Continuous Error Bands in ggplot2

How to make Continuous Error Bands in ggplot2 with Plotly.

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Default error bar plot

To create continuous errorbar plot we need to use df.summary. To add lower and upper error bars, use ymin = len-sd and ymax = len+sd.

library(plotly)
library(ggplot2)
library(dplyr)

df <- ToothGrowth
df$dose <- as.factor(df$dose)
df.summary <- df %>%
  group_by(dose) %>%
  summarise(
    sd = sd(len, na.rm = TRUE),
    len = mean(len)
  )

p <- ggplot(df.summary, aes(dose, len)) +
      geom_line(aes(group = 1)) +
      geom_errorbar( aes(ymin = len-sd, ymax = len+sd),width = 0.2) +
      geom_point(size = 2)

ggplotly(p)

Add jitter

library(plotly)
library(ggplot2)
library(dplyr)

df <- ToothGrowth
df$dose <- as.factor(df$dose)
df.summary <- df %>%
  group_by(dose) %>%
  summarise(
    sd = sd(len, na.rm = TRUE),
    len = mean(len)
  )

p <- ggplot(df, aes(dose, len)) +
  geom_jitter( position = position_jitter(0.2), color = "darkgray") + 
  geom_line(aes(group = 1), data = df.summary) +
  geom_errorbar(
    aes(ymin = len-sd, ymax = len+sd),
    data = df.summary, width = 0.2) +
  geom_point(data = df.summary, size = 2)

ggplotly(p)

Create groups

To make sure groups do not overlay, use position_dodge()

library(plotly)
library(ggplot2)
library(dplyr)

df <- ToothGrowth
df$dose <- as.factor(df$dose)
df.summary <- df %>%
  group_by(dose, supp) %>%
  summarise(
    sd = sd(len),
    len = mean(len)
  )

p <- ggplot(df.summary, aes(dose, len)) +
        geom_errorbar(
          aes(ymin = len-sd, ymax = len+sd, color = supp),
          position = position_dodge(0.3), width = 0.2
          )+
        geom_point(aes(color = supp), position = position_dodge(0.3)) +
        scale_color_manual(values = c("#00AFBB", "#E7B800")) 

ggplotly(p)

Add line with geom_line(), remember to apply position_dodge() to make sure groups do not overlay each other.

library(plotly)
library(ggplot2)
library(dplyr)

df <- ToothGrowth
df$dose <- as.factor(df$dose)
df.summary <- df %>%
  group_by(dose, supp) %>%
  summarise(
    sd = sd(len),
    len = mean(len)
  )

p <- ggplot(df.summary, aes(dose, len)) +
      geom_line(aes(linetype = supp, group = supp), position = position_dodge(0.3))+
      geom_errorbar(
        aes(ymin = len-sd, ymax = len+sd, color = supp),
        position = position_dodge(0.3), width = 0.2
        )+
      geom_point(aes(color = supp), position = position_dodge(0.3)) +
      scale_color_manual(values = c("#00AFBB", "#E7B800")) 


ggplotly(p)

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)