Distplots in R

How to make interactive Distplots in R with Plotly.


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.

Combined statistical representations with histogram

Several representations of statistical distributions are available in plotly, such as histograms, violin plots, box plots (see the complete list here). It is also possible to combine several representations in the same plot.

library(plotly)
library(ggplot2)
library(reshape2)
data(tips)

p <- ggplot(tips, aes(x=total_bill, weight = tip, color=sex, fill = sex)) +
  geom_histogram(binwidth=2.5) +
  ylab("sum of tip") + 
  geom_rug(sides="t", length = unit(0.3, "cm"))
fig <- ggplotly(p)
fig
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sexFemaleMaletotal_billsum of tip

Combined statistical representations with distplot figure factory

The distplot figure factory displays a combination of statistical representations of numerical data, such as histogram, kernel density estimation or normal curve, and rug plot.

Basic Distplot

A histogram, a kde plot and a rug plot are displayed.

library(ggplot2)  
library(plotly)

set.seed(1)    
hist_data <- data.frame(rnorm(1000, mean = 0, sd = 1))   
colnames(hist_data) = c('x')  
gg <- ggplot(hist_data,aes(x = x, color = 'density')) +  
  geom_histogram(aes(y = ..density..), bins = 7,  fill = '#67B7D1', alpha = 0.5) +  
  geom_density(color = '#67B7D1') +  
  geom_rug(color = '#67B7D1') + 
  ylab("") + 
  xlab("")  + theme(legend.title=element_blank()) +
  scale_color_manual(values = c('density' = '#67B7D1'))


ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff')) 
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Plot Multiple Datasets

library(ggplot2)    
library(plotly) 
set.seed(1)    
x1 <- rnorm(200, mean = 0, sd = 1) - 2  
x2 <- rnorm(200, mean = 0, sd = 1)   
x3 <- rnorm(200, mean = 0, sd = 1) + 2  
x4 <- rnorm(200, mean = 0, sd = 1) +4  
group_labels = c('Group 1', 'Group 2', 'Group 3', 'Group 4')  

df1 <- data.frame(x1, group_labels[1])  
colnames(df1) <- c('x', 'Group') 
df2 <- data.frame(x2, group_labels[2]) 
colnames(df2) <- c('x', 'Group') 
df3 <- data.frame(x3, group_labels[3]) 
colnames(df3) <- c('x', 'Group') 
df4 <- data.frame(x4, group_labels[4]) 
colnames(df4) <- c('x', 'Group') 
df <- rbind(df1,df2,df3,df4) 
colnames(df) <- c('x', 'Group') 

gg <- ggplot(data = df ) +  
  geom_histogram(aes(x=x, y = ..density.., fill=Group),bins = 29, alpha = 0.7) + 
 geom_density(aes(x=x, color=Group)) + geom_rug(aes(x=x, color=Group))+ 
  ylab("") + 
  xlab("")


ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff')) 
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-5.0-2.50.02.55.00.00.20.40.6
Group(Group 1,1)(Group 2,1)(Group 3,1)(Group 4,1)TimeValue A

Use Multiple Bin Sizes

Different bin sizes are used for the different datasets with the bin_size argument.

library(ggplot2) 
library(plotly)

set.seed(1)  
x1 <- rnorm(1000, mean = 0, sd = 1) - 2
x2 <- rnorm(1000, mean = 0, sd = 1) 
x3 <- rnorm(1000, mean = 0, sd = 1) + 2
x4 <- rnorm(1000, mean = 0, sd = 1) +4
group_labels = c('Group 1', 'Group 2', 'Group 3', 'Group 4')

df = data.frame(x1,x2,x3,x4, group_labels)

