Change limits to ggplot plots with xlim and ylim

Data visualization is an essential tool for data analysis, and R provides several libraries to create meaningful and appealing visualizations. One of the most popular libraries for data visualization in R is ggplot2, which allows users to create high-quality and customized plots. However, sometimes, users need to set limits to their ggplot plots to focus on specific areas of interest or to remove outliers. In this article, we will discuss why and how to set limits using xlim and ylim in ggplot, and explore alternatives in ggplot, base-R, and other graph packages.

Why do we need to set limits in ggplot?

Setting limits in ggplot is an important feature that allows users to zoom in or zoom out on a specific area of the plot. This feature can be useful in several situations, such as:

1. Focusing on a specific range of values: Sometimes, users want to focus on a particular range of values to analyze the behavior of the data in that range, and ignoring the outliers or other data points outside that range.
2. Removing outliers: Outliers can skew the plot and make it difficult to analyze the data. Setting limits can help to remove outliers and make the plot more representative of the data.
3. Adjusting the scale: Setting limits can help to adjust the scale of the plot and show the data in a more meaningful way.

How to use xlim and ylim in a ggplot?

xlim and ylim are the functions in ggplot that allow users to set limits on the x and y-axis, respectively. The syntax for using xlim and ylim is as follows:

p <- ggplot(data, aes(x = x_var, y = y_var)) + 
  geom_point()
p + xlim(min_value, max_value) + ylim(min_value, max_value)

In the above code, “p” is the plot created using ggplot, and “xlim” and “ylim” are the functions to set limits on the x and y-axis, respectively. “min_value” and “max_value” are the minimum and maximum values that users want to show in the plot.

Alternatives in ggplot, base-R, and other graph packages

In ggplot, users can use other functions to adjust the scale and focus on specific areas of the plot. For example, scale_x_continuous and scale_y_continuous functions can be used to set the limits on the x and y-axis. These functions provide more control over the scale and allow users to customize the axis labels, breaks, and other parameters.

In base-R, users can use the par function to set the limits on the x and y-axis. The syntax for using par is as follows:

par(xlim = c(min_value, max_value), ylim = c(min_value, max_value))

In addition to ggplot and base-R, several other graph packages in R provide the functionality to set limits on the plot. For example, lattice and plotly provide functions to set limits on the plot.

Conclusion

Setting limits in ggplot is an important feature that allows users to focus on specific areas of the plot, remove outliers, and adjust the scale. xlim and ylim are the functions in ggplot that allow users to set limits on the x and y-axis, respectively. In addition to ggplot, base-R, and other graph packages in R provide alternative ways to set limits on the plot. By using these functions, users can create customized plots that show the data in a more meaningful way.