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Images in R

How to add images to charts as background images or logos in R


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.

Add a Background Image

In this page we explain how to add static, non-interactive images as background, logo or annotation images to a figure. For exploring image data in interactive charts, see the tutorial on displaying image data.

A background image can be added to the layout of a figure by setting the images parameter of plot_ly$layout. The source attribute of a layout$images can be the URL of an image, or an image object.

library('plotly')
# Create figure
plot_ly(x = c(0, 0.5, 1, 2, 2.2), y = c(1.23, 2.5, 0.42, 3, 1), type = 'scatter', mode = 'lines+markers') %>% 
  # Add trace
  layout(
    images = list(
      list(
        # Add images
        source =  "https://images.plot.ly/language-icons/api-home/r-logo.png?raw=true",
        xref = "x",
        yref = "y",
        x = 0.2,
        y = 3,
        sizex = 2,
        sizey = 2,
        sizing = "stretch",
        opacity = 0.4,
        layer = "below"
      )
    )
  )%>%
  layout(plot_bgcolor='#e5ecf6',  
          xaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff'),  
          yaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff')  
          )

Add a Logo

See more examples of adding logos to charts!

library(plotly) 
x= c("-35.3", "-15.9", "-15.8", "-15.6", "-11.1", 
     "-9.6", "-9.2", "-3.5", "-1.9", "-0.9", 
     "1.0", "1.4", "1.7", "2.0", "2.8", "6.2", 
     "8.1", "8.5", "8.5", "8.6", "11.4", "12.5", 
     "13.3", "13.7", "14.4", "17.5", "17.7", 
     "18.9", "25.1", "28.9", "41.4") 

y = c("Designers, musicians, artists, etc.", 
      "Secretaries and administrative assistants", 
      "Waiters and servers", "Archivists, curators, and librarians", 
      "Sales and related", "Childcare workers, home car workers, etc.", 
      "Food preparation occupations", "Janitors, maids, etc.", 
      "Healthcare technicians, assistants. and aides", 
      "Counselors, social and religious workers", 
      "Physical, life and social scientists", "Construction", 
      "Factory assembly workers", "Machinists, repairmen, etc.", 
      "Media and communications workers", "Teachers", 
      "Mechanics, repairmen, etc.", "Financial analysts and advisers", 
      "Farming, fishing and forestry workers", 
      "Truck drivers, heavy equipment operator, etc.", "Accountants and auditors", 
      "Human resources, management analysts, etc.", "Managers", 
      "Lawyers and judges", "Engineers, architects and surveyors", 
      "Nurses", "Legal support workers", 
      "Computer programmers and system admin.", "Police officers and firefighters", 
      "Chief executives", "Doctors, dentists and surgeons") 

df = data.frame(x,y,stringsAsFactors = FALSE) 

m = list(r=20, l=300, b=75, t=125) 

fig <- plot_ly(data = df, x = ~x, y = ~y, type = 'bar', orientation = 'h', 
               marker = list(color = 'rgb(253, 240, 54)',  
               line = list(width = 2, color = 'rgb(0, 0, 0)'))) %>%  
  layout( xaxis = list(title = ""), yaxis = list(title = ""),
    images = list(  
      list(  
        source =  "https://raw.githubusercontent.com/cldougl/plot_images/add_r_img/vox.png",  
        xref = "paper",  
        yref = "paper",  
        x = 1.05,  
        y = 1.05,  
        sizex = 0.2,  
        sizey = 0.2,  
        xanchor="right",  
        yanchor="bottom" 
      )  
    ) ) 

fig <- fig %>% layout(autosize = F, margin = m, 
                      title=(paste("Moving Up, Moving Down<br>" , 
                               "<i>Percentile change in income between childhood and adulthood</i>")), 
                      hovermode="x" 
                      ) %>%
  layout(plot_bgcolor='#e5ecf6',  
          xaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff'),  
          yaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff')  
          )
fig

Zoom on Static Images

library(plotly) 

