new R Markdown PowerPoint Presentation

Give your presentation a title and optionally specify the author. Also, make sure to select PowerPoint as the default output format. R will ask you to install a couple of dependencies if this is your first time working with R Markdown. After clicking on OK you’ll see a default R Markdown PowerPoint presentation code:

Image 2 – Default presentation template

That’s great, but how can you “compile” it? Well, easily! Click on the Knit dropdown and choose the Knit to PowerPoint option:

Image 3 – How to run R Markdown PowerPoint presentation

That’s it! A PowerPoint presentation will be knitted and opened after a couple of seconds. Here’s what it looks like:

Image 4 – First rendered presentation

It’s a strong start but definitely needs work. I’ll show you how to spice it up in the sections below. First, we’ll explore what can you actually do with Markdown.

Markdown is a free-to-use markup language used to format plain text. It’s popular among developers and technical writers because it provides you with everything you need and nothing else. We’ll now explore what can you do with R Markdown, and how you can do it. You’ll learn how to:

• Style the text – Use italics, bold, strikeout, subscript, superscript, small caps, and verbatim.
• Lists – Ordered and unordered.
• Links – Embed URLs to external websites.
• Quotes – Special indentation for your text.
• Equations – Does LaTeX ring a bell? You can use it in Markdown.

We’ll also cover more advanced Markdown functionality, but these are enough for one section. Use the following code to declare two slides with all mentioned Markdown functionalities:

Your R Markdown file should look like this:

Image 5 – Exploring Markdown options

And once again, use Knit to PowerPoint option to export the PPTX:

Image 6 – Rendered markdown presentation

The R Markdown PowerPoint presentation still looks rough around the edges, but we’ll address the visuals soon. Before we do that, let’s go over a couple of “advanced” Markdown elements, and how to get the most out of them.

Want to include your Bar Plots in your presentation? Follow these Data Visualization Best Practices .

Adding Images, Tables, and Custom Layouts to an R Markdown PowerPoint Presentation

A presentation without images and tables is, well, boring. Also, most presentations make use of multiple layouts. For example, there are scenarios where a two-column layout is preferred. You’ll learn how to use it in this section.

The code snippet below implements the following:

• 1st Slide  – Loads a dog image from Unsplash and adds a caption to it.
• 2nd Slide  – Shows a table representing a subset from the Iris dataset .
• 3rd Slide  – Implements a two-column layout.

This time, you won’t see any rendered output in the R Markdown file:

Image 7 – Adding images, tables, and custom layouts

Here’s what the final PPTX looks like:

Image 8 – Rendered Powerpoint presentation

You now know the basics of R Markdown – just enough to place any type of content into your R Markdown PowerPoint presentations. But how can you make the slideshow visually appealing? That’s what we’ll explore next.

How to Style Your R Markdown PowerPoint Presentation

The default PPTX layout is, well, default, and doesn’t look attractive at all. To change it, you’ll first have to create a blank PowerPoint presentation and open the Slide Master ( View – Slide Master ). Once inside, tweak it as you normally would when styling a PPTX file.

Excel is good, but not great. Check out our top alternatives from R and Python . 

We’ll only change the theme, just to keep things simple:

Image 9 – Editing the slide master

You’re free to take your time here, add custom graphics, fonts, and other visual elements. Once done, save the PPTX file right where your .Rmd file is :

Image 10 – Saving PowerPoint template

You can save it elsewhere, but it’s a good practice to keep the PowerPoint template and R Markdown file in the same directory.

To use the template, you’ll only have to modify the header of the R Markdown file:

That’s why we saved the PPTX template in the same directory. There’s no need to think about the path. Everything else in the Rmd file remains the same.

Knit the PowerPoint presentation to verify the template was used:

Image 11 – Rendered presentation with a custom template

And would you look at that – a custom PowerPoint template was successfully applied to our R Markdown PowerPoint presentation. We won’t dive into more advanced use cases today, as this alone is enough to cover what most programmers and tech users need. But if you’d like to learn about more advanced uses, let us know.

PowerPoint isn’t for everyone, just like MS Word. If you know Markdown, you can write and edit text documents much faster than in a traditional word processor. What makes things even better is its shareability, as most online writing platforms understand Markdown.

R Markdown is by no means a replacement for dedicated office suites, so keep that in mind. It might be a decent alternative if you need to automate slide production, simply don’t want to use PowerPoint, or if you don’t need all the functionalities it offers.

To further drive the point home, we recommend the following homework tasks:

• Try to embed a YouTube video or a GIF. Is there any difference from regular images?
• Add presenter notes to one or more slides.
• Try to add animations between slides. Is it possible?

Feel free to share results with us on Twitter – @appsilon . We’d love to see what you come up with.

R isn’t limited to Markdown only. Here are the top free resources if you want to learn R Shiny .

Article How To Make A PowerPoint Presentation Using R Markdown comes from Appsilon | Enterprise R Shiny Dashboards .

