Bar Plots in ggplot2

How to make Bar Plots plots ggplot2 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.

geom_bar is designed to make it easy to create bar charts that show counts (or sums of weights).

Default bar plot

library(plotly)
g <- ggplot(mpg, aes(class))  
p <-  g + geom_bar()

ggplotly(p)

library(plotly)
g <- ggplot(mpg, aes(class))  
p <-  g + geom_bar(aes(weight = displ))

ggplotly(p)

Add colour

library(plotly)

dat <- data.frame(
    time = factor(c("Lunch","Dinner"), levels=c("Lunch","Dinner")),
    total_bill = c(14.89, 17.23)
)

p <- ggplot(data=dat, aes(x=time, y=total_bill, fill=time)) +
    geom_bar(stat="identity")

fig <- ggplotly(p)

fig

Setting custom colours:

library(plotly)

dat1 <- data.frame(
    sex = factor(c("Female","Female","Male","Male")),
    time = factor(c("Lunch","Dinner","Lunch","Dinner"), levels=c("Lunch","Dinner")),
    total_bill = c(13.53, 16.81, 16.24, 17.42)
)

p <- ggplot(data=dat1, aes(x=time, y=total_bill, fill=sex)) +
    geom_bar(stat="identity", position=position_dodge(), colour="black") +
    scale_fill_manual(values=c("#999999", "#E69F00"))

fig <- ggplotly(p)

fig

Stacking bar plots

Bar plots are automatically stacked when multiple bars are at the same location. The order of the fill is designed to match the legend.

library(plotly)
g <- ggplot(mpg, aes(class))  
p <-  g + geom_bar(aes(fill = drv))

ggplotly(p)

Showing mean

library(plotly)
df <- data.frame(trt = c("a", "b", "c"), outcome = c(2.3, 1.9, 3.2))  
p <-    
 ggplot(df, aes(trt, outcome)) +
  geom_col()

ggplotly(p)

geom_point() displays exactly the same information and doesn't require the y-axis to touch zero.

library(plotly)
df <- data.frame(trt = c("a", "b", "c"), outcome = c(2.3, 1.9, 3.2))  
p <-    
 ggplot(df, aes(trt, outcome)) +
  geom_point()

ggplotly(p)

You can also use geom_bar() with continuous data, in which case it will show counts at unique locations.

library(plotly)
df <- data.frame(x = rep(c(2.9, 3.1, 4.5), c(5, 10, 4)))  
p <-  ggplot(df, aes(x)) + geom_bar()

ggplotly(p)

Using binwidth

library(plotly)
df <- data.frame(x = rep(c(2.9, 3.1, 4.5), c(5, 10, 4)))  
p <-  ggplot(df, aes(x)) + geom_histogram(binwidth = 0.5)

ggplotly(p)

Error Bars

barplot with error bars

library(plotly)
library(dplyr)
set.seed(123)

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

df.summ <- df %>% group_by(cut) %>% summarize(Mean = mean(table), Min = min(table), Max = max(table))

p <- ggplot(df.summ, aes(x = cut, y = Mean, ymin = Min, ymax = Max, fill = cut)) + 
  geom_bar(stat = "identity") + 
  geom_errorbar() + 
  ggtitle("Bar chart with Error Bars")

ggplotly(p)

Ordered Bar Chart

ordering variable in geom_bar

library(plotly)
library(plyr)

dane<-data.frame(x=1:10,y=seq(-5,4),g=rep(c('A','B'),each=5))
dane$x<-as.factor(dane$x)

p <- ggplot(data=dane,aes(x=x,y=y,fill=g)) +
    geom_bar(stat="identity")

ggplotly(p)

Precentages

using geom_bar to show percentages

library(plotly)
set.seed(123)

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

p <- ggplot(df, aes(x = color)) + 
  geom_bar(aes(y = ..count../sum(..count..), fill = cut)) + 
  scale_fill_brewer(palette = "Set3") + 
  ylab("Percent") + 
  ggtitle("Show precentages in bar chart")

ggplotly(p)

Set manual colors using geom_bar to manually specify colors.

library(plotly)
library(RColorBrewer)
set.seed(123)

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

# Simply use fill = a vector of colors
p <- ggplot(df, aes(x = color)) +
  geom_bar(fill = brewer.pal(length(unique(df$color)), "Set3")) + 
  ylab("Count") + 
  ggtitle("Specify manual colors in a bar chart")

ggplotly(p)

Reordered Bar Chart

Re-ordering bars shown using geom_bar.

library(plotly)

df <- data.frame(x = as.factor(LETTERS[1:5]), 
                 y = sample(10:20, size = 5))

# First change factor levels
df$x <- factor(df$x, levels = c("C", "B", "A", "D", "E"))

# Plot
p <- ggplot(df, aes(x, y, fill = x)) + 
  geom_bar(stat = "identity") +
  ggtitle("Bar Chart with changed factor levels")

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)