Axes in ggplot2

How to work with Axes in ggplot2 with Plotly.

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Default plot

library(plotly)
library(ggplot2)

p <- ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  scale_x_continuous(name = "Displacement")

ggplotly(p)

Changing axis limits

library(plotly)
library(ggplot2)

p <- ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  scale_x_continuous(limits = c(0, 600))

ggplotly(p)

Changing axis ticks

The breaks argument is used to specify where the ticks appear. It takes a numeric vector equal to the length of the number of ticks.

library(plotly)
library(ggplot2)

p <- ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  scale_x_continuous(breaks = c(150, 300, 450))

ggplotly(p)

Changing tick labels

You can change the tick labels using the labels argument. In the below example, we use words instead of numbers. When adding labels, we need to ensure that the length of the breaks and labels are same.

library(plotly)
library(ggplot2)

p <- ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  scale_x_continuous(breaks = c(150, 300, 450),
  labels = c('One Hundred Fifty', 'Three Hundred', 'Four Hundred Fifity'))

ggplotly(p)

Changing position of labels

library(ggplot2)

p <- ggplot(mtcars) +
  geom_point(aes(disp, mpg)) +
  scale_x_continuous(position = 'top')

ggplotly(p)

Y-axis example

Everything above using scale_x_continuous() can be used in the same way for y axis with scale_y_continuous().

library(plotly)
library(ggplot2)

p <- ggplot(mtcars) + geom_point(aes(disp, mpg)) +
  scale_y_continuous(name = "Miles Per Gallon", limits = c(0, 45),
                     breaks = c(0, 15, 30, 45), position = 'right',
                     labels = c('zero', 'fifteen', 'thirty', 'fourtyfive'))

ggplotly(p)

Discrete axis labels

library(plotly)
library(ggplot2)

p <- ggplot(mtcars) +
  geom_bar(aes(factor(cyl))) +
  scale_x_discrete(labels = c("4" = "Four", "6" = "Six", "8" = "Eight"))

ggplotly(p)

Remove Axis Labels

library(plotly)
library(ggplot2)

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

p <- ggplot(df, aes(carat, price, color = cut)) +
  geom_point() +
  theme(axis.text = element_blank())

 ggplotly(p)

Vertical Text Orientation

library(plotly)
library(ggplot2)

lab <- paste("Vertical Label", c(1, 2, 3, 4, 5))

ds <- data.frame(x = sample(lab, size = 1000, replace = T),
                 y = sample(LETTERS[1:5], size = 1000, replace = T))

p <- ggplot(ds, aes(x = x, fill = y)) +
  geom_bar() +
  theme(axis.text.x = element_text(angle = 90)) +
  ggtitle("Vertical Axis Labels")

ggplotly(p)

Angled Text Orientation

library(plotly)
library(ggplot2)

lab <- paste("Angle Label", c(1, 2, 3, 4, 5))

ds <- data.frame(x = sample(lab, size = 1000, replace = T),
                 y = sample(LETTERS[1:5], size = 1000, replace = T))

p <- ggplot(ds, aes(x = x, fill = y)) +
  geom_bar() +
  theme(axis.text.x = element_text(angle = 45)) +
  ggtitle("Angle Axis Labels")

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)