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Title:	Create Interactive Web Graphics via 'plotly.js'
Version:	4.11.0
License:	MIT + file LICENSE
Description:	Create interactive web graphics from 'ggplot2' graphs and/or a custom interface to the (MIT-licensed) JavaScript library 'plotly.js' inspired by the grammar of graphics.
URL:	https://plotly-r.com,https://github.com/plotly/plotly.R,https://plotly.com/r/
BugReports:	https://github.com/plotly/plotly.R/issues
Depends:	R (≥ 3.2.0), ggplot2 (≥ 3.0.0)
Imports:	tools, scales, httr (≥ 1.3.0), jsonlite (≥ 1.6), magrittr,digest, viridisLite, base64enc, htmltools (≥ 0.3.6),htmlwidgets (≥ 1.5.2.9001), tidyr (≥ 1.0.0), RColorBrewer,dplyr, vctrs, tibble, lazyeval (≥ 0.2.0), rlang (≥ 1.0.0),crosstalk, purrr, data.table, promises
Suggests:	MASS, maps, hexbin, ggthemes, GGally, ggalluvial, testthat,knitr, shiny (≥ 1.1.0), shinytest2, curl, rmarkdown, Cairo,broom, webshot, listviewer, dendextend, sf, png, IRdisplay,processx, plotlyGeoAssets, forcats, withr, palmerpenguins,rversions, reticulate, rsvg, ggridges
LazyData:	true
RoxygenNote:	7.3.2
Encoding:	UTF-8
Config/Needs/check:	tidyverse/ggplot2, ggobi/GGally, rcmdcheck,devtools, reshape2, s2
NeedsCompilation:	no
Packaged:	2025-06-19 15:43:06 UTC; cpsievert
Author:	Carson Sievert [aut, cre], Chris Parmer [aut], Toby Hocking [aut], Scott Chamberlain [aut], Karthik Ram [aut], Marianne Corvellec [aut], Pedro Despouy [aut], Salim Brüggemann [ctb], Plotly Technologies Inc. [cph]
Maintainer:	Carson Sievert <cpsievert1@gmail.com>
Repository:	CRAN
Date/Publication:	2025-06-19 18:30:02 UTC

Render TeX in a plotly graph using MathJax

Description

This function makes it slightly easier to render TeX in a plotly graph –it ensures that MathJax is included with the final result and alsoensures the provided string is surrounded with$ (this is what plotly.jsuses to declare a string as TeX).

Usage

TeX(x)

Arguments

See Also

config

Examples

plot_ly(x = c(1, 2, 3, 4), y = c(1, 4, 9, 16)) %>%  layout(title = TeX("\\text{Some mathjax: }\\alpha+\\beta x")) %>%  config(mathjax = "cdn")

Add an annotation(s) to a plot

Description

Add an annotation(s) to a plot

Usage

add_annotations(p, text = NULL, ..., data = NULL, inherit = TRUE)

Arguments

Author(s)

Carson Sievert

Add data to a plotly visualization

Description

Add data to a plotly visualization

Usage

add_data(p, data = NULL)

Arguments

Examples

plot_ly() %>% add_data(economics) %>% add_trace(x = ~date, y = ~pce)

Apply function to plot, without modifying data

Description

Useful when you need two or more layers that apply a summary statisticto the original data.

Usage

add_fun(p, fun, ...)

Arguments

Add trace(s) to a plotly visualization

Description

Add trace(s) to a plotly visualization

Usage

add_trace(p, ..., data = NULL, inherit = TRUE)add_markers(p, x = NULL, y = NULL, z = NULL, ..., data = NULL, inherit = TRUE)add_text(  p,  x = NULL,  y = NULL,  z = NULL,  text = NULL,  ...,  data = NULL,  inherit = TRUE)add_paths(p, x = NULL, y = NULL, z = NULL, ..., data = NULL, inherit = TRUE)add_lines(p, x = NULL, y = NULL, z = NULL, ..., data = NULL, inherit = TRUE)add_segments(  p,  x = NULL,  y = NULL,  xend = NULL,  yend = NULL,  ...,  data = NULL,  inherit = TRUE)add_polygons(p, x = NULL, y = NULL, ..., data = NULL, inherit = TRUE)add_sf(p, ..., x = ~x, y = ~y, data = NULL, inherit = TRUE)add_table(p, ..., rownames = TRUE, data = NULL, inherit = TRUE)add_ribbons(  p,  x = NULL,  ymin = NULL,  ymax = NULL,  ...,  data = NULL,  inherit = TRUE)add_image(p, z = NULL, colormodel = NULL, ..., data = NULL, inherit = TRUE)add_area(p, r = NULL, theta = NULL, t = NULL, ..., data = NULL, inherit = TRUE)add_pie(p, values = NULL, labels = NULL, ..., data = NULL, inherit = TRUE)add_bars(p, x = NULL, y = NULL, ..., data = NULL, inherit = TRUE)add_histogram(p, x = NULL, y = NULL, ..., data = NULL, inherit = TRUE)add_histogram2d(  p,  x = NULL,  y = NULL,  z = NULL,  ...,  data = NULL,  inherit = TRUE)add_histogram2dcontour(  p,  x = NULL,  y = NULL,  z = NULL,  ...,  data = NULL,  inherit = TRUE)add_heatmap(p, x = NULL, y = NULL, z = NULL, ..., data = NULL, inherit = TRUE)add_contour(p, z = NULL, ..., data = NULL, inherit = TRUE)add_boxplot(p, x = NULL, y = NULL, ..., data = NULL, inherit = TRUE)add_surface(p, z = NULL, ..., data = NULL, inherit = TRUE)add_mesh(p, x = NULL, y = NULL, z = NULL, ..., data = NULL, inherit = TRUE)add_scattergeo(p, ...)add_choropleth(p, z = NULL, ..., data = NULL, inherit = TRUE)

Arguments

Author(s)

Carson Sievert

References

https://plotly-r.com/overview.html

https://plotly.com/r/

https://plotly.com/r/reference/

See Also

plot_ly()

