Pandas for Productivity Vlog Ep. 7: The necessity of making SQL queries scalable
Why this topic? Back in 2016, the size of my performance marketing portfolio tripled overnight. I was working 16-hour days […]
If you’re Gen X or Gen Y in tech, it’s a rough ride. Mid-career tech professionals of the 2020s have weathered two storms: data science and generative AI. In the spirit of continuous learning, I’m sharing how I’m navigating and evolving in this increasingly challenging space. Join me!
Why this topic? Back in 2016, the size of my performance marketing portfolio tripled overnight. I was working 16-hour days […]
Why this topic? The first time I encountered Google BigQuery in 2016, I was thrown off by some of its
Why this topic? This topic doesn’t have much documentation, yet is potentially very useful. Calculating moving averages in Excel is
Why this topic? This is a lead-in to next week’s episode, where I will talk about calculating moving averages in
Why this topic? There’s a lot of documentation on using Numpy’s arange function to create ranges of numbers. However, not
Why this topic? When we join two flat files, or a flat file to a SQL query output in Python,
Welcome to the launch of the Pandas for Productivity vlog series! Here, I discuss the peskier data wrangling challenges that
We previously discussed here that plotting charts in Python is second priority for beginners. Indeed, Python’s matplotlib library is very
The Pandas 1.x Cookbook, by Matt Harrison and Theodore Petrou, is now in its 2nd edition, published this February. Previously,