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Filled Area Plots in R

How to make a filled area plot in R. An area chart displays a solid color between the traces of a graph.


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Basic Filled Area Plot

To make an area plot with interior filling set fill to "tozeroy" in the call for the second trace. For more informations and options about the fill option checkout https://plotly.com/r/reference/#scatter-fill

library(plotly)

density <- density(diamonds$carat)

fig <- plot_ly(x = ~density$x, y = ~density$y, type = 'scatter', mode = 'lines', fill = 'tozeroy')
fig <- fig %>% layout(xaxis = list(title = 'Carat'),
         yaxis = list(title = 'Density'))

fig

Filled Area Plot with Multiple Traces

To make a filled area plot set fill to "tozeroy".

library(plotly)

diamonds1 <- diamonds[which(diamonds$cut == "Fair"),]
density1 <- density(diamonds1$carat)

diamonds2 <- diamonds[which(diamonds$cut == "Ideal"),]
density2 <- density(diamonds2$carat)

fig <- plot_ly(x = ~density1$x, y = ~density1$y, type = 'scatter', mode = 'lines', name = 'Fair cut', fill = 'tozeroy')
fig <- fig %>% add_trace(x = ~density2$x, y = ~density2$y, name = 'Ideal cut', fill = 'tozeroy')
fig <- fig %>% layout(xaxis = list(title = 'Carat'),
         yaxis = list(title = 'Density'))

fig

Selecting Hover Points

library(plotly)

fig <- plot_ly()
fig <- fig %>% add_trace(
    x = c(0,0.5,1,1.5,2),
    y = c(0,1,2,1,0),
    type = 'scatter',
    fill = 'toself',
    fillcolor = '#ab63fa',
    hoveron = 'points+fills',
    marker = list(
      color = '#ab63fa'
    ),
    line = list(
      color = '#ab63fa'
    ),
    text = "Points + Fills",
    hoverinfo = 'text'
  )
fig <- fig %>% add_trace(
    x = c(3,3.5,4,4.5,5),
    y = c(0,1,2,1,0),
    type = 'scatter',
    fill = 'toself',
    fillcolor = '#e763fa',
    hoveron = 'points',
    marker = list(
      color = '#e763fa'
    ),
    line = list(
      color = '#e763fa'
    ),
    text = "Points only",
    hoverinfo = 'text'
  )
fig <- fig %>% layout(
    title = "hover on <i>points</i> or <i>fill</i>",
    xaxis = list(
      range = c(0,5.2)
    ),
    yaxis = list(
      range = c(0,3)
    )
  )

fig

Custom Colors

library(plotly)

diamonds1 <- diamonds[which(diamonds$cut == "Fair"),]
density1 <- density(diamonds1$carat)

diamonds2 <- diamonds[which(diamonds$cut == "Ideal"),]
density2 <- density(diamonds2$carat)

fig <- plot_ly(x = ~density1$x, y = ~density1$y, type = 'scatter', mode = 'lines', name = 'Fair cut', fill = 'tozeroy',
        fillcolor = 'rgba(168, 216, 234, 0.5)',
        line = list(width = 0.5))
fig <- fig %>% add_trace(x = ~density2$x, y = ~density2$y, name = 'Ideal cut', fill = 'tozeroy',
            fillcolor = 'rgba(255, 212, 96, 0.5)')
fig <- fig %>% layout(xaxis = list(title = 'Carat'),
         yaxis = list(title = 'Density'))

fig

Area Plot without Lines

To make an area plot without lines set mode to "none".

library(plotly)

diamonds1 <- diamonds[which(diamonds$cut == "Fair"),]
density1 <- density(diamonds1$carat)

diamonds2 <- diamonds[which(diamonds$cut == "Ideal"),]
density2 <- density(diamonds2$carat)

fig <- plot_ly(x = ~density1$x, y = ~density1$y, type = 'scatter', mode = 'none', name = 'Fair cut', fill = 'tozeroy',
        fillcolor = 'rgba(168, 216, 234, 0.5)')
fig <- fig %>% add_trace(x = ~density2$x, y = ~density2$y, name = 'Ideal cut', fill = 'tozeroy',
            fillcolor = 'rgba(255, 212, 96, 0.5)')
fig <- fig %>% layout(xaxis = list(title = 'Carat'),
         yaxis = list(title = 'Density'))

fig

Interior Filling for Area Chart

To make an area plot with interior filling set fill to "tonexty" in the call for the second trace. For more informations and options about the fill option checkout https://plotly.com/r/reference/#scatter-fill