Examples

# the `plot_ly()` function initiates an object, and if no trace type# is specified, it sets a sensible defaultp <- plot_ly(economics, x = ~date, y = ~uempmed)p# some `add_*()` functions are a specific case of a trace type# for example, `add_markers()` is a scatter trace with mode of markersadd_markers(p)# scatter trace with mode of textadd_text(p, text = "%")# scatter trace with mode of lines add_paths(p)# like `add_paths()`, but ensures points are connected according to `x`add_lines(p)# if you prefer to work with plotly.js more directly, can always# use `add_trace()` and specify the type yourselfadd_trace(p, type = "scatter", mode = "markers+lines")# mappings provided to `plot_ly()` are "global", but can be overwrittenplot_ly(economics, x = ~date, y = ~uempmed, color = I("red"), showlegend = FALSE) %>%   add_lines() %>%  add_markers(color = ~pop)# a number of `add_*()` functions are special cases of the scatter traceplot_ly(economics, x = ~date) %>%   add_ribbons(ymin = ~pce - 1e3, ymax = ~pce + 1e3)# use `group_by()` (or `group2NA()`) to apply visual mapping# once per group (e.g. one line per group)txhousing %>%   group_by(city) %>%   plot_ly(x = ~date, y = ~median) %>%  add_lines(color = I("black"))## Not run: # use `add_sf()` or `add_polygons()` to create geo-spatial maps# http://blog.cpsievert.me/2018/03/30/visualizing-geo-spatial-data-with-sf-and-plotly/if (requireNamespace("sf", quietly = TRUE)) {  nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)  plot_ly() %>% add_sf(data = nc)}# univariate summary statisticsplot_ly(mtcars, x = ~factor(vs), y = ~mpg) %>%   add_boxplot()plot_ly(mtcars, x = ~factor(vs), y = ~mpg) %>%   add_trace(type = "violin")  # `add_histogram()` does binning for you...mtcars %>%  plot_ly(x = ~factor(vs)) %>%  add_histogram()  # ...but you can 'pre-compute' bar heights in Rmtcars %>%  dplyr::count(vs) %>%  plot_ly(x = ~vs, y = ~n) %>%  add_bars()# the 2d analogy of add_histogram() is add_histogram2d()/add_histogram2dcontour()library(MASS)(p <- plot_ly(geyser, x = ~waiting, y = ~duration))add_histogram2d(p)add_histogram2dcontour(p)# the 2d analogy of add_bars() is add_heatmap()/add_contour()# (i.e., bin counts must be pre-specified)den <- kde2d(geyser$waiting, geyser$duration)p <- plot_ly(x = den$x, y = den$y, z = den$z)add_heatmap(p)add_contour(p)# `add_table()` makes it easy to map a data frame to the table trace typeplot_ly(economics) %>%   add_table()# pie charts!ds <- data.frame(labels = c("A", "B", "C"), values = c(10, 40, 60))plot_ly(ds, labels = ~labels, values = ~values) %>%  add_pie() %>%  layout(title = "Basic Pie Chart using Plotly")  data(wind)plot_ly(wind, r = ~r, theta = ~t) %>%   add_area(color = ~nms) %>%  layout(    polar = list(      radialaxis = list(ticksuffix = "%"),       angularaxis = list(rotation = 90)    )  )# ------------------------------------------------------------# 3D chart types# ------------------------------------------------------------plot_ly(z = ~volcano) %>%   add_surface()plot_ly(x = c(0, 0, 1), y = c(0, 1, 0), z = c(0, 0, 0)) %>%   add_mesh()## End(Not run)

Animation configuration options

Description

Animations can be created by either using theframe argument inplot_ly() or the (unofficial)frame ggplot2 aesthetic inggplotly(). By default, animations populate a play buttonand slider component for controlling the state of the animation(to pause an animation, click on a relevant location on the slider bar).Both the play button and slider component transition between frames accordingrules specified byanimation_opts().

Usage

animation_opts(  p,  frame = 500,  transition = frame,  easing = "linear",  redraw = TRUE,  mode = "immediate")animation_slider(p, hide = FALSE, ...)animation_button(p, ..., label)

Arguments

Author(s)

Carson Sievert

Examples

df <- data.frame(  x = c(1, 2, 2, 1, 1, 2),  y = c(1, 2, 2, 1, 1, 2),  z = c(1, 1, 2, 2, 3, 3))plot_ly(df) %>%  add_markers(x = 1.5, y = 1.5) %>%  add_markers(x = ~x, y = ~y, frame = ~z)# it's a good idea to remove smooth transitions when there is# no relationship between objects in each viewplot_ly(mtcars, x = ~wt, y = ~mpg, frame = ~cyl) %>%  animation_opts(transition = 0)# works the same way with ggplotlyif (interactive()) {  p <- ggplot(txhousing, aes(month, median)) +    geom_line(aes(group = year), alpha = 0.3) +    geom_smooth() +    geom_line(aes(frame = year, ids = month), color = "red") +    facet_wrap(~ city)   ggplotly(p, width = 1200, height = 900) %>%    animation_opts(1000)}  #' # for more, see https://plotly.com/r/animating-views.html

Tools for working with plotly's REST API (v2)

Description

Convenience functions for working with version 2 of plotly's REST API.Upload R objects to a plotly account viaapi_create() and downloadplotly objects viaapi_download_plot()/api_download_grid().For anything else, useapi().

Usage

api_create(  x = last_plot(),  filename = NULL,  fileopt = c("overwrite", "new"),  sharing = c("public", "private", "secret"),  ...)## S3 method for class 'plotly'api_create(  x = last_plot(),  filename = NULL,  fileopt = "overwrite",  sharing = "public",  ...)## S3 method for class 'ggplot'api_create(  x = last_plot(),  filename = NULL,  fileopt = "overwrite",  sharing = "public",  ...)## S3 method for class 'data.frame'api_create(x, filename = NULL, fileopt = "overwrite", sharing = "public", ...)api_download_plot(id, username)api_download_grid(id, username)api(endpoint = "/", verb = "GET", body = NULL, ...)

Arguments

Author(s)

Carson Sievert

References

https://api.plot.ly/v2

See Also

signup()

Examples

## Not run: # ------------------------------------------------------------# api_create() makes it easy to upload ggplot2/plotly objects# and/or data frames to your plotly account# ------------------------------------------------------------# A data frame creates a plotly "grid". Printing one will take you # to the it's web address so you can start creating!(m <- api_create(mtcars))# A plotly/ggplot2 object create a plotly "plot".p <- plot_ly(mtcars, x = ~factor(vs))(r <- api_create(p))# api_create() returns metadata about the remote "file". Here is# one way you could use that metadata to download a plot for local use:fileID <- strsplit(r$file$fid, ":")[[1]]layout(  api_download_plot(fileID[2], fileID[1]),  title = sprintf("Local version of <a href='%s'>this</a> plot", r$file$web_url))------------------------------------------------------------# The api() function provides a low-level interface for performing # any action at any endpoint! It always returns a list.# ------------------------------------------------------------# list all the endpointsapi()# search the entire platform!# see https://api.plot.ly/v2/searchapi("search?q=overdose")api("search?q=plottype:pie trump fake")# these examples will require a user accountusr <- Sys.getenv("plotly_username", NA)if (!is.na(usr)) {  # your account info https://api.plot.ly/v2/#users  api(sprintf("users/%s", usr))  # your folders/files https://api.plot.ly/v2/folders#user  api(sprintf("folders/home?user=%s", usr))}# Retrieve a specific file https://api.plot.ly/v2/files#retrieveapi("files/cpsievert:14681")# change the filename https://api.plot.ly/v2/files#update# (note: this won't work unless you have proper credentials to the relevant account)api("files/cpsievert:14681", "PATCH", list(filename = "toy file")) # Copy a file https://api.plot.ly/v2/files#lookupapi("files/cpsievert:14681/copy", "POST")# Create a folder https://api.plot.ly/v2/folders#createapi("folders", "POST", list(path = "/starts/at/root/and/ends/here"))## End(Not run)

Convert a plotly object to an htmlwidget object

Description

This function was deprecated in 4.0.0,as plotly objects are now htmlwidget objects,so there is no need to convert them.

