Creating and Updating Figures in R
Creating and Updating Figures with Plotly's R graphing library
New to Plotly?
Plotly is a free and open-source graphing library for R. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.
The plotly R package exists to create, manipulate and render graphical figures (i.e. charts, plots, maps and diagrams) represented by data structures also referred to as figures. The rendering process uses the Plotly.js JavaScript library under the hood although R developers using this module very rarely need to interact with the Javascript library directly, if ever. Figures can be represented in R either as lists or as instances of the Plotly Figures, and are serialized as text in JavaScript Object Notation (JSON) before being passed to Plotly.js.
Figures As Lists
Figures can be represented as Lists and displayed using plotly_build function. The fig list in the example below describes a figure. It contains a single bar trace and a title.
library(plotly)
fig = list(
data = list(
list(
x = c(1, 2, 3),
y = c(1, 3, 2),
type = 'bar'
)
),
layout = list(
title = 'A Figure Specified By R List',
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff')
)
)
# To display the figure defined by this list, use the plotly_build function
plotly_build(fig)
Plotly Figures
The plot_ly function provides an automatically-generated hierarchy of classes that may be used to represent figures.
plot_ly figures have several benefits compared to plain R Lists.
plot_lyfigures provide precise data validation. If you provide an invalid property name or an invalid property value as the key to a Plotly Figure, an exception will be raised with a helpful error message describing the problem. This is not the case if you use plain R lists to build your figures.plot_lyfigures contain descriptions of each valid property as R docstrings. You can use these docstrings in the development environment of your choice to learn about the available properties as an alternative to consulting the online Full Reference.- Properties of
plot_lyfigures can be accessed using both dictionary-style key lookup (e.g.fig$x). plot_lyfigures support higher-level convenience functions for making updates to already constructed figures (.layout(),.add_trace()etc).plot_lyfigures support attached rendering and exporting functions that automatically invoke the appropriate functions.
Below you can find an example of one way that the figure in the example above could be specified using a plot_ly figure instead of a list.
library(plotly)
fig <- plot_ly(x = c(1, 2, 3), y = c(1, 3, 2), type = 'bar')%>%
layout(title = 'A Plotly Figure',
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig
Converting plot_ly figures To Lists and JSON
plot_ly figures can be turned into their R List representation. You can also retrieve the JSON string representation of a plotly figure using the fig.to_JSON() method.
library(plotly)
library(jsonlite)
fig <- plot_ly(x = c(1, 2, 3), y = c(1, 3, 2), type = 'bar')
plotly_json <- function(p, ...) {
plotly:::to_JSON(plotly_build(p), ...)
}
jfig <- plotly_json(fig, pretty = TRUE)
cat("List Representation of a plot_ly figure:")
## List Representation of a plot_ly figure:
str(fig, max.level = 2)