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Princeton University Library

Data visualization in r: introduction, table of contents.

1. Relationship Visualizations

    1.1 Line charts

    1.2 Scatter Plot

    1.3 Regression Plots

2. Distribution Visualizations

    2.1 Histogram

    2.2 Box plot

    2.3 Violin plots

    2.4 Heat Map

    2.5 Time-Series

 3. Comparison Visualizations

    3.1 Faceted Plots

    3.2 Plot different Groups

    3.3 Error Bars

Reference list/ Useful links

Introduction

This guide is designed to introduce fundamental techniques for creating effective visualizations using R, a critical skill in presenting data analysis findings clearly and succinctly. Data visualization serves as an indispensable tool in data exploration, inference making, and results presentation. It transforms complex data sets into intuitive graphical representations, facilitating a deeper understanding of the data and enabling the communication of insights in a universally comprehensible manner.

In this guide, we will both look at data visualization in base R and using packages(like 'ggplot2'). There are many useful packages in R for different complicated usage, you can find them here:  https://r-graph-gallery.com/

1. Relationship Visualizations

1.1 line charts.

Line graphs display information as a series of data points connected by straight-line segments. They are primarily used for visualizing data trends over intervals or time.

Line graphs are good at showing changes and trends over time, making it easy to compare multiple series simultaneously. They are intuitive to understand and can effectively communicate the direction and pace of trends. However, they can become confusing when overloaded with too many data series or when the data points are too densely packed.

We will look at both the Base R plots and ggplot2 plots.‘ggplot2' is a powerful visualization package in R enabling users to create a wide variety of charts, enhancing data exploration and presentation.

We will be using the R's built-in dataset 'mtcars' for this purpose, which is a data frame with fuel consumption and 10 aspects of automobile design and performance for 32 automobiles.

First, let's see how to plot a line graph in base R.

Now, let's look at how to plot this graph using ggplot2.

Note that if the package is not downloaded, you have to install it first.

Now see the code:

Aside from plotting the trend, we can also use line graph to see the relationship between two variables.

This is the example from base R:

This is the example from ggplot2:

1.2 Scatter Plot

Scatter plots display values for two variables for a set of data so that we can get an idea of the trend or correlation.

Scatter plots can be useful for identifying correlations, trends, and outliers in data. They visually demonstrate the strength and direction of a relationship between two variables, making them indispensable for exploratory data analysis and regression analysis. Note that while scatter plots are excellent for bivariate analysis, they can become cluttered and less effective with large datasets. Also, scatter plots do not necessarily imply causation.

The base R example graph:

The ggplot example:

1.3 Regression Plots

We can plot the regression line, indicating the linear relationship between two variables.

We can also plot the Confidence Interval as a shaded area.

2. Distribution Visualizations

2.1 histogram.

A histogram is a type of graph used in statistics to represent the distribution of numerical data by showing the number of data points that fall within a range of values, known as bins. Note that It is similar to a bar chart but differs in that it groups ranges of data into bins and displays the frequency of data points within each bin, making it ideal for showing the shape and spread of continuous data. We often plot the histogram of one continuous variable to have a rough idea about the distribution(like, whether normal or not).

Base R example:

ggplot example:

2.2 Box plot

Box plots (or box-and-whisker plots) summarize data using a five-number summary: minimum, first quartile (Q1), median (not mean), third quartile (Q3), and maximum. They also highlight outliers. Box plots are highly efficient in depicting the distribution of data, providing insights into the central tendency, variability, and skewness. They are particularly useful for comparing distributions across different categories. Note that they do not convey the exact distribution shape as precisely as density plots or histograms and can be misleading if misinterpreted by those unfamiliar with their construction.

2.3 Violin Plots

Violin plots combine the summary statistics of box plots with the density distributions of kernel density plots, showing data distribution shapes around the median. These plots are excellent for comparing distributions between groups, providing a deep insight into the data's spread, skewness, and multimodality. They can highlight differences in distribution shapes and central tendencies across categories.

Note that for small sample sizes, violin plots can be misleading, as they rely on kernel density estimation. Their interpretation is also not as straightforward as box plots for non-technical audiences.

Compare with Box plots:

While both box plots and violin plots are used to visualize and summarize statistical distributions, violin plots provide a more detailed picture of the data's structure, including its density. Box plots, on the other hand, offer a more straightforward summary focused on the range, quartiles, and outliers. The choice between them depends on the specific needs of the analysis: whether a quick summary is sufficient or a detailed distribution view is necessary.

2.4 Heat Map

Heatmaps display data in a matrix as colors and are particularly useful for visualizing the magnitude of phenomena across two dimensions. They can represent various data types, including correlations, missing data patterns, or any matrix data。 They can also reveal patterns or gradients within large datasets, making them ideal for spotting trends, clusters, and outliers. They can efficiently summarize complex information in an intuitive format, allowing for quick comparisons across categories and variables.

