Package 'trelliscopejs'

Title:	Create Interactive Trelliscope Displays
Description:	Trelliscope is a scalable, flexible, interactive approach to visualizing data (Hafen, 2013 <doi:10.1109/LDAV.2013.6675164>). This package provides methods that make it easy to create a Trelliscope display specification for TrelliscopeJS. High-level functions are provided for creating displays from within 'tidyverse' or 'ggplot2' workflows. Low-level functions are also provided for creating new interfaces.
Authors:	Ryan Hafen [aut, cre] , Barret Schloerke [aut]
Maintainer:	Ryan Hafen <[email protected]>
License:	BSD_3_clause + file LICENSE
Version:	0.2.10
Built:	2024-10-31 03:05:09 UTC
Source:	https://github.com/hafen/trelliscopejs

Help Index

trelliscopejs
Cast a data frame as a cognostics data frame
Cast Column as a Cognostic
Helper function for creating a cognostic for a link to another display in a filtered state
Href Cognostic
Cogs Wrapper Function
Create a cognostics template that can be edited and used to specify cognostics in a display #' @param x a data frame that will be used as an input for the trelliscope display. If NULL, a blank template will be created.
Facet Trelliscope
Cast a vector of URLs pointing to images as an image panel source
Cast a vector of URLs pointing to local images as an image panel source
Specify a collection of input cognostics to be stored in browser localStorage
Specify a collection of input cognostics to be stored using an API
Specify a radio button input
Specify a text input
Apply a function to each element of a vector and return a vector of cognostics data frames
Apply a function to each element of a vector and return a vector of plots
Map over multiple inputs simultaneously and return a vector of cognostics data frames
Map over multiple inputs simultaneously and return a vector of plots
Specify a markdown description for a display
Labels for ggplot2 "mpg" data
Panels Wrapper Function
Set up all auxiliary files needed for a Trelliscope app
Print facet trelliscope object
Set labels for a data frame
Specify how a display should be sorted
Use fidelius to password protect a trelliscope display
Create a Trelliscope Display
Shiny bindings for Trelliscope
Update Trelliscope app display list file
Construct a list of view items
Construct a list of view items
Write cognostics data for a display in a Trelliscope app
Write Trelliscope app configuration file
Write a "display object" file for a Trelliscope app
Write a plot object as a panel in a Trelliscope display
Write a list of plot objects as panels in a Trelliscope display

trelliscopejs

Description

Create interactive Trelliscope displays

Details

https://hafen.github.io/trelliscopejs/

Examples

help(package = trelliscopejs)
help(package = trelliscopejs)

Cast a data frame as a cognostics data frame

Description

Cast a data frame as a cognostics data frame

Usage

as_cognostics(
  x,
  cond_cols,
  key_col = NULL,
  cog_desc = NULL,
  needs_key = TRUE,
  needs_cond = TRUE,
  group = "common"
)
as_cognostics(
  x,
  cond_cols,
  key_col = NULL,
  cog_desc = NULL,
  needs_key = TRUE,
  needs_cond = TRUE,
  group = "common"
)

Arguments

`x`	a data frame
`cond_cols`	the column name(s) that comprise the conditioning variables
`key_col`	the column name that indicates the panel key
`cog_desc`	an optional named list of descriptions for the cognostics columns
`needs_key`	does the result need to have a "key" column?
`needs_cond`	does the result need to have conditioning variable columns?
`group`	value to be used in the `cog` group

Cast Column as a Cognostic

Description

Cast a column of a cognostics data frame as a cognostic object

Usage

cog(
  val = NULL,
  desc = "",
  group = "common",
  type = NULL,
  default_label = FALSE,
  default_active = TRUE,
  filterable = TRUE,
  sortable = TRUE,
  log = NULL
)
cog(
  val = NULL,
  desc = "",
  group = "common",
  type = NULL,
  default_label = FALSE,
  default_active = TRUE,
  filterable = TRUE,
  sortable = TRUE,
  log = NULL
)

Arguments

`val`	a scalar value (numeric, character, date, etc.)
`desc`	a description for this cognostic value
`group`	optional categorization of the cognostic for organizational purposes in the viewer (currently not implemented in the viewer)
`type`	the desired type of cognostic you would like to compute (see details)
`default_label`	should this cognostic be used as a panel label in the viewer by default?
`default_active`	should this cognostic be active (available for sort / filter / sample) by default?
`filterable`	should this cognostic be filterable? Default is `TRUE`. It can be useful to set this to `FALSE` if the cognostic is categorical with many unique values and is only desired to be used as a panel label.
`sortable`	should this cognostic be sortable?
`log`	when being used in the viewer for visual univariate and bivariate filters, should the log be computed? Useful when the distribution of the cognostic is very long-tailed or has large outliers. Can either be a logical or a positive integer indicating the base.

Details

Different types of cognostics can be specified through the type argument that will affect how the user is able to interact with those cognostics in the viewer. This can usually be ignored because it will be inferred from the implicit data type of val. But there are special types of cognostics, such as geographic coordinates and relations (not implemented) that can be specified as well. Current possibilities for type are "key", "integer", "numeric", "factor", "date", "time", "href".

Value

object of class "cog"

Examples

library(dplyr)
library(tidyr)
library(purrr)
library(ggplot2)
library(plotly)

mpg_cog <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cogs = map_cog(data, ~ tibble(
      mean_city_mpg = cog(mean(.$cty), desc = "Mean city mpg"),
      mean_hwy_mpg = cog(mean(.$hwy), desc = "Mean highway mpg"),
      most_common_drv = cog(tail(names(table(.$drv)), 1), desc = "Most common drive type")
    )),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers") %>%
        layout(
          xaxis = list(range = c(9, 47)),
          yaxis = list(range = c(7, 37)))
    })
  )

trelliscope(mpg_cog, name = "city_vs_highway_mpg", nrow = 1, ncol = 2)
library(dplyr)
library(tidyr)
library(purrr)
library(ggplot2)
library(plotly)

mpg_cog <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cogs = map_cog(data, ~ tibble(
      mean_city_mpg = cog(mean(.$cty), desc = "Mean city mpg"),
      mean_hwy_mpg = cog(mean(.$hwy), desc = "Mean highway mpg"),
      most_common_drv = cog(tail(names(table(.$drv)), 1), desc = "Most common drive type")
    )),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers") %>%
        layout(
          xaxis = list(range = c(9, 47)),
          yaxis = list(range = c(7, 37)))
    })
  )

trelliscope(mpg_cog, name = "city_vs_highway_mpg", nrow = 1, ncol = 2)

