Axes in ggplot2
How to work with Axes in 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.
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)