Why d3r?"
In d3r: 'd3.js' Utilities for R

d3r doesn't make beautiful interactive htmlwidgets, so what does it do? d3r provides helpers for d3.js in R by providing two (and more coming) functions. Note: this is very much a work in progress

easy dependency functions for d3.js v3 and v4
converter for R data structures to d3.js nested hierarchies

dependency functions

There are a whole lot of htmlwidgets built on top of d3.js, and each one requires a local copy of d3.js. On my computer, this means I have >15 copies of d3.js in my R library. When I build a htmlwidget, I have to copy d3.min.js along with license and other meta information. Lots of times I just want to add d3 to my htmltools::tags. d3r solves all of these problems by supplying functions d3_dep_v3() and d3_dep_v4() that return up-to-date htmltools::htmlDependency for d3. I'll start to convert each of my d3-based htmlwidgets to use d3r, and my life as an htmlwidget author will become easier. I will not need to worry any more when d3 updates. To add a dependency to a htmlwidget, we can use this pattern.

library(d3r)

widget$dependencies <- c(
  widget$dependencies,
  d3r::d3_dep_d3()
)

Often, I build ad-hoc html with htmltools::tags, and I want all the power of d3.js. Usually, I'll do something like

tags$head(tags$script("http://d3js.org/d3.v3.min.js"))

which isn't so bad but I lose the dependency conflict management built into htmltools and htmlwidgets. The more robust way is to use htmltools::htmlDependency.

attachDependencies(
  tagList(...),
  htmlDependency(
    name="d3",
    version="3.5.7",
    src=c(href="https://d3js.org"),
    script="d3.v3.min.js"
  )
)

That is a lot to type, so let's save a couple of lines with our new d3r helper function.

library(d3r)
attachDependencies(
  tagList(...),
  d3r::d3_dep_v4()
)

d3 hierarchy builder

Nested d3 hierarchies can be tricky especially for users from other languages, such as R, and for those not trained in the specialized dark of art of nested JSON. After converting R data to nested d3 hierarchies in many ways, I decided it was time to leverage my favorite pattern using tidyr::nest and dplyr to convert a R data.frame to a d3 hierarchy.

library(d3r)

(d3n <- d3_nest(
  data.frame(
    number=rep(1:4,each=3),
    letter=LETTERS[1:12],
    value=runif(12),
    stringsAsFactors=FALSE
  ),
  value_cols="value"
))

listviewer::jsonedit will help us visualize our hierarchy.

listviewer::jsonedit(d3n)

The data in the above example was not all that exciting. Let's look at how we might go from a R table to nested d3.

library(pipeR)

# will soon make s3 generic for table so no need
#  to explicitly convert to data.frame

Titanic %>>%
  as.data.frame() %>>%
  d3_nest(value_cols="Freq") %>>%
  listviewer::jsonedit()

lots more

There is a whole lot more left to do, but I think the current set of d3r functionality will already make using d3.js in R a little more pleasant. Please let me know if you have any ideas or spot any problems.