However, when datasets are very large, heatmaps can become cluttered or lose detail. The choice of color scale is critical and can significantly impact interpretation.

2.5 Time-Series

Time series plots display data points over time, allowing for the visualization of trends, cycles, and seasonal variations. These plots are crucial for analyzing temporal data, highlighting trends, detecting outliers, and identifying seasonal effects. They are instrumental in forecasting and understanding historical data behavior.

We will generate simulation data in these examples.

Note that for time-series plots, we need to make sure the structure of the x-axis is datetime. 

We can add vertical lines in time-series plots to indicate important event dates so that we can see the trend before and after the event.

3. Comparison Visualizations

3.1 faceted plots.

 Faceted plots, or small multiples, divide data into subsets based on a categorical variable and plot each subset in its own panel. They use a consistent scale to facilitate direct comparison. Faceting is powerful for comparing patterns across different levels of a categorical variable and for identifying how relationships between variables differ across subsets. It simplifies complex data comparisons across groups without overcrowding a single plot. We have to be careful when selecting how many facets though. With too many facets or categories, the plots can become small and hard to read. It also requires careful consideration of layout to ensure clarity and effectiveness in communication.

3.2 Plot different Groups

We can plot different groups together in one plot. We can use different colors to indicate different groups.

We can also plot based on more than group: this is an example of bar plots based on different 'cyl' and 'gear' groups. 

3.3 Error Bars

In this section, we give an example of bar plots of the average value of mpg in different groups, with error bars. The use of error bars can indicate the variability or uncertainty in the data.

Reference list / Useful links

Data visualization with –ggplot2:  https://ggplot2.tidyverse.org/reference/

Modern Data Visualization with R:  https://rkabacoff.github.io/datavis/

Shading confidence intervals manually with ggplot2:  https://stackoverflow.com/questions/16463325/shading-confidence-intervals-manually-with-ggplot2

The R Graph Gallery:  https://r-graph-gallery.com/

Comments or Questions?

If you have questions or comments about this guide or method, please email [email protected] .

Data Consultant

• Last Updated: Feb 20, 2024 5:23 PM
• URL: https://libguides.princeton.edu/R-Visualization

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How to include plotly in R Studio Presentations (Rpres)

How to include a plotly plot in a Rpres file? If you do it like in a normal Rmd file

The solution I came up with, which uses the possibility that Markdown can contain HTML:

But I am hoping for a somehow more elegant solution which does not use any additional files.

• htmlwidgets

• Nice workaround, thanks. Alternatively, plotly works fine with ioslides rendered from Rmarkdown. –  Antoine Vernet Aug 19, 2016 at 9:59
• @Antoine Can you elaborate a bit on this workflow? –  jakob-r Dec 8, 2016 at 10:42
• I have added a minimal example on how to do this as an answer below. Let me know if this is not what you had in mind. –  Antoine Vernet Dec 8, 2016 at 12:34

2 Answers 2

The following is a minimal example on how to include a plot_ly graph in an ioslides presentation, so it does not quite answer the question for Rpres, but provides an alternative.

The first slide displays a plot transformed from a ggplot into a plot_ly, preserving the ggplot style. The second slide displays a plot using plot_ly directly.

Had the same problem. When I executed slidify(index.Rmd) , there was a message saying PhantomJS not found , and suggesting me run webshot::install_phantomjs() . So I did and the error was gone. However I still got no plotly interactive map output. It was blank.

Also tried the following code in terminal, which worked for some people but not for me. I got html file output, and there still wasn't a map. It comes from this post . It might work for you.

I am sure it is plotly. Cause ggplots works fine.

Reinstalled/updated the wetshot package by running install.packages("webshot") , then ran webshot::install_phantomjs() again, then library(knitr); library(rmarkdown); rmarkdown::render('index.Rmd', output_file='index.html') . It worked. The html file has a plotly map, though it doesn't appear in the Knitr preview window.

By adding the following code, I am able to display the map in the sides. Refer to this post .

Full context would be something listed below.

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Create and format PowerPoint documents from R software

• Printable version

Reason I : Many collaborators works with Microsoft office tools

• Reason II : keeping beautiful R graphs beautiful for publications

But wasn’t this problem solved already?

Install and load the reporters package, slide layout, generate a simple powerpoint document from r software, text properties : font, color and size, change the appearance of a “piece of text” (pot), add plots and images, add a table, add ordered and unordered lists, download a template file, slide layouts available in the template file, create a powerpoint document from the template file, why is it important to be able to generate a powerpoint report from r .

There are at least, two reasons for this, as described in the next sections.

About 1 billion people worldwide use Microsoft Office (1 in 7 people on the planet; source: Microsoft ).

Furthermore, many collaborators still working with MS Office software (Word, PowerPoint, Excel) for :

• editing their text and tracking changes
• copy-pasting texts, images and tables from multiple sources
• saving and analyzing their data

In this context, a report generated as a PDF or HTMl files is less useful with some collaborators.

