Box Plots in ggplot2

How to make Box Plots in ggplot2 with Plotly.


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Basic Boxplot

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating)) + geom_boxplot()

ggplotly(p)

Colored Boxplot

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating, fill=cond)) + geom_boxplot()

ggplotly(p)

Flipped Boxplot

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating, fill=cond)) + geom_boxplot() +
    guides(fill=FALSE) + coord_flip()

ggplotly(p)

Boxplot w/ Stats

library(plotly)

set.seed(1234)
dat <- data.frame(cond = factor(rep(c("A","B"), each=200)), rating = c(rnorm(200),rnorm(200, mean=.8)))

p <- ggplot(dat, aes(x=cond, y=rating)) + geom_boxplot() +
    stat_summary(fun=mean, geom="point", shape=5, size=4)

ggplotly(p)

Boxplot Facets

library(plyr)
library(reshape2)
library(plotly)

set.seed(1234)
x<- rnorm(100)
y.1<-rnorm(100)
y.2<-rnorm(100)
y.3<-rnorm(100)
y.4<-rnorm(100)

df<- (as.data.frame(cbind(x,y.1,y.2,y.3,y.4)))

dfmelt<-melt(df, measure.vars = 2:5)

p <- ggplot(dfmelt, aes(x=factor(round_any(x,0.5)), y=value,fill=variable))+
    geom_boxplot()+
    facet_grid(.~variable)+
    labs(x="X (binned)")+
    theme(axis.text.x=element_text(angle=-90, vjust=0.4,hjust=1))

ggplotly(p)
-2.5-2-1.5-1-0.500.511.522.5-202-2.5-2-1.5-1-0.500.511.522.5-2.5-2-1.5-1-0.500.511.522.5-2.5-2-1.5-1-0.500.511.522.5
variabley.1y.2y.3y.4X (binned)valuey.1y.2y.3y.4

Time Series Facets

library(foreign)
library(MASS)
library(Hmisc)
library(reshape2)
library(plotly)

dat <- read.dta("https://stats.idre.ucla.edu/stat/data/ologit.dta")
invisible(lapply(dat[, c("apply", "pared", "public")], table))
invisible(ftable(xtabs(~ public + apply + pared, data = dat)))

p <- ggplot(dat, aes(x = apply, y = gpa)) +
    geom_boxplot(size = .75) +
    facet_grid(pared ~ public, margins = TRUE)

ggplotly(p)
2.02.53.03.54.02.02.53.03.54.0unlikelysomewhat likelyvery likely2.02.53.03.54.0unlikelysomewhat likelyvery likelyunlikelysomewhat likelyvery likely
applygpa01(all)01(all)

Outliers

library(plotly)
set.seed(123)

df <- diamonds[sample(1:nrow(diamonds), size = 1000),]

p <- ggplot(df, aes(cut, price, fill = cut)) + 
  geom_boxplot(outlier.shape = NA) + 
  ggtitle("Ignore outliers in ggplot2")

# Need to modify the plotly object and make outlier points have opacity equal to 0
fig <- plotly_build(p)

fig$data <- lapply(fig$data, FUN = function(x){
  x$marker = list(opacity = 0)
  return(x)
})

fig
FairGoodVery GoodPremiumIdeal050001000015000
cutFairGoodVery GoodPremiumIdealIgnore outliers in ggplot2cutprice

Linewidth

library(plotly)
set.seed(123)

df <- diamonds[sample(1:nrow(diamonds), size = 1000),]

p <- ggplot(df, aes(cut, price, fill = cut)) + 
  geom_boxplot(size = 1) + 
  ggtitle("Adjust line width of boxplot in ggplot2")

# Need to modify the plotly object to make sure line width is larger than default
fig <- plotly_build(p)

fig$data <- lapply(fig$data, FUN = function(x){
  x$line = list(width = 10)
  return(x)
})

fig
FairGoodVery GoodPremiumIdeal050001000015000
cutFairGoodVery GoodPremiumIdealAdjust line width of boxplot in ggplot2cutprice

Whiskers

library(plotly)
set.seed(123)

df <- diamonds[sample(1:nrow(diamonds), size = 1000),]

# This is how it needs to be done in ggplot
p <- ggplot(df, aes(color, price)) +
  stat_boxplot(geom ='errorbar') + 
  geom_boxplot()+
  ggtitle("Add horizontal lines to whiskers using ggplot2")

# Note that plotly will automatically add horozontal lines to the whiskers
p <- ggplot(df, aes(cut, price, fill = cut)) +
  geom_boxplot()+
  ggtitle("Add horizontal lines to whiskers using ggplot2")

ggplotly(p)
FairGoodVery GoodPremiumIdeal050001000015000
cutFairGoodVery GoodPremiumIdealAdd horizontal lines to whiskers using ggplot2cutprice

These example were inspired by Cookbook for R.

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)