Package 'd3r' reference manual

Title:	'd3.js' Utilities for R
Description:	Provides a suite of functions to help ease the use of 'd3.js' in R. These helpers include 'htmltools::htmlDependency' functions, hierarchy builders, and conversion tools for 'partykit', 'igraph,' 'table', and 'data.frame' R objects into the 'JSON' that 'd3.js' expects.
Authors:	Mike Bostock [aut, cph] (d3.js library in htmlwidgets/lib, http://d3js.org), Kent Russell [aut, cre, cph] (R interface), Gregor Aisch [aut, cph] (d3-jetpack creator, https://github.com/gka/d3-jetpack), Adam Pearce [aut] (core contributor to d3-jetpack), Ben Ortiz [ctb]
Maintainer:	Kent Russell <[email protected]>
License:	BSD_3_clause + file LICENSE
Version:	1.1.0
Built:	2024-10-26 02:55:06 UTC
Source:	https://github.com/timelyportfolio/d3r

Change Column Name in Children to "name"

Description

Change Column Name in Children to "name"

Usage

change_to_name(x, column = 1)
change_to_name(x, column = 1)

Arguments

`x`	`data.frame` or `data.frame` derivative, such as `tibble`
`column`	column to convert

Value

data.frame

'd3.js' Dependency for Version 4 Jetpack

Description

d3-jetpack is a set of nifty convenience wrappers that speed up your daily work with d3.js. Must be included after d3_dep_v4(). Learn more by reading d3-jetpack or by watching this YouTube.

Usage

d3_dep_jetpack(offline = TRUE)
d3_dep_jetpack(offline = TRUE)

Arguments

offline

logical to specify whether to use a local copy of d3.js (TRUE) or use cdn (FALSE)

Value

htmltools::htmlDependency

Examples

## Not run: 

library(d3r)
library(htmltools)

tl <- tagList(tags$script(HTML(sprintf(
"
var x = 5;

var svg = d3.select('body')
    .append('svg');

svg.append('rect')
    .at({
        x: 100,
        y: 100,
        width: 100,
        height: 100
    })
    .st({
        fill: 'blue',
        stroke: 'purple'
    });
"
))), d3_dep_v4(), d3_dep_jetpack())
browsable(tl)



tl <- tagList(tags$script(HTML(sprintf(
 "
 var svg = d3.select('body')
     .append('svg');

 test_data = [{x: 250, y: 250}, {x: 300, y: 300}, {x: 300, y: 100}];

 svg.appendMany(test_data, 'circle')
     .at({
         cx: function(d){return d.x},
         cy: function(d){return d.y},
         r: 50
     })
     .st({
         fill: 'purple',
         stroke: 'blue'
     });
 "
))), d3_dep_v4(), d3_dep_jetpack())

browsable(tl)


## End(Not run)
## Not run: 

library(d3r)
library(htmltools)

tl <- tagList(tags$script(HTML(sprintf(
"
var x = 5;

var svg = d3.select('body')
    .append('svg');

svg.append('rect')
    .at({
        x: 100,
        y: 100,
        width: 100,
        height: 100
    })
    .st({
        fill: 'blue',
        stroke: 'purple'
    });
"
))), d3_dep_v4(), d3_dep_jetpack())
browsable(tl)



tl <- tagList(tags$script(HTML(sprintf(
 "
 var svg = d3.select('body')
     .append('svg');

 test_data = [{x: 250, y: 250}, {x: 300, y: 300}, {x: 300, y: 100}];

 svg.appendMany(test_data, 'circle')
     .at({
         cx: function(d){return d.x},
         cy: function(d){return d.y},
         r: 50
     })
     .st({
         fill: 'purple',
         stroke: 'blue'
     });
 "
))), d3_dep_v4(), d3_dep_jetpack())

browsable(tl)


## End(Not run)

'd3.js' Dependency for Version 3

Description

'd3.js' Dependency for Version 3

Usage

d3_dep_v3(offline = TRUE)
d3_dep_v3(offline = TRUE)

Arguments

offline

logical to specify whether to use a local copy of d3.js (TRUE) or use cdn (FALSE)

