Posts tagged advanced

Edward Tufte’s NYC Weather In Bokeh

Hello, everyone! Welcome back to Cameron’s Corner. This week, I wanted to expand upon using Bokeh to visualize the weather by revisiting the Edward Tufte NYC Weather in 2003 visualization I recreated in Matplotlib. Except, this time, I want to see if Bokeh is up to the challenge.

All of the data & set up will be identical to the previous post from March, so we can gloss over those details. If you’re up to date, feel free to skip down to the Recreating Tufte in Bokeh section.

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Tufte Weather In Matplotlib

Hello, everyone! Welcome back to Cameron’s Corner. This week, I want to dive into a topic of particular and personal interest to me: the origins of data visualization. In fact, I’m so passionate about it, I’ll be hosting a seminar on March 17th, “Spot the Misleading Data Visualization!”

Edward Tufte is one of the pioneers of modern-day data visualization. In his work, he is brilliantly able to distill core concepts that can then be applied to nearly any form of visual communication. If you aren’t familiar with his work and are interested in the topic of data visualization in general, I highly recommend Tufte’s book, “The Visual Display of Quantitative Information”.

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Matplotlib: Arbitrary Precision

It’s no secret that matplotlib is one of my favorite tools in Python (sorry, pandas, I promise you’re a close second). But, I’m not sure if I’ve shared why I think matplotlib is such a great tool. I don’t love it because of its redundant APIs or simply because I’m familiar with it, I think matplotlib is a great tool because it has near-infinite flexibility. I refer to this as “arbitrary precision” as you can be as precise or imprecise as you want.

Want to put a Polygon in some arbitrary location?

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The Central Limit Theorem - Visualized

We have exciting things coming up at DUTC! Our “No-Tears Code Review” workshop series is almost here: get actually meaningful feedback on your code, working directly with our instructors and a small cohort of attendees. Register for the series here and get 20% off!

For this week, I’m finally sharing the code I wrote to produce my visualization demonstrating the Central Limit Theorem! But before we get to the code, I wanted to discuss the impact of this visualization and how it can be interpreted.

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Matplotlib Legends: Artists & Handlers

Hey all, got some matplotlib for you this week. I wanted to start touching on some more advanced ideas about it and decided to demonstrate a question I answered on Stack Overflow not long ago.

The question asked about custom legend artists- essentially asking “How can I change the style of the artists matplotlib presents in a given legend.” While the longest way to do this is to construct a Legend manually, thankfully matplotlib provides an escape hatch in the form of the handler_map argument.

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Python: Advanced Decorators

In a previous post, I shared a primer on how to approach the thinking of decorators and when we can apply them in our code. To summarize, we primarily see 3 entry points where decorators can dynamically effect our code:

entry point

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