Where’s the love for htmlwidgets?

If you’ve never heard of them, htmlwidgets are an amazing part of the work that RStudio (plus ramnathv and timelyportfolio) have undertaken to make R a beautiful tool for doing data science and communicating things about your data. Using leaflet, plotly, highcharter and more it’s possible to create rich interactive charts, maps and other visualisations directly from R without having to learn JavaScript

Charlie Hadley


February 7, 2018

If you’ve never heard of them, htmlwidgets are an amazing part of the work that RStudio (plus Ramnath Vaidyanathan and Kent Russell)1 have undertaken to make R a beautiful tool for doing data science and communicating things about your data. You probably haven’t heard about htmlwidgets, so let’s cover what it is first:

htmlwidgets is a tool for R developers that allows them to easily build R wrappers for JavaScript libraries, which means useRs can build interactive visualisations! Here are two of my favourite htmlwidget libraries:

  • highcharter: uses the awesome Highcharts library and allows beautiful looking charts, time series and more to be created directly from R code! I really love how professional it looks - see what happens if you select one of the items in the legend 😄

  • leaflet: uses the awesome Leaflet library that allows us to create interactive maps, choropleth and other charts. It has a cousin called mapview that’s even more powerful that I’ll be switching preference to as 2018 rolls on.

So why do I assume you haven’t heard of them?

Well, they’re hardly ever spoken about or searched for! Hadley Wickham is a huge promoter of the benefits of visualisation in data science2 but has only ever mentioned htmlwidgets on Twitter explicitly 3 times prior to February 2018. And just compare the Google Search Trends for tidyverse and htmlwidgets, there’s desperately little love for htmlwidgets.

The crux of the problem really is that htmlwidgets is a developer tool. The actual packages that folks build using it are really popular! htmlwidgets spiritual home is htmlwidgets.org which is maintained by the RStudio folks, where they keep a list of featured htmlwidgets libraries available oin CRAN. Here’s a quick overview of these libraries (as of February 2018), with the following notes:

It’s really easy to get download figures for CRAN using the cranlogs library. In the table below I’ve collected the daily download figures for the featured_htmlwidget_libraries from the first date htmlwidgets was published until 2022-06-20 and then calculated the median daily downloads.

## Get first release date of htmlwidgets
## This takes much longer than I'd like to run, so I've cheated
# vhistory_htmlwidgets <- versions::available.versions("htmlwidgets")
# release_date_htlmlwidgets <- vhistory_htmlwidgets$htmlwidgets %>%
#   filter(date == min(date)) %>%
#   select(date) %>%
#   .[[1]]
release_date_htlmlwidgets <- lubridate::ymd("2014-12-09")

cran_downloads <- featured_htmlwidget_libraries %>%
  select(package) %>%
  pmap(function(package, ...) {
    cran_downloads(packages = package, from = "2014-12-09", to = Sys.Date())
  }) %>%
  bind_rows() %>%

median_daily_downloads <- cran_downloads %>%
  filter(count > 0) %>%
  filter(package != "htmlwidgets") %>%
  group_by(package) %>%
  summarise(median.downloads = median(count)) %>%

dt_median_daily_downloads <- median_daily_downloads %>%
    options = list(dom = "t", pageLength = 13),
    colnames = c("htmlwidget library", "Median daily downloads (excluding zero download days)")

The top 6 libraries all have an median of more than 100 daily downloads, is that impressive? Well, I don’t have any feel for that unfortunately. The cranlogs tells us about top 100 downloaded packages, but these download figures are going to suffer from a highly positively skewed distribution. It would be fun to investigate this distribution and come back to this question in the future. All I want to show here is that the htmlwidgets libraries are really popular, but that there’s little exposure for the htmlwidgets branding.