Value

htmltools::htmlDependency

Examples

library(d3r)
library(htmltools)

tagList(d3_dep_v3())
library(d3r)
library(htmltools)

tagList(d3_dep_v3())

'd3.js' Dependency for Version 4

Description

'd3.js' Dependency for Version 4

Usage

d3_dep_v4(offline = TRUE)
d3_dep_v4(offline = TRUE)

Arguments

offline

logical to specify whether to use a local copy of d3.js (TRUE) or use cdn (FALSE)

Value

htmltools::htmlDependency

Examples

library(d3r)
library(htmltools)

tagList(d3_dep_v4())
library(d3r)
library(htmltools)

tagList(d3_dep_v4())

'd3.js' Dependency for Version 5

Description

'd3.js' Dependency for Version 5

Usage

d3_dep_v5(offline = TRUE)
d3_dep_v5(offline = TRUE)

Arguments

offline

logical to specify whether to use a local copy of d3.js (TRUE) or use cdn (FALSE)

Value

htmltools::htmlDependency

Examples

library(d3r)
library(htmltools)

tagList(d3_dep_v5())
library(d3r)
library(htmltools)

tagList(d3_dep_v5())

'd3.js' Dependency for Version 6

Description

'd3.js' Dependency for Version 6

Usage

d3_dep_v6(offline = TRUE)
d3_dep_v6(offline = TRUE)

Arguments

offline

logical to specify whether to use a local copy of d3.js (TRUE) or use cdn (FALSE)

Value

htmltools::htmlDependency

Examples

library(d3r)
library(htmltools)

tagList(d3_dep_v6())
library(d3r)
library(htmltools)

tagList(d3_dep_v6())

'd3.js' Dependency for Version 7

Description

'd3.js' Dependency for Version 7

Usage

d3_dep_v7(offline = TRUE)
d3_dep_v7(offline = TRUE)

Arguments

offline

logical to specify whether to use a local copy of d3.js (TRUE) or use cdn (FALSE)

Value

htmltools::htmlDependency

Examples

library(d3r)
library(htmltools)

tagList(d3_dep_v7())
library(d3r)
library(htmltools)

tagList(d3_dep_v7())

Convert 'igraph' to 'd3.js'

Description

Convert 'igraph' to 'd3.js'

Usage

d3_igraph(igrf = NULL, json = TRUE)
d3_igraph(igrf = NULL, json = TRUE)

Arguments

`igrf`	`igraph`
`json`	`logical` to return as `JSON`

Value

list

Examples

## Not run: 
library(igraph)
library(igraphdata)
library(d3r)

# with random graph
d3r::d3_igraph(igraph::sample_pa(100))

# check case where vertices 0 cols
d3_igraph(igraph::watts.strogatz.game(1, 50, 4, 0.05))

# with karate from igraphdata
#  notice graph attributes are added
data("karate",package="igraphdata")
(karate_d3 <- d3r::d3_igraph(karate))

listviewer::jsonedit(karate_d3)

data("kite",package="igraphdata")
listviewer::jsonedit(d3_igraph(kite))

## End(Not run)
## Not run: 
library(igraph)
library(igraphdata)
library(d3r)

# with random graph
d3r::d3_igraph(igraph::sample_pa(100))

# check case where vertices 0 cols
d3_igraph(igraph::watts.strogatz.game(1, 50, 4, 0.05))

# with karate from igraphdata
#  notice graph attributes are added
data("karate",package="igraphdata")
(karate_d3 <- d3r::d3_igraph(karate))

listviewer::jsonedit(karate_d3)

data("kite",package="igraphdata")
listviewer::jsonedit(d3_igraph(kite))

## End(Not run)

Create 'JSON' that 'd3.js' Expects

Description

Create 'JSON' that 'd3.js' Expects

Usage

d3_json(x = NULL, strip = TRUE)
d3_json(x = NULL, strip = TRUE)

Arguments

`x`	data, usually in the form of `data.frame` or `list`
`strip`	`logical` to remove outer array. Use `strip=TRUE` for hierarchies from `d3_nest`

Value

string of 'JSON' data

Convert a `data.frame` to a 'd3.js' Hierarchy

Description

Convert a data.frame to a 'd3.js' Hierarchy

Usage

d3_nest(data = NULL, value_cols = character(), root = "root", json = TRUE)
d3_nest(data = NULL, value_cols = character(), root = "root", json = TRUE)

