Plotting Libraries in Python

Hey,

Python provides many different libraries for data visualization, and sometimes it can be difficult to choose the right one for a specific task.

Three of the most popular options are Matplotlib, Seaborn, and Plotly. But when should you use which library?

• Matplotlib: A great choice for basic plotting and detailed customization. It gives you a high level of control over almost every element of your visualization.
• Seaborn: Built on top of Matplotlib, Seaborn makes it easier to create attractive and informative visualizations with less code. For example, you can easily color observations by group or add regression lines.
• Plotly: Particularly useful when you want to create interactive visualizations. It allows users to zoom, explore data points, and display additional information when hovering over a plot.

Of course, Python offers many other visualization libraries, but these three are among the most widely used. That's why I think it's important to understand their differences and know when to use each one.

I've also created a new module for the Statistics Globe Hub called "Data Visualization with Matplotlib, Seaborn, and Plotly in Python," where I demonstrate practical examples using all three libraries.

Learn more about the Hub.

And if you prefer R, you might be interested in my upcoming Data Visualization in R Using ggplot2 & Friends course, starting November 9, 2026.

Talk to you soon.

Joachim