Ever spent too much time debugging a data issue, only to realize it was caused by a join where the keys weren’t actually unique? Turns out, both polars AND pandas have a handy option that allows to detect duplicate keys early on, saving us from data explosions passing through silently and causing havoc downstream.

As a Christmas enthusiast, I’ve always been intrigued by the Advent of Code, a series of daily programming puzzles leading up to Christmas. This year, I’m taking on the challenge with either R or Python, adding a touch of whimsy by using a spinning wheel to choose my language each day. I’m also sharing my solutions on a special Advent of Code-themed website. Find out how you can create your own Advent of Code site and automate the process with the aochelpers R package.

A couple of months ago, I decided that it was time for me to finally grow out of my R comfort zone and start studying Python. I began my Python journey by reading the book Python for Data Analysis from Wes McKinney (creator of pandas, the Python equivalent of the tidyverse), and having finished it I wanted to put into practice what I’ve learned through an applied data analysis.