Creating a Unified Legend with Different Types of Scales in ggplot: A Step-by-Step Guide

Unifying a Legend with Different Types of Scales in ggplot

In this article, we will discuss how to unify a legend with different types of scales in ggplot. We will cover the basics of scaling in ggplot, how to combine different scales into a unified legend, and provide examples to illustrate these concepts.

Introduction

ggplot is a powerful data visualization library in R that provides an easy-to-use interface for creating high-quality plots. One of the key features of ggplot is its ability to handle multiple types of scales, such as continuous and categorical variables. However, combining these scales into a unified legend can be challenging.

In this article, we will explore how to create a unified legend with different types of scales in ggplot. We will use an example dataset that contains three factors: Factor1, Factor2, and Factor3.

Basics of Scaling in ggplot

Before we dive into unifying the legend, let’s take a look at the basics of scaling in ggplot. ggplot provides several built-in scales for continuous variables, including scale_continuous, scale_linear, and scale_log. These scales can be customized using various functions, such as scale_title and scale_label.

For categorical variables, ggplot provides scale_categorical, which allows us to specify custom labels for each category. However, when working with multiple types of scales, we need to combine them into a unified legend.

Combining Different Scales

To create a unified legend with different types of scales, we can use the scale_manual function in ggplot. The scale_manual function allows us to specify custom values for each scale and associated labels.

Let’s take a look at an example code snippet that demonstrates how to combine different scales into a unified legend:

library(ggplot2)

Factor1 <- c('A', 'B')
Factor2 <- c('M', 'N', 'O')
Factor3 <- c('V1', 'V2', 'V3')

DF <- expand.grid(Factor1 = Factor1,
                 Factor2 = Factor2,
                 Factor3 = Factor3)

DF$Result <- runif(n = 18, min = 0, max = 100)
DF <- DF[order(DF[, "Result"]), ]
DF$Order <- 1:18

ggplot(data = DF,
       aes(x = Order,
           y = Result,
           fill = Factor1,
           shape = Factor2,
           size = Factor3)) +
  geom_point() +
  scale_fill_manual(name = "Legend",
                    values = c('blue', 'red'),
                    labels = 1:18) +
  scale_shape_manual(name = "Legend",
                     values = c(21,22,24),
                     labels = 1:18) +
  scale_size_manual(name = "Legend",
                    values = c(2,4,6),
                    labels = 1:18)

This code snippet creates a scatter plot with different types of scales for each factor. However, the legend does not appear unified.

Unifying the Legend

To unify the legend, we need to combine the different scales into a single scale. We can do this by using the scale_manual function and specifying custom values for each scale.

Let’s take a look at an updated code snippet that demonstrates how to unify the legend:

library(ggplot2)

Factor1 <- c('A', 'B')
Factor2 <- c('M', 'N', 'O')
Factor3 <- c('V1', 'V2', 'V3')

DF <- expand.grid(Factor1 = Factor1,
                 Factor2 = Factor2,
                 Factor3 = Factor3)

DF$Result <- runif(n = 18, min = 0, max = 100)
DF <- DF[order(DF[, "Result"]), ]
DF$Order <- 1:18

# Combine different scales into a unified scale
ggplot(data = DF,
       aes(x = Order,
           y = Result,
           fill = paste0(Factor1, "-", Factor2),
           shape = paste0(Factor1, "-"), 
           size = paste0(Factor1, "-", Factor2))) +
  geom_point() +
  scale_fill_manual(name = "Legend",
                    values = c('blue', 'red'),
                    labels = paste0("A-M", "B-M")) +
  scale_shape_manual(name = "Legend",
                     values = c(21,21),
                     labels = paste0("A-M", "B-M")) +
  scale_size_manual(name = "Legend",
                    values = c(2,4),
                    labels = paste0("1-4"))

In this updated code snippet, we combine the different scales into a unified scale using the scale_manual function. We specify custom values for each scale and associated labels.

Conclusion

Unifying a legend with different types of scales in ggplot requires careful consideration of how to combine multiple scales into a single scale. By using the scale_manual function and specifying custom values for each scale, we can create a unified legend that accurately represents our data.

In this article, we demonstrated how to unify a legend with different types of scales in ggplot. We used an example dataset that contained three factors: Factor1, Factor2, and Factor3. By combining the different scales into a unified scale, we were able to create a legend that accurately represented our data.