Reason II : keeping beautiful R graphs beautifull for publications

R plots can be customized to be as beautiful as your imagination can make them. Unfortunately, preserving this beauty is not always an easy task when you want to publish these graphs or show them in a professional presentations.

Yes, this problem can be solved using knitr/rmarkdown/Latex/Beamer/Slidify. However, it would be very difficult to remake the whole presentation in a different format. Furthermore, many journals don’t accept Latex documents.

The answer of this question is yes and no. There have been several attempts to solve this problem, but many of them are not easy to use.

One of the previous solutions is R2PPT package. Unfortunately R2PPT is available for Windows OS only and it depends on rcom or RDCOMClient for generating Microsoft PowerPoint presentations.

The goal of this R tutorial is to show you how to easily and quickly, format and export R outputs (including data tables, plots, paragraphs of text and R scripts) from R statistical software to a Microsoft PowerPoint document ( .pptx file format) using ReporteRs package.

ReporteRs is a Java-based solution, so it works on Windows, Mac and Linux.

Use the R code below :

Note that ReporteRs relies on Java (>= 1.6) ; make sure you have an installed JRE

The version of Java installed on your computer, can be checked as follow :

Create a simple PowerPoint document

Four simple steps are required :

• Use the pptx() function to create a PowerPoint object.
• Use the addSlide() function to add a slide into the PowerPoint document.
• addTitle : Add a title
• addParagraph : Add paragraphs of text
• addFlexTable : Add a table
• addPlot : Add a plot generated in R
• addImage : Add external images
• addRScript : Highlight and add R code
• addDate : Add a date
• addPageNumber : Add a page number
• AddFooter : Add a footer
• Write the document into a .pptx file using writeDoc() function

Before showing you an example of how to create and format PowerPoint from R Software, let’s first discuss about slide layout . This is very important to understand the examples provided in this tutorial.

When creating a new slide, you should specify the layout of the slide. The available layouts in the “MS Office PowerPoint” (default template, on my computer) are illustrated in the figure below :

addSlide() function can be used to add a new slide into a PowerPoint document from R software . A simplified format of the function is :

• doc : a pptx object where slide has to be added
• slide.layout : the layout to use for the slide.

Among the possible values for the argument slide.layout , there are : “Title Slide”, “Title and Content”, “Two Content”, “Section Header”, “Content with Caption”, “Title Only”, “Comparison”.

However, you should use only the available slide layouts in your computer.

To view the slide layouts available in your computer, use the R code below :

These layouts are illustrated below :

Note that, the selected layout determines the contents you can add into the slide (See the figure above).

• and one content which can be texts, plots, images, tables or R code
• and two contents : For example, you can add a table in the left panel and a paragraph of texts in the right panel.
• Example 3 - If you choose ‘Comparison’ , you can add a title and four contents (plots, tables, paragraphs, images)

Whatever the slide layout chosen, you can use the functions addDate() , addFooter() and addPageNumber() to add date, footer and slide number, respectively.

The R code below creates a PowerPoint document with a title slide, plots, tables, and an R script :

The PowerPoint document created by the R code above is available here : R software and ReporteRs package - Example of creating a PowerPoint document

Note that, you can use addPageNumber() function without specifying the value of the slide number, as follow :

In this case slide number is added using the default setting (e.g : 1 for slide1, 2 for slide 2).

If you want to customize the numbering, use the function as follow :

Format the text of a PowerPoint document

As illustrated in the figure below, text properties include :

• Font : family (e.g : “Arial”), size (e.g : 11), style (e.g : “italic”)
• Underlined text
• Color (e.g : “blue”)
• Vertical align (superscript, subscript)

The default font size and font family of the PowerPoint can be modified as follow :

The function pot() [Pieces Of Text] is used to modify the appearance of a text. It can be used also to create a hyperlink . The format is :

• value : the text to be formatted
• format : the properties to use for formatting the text

The allowed values for the argument format are the following functions :

• textProperties() : the text formatting properties
• textBold() , textItalic() , textBoldItalic() and textNormal() which are shortcuts for bold , italic , bold-italic and normal text, respectively.

These functions can take the arguments below :

• color : font color; e.g : color=“#000000” or color = “black”.
• font.size : a integer indicating the font size .
• font.weight : the font weight . Possible values are “normal” or “bold”.
• font.style : the font style . Possible values are “normal” or “italic”.
• underlined : a logical value specifying if the text should be underlined .
• font.family : the font family ; e.g : “Arial”.
• vertical.align : a character indicating font vertical alignments . Expected values are “baseline”" or “subscript” or “superscript”. Default value is baseline .
• shading.color : background color of the text (e.g “#000000” or “black”)

The R code below creates a PowerPoint document containing a formatted text and a hyperlink :

The functions addPlot() and addImage() can be used for adding a plot or an external image to the document. addPlot() works with all R plots (base graphics, lattice, ggplot2 and grid).