Usage

as.widget(x, ...)

Arguments

Convert a list to a plotly htmlwidget object

Description

Convert a list to a plotly htmlwidget object

Usage

as_widget(x, ...)

Arguments

Examples

trace <- list(x = 1, y = 1)obj <- list(data = list(trace), layout = list(title = "my plot"))as_widget(obj)

Specify attributes of selection traces

Description

By default the name of the selection trace derives from the selected values.

Usage

attrs_selected(opacity = 1, ...)

Arguments

Author(s)

Carson Sievert

Estimate bounding box of a rotated string

Description

Estimate bounding box of a rotated string

Usage

bbox(txt = "foo", angle = 0, size = 12)

Arguments

References

https://www.dropbox.com/s/nc6968prgw8ne4w/bbox.pdf?dl=0

Modify the colorbar

Description

Modify the colorbar

Usage

colorbar(p, ..., limits = NULL, which = 1)

Arguments

Author(s)

Carson Sievert

Examples

p <- plot_ly(mtcars, x = ~wt, y = ~mpg, color = ~cyl)# pass any colorbar attribute -- # https://plotly.com/r/reference/#scatter-marker-colorbarcolorbar(p, len = 0.5)# Expand the limits of the colorbarcolorbar(p, limits = c(0, 20))# values outside the colorbar limits are considered "missing"colorbar(p, limits = c(5, 6))# also works on colorbars generated via a z valuecorr <- cor(diamonds[vapply(diamonds, is.numeric, logical(1))])plot_ly(x = rownames(corr), y = colnames(corr), z = corr) %>% add_heatmap() %>% colorbar(limits = c(-1, 1))

Set the default configuration for plotly

Description

Set the default configuration for plotly

Usage

config(  p,  ...,  cloud = FALSE,  showSendToCloud = cloud,  locale = NULL,  mathjax = NULL)

Arguments

Author(s)

Carson Sievert

Examples

# remove the plotly logo and collaborate button from modebarconfig(plot_ly(), displaylogo = FALSE, collaborate = FALSE)# enable mathjax# see more examples at https://plotly.com/r/LaTeX/plot_ly(x = c(1, 2, 3, 4), y = c(1, 4, 9, 16)) %>%  layout(title = TeX("\\text{Some mathjax: }\\alpha+\\beta x")) %>%  config(mathjax = "cdn")# change the language used to render date axes and on-graph text # (e.g., modebar buttons)today <- Sys.Date()x <- seq.Date(today, today + 360, by = "day")p <- plot_ly(x = x, y = rnorm(length(x))) %>%  add_lines()# japaneseconfig(p, locale = "ja")# germanconfig(p, locale = "de")# spanishconfig(p, locale = "es")# chineseconfig(p, locale = "zh-CN")

Embed a plot as an iframe into a Jupyter Notebook

Description

Embed a plot as an iframe into a Jupyter Notebook

Usage

embed_notebook(x, width = NULL, height = NULL, file = NULL)

Arguments

Author(s)

Carson Sievert

Access plotly user input event data in shiny

Description

This function must be called within a reactive shiny context.

Usage

event_data(  event = c("plotly_hover", "plotly_unhover", "plotly_click", "plotly_doubleclick",    "plotly_selected", "plotly_selecting", "plotly_brushed", "plotly_brushing",    "plotly_deselect", "plotly_relayout", "plotly_restyle", "plotly_legendclick",    "plotly_legenddoubleclick", "plotly_clickannotation", "plotly_afterplot",    "plotly_sunburstclick"),  source = "A",  session = shiny::getDefaultReactiveDomain(),  priority = c("input", "event"))

Arguments

Author(s)

Carson Sievert

References

• https://plotly-r.com/linking-views-with-shiny.html#shiny-plotly-inputs

• https://plotly.com/javascript/plotlyjs-function-reference/

See Also

event_register,event_unregister

Examples

## Not run: plotly_example("shiny", "event_data")## End(Not run)

Register a shiny input value

Description

Register a shiny input value

Usage

event_register(p, event = NULL)

Arguments

Author(s)

Carson Sievert

See Also

event_data

Un-register a shiny input value

Description

Un-register a shiny input value

Usage

event_unregister(p, event = NULL)

Arguments

Author(s)

Carson Sievert

See Also

event_data

Export a plotly graph to a static file

Description

This function is deprecated, usesave_image instead.

Usage

export(p = last_plot(), file = "plotly.png", selenium = NULL, ...)

Arguments

Details

For SVG plots, a screenshot is taken viawebshot::webshot().Sincephantomjs (and hencewebshot) does not support WebGL,the RSelenium package is used for exporting WebGL plots.

Author(s)

Carson Sievert

Convert a "basic" geoms to a plotly.js trace.

Description

This function makes it possible to convert ggplot2 geoms thatare not included with ggplot2 itself. Users shouldn't need to usethis function. It exists purely to allow other package authors to writetheir own conversion method(s).

Usage

geom2trace(data, params, p)

Arguments

Request a figure object

Description

Deprecated: seeapi_download_plot().

Usage

get_figure(username, id)

Arguments

Convert a ggplot to a list.

Description

Convert a ggplot to a list.

Usage

gg2list(  p,  width = NULL,  height = NULL,  tooltip = "all",  dynamicTicks = FALSE,  layerData = 1,  originalData = TRUE,  source = "A",  ...)

Arguments

Value

a 'built' plotly object (list with names "data" and "layout").

Convert ggplot2 to plotly

Description

This function converts aggplot2::ggplot() object to aplotly object.

Usage

ggplotly(  p = ggplot2::last_plot(),  width = NULL,  height = NULL,  tooltip = "all",  dynamicTicks = FALSE,  layerData = 1,  originalData = TRUE,  source = "A",  ...)

