Title: Interactive Charts of Nested and Hierarchical Data with 'D3.js'
Version: 0.5.0
Description: Builds interactive 'd3.js' hierarchical visualisation easily. D3partitionR makes it easy to build and customize sunburst, circle treemap, treemap, partition chart, ...
Depends: R (≥ 3.3.1)
Imports: data.table, magrittr, htmlwidgets, functional, RColorBrewer, titanic
License: AGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-07 14:24:29 UTC; Antoi
Author: Antoine Guillot [aut, cre], Mike Bostock [aut, cph] (d3.js library, http://d3js.org, nested treemap, icicle, zoomable circle treemap and sunb), Susie Lu [aut, cph] (d3-legend, http://d3-legend.susielu.com/), Kerry Rodden [aut, cph] (Breadcrumb Code for fixed sized breadcrumb.), Nadieh Bremer [aut, cph] (Placement of labels on arcs, https://www.visualcinnamon.com/2015/09/placing-text-on-arcs.html), Hub Spot [aut, cph] (tether.js)
Maintainer: Antoine Guillot <antoine.guil@outlook.fr>
Repository: CRAN
Date/Publication: 2017-10-07 14:36:03 UTC

Creates a D3partitionR object

Description

Creates a D3partitionR object

Usage

D3partitionR()

Value

A blank D3partitionR object (S3 class)

Shiny bindings for D3partitionR

Description

Output and render functions for using D3partitionR within Shiny applications and interactive Rmd documents.

Usage

D3partitionROutput(outputId, width = "100%", height = "400px")

renderD3partitionR(expr, env = parent.frame(), quoted = FALSE)

Arguments

outputId

output variable to read from

width, height

Must be a valid CSS unit (like '100%', '400px', 'auto') or a number, which will be coerced to a string and have 'px' appended.

expr

An expression that generates a D3partitionR

env

The environment in which to evaluate expr.

quoted

Is expr a quoted expression (with quote())? This is useful if you want to save an expression in a variable.

Append data to a D3partitionR object

Description

Append data to a D3partitionR object

Usage

add_data(D3partitionR_object, data, steps, count = "value", color = "name",
  label = "name", tooltip = "name", aggregate_fun = NULL)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

data

a data.frame object

steps

The vector of steps to be used

count

The variable to be used as the count variable, typically, the number of occurences.

color

a variable to use as color (default: name)

label

a variable to use as label (default: name)

tooltip

a variable to use as tooltip (default: name)

aggregate_fun

A named list of function which will be used to aggregates to variables used in color, label or tooltips. This only applies to variable in the provided dataset.

Value

The D3partitionR object with the appended data

Add informations (for instance new names, colors, ....) to the nodes of a D3_partitionR object

Description

Add informations (for instance new names, colors, ....) to the nodes of a D3_partitionR object

Usage

add_nodes_data(D3partitionR_object, nodes_data)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

nodes_data

a names list where the name of each element is the name of a node. The data will be appended to the node in the nested list

Value

The D3partitionR object with the appended nodes data

Add a title to a D3partitionR object

Description

Add a title to a D3partitionR object

Usage

add_title(D3partitionR_object, text, style = NULL)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

text

Title text

style

A valid CSS string which will be applied to the title)

Value

A D3partitionR object

Aggregate a data.frame in long format with a column containing steps of each session For instance the function can be used with a frame of the form Unique ID - Step - Value 1 - ... -Value N

Description

Aggregate a data.frame in long format with a column containing steps of each session For instance the function can be used with a frame of the form Unique ID - Step - Value 1 - ... -Value N

Usage

aggregate_sessions_to_path(data, step_col = "step", id_col = "ID",
  values_cols = NULL, agg_function_path = sum, agg_function_session = sum,
  sep = "->")

Arguments

data

A dataframe

step_col

The name of the column containig the steps. The steps are assumed to be ordered

id_col

Column containing the unique identifier of each session

values_cols

Names of the other columns to keep. Default: NULL

agg_function_path

Aggregation function on a path level

agg_function_session

Aggregation function on a session level

sep

String used to separate the different steps. Default: "->"

Value

A data.table with the columns specified in count_col, value_cols and one column per step in the path

Compile D3partitionR object to plot it

Description

Compile D3partitionR object to plot it

Usage

compile_D3_partitionR(D3partitionR_object)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

Value

A D3partitionR compiled object

Return al the leaf names

Description

Return al the leaf names

Usage

compute_unique_leaf_name(nested_list)

Arguments

nested_list

A nested_list where each node has a name attribute

Transform a dataframe to a nested lists structure (i.e. hierarchical).

Description

Transform a dataframe to a nested lists structure (i.e. hierarchical).

Usage

df_to_nest(data, step_cols, nodes_data = NULL, count_col = "value",
  value_cols = NULL, agg_function = sum, na_behavior = "rm")

Arguments

data

The data frame to convert to the nested structure. It needs to have several comlumns, each ones account for a given step

step_cols

vector containing the names of the columns which should be used as steps. The vector should be ordered. ex: c('step1','step2','step3')

nodes_data

A named list to add addition informations to each nodes

count_col

Number of occurences in this path (succesion of steps). Default: NULL

value_cols

Names of the other columns to keep. Default: NULL

agg_function

aggregation function to be applied to value_cols.Ex: mean, sum. Default: sum. Weighted version can also be used, the weighting will be done using the counting variable

na_behavior

How to deal with missing data ?

