Package 'esquisse'

Bootstrap Theme for Esquisse

Description

Bootstrap Theme for Esquisse

Usage

bs_theme_esquisse()

Value

A bslib::bs_theme().

---

Build aesthetics to use in a plot

Description

Build aesthetics to use in a plot

Usage

build_aes(data, ..., .list = NULL, geom = NULL)

Arguments

data	Data to use in the plot.
...	Named list of aesthetics.
.list	Alternative to ... to use a preexisting named list.
geom	Geom to use, according to the geom aesthetics may vary.

Value

An expression

Examples

# Classic
build_aes(iris, x = "Sepal.Width")
build_aes(iris, x = "Sepal.Width", y = "Sepal.Width")

# Explicit geom : no change
build_aes(iris, x = "Species", geom = "bar")

# Little trick if data is count data
df <- data.frame(
  LET = c("A", "B"),
  VAL = c(4, 7)
)
build_aes(df, x = "LET", y = "VAL", geom = "bar")

# e.g. :
library(ggplot2)
ggplot(df) +
  build_aes(df, x = "LET", y = "VAL", geom = "bar") +
  geom_bar(stat = "summary", fun = "mean")

---

Drag And Drop Input Widget

Description

Drag And Drop Input Widget

Usage

dragulaInput(
  inputId,
  label = NULL,
  sourceLabel,
  targetsLabels,
  targetsIds = NULL,
  choices = NULL,
  choiceNames = NULL,
  choiceValues = NULL,
  selected = NULL,
  status = "primary",
  replace = FALSE,
  copySource = TRUE,
  badge = TRUE,
  ncolSource = "auto",
  ncolGrid = NULL,
  nrowGrid = NULL,
  dragulaOpts = list(),
  boxStyle = NULL,
  targetsHeight = NULL,
  width = NULL,
  height = "100px"
)

Arguments

inputId	The input slot that will be used to access the value.
label	Display label for the control, or NULL for no label.
sourceLabel	Label display in the source box
targetsLabels	Labels for each target element.
targetsIds	Ids for retrieving values server-side, if NULL, the default, targetsLabels are used after removing all not-alphanumeric characters.
choices	List of values to select from (if elements of the list are named then that name rather than the value is displayed to the user). If this argument is provided, then choiceNames and choiceValues must not be provided, and vice-versa. The values should be strings; other types (such as logicals and numbers) will be coerced to strings.
choiceNames, choiceValues	List of names and values, respectively, that are displayed to the user in the app and correspond to the each choice (for this reason, choiceNames and choiceValues must have the same length). If either of these arguments is provided, then the other must be provided and choices must not be provided. The advantage of using both of these over a named list for choices is that choiceNames allows any type of UI object to be passed through (tag objects, icons, HTML code, ...), instead of just simple text.
selected	Default selected values. Must be a list with targetsIds as names.
status	If choices are displayed into a Bootstrap label, you can use Bootstrap status to color them, or NULL.
replace	When a choice is dragged in a target container already containing a choice, does the later be replaced by the new one ?
copySource	When replace = TRUE, does elements in source must be copied or moved ?
badge	Displays choices inside a Bootstrap badge. Use FALSE if you want to pass custom appearance with choiceNames.
ncolSource	Number of columns occupied by the source, default is "auto", meaning full row.
ncolGrid, nrowGrid	Number of columns / rows used to place source and targets boxes, see examples.
dragulaOpts	Options passed to dragula JavaScript library (see online documentation on GitHub). Note that options moves, accepts and invalid must be valid JavaScript code as they are evaluated on the client.
boxStyle	CSS style string to customize source and target container.
targetsHeight	Height for the target boxes.
width	Width of the input.
height	Height of each boxes, the total input height is this parameter X 2 (unless if targetsHeight is set).

Value

a UI definition

Note

The output server-side is a list with two slots: source and targets.

See Also

updateDragulaInput() to update choices server-side.

Examples

library(shiny)
library(esquisse)

ui <- fluidPage(
  tags$h2("Demo dragulaInput"),
  tags$br(),
  fluidRow(
    column(
      width = 6,
      
      dragulaInput(
        inputId = "dad1",
        label = "Default:",
        sourceLabel = "Source",
        targetsLabels = c("Target 1", "Target 2"),
        choices = month.abb,
        width = "100%"
      ),
      verbatimTextOutput(outputId = "result1"),
      
      tags$br(),
      
      dragulaInput(
        inputId = "dad3",
        label = "On same row:",
        sourceLabel = "Source",
        targetsLabels = c("Target 1", "Target 2"),
        choices = month.abb,
        width = "100%",
        ncolSource = 1,
        ncolGrid = 3
      ),
      verbatimTextOutput(outputId = "result3")
    ),
    
    column(
      width = 6,
      dragulaInput(
        inputId = "dad2",
        label = "Two rows:",
        sourceLabel = "Source",
        targetsLabels = c("x", "y", "color", "fill", "size", "facet"),
        choices = names(mtcars),
        width = "100%",
        ncolGrid = 3
      ),
      verbatimTextOutput(outputId = "result2"),
      
      tags$br(),
      
      dragulaInput(
        inputId = "dad4",
        label = "Two rows not filled:",
        sourceLabel = "Source",
        targetsLabels = c("x", "y", "color", "fill", "size"),
        choices = names(mtcars),
        width = "100%",
        ncolGrid = 3
      ),
      verbatimTextOutput(outputId = "result4")
    )
  )
)


server <- function(input, output, session) {
  
  output$result1 <- renderPrint(str(input$dad1))
  
  output$result2 <- renderPrint(str(input$dad2))
  
  output$result3 <- renderPrint(str(input$dad3))
  
  output$result4 <- renderPrint(str(input$dad4))
  
}

if (interactive())
  shinyApp(ui = ui, server = server)

---

Dropdown Input

Description

A dropdown menu for selecting a value.