Arguments

Details

Conversion of relative sizes depends on the size of the currentgraphics device (if no device is open, width/height of a new (off-screen)device defaults to 640/480). In other words,height andwidth must be specified at runtime to ensure sizing is correct.For examples on how to specify the output container'sheight/width in ashiny app, seeplotly_example("shiny", "ggplotly_sizing").

Author(s)

Carson Sievert

References

https://plotly.com/ggplot2/

See Also

plot_ly()

Examples

## Not run: # simple exampleggpenguins <- qplot(bill_length_mm , body_mass_g, data = palmerpenguins::penguins, color = species)ggplotly(ggpenguins)data(canada.cities, package = "maps")viz <- ggplot(canada.cities, aes(long, lat)) +  borders(regions = "canada") +  coord_equal() +  geom_point(aes(text = name, size = pop), colour = "red", alpha = 1/2)ggplotly(viz, tooltip = c("text", "size"))# linked scatterplot brushingd <- highlight_key(mtcars)qplot(data = d, x = mpg, y = wt) %>%  subplot(qplot(data = d, x = mpg, y = vs)) %>%   layout(title = "Click and drag to select points") %>%  highlight("plotly_selected")# more brushing (i.e. highlighting) examplesdemo("crosstalk-highlight-ggplotly", package = "plotly")# client-side linked brushing in a scatterplot matrixhighlight_key(palmerpenguins::penguins) %>%  GGally::ggpairs(aes(colour = Species), columns = 1:4) %>%  ggplotly(tooltip = c("x", "y", "colour")) %>%  highlight("plotly_selected")## End(Not run)

Separate groups with missing values

Description

This function is used internally by plotly, but may also be useful to somepower users. The details section explains when and why this function is useful.

Usage

group2NA(  data,  groupNames = "group",  nested = NULL,  ordered = NULL,  retrace.first = inherits(data, "GeomPolygon"))

Arguments

Details

If a group of scatter traces share the same non-positional characteristics(i.e., color, fill, etc), it is more efficient to draw them as a single tracewith missing values that separate the groups (instead of multiple traces),In this case, one should also take care to make sureconnectgapsis set toFALSE.

Value

a data.frame with rows ordered by:nested,thengroupNames, thenordered. As long asgroupNamescontains valid variable names, new rows will also be inserted to separatethe groups.

Examples

# note the insertion of new rows with missing values group2NA(mtcars, "vs", "cyl")# need to group lines by city somehow!plot_ly(txhousing, x = ~date, y = ~median) %>% add_lines()# instead of using group_by(), you could use group2NA()tx <- group2NA(txhousing, "city")plot_ly(tx, x = ~date, y = ~median) %>% add_lines()# add_lines() will ensure paths are sorted by x, but this is equivalenttx <- group2NA(txhousing, "city", ordered = "date")plot_ly(tx, x = ~date, y = ~median) %>% add_paths()

Hide color bar(s)

Description

Hide color bar(s)

Usage

hide_colorbar(p)

Arguments

See Also

hide_legend()

Examples

p <- plot_ly(mtcars, x = ~wt, y = ~cyl, color = ~cyl)hide_colorbar(p)

Hide guides (legends and colorbars)

Description

Hide guides (legends and colorbars)

Usage

hide_guides(p)

Arguments

See Also

hide_legend(),hide_colorbar()

Hide legend

Description

Hide legend

Usage

hide_legend(p)

Arguments

See Also

hide_colorbar()

Examples

p <- plot_ly(mtcars, x = ~wt, y = ~cyl, color = ~factor(cyl))hide_legend(p)

Query graphical elements in multiple linked views

Description

This function sets a variety of options for brushing (i.e., highlighting)multiple plots. These options are primarily designed for linkingmultiple plotly graphs, and may not behave as expected when linkingplotly to another htmlwidget package via crosstalk. In some cases,other htmlwidgets will respect these options, such as persistent selectionin leaflet (seedemo("highlight-leaflet", package = "plotly")).

Usage

highlight(  p,  on = "plotly_click",  off,  persistent = getOption("persistent", FALSE),  dynamic = FALSE,  color = NULL,  selectize = FALSE,  defaultValues = NULL,  opacityDim = getOption("opacityDim", 0.2),  selected = attrs_selected(),  debounce = 0,  ...)

Arguments

Author(s)

Carson Sievert

References

https://plotly-r.com/client-side-linking.html

See Also

attrs_selected()

Examples

# These examples are designed to show you how to highlight/brush a *single*# view. For examples of multiple linked views, see `demo(package = "plotly")` d <- highlight_key(txhousing, ~city)p <- ggplot(d, aes(date, median, group = city)) + geom_line()gg <- ggplotly(p, tooltip = "city") highlight(gg, dynamic = TRUE)# supply custom colors to the brush cols <- toRGB(RColorBrewer::brewer.pal(3, "Dark2"), 0.5)highlight(gg, on = "plotly_hover", color = cols, dynamic = TRUE)# Use attrs_selected() for complete control over the selection appearance# note any relevant colors you specify here should override the color arguments <- attrs_selected(  showlegend = TRUE,  mode = "lines+markers",  marker = list(symbol = "x"))highlight(layout(gg, showlegend = TRUE), selected = s)

Highlight/query data based on primary key

Description

This function simply creates an object of classcrosstalk::SharedData.The reason it exists is to make it easier to teach others how to leverageits functionality in plotly. It also makes it more discoverable if oneis already aware ofhighlight.

Usage

highlight_key(x, ...)

Arguments

Value

An object of classcrosstalk::SharedData

Author(s)

Carson Sievert

See Also

highlight

Hobbs data

Description

Description TBD.

Usage

hobbs

Format

A data frame with three variables:r,t,nms.

Embed a plotly grid as an iframe in a knitr doc

Description

Embed a plotly grid as an iframe in a knitr doc

Usage

knit_print.api_grid(x, options, ...)

Arguments

References

https://github.com/yihui/knitr/blob/master/vignettes/knit_print.Rmd

Embed a plotly grid as an iframe in a knitr doc

Description

Embed a plotly grid as an iframe in a knitr doc

Usage

knit_print.api_grid_local(x, options, ...)

Arguments

References

https://github.com/yihui/knitr/blob/master/vignettes/knit_print.Rmd

Embed a plotly figure as an iframe in a knitr doc

Description

Embed a plotly figure as an iframe in a knitr doc

Usage

knit_print.api_plot(x, options, ...)

Arguments

References

https://github.com/yihui/knitr/blob/master/vignettes/knit_print.Rmd

Retrieve the last plot to be modified or created.

Description

Retrieve the last plot to be modified or created.

Usage

last_plot()

See Also

ggplot2::last_plot()

Modify the layout of a plotly visualization

Description

Modify the layout of a plotly visualization

Usage

layout(p, ..., data = NULL)

Arguments

Author(s)

Carson Sievert

Mic data

Description

Description TBD.