## List of 8
## $ x :List of 6
## ..$ visdat :List of 1
## ..$ cur_data: chr "31194a89e971"
## ..$ attrs :List of 1
## ..$ layout :List of 3
## ..$ source : chr "A"
## ..$ config :List of 2
## ..- attr(*, "TOJSON_FUNC")=function (x, ...)
## $ width : NULL
## $ height : NULL
## $ sizingPolicy :List of 7
## ..$ defaultWidth : chr "100%"
## ..$ defaultHeight: num 400
## ..$ padding : num 0
## ..$ fill : NULL
## ..$ viewer :List of 6
## ..$ browser :List of 5
## ..$ knitr :List of 3
## $ dependencies :List of 5
## ..$ :List of 10
## .. ..- attr(*, "class")= chr "html_dependency"
## ..$ :List of 10
## .. ..- attr(*, "class")= chr "html_dependency"
## ..$ :List of 10
## .. ..- attr(*, "class")= chr "html_dependency"
## ..$ :List of 10
## .. ..- attr(*, "class")= chr "html_dependency"
## ..$ :List of 10
## .. ..- attr(*, "class")= chr "html_dependency"
## $ elementId : NULL
## $ preRenderHook:function (p, registerFrames = TRUE)
## $ jsHooks : list()
## - attr(*, "class")= chr [1:2] "plotly" "htmlwidget"
## - attr(*, "package")= chr "plotly"
cat("JSON Representation of a plot_ly figure:", jfig, sep = "\n\n")
## JSON Representation of a plot_ly figure:
##
## {
## "x": {
## "visdat": {
## "31194a89e971": ["function () ", "plotlyVisDat"]
## },
## "cur_data": "31194a89e971",
## "attrs": {
## "31194a89e971": {
## "x": [1, 2, 3],
## "y": [1, 3, 2],
## "alpha_stroke": 1,
## "sizes": [10, 100],
## "spans": [1, 20],
## "type": "bar"
## }
## },
## "layout": {
## "margin": {
## "b": 40,
## "l": 60,
## "t": 25,
## "r": 10
## },
## "xaxis": {
## "domain": [0, 1],
## "automargin": true,
## "title": []
## },
## "yaxis": {
## "domain": [0, 1],
## "automargin": true,
## "title": []
## },
## "hovermode": "closest",
## "showlegend": false
## },
## "source": "A",
## "config": {
## "modeBarButtonsToAdd": ["hoverclosest", "hovercompare"],
## "showSendToCloud": false
## },
## "data": [
## {
## "x": [1, 2, 3],
## "y": [1, 3, 2],
## "type": "bar",
## "marker": {
## "color": "rgba(31,119,180,1)",
## "line": {
## "color": "rgba(31,119,180,1)"
## }
## },
## "error_y": {
## "color": "rgba(31,119,180,1)"
## },
## "error_x": {
## "color": "rgba(31,119,180,1)"
## },
## "xaxis": "x",
## "yaxis": "y",
## "frame": null
## }
## ],
## "highlight": {
## "on": "plotly_click",
## "persistent": false,
## "dynamic": false,
## "selectize": false,
## "opacityDim": 0.20000000000000001,
## "selected": {
## "opacity": 1
## },
## "debounce": 0
## },
## "shinyEvents": ["plotly_hover", "plotly_click", "plotly_selected", "plotly_relayout", "plotly_brushed", "plotly_brushing", "plotly_clickannotation", "plotly_doubleclick", "plotly_deselect", "plotly_afterplot", "plotly_sunburstclick"],
## "base_url": "https://plot.ly"
## },
## "width": null,
## "height": null,
## "sizingPolicy": {
## "defaultWidth": "100%",
## "defaultHeight": 400,
## "padding": 0,
## "fill": null,
## "viewer": {
## "defaultWidth": null,
## "defaultHeight": null,
## "padding": null,
## "fill": true,
## "suppress": false,
## "paneHeight": null
## },
## "browser": {
## "defaultWidth": null,
## "defaultHeight": null,
## "padding": null,
## "fill": true,
## "external": false
## },
## "knitr": {
## "defaultWidth": null,
## "defaultHeight": null,
## "figure": true
## }
## },
## "dependencies": [
## {
## "name": "typedarray",
## "version": "0.1",
## "src": {
## "file": "htmlwidgets/lib/typedarray"
## },
## "meta": null,
## "script": "typedarray.min.js",
## "stylesheet": null,
## "head": null,
## "attachment": null,
## "package": "plotly",
## "all_files": false
## },
## {
## "name": "jquery",
## "version": "3.5.1",
## "src": {
## "file": "lib/jquery"
## },
## "meta": null,
## "script": "jquery.min.js",
## "stylesheet": null,
## "head": null,
## "attachment": null,
## "package": "crosstalk",
## "all_files": true
## },
## {
## "name": "crosstalk",
## "version": "1.2.1",
## "src": {
## "file": "www"
## },
## "meta": null,
## "script": "js/crosstalk.min.js",
## "stylesheet": "css/crosstalk.min.css",
## "head": null,
## "attachment": null,
## "package": "crosstalk",
## "all_files": true
## },
## {
## "name": "plotly-htmlwidgets-css",
## "version": "2.11.1",
## "src": {
## "file": "htmlwidgets/lib/plotlyjs"
## },
## "meta": null,
## "script": null,
## "stylesheet": "plotly-htmlwidgets.css",
## "head": null,
## "attachment": null,
## "package": "plotly",
## "all_files": false
## },
## {
## "name": "plotly-main",
## "version": "2.11.1",
## "src": {
## "file": "htmlwidgets/lib/plotlyjs"
## },
## "meta": null,
## "script": "plotly-latest.min.js",
## "stylesheet": null,
## "head": null,
## "attachment": null,
## "package": "plotly",
## "all_files": false
## }
## ],
## "elementId": null,
## "preRenderHook": ["function (p, registerFrames = TRUE) ", "{", " UseMethod(\"plotly_build\")", "}"],
## "jsHooks": []
## }
Representing Figures in Dash
Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Learn about how to install Dash for R at https://dashr.plot.ly/installation.
Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument.
library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)
library(plotly)
fig <- plot_ly() %>%
add_lines(x = c("a","b","c"), y = c(1,3,2))%>%
layout(title="sample figure")
app <- Dash$new()
app$layout(
htmlDiv(
list(
dccGraph(id = 'graph', figure=fig),
htmlPre(
id='structure',
style = list(border = 'thin lightgrey solid',
overflowY = 'scroll',
height = '275px')
)
)
)
)
app$callback(
output(id = 'structure', property='children'),
params=list(input(id='graph', property='figure')),
function(fig_json) {
plotly_json <- function(p, ...) {
plotly:::to_JSON(plotly_build(p), ...)
}
jfig <- plotly_json(fig, pretty = TRUE)
return(jfig)
})
#app$run_server()
Use app$run_server() to run the dash app.
Creating Figures
This section summarizes several ways to create new plot_ly figures with the plotly graphing library.
Plotly Scatter Plot
library(plotly)
data(iris)
fig <- plot_ly(data = iris, x = ~Sepal.Width, y = ~Sepal.Length, color = ~Species,
type = "scatter", mode = "markers")%>%
layout(title="A Plotly Figure", legend=list(title=list(text='species')),
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig
Make Subplots
The subplots() function produces a plot_ly figure that is preconfigured with a grid of subplots that traces can be added to.
library(plotly)
fig1 <- plot_ly(y = c(4, 2, 1), type = "scatter", mode = "lines") %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig2 <- plot_ly(y = c(2, 1, 3), type = "bar") %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig <- subplot(fig1, fig2)
fig
Updating Figures
Regardless of how a plot_ly figure was constructed, it can be updated by adding additional traces to it and modifying its properties.
Adding Traces
New traces can be added to a plot_ly figure using the add_trace() method. This method accepts a plot_ly figure trace and adds it to the figure. This allows you to start with an empty figure, and add traces to it sequentially.
library(plotly)
fig <- plot_ly()%>%
add_trace(x = c(1, 2, 3), y = c(1, 3, 2), type = 'bar') %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig
library(plotly)
data(iris)
fig <- plot_ly()%>%
add_trace(data = iris, x = ~Sepal.Width, y = ~Sepal.Length, color = ~Species,
type = "scatter", mode = "markers")%>%
layout(title="Using The add_trace() method With A Plotly Figure", legend=list(title=list(text='species')),
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))%>%
add_trace(x = c(2, 4), y = c(4, 8), type = "scatter", mode = "lines", line = list(color = 'grey')
, showlegend = FALSE)
fig
Updating Figure Layouts
plot_ly figures support an style() method that may be used to update multiple nested properties of a figure's layout.
Here is an example of updating the font size of a figure's title using style().
library(plotly)
fig <- plot_ly(x = c(1, 2, 3), y = c(1, 3, 2), type = 'bar')%>%
layout(title = list(text ='Using layout() With Plotly Figures', font = list(size = 17)),
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig
Updating Traces
plot_ly figures support an style() method that may be used to update multiple nested properties of one or more of a figure's traces.