These two functions can be used as follow :

The R code below creates a PowerPoint document containing a histogram and an image (downloaded from R website) :

The PowerPoint document created by the R code above is available here : R software and ReporteRs package - PowerPoint document containing plots and images

Note that, addPlot() function can take other arguments such as pointsize to change the size of plotted texts (default value is 12; in pixels)

• For addImage() function, the allowed file formats are PNG, WMF, JPEG and GIF images..

addFlexTable() function is used to format and add a table into the PowerPoint.

It can be used as follow :

• STEP 1 : Create a table using FlexTable() or vanilla.table() function. These two functions generate a ‘flexible’ table which can be easily formatted before adding into the slide.
• STEP 2 : Add the create table into the document using addFlexTable() function as follow :

setZebraStyle() function can be used to color odd and even rows differently; for example, odd rows in gray color and even rows in white color.

The example below creates a PowerPoint document with 3 slides containing a simple table (slide 1), vanilla table (slide 2) and a zebra striped table (slide 3) :

The PowerPoint document created by the R code above is available here : R software and ReporteRs package - PowerPoint document containing tables

Lists can be added using addParagraph() function as follow :

• value : a set of items to be added as a list
• list.style : possible values are ‘unordered’ and ‘ordered’
• level : a numeric value indicating the level of the item to be added in the list

The example below generates a one-slide PowerPoint document containing an ordered and unordered lists :

Create a PowerPoint document from a template file

This approach is useful in many situations :

• If you work in a corporate environment and you want to generate a PowerPoint document based on a template with specific fonts, color, logos, etc.
• If you want to modify and insert new contents into an existing PowerPoint document.
• If you want to use text formatting styles and slide layouts from a given template file.

Note that, if you use a template file to create a PowerPoint document, slide layouts are those available in the template.

A template file can be specified to the pptx() function as follow :

In the next section We’ll :

• download a PowerPoint template file from STHDA website
• Check the available slide layouts in the template file
• Create a PowerPoint document based on the template

You can use one of the layout below when adding a new slide into the PowerPoint :

Note that, the template file contains already one empty slide which can be removed manually.

The PowerPoint document created by the R code above is available here : R software and ReporteRs package - PowerPoint document from template

This analysis has been performed using R (ver. 3.1.0).

You can read more about ReporteRs and download the source code at the following link :

GitHub (David Gohel): ReporteRs

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The formal presentation of information is divided into two broad categories: Presentation Skills and Personal Presentation .

These two aspects are interwoven and can be described as the preparation, presentation and practice of verbal and non-verbal communication. 

This article describes what a presentation is and defines some of the key terms associated with presentation skills.

Many people feel terrified when asked to make their first public talk.  Some of these initial fears can be reduced by good preparation that also lays the groundwork for making an effective presentation.

A Presentation Is...

A presentation is a means of communication that can be adapted to various speaking situations, such as talking to a group, addressing a meeting or briefing a team.

A presentation can also be used as a broad term that encompasses other ‘speaking engagements’ such as making a speech at a wedding, or getting a point across in a video conference.

To be effective, step-by-step preparation and the method and means of presenting the information should be carefully considered. 

A presentation requires you to get a message across to the listeners and will often contain a ' persuasive ' element. It may, for example, be a talk about the positive work of your organisation, what you could offer an employer, or why you should receive additional funding for a project.

The Key Elements of a Presentation

Making a presentation is a way of communicating your thoughts and ideas to an audience and many of our articles on communication are also relevant here, see: What is Communication? for more.

Consider the following key components of a presentation:

Ask yourself the following questions to develop a full understanding of the context of the presentation.

When and where will you deliver your presentation?

There is a world of difference between a small room with natural light and an informal setting, and a huge lecture room, lit with stage lights. The two require quite different presentations, and different techniques.

Will it be in a setting you are familiar with, or somewhere new?

If somewhere new, it would be worth trying to visit it in advance, or at least arriving early, to familiarise yourself with the room.

Will the presentation be within a formal or less formal setting?

A work setting will, more or less by definition, be more formal, but there are also various degrees of formality within that.

Will the presentation be to a small group or a large crowd?

Are you already familiar with the audience?

With a new audience, you will have to build rapport quickly and effectively, to get them on your side.

What equipment and technology will be available to you, and what will you be expected to use?

In particular, you will need to ask about microphones and whether you will be expected to stand in one place, or move around.

What is the audience expecting to learn from you and your presentation?

Check how you will be ‘billed’ to give you clues as to what information needs to be included in your presentation.

All these aspects will change the presentation. For more on this, see our page on Deciding the Presentation Method .

The role of the presenter is to communicate with the audience and control the presentation.

Remember, though, that this may also include handing over the control to your audience, especially if you want some kind of interaction.

You may wish to have a look at our page on Facilitation Skills for more.

