ggplot2 axis scales and transformations


This R tutorial describes how to modify x and y axis limits (minimum and maximum values) using ggplot2 package. Axis transformations (log scale, sqrt, …) and date axis are also covered in this article.

Prepare the data

ToothGrowth data is used in the following examples :

# Convert dose column dose from a numeric to a factor variable
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
head(ToothGrowth)
##    len supp dose
## 1  4.2   VC  0.5
## 2 11.5   VC  0.5
## 3  7.3   VC  0.5
## 4  5.8   VC  0.5
## 5  6.4   VC  0.5
## 6 10.0   VC  0.5

Make sure that dose column is converted as a factor using the above R script.

Example of plots

library(ggplot2)
# Box plot 
bp <- ggplot(ToothGrowth, aes(x=dose, y=len)) + geom_boxplot()
bp
# scatter plot
sp<-ggplot(cars, aes(x = speed, y = dist)) + geom_point()
sp

Change x and y axis limits

There are different functions to set axis limits :

  • xlim() and ylim()
  • expand_limits()
  • scale_x_continuous() and scale_y_continuous()

Use xlim() and ylim() functions

To change the range of a continuous axis, the functions xlim() and ylim() can be used as follow :

# x axis limits
sp + xlim(min, max)
# y axis limits
sp + ylim(min, max)

min and max are the minimum and the maximum values of each axis.

# Box plot : change y axis range
bp + ylim(0,50)
# scatter plots : change x and y limits
sp + xlim(5, 40)+ylim(0, 150)

Use expand_limts() function

Note that, the function expand_limits() can be used to :

  • quickly set the intercept of x and y axes at (0,0)
  • change the limits of x and y axes
# set the intercept of x and y axis at (0,0)
sp + expand_limits(x=0, y=0)
# change the axis limits
sp + expand_limits(x=c(0,30), y=c(0, 150))

Use scale_xx() functions

It is also possible to use the functions scale_x_continuous() and scale_y_continuous() to change x and y axis limits, respectively.

The simplified formats of the functions are :

scale_x_continuous(name, breaks, labels, limits, trans)
scale_y_continuous(name, breaks, labels, limits, trans)

  • name : x or y axis labels
  • breaks : to control the breaks in the guide (axis ticks, grid lines, …). Among the possible values, there are :
    • NULL : hide all breaks
    • waiver() : the default break computation
    • a character or numeric vector specifying the breaks to display
  • labels : labels of axis tick marks. Allowed values are :
    • NULL for no labels
    • waiver() for the default labels
    • character vector to be used for break labels
  • limits : a numeric vector specifying x or y axis limits (min, max)
  • trans for axis transformations. Possible values are “log2”, “log10”, …


The functions scale_x_continuous() and scale_y_continuous() can be used as follow :

# Change x and y axis labels, and limits
sp + scale_x_continuous(name="Speed of cars", limits=c(0, 30)) +
  scale_y_continuous(name="Stopping distance", limits=c(0, 150))

Axis transformations

Log and sqrt transformations

Built in functions for axis transformations are :

  • scale_x_log10(), scale_y_log10() : for log10 transformation
  • scale_x_sqrt(), scale_y_sqrt() : for sqrt transformation
  • scale_x_reverse(), scale_y_reverse() : to reverse coordinates
  • coord_trans(x =“log10”, y=“log10”) : possible values for x and y are “log2”, “log10”, “sqrt”, …
  • scale_x_continuous(trans=‘log2’), scale_y_continuous(trans=‘log2’) : another allowed value for the argument trans is ‘log10’

These functions can be used as follow :

# Default scatter plot
sp <- ggplot(cars, aes(x = speed, y = dist)) + geom_point()
sp
# Log transformation using scale_xx()
# possible values for trans : 'log2', 'log10','sqrt'
sp + scale_x_continuous(trans='log2') +
  scale_y_continuous(trans='log2')
# Sqrt transformation
sp + scale_y_sqrt()
# Reverse coordinates
sp + scale_y_reverse() 

The function coord_trans() can be used also for the axis transformation

# Possible values for x and y : "log2", "log10", "sqrt", ...
sp + coord_trans(x="log2", y="log2")

Format axis tick mark labels

Axis tick marks can be set to show exponents. The scales package is required to access break formatting functions.

