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The world is messy and complex, even overwhelming. How can we make sense of it?

Data.

From the economy to health care to demographics to weather to education, data helps us to analyze, understand, and improve the world. No matter what the topic, there’s data out there for you to explore.

Making sense of these data sets requires appropriate tools. And over the last few years, the Pandas library and Python programming language have become the go-to software tools for millions of people around the world.

It seems like no matter where you turn, people are using Python and Pandas to analyze data. Banks, researchers, hardware companies, and hospitals all rely on Python and Pandas to make better decisions.

The problem? Pandas is massive, with hundreds of methods and numerous ways to accomplish the same goal. I often encounter people who have been using Pandas for years, only to discover that they didn’t know about a better, faster, more idiomatic way to do things.

Moreover, a huge number of Pandas tutorials use made-up data sets that lack the rough-and-tumble of the real world. If, as I wrote above, the world is messy, then it’s no surprise that our data sets are messy, too. Cleaning up our data sets isn’t always fun or easy, but it’s a necessary part of any data analyst’s job.

Bamboo Weekly aims to help you improve your Pandas fluency. Each week, we’ll look at a different aspect of Pandas functionality, via a freely available data set related to current events. Here’s how it works:

On Wednesdays, I send a short description of the news item I want to investigate, a question I want to ask, and a data set you can use to answer it.

On Thursdays, I send my solution to the problem, along with an explanation of why I solved it that way.

In the comments, paid subscribers can discuss the question, my solution, and how else we might have solved it. I’m hoping that we’ll be able to have constructive discussions and debates over these techniques, creating a community of people constantly aiming to improve their data-analysis skills.

I’ve been teaching Python and Pandas for many years, and I’ve been writing about programming and data science for about as long. But Bamboo Weekly is a new kind of publication, different from what I’ve written before. I’m thus hoping — even expecting — to hear from readers with suggestions for topics to discuss, or ways to improve the newsletter.

Bamboo Weekly will start on February 22nd. (I’ll be putting together some free previews between now and then, in part to practice working with Substack’s editor and technology.) If you have questions, suggestions for topics to cover, or interesting data sets that I should know about, please send them to me at [email protected].

I’m excited to launch Bamboo Weekly, and hope that you’ll join me.