Usage

dropInput(
  inputId,
  choicesNames,
  choicesValues,
  selected = NULL,
  dropUp = FALSE,
  dropWidth = NULL,
  dropMaxHeight = NULL,
  dropPreScrollable = FALSE,
  btnClass = "btn-link",
  width = NULL
)

Arguments

inputId	The input slot that will be used to access the value.
choicesNames	A tagList of HTML tags to show in the dropdown menu.
choicesValues	Vector corresponding to choicesNames for retrieving values server-side.
selected	The initial selected value, must be an element of choicesValues, default to the first item of choicesValues.
dropUp	Open the menu above the button rather than below.
dropWidth	Width of the dropdown menu.
dropMaxHeight	Maximal height for the menu.
dropPreScrollable	Force scroll bar to appear in the menu.
btnClass	Class for buttons in dropdown menu, default is "btn-link", you can use for example "btn-default" to display regular buttons.
width	The width of the input.

See Also

updateDropInput

Examples

if (interactive()) {

  library(shiny)
  library(esquisse)

  ui <- fluidPage(
    tags$h2("Drop Input"),
    dropInput(
      inputId = "mydrop",
      choicesNames = tagList(
        list(icon("home"), style = "width: 100px;"),
        list(icon("flash"), style = "width: 100px;"),
        list(icon("cogs"), style = "width: 100px;"),
        list(icon("fire"), style = "width: 100px;"),
        list(icon("users"), style = "width: 100px;"),
        list(icon("info"), style = "width: 100px;")
      ),
      choicesValues = c("home", "flash", "cogs",
                        "fire", "users", "info"),
      dropWidth = "220px"
    ),
    verbatimTextOutput(outputId = "res")
  )

  server <- function(input, output, session) {
    output$res <- renderPrint({
      input$mydrop
    })
  }

  shinyApp(ui, server)

}

---

Explore and Visualize Your Data Interactively

Description

A 'shiny' gadget to create 'ggplot2' figures interactively with drag-and-drop to map your variables to different aesthetics. You can quickly visualize your data accordingly to their type, export in various formats, and retrieve the code to reproduce the plot.

Author(s)

Fanny Meyer & Victor Perrier (@dreamRs_fr)

See Also

Useful links:

• https://dreamrs.github.io/esquisse/

• https://github.com/dreamRs/esquisse

• Report bugs at https://github.com/dreamRs/esquisse/issues

Examples

## Not run: 

esquisser()

# launch esquisse with specific data:
esquisser(mtcars)


## End(Not run)

---

Deprecated functions

Description

Deprecated functions

Usage

esquisseContainer(...)

Arguments

...	See esquisse_container()

Note

The following functions are deprecated and will be removed in next release:

• esquisseContainer : replaced by esquisse_container

---

esquisse exported operators and S3 methods

Description

esquisse exported operators and S3 methods

---

Esquisse module

Description

Use esquisse as a module in a Shiny application.

Usage

esquisse_ui(
  id,
  header = esquisse_header(),
  container = esquisse_container(),
  controls = c("options", "labs", "axes", "geoms", "theme", "filters", "code"),
  insert_code = FALSE,
  play_pause = TRUE,
  layout_sidebar = FALSE,
  downloads = downloads_labels(),
  n_geoms = 8
)

esquisse_server(
  id,
  data_rv = NULL,
  name = "data",
  default_aes = c("fill", "color", "size", "group", "facet"),
  import_from = c("env", "file", "copypaste", "googlesheets", "url"),
  n_geoms = 8,
  drop_ids = TRUE,
  notify_warnings = NULL
)

esquisse_container(width = "100%", height = "700px", fixed = FALSE)

esquisse_header(
  import_data = TRUE,
  show_data = TRUE,
  update_variable = TRUE,
  create_column = TRUE,
  cut_variable = TRUE,
  update_factor = TRUE,
  settings = TRUE,
  close = TRUE,
  .before = NULL,
  .after = NULL
)

