After four sold-out years in New York City, the R Conference made its debut in Washington DC to a sold-out crowd of data scientists at the Ronald Reagan Building on November 8th & 9th. Our speakers shared presentations on a variety of R-related topics.

A big thank you to our speakers Max Kuhn, Emily Robinson, Mike Powell, Mara Averick, Max Richman, Stephanie Hicks, Michael Garris, Kelly O’Briant, David Smith, Anna Kirchner, Roger Peng, Marck Vaisman, Soumya Kalra, Jonathan Hersh, Vivian Peng, Dan Chen, Catherine Zhou, Jim Klucar, Lizzy Huang, Refael Lav, Ami Gates, Abhijit Dasgupta, Angela Li  and Tommy Jones.

Some of the amazing speakers

Some highlights from the conference:

R Superstars Mara Averick, Roger Peng and Emily Robinson

Mara Averick, Roger Peng and Emily Robinson

A hallmark of our R conferences is that the speakers hang out with all the attendees and these three were crowd favorites.

Michael Powell Brings R to the aRmy

Major Michael Powell

Major Michael Powell describes how R has brought efficiency to the Army Intelligence and Security Command by getting analysts out of Excel and into the Tidyverse. “Let me turn those 8 hours into 8 seconds for you,” says Powell.

Max Kuhn Explains the Applications of Equivocals to Apply Levels of Certainty to Predictions

Max Kuhn

After autographing his book, Applied Predictive Modeling, for a lucky attendee, Max Kuhn explains how Equivocals can be applied to individual predictions in order to avoid reporting predictions when there is significant uncertainty.

NYR and DCR Speaker Emily Robinson Getting an NYR Hoodie for her Awesome Tweeting

Emily Robinson

Emily Robinson tweeted the most at the 2018 NYR conference, winning her a WASD mechanical keyboard and at DCR she came in second so we gave her a limited edition NYR hoodie.

Max Richman Shows How SQL and R can Co-Exist

Max Richman

Max Richman, wearing the same shirt he wore when he spoke at the first NYR, shows parallels between dplyr and SQL.

Michael Garris Tells the Story of the MNIST Dataset

Michael Garris

Michael Garris was a member of the team that built the original MNIST dataset, which set the standard for handwriting image classification in the early 1990s. This talk may have been the first time the origin story was ever told.

R Stats Luminary Roger Peng Explains Relationship Between Air Pollution and Public Health

Roger Peng

Roger Peng shows us how air pollution levels has fallen over the past 50 years resulting in dramatic improvements in air quality and health (with help from R).

Kelly O’Briant Combining R with Serverless Computing

Kelly O'Briant

Kelly O’Briant demonstrates how to easily deploy R projects on Google Compute Engine and promoted the new #radmins hashtag.

Hot Dog vs Not Hot Dog by David Smith (Inspired by Jian-Yang from HBO’s Silicon Valley)

David Smith

David Smith, one of the original R users, shows how to recreate HBO’s Silicon Valley’s Not Hot Dog app using R and Azure

Jon Hersh Describes How to Push for Data Science Within Your Organization

Jon Hersh

Jon Hersh discusses the challenges, and solutions, of getting organizations to embrace data science.

Vivian Peng and the Importance of Data Storytelling

Vivian Peng

Vivian Peng asks the question, how do we protect the integrity of our data analysis when it’s published for the world to see?

Dan Chen Signs His Book for David Smith

Dan Chen and David Smith

Dan Chen autographing a copy of his book, Pandas for Everyone, for David Smith. Now David Smith has to sign his book, An Introduction to R, for Dan.

Malorie Hughes Analyzing Tweets

Malorie Hughes

On the first day I challenged the audience to analyze the tweets from the conference and Malorie Hughes, a data scientist with NPR, designed a Twitter analytics dashboard to track the attendee with the most tweets with the hashtag #rstatsdc. Seth Wenchel won a WASD keyboard for the best tweeting. And we presented Malorie wit a DCR speaker mug.

Strong Showing from the #RLadies!

The R-Ladies

The #rladies group is growing year after year and it is great seeing them in force at NYR and DCR!

Packages

Matthew Hendrickson, a DCR attendee, posted on twitter every package mentioned during the two-day conference: tidyverse, tidycensus, leaflet, leaflet.extras, funneljoin, glmnet, xgboost, rstan, rstanarm, LowRankQP, dplyr, coefplot, bayesplot, keras, tensorflow, lars, magrittr, purrr, rsample, useful, knitr, rmarkdown, ggplot2, ggiraph, ggrepel, ggraph, ggthemes, gganimate, ggmap, plotROC, ggridges, gtrendsr, tlnise, tm, Bioconductor, plyranges, sf, tmap, textmineR, tidytext, gmailr, rtweet, shiny, httr, parsnip, probably, plumber, reprex, crosstalk, arules and arulesviz.

Data Community DC

Data Community DC

A special thanks to the Data Community DC for helping us make the DC R Conference an incredible experience.

Videos

The videos for the conference will be posted in the coming weeks to dc.rstats.ai.

See You Next Year

Looking forward to more great conferences at next year’s NYR and DCR!