Helper function for creating a cognostic for a link to another display in a filtered state

Description

Helper function for creating a cognostic for a link to another display in a filtered state

Usage

cog_disp_filter(
  display,
  var,
  val,
  desc = "link",
  group = "common",
  type = c("href", "href_hash"),
  default_label = FALSE,
  default_active = FALSE,
  filterable = FALSE,
  sortable = FALSE
)
cog_disp_filter(
  display,
  var,
  val,
  desc = "link",
  group = "common",
  type = c("href", "href_hash"),
  default_label = FALSE,
  default_active = FALSE,
  filterable = FALSE,
  sortable = FALSE
)

Arguments

`display`	A string indicating the name of the display to link to.
`var`	A string indicating the variable name to filter on.
`val`	A string indicating the value of the filter.
`desc`	a description for this cognostic value
`group`	optional categorization of the cognostic for organizational purposes in the viewer (currently not implemented in the viewer)
`type`	of either "href" or "href_hash". "href" will open the link in a new page. "href_hash" will update the page's hash and reload the page (useful when changing state inside an iframe)
`default_label`	should this cognostic be used as a panel label in the viewer by default?
`default_active`	should this cognostic be active (available for sort / filter / sample) by default?
`filterable`	should this cognostic be filterable? Default is `TRUE`. It can be useful to set this to `FALSE` if the cognostic is categorical with many unique values and is only desired to be used as a panel label.
`sortable`	should this cognostic be sortable?

Href Cognostic

Description

Create href to be used as cognostics in a trelliscope display

Usage

cog_href(
  x,
  desc = "link",
  group = "common",
  type = c("href", "href_hash"),
  default_label = FALSE,
  default_active = FALSE,
  filterable = FALSE,
  sortable = FALSE,
  log = FALSE
)
cog_href(
  x,
  desc = "link",
  group = "common",
  type = c("href", "href_hash"),
  default_label = FALSE,
  default_active = FALSE,
  filterable = FALSE,
  sortable = FALSE,
  log = FALSE
)

Arguments

`x`	URL to link to
`desc`, `group`, `default_label`, `default_active`, `filterable`, `sortable`, `log`	arguments passed to `cog`
`type`	of either "href" or "href_hash". "href" will open the link in a new page. "href_hash" will update the page's hash and reload the page (useful when changing state inside an iframe)

Examples


library(dplyr)
library(tidyr)
library(plotly)
iris %>%
  nest(data = -Species) %>%
  mutate(
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~Sepal.Length, y = ~Sepal.Width,
        type = "scatter", mode = "markers")
    }),
    wiki_link = cog_href(paste0("https://en.wikipedia.org/wiki/Iris_",
      tolower(Species))[1], default_label = TRUE,
      desc = "link to species on wikipedia")
  ) %>%
  trelliscope(name = "iris_species", ncol = 3)

library(dplyr)
library(tidyr)
library(plotly)
iris %>%
  nest(data = -Species) %>%
  mutate(
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~Sepal.Length, y = ~Sepal.Width,
        type = "scatter", mode = "markers")
    }),
    wiki_link = cog_href(paste0("https://en.wikipedia.org/wiki/Iris_",
      tolower(Species))[1], default_label = TRUE,
      desc = "link to species on wikipedia")
  ) %>%
  trelliscope(name = "iris_species", ncol = 3)

Cogs Wrapper Function

Description

Cogs Wrapper Function

Usage

cogs(.x, .f, ...)
cogs(.x, .f, ...)

Arguments

`.x`	a list or atomic vector (see `map` for details)
`.f`	a function, formula, or atomic vector (see `map` for details)
`...`	additional arguments passed on to .f (see `map` for details)

Details

See map

Examples


library(dplyr)
library(tidyr)
library(plotly)
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    additional_cogs = map_cog(data, function(x) {
      tibble(
        max_city_mpg = cog(max(x$cty), desc = "Max city mpg"),
        min_city_mpg = cog(min(x$cty), desc = "Min city mpg"))
    }),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers")
    })
  ) %>%
  trelliscope(name = "city_vs_highway_mpg", nrow = 1, ncol = 2)

library(dplyr)
library(tidyr)
library(plotly)
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    additional_cogs = map_cog(data, function(x) {
      tibble(
        max_city_mpg = cog(max(x$cty), desc = "Max city mpg"),
        min_city_mpg = cog(min(x$cty), desc = "Min city mpg"))
    }),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers")
    })
  ) %>%
  trelliscope(name = "city_vs_highway_mpg", nrow = 1, ncol = 2)

Create a cognostics template that can be edited and used to specify cognostics in a display #' @param x a data frame that will be used as an input for the trelliscope display. If NULL, a blank template will be created.

Description

Create a cognostics template that can be edited and used to specify cognostics in a display #' @param x a data frame that will be used as an input for the trelliscope display. If NULL, a blank template will be created.

Usage

create_cog_template(x = NULL)
create_cog_template(x = NULL)

Note

The input 'x' can be a starting point and does not need to contain all variables that may be added later. Also note that after you edit the output (for example using the editData package, or writing to a csv and editing in Excel) to reflect how you would like the cognostics to display in the viewer, you can Add this specification to your trelliscope display with [add_cog_template()].

