Hackers and Slackers: Data Science for Badasses


21 Posts
The hacker poison of choice.

I Owe My Job to Mr. Robot

Entering the Dataverse

What's up data gang? If you've been reading along throughout this journey, you'll realize that all of my posts have something in common (other than Excel...smartass), they all assume that you're already working with data...even if it's just cursory exposure. Well, every journey of a thousand worksheets begins with a single lookup, and hopefully this story will help you position yourself to inner-join the fraternity of functions.

For the two of you who went out of the way

Data Author imageMax Mileaf August 14

Abusing Tableau to Handle ETL Workflows

Weaponizing APIs against tyrannical software

Before we get into the specifics of how to sadistically abuse Tableau, let's clear the air: there's something about inaccessible, expensive, proprietary enterprise software that tends to put me in a touchy mood. As we know, B2B software pricing has nothing to do with code quality or even value-add, but rather the tendency of businesses to create time-based urgencies without warning; the kinds of urgencies which may be solved by, say, a tool of sorts.

My first interaction with Tableau

Tableau Author imageTodd Birchard August 03

Hacking Your Tableau Linux Server

Turning a BI tool into your data GUI slave

Let's say you're a Data Scientist. Well maybe not a data scientist... I mean, those online data analysis courses were definitely worth it, and you'd made it this far without being quizzed on Bayesian linear regression. So maybe you're analyst or something, but whatever:  you use Tableau, So you must be a Scientist™.

I've admitted a few times in the past to have purchased a personal Tableau Server license in my more ignorant years (aka a few months ago). While

Tableau Author imageTodd Birchard July 26

Data Could Save Humanity if it Weren't for Humanity

A compelling case for robot overlords.

A decade has passed since I stumbled into technical product development. Looking back, I've spent that time almost exclusively in the niche of data-driven products and engineering. While it seems obvious now, I realized in the 2000s that you could generally create two types of product: you could either build a (likely uninspired) UI for existing data, or you could build products which produced new data or interpreted existing data in a new useful way. Betting on the latter seemed

Data Author imageTodd Birchard July 20

Extracting Massive Datasets in Python

Abusing APIs for all they’re worth

Taxation without representation. Colonialism. Not letting people eat cake. Human beings rightfully meet atrocities with action in an effort to change the worked for the better. Cruelty by mankind justifies revolution, and it is this writer's opinion that API limitations are one such cruelty.

The data we need and crave is stashed in readily available APIs all around us. It's as though we have the keys to the world, but that power often cones with a few caveats:

  • Your "key"
Python Author imageTodd Birchard July 04


Adventures in Excel

If you've been following along on our proverbial Hogwarts for budding Excel wizardry, you would know that we recently crossed an important Rubicon upon which all Excel, and indeed all computer programming languages are built: The mighty IF statement. Remember, the IF statement allows the wielder to fork reality at their whim, to bend the code on a lark, to be the Franklin Richards of the spreadsheet just by asking the computer a simple true/false question. Considering the gravity

Excel Author imageMax Mileaf June 20

Dealing with XML in Python

Because you'll probably have to

Life is filled with things we don't want to do; you're a developer so you probably understand this to a higher degree than most people. Sometimes we waste weeks off our lives thanks to an unreasonable and unknowledgable stakeholder. Other times, we need to deal with XML trees.

At some point or another you're going to need to work with an API that returns information in XML format. "Sure," we might think, "I'll just import the standard

Python Author imageTodd Birchard June 19

Getting Iffy With it

Adventures in Excel

If you've been following along, we discussed in the last several posts of this series how, if you're not working in a very "tech forward" organization (like my two compatriots on his site), but you have the same title, you're probably obtaining your data from another department (or it might be a sentient sponge, or a gang of squirrels with dreams of world domination, you'll actually have no idea) who you will have no contact with. As a

Excel Author imageMax Mileaf June 10

Taking Out the Trash

Dealing With Dirty Data Pt 2

In my last post, we explored the organizational structure of many large companies and how this pertains to one's duties as a fledgling data analyst. I highly recommend you go back and read the first post on "dirty" data, but just in case you're one of those rebels who thinks that they're too cool to read part 1, here's a quick refresher to put you back in the analytical mindset (which is the perfect combination tactical laziness, ADHD,

Excel Author imageMax Mileaf June 05