6 Pandas Mistakes That Silently Tell You Are a Rookie

<h2>Introduction</h2> <p>We are all used to the big, fat, red error messages that frequently pop up while we code. Fortunately, people won&rsquo;t spot it because we always fix those errors. But how about the mistakes that give no errors? These are the trickiest, but the pros could easily call them out.</p> <p>These mistakes are not related to the API or syntax of the tool you are using but are directly associated with best practices and how much time you spend on a tool. Today, we are here to talk about six of such mistakes that come up often among beginner Pandas users, and we will learn how to solve them.</p> <h2>1. Using Pandas itself</h2> <p>It is kind of ironic that the first mistake is related to actually using Pandas for certain tasks. Specifically, today&rsquo;s real-world tabular datasets are just massive. To read them into your environment with Pandas would be a huge mistake.</p> <p>Why? Because it is so damn slow! Below, we load the TPS October dataset from 2021 with 1M rows and ~300 features, taking up a whopping 2.2GB of disk space.</p> <p><a href="https://pub.towardsai.net/6-pandas-mistakes-that-silently-tell-you-are-a-rookie-f075c91595e9"><strong>Read More</strong></a></p>