gg <- ggplot(df,aes() ) + 
  geom_histogram(aes(x = x1, y = ..density.., fill = '#67B7D1'), alpha = 0.7, bins = 29) +
  geom_histogram(aes(x = x2, y = ..density.., fill = '#ff8080'), alpha = 0.7, bins = 20) +
  geom_histogram(aes(x = x3, y = ..density.., fill = '#ff99dd'), alpha = 0.7, bins = 10) +
  geom_histogram(aes(x = x4, y = ..density.., fill = '#ff9900'), alpha = 0.7, bins = 5) +
  geom_density(aes(x = x1),color = '#67B7D1') + 
  geom_density(aes(x = x2),color = '#ff8080') +
  geom_density(aes(x = x3),color = '#ff99dd') +
  geom_density(aes(x = x4),color = '#ff9900') +
  geom_rug(aes(x = x1),color = '#67B7D1') + 
  geom_rug(aes(x = x2),color = '#ff8080') +
  geom_rug(aes(x = x3),color = '#ff99dd') +
  geom_rug(aes(x = x4),color = '#ff9900') + 
  theme(legend.title=element_blank()) +
  scale_fill_identity(labels = c('Group 1', 'Group 2', 'Group 3', 'Group 4'),
                      guide = "legend")  +
  labs(x = '',
       y = '')

ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff')) 
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-8-40480.00.10.20.30.4
fill#67B7D1#ff8080#ff99dd#ff9900TimeValue A

Plot Normal Curve

library(ggplot2)    
library(plotly) 
set.seed(1)    
x1 <- rnorm(200, mean = 0, sd = 1)  
x2 <- rnorm(200, mean = 0, sd = 1) + 2 

group_labels = c('Group 1', 'Group 2')  

df1 <- data.frame(x1, group_labels[1])  
colnames(df1) <- c('x', 'Group') 
df2 <- data.frame(x2, group_labels[2]) 
colnames(df2) <- c('x', 'Group') 

df <- rbind(df1,df2) 
colnames(df) <- c('x', 'Group') 

gg <- ggplot(data = df , aes(x=x)) +  
  geom_histogram(aes(y = ..density.., fill=Group),bins = 30, alpha = 0.7)+ 
  geom_density(aes(color=Group))+  
  geom_rug(aes(color=Group))+ 
  labs(x = '',  
       y = '',  
       title = 'Distplot with Normal Distribution')  

ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff')) 
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-2.50.02.55.00.00.20.40.6
Group(Group 1,1)(Group 2,1)Distplot with Normal DistributionTimeValue A

Plot Only Curve and Rug

library(ggplot2)    
library(plotly) 
set.seed(1)    
x1 <- rnorm(200, mean = 0, sd = 1) - 1
x2 <- rnorm(200, mean = 0, sd = 1) 
x3 <- rnorm(200, mean = 0, sd = 1) + 1

group_labels = c('Group 1', 'Group 2', 'Group 3')  

df1 <- data.frame(x1, group_labels[1])  
colnames(df1) <- c('x', 'Group') 
df2 <- data.frame(x2, group_labels[2]) 
colnames(df2) <- c('x', 'Group') 
df3 <- data.frame(x3, group_labels[3]) 
colnames(df3) <- c('x', 'Group') 

df <- rbind(df1,df2,df3) 
colnames(df) <- c('x', 'Group') 

gg <- ggplot(data = df ) +  
 geom_density(aes(x=x, color=Group)) + geom_rug(aes(x=x, color=Group)) + 
  ylab("") + 
  xlab("")

ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),
         title = 'Curve and Rug Plot') 
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-20240.00.10.20.30.4
GroupGroup 1Group 2Group 3Curve and Rug PlotTimeValue A

Plot Only Hist and Rug

library(ggplot2)    
library(plotly) 
set.seed(1)    
x1 <- rnorm(200, mean = 0, sd = 1) - 1
x2 <- rnorm(200, mean = 0, sd = 1) 
x3 <- rnorm(200, mean = 0, sd = 1) + 1

group_labels = c('Group 1', 'Group 2', 'Group 3')  

df1 <- data.frame(x1, group_labels[1])  
colnames(df1) <- c('x', 'Group') 
df2 <- data.frame(x2, group_labels[2]) 
colnames(df2) <- c('x', 'Group') 
df3 <- data.frame(x3, group_labels[3]) 
colnames(df3) <- c('x', 'Group') 

df <- rbind(df1,df2,df3) 
colnames(df) <- c('x', 'Group') 

gg <- ggplot(data = df ) +  
  geom_histogram(aes(x=x, y = ..density.., fill=Group),bins = 29, alpha = 0.7) + 
  geom_rug(aes(x=x, color=Group)) + 
  ylab("") + 
  xlab("")


ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),
         title = 'Hist and Rug Plot') 
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-20240.000.250.500.751.00
Group(Group 1,1)(Group 2,1)(Group 3,1)Hist and Rug PlotTimeValue A

Plot Hist and Rug with Different Bin Sizes

library(ggplot2)  
library(plotly)

set.seed(1) 
x1 <- rnorm(1000, mean = 0, sd = 1) - 2
x2 <- rnorm(1000, mean = 0, sd = 1) 
x3 <- rnorm(1000, mean = 0, sd = 1) + 2

df <- data.frame(x1, x2, x3)

gg <- ggplot(df,aes() ) + 
  geom_histogram(aes(x = x1, y = ..density.., fill = '#67B7D1'), alpha = 0.7, bins = 5) +
  geom_histogram(aes(x = x2, y = ..density.., fill = '#ff8080'), alpha = 0.7, bins = 17) +
  geom_histogram(aes(x = x3, y = ..density.., fill = '#ff99dd'), alpha = 0.7, bins = 29) +
  geom_rug(aes(x = x1),color = '#67B7D1') + 
  geom_rug(aes(x = x2),color = '#ff8080') +
  geom_rug(aes(x = x3),color = '#ff99dd') +
  labs(x = '',
       y = '',
       title = 'Hist and Rug Plot') +
  theme(legend.title=element_blank()) +
  scale_fill_identity(labels = c('Group 1', 'Group 2', 'Group 3'),
                      guide = "legend") 


ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),
         title = 'Hist and Rug Plot') 
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-4040.00.10.20.30.4
fill#67B7D1#ff8080#ff99ddHist and Rug PlotTimeValue A

Plot Only Hist and Curve

library(ggplot2)    
library(plotly) 
set.seed(1)    
x1 <- rnorm(200, mean = 0, sd = 1) - 2  
x2 <- rnorm(200, mean = 0, sd = 1)   
x3 <- rnorm(200, mean = 0, sd = 1) + 2  
x4 <- rnorm(200, mean = 0, sd = 1) +4  
group_labels = c('Group 1', 'Group 2', 'Group 3', 'Group 4')  

df1 <- data.frame(x1, group_labels[1])  
colnames(df1) <- c('x', 'Group') 
df2 <- data.frame(x2, group_labels[2]) 
colnames(df2) <- c('x', 'Group') 
df3 <- data.frame(x3, group_labels[3]) 
colnames(df3) <- c('x', 'Group') 
df4 <- data.frame(x4, group_labels[4]) 
colnames(df4) <- c('x', 'Group') 
df <- rbind(df1,df2,df3,df4) 
colnames(df) <- c('x', 'Group') 

gg <- ggplot(data = df ) +  
  geom_histogram(aes(x=x, y = ..density.., fill=Group),bins = 29, alpha = 0.7) + 
 geom_density(aes(x=x, color=Group)) + 
  ylab("") + 
  xlab("")


ggplotly(gg)%>% 
  layout(plot_bgcolor='#e5ecf6',   
             xaxis = list(   
               title='Time', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),   
             yaxis = list(   
               title='Value A', 
               zerolinecolor = '#ffff',   
               zerolinewidth = 2,   
               gridcolor = 'ffff'),
         title = 'Hist and Curve Plot') 
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-5.0-2.50.02.55.00.00.20.40.6
Group(Group 1,1)(Group 2,1)(Group 3,1)(Group 4,1)Hist and Curve PlotTimeValue A

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)
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