#Constants 
img_width = 1600 
img_height = 900 
scale_factor = 0.5 


# Add invisible scatter trace. 
# This trace is added to help the autoresize logic work. 
fig <- plot_ly(width=img_width * scale_factor, 
               height=img_height * scale_factor 
) %>% 
  add_trace( x= c(0, img_width * scale_factor), 
             y= c(0, img_height * scale_factor), 
             type = 'scatter',  mode = 'markers', alpha = 0) 

# Configure axes 
xconfig <- list( 
  title = "", 
  zeroline = FALSE, 
  showline = FALSE, 
  showticklabels = FALSE, 
  showgrid = FALSE, 
  range = c(0, img_width * scale_factor) 
) 

yconfig <- list( 
  title = "", 
  zeroline = FALSE, 
  showline = FALSE, 
  showticklabels = FALSE, 
  showgrid = FALSE, 
  range = c(0, img_height * scale_factor), 
  scaleanchor="x" 
) 

fig <- fig %>% layout(xaxis = xconfig, yaxis = yconfig) 

# Add image 

fig <- fig %>% layout( 
  images = list(  
    list(  
      source =  "https://raw.githubusercontent.com/michaelbabyn/plot_data/master/bridge.jpg",  
      x=0, 
      sizex=img_width * scale_factor, 
      y=img_height * scale_factor, 
      sizey=img_height * scale_factor, 
      xref="x", 
      yref="y", 
      opacity=1.0, 
      layer="below", 
      sizing="stretch" 
    )  
  )) 

# Configure other layout 

m = list(r=0, l=0, b=0, t=0) 
fig <- fig %>% layout(margin = m) %>%
  layout(plot_bgcolor='#e5ecf6',  
          xaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff'),  
          yaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff')  
          )
fig

Annotating layout image with shapes

It can be useful to add shapes to a layout image, for highlighting an object, drawing bounding boxes as part of a machine learning training set, or identifying seeds for a segmentation algorithm.

In order to enable shape drawing, you need to

  • define a dragmode corresponding to a drawing tool ('drawline','drawopenpath', 'drawclosedpath', 'drawcircle', or 'drawrect')

  • add modebar buttons corresponding to the drawing tools you wish to use.

The style of new shapes is specified by the newshape layout attribute. Shapes can be selected and modified after they have been drawn. More details and examples are given in the tutorial on shapes.

Drawing or modifying a shape triggers a relayout event, which can be captured by a callback inside a Dash application.

library(plotly) 

#Constants 
img_width = 1600 
img_height = 900 
scale_factor = 0.5 

fig <- plot_ly() %>% 
  add_trace( x= c(0, img_width ), 
             y= c(0, img_height ), 
             type = 'scatter',  mode = 'markers', alpha = 0)%>% 
  layout(images = list(  
    list(  
      source =  "https://raw.githubusercontent.com/michaelbabyn/plot_data/master/bridge.jpg",  
      x=0, 
      sizex=img_width, 
      y=0, 
      sizey=img_height, 
      xref="x", 
      yref="y", 
      opacity=1.0, 
      layer="below" 
    )  
  )) 

xconfig <- list( 
  title = "", 
  showgrid = FALSE, 
  range = c(0, img_width) 
) 

yconfig <- list( 
  title = "", 
  showgrid = FALSE, 
  range = c(img_height,0), 
  scaleanchor="x" 
) 

fig <- fig %>% layout(xaxis = xconfig, yaxis = yconfig) 

#Add lineshape 
fig <- fig %>%  
  add_segments(x = 650, xend = 1080, y = 380, yend = 180, line = list( color = 'cyan'),inherit = FALSE, showlegend = FALSE) 

fig <- fig %>% layout(dragmode='drawrect', 
                      newshape=list(line = list(color='cyan')), 
                      title = 'Drag to add annotations - use modebar to change drawing tool') 