Facet Trelliscope

Description

Facet Trelliscope

Usage

facet_trelliscope(
  facets,
  nrow = 1,
  ncol = 1,
  scales = "same",
  name = NULL,
  group = "common",
  desc = ggplot2::waiver(),
  md_desc = ggplot2::waiver(),
  path = NULL,
  height = 500,
  width = 500,
  inputs = NULL,
  state = NULL,
  views = NULL,
  jsonp = TRUE,
  as_plotly = FALSE,
  plotly_args = NULL,
  plotly_cfg = NULL,
  split_sig = NULL,
  google_analytics_id = NULL,
  self_contained = FALSE,
  thumb = TRUE,
  require_token = FALSE,
  id = NULL,
  order = 1,
  disclaimer = FALSE,
  update_plots = TRUE,
  auto_cog = FALSE,
  split_layout = FALSE,
  data = ggplot2::waiver()
)
facet_trelliscope(
  facets,
  nrow = 1,
  ncol = 1,
  scales = "same",
  name = NULL,
  group = "common",
  desc = ggplot2::waiver(),
  md_desc = ggplot2::waiver(),
  path = NULL,
  height = 500,
  width = 500,
  inputs = NULL,
  state = NULL,
  views = NULL,
  jsonp = TRUE,
  as_plotly = FALSE,
  plotly_args = NULL,
  plotly_cfg = NULL,
  split_sig = NULL,
  google_analytics_id = NULL,
  self_contained = FALSE,
  thumb = TRUE,
  require_token = FALSE,
  id = NULL,
  order = 1,
  disclaimer = FALSE,
  update_plots = TRUE,
  auto_cog = FALSE,
  split_layout = FALSE,
  data = ggplot2::waiver()
)

Arguments

`facets`	formula to facet the panels on. Similar to `ggplot2::facet_wrap`'s `facets`
`nrow`	the number of rows of panels to display by default
`ncol`	the number of columns of panels to display by default
`scales`	should scales be the same (`"same"`, the default), free (`"free"`), or sliced (`"sliced"`). May provide a single string or two strings, one for the X and Y axis respectively.
`name`	name of the display
`group`	group that the display belongs to
`desc`	description of the display
`md_desc`	optional string of markdown that will be shown in the viewer for additional context about the display
`path`	the base directory of the trelliscope application
`height`	height in pixels of each panel
`width`	width in pixels of each panel
`inputs`	optional set of input specifications (using `input_cogs`) to allow user input for each panel
`state`	the initial state the display will open in
`views`	an optional list of pre-specified views of the display (experimental)
`jsonp`	should json for display object be jsonp (TRUE) or json (FALSE)?
`as_plotly`	should the panels be written as plotly objects?
`plotly_args`	optional named list of arguments to send to `ggplotly`
`plotly_cfg`	optional named list of arguments to send to plotly's `config` method
`split_sig`	optional string that specifies the "signature" of the data splitting. If not specified, this is calculated as the md5 hash of the sorted unique facet variables. This is used to identify "related displays" - different displays that are based on the same faceting scheme. This parameter should only be specified manually if a display's faceting is mostly similar to another display's.
`google_analytics_id`	optional string specifying Google Analytics ID
`self_contained`	should the Trelliscope display be a self-contained html document? (see note)
`thumb`	should a thumbnail be created?
`require_token`	require a special token for all displays to be visible (experimental)
`id`	set a hard-coded ID for this app (do not set this if the display will be part of a larger web page)
`order`	an integer indicating the order that the display should appear in if using multiple displays
`disclaimer`	an optional string of html to include as a disclaimer for the set of displays
`auto_cog`	should auto cogs be computed (if possible)?
`split_layout`	boolean that determines if the layout is split into components like a facet_grid vs. individual panels like facet_wrap. Only applies to ggplot2 plot objects.
`data`	data used for faceting. Defaults to the first layer data

Note

Note that self_contained is severely limiting and should only be used in cases where you would either like your display to show up in the RStudio viewer pane, in an interactive R Markdown Notebook, or in a self-contained R Markdown html document.

Examples

## Not run: 
library(ggplot2)

# basically swap out facet_wrap for facet_trelliscope
qplot(cty, hwy, data = mpg) +
  facet_trelliscope(~ class + manufacturer)

# not required, but if you set labels, these will be added as
# descriptions to the cognostics that are automatically computed
mpg <- set_labels(mpg, mpg_labels)

qplot(cty, hwy, data = mpg) +
  theme_bw() +
  facet_trelliscope(~ manufacturer + class, nrow = 2, ncol = 4)

# using plotly
library(plotly)
qplot(cty, hwy, data = mpg) +
  theme_bw() +
  facet_trelliscope(~ manufacturer + class, nrow = 2, ncol = 4, as_plotly = TRUE)

qplot(class, cty, data = mpg, geom = c("boxplot", "jitter"), na.rm = TRUE) +
  facet_trelliscope(~ class, ncol = 7, height = 800, width = 200,
    state = list(sort = list(sort_spec("cty_mean")))) +
  theme_bw()

library(gapminder)
qplot(year, lifeExp, data = gapminder) +
  xlim(1948, 2011) + ylim(10, 95) + theme_bw() +
  facet_trelliscope(~ country + continent, nrow = 2, ncol = 7,
    width = 300, as_plotly = TRUE,
    plotly_cfg = list(displayModeBar = FALSE))

## End(Not run)
## Not run: 
library(ggplot2)

# basically swap out facet_wrap for facet_trelliscope
qplot(cty, hwy, data = mpg) +
  facet_trelliscope(~ class + manufacturer)

# not required, but if you set labels, these will be added as
# descriptions to the cognostics that are automatically computed
mpg <- set_labels(mpg, mpg_labels)

qplot(cty, hwy, data = mpg) +
  theme_bw() +
  facet_trelliscope(~ manufacturer + class, nrow = 2, ncol = 4)

# using plotly
library(plotly)
qplot(cty, hwy, data = mpg) +
  theme_bw() +
  facet_trelliscope(~ manufacturer + class, nrow = 2, ncol = 4, as_plotly = TRUE)

qplot(class, cty, data = mpg, geom = c("boxplot", "jitter"), na.rm = TRUE) +
  facet_trelliscope(~ class, ncol = 7, height = 800, width = 200,
    state = list(sort = list(sort_spec("cty_mean")))) +
  theme_bw()

library(gapminder)
qplot(year, lifeExp, data = gapminder) +
  xlim(1948, 2011) + ylim(10, 95) + theme_bw() +
  facet_trelliscope(~ country + continent, nrow = 2, ncol = 7,
    width = 300, as_plotly = TRUE,
    plotly_cfg = list(displayModeBar = FALSE))

## End(Not run)

Cast a vector of URLs pointing to images as an image panel source

Description

Cast a vector of URLs pointing to images as an image panel source

Usage

img_panel(x)
img_panel(x)

Arguments

`x`	a vector of URLs pointing to images

Cast a vector of URLs pointing to local images as an image panel source

Description

Cast a vector of URLs pointing to local images as an image panel source

Usage

img_panel_local(x)
img_panel_local(x)

Arguments

`x`	a vector of URLs pointing to images

Note

x must be paths relative to the path argument passed to trelliscope.

