9/8/2023 0 Comments Ggplot2 scatter plot![]() ![]() ![]() G2> Reader request: Display Regression Line Equation on Scatterplot All of the theme options can be found here.I often the theme_bw() layer, which gets rid of the gray. I personally don't like the look of the default gray so here are some quick ways to change it. The look of the plot in terms of the background colors and style is the theme(). Then we show three basic options to modify the legend. We start off by creating a new ggplot base object, g1, which colors the points by a factor variable. If you want to change around the limits of the axis, and exactly where the breaks are, you use the scale_x_continuous (and scale_y_continuous for the y-axis). If you want to change the font size and style of the label, then you need to use the theme() layer. If you only want to quickly add labels you can use the labs() layer. We're sticking with the basic p1 plot, but now changing the shape and size of the points: p2 > Add lines to scatterplot p2 > Change axis labels We start with options for colors just by adding how we want to color our points in the geom_point() layer: p2 > Change shape or size of points We are going to use the mtcars data that is available through R. ![]() In this post, we focus only on scatterplots with a continuous x and continuous y. You can also easily add regression lines and summary statistics.įor great reference guides, use the ggplot2 documentation or the R Graphs Cookbook. You start with the basic of the data you want your plot to include (x and y variables), and then layer on top the kind of plotting colors/symbols you want, the look of the x- and y-axes, the background color, etc. The way ggplot2 works is by layering components of your plot on top of each other. Since I constantly forget the options that I need to customize my plots, this next series of posts will serve as cheatsheets for scatterplots, barplots, and density plots. I have made some pretty cool plots with it, but on the whole I find myself making a lot of the same ones, since doing something over and over again is generally how research goes. The graphics package ggplot2 is powerful, aesthetically pleasing, and (after a short learning curve to understand the syntax) easy to use. ![]()
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