ggplot Shapes in R to Create Scatter Plots

4 min readNov 15, 2023

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Learn to use ggplot shapes in R to create beautiful and informative scatter plots with different point shapes, colors, sizes, and fills.

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How to Use ggplot Shapes in R to Create Stunning Scatter Plots

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KeyPoints

ggplot shapes represent the points in a scatter plot, and they can be used to distinguish different groups of data, highlight outliers, or add more information to the plot.
We can use 25 different ggplot shapes, ranging from simple circles and squares to more complex shapes like stars and triangles. We can customize the shapes, colors, sizes, and fill to suit our needs.
We can map a variable to the shape of the points using the aes() function, which will create a different point shape for each variable level and add a legend to the plot.
We can use geom_jitter() and geom_count() to deal with overplotting, which occurs when there are too many points in the plot that overlap with each other. geom_jitter() adds a small amount of random noise to the x and y coordinates of the points, and geom_count() adds points with sizes proportional to the number of observations at each position.
We can use geom_smooth() to add a regression line and a confidence interval to the plot, which can help to show the trend and the uncertainty of the relationship between the variables. Using the level argument, you can use different regression models, such as linear or loess, and control the confidence level.

Before We start, Make sure you read the following:

Setting the Stage: Basic Scatter Plot

Let’s kick off our journey by building a strong foundation. Creating a basic scatter plot involves utilizing the ggplot() function and specifying the aesthetics. Here’s a snippet of code to get you started:

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