Arguments

id	Module ID.
header	Either TRUE or FALSE to display or not esquisse header, or a named list where names are : settings, close, import and show_data and values are TRUE or FALSE to display or not the corresponding button.
container	Container in which display the addin, default is to use esquisse_container(), see examples. Use NULL for no container (behavior in versions <= 0.2.1). Must be a function.
controls	Controls menu to be displayed. Use NULL to hide all menus.
insert_code	Logical, Display or not a button to insert the ggplot code in the current user script (work only in RStudio).
play_pause	Display or not the play / pause button.
layout_sidebar	Put controls in a sidebar on the left rather than below the chart in dropdowns.
downloads	Export options available or NULL for no export. See downloads_labels().
n_geoms	Number of geoms the user can use.
data_rv	Either: A shiny::reactiveValues() with a slot data containing a data.frame to use in the module and a slot name corresponding to the name of the data.frame used for the generated code. A shiny::reactive() function returning a data.frame. See argument name for the name used in generated code. A data.frame object.
name	The default name to use in generated code. Can be a reactive function return a single character.
default_aes	Default aesthetics to be used, can be a character vector or reactive function returning one.
import_from	From where to import data, argument passed to datamods::import_server(), use NULL to prevent the modal to appear.
drop_ids	Argument passed to datamods::filter_data_server. Drop columns containing more than 90% of unique values, or than 50 distinct values.
notify_warnings	See safe_ggplot(). If NULL, the user can make his or her own choice via the settings menu, default is to show warnings once.
width, height	The width and height of the container, e.g. "400px", or "100%"; see htmltools::validateCssUnit().
fixed	Use a fixed container, e.g. to use use esquisse full page. If TRUE, width and height are ignored. Default to FALSE. It's possible to use a vector of CSS unit of length 4 to specify the margins (top, right, bottom, left).
import_data	Show button to import data.
show_data	Show button to display data.
update_variable	Show button to update selected variables and convert them.
create_column	Show button to create a new column based on an expression.
cut_variable	Show button to allow to convert a numeric variable into factor.
update_factor	Show button to open window to reorder factor levels and update them.
settings	Show button to open settings modal (to select aesthetics to use).
close	Show button to stop the app and close addin.
.before, .after	Custom content to put in the header, typically buttons.

Value

A reactiveValues with 3 slots :

• code_plot : code to generate plot.

• code_filters : a list of length two with code to reproduce filters.

• data : data.frame used in plot (with filters applied).

Examples

### Part of a Shiny app ###

library(shiny)
library(esquisse)

ui <- fluidPage(

  theme = bs_theme_esquisse(),

  tags$h1("Use esquisse as a Shiny module"),

  radioButtons(
    inputId = "data",
    label = "Data to use:",
    choices = c("iris", "mtcars"),
    inline = TRUE
  ),
  checkboxGroupInput(
    inputId = "aes",
    label = "Aesthetics to use:",
    choices = c(
      "fill", "color", "size", "shape",
      "weight", "group", "facet", "facet_row", "facet_col"
    ),
    selected = c("fill", "color", "size", "facet"),
    inline = TRUE
  ),
  esquisse_ui(
    id = "esquisse",
    header = FALSE, # dont display gadget title
    container = esquisse_container(height = "700px")
  )
)

server <- function(input, output, session) {

  data_rv <- reactiveValues(data = iris, name = "iris")

  observeEvent(input$data, {
    if (input$data == "iris") {
      data_rv$data <- iris
      data_rv$name <- "iris"
    } else {
      data_rv$data <- mtcars
      data_rv$name <- "mtcars"
    }
  })

  esquisse_server(
    id = "esquisse",
    data_rv = data_rv,
    default_aes = reactive(input$aes)
  )

}

if (interactive())
  shinyApp(ui, server)


### Whole Shiny app ###

library(shiny)
library(esquisse)


# Load some datasets in app environment
my_data <- data.frame(
  var1 = rnorm(100),
  var2 = sample(letters[1:5], 100, TRUE)
)


ui <- fluidPage(
  theme = bs_theme_esquisse(),
  esquisse_ui(
    id = "esquisse",
    header = esquisse_header(
      close = FALSE, # hide the close button
      .after = actionButton( # custom button
        inputId = "open_modal",
        label = NULL,
        icon = icon("plus")
      )
    ),
    container = esquisse_container(fixed = TRUE),
    play_pause = FALSE,
    controls = c("settings", "labs", "axes", "geoms", "theme", "filters", "code", "export"),
    layout_sidebar = TRUE
  )
)

server <- function(input, output, session) {

  esquisse_server(id = "esquisse")


  observeEvent(input$open_modal, {
    showModal(modalDialog("Some content"))
  })
}

if (interactive())
  shinyApp(ui, server)



## You can also use a vector of margins for the fixed argument,
# useful if you have a navbar for example

library(shiny)
library(esquisse)
library(datamods)

ui <- navbarPage(
  title = "My navbar app",
  theme = bs_theme_esquisse(),
  tabPanel(
    title = "esquisse",
    esquisse_ui(
      id = "esquisse", 
      header = FALSE,
      container = esquisse_container(
        fixed = c(55, 0, 0, 0)
      )
    )
  )
)

server <- function(input, output, session) {
  
  # lauch import data modal
  import_modal(
    id = "import-data",
    from = c("env", "file", "copypaste"),
    title = "Import data"
  )
  data_imported_r <- datamods::import_server("import-data")

  data_rv <- reactiveValues(data = data.frame())
  observeEvent(data_imported_r$data(), {
    data_rv$data <- data_imported_r$data()
    data_rv$name <- data_imported_r$name()
  })
  
  esquisse_server(id = "esquisse", data_rv = data_rv)
  
}

if (interactive())
  shinyApp(ui, server)

---

An add-in to easily create plots with ggplot2

Description

Select data to be used and map variables to aesthetics to produce a chart, customize common elements and get code to reproduce the chart.

Usage

esquisser(
  data = NULL,
  controls = c("options", "labs", "axes", "geoms", "theme", "filters", "code"),
  viewer = getOption(x = "esquisse.viewer", default = "dialog")
)

Arguments

data	a data.frame, you can pass a data.frame explicitly to the function, otherwise you'll have to choose one in global environment.
controls	Controls menu to be displayed. Use NULL to hide all menus.
viewer	Where to display the gadget: "dialog", "pane" or "browser" (see viewer).

