Data is the future. Heck, you could make a compelling argument that it’s the present.
If you know how to work with data, then your career is virtually assured. You’ll have your pick of cool jobs, interesting projects, good employers, and smart colleagues.
Even better? The most popular language for working with data is Python. Which means that Python skills give you an edge in getting such work.
But Python’s builtin data structures are too big, slow, and clunky for working with data.They’re just not the right tool for the job.
Fortunately, we have Pandas. This library can do it all — importing, exporting, cleaning, and analzying data.
Pandas is fast, flexible, and powerful. The fact that it’s written in Python means that you can combine it with your own functions and classes, or any of the 400,000+ packages on PyPI. It’s no surprise that companies are switching away from Excel and Matlab, in favor of Pandas.
However, Pandas is a really big, complex library. Mastering it can take years, because there’s just so much to learn and remember.
I’ve been teaching Pandas for years — and I’m constantly learning new ways to do things, often from my students. I’m always reaching for the documentation, because there’s no way to remember all of the methods and options.
If you’ve ever learned a foreign language, then you know the only way to fluency is constant practice. Even when you’re fluent, you need practice to keep your skills sharp.
In the same way, the only way to improve your Pandas skills is constant practice.
But where can you get such practice? And more importantly, where you can you get practice with real-world data, on relevant topics?
I’ve always included such real-world data sets in my courses. Whether it’s my corporate training, my online Pandas course, my Pandas Workout book, or even my data bootcamp, I use interesting data sets that we can relate to, and ask questions that are likely in data-analysis projects.
But a course can only cover so much content. And besides, a lot of learning happens over time, as the ideas drip-drip-drip into your brain, helping you to gain fluency.
That’s why I’m excited to announce my newest product, Bamboo Weekly.
Bamboo Weekly is all about improving your Pandas fluency, one week at a time:
- Every Wednesday, I’ll pose questions having to do with current events. I’ll point you to a public data set you can use to answer those questions.
- On Thursday, I’ll share my answer with you, helping you to improve your Pandas skills. I’ll go through it in my usual, detailed style, explaining what I’m doing and why I’m doing it that way.
Over time, Bamboo Weekly will sharpen your skills, so that you can get an amazing data-related job — or just write more efficient, idiomatic, debuggable Pandas.
I’ve been publishing Bamboo Weekly for a few weeks already, and the content is currently 100% free of charge, in the archive.
I’ll continue to publish some free editions. But the majority of the issues, as well as the accompanying discussion, will be limited to paid subscribers.
Meanwhile, take a look! This week’s problem is all about earthquakes, analyzing data from the horrific natural disaster that took place on February 6th in Turkey and Syria. I hope that you’ll find the data, and its analysis, as interesting as I did.
Please join me at https://BambooWeekly.com/.
Questions? Comments? Thoughts? Just e-mail me at reuven@lerner.co.il, or at @reuvenmlerner on Twitter.