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How to Change Axis Scales in R Plots?

  • Last Updated : 19 Dec, 2021

In this article, we will learn how to change Axis Scales in the R Programming Language.

Method 1: Change Axis Scales in Base R

To change the axis scales on a plot in base R Language, we can use the xlim() and ylim() functions. The xlim() and ylim() functions are convenience functions that set the limit of the x-axis and y-axis respectively. This function takes a vector as an argument which contains the values of lower axis limit and higher axis limit.

Syntax: plot( df$xaxis, df$yaxis, xlim, ylim)

where,

  • df: determines the data frame in use.
  • xaxis and yaxis: determine the axis variables for plotting.
  • xlim: determines the vector that contains x-axis limits.
  • ylim: determines the vector that contains y-axis limits.

Example: Basic example where plot axis limits are set from 0 to 2 for the x-axis and from 18 to 20 for the y-axis.

R




# create sample data frame
sample_data <- data.frame(x=rnorm(100),
                          y=rnorm(100)+20)
  
# create plot with custom axis scales
plot(sample_data$x, sample_data$y, xlim=c(0,2),
     ylim=c(18,20))

Output:

Output

Convert axis scales to log scale:

To convert the axis scale log scale in the base R plot, we use the log argument of the plot() function. The log argument converts the given axis into its log scale alternative. This helps us in visualizing the skew data frames.

Syntax: plot( df$xaxis, df$yaxis, log)

where,

  • df: determines the data frame in use.
  • xaxis and yaxis: determine the axis variables for plotting.
  • log: determines the axis which has to be converted in log scale.

Example: Basic example where the x-axis has been converted to its log scale alternative.

R




# create sample data frame
sample_data <- data.frame(x=rnorm(100),
                          y=rnorm(100)+20)
  
# create plot with log x-axis scale
plot(sample_data$x, sample_data$y, log='x')

Output:

Output

Method 2: Change Axis Scales in ggplot2

To change the axis scales on a plot made using the ggplot2 package in the R Language, we can use the xlim() and ylim() functions. These functions can be used along with the ggplot() function by adding them using plus(+) symbol The xlim() and ylim() functions are convenience functions that set the limit of the x-axis and y-axis respectively. This function takes a vector as an argument which contains the values of lower axis limit and higher axis limit.

Syntax:

ggplot() + xlim() +ylim()

where,

xlim(): takes two values as input that are lower x-axis limit and higher x-axis limit.

ylim(): takes two values as input that are lower y-axis limit and higher y-axis limit.

Example:

Here, is a basic example of a ggplot2 plot where plot axis limits are set from 0 to 2 for the x-axis and from 18 to 20 for the y-axis.

R




# load library ggplot2
library(ggplot2)
  
# create sample data frame
sample_data <- data.frame(x=rnorm(100),
                          y=rnorm(100)+20)
  
# create plot with custom axis scales
ggplot(sample_data, aes(x=x, y=y))+
        geom_point()+
        xlim(0,2)+
        ylim(18,20)

Output:

Output

Convert axis scales to log scale:

To convert the axis scale log scale in the R plot made using the ggplot2 package, we use the scale_y_continuous() and scale_y_continuous() functions along with the trans argument for the x-axis and the y-axis transformation respectively. The trans argument takes a logarithmic identifier as an argument and then converts the axis into the given log scale alternative. This helps us in visualizing the skew data frames.

Syntax: plot + scale_x_continuous( trans ) + scale_y_continuous( trans )

where, trans: determines the exact log scale for transformation

Example: Basic example of a ggplot2 plot where the x-axis has been converted to its log scale alternative.

R




# load library ggplot2
library(ggplot2)
  
# create sample data frame
sample_data <- data.frame(x=rnorm(100),
                          y=rnorm(100)+20)
  
# create plot with log x-axis sclae
ggplot(sample_data, aes(x=x, y=y))+
        geom_point()+
        scale_x_continuous( trans= 'log10')

Output:

Output


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