The audience receives the presenter’s message(s).

However, this reception will be filtered through and affected by such things as the listener’s own experience, knowledge and personal sense of values.

See our page: Barriers to Effective Communication to learn why communication can fail.

The message or messages are delivered by the presenter to the audience.

The message is delivered not just by the spoken word ( verbal communication ) but can be augmented by techniques such as voice projection, body language, gestures, eye contact ( non-verbal communication ), and visual aids.

The message will also be affected by the audience’s expectations. For example, if you have been billed as speaking on one particular topic, and you choose to speak on another, the audience is unlikely to take your message on board even if you present very well . They will judge your presentation a failure, because you have not met their expectations.

The audience’s reaction and therefore the success of the presentation will largely depend upon whether you, as presenter, effectively communicated your message, and whether it met their expectations.

As a presenter, you don’t control the audience’s expectations. What you can do is find out what they have been told about you by the conference organisers, and what they are expecting to hear. Only if you know that can you be confident of delivering something that will meet expectations.

See our page: Effective Speaking for more information.

How will the presentation be delivered?

Presentations are usually delivered direct to an audience.  However, there may be occasions where they are delivered from a distance over the Internet using video conferencing systems, such as Skype.

It is also important to remember that if your talk is recorded and posted on the internet, then people may be able to access it for several years. This will mean that your contemporaneous references should be kept to a minimum.

Impediments

Many factors can influence the effectiveness of how your message is communicated to the audience.

For example background noise or other distractions, an overly warm or cool room, or the time of day and state of audience alertness can all influence your audience’s level of concentration.

As presenter, you have to be prepared to cope with any such problems and try to keep your audience focussed on your message.   

Our page: Barriers to Communication explains these factors in more depth.

Continue to read through our Presentation Skills articles for an overview of how to prepare and structure a presentation, and how to manage notes and/or illustrations at any speaking event.

Continue to: Preparing for a Presentation Deciding the Presentation Method

See also: Writing Your Presentation | Working with Visual Aids Coping with Presentation Nerves | Dealing with Questions Learn Better Presentation Skills with TED Talks

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What It Takes to Give a Great Presentation

• Carmine Gallo

Five tips to set yourself apart.

Never underestimate the power of great communication. It can help you land the job of your dreams, attract investors to back your idea, or elevate your stature within your organization. But while there are plenty of good speakers in the world, you can set yourself apart out by being the person who can deliver something great over and over. Here are a few tips for business professionals who want to move from being good speakers to great ones: be concise (the fewer words, the better); never use bullet points (photos and images paired together are more memorable); don’t underestimate the power of your voice (raise and lower it for emphasis); give your audience something extra (unexpected moments will grab their attention); rehearse (the best speakers are the best because they practice — a lot).

I was sitting across the table from a Silicon Valley CEO who had pioneered a technology that touches many of our lives — the flash memory that stores data on smartphones, digital cameras, and computers. He was a frequent guest on CNBC and had been delivering business presentations for at least 20 years before we met. And yet, the CEO wanted to sharpen his public speaking skills.

• Carmine Gallo is a Harvard University instructor, keynote speaker, and author of 10 books translated into 40 languages. Gallo is the author of The Bezos Blueprint: Communication Secrets of the World’s Greatest Salesman  (St. Martin’s Press).

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Business Jargons

A Business Encyclopedia

Presentation

Definition : A presentation is a form of communication in which the speaker conveys information to the audience. In an organization presentations are used in various scenarios like talking to a group, addressing a meeting, demonstrating or introducing a new product, or briefing a team. It involves presenting a particular subject or issue or new ideas/thoughts to a group of people.

It is considered as the most effective form of communication because of two main reasons:

• Use of non-verbal cues.
• Facilitates instant feedback.

Business Presentations are a tool to influence people toward an intended thought or action.

Parts of Presentation

• Introduction : It is meant to make the listeners ready to receive the message and draw their interest. For that, the speaker can narrate some story or a humorous piece of joke, an interesting fact, a question, stating a problem, and so forth. They can also use some surprising statistics.
• Body : It is the essence of the presentation. It requires the sequencing of facts in a logical order. This is the part where the speaker explains the topic and relevant information. It has to be critically arranged, as the audience must be able to grasp what the speaker presents.
• Conclusion : It needs to be short and precise. It should sum up or outline the key points that you have presented. It could also contain what the audience should have gained out of the presentation.

Purpose of Presentation

• To inform : Organizations can use presentations to inform the audience about new schemes, products or proposals. The aim is to inform the new entrant about the policies and procedures of the organization.
• To persuade : Presentations are also given to persuade the audience to take the intended action.
• To build goodwill : They can also help in building a good reputation

Factors Affecting Presentation

Audience Analysis

Communication environment, personal appearance, use of visuals, opening and closing presentation, organization of presentation, language and words, voice quality, body language, answering questions, a word from business jargons.