To show some examples, we will start with a figure that contains bar and scatter traces across two subplots.
library(plotly)
fig1 <- plot_ly(x = c(0,1, 2), y = c(2, 1, 3), type = 'bar', name = 'b', color = I("red")) %>%
add_trace(x = c(0,1, 2), y = c(4, 2, 3.5), type = 'scatter', mode = 'markers', name = 'a',
marker = list(size = 20, color = 'rgb(51, 204, 51)')) %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig2 <- plot_ly(x = c(0,1, 2), y = c(1, 3, 2), type = 'bar', name = 'c', color = I("#33cc33")) %>%
add_trace(x = c(0,1, 2), y = c(2, 3.5, 4), type = 'scatter', mode = 'markers', name = 'd',
marker = list(size = 20, color = 'rgb(255, 0, 0)')) %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig <- subplot(fig1, fig2)
fig
Note that both scatter and bar traces have a marker.color property to control their coloring. Here is an example of using style() to modify the color of all traces.
library(plotly)
fig1 <- plot_ly(x = c(0,1, 2), y = c(2, 1, 3), type = 'bar', name = 'b', color = I("red")) %>%
add_trace(x = c(0,1, 2), y = c(4, 2, 3.5), type = 'scatter', mode = 'markers', name = 'a',
marker = list(size = 20, color = 'rgb(51, 204, 51)')) %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig1 <- style(fig1, marker = list(size = 20, color = "blue"))
fig2 <- plot_ly(x = c(0,1, 2), y = c(1, 3, 2), type = 'bar', name = 'c', color = I("#33cc33")) %>%
add_trace(x = c(0,1, 2), y = c(2, 3.5, 4), type = 'scatter', mode = 'markers', name = 'd',
marker = list(size = 20, color = 'rgb(255, 0, 0)')) %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig2 <- style(fig1, marker = list(size = 20, color = "blue"))
fig <- subplot(fig1, fig2)
fig
The style() method supports a traces argument to control which traces should be updated. Only traces given will be updated. Here is an example of using a traces to only update the color of the bar traces.
library(plotly)
fig1 <- plot_ly(x = c(0,1, 2), y = c(2, 1, 3), type = 'bar', name = 'b', color = I("red")) %>%
add_trace(x = c(0,1, 2), y = c(4, 2, 3.5), type = 'scatter', mode = 'markers', name = 'a',
marker = list(size = 20, color = 'rgb(51, 204, 51)')) %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig1 <- style(fig1, marker = list(color = "blue"), traces = c(1))
fig2 <- plot_ly(x = c(0,1, 2), y = c(1, 3, 2), type = 'bar', name = 'c', color = I("#33cc33")) %>%
add_trace(x = c(0,1, 2), y = c(2, 3.5, 4), type = 'scatter', mode = 'markers', name = 'd',
marker = list(size = 20, color = 'rgb(255, 80, 80)')) %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig2 <- style(fig2, marker = list(color = "blue"), traces = c(1))
fig <- subplot(fig1, fig2)
fig
Overwrite Existing Properties When Using Update Methods
style() will overwrite the prior value of existing properties, with the provided value.
In the example below, the red color of markers is overwritten when updating marker in style().
library(plotly)
fig <- plot_ly()%>%
add_trace(x = c(1, 2, 3), y = c(1, 3, 2), type = 'bar', marker = list(color = 'red')) %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
style(fig, marker = list(opacity = 0.4))
Updating Figure Axes
Plotly figures support layout method that may be used to update multiple nested properties of one or more of a figure's axes. Here is an example of using layout to disable the vertical grid lines across all subplots in a figure produced by Plotly.
