How To Make Your Matplotlib Bar Charts Stand Out

Bar charts are a commonly used data visualisation tool where categorical features are represented by bars of varying lengths/heights. The height or length of the bar corresponds to the value being represented for that category.
Bar charts can easily be created in matplotlib. However, the matplotlib library is often regarded as a library that produces unexciting charts and can be challenging to work with. With perseverance, exploration, and a few extra lines of Python code, we can generate distinctive, aesthetically pleasing and informative figures.
In this video, I show you how you can transform a basic matplotlib bar chart into something that is much more informative and much nicer to look at.
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The dataset used for this tutorial is a subset of a training dataset used as part of a Machine Learning competition run by Xeek and FORCE 2020.
Bormann, Peter, Aursand, Peder, Dilib, Fahad, Manral, Surrender, & Dischington, Peter. (2020). FORCE 2020 Well well log and lithofacies dataset for machine learning competition [Data set]. Zenodo. doi.org/10.5281/zenodo.4351156
This dataset is licensed under a Creative Commons Attribution 4.0 International license.
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[@vitorribeirosa]

Thanks, Andy!!!
Even knowing bar plotting pretty well, I learn at least one or two great trick in your videos.
I appreciate your videos and recommend them to colleagues very often.
Cheers!!!

[@ovilla81]

Many thanks! I was able to compile some data and send it to my boss weekly using these skills.

[@eedoan]

loved it!

[@Sockheadrps]

keep up the videos man thanks for the tutorials

[@AndyMcDonald42]

Thanks, will do!

[@ici6308]

Very nice tuto ! Five star *****

[@AndyMcDonald42]

Thanks 👍

[@gmostafaali]

It’s a nice tutorial and great explanation!

[@eladiomendez8226]

Awesome video. It would help if you made the font size larger for the code to make following easier.

[@AndyMcDonald42]

Thanks. I was trying to balance the text size with the figure size without too much scrolling. I will see what I can do going forward 🙂. I will also be adding the notebooks and code to a new GitHub repository shortly which should help.

[@petroali6412]

wellcome back sir

[@AndyMcDonald42]

Thanks