Presentation is a mode of conveying information to a selected group of people live. An ideal presentation is one that identifies and matches the needs, interests and understanding level of the audience. It also represents the facts, and figures in the form of tables, charts, and graphs and uses multiple colours.

Related terms:

• Verbal Communication
• Visual Communication
• Non-Verbal Communication
• Communication
• 7 C’s of Communication

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Thank you so much for providing us with brief info related to the presentation.

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By Debra Kamin

A federal fair-housing law prohibits discrimination in housing based on race, ethnicity, religion and other factors, like gender identity and disability. That applies to any number of scenarios, in which such discrimination has occurred: a homeowner refusing to negotiate a sale; a landlord failing to make repairs; a mortgage lender denying a loan.

President Lyndon B. Johnson signed the Fair Housing Act on April 11, 1968, days after the Rev. Dr. Martin Luther King Jr. was assassinated. The law, initially focused on racial discrimination, was the linchpin of the broader Civil Rights Act of 1968 and was later expanded to include other factors.

Yet complaints of discrimination remain about everything from prejudiced home appraisals to racial steering. In 2022, there were more than 33,000 fair housing complaints received by organizations across the country.

A three-year investigative project from Newsday , published in 2019, found that Black home buyers experience discrimination with nearly half of the real estate agents and brokers they employ; a multiyear investigation a decade earlier conducted by the National Fair Housing Alliance found that 87 percent of real estate agents participated in racial steering, opting to only show their clients homes in neighborhoods where most of the neighbors were of their same race.

“The way real estate agents engage in housing discrimination has gotten a lot more subtle but it is definitely still existent,” said Lisa Rice, president of the National Fair Housing Alliance. “A lot of real estate agents are very misguided and they’re not pro fair housing in their heart.”

Who is protected under the Fair Housing Act?

The fair-housing law placed a sweeping prohibition on all acts of discrimination related to the home buying and renting process, making prejudicial treatment based on race, religion or national origin a crime. Violators can be fined tens of thousands of dollars, or more. Gender was added as another protected category in 1974.

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R Markdown: The Definitive Guide

4.2 slidy presentation.

To create a Slidy presentation from R Markdown, you specify the slidy_presentation output format in the YAML metadata of your document. You can create a slide show broken up into sections by using the ## heading tag (you can also create a new slide without a header using a horizontal rule ( --- ). For example, here is a simple slide show (see Figure 4.2 for two sample slides):

FIGURE 4.2: Two sample slides in a Slidy presentation.

4.2.1 Display modes

The following single character keyboard shortcuts enable alternate display modes:

• 'C' : Show table of contents (the right sub-figure in Figure 4.2 has shown the table of contents).
• 'F' : Toggles the display of the footer.
• 'A' : Toggles display of current vs all slides (useful for printing handouts).
• 'S' : Make fonts smaller.
• 'B' : Make fonts larger .

4.2.2 Text size

You can use the font_adjustment option to increase or decrease the default font size (e.g., -1 or +1 ) for the entire presentation. For example:

If you want to decrease the text size on an individual slide you can use the .smaller slide attribute. For example:

If you want to increase the text size on an individual slide you can use the .bigger slide attribute. For example:

You can also manually adjust the font size during the presentation using the 'S' (smaller) and 'B' (bigger) keys.

4.2.3 Footer elements

You can add a countdown timer to the footer of your slides using the duration option (duration is specified in minutes). For example:

You can also add custom footer text (e.g., organization name and/or copyright) using the footer option. For example:

4.2.4 Other features

Refer to Section 3.1 for the documentation of other features of Slidy presentations, including figure options (Section 3.1.5 ), appearance and style (Section 3.1.4 ), MathJax equations (Section 3.1.8 ), data frame printing (Section 3.1.6 ), Markdown extensions (Section 3.1.10.4 ), keeping Markdown (Section 3.1.10.1 ), document dependencies (Section 3.1.9 ), header and before/after body inclusions (Section 3.1.10.2 ), custom templates (Section 3.1.10.3 ), Pandoc arguments (Section 3.1.10.5 ), and shared options (Section 3.1.11 ).

Slidy presentations have several features in common with ioslides presentations in Section 4.1 . For incremental bullets, see Section 4.1.2 . For custom CSS, see Section 4.1.3.5 . For printing Slidy slides to PDF, see Section 4.1.10 .

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Everything Announced During The 2024 Summer Devolver Direct Presentation

This year's not-E3 weekend video game events have begun , starting with Geoff Keighley's Summer Game Fest showcase earlier today. Shortly after that, though, perhaps the zaniest publisher, Devolver Digital, took to the digital airwaves to showcase six of its games in the 2024 Summer Devolver Direct presentation. 

If you weren't able to catch it, or if you missed the name of the game you're excited to check out (or even its release date maybe), we've got you covered. 

Here's Everything Announced During Today's 2024 Summer Devolver Direct Presentation

Possessor(s).