Arguments

`data`	`data.frame` or `data.frame` derivative, such as `tibble`
`value_cols`	`character` vector with the names of the columns to use as data
`root`	`character` name of the root level of the hierarchy
`json`	`logical` to return as `JSON`

Value

nested data.frame

Examples

# convert Titanic to a nested d3 hierarchy

# devtools::install_github("timelyportfolio/d3r")
library(d3r)
library(dplyr)

titanic_df <- data.frame(Titanic)
tit_tb <- titanic_df %>%
  select(Class,Age,Survived,Sex,Freq) %>%
  d3_nest(value_cols="Freq", root="titanic")

tit_tb

# see as tibble
titanic_df %>%
  select(Class,Age,Survived,Sex,Freq) %>%
  d3_nest(value_cols="Freq", root="titanic", json=FALSE)

# see the structure with listviewer
tit_tb %>%
  listviewer::jsonedit()
## Not run: 
  library(treemap)
  library(d3r)
  library(dplyr)
  library(tidyr)

  treemap::random.hierarchical.data() %>%
    d3_nest(value_cols = "x")

  # use example from ?treemap
  data(GNI2014)
  treemap(
    GNI2014,
    index=c("continent", "iso3"),
    vSize="population",
    vColor="GNI",
    type="value",
    draw=FALSE
  ) %>%
    {.$tm} %>%
    select(continent,iso3,color,vSize) %>%
    d3_nest(value_cols = c("color", "vSize"))

## End(Not run)
# convert Titanic to a nested d3 hierarchy

# devtools::install_github("timelyportfolio/d3r")
library(d3r)
library(dplyr)

titanic_df <- data.frame(Titanic)
tit_tb <- titanic_df %>%
  select(Class,Age,Survived,Sex,Freq) %>%
  d3_nest(value_cols="Freq", root="titanic")

tit_tb

# see as tibble
titanic_df %>%
  select(Class,Age,Survived,Sex,Freq) %>%
  d3_nest(value_cols="Freq", root="titanic", json=FALSE)

# see the structure with listviewer
tit_tb %>%
  listviewer::jsonedit()
## Not run: 
  library(treemap)
  library(d3r)
  library(dplyr)
  library(tidyr)

  treemap::random.hierarchical.data() %>%
    d3_nest(value_cols = "x")

  # use example from ?treemap
  data(GNI2014)
  treemap(
    GNI2014,
    index=c("continent", "iso3"),
    vSize="population",
    vColor="GNI",
    type="value",
    draw=FALSE
  ) %>%
    {.$tm} %>%
    select(continent,iso3,color,vSize) %>%
    d3_nest(value_cols = c("color", "vSize"))

## End(Not run)

Convert partykit to d3.js hierarchy

Description

This thing is not even close to being done, so please help with ideas and contributions.

Usage

d3_party(tree = NULL, json = TRUE)
d3_party(tree = NULL, json = TRUE)

Arguments

`tree`	`partykit` object to be converted
`json`	`logical` to return `list` or `json`

Value

list or json depending on json arg

Examples

## Not run: 

  library(d3r)
  # from ?rpart
  data("kyphosis", package="rpart")
  d3_party(
    rpart::rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
  )

  # if you want the list instead of json
  d3_party(
    rpart::rpart(Kyphosis ~ Age + Number + Start, data = kyphosis),
    json = FALSE
  )

  # with ctree instead of rpart
  #  using example from ?ctree
  d3_party(partykit::ctree(Species ~ .,data = iris))


  #devtools::install_github("timelyportfolio/d3treeR")

  library(d3treeR)

  d3tree2(
    d3_party(
      rpart::rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
    ),
    celltext = "rule",
    valueField = "n"
  )


## End(Not run)
## Not run: 

  library(d3r)
  # from ?rpart
  data("kyphosis", package="rpart")
  d3_party(
    rpart::rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
  )

  # if you want the list instead of json
  d3_party(
    rpart::rpart(Kyphosis ~ Age + Number + Start, data = kyphosis),
    json = FALSE
  )