Value

A data.table with the columns specified in count_col, value_cols and one column per step in the path

Find the maximum values of a given var in a tree

Description

Find the maximum values of a given var in a tree

Usage

find_min_max_tree(nested_list, variable = "value")

Arguments

nested_list

A nested_list where each node has a name attribute

variable

A nested_list where each node has a name attribute

Return al the possible nodes names

Description

Return al the possible nodes names

Usage

get_all_nodes_names(nested_list, variable = "name")

Arguments

nested_list

A nested_list where each node has a name attribute

variable

the variable to collect

Check if a variable is present in a D3partitionR object

Description

Check if a variable is present in a D3partitionR object

Usage

is_present_variable(variable, D3partitionR_object)

Arguments

variable

The variable which presence is to be checked

D3partitionR_object

The D3partitionR object

Value

TRUE/FALSE

Plot D3partitionR object

Description

Plot D3partitionR object

Usage

## S3 method for class 'D3partitionR'
plot(x, width = NULL, height = NULL,
  elementId = NULL, sizingPolicy = NULL, ...)

Arguments

x

A D3partitionR object to plot

width

width of the widget in pixel/percent

height

height of the widget in pixel/percent

elementId

html id of the widget

sizingPolicy

sizing policy

...

parameters for method consistency

Examples

require(titanic)
require(data.table)
## Reading data
titanic_data = data.table(titanic::titanic_train)

##Agregating data to have unique sequence for the 4 variables
var_names=c('Sex','Embarked','Pclass','Survived')
data_plot=titanic_data[,.N,by=var_names]
data_plot[,(var_names):=lapply(var_names,function(x){data_plot[[x]]=paste0(x,' ',data_plot[[x]])
})]

## Plotting the chart
library("magrittr")
d3=D3partitionR() %>%
 add_data(data_plot,count = 'N',steps=c('Sex','Embarked','Pclass','Survived')) %>%
 add_title('Titanic')
## Not run: 
plot(d3)

## End(Not run)

Check if the scale variable is discrete or continuous

Description

Check if the scale variable is discrete or continuous

Usage

scale_type(color_variable, D3partitionR_object)

Arguments

color_variable

The color variable to be assessed

D3partitionR_object

The D3partitionR object

Value

TRUE/FALSE

Set the chart_type

Description

Set the chart_type

Usage

set_chart_type(D3partitionR_object, chart_type)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

chart_type

type fo chart to use (in c('sunburst','treemap','circle_treemap','partition_chart','icicle') )

Value

A D3partitionR object

Add a custom discrete color scale

Description

Add a custom discrete color scale

Usage

set_continuous_color_scale(D3partitionR_object, color_palette)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

color_palette

a vector of two colors, the first one is use on the bottom of the scale, the other on the top.

Value

A D3partitionR object

Add a custom discrete color scale

Description

Add a custom discrete color scale

Usage

set_discrete_color_scale(D3partitionR_object, color_palette)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

color_palette

A vector (or a named vector with levels of the variable color)

Value

A D3partitionR object

Set the labels parameters

Description

Set the labels parameters

Usage

set_labels_parameters(D3partitionR_object, visible = T, cut_off = 3,
  style = NULL)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

visible

boolean, should the labels be diplayed ? Default: TRUE

cut_off

a numeric variable between 0 and 100. Nodes which represent less than cut_off percents of the current root will have their labels hidden.

style

a valid CSS string to be applied to the labels. Default: NULL

Value

A D3partitionR object

Set the legend parameter

Description

Set the legend parameter

Usage

set_legend_parameters(D3partitionR_object, visible = T, zoom_subset = F,
  width = 100)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

visible

boolean, should the trail be diplayed ? Default: TRUE

zoom_subset

boolean, if TRUE, only the modalities present in the children of the zoomed rrot are displayed kin the legend.

width

legend width in pixel

Value

A D3partitionR object

Configuration of a D3partitionR object as a Shiny input

Description

Configuration of a D3partitionR object as a Shiny input

Usage

set_shiny_input(D3partitionR_object, input_id,
  enabled_inputs = list(clicked_node = T, leaves = T, nodes = T, ancestors =
  T, children_path = F))

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

input_id

The id of the input

enabled_inputs

which inputs should be enabled ? defaut to list(clicked_node=T,leaf=T,nodes=T,ancestors=T,child_path=F)

Value

A D3partitionR object

Set the tooltips parameter

Description

Set the tooltips parameter

Usage

set_tooltip_parameters(D3partitionR_object, visible = T, style = NULL,
  builder = "table")

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

visible

boolean, should the trail be diplayed ? Default: TRUE

style

a valid CSS string to be applied to the tooltip. Default: NULL

builder

Tooltip builder to use for the tooltip. Can either one of the predefined tooltip ('table','basic') or a js expression returning a tooltip.

Value

A D3partitionR object

Enable/disable the trail of steps

Description

Enable/disable the trail of steps

Usage

set_trail(D3partitionR_object, visible = T)

Arguments

D3partitionR_object

The D3partitionR object to which the data should be appended

visible

boolean, should the trail be diplayed ? Default: TRUE

Value

A D3partitionR object

Strip a dataframe containing a step into separate columns

Description

Strip a dataframe containing a step into separate columns

Usage

strip_path(data, path_col = "path", count_col = "count",
  value_cols = NULL, sep = "->")

Arguments

data

A dataframe containing the path.

path_col

Name of the column containing the path. The path should be a string of the format "step 1 -> step 2 -> step 3" .Default: "path"

count_col

Name of the column containing the number of occurences of the path. Default: "count"

value_cols

Names of the other columns to keep. Default: NULL

sep

String used to separate the different steps. Default: "->"

Value

A data.table with the columns specified in count_col, value_cols and one column per step in the path

Build tooltip html function

Description

Build tooltip html function

Usage

tooltip_builder(type)

Arguments

type

a tooltip type: 'basic' (i.e the variable value) or 'table'(i.e. a table with the variables names and value)