# How to visualise scatter plots with marginal density plots in R

Visualizing data in scatter plots can be useful for understanding the relationship between two variables. However, when working with large datasets, scatter plots can become cluttered and difficult to interpret. One way to overcome this issue and to gain more insight into your data is by adding marginal density plots to the scatter plots. In R, there are several ways to create scatter plots with marginal density plots, such as using the ggplot2 library or the lattice package.

When creating scatter plots with marginal density plots, the scatter plot shows the relationship between two variables, and the marginal density plots show the distribution of the variables separately. The marginal density plots are typically placed on the top and the right of the scatter plot, and they help to provide additional information about the distribution of the variables.

One way to create scatter plots with marginal density plots in R is by using the ggplot2 library and the ggExtra package. The ggExtra package provides the ggMarginal() function which can be added to a scatter plot created with ggplot2 to create marginal density plots.

Another way to create scatter plots with marginal density plots in R is by using the lattice package. The lattice package provides the xyplot() function which can be used to create scatter plots with marginal density plots. The density plots are added to the scatter plot by specifying the type of marginal plot and the variables to be plotted.

It’s worth noting that scatter plots with marginal density plots can be useful when you have large datasets and you want to identify patterns or trends in the data. The marginal density plots provide additional information about the distribution of the variables separately. However, it’s important to be aware that the choice of the type of marginal plot can affect the results, and it’s a good idea to consult with experts before visualizing data in scatter plots with marginal density plots.

In summary, visualizing data in scatter plots can be useful for understanding the relationship between two variables. However, when working with large datasets, scatter plots can become cluttered and difficult to interpret. One way to overcome this issue and to gain more insight into your data is by adding marginal density plots to the scatter plots. In R, there are several ways to create scatter plots with marginal density plots, such as using the ggplot2 library and the ggExtra package or the lattice package. It’s worth noting that scatter plots with marginal density plots can be useful when you have large datasets and you want to identify patterns or trends in the data. The marginal density plots provide additional information about the distribution of the variables separately. However, it’s important to be aware that the choice of the type of marginal plot can affect the results, and it’s a good idea to consult with experts before visualizing data in scatter plots with marginal density plots.

In this Applied Machine Learning Recipe, you will learn: How to visualise scatter plots with marginal density plots in R.