It is important for a capital business to understand the exposure on its books. Here is a quick visualization of exposure vs. market value using matplotlib.
A newborn may only eat, sleep, and poop, but they sure do it a lot! Here is a sample of two weeks of an an infant's schedule visualized with matplotlib.
It's handy to be able to quickly find the differences between two Excel files. Below is a quick example of doing so using Python and pandas.
Adding interactivity to data visualizations can be helpful for better exploring the data and fun. Sharing interactive visualizations online extends the benefits to others. In this post I will show some examples of using the Altair library to create and share some simple interactive visualizations. The examples below are largely derived from the excellent Altair gallery—I claim no original work on these but enjoyed working with them to learn the mechanics of interactive visualization in Altair.
I previously wrote about automation using Makefiles to bundle together running multiple scripts into a single command. Using the subprocess library we can perform the same tasks entirely in Python.
Here is how to highlight select countries with Cartopy.
Here are some examples of base world maps (excluding Antarctica which is cropped out) using Cartopy.
I recently needed to extract data from the screenshot of a graph. The data was provided by a third party in that format so I had to work with what I was given.