ggplot with 2 y axes on each side and different scales

Plotting with Multiple Y-Axes in ggplot: A Complete Guide 📊

👋 Hey there! Are you struggling to plot a bar chart and a line chart with different scales in ggplot? 🤔 Don't worry, you're not alone! Many people face this common issue when trying to combine multiple charts in a single visualization. But fear not, because we're here to help you out! 🙌

The Problem 😫

So, you want to create a bar chart to display counts and a line chart to show rates, all in one single chart. You find it relatively easy to produce both plots separately using geom_bar and geom_line, but when you combine them together, you notice that the scale of the bar chart (first layer) gets overlapped by the line chart (second layer). 😱

The Solution 🎉

Fortunately, there is a way to overcome this hurdle and have separate y-axes for each layer of your combined chart. 📈 Here's how you can achieve that:

Step 1: Load the Required Packages 📦

To begin with, make sure you have the necessary packages installed. We'll be using ggplot2, so let's load it:

library(ggplot2)

Step 2: Create Your Data Frames 📊

Next, you need to prepare your data frames for the bar and line charts. Make sure you have separate data frames for each layer. Let's assume you have two data frames, df_counts for the bar chart and df_rates for the line chart.

Step 3: Generate the Initial Plot 🌈

Now, it's time to create the initial plot without any y-axis adjustments. Use the geom_bar and geom_line layers to plot the counts and rates, respectively.

combined_plot <- ggplot() +
  geom_bar(data = df_counts, aes(x = <x_variable>, y = <y_variable1>), stat = "identity") +
  geom_line(data = df_rates, aes(x = <x_variable>, y = <y_variable2>), color = "red")

Step 4: Define the Right Axis Boundaries 📐

To maintain separate scales for each y-axis, we need to rescale the second layer (line chart). We can achieve this by creating a new scale for the right side of the chart using scale_y_continuous with an appropriate limits parameter.

combined_plot <- combined_plot +
  scale_y_continuous(sec.axis = sec_axis(trans = ~., 
                                         breaks = <appropriate_breaks>,
                                         labels = <appropriate_labels>,
                                         limits = <right_axis_limits>))

Step 5: Customize the Right Axis Appearance 🎨

To make the right y-axis visually distinct, you can further customize its appearance. Play around with attributes like color, text size, and title to match your chart's style and improve readability.

combined_plot <- combined_plot +
  theme(axis.text.y.right = element_text(color = "red"),
        axis.title.y.right = element_text(color = "red", size = 12))

Step 6: Finalize Your Chart 🏁

Lastly, add some finishing touches to enhance the overall aesthetics of your chart. Customize the plot title, labels, legends, or any other visual elements you want to include.

combined_plot <- combined_plot +
  labs(title = "Bar Chart for Counts and Line Chart for Rates",
       x = "X-axis Label",
       y = "Counts",
       y2 = "Rates") +
  theme(plot.title = element_text(size = 16, face = "bold"),
        legend.position = "top")

Step 7: Enjoy Your Beautiful Dual-Y Axis Chart! 🌟

That's it! You've successfully created a bar chart with counts and a line chart with rates, benefiting from separate y-axes for each layer. Celebrate your newfound visualization prowess and go ahead, amaze your audience by sharing this beautiful chart! 🎉

Your Turn! 📝

Now that you know how to plot with multiple y-axes in ggplot, it's time to give it a try! Share your creative chart examples in the comments below or on Twitter using the hashtag #DualYPlotting. We can't wait to see what you come up with! 😍

If you found this guide helpful, don't forget to share it with your friends and colleagues who may be struggling with the same issue. Remember, great charts deserve to be shared! 🚀