Usage

mic

Format

A data frame with three variables:r,t,nms.

Objects exported from other packages

Description

These objects are imported from other packages. Follow the linksbelow to see their documentation.

magrittr

%>%

Usage

mutate(.data, ...)mutate_(.data, ..., .dots = list())transmute(.data, ...)transmute_(.data, ..., .dots = list())select(.data, ...)select_(.data, ..., .dots = list())rename(.data, ...)rename_(.data, ..., .dots = list())group_by(.data, ..., .add = FALSE, .drop = group_by_drop_default(.data))group_by_(.data, ..., .dots = list(), add = FALSE)groups(x)ungroup(x, ...)summarise(.data, ..., .by = NULL, .groups = NULL)summarise_(.data, ..., .dots = list())do(.data, ...)do_(.data, ..., .dots = list())arrange(.data, ..., .by_group = FALSE)arrange_(.data, ..., .dots = list())distinct(.data, ..., .keep_all = FALSE)distinct_(.data, ..., .dots, .keep_all = FALSE)slice(.data, ..., .by = NULL, .preserve = FALSE)slice_(.data, ..., .dots = list())filter(.data, ..., .by = NULL, .preserve = FALSE)filter_(.data, ..., .dots = list())

Plotly Offline

Description

Deprecated in version 2.0 (offline plots are now the default)

Usage

offline(p, height, width, out_dir, open_browser)

Arguments

Value

a plotly object of class "offline"

Author(s)

Carson Sievert

Static image exporting via orca

Description

This function is deprecated, usesave_image() instead.

Usage

orca(  p,  file = "plot.png",  format = tools::file_ext(file),  scale = NULL,  width = NULL,  height = NULL,  mathjax = FALSE,  parallel_limit = NULL,  verbose = FALSE,  debug = FALSE,  safe = FALSE,  more_args = NULL,  ...)orca_serve(  port = 5151,  mathjax = FALSE,  safe = FALSE,  request_limit = NULL,  keep_alive = TRUE,  window_max_number = NULL,  quiet = FALSE,  debug = FALSE,  more_args = NULL,  ...)

Arguments

Methods

Theorca_serve() function returns an object with two methods:

export(p, file = "plot.png", format = tools::file_ext(file), scale = NULL, width = NULL, height = NULL)

Export a static image of a plotly graph. Arguments found here are the same as those found inorca()

close()

Close down the orca server and kill the underlying node process.

Fields

Theorca_serve() function returns an object with two fields:

port

The port number that the server is listening to.

process

An R6 class for controlling and querying the underlying node process.

Author(s)

Carson Sievert

Examples

## Not run: # NOTE: in a headless environment, you may need to set `more_args="--enable-webgl"`# to export webgl correctlyp <- plot_ly(z = ~volcano) %>% add_surface()orca(p, "surface-plot.svg")#' # launch the serverserver <- orca_serve()# export as many graphs as you'd likeserver$export(qplot(1:10), "test1.pdf")server$export(plot_ly(x = 1:10, y = 1:10), "test2.pdf")# the underlying process is exposed as a field, so you# have full control over the external processserver$process$is_alive()# convenience method for closing down the serverserver$close()# remove the exported files from diskunlink("test1.pdf")unlink("test2.pdf")## End(Not run)

Use a partial bundle of plotly.js

Description

Leveraging plotly.js' partial bundles can lead to smaller file sizesand faster rendering. The full list of available bundles, and thetrace types that they support, are availablehere

Usage

partial_bundle(p, type = "auto", local = TRUE, minified = TRUE)

Arguments

Details

WARNING: use this function with caution when rendering multipleplotly graphs on a single website. That's because, if multiple plotly.jsbundles are used, the most recent bundle will override the other bundles.See the examples section for an example.

Author(s)

Carson Sievert

Examples

# ----------------------------------------------------------------------# This function is always safe to use when rendering a single # plotly graph. In this case, we get a 3x file reduction.# ----------------------------------------------------------------------## Not run: library(plotly)p <- plot_ly(x = 1:10, y = 1:10) %>% add_markers()save_widget <- function(p, f) {  owd <- setwd(dirname(f))  on.exit(setwd(owd))  htmlwidgets::saveWidget(p, f)  mb <- round(file.info(f)$size / 1e6, 3)  message("File is: ", mb," MB")}f1 <- tempfile(fileext = ".html")f2 <- tempfile(fileext = ".html")save_widget(p, f1)save_widget(partial_bundle(p), f2)# ----------------------------------------------------------------------# But, since plotly.js bundles override one another, # be careful when putting multiple graphs in a larger document!# Note how the surface (part of the gl3d bundle) renders, but the # heatmap (part of the cartesian bundle) doesn't...# ----------------------------------------------------------------------library(htmltools)p1 <- plot_ly(z = ~volcano) %>%   add_heatmap() %>%  partial_bundle()p2 <- plot_ly(z = ~volcano) %>%   add_surface() %>%  partial_bundle()browsable(tagList(p1, p2))## End(Not run)

Plot an interactive dendrogram

Description

This function takes advantage of nested key selections to implement aninteractive dendrogram. Selecting a node selects all the labels (i.e. leafs)under that node.

Usage

plot_dendro(d, set = "A", xmin = -50, height = 500, width = 500, ...)

Arguments

Author(s)

Carson Sievert

See Also

plot_ly(),plot_mapbox(),ggplotly()

Examples

## Not run: hc <- hclust(dist(USArrests), "ave")dend1 <- as.dendrogram(hc)plot_dendro(dend1, height = 600) %>%   hide_legend() %>%   highlight(persistent = TRUE, dynamic = TRUE)## End(Not run)

Initiate a plotly-geo object

Description

Use this function instead ofplot_ly() to initializea plotly-geo object. This enforces the entire plot so usethe scattergeo trace type, and enables higher level geometrieslikeadd_polygons() to work

Usage

plot_geo(data = data.frame(), ..., offline = FALSE)

Arguments

Author(s)

Carson Sievert

See Also

plot_ly(),plot_mapbox(),ggplotly()

Examples

map_data("world", "canada") %>%  group_by(group) %>%  plot_geo(x = ~long, y = ~lat) %>%  add_markers(size = I(1))

Initiate a plotly visualization

Description

This function maps R objects toplotly.js,an (MIT licensed) web-based interactive charting library. It providesabstractions for doing common things (e.g. mapping data values tofill colors (viacolor) or creatinganimations (viaframe)) and setssome different defaults to make the interface feel more 'R-like'(i.e., closer toplot() andggplot2::qplot()).