library(plotly)
data(iris)
fig <- iris%>%
group_by(Species) %>%
do(p=plot_ly(., x = ~Sepal.Width, y = ~Sepal.Length, color = ~Species, type = "scatter", mode = "markers")) %>%
subplot(nrows = 1, shareX = TRUE, shareY = TRUE)
fig <- fig%>%
layout(title = "Updating x axis in a Plotly Figure", legend=list(title=list(text='species')),
xaxis = list(showgrid = F),
xaxis2 = list(showgrid = F),
xaxis3 = list(showgrid = F),
annotations = list(
list(
x = 0.16,
y = 0.95,
font = list(size = 10),
text = "species=setosa",
xref = "paper",
yref = "paper",
xanchor = "center",
yanchor = "bottom",
showarrow = FALSE
),
list(
x = 0.5,
y = 0.95,
font = list(size = 10),
text = "species=versicolor",
xref = "paper",
yref = "paper",
xanchor = "center",
yanchor = "bottom",
showarrow = FALSE
),
list(
x = 0.85,
y = 0.95,
font = list(size = 10),
text = "species=virginica",
xref = "paper",
yref = "paper",
xanchor = "center",
yanchor = "bottom",
showarrow = FALSE
)),
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig
Other Update Methods
Figures created with the plotly graphing library also support:
- the
images()method in order to update background layout images, annotations()in order to update annotations,- and
shapes()in order to update shapes.
Chaining Figure Operations
All of the figure update operations described above are methods that return a reference to the figure being modified. This makes it possible to chain multiple figure modification operations together into a single expression.
Here is an example of a chained expression that:
- sets the title font size using
layout.title.font.size, - disables vertical grid lines using
layout.xaxis, - updates the size and color of the markers and bar using
style(), - and then displaying the figure.
library(plotly)
t <- list(size = 15)
fig <- plot_ly(x = c(0,1, 2), y = c(2, 1, 3), type = 'bar', name = 'b', color = I("red")) %>%
add_trace(x = c(0,1, 2), y = c(4, 2, 3.5), type = 'scatter', mode = 'markers', name = 'a',
marker = list(size = 10, color = 'rgb(51, 204, 51)'))
#updates the size and color of the markers and bar
fig <- style(fig, marker = list(size = 20, color = "blue"))
fig <- style(fig, marker = list(color = "yellow"), traces = c(1))
fig <- style(fig, marker = list(color = "yellow", line = list(color = 'rgb(8,48,107)',
width = 1.5)), traces = c(1))
fig <- fig %>%
layout(title = list(text = "Chaining Multiple Figure Operations With A Plotly Figure",
#setting the title font size
font = t),
#disables vertical grid lines
xaxis = list(showgrid = F),
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
#displaying the figure
fig
Property Assignment
Trace and layout properties can be updated using property assignment syntax. Here is an example of setting the figure title using property assignment.
library(plotly)
fig <- plot_ly()%>%
add_trace(x = c(1, 2, 3), y = c(1, 3, 2), type = 'bar')%>%
layout(title = 'Using Property Assignment Syntax With A Plotly Figure',
plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig <- style(fig,marker = list(line = list(color = 'lightblue', width = 0)))
fig
And here is an example of updating the bar outline using property assignment.
library(plotly)
fig <- plot_ly()%>%
add_trace(x = c(1, 2, 3), y = c(1, 3, 2), type = 'bar') %>%
layout(plot_bgcolor='#e5ecf6',
xaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'),
yaxis = list(
zerolinecolor = '#ffff',
zerolinewidth = 2,
gridcolor = 'ffff'))
fig <- style(fig,marker = list(line = list(color = 'lightblue', width = 0)))
fig$x$data[[1]]$marker$line$color <- 'black'
fig$x$data[[1]]$marker$line$width <- 4
fig
What About Dash?
Dash for R is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.
Learn about how to install Dash for R at https://dashr.plot.ly/installation.
Everywhere in this page that you see fig, you can display the same figure in a Dash for R application by passing it to the figure argument of the Graph component from the built-in dashCoreComponents package like this:
library(plotly)
fig <- plot_ly()
# fig <- fig %>% add_trace( ... )
# fig <- fig %>% layout( ... )
library(dash)
library(dashCoreComponents)
library(dashHtmlComponents)
app <- Dash$new()
app$layout(
htmlDiv(
list(
dccGraph(figure=fig)
)
)
)
app$run_server(debug=TRUE, dev_tools_hot_reload=FALSE)