Value

NULL. You can view code used to produce the chart, copy it or insert it in current script.

Examples

if (interactive()) {
# Launch with :
esquisser(iris)
# If in RStudio it will be launched by default in dialog window
# If not, it will be launched in browser

# Launch esquisse in browser :
esquisser(iris, viewer = "browser")

# You can set this option in .Rprofile :
options("esquisse.viewer" = "viewer")
# or
options("esquisse.viewer" = "browser")

# esquisse use shiny::runApp
# see ?shiny::runApp to see options
# available, example to use custom port:

options("shiny.port" = 8080)
esquisser(iris, viewer = "browser")

}

---

Potential geometries according to the data

Description

From the data and variable used in aesthetics, decide which geometry can be used and which one is used by default.

Usage

potential_geoms(data, mapping, auto = FALSE)

potential_geoms_ref()

Arguments

data	A data.frame
mapping	List of aesthetic mappings to use with data.
auto	Return only one geometry.

Value

A character vector

Examples

library(ggplot2)

# One continuous variable
potential_geoms(
  data = iris,
  mapping = aes(x = Sepal.Length)
)

# Automatic pick a geom
potential_geoms(
  data = iris,
  mapping = aes(x = Sepal.Length),
  auto = TRUE
)

# One discrete variable
potential_geoms(
  data = iris,
  mapping = aes(x = Species)
)

# Two continuous variables
potential_geoms(
  data = iris,
  mapping = aes(x = Sepal.Length, y = Sepal.Width)
)
# Reference used by esquisse to select available geoms
# and decide which one to use by default
potential_geoms_ref()

---

Generate code to create a ggplot2

Description

Generate code to create a ggplot2

Usage

ggcall(
  data = NULL,
  mapping = NULL,
  geom = NULL,
  geom_args = list(),
  scales = NULL,
  scales_args = list(),
  coord = NULL,
  coord_args = list(),
  labs = list(),
  theme = NULL,
  theme_args = list(),
  facet = NULL,
  facet_row = NULL,
  facet_col = NULL,
  facet_args = list(),
  xlim = NULL,
  ylim = NULL
)

Arguments

data	Character. Name of the data.frame.
mapping	List. Named list of aesthetics.
geom	Character. Name of the geom to use (with or without "geom_").
geom_args	List. Arguments to use in the geom.
scales	Character vector. Scale(s) to use (with or without "scale_").
scales_args	List. Arguments to use in scale(s), if scales is length > 1, must be a named list with scales names.
coord	Character. Coordinates to use (with or without "coord_").
coord_args	Arguments for coordinates function.
labs	List. Named list of labels to use for title, subtitle, x & y axis, legends.
theme	Character. Name of the theme to use (with or without "theme_").
theme_args	Named list. Arguments for ggplot2::theme().
facet	Character vector. Names of variables to use in ggplot2::facet_wrap.
facet_row	Character vector. Names of row variables to use in ggplot2::facet_grid().
facet_col	Character vector. Names of col variables to use in ggplot2::facet_grid().
facet_args	Named list. Arguments for ggplot2::facet_wrap().
xlim	A vector of length 2 representing limits on x-axis.
ylim	A vector of length 2 representing limits on y-axis.

Value

a call that can be evaluated with eval.

Examples

# Default:
ggcall()

# With data and aes
ggcall("mtcars", list(x = "mpg", y = "wt"))

# Evaluate the call
library(ggplot2)
eval(ggcall("mtcars", list(x = "mpg", y = "wt")))


# With a geom:
ggcall(
  data = "mtcars",
  mapping = list(x = "mpg", y = "wt"),
  geom = "point"
)

# With options
ggcall(
  data = "mtcars",
  mapping = list(x = "hp", y = "cyl", fill = "color"),
  geom = "bar",
  coord = "flip",
  labs = list(title = "My title"),
  theme = "minimal",
  facet = c("gear", "carb"),
  theme_args = list(legend.position = "bottom")
)

# Theme
ggcall(
  "mtcars", list(x = "mpg", y = "wt"),
  theme = "theme_minimal",
  theme_args = list(
    panel.ontop = TRUE,
    legend.title = rlang::expr(element_text(face = "bold"))
  )
)

# Theme from other package than ggplot2
ggcall(
  "mtcars", list(x = "mpg", y = "wt"),
  theme = "ggthemes::theme_economist"
)


# One scale
ggcall(
  data = "mtcars",
  mapping = list(x = "mpg", y = "wt", color = "qsec"),
  geom = "point",
  scales = "color_distiller",
  scales_args = list(palette = "Blues")
)

# Two scales
ggcall(
  data = "mtcars",
  mapping = list(x = "mpg", y = "wt", color = "qsec", size = "qsec"),
  geom = "point",
  scales = c("color_distiller", "size_continuous"),
  scales_args = list(
    color_distiller = list(palette = "Greens"),
    size_continuous = list(range = c(1, 20))
  )
)


# Coordinates
ggcall(
  data = "mtcars",
  mapping = list(x = "mpg", y = "wt"),
  geom = "point",
  coord = "fixed"
)
ggcall(
  data = "mtcars",
  mapping = list(x = "mpg", y = "wt"),
  geom = "point",
  coord = "fixed",
  coord_args = list(ratio = 5)
)

---

Utility to export ggplot objects to PowerPoint

Description

You can use the RStudio addin to interactively select ggplot objects, or directly pass their names to the function.