I can demonstrate the growing popularity of the libraries with a timeseries chart using dygraphs, I’ve chosen to perform a simple 28-day moving average on the data as there is a lot of inter-day noise:

## CSS hackery to place the legend nicely and account for the yellow colour in the "Paired"
## colour scheme
dygraph_css <- tempfile(fileext = ".css")
dygraph_css_file <- file(dygraph_css)
writeLines(".dygraph-title {color: navy;font-weight: bold;}
.dygraph-axis-label {font-weight: bold;}
.dygraph-legend {background: #ebebeb !important;left: 100px !important;top: 100px !important;}
.dygraph {background: #ebebeb !important;}", dygraph_css_file)
cran_downloads_28ma <- cran_downloads %>%
  filter(package != "htmlwidgets") %>%
  group_by(package) %>%
  mutate(mean.count = rollmean(
    count, k = 28, na.pad = TRUE,
    align = "right"
  )) %>%
  ungroup() %>%
  replace_na(list(mean.count = 0)) %>%

cran_downloads_28ma %>%
  mutate(package = fct_relevel(package, median_daily_downloads$package)) %>%
  spread(package, mean.count) %>%
  # filter(date > ymd("2017-08-01")) %>%
  timetk::tk_xts(date_var = date) %>%
  dygraph(main = "Featured htmlwidgets library downloads from CRAN<br> <span style='font-size:18px;'>(28 day moving average)</span>",
          width = "100%") %>%
  dyCSS(dygraph_css) %>%
  dyOptions(colors = RColorBrewer::brewer.pal(12, "Paired")) %>%
  dyAxis("y", label = "CRAN Downloads") %>%
  dyLegend(labelsSeparateLines = TRUE)

I hoped to get a good idea on Twitter about how many folks were using htmlwidgets libraries without knowing that’s what they were. Unfortuntely, the reach of my poll was very small with the tweet only appearing in a timeline 307 times. I’d really like to collect more data about this and return to this topic in the future.

Promoting the htmlwidgets brand

I think it’s shame that there isn’t more exposure for the htmlwidgets brand and underlying technology. I meet a lot of folks in my training courses who have simply never heard the term, despite perhaps using leaflet or plotly already. If these folks knew they were htmlwidgets they could perhaps find more tools for visualising their data in new and interesting ways.

These are the things I’d really love to see:

  • htmlwidgets hexsticker: Hexstickers are awesome and really popular amongst useRs, it would be awesome to have a dedicated sticker for the htmlwidgets brand.
  • htmlwidgets mentioned in plain simple human language in the following places; GitHub README pages, Package DESCRIPTION files, and in the welcome pages for dedicated package websites. Of course, displaying the htmlwidgets hexsticker on the README would really help promote the brand
  • Talk about htmlwidgets more in Tweets and other comms channels from RStudio.

I kind of get the feeling that htmlwidgets is currently in stealth mode and I’m not sure why. Maybe RStudio are waiting until the (exciting!) crosstalk features are added to more htmlwidgets libraries? But that feels like a 2.0 feature!

I’m going to do everything I can in my teaching, evangelism and general talking about R at parties to promote htmlwidgets and I’d love to see others do the same. I also plan to come back later and revisit this subject, analysing other datasets (like StackOverflow questions) and seeing if anything has changed.

I will finish off with a little bit of self-promotion. I have a 5 hour+ overview of htmlwidgets on LinkedIn Learning and Lynda.com that you might find useful:

R: Interactive Visualizations with htmlwidgets by Martin Hadley


  1. Thanks to Joe Chung for highlighting @ramnath_vaidya and @timelyportfolio’s contributions on Twitter link.↩︎

  2. Citation needed.↩︎



BibTeX citation:
  author = {Charlie Hadley},
  title = {Where’s the Love for Htmlwidgets?},
  date = {2018-02-07},
  url = {https://visibledata.co.uk/posts/2018-02-07_where-s-the-love-for-htmlwidgets},
  langid = {en}
For attribution, please cite this work as:
Charlie Hadley. 2018. “Where’s the Love for Htmlwidgets?” February 7, 2018. https://visibledata.co.uk/posts/2018-02-07_where-s-the-love-for-htmlwidgets.