Plotting in Python

Python plotting options

Plotting libraries available in Python. Source:

Python has many nice, useful libraries that can be used for plotting. In the figure above, you can see a number of the available plotting library options, along with how they relate to one another. Of the options above, we would like to highlight:


Explore the galleries and examples of different visualization libraries above to learn what’s possible to do in Python.

As you can see from the examples, the plotting possibilities in Python are numerous and rich. Do you need to know them all? Of course not. Not even we do. It is not even rational for trying to use them all, instead you should start by learning to use one of them that suits your needs and then later extend your knowledge and skills to other visualizing libraries when necessary. In our courses, we will be start our plotting experiments with Matplotlib and Plotly that makes it possible to store and show our interactive plots in the web.


Later, in the Automating GIS processes course, we will be learning a little bit of Bokeh as well. We will likely work also in Matplotlib in the Introduction to Quantitative Geology course.