Usage

ggplot_to_ppt(gg = NULL)

Arguments

gg	character. Name(s) of ggplot object(s), if NULL, launch the Shiny gadget.

Value

Path to the temporary PowerPoint file.

Examples

# Shiny gadget
if (interactive()) {

ggplot_to_ppt()



# Or with an object's name
library(ggplot2)
p <- ggplot(iris) +
  geom_point(aes(Sepal.Length, Sepal.Width))

ggplot_to_ppt("p")

}

---

Render ggplot module

Description

Display a plot on the client and allow to download it.

Usage

ggplot_output(
  id,
  width = "100%",
  height = "400px",
  downloads = downloads_labels(),
  ...
)

downloads_labels(
  label = ph("download-simple"),
  png = tagList(ph("image"), "PNG"),
  pdf = tagList(ph("file-pdf"), "PDF"),
  svg = tagList(ph("browsers"), "SVG"),
  jpeg = tagList(ph("image"), "JPEG"),
  pptx = tagList(ph("projector-screen"), "PPTX"),
  more = tagList(ph("gear"), i18n("More options"))
)

render_ggplot(
  id,
  expr,
  ...,
  env = parent.frame(),
  quoted = FALSE,
  filename = "export-ggplot",
  resizable = FALSE,
  use_plotly = reactive(FALSE),
  width = reactive(NULL),
  height = reactive(NULL)
)

Arguments

id	Module ID.
width, height	Width / Height of the plot, in the server it has to be a shiny::reactive() function returning a new width/height for the plot.
downloads	Labels for export options, use downloads_labels() or NULL to disable export options.
...	Parameters passed to shiny::plotOutput() (ggplot_output) or shiny::renderPlot() (render_ggplot).
label	Main label for export button
png, pdf, svg, jpeg, pptx	Labels to display in export menu, use NULL to disable specific format.
more	Label for "more" button, allowing to launch export modal.
expr	An expression that generates a ggplot object.
env	The environment in which to evaluate expression.
quoted	Is expr a quoted expression (with quote())? This is useful if you want to save an expression in a variable.
filename	A string of the filename to export WITHOUT extension, it will be added according to type of export.
resizable	Can the chart size be adjusted by the user?
use_plotly	A shiny::reactive() function returning TRUE or FALSE to render the plot with plotly::ggplotly() or not.

Value

Server-side, a reactiveValues with the plot.

Examples

library(shiny)
library(ggplot2)
library(esquisse)


ui <- fluidPage(
  tags$h2("ggplot output"),
  selectInput("var", "Variable:", names(economics)[-1]),
  ggplot_output("MYID", width = "600px")
)

server <- function(input, output, session) {
  
  render_ggplot("MYID", {
    ggplot(economics) + 
      geom_line(aes(date, !!sym(input$var))) + 
      theme_minimal() + 
      labs(
        title = "A cool chart made with ggplot2",
        subtitle = "that you can export in various format"
      )
  })
}

if (interactive())
  shinyApp(ui, server)

---

Picker input to select color(s) or palette

Description

Select menu to view and choose a color or a palette of colors.

Usage

colorPicker(
  inputId,
  label,
  choices,
  selected = NULL,
  textColor = "#000",
  plainColor = FALSE,
  multiple = FALSE,
  pickerOpts = list(),
  width = NULL
)

updateColorPicker(
  session = getDefaultReactiveDomain(),
  inputId,
  choices,
  textColor = "#000",
  plainColor = FALSE,
  multiple = FALSE
)

palettePicker(
  inputId,
  label,
  choices,
  selected = NULL,
  textColor = "#000",
  plainColor = FALSE,
  pickerOpts = list(),
  width = NULL
)

updatePalettePicker(
  session = getDefaultReactiveDomain(),
  inputId,
  choices,
  selected = NULL,
  textColor = "#000",
  plainColor = FALSE
)

Arguments

inputId	The input slot that will be used to access the value.
label	Display label for the control, or NULL for no label.
choices	List of values to select from. Values must be valid Hex colors. If elements of the list are named then that name rather than the value is displayed to the user.
selected	The initially selected value (or multiple values if multiple = TRUE). If not specified then defaults to the first value for single-select lists and no values for multiple select lists.
textColor	Color of the text displayed above colors, can be a vector of the same length as choices.
plainColor	Color the full space of the choice menu.
multiple	Is selection of multiple items allowed?
pickerOpts	Options for pickerInput.
width	The width of the input : 'auto', 'fit', '100px', '75%'.
session	Shiny session.

Value

A select control that can be added to a UI definition.