Usage

plot_ly(  data = data.frame(),  ...,  type = NULL,  name,  color,  colors = NULL,  alpha = NULL,  stroke,  strokes = NULL,  alpha_stroke = 1,  size,  sizes = c(10, 100),  span,  spans = c(1, 20),  symbol,  symbols = NULL,  linetype,  linetypes = NULL,  split,  frame,  width = NULL,  height = NULL,  source = "A")

Arguments

Details

Unlesstype is specified, this function just initiates a plotlyobject with 'global' attributes that are passed onto downstream uses ofadd_trace() (or similar). Aformula must always be used whenreferencing column name(s) indata (e.g.plot_ly(mtcars, x = ~wt)).Formulas are optional when supplying values directly, but they dohelp inform default axis/scale titles(e.g.,plot_ly(x = mtcars$wt) vsplot_ly(x = ~mtcars$wt))

Author(s)

Carson Sievert

References

https://plotly-r.com/overview.html

See Also

• For initializing a plotly-geo object:plot_geo()

• For initializing a plotly-mapbox object:plot_mapbox()

• For translating a ggplot2 object to a plotly object:ggplotly()

• For modifying any plotly object:layout(),add_trace(),style()

• For linked brushing:highlight()

• For arranging multiple plots:subplot(),crosstalk::bscols()

• For inspecting plotly objects:plotly_json()

• For quick, accurate, and searchable plotly.js reference:schema()

Examples

## Not run: # plot_ly() tries to create a sensible plot based on the information you # give it. If you don't provide a trace type, plot_ly() will infer one.plot_ly(economics, x = ~pop)plot_ly(economics, x = ~date, y = ~pop)# plot_ly() doesn't require data frame(s), which allows one to take # advantage of trace type(s) designed specifically for numeric matricesplot_ly(z = ~volcano)plot_ly(z = ~volcano, type = "surface")# plotly has a functional interface: every plotly function takes a plotly# object as it's first input argument and returns a modified plotly objectadd_lines(plot_ly(economics, x = ~date, y = ~unemploy/pop))# To make code more readable, plotly imports the pipe operator from magrittreconomics %>% plot_ly(x = ~date, y = ~unemploy/pop) %>% add_lines()# Attributes defined via plot_ly() set 'global' attributes that # are carried onto subsequent traces, but those may be over-writtenplot_ly(economics, x = ~date, color = I("black")) %>% add_lines(y = ~uempmed) %>% add_lines(y = ~psavert, color = I("red"))# Attributes are documented in the figure reference -> https://plotly.com/r/reference# You might notice plot_ly() has named arguments that aren't in this figure# reference. These arguments make it easier to map abstract data values to# visual attributes.p <- plot_ly(palmerpenguins::penguins, x = ~bill_length_mm, y = ~body_mass_g)add_markers(p, color = ~bill_depth_mm, size = ~bill_depth_mm)add_markers(p, color = ~species)add_markers(p, color = ~species, colors = "Set1")add_markers(p, symbol = ~species)add_paths(p, linetype = ~species)## End(Not run)

Initiate a plotly-mapbox object

Description

Use this function instead ofplot_ly() to initializea plotly-mapbox object. This enforces the entire plot so usethe scattermapbox trace type, and enables higher level geometrieslikeadd_polygons() to work

Usage

plot_mapbox(data = data.frame(), ...)

Arguments

Author(s)

Carson Sievert

See Also

plot_ly(),plot_geo(),ggplotly()

Examples

## Not run: plot_mapbox(res_mn)plot_mapbox(res_mn, color = ~INDRESNAME)map_data("world", "canada") %>%  group_by(group) %>%  plot_mapbox(x = ~long, y = ~lat) %>%  add_polygons() %>%  layout(    mapbox = list(      center = list(lat = ~median(lat), lon = ~median(long))    )  )## End(Not run)

Main interface to plotly

Description

This function is now deprecated. It used to provide a way to store plotlyaccount credentials, but that can now be done with environment variables.For more details and examples, seehttps://plotly.com/r/getting-started/.

If you're here looking for an intro/overview of the package, see thereadme

Usage

plotly(username, key)

Arguments

See Also

ggplotly(),plot_ly(),signup()

Shiny bindings for plotly

Description

Output and render functions for using plotly within Shinyapplications and interactive Rmd documents.

Usage

plotlyOutput(  outputId,  width = "100%",  height = "400px",  inline = FALSE,  reportTheme = TRUE,  fill = !inline)renderPlotly(expr, env = parent.frame(), quoted = FALSE)

Arguments

Modify a plotly object inside a shiny app

Description

Modify a plotly object inside a shiny app

Usage

plotlyProxy(  outputId,  session = shiny::getDefaultReactiveDomain(),  deferUntilFlush = TRUE)plotlyProxyInvoke(p, method, ...)

Arguments

Examples

if (require("shiny") && interactive()) {  plotly_example("shiny", "proxy_relayout")  plotly_example("shiny", "proxy_mapbox")}

Create a static image

Description

The images endpoint turns a plot (which may be given in multiple forms)into an image of the desired format.

Usage

plotly_IMAGE(  x,  width = 1000,  height = 500,  format = "png",  scale = 1,  out_file,  ...)

Arguments

Examples

## Not run: p <- plot_ly(x = 1:10)Png <- plotly_IMAGE(p, out_file = "plotly-test-image.png")Jpeg <- plotly_IMAGE(p, format = "jpeg", out_file = "plotly-test-image.jpeg")Svg <- plotly_IMAGE(p, format = "svg",  out_file = "plotly-test-image.svg")Pdf <- plotly_IMAGE(p, format = "pdf",  out_file = "plotly-test-image.pdf")## End(Not run)

Create/Modify plotly graphs

Description

Deprecated: seeapi_create().

Usage

plotly_POST(  x = last_plot(),  filename = NULL,  fileopt = "overwrite",  sharing = c("public", "private", "secret"),  ...)

Arguments

See Also

plot_ly(),signup()

'Build' (i.e., evaluate) a plotly object

Description

This generic function creates the list object sent to plotly.jsfor rendering. Using this function can be useful for overriding defaultsprovided byggplotly/plot_ly or for debugging renderingerrors.

Usage

plotly_build(p, registerFrames = TRUE)

Arguments

Examples

p <- plot_ly(economics, x = ~date, y = ~pce)# the unevaluated plotly objectstr(p)# the evaluated datastr(plotly_build(p)$x$data)

Obtain data associated with a plotly graph

Description

plotly_data() returns data associated witha plotly visualization (if there are multiple data frames, by default,it returns the most recent one).