For a while I’ve been trying to find the best slideshow format to create using RMarkdown. My go-to format is ioslides because it has a presenter mode that works in self-contained mode, meaning the entire presentation is in one file. The drawback is that fullscreen images is not a built in feature.

Another popular format is reveal.js. This allows for fullscreen images, but presenter mode is not possible while keeping the file self-contained.

A very promising format is from the xaringan package which is based on remarkjs. This allows for beautiful, fullscreen images and it has an excellent presenter mode. This can all be done with a self-contained file. The problem is, due to the nature of the format, having all the images URI encoded for self-contained mode causes the file to open very slowly. I gave a talk about web scraping at the MIT Sports Analytics Conference which takes over five minutes to open.

Given all this, I decided to hack my way to a solution using ioslides. After some prep it works quite well.

This is a long post, so if you want it all in one place, skip ahead.

The Problem

RMarkdown slides are initiated using two hash tags (##). Metadata can be encoded in curly braces ({}) after the hash tags and any heading text.

## Heading Text {.SlideClass #SlideID0 attr=value0}

Slide Content

The thing is, SlideClass, SlideID and the attr value are applied to an <article> tag inside a <slide>, not to the <slide>.

<slide class=''>
    <hgroup>
        <h2>Heading Text</h2>
    </hgroup>

    <article  attr="value0" class="SlideClass" id="SlideID0">
        <p>Slide Content</p>
    </article>
</slide>

This precludes us from setting style="background-url(filename.jpg)" in the header metadata. Further, doing so would still leave just a link to the file and now URI encode it.

The Solution

The solution is to specify the image in CSS and associate it with a specific ID. However, at this point, it will only be associated with the <article>.

#SlideID1 {
    background-image: url(Cowboy-Lasso.jpg);
}

To keep things looking nice, in a separate CSS block we specify some background image properties that apply to all slide background images.

slide {
    background-position: center;
    background-repeat: no-repeat;
    background-size: contain;
}
## Background One {.SlideClass #SlideID1}

Some Text Here
knitr::include_graphics(file.path(imageDir, 'Background-Article.png'))

The trick is to associate the image, in CSS, with the ID of the <slide>. Even though we assign an ID to the <article> this does not help us know the ID of the <slide>. To get around this we use a bit of jQuery. We write some code that take a name attribute from every <article> tag and assigns it as an ID for the corresponding <slide> tags.

$(document).ready(function(){
    // for every article tag inside a slide tag
    $("slide > article").each(function(){
        // copy the article name to the parentNode's (the slide) ID
        this.parentNode.id=$(this).attr('name');
    });
});

In order for this to work, we also need to load jQuery. The quickest way I have found to do this is to use htmltools to

```{r deps,include=FALSE}
# this ensures jquery is loaded
dep <- htmltools::htmlDependency(name = "jquery", version = "1.11.3", src = system.file("rmd/h/jquery-1.11.3", package='rmarkdown'), script = "jquery.min.js")
# attach the dependency to an empty span
htmltools::attachDependencies(htmltools::tags$span(''), dep)
```

The order matters, and jQuery must be loaded first. So rather than deal with this code every time we write a presentation let’s be good coders and save this to an Rmd file called ‘LoadJQuery.Rmd’.

---
title: "Load JQuery"
author: "Jared P. Lander"
date: "July 1, 2017"
output: ioslides_presentation
---

```{r deps,include=FALSE}
# this ensures jquery is loaded
dep <- htmltools::htmlDependency(name = "jquery", version = "1.11.3", src = system.file("rmd/h/jquery-1.11.3", package='rmarkdown'), script = "jquery.min.js")
htmltools::attachDependencies(htmltools::tags$span(''), dep)
```

```{js move-id-background-color}
$(document).ready(function(){
    // for every article tag inside a slide tag
    $("slide > article").each(function(){
        // copy the article name to the parentNode's (the slide) ID
        this.parentNode.id=$(this).attr('name');
    });
});
```

Then in the presentation Rmd file, toward the top, this file is loaded as a chunk child.

```{r load-jquery,child='LoadJQuery.Rmd'}
```

Now, any time a name attribute is included in heading metadata, that name will become the id for the enclosing <slide>.

## Background Two {.SlideClass #SlideID2 name=Slide2}

Some more text here

becomes

<slide class="current" data-slide-num="4" data-total-slides="4" id="Slide2">
    <hgroup>
        <h2>Background Two</h2>
    </hgroup>
    
    <article id="SlideID2" class="SlideClass">
        <p>Some more text here</p>
    </article>
</slide>

Then there is the matter of writing the CSS so that the image file is URI encoded. This can become laborious so we write a function to do it.

```{r background-function,include=FALSE}
makeBG <- function(id, file)
{
    cat(
        sprintf('<style type="text/css">\n#%s {\nbackground-image: url(%s);\n}\n</style>',
                id, knitr::image_uri(file))
    )
}
```

Anywhere in the document, though most logically in the intended slide, that function is called, specifying the slide ID and the image.

## Background Three {.SlideClass #SlideID3}

Full screen background

```{r results='asis',echo=FALSE}
makeBG(id='Slide3', 'Cowboy-Lasso.jpg')
```

This results in the following slide.