Examples

# colorPicker -------------------------------------------------------------

library(shiny)
library(esquisse)
library(scales)


ui <- fluidPage(
  tags$h2("colorPicker examples"),
  fluidRow(
    column(
      width = 3,
      colorPicker(
        inputId = "col1",
        label = "With a vector of colors:",
        choices = brewer_pal(palette = "Dark2")(8)
      ),
      verbatimTextOutput("res1"),
      colorPicker(
        inputId = "col5",
        label = "Update colors:",
        choices = brewer_pal(palette = "Blues", direction = -1)(8),
        textColor = "#FFF"
      ),
      verbatimTextOutput("res5"),
      radioButtons(
        "update", "Colors", c("Blues", "Greens", "Reds"),
        inline = TRUE
      )
    ),
    column(
      width = 3,
      colorPicker(
        inputId = "col2",
        label = "Change text color:",
        choices = brewer_pal(palette = "Blues")(8), 
        textColor = c("black", "black", "black", "white",
                      "white", "white", "white", "white")
      ),
      verbatimTextOutput("res2")
    ),
    column(
      width = 3,
      colorPicker(
        inputId = "col3",
        label = "With a list of vector of colors:",
        choices = list(
          "Blues" = brewer_pal(palette = "Blues")(8),
          "Reds" = brewer_pal(palette = "Reds")(8),
          "Greens" = brewer_pal(palette = "Greens")(8)
        )
      ),
      verbatimTextOutput("res3")
    ),
    column(
      width = 3,
      colorPicker(
        inputId = "col4",
        label = "Plain color & multiple choices:",
        choices = brewer_pal(palette = "Paired")(8), 
        plainColor = TRUE, 
        multiple = TRUE, 
        pickerOpts = list(`selected-text-format`= "count > 3")
      ),
      verbatimTextOutput("res4")
    )
  )
)

server <- function(input, output, session) {
  
  output$res1 <- renderPrint(input$col1)
  output$res2 <- renderPrint(input$col2)
  output$res3 <- renderPrint(input$col3)
  output$res4 <- renderPrint(input$col4)
  output$res5 <- renderPrint(input$col5)
  
  observeEvent(input$update, {
    updateColorPicker(
      inputId = "col5",
      choices = brewer_pal(palette = input$update, direction = -1)(8),
      textColor = "#FFF"
    )
  })
  
}

if (interactive()) {
  shinyApp(ui, server)
}

# palettePicker -----------------------------------------------------------

library(shiny)
library(esquisse)
library(scales)

ui <- fluidPage(
  tags$h2("pickerColor examples"),
  
  fluidRow(
    column(
      width = 4,
      palettePicker(
        inputId = "pal1", 
        label = "Select a palette:", 
        choices = list(
          "Blues" = brewer_pal(palette = "Blues")(8),
          "Reds" = brewer_pal(palette = "Reds")(8)
        )
      ),
      verbatimTextOutput("res1"),
      palettePicker(
        inputId = "pal4", 
        label = "Update palette:", 
        choices = list(
          "Blues" = brewer_pal(palette = "Blues")(8),
          "Reds" = brewer_pal(palette = "Reds")(8)
        )
      ),
      verbatimTextOutput("res4"),
      radioButtons(
        "update", "Palettes:", c("default", "viridis", "brewer"),
        inline = TRUE
      )
    ),
    column(
      width = 4,
      palettePicker(
        inputId = "pal2", 
        label = "With a list of palette:", 
        choices = list(
          "Viridis" = list(
            "viridis" = viridis_pal(option = "viridis")(10),
            "magma" = viridis_pal(option = "magma")(10),
            "inferno" = viridis_pal(option = "inferno")(10),
            "plasma" = viridis_pal(option = "plasma")(10),
            "cividis" = viridis_pal(option = "cividis")(10)
          ),
          "Brewer" = list(
            "Blues" = brewer_pal(palette = "Blues")(8),
            "Reds" = brewer_pal(palette = "Reds")(8),
            "Paired" = brewer_pal(palette = "Paired")(8),
            "Set1" = brewer_pal(palette = "Set1")(8)
          )
        ), 
        textColor = c(
          rep("white", 5), rep("black", 4) 
        )
      ),
      verbatimTextOutput("res2")
    ),
    column(
      width = 4,
      palettePicker(
        inputId = "pal3", 
        label = "With plain colors:", 
        choices = list(
          "BrBG" = brewer_pal(palette = "BrBG")(8), 
          "PiYG" = brewer_pal(palette = "PiYG")(8), 
          "PRGn" = brewer_pal(palette = "PRGn")(8), 
          "PuOr" = brewer_pal(palette = "PuOr")(8), 
          "RdBu" = brewer_pal(palette = "RdBu")(8), 
          "RdGy" = brewer_pal(palette = "RdGy")(8), 
          "RdYlBu" = brewer_pal(palette = "RdYlBu")(8), 
          "RdYlGn" = brewer_pal(palette = "RdYlGn")(8), 
          "Spectral" = brewer_pal(palette = "Spectral")(8)
        ), 
        plainColor = TRUE, 
        textColor = "white"
      ),
      verbatimTextOutput("res3")
    )
  )
)

server <- function(input, output, session) {
  
  output$res1 <- renderPrint(input$pal1)
  output$res2 <- renderPrint(input$pal2)
  output$res3 <- renderPrint(input$pal3)
  output$res4 <- renderPrint(input$pal4)
  
  observeEvent(input$update, {
    if (input$update == "default") {
      updatePalettePicker(
        inputId = "pal4",
        choices = list(
          "Blues" = brewer_pal(palette = "Blues")(8),
          "Reds" = brewer_pal(palette = "Reds")(8)
        )
      )
    } else if (input$update == "viridis") {
      updatePalettePicker(
        inputId = "pal4",
        choices = list(
          "viridis" = viridis_pal(option = "viridis")(10),
          "magma" = viridis_pal(option = "magma")(10),
          "inferno" = viridis_pal(option = "inferno")(10),
          "plasma" = viridis_pal(option = "plasma")(10),
          "cividis" = viridis_pal(option = "cividis")(10)
        ),
        textColor = "#FFF"
      )
    } else if (input$update == "brewer") {
      updatePalettePicker(
        inputId = "pal4",
        choices = list(
          "Blues" = brewer_pal(palette = "Blues")(8),
          "Reds" = brewer_pal(palette = "Reds")(8),
          "Paired" = brewer_pal(palette = "Paired")(8),
          "Set1" = brewer_pal(palette = "Set1")(8)
        )
      )
    }
  })
}

