Color Scatter Plot Points in R Based on Multiple Conditions Using ggplot2

Learn how to color scatter plot points in R using ggplot2 when meeting two or more conditions by employing `rowSums` for dynamic coloring.
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How to Color Scatter Plot Points in R Based on Multiple Conditions

Creating scatter plots in R is a common task for data visualization, especially when using libraries like ggplot2 and tidyverse. Sometimes, we might want to enhance our scatter plots by coloring points based on specific conditions. For example, you may want to color the points red if they meet two or more TRUE conditions across different columns in your dataset. In this post, we will walk through the steps needed to achieve this using R.

The Problem

Consider a dataset where you have several numeric values along with multiple logical conditions. You've likely faced the need to display these conditions visually by changing the color of points in a scatter plot. In the example provided (as seen in the table below), you need to plot value1 against value2, and color the points based on how many conditions are TRUE:

value1value2condition1condition2condition32.30.1FALSEFALSETRUE3.52.6FALSEFALSETRUE3.12.5TRUETRUETRUE3.22.3FALSETRUETRUE...............How can you programmatically check these conditions to color the points correctly? Let's explore how to do this effectively.

Solution Overview

To solve the problem of coloring scatter plot points based on multiple conditions in R, we can use two primary methods:

Using Base R

Using the Tidyverse approach with ggplot2

Method 1: Using Base R

With Base R, you can utilize the rowSums() function combined with ifelse() to create a color vector. Here's how:

[[See Video to Reveal this Text or Code Snippet]]

In this method:

rowSums(df1[3:5]) calculates the sum of TRUE values in columns that start from the third up to the fifth (condition columns).

The ifelse() function checks if the sum is greater than 1 (meaning two or more conditions are TRUE), assigning colors accordingly.

Method 2: Using Tidyverse with ggplot2

This method is more modern and leverages the power of the tidyverse package. You will create a new color column using mutate() and case_when(). Here's the code to do so:

[[See Video to Reveal this Text or Code Snippet]]

Explanation of the Code

Library imports: dplyr is used for data manipulation and ggplot2 for plotting.

mutate() function: This creates a new column colr based on the number of TRUE conditions using case_when(), attaching "red" for points meeting the criteria and "black" otherwise.

ggplot() function: This visualizes the data with aesthetic mappings where value1 is on the x-axis, value2 on the y-axis, and color determined by colr.

Conclusion

Being able to color scatter plot points based on multiple conditions adds valuable insights to your data visualization. By utilizing the features of Base R or the Tidyverse, you can effectively highlight important data points that meet specific criteria, making your scatter plots not only more informative but also visually appealing.

Feel free to adapt the provided code examples to your own datasets for customized scatter plots in R!