My Matplotlib can beat up your Matplotlib!

Don't Use This Code

I can make most static visualizations with high-level interfaces like seaborn, plotnine, matplotlib.pyplot, why would I need more?

<h2>Summary</h2><p><em><strong>I can make most of my static visualizations with high-level interfaces like seaborn, plotnine, matplotlib.pyplot, why would I need to ever learn more? </strong></em></p><p>These are some famous last words before hitting a hard wall in the creation of your data visualizations. While not as common as a bar chart or a line chart, modern data visualizations have introduced charts like the “funnel”, “tree diagram”, “sunburst”, “waffle”, “parallel coordinates/categories”, and many more. While most of these chart types exist in their own respective convenient packages, they don’t have a uniform API and often make opinionated changes to your underlying Figure or Axes causing you to dig through source code anyways to make the adjustments you want. Thankfully, we don’t need to be fully reliant on these packages if we expand our understanding of their shared Matplotlib foundation.</p><p>Join our resident Matplotlib expert Cameron Riddell for a deeper understanding of our data visualization tools to not only break through barriers we encounter in our work, but also reduce our reliance on someone else’s code and opinions on what our viz should look like.</p>

<h2>Presenter: Cameron Riddell</h2><p><strong>Cameron Riddell</strong> joined Don’t Use This Code in 2021. Prior to joining our team, he worked in academia studying various aspects of psychology, including the neural activity underlying social interaction, perception of taste, and human memory. His studies naturally led him to learn Python, which he has been writing for over 8 years with a strong emphasis on data analytics and scientific communication.</p><p>As our resident pandas &amp; matplotlib expert, Cameron takes a uniquely data-driven, analytical approach to his work and research. He enjoys sharing his knowledge both in and out of the classroom; in fact, he is ranked in the top 4% of all answerers on Stack Overflow. Thanks to his efforts, people overcome their coding challenges! His academic background and focus on programmatic thinking bring a great perspective to the training team at Don’t Use This Code.</p>

<h2>Presented by: Don't Use This Code</h2><p>Don't Use This Code is a professional training, coaching, and consulting company deeply invested in open source technologies, centered around the PyData stack for scientific and numeric computing. We are dedicated to bringing better processes and a better understanding of these powerful tools.</p><p>We are continually seeking new partners, clients, and engagements for our services. Organizations looking to better employ these tools would benefit from our wide range of training courses on offer (<a href="https://learning.dutc.io" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">learning.dutc.io</a>), ranging from an intensive introduction to Python fundamentals to advanced applications of Python for building large-scale production systems. Working with your team, we can craft targeted curricula to meet your training goals. We are also available for consulting services, such as building scientific computing and numerical analysis systems using technologies like Python and React.</p><p>We pride ourselves on delivering top-notch training uniquely valuable to each individual attendee, and we do so by investing in three key areas: our content, our processes, and our contributors.</p><h2></h2>

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My Matplotlib can beat up your Matplotlib!

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My Matplotlib can beat up your Matplotlib!

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