if (interactive()) {
  shinyApp(ui, server)
}

---

Match list of arguments to arguments of geometry

Description

Match list of arguments to arguments of geometry

Usage

match_geom_args(
  geom,
  args,
  add_aes = TRUE,
  mapping = list(),
  add_mapping = FALSE,
  exclude_args = NULL,
  envir = "ggplot2"
)

Arguments

geom	Character. name of the geometry.
args	Named list, parameters to be matched to the geometry arguments.
add_aes	Add aesthetics parameters (like size, fill, ...).
mapping	Mapping used in plot, to avoid setting fixed aesthetics parameters.
add_mapping	Add the mapping as an argument.
exclude_args	Character vector of arguments to exclude, default is to exclude aesthetics names.
envir	Package environment to search in.

Value

a list().

Examples

# List of parameters
params <- list(
  bins = 30,
  scale = "width",
  adjust = 2,
  position = "stack",
  size = 1.6,
  fill = "#112246"
)

# Search arguments according to geom
match_geom_args(geom = "histogram", args = params)
match_geom_args(geom = "violin", args = params)
match_geom_args(geom = "bar", args = params, add_aes = FALSE)
match_geom_args(geom = "point", args = params)
match_geom_args(geom = "point", args = params, add_aes = FALSE)

---

Safely render a ggplot in Shiny application

Description

Safely render a ggplot in Shiny application

Usage

safe_ggplot(
  expr,
  data = NULL,
  show_notification = c("always", "once", "never"),
  session = shiny::getDefaultReactiveDomain()
)

Arguments

expr	Code to produce a ggplot object.
data	Argument passed to eval_tidy to evaluate expression.
show_notification	Strategy for notifications when a warning occurs: "always" : default, show notifications for each warnings ⁠"once⁠ : show notification once per warning "never" : do not display notifications.
session	Session object to send notification to.

Value

Output of ggplot_build.

Examples

if (interactive()) {
  library(shiny)
  library(ggplot2)

  ui <- fluidPage(
    fluidRow(
      column(
        width = 3,
        selectInput(
          inputId = "var",
          label = "Var:",
          choices = c("Sepal.Width", "Do.Not.Exist")
        )
      ),
      column(
        width = 9,
        plotOutput(outputId = "plot")
      )
    )
  )

  server <- function(input, output, session) {

    output$plot <- renderPlot({
      p <- ggplot(iris) +
        geom_point(aes_string("Sepal.Length", input$var))
      safe_ggplot(p)
    })

  }

  shinyApp(ui, server)
}

---

Save ggplot module

Description

Save a ggplot object in various format and resize it before saving.

Usage

save_ggplot_ui(
  id,
  output_format = c("png", "pdf", "svg", "jpeg", "bmp", "eps", "tiff")
)

save_ggplot_modal(
  id,
  title = NULL,
  output_format = c("png", "pdf", "svg", "jpeg", "bmp", "eps", "tiff")
)

save_ggplot_server(id, plot_rv)

Arguments

id	Module ID.
output_format	Output formats offered to the user.
title	Modal's title.
plot_rv	A reactiveValues with a slot plot containing a ggplot object.

Value

No value. Use in UI & server of shiny application.

Examples

library(shiny)
library(ggplot2)
library(esquisse)


ui <- fluidPage(
  tags$h2("Save a ggplot"),
  selectInput("var", "Variable:", names(economics)[-1]),
  plotOutput("plot", width = "600px"),
  actionButton("save", "Save this plot")
)

server <- function(input, output, session) {
  
  rv <- reactiveValues(plot = NULL)
  
  output$plot <- renderPlot({
    rv$plot <- ggplot(economics) + 
      geom_line(aes(date, !!sym(input$var))) + 
      theme_minimal()
    rv$plot
  })
  
  observeEvent(input$save, {
    save_ggplot_modal("ID", "Save plot")
  })
  save_ggplot_server("ID", rv)
}

if (interactive())
  shinyApp(ui, server)

---

Update Dragula Input

Description

Update dragulaInput() widget server-side.

Usage

updateDragulaInput(
  session,
  inputId,
  choices = NULL,
  choiceNames = NULL,
  choiceValues = NULL,
  selected = NULL,
  selectedNames = NULL,
  selectedValues = NULL,
  badge = TRUE,
  status = "primary"
)

Arguments

session	The session object passed to function given to shinyServer.
inputId	The input slot that will be used to access the value.
choices	List of values to select from (if elements of the list are named then that name rather than the value is displayed to the user). If this argument is provided, then choiceNames and choiceValues must not be provided, and vice-versa. The values should be strings; other types (such as logicals and numbers) will be coerced to strings.
choiceNames, choiceValues	List of names and values, respectively, that are displayed to the user in the app and correspond to the each choice (for this reason, choiceNames and choiceValues must have the same length). If either of these arguments is provided, then the other must be provided and choices must not be provided. The advantage of using both of these over a named list for choices is that choiceNames allows any type of UI object to be passed through (tag objects, icons, HTML code, ...), instead of just simple text.
selected	Default selected values. Must be a list with targetsIds as names.
selectedNames, selectedValues	Update selected items with custom names and values.
badge	Displays choices inside a Bootstrap badge. Use FALSE if you want to pass custom appearance with choiceNames.
status	If choices are displayed into a Bootstrap label, you can use Bootstrap status to color them, or NULL.