#Add modebar buttons 
fig <- fig %>%  
  config(modeBarButtonsToAdd = c('drawline', 
                                 'drawopenpath', 
                                 'drawclosedpath', 
                                 'drawcircle', 
                                 'drawrect', 
                                 'eraseshape')) %>%
  layout(plot_bgcolor='#e5ecf6',  
          xaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff'),  
          yaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff')  
          )

fig

Images Placed Relative to Axes

Using xref='x domain' or yref='y domain', images can be placed relative to axes. As an example, the following shows how to put an image in the top corner of a subplot (try panning and zooming the resulting figure):

library(plotly) 

db1 <- iris[iris$Species == "setosa", ] 
db2 <- iris[iris$Species == "versicolor", ] 
db3 <- iris[iris$Species == "virginica", ] 

fig1 <- plot_ly(data = db1, x = ~Sepal.Length, y = ~Sepal.Width, type = 'scatter', mode = 'markers') %>% 
  layout(xaxis = list(range = c(4,8))) 
# add images
fig1 <- fig1 %>% layout( 
  images = list(  
    list(  
      # sources of images
      source =  "https://upload.wikimedia.org/wikipedia/commons/thumb/f/fe/Iris_setosa_var._setosa_%282595031014%29.jpg/360px-Iris_setosa_var._setosa_%282595031014%29.jpg",  
      row=1, 
      col=1, 
      source=1, 
      xref="x domain", 
      yref="y domain", 
      x=1, 
      y=1, 
      xanchor="right", 
      yanchor="top", 
      sizex=0.2, 
      sizey=0.2 
    )  
  )) 

fig2 <- plot_ly(data = db2, x = ~Sepal.Length, y = ~Sepal.Width, type = 'scatter', mode = 'markers') %>% 
  layout(xaxis = list(range = c(4,8))) 
# add images
fig2 <- fig2 %>% layout( 
  images = list(  
    list(  
      # sources of images
      source =  "https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Iris_versicolor_quebec_1.jpg/320px-Iris_versicolor_quebec_1.jpg",  
      row=1, 
      col=2, 
      source=2, 
      xref="x domain", 
      yref="y domain", 
      x=2.05, 
      y=1, 
      xanchor="right", 
      yanchor="top", 
      sizex=0.2, 
      sizey=0.2 
    )  
  )) 

fig3 <- plot_ly(data = db3, x = ~Sepal.Length, y = ~Sepal.Width, type = 'scatter', mode = 'markers') %>% 
  layout(xaxis = list(range = c(4,8), title = 'Sepal..Length')) 
# add images  
fig3 <- fig3 %>% layout( 
  images = list(  
    list(  
      # sources of images
      source =  "https://upload.wikimedia.org/wikipedia/commons/thumb/f/f8/Iris_virginica_2.jpg/480px-Iris_virginica_2.jpg",  
      row=1, 
      col=3, 
      source=2, 
      xref="x domain", 
      yref="y domain", 
      x=3.15, 
      y=1, 
      xanchor="right", 
      yanchor="top", 
      sizex=0.2, 
      sizey=0.2 
    )  
  )) 

fig <- subplot(fig1, fig2, fig3, shareY = TRUE, shareX = TRUE) %>% layout(showlegend = FALSE) 

annotations = list(  
  list(  
    x = 0.2,   
    y = 1.0,   
    font = list(size = 10),   
    text = "species=setosa",   
    xref = "paper",   
    yref = "paper",   
    xanchor = "center",   
    yanchor = "bottom",   
    showarrow = FALSE  
  ),   
  list(  
    x = 0.8,   
    y = 1,   
    font = list(size = 10),   
    text = "species=versicolor",   
    xref = "paper",   
    yref = "paper",   
    xanchor = "center",   
    yanchor = "bottom",   
    showarrow = FALSE  
  ),   
  list(  
    x = 0.5,   
    y = 1,   
    font = list(size = 10),   
    text = "species=virginica",   
    xref = "paper",   
    yref = "paper",   
    xanchor = "center",   
    yanchor = "bottom",   
    showarrow = FALSE  
  )) 

fig <- fig %>%
  layout(annotations = annotations)  %>%layout(plot_bgcolor='#e5ecf6',  
          xaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff'),  
          yaxis = list(  
            zerolinecolor = '#ffff',  
            zerolinewidth = 2,  
            gridcolor = 'ffff')  
          )
options(warn = -1) 
fig

Reference

See https://plotly.com/r/reference/layout/images/ for more information and chart attribute options!

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)