Log-Log Plot using ggplot2
To create a Log-Log plot in the ggplot2. We convert the data frame values to their logarithmic values by using the log() function. The log() function converts the data value into its logarithmic value. Then we pass the converted data frame as an argument to the ggplot() function and use the geom_point() function to draw a scatter plot.
Syntax:
plot_dataframe <- data.frame( x= log(df$x), y= log(df$y) )
ggplot( plot_dataframe, aes( x, y) ) + geom_point() + labs ( title )
where,
- df: determines the data frame that is to be plotted..
- title: determines the title of plot.
Example:
Here, is an example of a basic log-log plot made using the ggplot2 package of the R Language.
R
# load library ggplot2 library(ggplot2) # create sample data frame sample_data <- data.frame(x=1:12, y=c(10, 12, 3, 6, 2, 23, 12, 15, 17, 5, 12, 23)) # convert dataframe data into Log data plot_data <- data.frame( x=log(sample_data$x), y=log(sample_data$y) ) # create scatterplot using geom_point function ggplot(plot_data, aes(x=x, y=y)) + geom_point()+ labs(title='Log-Log Plot', x='Log(x)', y='Log(y)') |
Output:
How to Create a Log-Log Plot in R?
In this article, we will discuss how to create a Log-Log plot in the R Programming Language.
A log-log plot is a plot that uses logarithmic scales on both the axes i.e., the x-axis and the y-axis.We can create a Log-Log plot in the R language by following methods.
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