Examples

## Not run: 
# assuming images are available locally in relative path pokemon_local/images
pokemon$img <- img_panel_local(paste0("images/", basename(pokemon$url_image)))
trelliscope(pokemon, name = "pokemon", path = "pokemon_local")

## End(Not run)
## Not run: 
# assuming images are available locally in relative path pokemon_local/images
pokemon$img <- img_panel_local(paste0("images/", basename(pokemon$url_image)))
trelliscope(pokemon, name = "pokemon", path = "pokemon_local")

## End(Not run)

Specify a collection of input cognostics to be stored in browser localStorage

Description

Specify a collection of input cognostics to be stored in browser localStorage

Usage

input_cogs(..., feedback_email = NULL, extra_cogs = NULL)
input_cogs(..., feedback_email = NULL, extra_cogs = NULL)

Arguments

`feedback_email`	optional feedback email address that input feedback can be sent to
`extra_cogs`	optional vector of names of non-input "regular" cognostics to include in the csv output
`...`	objects created by any of `input_radio`, `input_text`

Specify a collection of input cognostics to be stored using an API

Description

Specify a collection of input cognostics to be stored using an API

Usage

input_cogs_api(
  ...,
  set_url,
  get_url,
  get_request_options = list(mode = "cors", method = "GET", headers =
    list(`Content-Type` = "application/json", Accept = "application/json")),
  set_request_options = list(mode = "cors", method = "POST", headers =
    list(`Content-Type` = "application/json", Accept = "application/json"))
)
input_cogs_api(
  ...,
  set_url,
  get_url,
  get_request_options = list(mode = "cors", method = "GET", headers =
    list(`Content-Type` = "application/json", Accept = "application/json")),
  set_request_options = list(mode = "cors", method = "POST", headers =
    list(`Content-Type` = "application/json", Accept = "application/json"))
)

Arguments

`set_url`	URL of the API endpoint for setting a single input
`get_url`	URL of the API endpoint for getting all inputs for the display
`get_request_options`	request options for the API call to set inputs
`set_request_options`	request options for the API call to get inputs
`...`	objects created by any of `input_radio`, `input_text`

Details

See [here](https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API/Using_Fetch#supplying_request_options for more information about request options.

Specify a radio button input

Description

Specify a radio button input

Usage

input_radio(name, desc = NULL, options, group = NULL, default_label = TRUE)
input_radio(name, desc = NULL, options, group = NULL, default_label = TRUE)

Arguments

`name`	name of the input
`desc`	optional description of the input
`options`	a character vector of options to select between
`group`	optional categorization of the input for organizational purposes in the viewer (currently not implemented in the viewer)
`default_label`	should this input be shown under the panel in the viewer by default?

Specify a text input

Description

Specify a text input

Usage

input_text(
  name,
  desc = NULL,
  width = 80,
  height = 3,
  group = NULL,
  default_label = TRUE
)
input_text(
  name,
  desc = NULL,
  width = 80,
  height = 3,
  group = NULL,
  default_label = TRUE
)

Arguments

`name`	name of the input
`desc`	optional description of the input
`width`	width (in characters) of the text box popout
`height`	height (in lines of text) of the text box popout
`group`	optional categorization of the input for organizational purposes in the viewer (currently not implemented in the viewer)
`default_label`	should this input be shown under the panel in the viewer by default?

Apply a function to each element of a vector and return a vector of cognostics data frames

Description

Apply a function to each element of a vector and return a vector of cognostics data frames

Usage

map_cog(.x, .f, ...)
map_cog(.x, .f, ...)

Arguments

`.x`	a list or atomic vector (see `map` for details)
`.f`	a function, formula, or atomic vector (see `map` for details)
`...`	additional arguments passed on to .f (see `map` for details)

Details

See map

Examples


library(dplyr)
library(tidyr)
library(plotly)
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cog = map_cog(data, function(x) tibble(mean_hwy = mean(x$hwy))),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers")
    })
  ) %>%
  trelliscope(name = "city_vs_highway_mpg")

library(dplyr)
library(tidyr)
library(plotly)
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cog = map_cog(data, function(x) tibble(mean_hwy = mean(x$hwy))),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers")
    })
  ) %>%
  trelliscope(name = "city_vs_highway_mpg")

Apply a function to each element of a vector and return a vector of plots

Description

Apply a function to each element of a vector and return a vector of plots

Usage

map_plot(.x, .f, ...)
map_plot(.x, .f, ...)

Arguments

`.x`	a list or atomic vector (see `map` for details)
`.f`	a function, formula, or atomic vector (see `map` for details)
`...`	additional arguments passed on to .f (see `map` for details)

Details

See map

Examples


library(dplyr)
library(tidyr)
library(purrr)
library(plotly)
library(gapminder)

# nest gapminder data by country
by_country <- gapminder %>%
  nest(data = !one_of(c("country", "continent")))

# add in a plot column with map_plot
by_country <- by_country %>% mutate(
  panel = map_plot(data, function(x) {
    plot_ly(data = x, x = ~year, y = ~lifeExp,
      type = "scatter", mode = "markers") %>%
      layout(
        xaxis = list(range = c(1948, 2011)),
        yaxis = list(range = c(10, 95)))
  }))

# plot it
by_country %>%
  trelliscope("gapminder", nrow = 2, ncol = 7, width = 300)

# example using mpg data
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(panel = map_plot(data, function(x) {
    plot_ly(data = x, x = ~hwy, y = ~cty,
      type = "scatter", mode = "markers")
  })) %>%
  trelliscope(name = "city_vs_highway_mpg")

library(dplyr)
library(tidyr)
library(purrr)
library(plotly)
library(gapminder)