Usage

plotly_data(p, id = p$x$cur_data)## S3 method for class 'plotly'groups(x)## S3 method for class 'plotly'ungroup(x, ...)## S3 method for class 'plotly'group_by(.data, ...)## S3 method for class 'plotly'mutate(.data, ...)## S3 method for class 'plotly'do(.data, ...)## S3 method for class 'plotly'summarise(.data, ...)## S3 method for class 'plotly'arrange(.data, ...)## S3 method for class 'plotly'select(.data, ...)## S3 method for class 'plotly'filter(.data, ...)## S3 method for class 'plotly'distinct(.data, ...)## S3 method for class 'plotly'slice(.data, ...)## S3 method for class 'plotly'rename(.data, ...)## S3 method for class 'plotly'transmute(.data, ...)## S3 method for class 'plotly'group_by_(.data, ...)## S3 method for class 'plotly'mutate_(.data, ...)## S3 method for class 'plotly'do_(.data, ...)## S3 method for class 'plotly'summarise_(.data, ...)## S3 method for class 'plotly'arrange_(.data, ...)## S3 method for class 'plotly'select_(.data, ...)## S3 method for class 'plotly'filter_(.data, ...)## S3 method for class 'plotly'distinct_(.data, ...)## S3 method for class 'plotly'slice_(.data, ...)## S3 method for class 'plotly'rename_(.data, ...)## S3 method for class 'plotly'transmute_(.data, ...)

Arguments

Examples

# use group_by() to define groups of visual markingsp <- txhousing %>%  group_by(city) %>%  plot_ly(x = ~date, y = ~sales)p# plotly objects preserve data groupings groups(p)plotly_data(p)# dplyr verbs operate on plotly objects as if they were data framesp <- economics %>%  plot_ly(x = ~date, y = ~unemploy / pop) %>%  add_lines() %>%  mutate(rate = unemploy / pop) %>%   filter(rate == max(rate))plotly_data(p)add_markers(p)layout(p, annotations = list(x = ~date, y = ~rate, text = "peak"))# use group_by() + do() + subplot() for trellis displays d <- group_by(mpg, drv)plots <- do(d, p = plot_ly(., x = ~cty, name = ~drv))subplot(plots[["p"]], nrows = 3, shareX = TRUE)# arrange displays by their meanmeans <- summarise(d, mn = mean(cty, na.rm = TRUE))means %>%  dplyr::left_join(plots) %>%  arrange(mn) %>%  subplot(nrows = NROW(.), shareX = TRUE)  # more dplyr verbs applied to plotly objectsp <- mtcars %>%  plot_ly(x = ~wt, y = ~mpg, name = "scatter trace") %>%  add_markers()p %>% slice(1) %>% plotly_data()p %>% slice(1) %>% add_markers(name = "first observation")p %>% filter(cyl == 4) %>% plotly_data()p %>% filter(cyl == 4) %>% add_markers(name = "four cylinders")

Create a complete empty plotly graph.

Description

Useful when used withsubplot()

Usage

plotly_empty(...)

Arguments

Run a plotly example(s)

Description

Provides a unified interface for running demos, shiny apps, and Rmd documentswhich are bundled with the package.

Usage

plotly_example(type = c("demo", "shiny", "rmd"), name, edit = TRUE, ...)

Arguments

Author(s)

Carson Sievert

Inspect JSON sent to plotly.js

Description

This function is useful for obtaining/viewing/debugging JSONsent to plotly.js.

Usage

plotly_json(p = last_plot(), jsonedit = interactive(), pretty = TRUE, ...)

Arguments

Examples

  plotly_json(plot_ly())plotly_json(plot_ly(), FALSE)

Print method for a 'generic' API response

Description

Print method for a 'generic' API response

Usage

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

Arguments

Print a plotly grid object

Description

Print a plotly grid object

Usage

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

Arguments

Print a plotly grid object

Description

Print a plotly grid object

Usage

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

Arguments

Print a plot on plotly's platform

Description

Print a plot on plotly's platform

Usage

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

Arguments

Print method for kaleido

Description

S3 method forkaleido().

Usage

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

Arguments

Add a range slider to the x-axis

Description

Add a range slider to the x-axis

Usage

rangeslider(p, start = NULL, end = NULL, ...)

Arguments

Author(s)

Carson Sievert

Examples

plot_ly(x = time(USAccDeaths), y = USAccDeaths) %>%   add_lines() %>%  rangeslider()  d <- tibble::tibble(  time = seq(as.Date("2016-01-01"), as.Date("2016-08-31"), by = "days"),  y = rnorm(seq_along(time)) ) plot_ly(d, x = ~time, y = ~y) %>%  add_lines() %>%  rangeslider(d$time[5], d$time[50])

Encode a raster object as a data URI

Description

Encode a raster object as a data URI, which is suitable foruse withlayout()images.This is especially convenient for embedding raster images on a plot ina self-contained fashion (i.e., so they don't depend on external URL links).

Usage

raster2uri(r, ...)

Arguments

Author(s)

Carson Sievert

References

https://plotly-r.com/embedding-images.html

Examples

# a red gradient (from ?as.raster)r <- as.raster(matrix(hcl(0, 80, seq(50, 80, 10)), nrow = 4, ncol = 5))plot(r)# embed the raster as an imageplot_ly(x = 1, y = 1) %>%   layout(    images = list(list(     source = raster2uri(r),     xref = "paper",      yref = "paper",      x = 0, y = 0,      sizex = 0.5, sizey = 0.5,      xanchor = "left", yanchor = "bottom"  )) )

Remove TypedArray polyfill

Description

By default, plotly.js' TypedArray polyfill is included as a dependency, soprinting "just works" in any context. Many users won't need this polyfill,so this function may be used to remove it and thus reduce the size of the page.

Usage

remove_typedarray_polyfill(p)

Arguments

Details

The polyfill seems to be only relevant for those rendering plotsvia phantomjs and RStudio on some Windows platforms.

Examples

## Not run: p1 <- plot_ly()p2 <- remove_typedarray_polyfill(p1)t1 <- tempfile(fileext = ".html")htmlwidgets::saveWidget(p1, t1)file.info(t1)$sizehtmlwidgets::saveWidget(p2, t1)file.info(t1)$size## End(Not run)

Minnesotan Indian Reservation Lands

Description

Minnesotan Indian Reservation Lands

Usage

res_mn

Format

An sf data frame with 13 features and 5 fields

References

https://www.dot.state.mn.us/maps/gdma/gis-data.html

Save plot as a static image

Description

Static image exporting viathe kaleido python package.kaleido() importskaleido into areticulated Python session and returns a⁠$transform()⁠method for converting R plots into static images.save_image() provides a convenience wrapper aroundkaleido()$transform().

Usage

save_image(p, file, ..., width = NULL, height = NULL, scale = NULL)kaleido(...)

