Combining multiple plots and adding lines connecting points from one plot to another can be a powerful way to link related data visually. This article explains how to accomplish this using ggplot2 in R Programming Language.

Combined ggplots

Combining plots involves displaying multiple plots within a single figure. This is often done to compare different datasets or different aspects of the same dataset side by side.

Connecting Lines Between Plots

Connecting lines between points on different plots can help highlight relationships or correspondences between the data points. This can be useful in various applications, such as linking time points across different variables or showing before-and-after changes.

Now we will discuss step by step How to add lines on combined ggplots, from points on one plot to points on the other.

Step 1. Install and Load Necessary Packages

First, ensure you have ggplot2 installed and then load it along with gridExtra for combining plots:

install.packages("ggplot2")
install.packages("gridExtra")

library(ggplot2)
library(gridExtra)

Step 2. Create Sample Data

Let’s create sample datasets for our plots:

# Sample data for plot 1
data1 <- data.frame(
  x = 1:5,
  y = c(2, 4, 3, 5, 6)
)

# Sample data for plot 2
data2 <- data.frame(
  x = 1:5,
  y = c(3, 5, 2, 6, 4)
)

Step 3. Create Individual Plots

Create two separate ggplots:

# Plot 1
plot1 <- ggplot(data1, aes(x = x, y = y)) +
  geom_point(color = "blue", size = 3) +
  labs(title = "Plot 1", x = "X", y = "Y") +
  theme_minimal()

# Plot 2
plot2 <- ggplot(data2, aes(x = x, y = y)) +
  geom_point(color = "red", size = 3) +
  labs(title = "Plot 2", x = "X", y = "Y") +
  theme_minimal()

Step 4. Combine Plots

Combine the two plots using grid.arrange from the gridExtra package:

# Combine plots
combined_plot <- grid.arrange(plot1, plot2, ncol = 2)
combined_plot 

Output:

Add lines on combined ggplots, from points on one plot to points on the other

Step 5. Add Connecting Lines

To add lines connecting points from one plot to another, you need to overlay the combined plots with lines using the base grid package. Here’s how:

# Sample data for plot 1
data1 <- data.frame(
  x = 1:5,
  y = c(2, 4, 3, 5, 6),
  source = "Data 1"
)

# Sample data for plot 2
data2 <- data.frame(
  x = 1:5,
  y = c(3, 5, 2, 6, 4),
  source = "Data 2"
)

# Combine data
combined_data <- rbind(data1, data2)

# Create the combined plot with facetting by source
combined_plot <- ggplot(combined_data, aes(x = x, y = y)) +
  geom_point(aes(color = source), size = 3) +
  geom_segment(data = data.frame(
    x = data1$x,
    y = data1$y,
    xend = data2$x,
    yend = data2$y,
    source = data1$source  # Ensure source is consistent across layers
  ), aes(x = x, y = y, xend = xend, yend = yend), linetype = "dotted", 
               color = "green") +
  facet_wrap(~source, scales = "free", ncol = 2) +
  labs(title = "Combined Plot with Connecting Lines", x = "X", y = "Y") +
  theme_minimal() +
  scale_color_manual(values = c("Data 1" = "blue", "Data 2" = "red"))

print(combined_plot)

Output:

Add lines on combined ggplots, from points on one plot to points on the other

The resulting plot will have two panels:

• Left panel shows points from Data 1 in blue.
• Right panel shows points from Data 2 in red.

Dotted gray lines connect corresponding points between the two panels, illustrating relationships between these points.

Conclusion

Adding lines to connect points between combined ggplots can greatly enhance the interpretability of your visualizations by clearly showing relationships between different datasets or different aspects of the same dataset. Using ggplot2 in combination with base grid functions, you can create sophisticated and informative plots in R. This technique is particularly useful in comparative studies and time series analyses where linking corresponding points is crucial.