# nest gapminder data by country
by_country <- gapminder %>%
  nest(data = !one_of(c("country", "continent")))

# add in a plot column with map_plot
by_country <- by_country %>% mutate(
  panel = map_plot(data, function(x) {
    plot_ly(data = x, x = ~year, y = ~lifeExp,
      type = "scatter", mode = "markers") %>%
      layout(
        xaxis = list(range = c(1948, 2011)),
        yaxis = list(range = c(10, 95)))
  }))

# plot it
by_country %>%
  trelliscope("gapminder", nrow = 2, ncol = 7, width = 300)

# example using mpg data
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(panel = map_plot(data, function(x) {
    plot_ly(data = x, x = ~hwy, y = ~cty,
      type = "scatter", mode = "markers")
  })) %>%
  trelliscope(name = "city_vs_highway_mpg")

Map over multiple inputs simultaneously and return a vector of cognostics data frames

Description

Map over multiple inputs simultaneously and return a vector of cognostics data frames

Usage

map2_cog(.x, .y, .f, ...)

pmap_cog(.l, .f, ...)
map2_cog(.x, .y, .f, ...)

pmap_cog(.l, .f, ...)

Arguments

`.x`, `.y`	Vectors of the same length. A vector of length 1 will be recycled.
`.f`	A function, formula, or atomic vector (see `map2` for details)
`...`	additional arguments passed on to .f.
`.l`	A list of lists. The length of .l determines the number of arguments that .f will be called with. List names will be used if present.

Details

See map2

Examples


library(tidyr)
library(purrr)
library(plotly)
library(dplyr)

iris %>%
  nest(data = -Species) %>%
  mutate(
    mod = map(data, ~ lm(Sepal.Length ~ Sepal.Width, data = .x)),
    cogs = map2_cog(data, mod, function(data, mod) {
      tibble(max_sl = max(data$Sepal.Length), slope = coef(mod)[2])
    }),
    panel = map2_plot(data, mod, function(data, mod) {
      plot_ly(data = data, x = ~Sepal.Width, y = ~Sepal.Length,
        type = "scatter", mode = "markers", name = "data") %>%
        add_trace(data = data, x = ~Sepal.Width, y = ~predict(mod),
          mode = "lines", name = "lm")
    })) %>%
  trelliscope(name = "iris")

library(tidyr)
library(purrr)
library(plotly)
library(dplyr)

iris %>%
  nest(data = -Species) %>%
  mutate(
    mod = map(data, ~ lm(Sepal.Length ~ Sepal.Width, data = .x)),
    cogs = map2_cog(data, mod, function(data, mod) {
      tibble(max_sl = max(data$Sepal.Length), slope = coef(mod)[2])
    }),
    panel = map2_plot(data, mod, function(data, mod) {
      plot_ly(data = data, x = ~Sepal.Width, y = ~Sepal.Length,
        type = "scatter", mode = "markers", name = "data") %>%
        add_trace(data = data, x = ~Sepal.Width, y = ~predict(mod),
          mode = "lines", name = "lm")
    })) %>%
  trelliscope(name = "iris")

Map over multiple inputs simultaneously and return a vector of plots

Description

Map over multiple inputs simultaneously and return a vector of plots

Usage

map2_plot(.x, .y, .f, ...)

pmap_plot(.l, .f, ...)
map2_plot(.x, .y, .f, ...)

pmap_plot(.l, .f, ...)

Arguments

`.x`, `.y`	Vectors of the same length. A vector of length 1 will be recycled.
`.f`	A function, formula, or atomic vector (see `map2` for details)
`...`	additional arguments passed on to .f.
`.l`	A list of lists. The length of .l determines the number of arguments that .f will be called with. List names will be used if present.

Details

See map2

Examples


library(tidyr)
library(purrr)
library(plotly)
library(dplyr)

iris %>%
  nest(data = -Species) %>%
  mutate(
    mod = map(data, ~ lm(Sepal.Length ~ Sepal.Width, data = .x)),
    panel = map2_plot(data, mod, function(data, mod) {
      plot_ly(data = data, x = ~Sepal.Width, y = ~Sepal.Length,
        type = "scatter", mode = "markers", name = "data") %>%
        add_trace(data = data, x = ~Sepal.Width, y = ~predict(mod),
          mode = "lines", name = "lm")
    })) %>%
  trelliscope(name = "iris")

library(tidyr)
library(purrr)
library(plotly)
library(dplyr)

iris %>%
  nest(data = -Species) %>%
  mutate(
    mod = map(data, ~ lm(Sepal.Length ~ Sepal.Width, data = .x)),
    panel = map2_plot(data, mod, function(data, mod) {
      plot_ly(data = data, x = ~Sepal.Width, y = ~Sepal.Length,
        type = "scatter", mode = "markers", name = "data") %>%
        add_trace(data = data, x = ~Sepal.Width, y = ~predict(mod),
          mode = "lines", name = "lm")
    })) %>%
  trelliscope(name = "iris")

Specify a markdown description for a display

Description

Specify a markdown description for a display

Usage

md_description(
  content = "",
  title = "Information About This Display",
  show = FALSE
)
md_description(
  content = "",
  title = "Information About This Display",
  show = FALSE
)

Arguments

`content`	Markdown content
`title`	Title of the dialog box that displays this content
`show`	should the markdown description be shown by default when the display is loaded?

Labels for ggplot2 "mpg" data

Description

Labels for ggplot2 "mpg" data

Usage

mpg_labels
mpg_labels

Format

An object of class list of length 10.

Panels Wrapper Function

Description

Panels Wrapper Function

Usage

panels(.x, .f, ...)
panels(.x, .f, ...)