  # with ctree instead of rpart
  #  using example from ?ctree
  d3_party(partykit::ctree(Species ~ .,data = iris))


  #devtools::install_github("timelyportfolio/d3treeR")

  library(d3treeR)

  d3tree2(
    d3_party(
      rpart::rpart(Kyphosis ~ Age + Number + Start, data = kyphosis)
    ),
    celltext = "rule",
    valueField = "n"
  )


## End(Not run)

Converts Table to 'd3' Nodes and Links

Description

Converts Table to 'd3' Nodes and Links

Usage

d3_table(tB = NULL, vars = NULL, agg = "Freq")
d3_table(tB = NULL, vars = NULL, agg = "Freq")

Arguments

`tB`	`table` to convert
`vars`	`character` vector of column names
`agg`	`character` column name of aggregated value

Value

list of two data.frames - one for nodes and one for links of the network. This structure is helpful when working with networkD3 and visNetwork.

Examples

library(d3r)
d3_table(Titanic, c("Class","Sex"))

library(d3r)
d3_table(Titanic, c("Class","Sex"))

Create V8 Context with D3

Description

Create V8 Context with D3

Usage

d3_v8(...)
d3_v8(...)

Arguments

...

arguments passed to v8()

Value

v8 context with d3.js loaded and available as d3

Examples

## Not run: 

# to do this all in R, please see ggraph
# https://github.com/thomasp85/ggraph
# by Thomas Lin Pedersen
library(d3r)

# make a simple data.frame of US state data
states <- data.frame(
  region = as.character(state.region),
  state = as.character(state.abb),
  population = state.x77[,"Population"],
  stringsAsFactors = FALSE
)

# use d3_nest to get the data.frame in a d3 hierarchy
state_hier <- d3_nest(
  states,
  value_cols = "population"
)

# use d3_v8 to do something useful with d3 and, our state data
ctx <- d3_v8()
ctx$eval(sprintf(
  " var states = %s",
  state_hier
))
ctx$eval(
"
// we assigned the variable states above
//  so now make it a real d3 hierarchy
var root = d3.hierarchy(states);

// sum on population
root.sum(function(d) {return d.population ? d.population : 0});


// use d3 to circle pack or state hierarchy
d3.pack()(root);

// get something we can convert into a data.frame in R
var states_packed = [];
root.each(function(d) {
  states_packed.push({
    name: d.data.name,
    radius: d.r,
    x: d.x,
    y: d.y
  });
});
"
)

# now get states_packed from our context
#  to plot in R
states_packed <- ctx$get("states_packed")
opar <- par(no.readonly=TRUE)
# make it square
par(pty="s")
symbols(
  states_packed$x,
  states_packed$y,
  states_packed$radius,
  inches=FALSE,
  asp=1
)
text(y~x, data=states_packed, labels=states_packed$name)
# return to original par before we made it square
par(opar)

# d3.quadtree example

library(d3r)

x = runif(100)
y = runif(100)

ctx <- d3_v8()
# assign pts as array of pts in V8
ctx$assign("pts", matrix(c(x,y),ncol=2,byrow=TRUE))
# use d3.quadtree() to plot rects
ctx$eval(
  "
  var d3q = d3.quadtree()
  .addAll(pts);
  // nodes function from https://bl.ocks.org/mbostock/4343214
  function nodes(quadtree) {
  var nodes = [];
  quadtree.visit(function(node, x0, y0, x1, y1) {
  nodes.push({x0:x0, y0:y0, x1: x1, y1: y1})
  });
  return nodes;
  }
  "
)

nodes <- ctx$get("nodes(d3q)", simplifyVector = FALSE)
# draw points
opar <- par(no.readonly=TRUE)
# make it square
par(pty="s")
plot(y~x)
# draw quadtree rects
rect(
  lapply(nodes,function(x){x$x0}),
  lapply(nodes,function(x){x$y0}),
  lapply(nodes,function(x){x$x1}),
  lapply(nodes,function(x){x$y1})
)
par(opar)

## End(Not run)
## Not run: 

# to do this all in R, please see ggraph
# https://github.com/thomasp85/ggraph
# by Thomas Lin Pedersen
library(d3r)

# make a simple data.frame of US state data
states <- data.frame(
  region = as.character(state.region),
  state = as.character(state.abb),
  population = state.x77[,"Population"],
  stringsAsFactors = FALSE
)

