The python visualization world can be a frustrating place for a new user. There
are many different options and choosing the right one is a challenge.
For example, even after 2 years, this article is one of the top posts that
lead people to this site. In that article, I threw some shade at matplotlib
and dismissed it during the analysis. However, after using tools such as pandas,
scikit-learn, seaborn and the rest of the data science stack in python - I
think I was a little premature in dismissing matplotlib. To be honest, I
did not quite understand it and how to use it effectively in my workflow.
Now that I have taken the time to learn some of these tools and how to use them with
matplotlib, I have started to see matplotlib as an indispensable tool.
This post will show how I use matplotlib and provide some recommendations for users getting
started or users who have not taken the time to learn matplotlib. I do firmly believe
matplotlib is an essential part of the python data science stack and hope this
article will help people understand how to use it for their own visualizations.