Arguments

Value

Forsave_image(), the generatedfile. Forkaleido(), an environment that contains:

• transform(): a function to convert plots objects into static images. This function has the same signature (i.e., arguments) assave_image()

• shutdown(): a function for shutting down any currently running subprocessesthat were launched viatransform()

• scope: a reference to the underlyingkaleido.scopes.plotly.PlotlyScopepython object. Modify this object to customize the underlying Chromiumsubprocess and/or configure other details such as URL to plotly.js, MathJax, etc.

Installation

kaleido() requiresthe kaleido python package to be usable via thereticulate package. If you're starting from scratch, you installeveything you need with the following R code:

install.packages("reticulate")library(reticulate)use_python(install_python())py_install(c("kaleido", "plotly"))

Examples

## Not run:   # Save a single image  p <- plot_ly(x = 1:10)  tmp <- tempfile(fileext = ".png")  save_image(p, tmp)  file.show(tmp)  # Efficiently save multiple images  scope <- kaleido()  for (i in 1:5) {    scope$transform(p, tmp)  }  # Remove and garbage collect to remove   # R/Python objects and shutdown subprocesses  rm(scope); gc()## End(Not run)

Acquire (and optionally display) plotly's plot schema

Description

The schema contains valid attributes names, their value type,default values (if any), and min/max values (if applicable).

Usage

schema(jsonedit = interactive(), ...)

Arguments

Examples

s <- schema()# retrieve acceptable `layout.mapbox.style` valuesif (!is.na(Sys.getenv('MAPBOX_TOKEN', NA))) {  styles <- s$layout$layoutAttributes$mapbox$style$values  subplot(    plot_mapbox() %>% layout(mapbox = list(style = styles[3])),    plot_mapbox() %>% layout(mapbox = list(style = styles[5]))  )}

View colors already formatted by toRGB()

Description

Useful for viewing colors after they've been converted to plotly.js'color format – "rgba(255, 255, 255, 1)"

Usage

showRGB(x, ...)

Arguments

Author(s)

Carson Sievert

Examples

showRGB(toRGB(colors()), labels = FALSE)

Create a new plotly account.

Description

A sign up interface to plotly through the R Console.

Usage

signup(username, email, save = TRUE)

Arguments

Value

• api_key key to use with the api

• tmp_pw temporary password to access your plotly account

References

https://plotly.com/rest/

Examples

## Not run: # You need a plotly username and API key to communicate with the plotly API.# If you don't already have an API key, you can obtain one with a valid# username and email via signup().s <- signup('anna.lyst', 'anna.lyst@plot.ly')# If you already have a username and API key, please create the following# environment variables:Sys.setenv("plotly_username" = "me")Sys.setenv("plotly_api_key" = "mykey")# You can also change the default domain if you have a plotly server.Sys.setenv("plotly_domain" = "http://mydomain.com")# If you want to automatically load these environment variables when you# start R, you can put them inside your ~/.Rprofile # (see help(.Rprofile) for more details)## End(Not run)

Modify trace(s)

Description

Modify trace(s) of an existing plotly visualization. Useful when used inconjunction withget_figure().

Usage

style(p, ..., traces = NULL)

Arguments

Author(s)

Carson Sievert

See Also

api_download_plot()

Examples

# style() is especially useful in conjunction with ggplotly()# It allows you to leverage the underlying plotly.js library to change # the return result of ggplotly()(p <- ggplotly(qplot(data = mtcars, wt, mpg, geom = c("point", "smooth"))))# removes hoverinfo for the line/ribbon traces (use `plotly_json()` to verify!)style(p, hoverinfo = "none", traces = c(2, 3))# another example with plot_ly() instead of ggplotly()marker <- list(  color = "red",  line = list(    width = 20,     color = "black" ))(p <- plot_ly(x = 1:10, y = 1:10, marker = marker))# note how the entire (marker) object is replaced if a list is providedstyle(p, marker = list(line = list(color = "blue")))# similar to plotly.js, you can update a particular attribute like so # https://github.com/plotly/plotly.js/issues/1866#issuecomment-314115744style(p, marker.line.color = "blue") # this clobbers the previously supplied marker.line.colorstyle(p, marker.line = list(width = 2.5), marker.size = 10)

View multiple plots in a single view

Description

View multiple plots in a single view

Usage

subplot(  ...,  nrows = 1,  widths = NULL,  heights = NULL,  margin = 0.02,  shareX = FALSE,  shareY = FALSE,  titleX = shareX,  titleY = shareY,  which_layout = "merge")

Arguments

Value

A plotly object

Author(s)

Carson Sievert

Examples

# pass any number of plotly objects to subplot()p1 <- plot_ly(economics, x = ~date, y = ~uempmed)p2 <- plot_ly(economics, x = ~date, y = ~unemploy)subplot(p1, p2, p1, p2, nrows = 2, margin = 0.05)#'  # anchor multiple traces on the same legend entry p1 <- add_lines(p1, color = I("black"), name = "1st", legendgroup = "1st") p2 <- add_lines(p2, color = I("red"), name = "2nd", legendgroup = "2nd")  subplot(   p1, style(p1, showlegend = FALSE),   p2, style(p2, showlegend = FALSE),   nrows = 2, margin = 0.05 )# or pass a listeconomics_long %>%  split(.$variable) %>%  lapply(function(d) plot_ly(d, x = ~date, y = ~value)) %>%  subplot(nrows = NROW(.), shareX = TRUE)  # or pass a tibble with a list-column of plotly objectseconomics_long %>%  group_by(variable) %>%  do(p = plot_ly(., x = ~date, y = ~value)) %>%  subplot(nrows = NROW(.), shareX = TRUE)  # learn more at https://plotly.com/r/subplots/

Convert R colours to RGBA hexadecimal colour values

Description

Convert R colours to RGBA hexadecimal colour values

Usage

toRGB(x, alpha = 1)

Arguments

Value

hexadecimal colour value (if is.na(x), return "transparent" for compatibility with Plotly)

See Also

showRGB()

Examples

toRGB("steelblue") # [1] "rgba(70,130,180,1)"m <- list(  color = toRGB("red"),  line = list(    color = toRGB("black"),     width = 19  ))plot_ly(x = 1, y = 1, marker = m)

Convert trace types to WebGL

Description

Convert trace types to WebGL

Usage

toWebGL(p)

Arguments

Examples

# currently no bargl trace typetoWebGL(ggplot() + geom_bar(aes(1:10)))toWebGL(qplot(1:10, 1:10))

Convert a geom to a "basic" geom.

Description

This function makes it possible to convert ggplot2 geoms thatare not included with ggplot2 itself. Users shouldn't need to usethis function. It exists purely to allow other package authors to writetheir own conversion method(s).

Usage

to_basic(data, prestats_data, layout, params, p, ...)

Arguments

Wind data

Description

Description TBD.

Usage

wind

Format

A data frame with three variables:r,t,nms.