Arguments

`.x`	a list or atomic vector (see `map` for details)
`.f`	a function, formula, or atomic vector (see `map` for details)
`...`	additional arguments passed on to .f (see `map` for details)

Details

See map

Examples


library(dplyr)
library(tidyr)
library(plotly)
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(panel = map_plot(data, function(x) {
    plot_ly(data = x, x = ~hwy, y = ~cty,
      type = "scatter", mode = "markers")
  })) %>%
  trelliscope(name = "city_vs_highway_mpg")

library(dplyr)
library(tidyr)
library(plotly)
ggplot2::mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(panel = map_plot(data, function(x) {
    plot_ly(data = x, x = ~hwy, y = ~cty,
      type = "scatter", mode = "markers")
  })) %>%
  trelliscope(name = "city_vs_highway_mpg")

Set up all auxiliary files needed for a Trelliscope app

Description

Set up all auxiliary files needed for a Trelliscope app

Usage

prepare_display(
  base_path,
  id,
  self_contained = FALSE,
  jsonp = TRUE,
  require_token = FALSE,
  disclaimer = FALSE,
  pb = NULL
)
prepare_display(
  base_path,
  id,
  self_contained = FALSE,
  jsonp = TRUE,
  require_token = FALSE,
  disclaimer = FALSE,
  pb = NULL
)

Arguments

`base_path`	the base directory of the trelliscope application
`id`	a unique id for the application
`self_contained`	should the Trelliscope display be a self-contained html document?
`jsonp`	should json for display list and app config be jsonp (TRUE) or json (FALSE)?
`require_token`	require a special token for all displays to be visible (experimental)
`disclaimer`	an optional string of html to include as a disclaimer for the set of displays
`pb`	optional progress bar object to pass in and use to report progress

Print facet trelliscope object

Description

Print facet trelliscope object

Usage

## S3 method for class 'facet_trelliscope'
print(x, ...)
## S3 method for class 'facet_trelliscope'
print(x, ...)

Arguments

`x`	plot object
`...`	ignored

Set labels for a data frame

Description

Set labels for a data frame

Usage

set_labels(dat, label_list)
set_labels(dat, label_list)

Arguments

`dat`	a data frame to apply labels to
`label_list`	a named list with names matching those of `dat` and values being labels

Value

data frame with labels attached as attributes (attached to each column and named "label")

Specify how a display should be sorted

Description

Specify how a display should be sorted

Usage

sort_spec(name, dir = "asc")
sort_spec(name, dir = "asc")

Arguments

`name`	variable name to sort on
`dir`	direction to sort ('asc' or 'desc')

Use fidelius to password protect a trelliscope display

Description

Use fidelius to password protect a trelliscope display

Usage

tr_charm(x, ...)
tr_charm(x, ...)

Arguments

`x`	an object of class "facet_trelliscope" or "trelliscopejs_widget"
`...`	arguments passed to [fidelius::charm()]

Create a Trelliscope Display

Description

Create a Trelliscope Display

Usage

trelliscope(
  x,
  name,
  group = "common",
  panel_col = NULL,
  cond_cols = NULL,
  desc = "",
  md_desc = "",
  path,
  height = 500,
  width = 500,
  inputs = NULL,
  google_analytics_id = NULL,
  auto_cog = FALSE,
  state = NULL,
  views = NULL,
  nrow = 1,
  ncol = 1,
  jsonp = TRUE,
  split_sig = NULL,
  self_contained = FALSE,
  thumb = FALSE,
  require_token = FALSE,
  id = NULL,
  order = 1,
  disclaimer = FALSE,
  update_plots = TRUE
)
trelliscope(
  x,
  name,
  group = "common",
  panel_col = NULL,
  cond_cols = NULL,
  desc = "",
  md_desc = "",
  path,
  height = 500,
  width = 500,
  inputs = NULL,
  google_analytics_id = NULL,
  auto_cog = FALSE,
  state = NULL,
  views = NULL,
  nrow = 1,
  ncol = 1,
  jsonp = TRUE,
  split_sig = NULL,
  self_contained = FALSE,
  thumb = FALSE,
  require_token = FALSE,
  id = NULL,
  order = 1,
  disclaimer = FALSE,
  update_plots = TRUE
)

Arguments

`x`	an object to create at trelliscope display for
`name`	name of the display
`group`	group that the display belongs to
`panel_col`	optional string specifying the column to use for panels (if there are multiple plot columns in `x`)
`cond_cols`	optionsl vector of columns to specify as "conditioning" columns - combined they must be unique and not have any missing values
`desc`	optional text description of the display
`md_desc`	optional string of markdown that will be shown in the viewer for additional context about the display
`path`	the base directory of the trelliscope application
`height`	height in pixels of each panel
`width`	width in pixels of each panel
`inputs`	optional set of input specifications (using `input_cogs`) to allow user input for each panel
`google_analytics_id`	optional string specifying Google Analytics ID
`auto_cog`	should auto cogs be computed (if possible)?
`state`	the initial state the display will open in
`views`	an optional list of pre-specified views of the display (experimental)
`nrow`	the number of rows of panels to display by default
`ncol`	the number of columns of panels to display by default
`jsonp`	should json for display object be jsonp (TRUE) or json (FALSE)?
`split_sig`	optional string that specifies the "signature" of the data splitting. If not specified, this is calculated as the md5 hash of the sorted unique facet variables. This is used to identify "related displays" - different displays that are based on the same faceting scheme. This parameter should only be specified manually if a display's faceting is mostly similar to another display's.
`self_contained`	should the Trelliscope display be a self-contained html document? (see note)
`thumb`	should a thumbnail be created?
`require_token`	require a special token for all displays to be visible (experimental)
`id`	set a hard-coded ID for this app (do not set this if the display will be part of a larger web page)
`order`	an integer indicating the order that the display should appear in if using multiple displays
`disclaimer`	an optional string of html to include as a disclaimer for the set of displays
`update_plots`	should the plots be updated? This is to allow slight updates to the underlying display data without the need to re-render all of the plots. Use it carefully.