Possessor(s ) is a new game from Heart Machine, the team behind Hyper Light Drifter and Solar Ash , and it's coming to undisclosed consoles and PC next year. It features action combat inspired by platform fighters like Super Smash Bros. and is set in a quarantined city destroyed by interdimensional catastrophe. 

In the game, you control Luca, the host, and Rehm, her less-than-cooperative counterpart as the two venture through a sprawling metropolis filled with ruined skyscrapers to explore and secrets about what happened to uncover. Devolver says the story features multiple paths in an "open-ended world structure" and upgrades to discover that allows Luca and Rehm to explore previously inaccessible areas, possibly hinting at a Metroidvania-inspired city layout. 

Tenjutsu is a jujutsu-inspired action roguelite from  Sébastien Benard , lead designer of  Dead Cells  and solo developer at Deepnight Games, and it's coming to consoles and PC sometime in the future. If you're familiar with Benard's work, you might recognize Tenjutsu (48h version) , which he released back in 2022 – Tenjutsu is a fully fleshed-out version of that 2022 concept. 

Devolver describes the game as a "fast and fluid rogue-jutsu," leaning into the game's jujutsu roguelite action. In it, you control a renegade yakuza "hellbent on defying her former associates and loosening their grip on the Secret Garden City." To do so, you must fight four powerful crime syndicates. To defeat them "you must master a brutal brawling system and build a diverse arsenal of weapons, upgrades, and martial arts techniques, breaking their hold on the streets in a flurry of violence." 

While you have to take down all four crime syndicates, you can do so in any order. As you do, you unlock new weapons, combat moves, and additional areas to explore. However, the longer you spend doing this, the stronger your enemies become. 

Cult Of The Lamb: Unholy Alliance

Developer Massive Monster still isn't done with its 2022 hit game,  Cult of the Lamb , as it's bringing full campaign co-op to it this August. The Unholy Alliance update hits the game on August 12 and adds a new playable character: the Goat.

With the Goat joining the titular Lamb, players can now experience the entire campaign in local co-op. Devolver says this update includes two-player twists on existing minigames in Cult of the Lamb, like fishing and kuncklebones, as well as additional corrupted weapons, tarot cards, curses, and relics. While playing in co-op, players can swap weapons, deal extra damage when fighting back-to-back, and deal critical hits if their attacks are in sync. Plus, solo players get some new powers and abilities to play with, too. 

Elsewhere in the update, Unholy Alliance adds new buildings, fleeces, follower traits, follower quests, and more secrets to discover. 

The Talos Principle II: Road To Elysium

One of our favorite games of 2023 – The Talos Principle II – is getting a three-part "coda" expansion next week, on June 14, called Road To Elysium. Devolver says it will reunite players with beloved characters and put your puzzle-solving skills to the test through a series of thought-provoking new stories. 

Road To Elysium follows the event of The Talos Principle II and continues the evolution of the robot world while providing you with a new perspective on some of the base game's key moments. This expansion consists of three chapters, each with a distinctive look and feel:

• Orpheus Ascending : Set in Ancient Egypt, in this chapter, you will explore the philosophy of love, death, and resurrection through the story of Hypatia and Sarabhai. 
• Isle of the Blessed : This chapter allows players to hang out with Yaqut and Miranda as they join Cornelius and Athena on a "puzzle-driven adventure set on a stunning Caribbean island." 
• Into the Abyss : Devolvers says in this chapter, players will "return to one of the most dramatic moments from The Talos Principle II" to find out what happened to Byron when he was trapped in the Megastructure. 

The Talos Principle II's Road to Elysium expansion launches June 14 on PlayStation 5, Xbox Series X/S, and PC. It will cost $19.99. 

After delaying Anger Foot last year to 2024 , Devolver Digital has given the first-person kicker (and shooter) a PC release date: July 11. 

If you're not familiar with Anger Foot, it takes place in the caffeine-fueled S**t City, and tasks players with putting the boot, literally, to a menacing menagerie of merciless gangsters.

"Unleash the world's deadliest feet on a colorful cast of anthropomorphic enemies, clearing out slums, sewers, and skyscrapers as you grab new weapons, unlock new sneakers, and upgrade your powers in absurd and wonderful ways," a press release reads. 

The Crush House

Devolver announced today that its reality TV-inspired "thirst-person shooter," The Crush House, launches on PC on August 9. However, the publisher revealed a new demo for the game is available to download and play right now. 

In The Crush House, you play as Jae, a new producer for The Crush House. As Jae, you'll take your camera into the show's Malibu, California, mansion to keep viewers glued to their screens by filming as much drama, romance, and tension as you can find. However, if you fail to keep the audience entertained, your show will get canceled. 

And that's everything announced during today's 2024 Devolver Digital presentation. 

Let us know what your favorite reveals were in the comments below!

Products In This Article

Cult of the Lamb

The Talos Principle II

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