Examples

if (interactive()) {

library("shiny")
library("esquisse")

ui <- fluidPage(
  tags$h2("Update dragulaInput"),
  radioButtons(
    inputId = "update",
    label = "Dataset",
    choices = c("iris", "mtcars")
  ),
  tags$br(),
  dragulaInput(
    inputId = "myDad",
    sourceLabel = "Variables",
    targetsLabels = c("X", "Y", "fill", "color", "size"),
    choices = names(iris),
    replace = TRUE, width = "400px", status = "success"
  ),
  verbatimTextOutput(outputId = "result")
)

server <- function(input, output, session) {

  output$result <- renderPrint(str(input$myDad))

  observeEvent(input$update, {
    if (input$update == "iris") {
      updateDragulaInput(
        session = session,
        inputId = "myDad",
        choices = names(iris),
        status = "success"
      )
    } else {
      updateDragulaInput(
        session = session,
        inputId = "myDad",
        choices = names(mtcars)
      )
    }
  }, ignoreInit = TRUE)

}

shinyApp(ui, server)

}

---

Change the value of a drop input on the client

Description

Change the value of a drop input on the client

Usage

updateDropInput(session, inputId, selected = NULL, disabled = NULL)

Arguments

session	The session object passed to function given to shinyServer.
inputId	The id of the input object.
selected	The initially selected value.
disabled	Choices (choicesValues) to disable.

See Also

dropInput

Examples

if (interactive()) {

  library(shiny)
  library(esquisse)

  myChoices <- tagList(
    list(icon("home"), style = "width: 100px;"),
    list(icon("flash"), style = "width: 100px;"),
    list(icon("cogs"), style = "width: 100px;"),
    list(icon("fire"), style = "width: 100px;"),
    list(icon("users"), style = "width: 100px;"),
    list(icon("info"), style = "width: 100px;")
  )


  ui <- fluidPage(
    tags$h2("Update Drop Input"),
    fluidRow(
      column(
        width = 6,
        dropInput(
          inputId = "mydrop",
          choicesNames = myChoices,
          choicesValues = c("home", "flash", "cogs", "fire", "users", "info"),
          dropWidth = "220px"
        ),
        verbatimTextOutput(outputId = "res")
      ),
      column(
        width = 6,
        actionButton("home", "Select home"),
        actionButton("flash", "Select flash"),
        actionButton("cogs", "Select cogs"),
        actionButton("fire", "Select fire"),
        actionButton("users", "Select users"),
        actionButton("info", "Select info"),
        checkboxGroupInput(
          inputId = "disabled",
          label = "Choices to disable",
          choices = c("home", "flash", "cogs", "fire", "users", "info")
        ),
        actionButton("disable", "Disable")
      )
    )
  )

  server <- function(input, output, session) {

    output$res <- renderPrint({
      input$mydrop
    })

    observeEvent(input$home, {
      updateDropInput(session, "mydrop", "home")
    })
    observeEvent(input$flash, {
      updateDropInput(session, "mydrop", "flash")
    })
    observeEvent(input$cogs, {
      updateDropInput(session, "mydrop", "cogs")
    })
    observeEvent(input$fire, {
      updateDropInput(session, "mydrop", "fire")
    })
    observeEvent(input$users, {
      updateDropInput(session, "mydrop", "users")
    })
    observeEvent(input$info, {
      updateDropInput(session, "mydrop", "info")
    })

    observeEvent(input$disable, {
      if (!is.null(input$disabled)) {
        updateDropInput(session, "mydrop", disabled = input$disabled)
      } else {
        updateDropInput(session, "mydrop", disabled = character(0))
      }
    })
  }

  shinyApp(ui, server)

}

---

Automatically select appropriate color scale

Description

Automatically select appropriate color scale

Usage

which_pal_scale(
  mapping,
  palette = "ggplot2",
  data = NULL,
  fill_type = c("continuous", "discrete"),
  color_type = c("continuous", "discrete"),
  reverse = FALSE
)

Arguments

mapping	Aesthetics used in ggplot.
palette	Color palette.
data	An optional data.frame to choose the right type for variables.
fill_type, color_type	Scale to use according to the variable used in fill/color aesthetic : "discrete" or "continuous". Ignored if data is provided: it will be guessed from data.
reverse	Reverse colors order or not.

Value

a list

Examples

library(ggplot2)

# Automatic guess according to data
which_pal_scale(
  mapping = aes(fill = Sepal.Length),
  palette = "ggplot2",
  data = iris
)
which_pal_scale(
  mapping = aes(fill = Species),
  palette = "ggplot2",
  data = iris
)


# Explicitly specify type
which_pal_scale(
  mapping = aes(color = variable),
  palette = "Blues",
  color_type = "discrete"
)


# Both scales
which_pal_scale(
  mapping = aes(color = var1, fill = var2),
  palette = "Blues",
  color_type = "discrete",
  fill_type = "continuous"
)

---