Note: This post assumes a passing familiarity with linear regression. Aside from that, it's a highly applied intro to D-in-D regression and panel data techniques. In Due Time In one of my favorite episodes of Futurama, the universe experiences "time skips."... Continue Reading →
Why Even Try, Man? I recently came upon Brian Granger and Jake VanderPlas's Altair, a promising young visualization library. Altair seems well-suited to addressing Python's ggplot envy, and its tie-in with JavaScript's Vega-Lite grammar means that as the latter develops new... Continue Reading →
Note: In this post, I assume some familiarity with PyMC. If you need to get up to speed in a hurry and you're familiar with linear regression, go here for a tutorial. Alternatively, you can read for the methodological intuition,... Continue Reading →
Warning: This is a love story between a man and his Python module As I mentioned previously, one of the most powerful concepts I've really learned at Zipfian has been Bayesian inference using PyMC. PyMC is currently my favorite library... Continue Reading →
The Point of this Post: To Document an Example In this update, we'll cover reading data into a pandas DataFrame, Seaborn, creating multi-plot figures with matplotlib.pyplot.subplots(), LaTeX labeling, and parameterizing Gamma distributions using SciPy. I've been sitting on this example... Continue Reading →
Dan Saber 