Note

Examples

## Not run: 
library(dplyr)
library(tidyr)
library(purrr)
library(plotly)
library(ggplot2)

# tidyverse + plotly
d <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    mean_city_mpg = map_dbl(data, ~ mean(.$cty)),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers")
    })
  )

d %>% trelliscope(name = "city_vs_highway_mpg")

# set default layout
d %>% trelliscope(name = "city_vs_highway_mpg", nrow = 2, ncol = 3)

# set the output path for where files will be stored
my_displays <- tempfile()
d %>% trelliscope(name = "city_vs_highway_mpg", path = my_displays)

# multiple displays can be added to the same path and all will be available in the viewer
d %>% trelliscope(name = "city_vs_highway_mpg2", path = my_displays)

# ordering the data frame will set default sort order of the display
d %>%
  arrange(-mean_city_mpg) %>%
  trelliscope(name = "city_vs_highway_mpg")

# tidyverse + ggplot2
mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    panel = map_plot(data, ~
      qplot(cty, hwy, data = .) + xlab("cty") + ylab("hwy") +
        xlim(7, 37) + ylim(9, 47) + theme_bw())) %>%
  trelliscope(name = "tidy_gg")

# computing additional cognostics
mpg_cog <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cogs = map_cog(data, ~ tibble(
      mean_city_mpg = mean(.$cty),
      mean_hwy_mpg = mean(.$hwy),
      most_common_drv = tail(names(table(.$drv)), 1)
    ))
  )

# computing additional cognostics explicitly using cog()
# so we can specify descriptions, etc.
mpg_cog2 <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cogs = map_cog(data, ~ tibble(
      mean_city_mpg = cog(mean(.$cty), desc = "Mean city mpg"),
      mean_hwy_mpg = cog(mean(.$hwy), desc = "Mean highway mpg"),
      most_common_drv = cog(tail(names(table(.$drv)), 1), desc = "Most common drive type")
    )),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers") %>%
        layout(
          xaxis = list(range = c(9, 47)),
          yaxis = list(range = c(7, 37)))
    })
  )

mpg_cog2 %>%
  trelliscope(name = "city_vs_highway_mpg", nrow = 1, ncol = 2)

## End(Not run)
## Not run: 
library(dplyr)
library(tidyr)
library(purrr)
library(plotly)
library(ggplot2)

# tidyverse + plotly
d <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    mean_city_mpg = map_dbl(data, ~ mean(.$cty)),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers")
    })
  )

d %>% trelliscope(name = "city_vs_highway_mpg")

# set default layout
d %>% trelliscope(name = "city_vs_highway_mpg", nrow = 2, ncol = 3)

# set the output path for where files will be stored
my_displays <- tempfile()
d %>% trelliscope(name = "city_vs_highway_mpg", path = my_displays)

# multiple displays can be added to the same path and all will be available in the viewer
d %>% trelliscope(name = "city_vs_highway_mpg2", path = my_displays)

# ordering the data frame will set default sort order of the display
d %>%
  arrange(-mean_city_mpg) %>%
  trelliscope(name = "city_vs_highway_mpg")

# tidyverse + ggplot2
mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    panel = map_plot(data, ~
      qplot(cty, hwy, data = .) + xlab("cty") + ylab("hwy") +
        xlim(7, 37) + ylim(9, 47) + theme_bw())) %>%
  trelliscope(name = "tidy_gg")

# computing additional cognostics
mpg_cog <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cogs = map_cog(data, ~ tibble(
      mean_city_mpg = mean(.$cty),
      mean_hwy_mpg = mean(.$hwy),
      most_common_drv = tail(names(table(.$drv)), 1)
    ))
  )

# computing additional cognostics explicitly using cog()
# so we can specify descriptions, etc.
mpg_cog2 <- mpg %>%
  nest(data = !one_of(c("manufacturer", "class"))) %>%
  mutate(
    cogs = map_cog(data, ~ tibble(
      mean_city_mpg = cog(mean(.$cty), desc = "Mean city mpg"),
      mean_hwy_mpg = cog(mean(.$hwy), desc = "Mean highway mpg"),
      most_common_drv = cog(tail(names(table(.$drv)), 1), desc = "Most common drive type")
    )),
    panel = map_plot(data, function(x) {
      plot_ly(data = x, x = ~cty, y = ~hwy,
        type = "scatter", mode = "markers") %>%
        layout(
          xaxis = list(range = c(9, 47)),
          yaxis = list(range = c(7, 37)))
    })
  )

mpg_cog2 %>%
  trelliscope(name = "city_vs_highway_mpg", nrow = 1, ncol = 2)

## End(Not run)

Shiny bindings for Trelliscope

Description

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

Usage

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

renderTrelliscope(expr, env = parent.frame(), quoted = FALSE)
trelliscopeOutput(outputId, width = "100%", height = "400px")

renderTrelliscope(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 trelliscopejs_widget
`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.

Update Trelliscope app display list file

Description

Update Trelliscope app display list file

Usage

update_display_list(base_path, jsonp = TRUE)
update_display_list(base_path, jsonp = TRUE)

Arguments

`base_path`	the base directory of the trelliscope application
`jsonp`	should json for display list be jsonp (TRUE) or json (FALSE)?

Construct a list of view items

Description

Construct a list of view items

Usage

view_item(name, hash)
view_item(name, hash)

Arguments

`name`	A string indicating the name of the view (will be displayed in the "Views" sidebar)
`hash`	A URL hash that sends the user to this view (typically the URL starting with &nrow=...)

Construct a list of view items

Description

Construct a list of view items

Usage

view_list(...)
view_list(...)

Arguments

...

Objects created using view_item

Write cognostics data for a display in a Trelliscope app

Description

Write cognostics data for a display in a Trelliscope app

Usage

write_cognostics(cogdf, base_path, id, name, group = "common", jsonp = TRUE)
write_cognostics(cogdf, base_path, id, name, group = "common", jsonp = TRUE)

Arguments

`cogdf`	a data frame of cognostics, prepared with `as_cognostics`
`base_path`	the base directory of the trelliscope application
`id`	a unique id for the application
`name`	name of the display
`group`	group that the display belongs to
`jsonp`	should json for cognostics be jsonp (TRUE) or json (FALSE)?