# Log2 scaling of the y axis (with visually-equal spacing)
library(scales)
sp + scale_y_continuous(trans = log2_trans())
# show exponents
sp + scale_y_continuous(trans = log2_trans(),
    breaks = trans_breaks("log2", function(x) 2^x),
    labels = trans_format("log2", math_format(2^.x)))

Note that many transformation functions are available using the scales package : log10_trans(), sqrt_trans(), etc. Use help(trans_new) for a full list.

Format axis tick mark labels :

library(scales)
# Percent
sp + scale_y_continuous(labels = percent)
# dollar
sp + scale_y_continuous(labels = dollar)
# scientific
sp + scale_y_continuous(labels = scientific)

Display log tick marks

It is possible to add log tick marks using the function annotation_logticks().

Note that, these tick marks make sense only for base 10

The Animals data sets, from the package MASS, are used :

library(MASS)
head(Animals)
##                     body brain
## Mountain beaver     1.35   8.1
## Cow               465.00 423.0
## Grey wolf          36.33 119.5
## Goat               27.66 115.0
## Guinea pig          1.04   5.5
## Dipliodocus     11700.00  50.0

The function annotation_logticks() can be used as follow :

library(MASS) # to access Animals data sets
library(scales) # to access break formatting functions
# x and y axis are transformed and formatted
p2 <- ggplot(Animals, aes(x = body, y = brain)) + geom_point() +
     scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
              labels = trans_format("log10", math_format(10^.x))) +
     scale_y_log10(breaks = trans_breaks("log10", function(x) 10^x),
              labels = trans_format("log10", math_format(10^.x))) +
     theme_bw()
# log-log plot without log tick marks
p2
# Show log tick marks
p2 + annotation_logticks()  

Note that, default log ticks are on bottom and left.

To specify the sides of the log ticks :

# Log ticks on left and right
p2 + annotation_logticks(sides="lr")
# All sides
p2+annotation_logticks(sides="trbl")

Allowed values for the argument sides are :

  • t : for top
  • r : for right
  • b : for bottom
  • l : for left
  • the combination of t, r, b and l

Format date axes

The functions scale_x_date() and scale_y_date() are used.

Example of data

Create some time serie data

df <- data.frame(
  date = seq(Sys.Date(), len=100, by="1 day")[sample(100, 50)],
  price = runif(50)
)
df <- df[order(df$date), ]
head(df)
##          date      price
## 33 2016-09-21 0.07245190
## 3  2016-09-23 0.51772443
## 23 2016-09-25 0.05758921
## 43 2016-09-26 0.99389551
## 45 2016-09-27 0.94858770
## 29 2016-09-28 0.82420890

Plot with dates

# Plot with date
dp <- ggplot(data=df, aes(x=date, y=price)) + geom_line()
dp

Format axis tick mark labels

Load the package scales to access break formatting functions.

library(scales)
# Format : month/day
dp + scale_x_date(labels = date_format("%m/%d")) +
  theme(axis.text.x = element_text(angle=45))
# Format : Week
dp + scale_x_date(labels = date_format("%W"))
# Months only
dp + scale_x_date(breaks = date_breaks("months"),
  labels = date_format("%b"))

Note that, since ggplot2 v2.0.0, date and datetime scales now have date_breaks, date_minor_breaks and date_labels arguments so that you never need to use the long scales::date_breaks() or scales::date_format().

Date axis limits

US economic time series data sets (from ggplot2 package) are used :

head(economics)
##         date   pce    pop psavert uempmed unemploy
## 1 1967-07-01 507.4 198712    12.5     4.5     2944
## 2 1967-08-01 510.5 198911    12.5     4.7     2945
## 3 1967-09-01 516.3 199113    11.7     4.6     2958
## 4 1967-10-01 512.9 199311    12.5     4.9     3143
## 5 1967-11-01 518.1 199498    12.5     4.7     3066
## 6 1967-12-01 525.8 199657    12.1     4.8     3018

Create the plot of psavert by date :

  • date : Month of data collection
  • psavert : personal savings rate
# Plot with dates
dp <- ggplot(data=economics, aes(x=date, y=psavert)) + geom_line()
dp
# Axis limits c(min, max)
min <- as.Date("2002-1-1")
max <- max(economics$date)
dp+ scale_x_date(limits = c(min, max))

Go further

See also the function scale_x_datetime() and scale_y_datetime() to plot a data containing date and time.

Infos

This analysis has been performed using R software (ver. 3.2.4) and ggplot2 (ver. )


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