# use d3_nest to get the data.frame in a d3 hierarchy
state_hier <- d3_nest(
  states,
  value_cols = "population"
)

# use d3_v8 to do something useful with d3 and, our state data
ctx <- d3_v8()
ctx$eval(sprintf(
  " var states = %s",
  state_hier
))
ctx$eval(
"
// we assigned the variable states above
//  so now make it a real d3 hierarchy
var root = d3.hierarchy(states);

// sum on population
root.sum(function(d) {return d.population ? d.population : 0});


// use d3 to circle pack or state hierarchy
d3.pack()(root);

// get something we can convert into a data.frame in R
var states_packed = [];
root.each(function(d) {
  states_packed.push({
    name: d.data.name,
    radius: d.r,
    x: d.x,
    y: d.y
  });
});
"
)

# now get states_packed from our context
#  to plot in R
states_packed <- ctx$get("states_packed")
opar <- par(no.readonly=TRUE)
# make it square
par(pty="s")
symbols(
  states_packed$x,
  states_packed$y,
  states_packed$radius,
  inches=FALSE,
  asp=1
)
text(y~x, data=states_packed, labels=states_packed$name)
# return to original par before we made it square
par(opar)

# d3.quadtree example

library(d3r)

x = runif(100)
y = runif(100)

ctx <- d3_v8()
# assign pts as array of pts in V8
ctx$assign("pts", matrix(c(x,y),ncol=2,byrow=TRUE))
# use d3.quadtree() to plot rects
ctx$eval(
  "
  var d3q = d3.quadtree()
  .addAll(pts);
  // nodes function from https://bl.ocks.org/mbostock/4343214
  function nodes(quadtree) {
  var nodes = [];
  quadtree.visit(function(node, x0, y0, x1, y1) {
  nodes.push({x0:x0, y0:y0, x1: x1, y1: y1})
  });
  return nodes;
  }
  "
)

nodes <- ctx$get("nodes(d3q)", simplifyVector = FALSE)
# draw points
opar <- par(no.readonly=TRUE)
# make it square
par(pty="s")
plot(y~x)
# draw quadtree rects
rect(
  lapply(nodes,function(x){x$x0}),
  lapply(nodes,function(x){x$y0}),
  lapply(nodes,function(x){x$x1}),
  lapply(nodes,function(x){x$y1})
)
par(opar)

## End(Not run)

Apply 'promote_na' to All Rows

Description

Apply 'promote_na' to All Rows

Usage

promote_na(x)
promote_na(x)

Arguments

`x`	`data.frame`

Value

data.frame

Promote NA to Top Level

Description

Promote NA to Top Level

Usage

promote_na_one(x)
promote_na_one(x)

Arguments

`x`	`data.frame`

Value

data.frame

Package 'd3r'

Help Index

Change Column Name in Children to "name"

Description

Usage

Arguments

Value

'd3.js' Dependency for Version 4 Jetpack

Description

Usage

Arguments

Value

See Also

Examples

'd3.js' Dependency for Version 3

Description

Usage

Arguments

Value

See Also

Examples

'd3.js' Dependency for Version 4

Description

Usage

Arguments

Value

See Also

Examples

'd3.js' Dependency for Version 5

Description

Usage

Arguments

Value

See Also

Examples

'd3.js' Dependency for Version 6

Description

Usage

Arguments

Value

See Also

Examples

'd3.js' Dependency for Version 7

Description

Usage

Arguments

Value

See Also

Examples

Convert 'igraph' to 'd3.js'

Description

Usage

Arguments

Value

Examples

Create 'JSON' that 'd3.js' Expects

Description

Usage

Arguments

Value

Convert a data.frame to a 'd3.js' Hierarchy

Description

Usage

Arguments

Value

Examples

Convert partykit to d3.js hierarchy

Description

Usage

Arguments

Value

Examples

Converts Table to 'd3' Nodes and Links

Description

Usage

Arguments

Value

Examples

Create V8 Context with D3

Description

Convert a `data.frame` to a 'd3.js' Hierarchy