library(plotly)

month <- c('January', 'February', 'March', 'April', 'May', 'June', 'July',
           'August', 'September', 'October', 'November', 'December')
high_2014 <- c(28.8, 28.5, 37.0, 56.8, 69.7, 79.7, 78.5, 77.8, 74.1, 62.6, 45.3, 39.9)
low_2014 <- c(12.7, 14.3, 18.6, 35.5, 49.9, 58.0, 60.0, 58.6, 51.7, 45.2, 32.2, 29.1)
data <- data.frame(month, high_2014, low_2014)
data$average_2014 <- rowMeans(data[,c("high_2014", "low_2014")])

#The default order will be alphabetized unless specified as below:
data$month <- factor(data$month, levels = data[["month"]])

fig <- plot_ly(data, x = ~month, y = ~high_2014, type = 'scatter', mode = 'lines',
        line = list(color = 'rgba(0,100,80,1)'),
        showlegend = FALSE, name = 'High 2014')
fig <- fig %>% add_trace(y = ~low_2014, type = 'scatter', mode = 'lines',
            fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(0,100,80,1)'),
            showlegend = FALSE, name = 'Low 2014')
fig <- fig %>% layout(title = "High and Low Temperatures in New York",
         paper_bgcolor='rgb(255,255,255)', plot_bgcolor='rgb(229,229,229)',
         xaxis = list(title = "Months",
                      gridcolor = 'rgb(255,255,255)',
                      showgrid = TRUE,
                      showline = FALSE,
                      showticklabels = TRUE,
                      tickcolor = 'rgb(127,127,127)',
                      ticks = 'outside',
                      zeroline = FALSE),
         yaxis = list(title = "Temperature (degrees F)",
                      gridcolor = 'rgb(255,255,255)',
                      showgrid = TRUE,
                      showline = FALSE,
                      showticklabels = TRUE,
                      tickcolor = 'rgb(127,127,127)',
                      ticks = 'outside',
                      zeroline = FALSE))

fig

Stacked Area Chart with Original Values

library(plotly)

data <- t(USPersonalExpenditure)
data <- data.frame("year"=rownames(data), data)

fig <- plot_ly(data, x = ~year, y = ~Food.and.Tobacco, name = 'Food and Tobacco', type = 'scatter', mode = 'none', stackgroup = 'one', fillcolor = '#F5FF8D')
fig <- fig %>% add_trace(y = ~Household.Operation, name = 'Household Operation', fillcolor = '#50CB86')
fig <- fig %>% add_trace(y = ~Medical.and.Health, name = 'Medical and Health', fillcolor = '#4C74C9')
fig <- fig %>% add_trace(y = ~Personal.Care, name = 'Personal Care', fillcolor = '#700961')
fig <- fig %>% add_trace(y = ~Private.Education, name = 'Private Education', fillcolor = '#312F44')
fig <- fig %>% layout(title = 'United States Personal Expenditures by Categories',
         xaxis = list(title = "",
                      showgrid = FALSE),
         yaxis = list(title = "Expenditures (in billions of dollars)",
                      showgrid = FALSE))

fig

Stacked Area Chart with Cumulative Values

library(plotly)

data <- t(USPersonalExpenditure)
data <- data.frame("year"=rownames(data), data)

fig <- plot_ly(data, x = ~year, y = ~Food.and.Tobacco, name = 'Food and Tobacco', type = 'scatter', mode = 'none', stackgroup = 'one', groupnorm = 'percent', fillcolor = '#F5FF8D')
fig <- fig %>% add_trace(y = ~Household.Operation, name = 'Household Operation', fillcolor = '#50CB86')
fig <- fig %>% add_trace(y = ~Medical.and.Health, name = 'Medical and Health', fillcolor = '#4C74C9')
fig <- fig %>% add_trace(y = ~Personal.Care, name = 'Personal Care', fillcolor = '#700961')
fig <- fig %>% add_trace(y = ~Private.Education, name = 'Private Education', fillcolor = '#312F44')
fig <- fig %>% layout(title = 'United States Personal Expenditures by Categories',
         xaxis = list(title = "",
                      showgrid = FALSE),
         yaxis = list(title = "Proportion from the Total Expenditures",
                      showgrid = FALSE,
                      ticksuffix = '%'))

fig

Reference

See https://plotly.com/r/reference/#area 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)