Write Trelliscope app configuration file

Description

Write Trelliscope app configuration file

Usage

write_config(
  base_path,
  id,
  self_contained = FALSE,
  jsonp = TRUE,
  require_token = FALSE,
  disclaimer = FALSE,
  split_layout = FALSE,
  has_legend = FALSE
)
write_config(
  base_path,
  id,
  self_contained = FALSE,
  jsonp = TRUE,
  require_token = FALSE,
  disclaimer = FALSE,
  split_layout = FALSE,
  has_legend = FALSE
)

Arguments

`base_path`	the base directory of the trelliscope application
`id`	a unique id for the application
`self_contained`	should the Trelliscope display be a self-contained html document?
`jsonp`	should json for app config be jsonp (TRUE) or json (FALSE)?
`require_token`	require a special token for all displays to be visible (experimental)
`disclaimer`	an optional string of html to include as a disclaimer for the set of displays
`split_layout`	boolean that determines if the layout is split into components like a facet_grid vs. individual panels like facet_wrap. Only applies to ggplot2 plot objects.
`has_legend`	should a legend be reported for split_layout

Write a "display object" file for a Trelliscope app

Description

Write a "display object" file for a Trelliscope app

Usage

write_display_obj(
  cogdf,
  panel_example,
  base_path,
  id,
  name,
  group = "common",
  desc = "",
  height = 500,
  width = 500,
  inputs = NULL,
  md_desc = "",
  state = NULL,
  google_analytics_id = NULL,
  views = NULL,
  jsonp = TRUE,
  split_sig = NULL,
  panel_img_col = NULL,
  self_contained = FALSE,
  thumb = TRUE,
  split_layout = FALSE,
  split_aspect = NULL,
  has_legend = FALSE,
  order = 1,
  pb = NULL
)
write_display_obj(
  cogdf,
  panel_example,
  base_path,
  id,
  name,
  group = "common",
  desc = "",
  height = 500,
  width = 500,
  inputs = NULL,
  md_desc = "",
  state = NULL,
  google_analytics_id = NULL,
  views = NULL,
  jsonp = TRUE,
  split_sig = NULL,
  panel_img_col = NULL,
  self_contained = FALSE,
  thumb = TRUE,
  split_layout = FALSE,
  split_aspect = NULL,
  has_legend = FALSE,
  order = 1,
  pb = NULL
)

Arguments

`cogdf`	a data frame of cognostics, prepared with `as_cognostics`
`panel_example`	an example object of one panel of a display (can be trellis, ggplot2, or htmlwidget object)
`base_path`	the base directory of the trelliscope application
`id`	a unique id for the application
`name`	name of the display
`group`	group that the display belongs to
`desc`	description of the display
`height`	height in pixels of each panel
`width`	width in pixels of each panel
`inputs`	optional set of input specifications (using `input_cogs`) to allow user input for each panel
`md_desc`	optional string of markdown that will be shown in the viewer for additional context about the display
`state`	the initial state the display will open in
`google_analytics_id`	optional string specifying Google Analytics ID
`views`	an optional list of pre-specified views of the display (experimental)
`jsonp`	should json for display object be jsonp (TRUE) or json (FALSE)?
`split_sig`	optional string "signature" specifying the data splitting
`panel_img_col`	which column (if any) is a panel image column?
`self_contained`	should the Trelliscope display be a self-contained html document?
`thumb`	should a thumbnail be created?
`split_layout`	boolean that determines if the layout is split into components like a facet_grid vs. individual panels like facet_wrap. Only applies to ggplot2 plot objects.
`split_aspect`	list indicating aspect ratios of axes for a split layout. Only applies to ggplot2 plot objects.
`has_legend`	should a legend be reported for split_layout
`order`	an integer indicating the order that the display should appear in if using multiple displays
`pb`	optional progress bar object to pass in and use to report progress

Write a plot object as a panel in a Trelliscope display

Description

Write a plot object as a panel in a Trelliscope display

Usage

write_panel(
  plot_object,
  key,
  base_path,
  name,
  group = "common",
  width,
  height,
  jsonp = TRUE,
  split_layout = FALSE
)
write_panel(
  plot_object,
  key,
  base_path,
  name,
  group = "common",
  width,
  height,
  jsonp = TRUE,
  split_layout = FALSE
)

Arguments

`plot_object`	a plot object to be written (can be trellis, ggplot2, or htmlwidget)
`key`	a string identifying the panel key, which will be used as the panel file name and which the `panelKey` column of the cognostics data frame should point to
`base_path`	the base directory of the trelliscope application
`name`	name of the display that the panel belongs to
`group`	group name of the display that the panel belongs to
`width`	width in pixels of each panel
`height`	height in pixels of each panel
`jsonp`	should json for panel be jsonp (TRUE) or json (FALSE)?
`split_layout`	boolean that determines if the layout is split into components like a facet_grid vs. individual panels like facet_wrap. Only applies to ggplot2 plot objects.

Write a list of plot objects as panels in a Trelliscope display

Description

Write a list of plot objects as panels in a Trelliscope display

Usage

write_panels(plot_list, ..., pb = NULL)
write_panels(plot_list, ..., pb = NULL)

Arguments

`plot_list`	a named list of plot objects to be written as panels (objects can be trellis, ggplot2, or htmlwidget) with the list names being the keys for the panels
`...`	params passed directly to `write_panel`
`pb`	optional progress bar object to pass in and use to report progress

Package 'trelliscopejs'

Help Index

trelliscopejs

Description

Details

Examples

Cast a data frame as a cognostics data frame

Description

Usage

Arguments

Cast Column as a Cognostic

Description

Usage

Arguments

Details

Value

Examples

Helper function for creating a cognostic for a link to another display in a filtered state

Description

Usage

Arguments

Href Cognostic

Description

Usage

Arguments

See Also

Examples

Cogs Wrapper Function

Description

Usage

Arguments

Details

Examples

Create a cognostics template that can be edited and used to specify cognostics in a display #' @param x a data frame that will be used as an input for the trelliscope display. If NULL, a blank template will be created.

Description

Usage

Note

Facet Trelliscope

Description

Usage

Arguments

Note

Examples

Cast a vector of URLs pointing to images as an image panel source

Description

Usage

Arguments

Cast a vector of URLs pointing to local images as an image panel source

Description

Usage

Arguments

Note

Examples

Specify a collection of input cognostics to be stored in browser localStorage

Description

Usage

Arguments

Specify a collection of input cognostics to be stored using an API

Description

Usage

Arguments

Details

Specify a radio button input

Description

Usage

Arguments

Specify a text input

Description

Usage

Arguments

Apply a function to each element of a vector and return a vector of cognostics data frames

Description

Usage

Arguments

Details

Examples

Apply a function to each element of a vector and return a vector of plots

Description

Usage

Arguments