Working with data often means having to plot it, and there are different ways to do that. Matplotlib is a popular library to create plots, and in this article, we’re going to look at how to add a secondary Y axis to it! Keep on reading if you’d like to learn how to make Matplotlib charts with two y axes, and plot your data with even greater precision.
Matplotlib’s Secondary Y Axis feature can be a valuable tool for comparing sets of data with different value ranges, as it allows users to display two distinct Y axes on the same plot. Here are a few tips for using it properly:
- Set clear labels for each Y axis to help your audience differentiate them. Add a legend to the chart as well for even more clarity.
- Match up the scales when it comes to the values of each Y axis. This will help visualize the relationship between the two datasets.
- Be careful with mixing datatypes, as mixing datatypes can lead to unexpected errors. Mixing categorical and numerical data is not allowed.
In conclusion, the Secondary Y Axis feature in matplotlib can be a great way to improve your graphs, as long as you are aware of the pitfalls and use it accordingly. If you use it properly, your charts will be easier to understand and the data comparisons you are visualizing will be even clearer.
Matplotlib is an incredibly powerful tool for plotting and visualizing data, and secondary Y axes offer an elegant solution for plotting multiple datasets with varying scales. If you want to create delightful visuals for your data, Matplotlib is a great place to start. Good luck!